Podcasts about Industrial Revolution

On Monday's Mark Levin Show, do you use TikTok, Instagram, X, or any social media? What about a computer? Laptop? iPhone? Smart TV? Netflix? Have you seen a doctor or been to a hospital? Have you driven a car? Taken an airplane? Use email? Congratulations! You use AI! And in order to use AI, you need data centers. Amazing how quickly people fall for lies about data centers. It's the pandemic and fracking all over again. Luddites who don't believe in industrial progress tell people they'll lose their jobs, but data centers will create jobs you've never even heard of. If we want to keep pace with adversaries like China, we'd better ignore the Luddites and pandering politicians and go all in on industrial progress. Also, how would the most advanced society and economy survive without data centers? Foreign countries like China, India and Israel are embracing AI. If they support data centers and America doesn't, where do you think tech workers will go? How do you turn off the human brain? Some say if the GOP loses the midterm elections it will be because of data centers. Wasn't Iran supposed to be the main issue in the midterms? A lot of these Luddites and isolationists are the same. Then, if we hit the brakes hard on AI and data centers, we won't have the most advanced computers, medical care, and other things. Those who oppose data centers haven't lived in a society that put the brakes on the future. They're happy living in the present, but you can't sustain the present without AI. The world won't want our products and services. Or maybe you prefer Cuba with their 1950s Chevys and no medical advances? All great empires of the past, including Britain, are gone. Will America be next? Finally, AI data centers know no economic or social classes. Everyone benefits from them. Yet, the class warfare ideologues want you to believe there are. In East Loudoun County VA, one of the wealthiest and most highly educated populations in the country if not the world, sit the vast majority of our country's data centers -- upwards of 80%. The end-users are of every walk of life. Those who construct the data centers are union, non-union, blue collar, as well as computer geeks and a wide variety of trades and skilled workers. Those who operate them tend to be highly educated in the STEMs. And we cannot imagine how many new technologies, inventions, products, services, cures, enterprises, etc., will grow from this new Industrial Revolution. Learn more about your ad choices. Visit podcastchoices.com/adchoices

What does it mean to be a good man? In this episode, Dru Johnson talks with Professor Nancy Pearcey about masculinity, toxic masculinity, feminism, fatherhood, Christianity, and the cultural forces that have shaped modern ideas about men.Pearcey explains why she wrote her book on masculinity after seeing increasingly hostile portrayals of men in popular culture and explores the deeper history behind these attitudes. Rather than tracing hostility toward men only to second-wave feminism, she argues that its roots extend back to the Industrial Revolution and changing ideas about work, family, masculinity, and human nature.The conversation examines how Darwinism and evolutionary psychology have contributed to negative cultural scripts about male aggression, sexuality, and dominance—and how those ideas can help explain the appeal of figures such as Andrew Tate. Pearcey also discusses research suggesting that Christian men can be loving husbands, engaged fathers, and committed family members.The episode explores the importance of recovering a healthier vision of biblical masculinity centered on responsibility, virtue, service, protection, provision, fatherhood, and family. It also considers how working from home, integrating family and work, and reconnecting fathers with their children could help reshape modern family life.Order Professor Nancy Pearcey's book here: https://bakerpublishinggroup.com/products/9780801075735_the-toxic-war-on-masculinityProfessor Nancy Pearcey's website: https://www.nancypearcey.com/Contact us at The Biblical Mind: Click HereWe are listener supported. Give to the cause here: https://thebiblicalmind.org/give/For more articles: https://thebiblicalmind.org/Social Links:Facebook: https://www.facebook.com/HebraicThoughtInstagram: https://www.instagram.com/hebraicthoughtThreads: https://www.threads.net/hebraicthoughtX: https://www.twitter.com/HebraicThoughtBluesky: https://bsky.app/profile/hebraicthought.orgChapters00:00 — Covenant, new Christians, and the intellectual questions nobody knew how to answer02:19 — How the conversation will work and why the book matters04:04 — Why Pearcey wrote the book after seeing anti-male rhetoric everywhere06:38 — Abuse, feminism, and moving from blame to healing09:06 — Anti-male language before the 20th century11:50 — Darwinism, social Darwinism, and the “beast within” script13:44 — Andrew Tate as a popularizer of older intellectual ideas16:16 — The universal “three Ps” of masculinity: provide, protect, procreate18:11 — The difference between the “good man” and the “real man”21:23 — Why empirical research matters for claims about Christian men22:21 — What the studies say about evangelical husbands and fathers25:26 — Why churches often discourage men instead of encouraging them27:24 — How the Industrial Revolution changed fathers and family life34:39 — Pandemic remote work and fathers getting closer to their children36:24 — Work, family, and the real-life benefits of flexibility40:36 — Men on the daddy track and the cost of choosing family43:08 — Bringing work home for women and the recovery of integrated family life47:16 — Millennials and Gen Z want a more integrated life48:45 — What Pearcey means by secular and how the split developed50:55 — The historical reversal that made women seem morally superior53:13 — The double standard in dating and the pressure on women to police men55:25 — Why the title is controversial and how people misread the bookSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Ocean acidification makes it harder for corals to grow and for oysters and clams to create shells. Learn more at https://www.yaleclimateconnections.org/ 

In this episode of The Catholic Money Show, Amanda and Jonathan kick off a new series on Magnifica Humanitas, Pope Leo XIV's letter on safeguarding the human person in the age of artificial intelligence.More than a century after Rerum Novarum responded to the upheaval of the Industrial Revolution, the Church is once again speaking into a technological revolution as it unfolds—this time around AI.Amanda and Jonathan introduce the major themes they'll explore throughout the series, including:Why the rise of AI is about far more than productivity and convenienceThe tension between technological progress and human dignityWhat the Tower of Babel has to do with our current momentWhy profit and efficiency cannot become the highest goodsThe importance of the common good as AI becomes more powerfulHow work, money, power, and technology intersect with Catholic social teachingWhy wisdom, virtue, and restraint matter when humanity gains unprecedented powerHow Catholics can engage new technology without allowing it to diminish the human personThis episode serves as an introduction to the series. Over the coming episodes, Amanda and Jonathan will work through each chapter of Magnifica Humanitas, beginning with the foundations of Catholic social teaching before moving into its practical implications for AI, technology, work, and human life.Grab a copy of the document and follow along with us as we ask one of the biggest questions of our time: Will technology serve humanity—or will humanity begin serving the technology?

Edited Transcript Below for Readers on Substack. A pivotal astrological week centered on the Lunar Eclipse on August 28 and a rare sequence of personal planets (Sun, Mercury, Venus) crossing the South Node and Regulus at 0° Virgo — a pattern Louise frames as accelerating the "fall of kings" and a long-term paradigm shift toward humility, stewardship, and inner work. The overarching theme is surrender, self-care, and transformation amid heightened emotional intensity.Venus Retrograde Heroine's Journey 2026 https://www.louiseedington.com/VenusRetrograde2026Features and Press ReleasesUSA Today! https://www.usatoday.com/press-release/story/39476/louise-edington-launches-landmark-venus-retrograde-program-as-she-approaches-15-years-in-business/https://www.womansworld.com/contributors/louise-edington-fear-astrologyhttps://feedvoice.com/louise-edington-on-why-midlife-women-are-turning-to-astrology-for-self-trust-instead-of-self-improvement/International Business Times https://www.ibtimes.com/louise-edington-reclaiming-language-stars-through-intuition-embodiment-matrifocal-wisdom-3803596Wellness Voice https://wellnessvoice.com/louise-edington-on-reclaiming-the-language-of-the-stars-through-intuition-embodiment-and-matrifocal-wisdom/Red Seeds Tarot https://www.etsy.com/uk/shop/TheRedSeedsW.I.T.C.H. Oracle Deck https://a.co/d/0bOgiJsrBefore We Dive InA few things before we get into what is — still — an extraordinary week.AstroTheoros has been adding features since I last mentioned them on the lunar eclipse video: chart import (from nearly any source) and export (to CSV), chart folders, chart notes with a timeline, and lovely PDF print options. More is in the works. If you're looking for affordable, cloud-based astrology software that works on any device, go and check it out. Code COSMICOWL at astrotheoros.com — one free month on the monthly plan, or one extra month off the yearly plan.Venus Retrograde: Heroine's Journey — we now have 50 people enrolled. First call is October 1st. The price is holding through the end of August, so this week is your last chance at the current rate. And — this matters, so I'm saying it clearly — I offer partial scholarships. If you genuinely cannot afford the class, please email me at louise@louiseedington.com with a “pay what you can” offer. I do believe in some form of exchange, but I believe even more in this work reaching the people who need it. Please be in integrity — you don't need to give me your life story. Just be honest. louiseedington.com/VenusRetrograde2026My article — “Can We Let Evolutionary Astrology Evolve?” — is on Substack now. I'm not calling for anyone to cancel evolutionary astrology as a whole. I'm calling for patience, grace, and recognition that the practice itself is already evolving — which is rather fitting. I've had people come out of the woodwork in response to it, in good ways, and there will be follow-ups. Subscribe free on Substack to get it in your inbox.Spiral Weave / Spiral Codex membership — $10/month or $90/year — is where we go deeper together. Live calls, community, and the monthly Ask Me Almost Anything. Link below. Membership is OFF Substack going forward.The Big Picture: Three Planets Cross RegulusBefore we move into the week, I want to give you the context that has been building for months — because it reaches a significant milestone this week.Regulus — the Royal Star, one of the four great fixed stars of the ancient sky — moved from Leo into Virgo from our perspective in late 2011. Before Virgo, it spent approximately 2,160 years in Leo. Before that, 2,160 years in Cancer. And before that, Gemini.The astrologer Michael Lutin — rest in peace, a truly lovely man — apparently wrote about Regulus's ingress into Virgo in practically every post after it happened. His words, which I keep coming back to: “Long after this foolish war is over, Regulus in Virgo will produce beings — the future stewards of the Earth and planets. The goddesses.” And he also said: kings in rags.Now here is where we are this week: the three most personal solar system bodies — Venus, the Sun, and Mercury — are all crossing the South Node and then Regulus, one after another, for the first time since the South Node met Regulus at 0° Virgo.Venus crossed first. The Sun crossed last week. And this Tuesday: Mercury crosses the South Node and then meets Regulus.These are the three bodies closest to the Sun — the inner solar system, our most personal planetary energies. In order from Sun outward: Mercury, Venus, Earth. All three crossing that symbolic drain and meeting Regulus in its new sign. Not kings. Something different. Something more humble, more curious, more meaningful, more Virgo.I also want to mention the larger wheel. I believe the turning of the ages began in 1781, when Uranus was discovered — that moment of collective breakthrough also marked the start of the Industrial Revolution. It takes a very long time to turn the great wheel. We are roughly three ages back from when the descent began — Gemini to Cancer to Leo — and now, with Regulus in Virgo, we are at the point between the descent and the return. Beginning to push back up. That is where we are.Three Out-of-Bounds Bodies — and a PrescriptionThis week, the Moon, Mars, and Pluto are all out of bounds simultaneously. That is not nothing.The Moon out of bounds means our emotions are running beyond the normal range — heightened, eccentric, more extreme in some direction.Mars out of bounds (since August 3rd) means protective instincts and defensive reactions have been especially reactive. Mars in Cancer is already sensitive and protective; out of bounds, it's been operating well beyond convention. The good news: Mars comes back in bounds on Friday the 28th, the eclipse day.Pluto out of bounds happens for about three months around this time of year, and will continue until 2035 — after which Pluto never goes out of bounds again in any of our lifetimes. Rosie Finn's book Persephone's Revolution documents the pattern: Pluto out of bounds to the south has historically coincided with people rising up, more peaceful collective energy. Pluto out of bounds to the north coincided with the Second World War. We are in the south-running period. That is, in Rosie's words, the revolution.The prescription for all of this: radical self-care. Not the usual amount. More than you'd normally think necessary. Out-of-bounds planets go beyond the norm — so your self-care needs to go beyond your norm too. Keep your boundaries. Retreat when you need to. Do what genuinely restores you.The Cards — A First GlanceFrom the Red Seeds Tarot and the Witch Oracle: The Hanged Goddess (upright!), Two of Bees reversed, Queen of Seeds reversed, and The Companion.Pause. Inner turmoil. Inner pillars. And your body as the cauldron. Every single card is pointing in the same direction: inward. More at the end.Day by DaySunday, August 23 — Sun Meets Regulus. The Third Great Crossing Begins.The Moon in Capricorn, out of bounds, opens the week by opposing Ceres — the Great Mother, the one I wrote my book on. Self-care first. What are your needs right now, really? Then the Moon squares Neptune — forming a mutable T-square that forces change and says: surrender. Let go. Trust the flow.At 3:12am Eastern, the Sun meets Regulus exactly at 0°11' Virgo. Venus is already past this point, heading ahead. Now the Sun has joined her. Two personal planets past the drain, past Regulus, heading toward what comes next — including the Venus Star Point, the Cazimi in Scorpio, on October 23rd. (That Star Point, incidentally, squares 20° Aquarius — a potent point I'll speak to more in the Venus class.)Venus is now falling in the sky — every morning in the east she rises closer and closer to the rising Sun, descending back toward conjunction. We are in the falling phase of her cycle. The invitation: more humility, more curiosity, more meaning, more Virgo. Less performance, less pedestal energy. Let it go.Happy birthday, Virgo humans. Your season is carrying something remarkable.Mercury in Leo trines Eris — the messenger meeting the original table-turner. Eris does not like artifice. She does not like the glitz and vanity and pedestal energy of shadow Leo. She is the one who says I was created equal and I will not submit — and she says it again now through Mercury. Expect more news of people falling from pedestals. More truth being spoken. More of the old guard losing its grip.The Moon opposes Mars (both out of bounds — very heightened), then conjuncts Asteroid Lilith (talk to the hand, enough) and Pholus (Pandora's box wide open). We've had enough. The lid is coming off more things. There is grief in all of this. There is loss. People are going to be feeling it this week — whether it's playing out in their personal lives or in the collective. Both are real.The Sun in Virgo trines Chiron — an Earth trine. Healing the wounds around being human. Around how we've treated each other. Around our severed relationship with the Earth itself. This is an ongoing theme for the Chiron-in-Taurus years, and the Sun newly in Virgo is making it tangible.The out-of-bounds Moon squares Saturn retrograde — initiating, letting go of old institutions, old rules, old self-limiting beliefs. The structures that are stagnant. They are going.Monday, August 24 — Capricorn Moon. Radical Self-Care. The Inner Crossroads.The Moon is still out of bounds in Capricorn all day — and Capricorn Moons can feel a bit cold, emotionally blunt. With everything going on right now, you or people around you may seem more shut down than usual. That's self-protection, not coldness. Give yourself and others some latitude.The prescription is clear: more self-care than you normally think you need. Out-of-bounds planets go beyond the norm. Match that.The Moon squares Venus — both out of bounds, both in their own way asking: what do we value? What are we creating? What relationships, contracts, and connections need new boundaries? Where are we letting go of the old and building something genuinely different?Mercury trines Vesta — the messenger in conversation with the inner flame. This isn't coming from outside. The flame is within. The article I wrote on evolutionary astrology (link below) speaks to this — the turning of astrology toward helping people explore their interior landscape, rather than telling them what it means.The Moon sextiles Nessus — seeing the toxins within and without. Bloodletting the inherited poisons, the patterns that have been running. Then the Moon squares Pallas Athena — wise strategy, wise justice. How are we going to fight for this? And how do we find the strategy within ourselves first?Mercury opposes Hecate at 28°57' Aquarius. Hecate — the torchbearer at the crossroads, the triple moon goddess — is in the sign of the future, the collective, the Aquarian North Node. Mercury opposing her says: the crossroads is within. The way forward is through the interior, not through the external drama. Tune in.The Moon squares Eris to close the day — tables still turning, within and without.Tuesday, August 25 — Mercury Crosses the South Node. Mercury Meets Regulus. Vesta Stations Retrograde.Three major events. One day.At 5:01am Eastern, the Moon enters Aquarius — back in bounds, or very close to it, stepping into the sign of the future.At 5:04am Eastern, Mercury conjuncts the South Node. The drain. The third major personal planet to cross this threshold since the South Node met Regulus at 0° Virgo.First Venus crossed — love, values, our relationship to all things, our social and material world. Then the Sun — the very core of our solar system, our identity, the ego and the heart simultaneously. Now Mercury — the mind, the voice, communication, the messenger between worlds.Three, in succession. All releasing through the drain. All letting go of old ideas, old beliefs, old ways of thinking about leadership and hierarchy and who gets to be on a pedestal.And then: at 7:04am, Mercury enters Virgo. Crossing from Leo (the voice of the heart) into Virgo (the meaningful, discerning, humble voice). Mercury is strong in Virgo — curious, detail-oriented, wanting to find the meaning, wanting to get it right not for praise but because doing the right thing matters.At 9:26am, Mercury conjuncts Regulus at 0° Virgo.Three planets. Venus. Sun. Mercury. All having now crossed Regulus in Virgo for the first time since the South Node met it. All going down the drain of the age of kings, and emerging — more humble, more curious, more Virgo. Kings in rags. Future stewards of the Earth and planets. The goddesses.I am just like... I love astrology. And I love Michael Lutin for seeing this.The Moon in Aquarius then squares Haumea, trines Sedna (adapt or die, but also — so many kinds of death), and conjuncts Pluto — the basket activation again. The Moon carries the collective emotional energy through the 4° basket degree, four legs of stability, and we are held.At 2:01pm Eastern, Vesta stations retrograde. Vesta — the inner flame, focus, commitment, sacred devotion — goes retrograde. And look at the Aries cluster now: Neptune retrograde, Manwë retrograde, Saturn retrograde, Pallas Athena retrograde, Eris retrograde, and now Vesta retrograde. All those Aries energies — the new beginning, the identity in the emerging aeon — going back, reviewing, revisiting. We are not finished with what Aries has been teaching us about who we are becoming. The retrograde does not cancel the flame. It turns it inward to assess what it's actually devoted to.Mercury in Virgo trines Chiron — and I want to sit with this one. Virgo, in the older traditions, was the healer, the witch, the medicine carrier, the one with the pouch of herbs who knew how to tend bodies and communities. Chiron is the wounded healer, the shaman, the one who becomes medicine through the wound. Together: be the medicine. Not just know about healing. Embody it.The Moon then trines Uranus — the basket activates again, and we are held in it. Still. Despite everything.Wednesday, August 26 — Moon Opposes Jupiter. The Pedestal Shadow.The Aquarius Moon opposes Jupiter and Hygieia in Leo — and I find this potent. Jupiter in Leo is the expander in the sign of kings, of leaders, of the performer. And now the Moon — the people, the collective emotions — is directly across from it, in the sign of the future.What we're starting to see, I think, is not just the fall of individual gurus and leaders. We're starting to see the shadow of how we've participated in putting them there. Not just in them, but in us. The energy of wanting someone to tell us the answers. The hunger for authority figures. The guru culture, the cult-of-personality culture, the tendency to surrender our inner judge to someone else's version of truth. Jupiter expanded all of that. Now we're looking at it clearly.Jupiter will go retrograde at some point soon, which means it will turn back to review that Leo territory more carefully. Watch that.The Moon sextiles Saturn — self-limiting beliefs, old structures. Let them go. And Mercury sextiles Haumea — the Great Mother of regeneration. All three personal planets are now moving toward Scorpio, toward the Venus Star Point, toward the Venus and Mercury retrogrades. It is going to be intentional. The Venus class exists to help you work with this from the inside out — the meditations are channeled, not scripted, so each journey is genuinely different.Thursday, August 27 — Moon Into Pisces. Mercury Cazimi at 4° Virgo. Moon Conjuncts North Node.The Moon moves through Aquarius — sextiling Pallas Athena (strategy), conjuncting Chariklo (the cosmic doula is holding space for the story we're weaving), sextiling Eris and Vesta (burn things off, from devotion and inner flame) — and then meets Hecate at the crossroads. Always. She is always there.And then the Mercury Cazimi — the Sun and Mercury meet exactly, in a superior (exterior) conjunction at 4° Virgo. Mercury is behind the Sun from our perspective, meaning it's on the far side — gathering information from outer space, which it then channels through the solar core. These exterior Cazimis are often moments of receiving rather than transmitting: something is coming in that Mercury will carry forward toward the coming retrograde.4° Virgo. The basket degree, again. Four legs of the table. When the basket peaked in July, the Moon at 4° of Libra, Scorpio, Sagittarius, Capricorn each activated the whole configuration in turn. Now Mercury and the Sun meet at 4° Virgo. The messenger is filled with what it needs to carry toward the Venus retrograde and then into its own retrograde in Scorpio. Information from the far side, encoded in the cauldron, to be distilled in the descent to come.At 3:03pm Eastern, the Moon enters Pisces — and the emotional waters deepen as we move toward the eclipse tomorrow. The Moon sextiles Chiron and trines Haumea — a water grand trine still operational, eroding, regenerating. The Moon squares Sedna — adapt, or be changed. The Moon conjuncts the North Node — the Aquarian future, the care-for-each-other energy, the people rising up. Forget the labels. Just vote for the person who genuinely wants to care for people. They are human. They will not be perfect. But listen to what they say.Friday, August 28 — Venus Day. The Lunar Eclipse. Mars Back in Bounds.The full lunar eclipse post and video cover all the detail — please do go and read/watch those. But here's what matters from this forecast's perspective.The eclipse is at 4° Pisces/Virgo — the basket degree, the number of stability. Four legs. We are held.Mars moves back in bounds on this day. He's been out of bounds since August 3rd — erratic, sensitive, defensive, more extreme than usual. Now, at last, he comes back within the established range. You may notice a very slight settling of some of that reactive, overly self-protective energy. Mars in Cancer at its highest is the fierce guardian — protective of home and family, yes, but from love rather than fear.Mercury square Uranus exactly at 5° — number of change. Radical shift in perceptions. Could come as shocking news, shocking falls, or shocking good news. The Uranian energy doesn't telegraph which. Stay awake.The Moon in Pisces trines Ceres — amid eclipse energy, Ceres in Cancer says: meet your needs. Take care of yourself. Your family and community. There may be grief around ancestors, around family, around inheritance. Let the water move through.The Sun in Virgo sextiles Ceres and squares Uranus — more eclipse activation, more radical change in the practical, meaningful sign of Virgo. This is the call to do things differently in the everyday, the ordinary, the somatic. Virgo is the medicine carrier. Be the medicine.The Moon trines Mars (now back in bounds) — water to water, Cancer and Pisces. The guardian and the depths. The eclipse is very emotional. Let it be. Surrender. The Hanged Goddess is upright this week precisely because we need her permission to pause.The Moon also trines Asteroid Lilith — talk to the hand. We are not going back to the old way.Saturday, August 29 — Quiet Close. Moon Into Aries.The Moon in Pisces closes the week quietly — meeting Nessus (the poisons, the inherited patterns, a last look at what we're releasing in this eclipse), then sextiling Juno (contracts, the renegotiating continues).And then, at 10:37pm Eastern, the Moon enters Aries — and we end the week with the Moon about to move through that entire retrograde cluster: Neptune, Manwë, Saturn, Pallas Athena, Eris, and Vesta, all revisiting, reflecting, reviewing, in the sign of new beginnings.As the week closes: Venus, the Sun, and Mercury are the only major planetary bodies on the Virgo side of Regulus and the South Node. All the rest are still coming. It will take a while. This is a turning of a great wheel, not the flipping of a switch.But the three most personal planets are leading the way. Be more meaningful. Be more curious. Be more humble. Be the medicine.The Cards in DetailThe Hanged Goddess — I Am Paused (upright this time):In the Red Seeds Tarot by Linda Hill (find her on Etsy, UK), the Hanged Goddess is Demeter — the Great Mother who, in the myth, became weary of both mortals and gods and withdrew to her newly built temple, closing the door to everyone. She knew that to invoke the powers of healing, she would need silence and isolation. And so she paused.“A change of perspective is much needed. The complexity of life can imbalance us at times, leaving us feeling lost, drained, exhausted. Confusion surrounds us, and we can't see the wood for the trees. Have we forgotten who we are? What has brought us to this point? Is it time to stop and pause? Old cycles, habits, poor self-care may have blocked our way. It's time to surrender to the self and allow the depths of our being to open gently. It is not necessary to hurry or try to direct what should happen next. There is really nothing for us to do but wait. Such a position helps us to see things in a very different light. New perspectives will arise. There is much to come from this.”Herman Hesse: “Within you there is a stillness and sanctuary to which you can retreat at any time and be yourself.”This is Demeter closing the temple door. This is the invitation: close the door. Just for a while. Let the silence in. Let the new perspective arise.Two of Bees (Swords), reversed — Inner Turmoil:This week there may be anxiety, inner turmoil, indecision. Everything feels tense inside. Reversed, this card asks for all the inner work — going within rather than pushing outward, balancing the nervous system, retreating, doing the self-care. The Hanged Goddess gave you the permission. Take it.This is strong energy. The eclipses are strong. You do not have to perform having it together right now.Queen of Seeds (Pentacles), reversed — Inner Pillars:In this deck there are two Queens of Seeds, and they both came out this week. They embrace the Divine Feminine — nurture, healing, generosity, intuition, stability, and service. Like the Caryatids — the sculpted figures from the Eleusinian Mysteries who literally held up the sanctuary — these queens hold things up.“We can be supportive and in service of those in need, whilst always remembering to nurture, support, and stabilize ourselves first. This feminine energy has agency: self-sufficient, strong, kind, empowered, and belonging to no gender. These queens held up the Eleusinian sanctuary for many years, on many levels. These queens hold us up. Know that we are supported and always cared for.”Reversed this week, I read these Queens as pointing you toward the inner pillars of support — the ones that don't require anyone else's permission or presence. And to remember Michael Lutin's words: future stewards of the Earth and planets, the goddesses. That doesn't mean only women. It means the goddess energy — the nurturing, supportive, reciprocal, holding energy — within all of us.The Companion (Witch Oracle):Your body. The cauldron. It has appeared before and it keeps appearing because the message keeps being needed.“Your body, like a cauldron, holds the energy of what you put into it. Are you putting shame, diminishment, or rejection into it? Or acceptance, appreciation, adoration?Science would have you believe your body is an experiment. Religion would have you believe your body is a sin. A witch would have you believe your body is a marvel — a cauldron of celebration, home to spells of delight, healing, and wonder.Your body is a sacred companion. She is the one entity that will never leave you during your journey as a human. She is always working on your behalf to restore, heal, and create the balance that allows you to participate in this life. This kind of loyalty deserves devotion, not diminishment.Shed the weight of expectations. Trim down the thoughts of too much and not enough. Dance like your hips move mountains. Put some magic of unabashed self-approval in your cauldron, and witness how the steam of that self-esteem wafts out into the world — passing on permission for others to feel the same about their unique shape.A witch understands that liking and loving herself, her body, just as it is, in a toxic patriarchy, is an act of rebellion.Be the rebel.”And here is what I want to add: your body is also the cradle. It is the basket. It is the cauldron that is being held in the larger cauldron of these four great outer planets at 4°. You are held. Your body is held. The transformation is happening inside it, and through it, and because of it.Summing UpMercury crosses the South Node and meets Regulus. Vesta stations retrograde, joining the entire Aries cluster in reflection. The Mercury Cazimi at the basket degree of 4° Virgo brings through what needs to be carried toward the Venus and Mercury retrogrades. Mars comes back in bounds on eclipse day. The lunar eclipse arrives at 4° Pisces — held, stable, held.And four cards all pointing inward: pause. The turmoil is real, and it belongs inside where you can work with it. The inner pillars of support are there. Your body is the cauldron, the companion, the sacred rebel.Three planets have now crossed Regulus in Virgo. Kings in rags. Future stewards of the Earth and planets. The goddesses.We are in the birth canal, and we are pushing.Go close the temple door for a while. Let the new perspective arrive.— LouiseVenus Retrograde: Heroine's Journey — price holds through end of August. Partial scholarships available: louise@louiseedington.com. louiseedington.com/VenusRetrograde2026“Can We Let Evolutionary Astrology Evolve?” — now on Substack. Subscribe free for all posts.AstroTheoros — chart import/export, folders, notes, PDF printing, and growing asteroid support. Code COSMICOWL at astrotheoros.com.Code COSMICOWL20 (20% off) or COSMICOWL30 (30% off $99+) at Otter Spirit.Spiral Weave / Spiral Codex membership — $10/month or $90/year. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit cosmicowlastrology.substack.com/subscribe

What if the Industrial Revolution wasn't sparked by the steam engine, but by a quiet legal revolution in how England handled property rights? Ben Southwood of Works in Progress argues that the Glorious Revolution of the 1680s unleashed British growth by empowering a Parliament composed of landowners who simplified their own tangled, inefficient property rights. Through thousands of case-by-case acts, they freed up land for investment, consolidated inefficient farm ownership, and enabled a boom in privately-built roads, canals, and navigable rivers that created national markets. Along the way you'll learn why roads once moved at 1.5 miles per hour, and how these centuries-old lessons about buying off holdouts might solve today's housing and infrastructure gridlock.

Eric Williams was Trinidad and Tobago's first Prime Minister after independence. Pretty consequential stuff. But for us, and for this week's guest Alex Renton, Eric was so much more.Because in the 1940s, he became the first historian to forensically question the economics of slavery. The Oxford Dictionary of National Biography has dubbed his masterpiece, Capitalism and Slavery, "the most influential book" on the history of the subject in the 20th century. It aligns the slave economy not only with the expansion of the British Empire, but also with the Napoleonic Wars and the Industrial Revolution – and it questions the motives behind the abolitionist movement.Heady stuff. But also great fun and we thoroughly recommend this week's listen. Enjoy the rest of your summer and see you soon!Head over to www.trappedhistory.com to sign up to the award-winning podcast, get our newsletter, bonus episodes and much, much more. Hosted on Acast. See acast.com/privacy for more information.

Ben Horowitz, Travis Kalanick, and Erik Torenberg take the stage at Atoms' launch event for a candid fireside conversation about entrepreneurship, company building, and why Kalanick believes the next industrial revolution will be powered by AI. They revisit pivotal moments from Uber's history, including the decision not to acquire Lyft, lessons from scaling one of the world's fastest-growing companies, and how Kalanick has evolved as a founder. The conversation also explores Atoms' vision for industrial AI, why software is moving into the physical world, what it takes to build enduring company cultures, and why Kalanick believes the biggest opportunities of the next decade lie in transforming industries like food production, mining, and manufacturing.   Resources: Follow Travis Kalanick on X: https://x.com/travisk Follow Ben Horowitz on X: https://x.com/bhorowitz Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It feels like we're stuck in an endless debate about what AI is going to mean for jobs and the economy. The prediction you hear from the people closest to the technology — both its critics and its boosters — is that mass automation is coming, and with it mass unemployment. In response, some AI CEOs are promising a post-labor Golden Age of abundance and universal high income. But you also hear from some techno-optimists and economists that AI will create more jobs than it destroys and that society's fears are unjustified. When these arguments are traded back and forth, no one can know what's actually true, and nothing happens. And caught in the middle of this debate are actual workers trying to figure out what this means for their family and themselves, or whether their kids should go to college. And as long as that debate stays alive, nobody plans or takes action ahead of what's coming. So this week on Your Undivided Attention, rather than continuing to referee this debate, we follow the incentives and show you where they're actually taking us in the very near future. Our guest, economist Molly Kinder, argues that we're entering what she calls the “messy middle”: a period of concentrated and uneven workforce disruption. She has evidence-based arguments about where, specifically, AI will affect the labor force, what the second and third-order consequences of those effects might be, and what we need to do today to protect people's livelihoods. Molly recently left her position as a senior fellow at the Brookings Institution to become the founding CEO of a new organization dedicated to addressing AI's impact on jobs. Her Substack, Kinder Futures: Dispatches on AI, Work & What Comes Next, features some of the clearest-eyed analysis of AI's impact on the economy.RECOMMENDED MEDIA Kinder Futures: Dispatches on AI, Work & What Comes Next (Molly's Substack) Molly's blog posts at Brookings The Yale Budget Lab's AI Labor Market Tracker RECOMMENDED YUA EPISODES AI and the Future of Work: What You Need to Know Is AI Productivity Worth Our Humanity? with Prof. Michael Sandel AI and Jobs: How to Make AI Work With Us, Not Against Us with Daron Acemoglu   Corrections Molly incorrectly referred to cuts to “Medicare for the neediest populations.” The cuts she describes are to Medicaid. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Madelyn O'Farrell and Santosh Sankar unpack the data center boom and the idea of compute as the next utility powering an “industrial renaissance.” They explore how AI models are commoditizing, shifting value to the application layer, and draw historical parallels to industrialists like Rockefeller and Carnegie in terms of capital intensity, vertical integration, and long-lived infrastructure. The discussion dives into the biggest bottleneck (access to energy and grid capacity) along with underwhelming GPU utilization, the need for better observability and efficiency, and trends like prefab “constructuring” in data center construction. They also highlight labor and skills constraints in specialty construction, tools like Record Lens to digitize field operations, and the potential for a Foxconn-style contract manufacturer for electrical equipment. The episode closes on what excites them about founders in this space: deep problem understanding, real industrial pain points, and the ambition to build in the physical economy rather than chasing AI hype. Highlights from their conversation include: Setting up Compute as a New Utility and AI Data Center Boom (0:38) Why Compute Becomes a Utility and Implications for Trillion Dollar Tech (3:50) Drawing Parallels Between AI Infrastructure and the Industrial Revolution (6:56) Capital Intensity, Supply Chains, and Long Lived Industrial Assets (7:50) Financing Data Centers Like Power Plants and Identifying Key Bottlenecks (11:44) Energy Queue, Grid Constraints, and Alternative Generation Opportunities (12:25) Efficiency, Grid Utilization, and Rising Importance of Operational Arbitrage (15:13) Utilization, ROI vs. Dark Capacity, and Lessons from the Dot Com Era (21:23) Constructuring Trend and Prefab Manufacturing for Data Centers (26:16) Record Lens and AI Native Project Management for Grid Scale Construction (29:24) Idea of a Foxconn Model for Electrical Equipment Manufacturing (32:47) Standardization, Certification, and Cyber Risk in Grid Infrastructure (36:22) Founder Traits, Industrial Ambition, and Solving Top Three Customer Problems (38:00) Gold Rush Dynamics, Real Pain Points, and Building in the Physical Economy (41:31) FInal Thoughts and Takeaways (42:42) Dynamo Ventures is a venture firm backing founders upgrading the physical economy. As intelligence moves into critical infrastructure and technology collides with physics, industry is entering a new era of transformation - the industrial renaissance. Born from the dirt and grit of supply chains and shaped by operations, not spreadsheets, Dynamo focuses on the complex realities of building in the real world. We invest in companies transforming infrastructure, manufacturing, logistics, transportation, and the systems that power global commerce. Dynamo works closely with founders who combine ambition with a bias to action, bringing a builder mindset to venture capital through deep operational insight, systematic pressure-testing and hands-on partnership. Our purpose is simple: to back the relentless shaping the industrial renaissance. Learn more at www.dynamo.vc Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Our speaker to day is Patrick Allitt who is a Professor of History at Emory where he teaches courses in the American Revolution and the Industrial Revolution. Patrick also lectures for the Teaching Company with the Great Courses. I have taken six of Patrick's courses and they are absolutely fabulous that are available on their website.I want to learn from Patrick about why the British government demanded that American colonies pay their fair for their own defense, and why the Crown chose war instead of reconciliation. Americans learn in school why the patriots fought against taxation without representation, but we didn't consider why many American colonialists preferred King George's rule. Get full access to What Happens Next in 6 Minutes with Larry Bernstein at www.whathappensnextin6minutes.com/subscribe

Send us Fan MailThis week on the ole pod john: Going around back, AI ushering in 10x the Industrial Revolution, Tim Robbins, and not equating fame with success.Support the showThanks for listening! Listen, rate, subscribe and other marketing type slogans! Here's my Insta:@dannypalmernyc@thedannypalmershow@blackcatcomedy (NYC stand-up show every Friday at 9 pm. 172 Rivington St.)And subscribe to my Patreon? Maybe? If you know how to? I don't know how it works. Let's just leave this thing be:https://www.patreon.com/thedannypalmershow

David Epstein is General Partner at USF Ventures, the venture fund backing companies connected to the University of San Francisco. He was previously a General Partner at Crosslink Capital and has held management and CEO roles at more than half a dozen startups. He also teaches entrepreneurship and finance, and began his career at Data General as a computer designer, on the project chronicled in Tracy Kidder's Pulitzer Prize winning The Soul of a New Machine.In this episode, Dave argues that the real AI bottleneck isn't chips, power, or capital. It's data. We get into why frontier labs backing open weight models is a defensive move rather than a principled one, where early stage startups can still win, and why he thinks jobs will disappear faster than they get created.⭐This episode is brought to you by Podcast10x. We help founders and investors turn one podcast episode into a full month of content. Strategy, production, and distribution handled end to end. Learn more at https://podcast10x.comWhat we cover:→ Why "AI company" is no longer a category, and the pitch deck claim that has become his pet peeve→ Why AI isn't a tool anymore, and what makes this cycle different from the dot com era→ The real bottleneck: why we've exhausted the internet's data and what comes next→ Money as the constraint nobody prices in, and the circularity in the current data center build out→ How Chinese open weight models pull revenue out of token charges and subscriptions→ Why big lab support for open models is defensive positioning→ Who survives if open weights take share, and why consolidation is coming→ Where early stage startups can still win: drug discovery, financial services, legal→ Why the likely exit is a sale, not an IPO→ Ethical investing as a return rather than a tax, and why it's tough to work with jerks→ Why self-regulation rarely works, and what 2008 tells us about the current AI alliance→ Why layoffs are just the beginning, and the Industrial Revolution parallel everyone forgets→ Where the jobs actually are: management, human facing care, and the trades→ What top tier VCs get right, and why VCs are also lemmings→ Quantum computing as a data center accelerator, and the password problem it creates→ Physics AI vs physical AI, and the validation problem sitting on top of both→ Five year predictions: AGI, commonplace robots, and why consciousness doesn't matterConnect with Dave Epstein:LinkedIn: https://www.linkedin.com/in/thedavee/USF Ventures: https://usfventures.comConnect with Prashant Choubey:LinkedIn: https://linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comVC10X website - https://vc10x.comTimestamps:(00:00) - Preview(00:56) - Introduction to David Epstein and the Episode's Topics(02:48) - How the AI Startup Landscape Has Fundamentally Changed(05:08) - Comparing the Current AI Boom to the Internet Boom(06:25) - Identifying the Next AI Bottleneck: Chips, Power, or Data?(09:30) - Why Money is an Overlooked Bottleneck for AI Development(11:14) - The Cyclical Nature of AI Investments and Financing(12:46) - Analyzing Big Tech's Support for Open Source Models(15:12) - Winners and Losers: Open Source vs. Frontier Models(18:01) - How Early-Stage Startups Can Compete and Win in the AI Space(20:53) - The Role of Ethics in AI Investment Decisions(23:31) - The Challenge of Upholding Ethics in a Competitive Market(26:21) - Implications of the OpenAI Model Escaping(29:46) - The Future of AI-Driven Job Disruption(32:46) - Where to Find Employment Opportunities in the AI World(37:43) - How Top-Tier VCs Evaluate Founders and Make Decisions(40:21) - The Most Exciting Emerging Areas of Innovation(43:18) - Explaining Quantum Computing's Potential and Impact(48:39) - An Ambitious AI Prediction for the Next 5 Years(51:35) - Rapid Fire Round: USF Ventures' Investment Strategy(53:06) - Conclusion

Episode: 2623 Thomas Carlyle and the Working of Free Markets.  Today, economic salvation.

Artificial intelligence is rapidly becoming part of nearly every conversation in healthcare, but many executives are still asking the same question: What do I actually need to understand to make good business decisions? On this episode of The Dish on Health IT, Brian Dwyer, Business Strategist at Point-of-Care Partners, is joined by Sam Schifman, Principal Engineer for AI at Red Hat and Consultant at Point-of-Care Partners, and Kendra Obrist, Senior Consultant and Payer Interoperability Subject Matter Expert at Point-of-Care Partners, for a practical discussion about how healthcare leaders can evaluate AI opportunities without needing to become technical experts. Together, they explore where AI is delivering measurable value today, why many initiatives struggle to achieve expected outcomes, how to evaluate vendors and risk, what emerging policy and governance trends mean for healthcare organizations, and why strong data quality and interoperability remain essential to AI success. The conversation begins by unpacking what people actually mean when they say they're "using AI." Sam explains the differences between predictive AI, generative AI, conversational AI, and the rapidly emerging world of agentic AI, while Kendra encourages listeners not to get caught up in the terminology. Instead, she emphasizes starting with the business problem that needs to be solved and then determining whether AI is the right tool for the job. Brian then asks where AI is creating meaningful value today. Kendra highlights opportunities across administrative workflows, including documentation, member and provider engagement, claims, prior authorization, and other operational processes where reducing friction can improve efficiency and the user experience. Sam builds on that discussion by encouraging organizations to evaluate AI initiatives based on business outcomes and measurable success metrics rather than technical benchmarks, while recognizing that every AI implementation introduces its own set of risks and tradeoffs. The discussion shifts to why technically impressive AI projects often fail to produce meaningful business results. Kendra explains that organizations can become captivated by polished demonstrations without fully considering governance, data quality, workflow redesign, adoption, and organizational change management. Sam reinforces the importance of understanding AI's inherent uncertainty, establishing appropriate human oversight, and preparing employees for new ways of working as AI becomes integrated into everyday operations. Brian next explores how much AI healthcare executives actually need to understand. Rather than suggesting leaders become AI specialists, Sam encourages executives to develop enough knowledge to ask informed questions and avoid treating AI as an incomprehensible "black box." Kendra complements that advice by encouraging leaders to personally experiment with AI tools so they can better understand both their strengths and limitations before making strategic decisions. As organizations increasingly evaluate AI-enabled products, the panel discusses the questions healthcare leaders should ask prospective vendors. Beyond understanding how an AI solution works, they explore governance, transparency, auditability, accountability, data requirements, quality assurance, and vendor responsibility when AI produces unexpected results. Sam also introduces the concept of AI sovereignty, encouraging organizations to think carefully about long-term dependence on foundational AI models and the flexibility they'll need as technology and regulations continue to evolve. The conversation also examines the rapidly changing policy landscape surrounding AI. Kendra explains how federal agencies are currently taking a sector-specific approach to oversight while states continue introducing their own transparency, bias, and human review requirements. Together, they discuss the operational challenges this evolving patchwork of regulations creates for healthcare organizations operating across multiple states and why adaptability will become increasingly important. Looking ahead, Brian asks what developments deserve executives' attention and which trends may be receiving more attention than they warrant. Sam discusses why organizations should avoid assuming generative AI is always the right answer, highlighting continued opportunities for predictive AI, machine learning, and even traditional software approaches when they better fit the problem. Kendra shares why agentic AI and coordinated teams of AI agents may fundamentally reshape how work is performed across healthcare organizations. The episode concludes with each guest sharing one final takeaway for healthcare leaders. Sam encourages organizations to begin thinking strategically about AI sovereignty, security, and organizational flexibility as AI becomes increasingly embedded in core business operations. Kendra leaves listeners with a broader perspective, comparing AI's impact on knowledge work to the Industrial Revolution's impact on physical labor, and encourages leaders to embrace the technology thoughtfully rather than waiting until they feel they have all the answers. This episode offers practical guidance for healthcare executives who want to make informed AI decisions, ask better questions of vendors and internal teams, and develop an AI strategy grounded in business value rather than technology for technology's sake. Would you be interested in joining a future AI 101 webinar designed for healthcare executives? Sign up to be invited and tell us what you want to learn. We may not be able to pack everything into one webinar but we can do our best to make it as informative as possible. 

Sammy Murphy is the firstborn child in Sulfur Creek, an isolated coal mining town located on a rich seam of Bituminous coal discovered by a young gentleman born of wealth in the late 19th Century, the golden age of America's Industrial Revolution. The historical novel follows the life of Sammy from birth to death, capturing his transformation and struggles as a reclusive character, juxtaposed with his boss, who personifies the era's industrial barons. Barry Bacon, who grew up in luxury on Fifth Avenue in New York, is an ambitious American industrialist who fancies himself a peer to iron and steel magnate Andrew Carnegie. Driven by unbridled ambition, Bacon's dreams stretch far beyond the soot-covered rooftops of Sulfur Creek. His tale of arrogance and flawed leadership chronicles the precipitous rise and fall that mirrors the volatile spirit of the industrial age.

In this episode of Crossing Faiths, John Pinna interviews Devan Patel, a lawyer and strategist who collaborates with multi-faith communities on technology, policy, and ethics. The discussion centers on the intersection of artificial intelligence, human dignity, and religious communities, particularly focusing on the Vatican's forward-looking involvement in the AI discourse. Patel shares details about the newly released papal encyclical Magnifica Humanitas issued by Pope Leo XIV, which addresses the safeguarding of human dignity in the age of AI. Drawing historical parallels to Pope Leo XIII's Rerum Novarum, which responded to the Industrial Revolution, the conversation explores how various global faith leaders are universally responding to the risks of AI—such as companion chatbots affecting youth—and how the Vatican's receptive, human-centric framework provides a welcome platform for collaborative, cross-disciplinary dialogue on technology's future. Devan Patel is a Washington, D.C.-based lawyer, political strategist, and educator who operates at the intersection of law, faith, and technology. He is the founder and president of Crux Advisory Group, a fellow in AI ethics at the Rainey Center for Public Policy, and an adjunct professor of law at Notre Dame Law School. Throughout his career, Patel has focused heavily on legal strategy, public policy, and international AI ethics, which includes co-drafting the Electoral Count Reform Act, working on amendments for the Respect for Marriage Act, and convening industry leaders and faith figures at the Vatican to establish global ethical principles for artificial intelligence. https://www.devanpatel.com/

This is the second stop on our five-part audio guide to Asheville, North Carolina, and it reaches back a lot further than you might expect. In this episode of Unpacked by Afar, host Aislyn Greene unpacks the long, strange story of Asheville wellness, and why doctors have been sending patients to these mountains for more than a century and a half. To understand where Asheville wellness began, Aislyn talks with David Freedman, an infectious disease physician and travel medicine expert who retired to the city. He explains the era of climatotherapy, when clean mountain air and a just-right altitude were prescribed for the respiratory illnesses of the Industrial Revolution, and for the deadliest disease of the 19th century, tuberculosis. It's a history written into the architecture itself, from buildings angled toward the prevailing wind to the once-ubiquitous sleeping porch, and even into the phrase “health resort,” which Asheville helped invent. Then Aislyn brings the story to the present, where Asheville wellness has grown into one of the most diverse scenes in the country. She heads into the Asheville Salt Cave and Spa, surrounded by 30 tons of ancient Himalayan salt, and hears from owner Jodie Appel about the surprising family story that started it all. She also sits in on a sound bath with sound therapist Kristin Hillegas, and gathers the full, wonderfully weird range of what you can try here, from hydrotherapy and aura photography to a practitioner known as the Breath Nurse. It all adds up to a rich piece of cultural travel and a portrait of a place locals call the Happy City. Whatever draws you to these mountains, it's a reminder that the best travel experiences often start with simply feeling better, and that knowing where to go can be its own kind of medicine. Unpacked by Afar is a travel podcast that unpacks one destination at a time. This Asheville audio guide continues across three more episodes, so look for the rest of the series waiting in the feed. GUESTS David O. Freedman, infectious disease physician and travel medicine expert, Asheville Jodi Appel, owner, Asheville Salt Cave and Spa Kristin Hillegas, sound therapist, who runs Serenity Sound Healing of Asheville and leads sound baths at the Center for Spiritual Living Asheville Tebbé Davis, guide and storyteller, Asheville By Foot walking tours (returning from episode 1) PLACES WE VISITED Asheville Salt Cave and Spa Center for Spiritual Living Asheville Serenity Sound Healing of Asheville The Spa at Omni Grove Park Inn CHAPTERS (00:00) A century-old prescription: go to the mountains (01:40) A sound bath to begin (02:10) Meet David Freedman and the science of climatotherapy (03:40) Fresh air, altitude, and the architecture of breathing (07:50) Tuberculosis and the “Robber of Youth” (09:20) John Dickson's “cure” and the birth of the “health resort” (11:10) From sanitariums to a modern wellness scene (11:20) Inside the Asheville Salt Cave (13:00) Jodi Appell on salt, her father, and opening the spa (17:00) A sound bath, up close (19:00) Why Asheville calls itself the “Happy City” (20:45) People still come here to feel better MORE FROM AFAR Asheville Travel Guide 10 Travel Itineraries for Exploring Asheville Your Way (includes a restorative, wellness-minded itinerary) Learn more about your ad choices. Visit megaphone.fm/adchoices

As America celebrates its 250th anniversary, Leslie Marshall welcomes Scott Paul, President of the Alliance for American Manufacturing, for a fascinating look at the people, places, and industries that helped build the nation. Drawing from his "American Manufacturing 250" tour, Scott takes listeners from the birthplace of America's Industrial Revolution at Slater Mill in Rhode Island to Pittsburgh's legendary Carrie Blast Furnaces and finally to Detroit's "Arsenal of Democracy," where American factories helped secure victory in World War II. Along the way, Leslie and Scott explore how manufacturing has shaped America's economy, workforce, and national identity—and why a strong manufacturing base remains critical to the country's future. Scott also highlights the Alliance for American Manufacturing's state-by-state Made in America Showcase, celebrating innovative products and companies that continue America's manufacturing legacy today. It's an engaging conversation about America's past, present, and future—and the enduring role manufacturing plays in all three. To learn more, visit AmericanManufacturing.org, subscribe to the Alliance for American Manufacturing's YouTube channel at youtube.com/@AmericanMfg to watch episodes of 'The Manufacturing Report,' and follow the Alliance on X @KeepItMadeInUSA and Scott Paul @ScottPaulAAM for the latest news and insights on American manufacturing.

As America celebrates its 250th anniversary, Leslie Marshall welcomes Scott Paul, President of the Alliance for American Manufacturing, for a fascinating look at the people, places, and industries that helped build the nation. Drawing from his "American Manufacturing 250" tour, Scott takes listeners from the birthplace of America's Industrial Revolution at Slater Mill in Rhode Island to Pittsburgh's legendary Carrie Blast Furnaces and finally to Detroit's "Arsenal of Democracy," where American factories helped secure victory in World War II. Along the way, Leslie and Scott explore how manufacturing has shaped America's economy, workforce, and national identity—and why a strong manufacturing base remains critical to the country's future. Scott also highlights the Alliance for American Manufacturing's state-by-state Made in America Showcase, celebrating innovative products and companies that continue America's manufacturing legacy today. It's an engaging conversation about America's past, present, and future—and the enduring role manufacturing plays in all three. To learn more, visit AmericanManufacturing.org, subscribe to the Alliance for American Manufacturing's YouTube channel at youtube.com/@AmericanMfg to watch episodes of 'The Manufacturing Report,' and follow the Alliance on X @KeepItMadeInUSA and Scott Paul @ScottPaulAAM for the latest news and insights on American manufacturing.

In this episode, Savannah asks Julie the question, "Why do women get to wear pants and men don't get to wear skirts?" In Western Culture, the idea of men wearing feminine clothes is considered outlandish and fetishistic, while women wearing pants or more masculine articles of clothing is normalized and not seen as out of place. From the necessary changing fashion styles as humans found themselves in the Industrial Revolution to women fighting for their own rights for fashion equality, the modern era is still wrought with inconsistencies and inequalities.-----SAVANNAH HAUK is the author of “Living with Crossdressing: Defining a New Normal” and “Living with Crossdressing: Discovering your True Identity“. While both focus on the male-to-female (mtf) crossdresser, “Defining a New Normal” delves into crossdressing and relationships and “Discovering Your True Identity” looks at the individual crossdressing journey. Her latest achievements are two TEDx Talks, one entitled "Demystifying the Crossdressing Experience" and the other "13 Milliseconds: First Impressions of Gender Expression". Savannah is a male-to-female dual-gender crossdresser who is visible in the Upstate of South Carolina, active in local groups and advocating as a public speaker at LGBTQ+ conferences and workshops across the United States. At the moment, Savannah is working on more books, blogs, and projects focused on letting every crossdresser–young and mature–find their own confidence, expression, identity and voice.IG @savannahhauk | FB @savannahhauk | FB @livingwithcrossdressing | web @livingwithcrossdressing.com------JULIE RUBENSTEIN is a dedicated ally to transgender community and the certified image consultant and co-owner of Fox and Hanger. F&H is a unique service for transgender women and male-to-female crossdressers that creates customized virtual fashion and style “lookbooks”. Julie intuitively connects with each client to find them appropriate clothes, makeup, hair, and shape wear all in alignment with their budget, body type, authentic style and unique personality. Julie also provides enfemme coaching and wardrobe support. Julie has made it her life's work to help MTF individuals feel safe and confident when it comes to their female persona, expression and identity.IG @Juliemtfstyle | FB @foxandhanger | web @FoxandHanger.com

Francis Fukuyama is the Olivier Nomellini Senior Fellow at Stanford University's Freeman Spogli Institute for International Studies (FSI), and a faculty member of FSI's Center on Democracy, Development and the Rule of Law (CDDRL). He is also Director of Stanford's Ford Dorsey Master's in International Policy, and a professor (by courtesy) of Political Science. In addition he is the author of several books. His most recent titles are Liberalism and Its Discontents, Identity: The Demand for Dignity and the Politics of Resentment, and the upcoming In the Realm of the Last Man: A Memoir. Greg and Francis talk about Frank's “End of History” thesis and later work on liberalism, identity, trust, and political order. Fukuyama argues long-run historical progress is visible in the gap between developed and developing societies, but he still sees no coherent “higher” alternative to liberal democracy and market society. He also explains that modern discontent through generational forgetting of 20th-century horrors and a deeper human desire for recognition and struggle (thymos), including megalothymia - the drive for superiority, which can turn tyrannical.  They discuss how modern prosperity arose from Europe's unique mix of innovation culture, political fragmentation, religious schism, and family changes that fostered individualism. Frank contrasts state strength with constraint, and traces democracy's path through England to parliament and common law, critiques American anti-statism in state-building, and examines China vs India. They also discuss war's effects on state capacity, the internet's role in polarization and factual disagreement, and the need for shared liberal norms. *unSILOed Podcast is produced by University FM.* Episode Quotes: The collapse of a shared factual basis  [47:23] Liberal societies need to tolerate viewpoint diversity, but what we're seeing goes way beyond this. This is kind of empirical, factual diversity where people don't accept the same factual basis of the nature of the world. So, you know, are vaccines safe? Well, we used to think there was consensus about that because you have this whole accepted scientific system for empirical testing of propositions like that, and for some reason now people don't trust that anymore, or, you know, who won the last election, sort of, issue. Very hard to have a democracy if you disagree about whether you had a free and fair election, right? And these, again, I think would not have existed in the pre-internet age, that kind of disagreement over just simple factual information. The absence of a higher alternative to liberal democracy  [05:18] A lot of people have lost faith in liberal democracy, but I still don't see anyone posing a real alternative of a higher society. Does the rule of law hold without shared norms? [54:46] One thing that the last few years have taught me is that, in a way, you know, we used to think there's law and there are norms, and the norms are basically more flighty and less weighty, but the law is really a big barrier to bad action. And I think we're realizing that's not true. Everything is normative. Why the drive for superiority can't simply be eliminated [12:42] It was Bob Iger or some big CEO who wanted to climb the seven highest mountains in the world, you know? So there's a lot of ways that you can demonstrate your superiority that are basically, if not socially constructive, they're at least peaceful; you know, they're not going to harm other people. But it turns out that for Donald Trump, at least that wasn't enough. And I think that's a basic problem. You want outlets for this, what I call "megalothumia." This is the desire to be recognized as superior, and basically you can't have a society without that. I mean, you're not going to have any great baseball players, musicians, you know, philosophers if you don't have people that want to be excellent at something. But that also unleashes a kind of tyrannical desire to simply dominate, and I think that's the problem we're dealing with right now. Show Links: Recommended Resources: United States Agency for International Development Karl Marx Liberalism Thumos Bob Iger Choosing the Right Pond: Human Behavior and the Quest for Status Joel Mokyr Roman Empire Reformation Caesaropapism Henry II of England Estates of the Realm Oliver Cromwell Glorious Revolution Assize of Novel Disseisin Code of Justinian Neal Stephenson Robert D. Putnam Guest Profile: Faculty Profile at Stanford University Wikipedia Profile Social Profile on X Guest Work: Amazon Author Page In the Realm of the Last Man: A Memoir Liberalism and Its Discontents Identity: The Demand for Dignity and the Politics of Resentment State Building: Governance and World Order in the 21st Century Political Order and Political Decay: From the Industrial Revolution to the Globalization of Democracy The Origins of Political Order: From Prehuman Times to the French Revolution Our Posthuman Future: Consequences of the Biotechnology Revolution Trust: The Social Virtues and the Creation of Prosperity End of History and the Last Man Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This is Part 2! For Part 1, check the feed!This week we're joined by friend of the show, producer, writer and actor (and proud Welshman), Jonny Owen to discuss the golden age of Industrial Revolution era Wales!We'll chat copper in Swansea, the iron town of Merthyr Tydfil, and the sheer volume of steam coal dug out of the Cynon Valley, the Rhondda Valley and the Taff Valley.Jonny is heading to Hamburg in his one day Time Machine so what better time to ask you if this is a good idea? Or what you'd do with yours? Do email: hello@ohwhatatime.comPart 1 is released on Monday and Part 2 on Tuesday - but if you want more Oh What A Time and both parts at once, you should sign up for our Patreon! On there you'll now find:•The full archive of bonus episodes•Brand new bonus episodes each month•OWAT subscriber group chats•Loads of extra perks for supporters of the show•PLUS ad-free episodes earlier than everyone elseJoin us at

Host Richard Cunningham welcomes co-host John Coleman for July's Marks on the Market, joined by two veteran venture investors: Phil Jung, who helps lead the venture investing business at Sovereign's Capital, and Mark Phillips, co-founder and managing partner at Eleven Tribes Ventures. The panel digs into a historic first half of 2026 for venture capital, the "barbell" strategy reshaping early-stage investing, and why faith-driven investors need to understand both the opportunity and the constraints of the AI boom. Phil and Mark bring an early-stage, seed-focused lens shaped by operator-led, vertically focused founders — from wire harnessing to waste management — while John Coleman zooms out to the macro picture: record public market concentration, a $725 billion capex commitment from the hyperscalers, and the possibility that this technological shift could be ten times bigger and ten times faster than the Industrial Revolution. The conversation closes, as always, with reflections on Scripture and what it means to build — and rest — under God's sovereignty in the middle of historic disruption. Key Topics: A record-breaking first half of 2026: $412 billion invested in venture capital, more than all of 2025 combined The "barbell" approach to early-stage investing: mega AI valuations on one end, capital-efficient vertical AI solutions on the other Why physical products, deep tech, and hard tech are back in vogue after years out of favor Constraints on the AI boom investors should watch: capital expenditure limits, energy demands, and regulatory fragmentation Token costs, open-source models, and who ultimately controls the data Closing reflections from Psalm 127 and John 4 on surrender, weariness, and calling Notable Quotes: "It really is an unprecedented venture market in the moment that we have never seen before." - Phil Jung "Increasingly your software platform, your product is no longer the moat... it's distribution... and then it's integration." - Mark Phillips "We serve a God who's in control, who's unchanging, who created a universe far more complex than anything we're talking about here." - John Coleman

This week we're joined by friend of the show, producer, writer and actor (and proud Welshman), Jonny Owen to discuss the golden age of Industrial Revolution era Wales!We'll chat copper in Swansea, the iron town of Merthyr Tydfil, and the sheer volume of steam coal dug out of the Cynon Valley, the Rhondda Valley and the Taff Valley.Jonny is heading to Hamburg in his one day Time Machine so what better time to ask you if this is a good idea? Or what you'd do with yours? Do email: hello@ohwhatatime.comPart 1 is released on Monday and Part 2 on Tuesday - but if you want more Oh What A Time and both parts at once, you should sign up for our Patreon! On there you'll now find:•The full archive of bonus episodes•Brand new bonus episodes each month•OWAT subscriber group chats•Loads of extra perks for supporters of the show•PLUS ad-free episodes earlier than everyone elseJoin us at

This is episode 3 of a six-part series on food imperialism. Welcome to Edible Empire, a podcast by Planet Pulse Pacific about the hidden cost of our food.Food isn't just about taste—it's power. This podcast explores how empires and corporations built control through agriculture, reshaping cultures and feeding some at the expense of others.This episode traces the global impact of the palm oil industry from its indigenous roots to modern supply chains through three expert interviews.Dr Jonathan Robins opens by detailing the pre-colonial history of oil palm in West Africa and explaining how European empires weaponised the crop to fuel the Industrial Revolution, establishing structural patterns that mirror today's agribusiness models.Dr Helena Varkkey then unpacks the political economy of Malaysian production, exposing how entrenched relationships between political elites and conglomerates shield the industry from regulation.Farwiza Farhan brings a frontline conservation perspective from Indonesia, documenting how government-incentivised monoculture plantations drive deforestation, threaten endangered species, and violate Indigenous land rights. Together, the experts critique the effectiveness of voluntary sustainability certification schemes like the RSPO, debate whether palm oil can ever be truly sustainable at scale, and highlight the efforts of local communities fighting back against corporate food imperialism.Make sure you subscribe so you don't miss out on the next episode!Resources from this episode:https://www.mtu.edu/social-sciences/department/faculty/robins/https://commoditiesofempire.org.uk/about/jonathan-robins/https://theconversation.com/profiles/jonathan-e-robins-1227071https://seapeat.wixsite.com/homehttps://cgsea.org/https://umexpert.um.edu.my/helenav To view all the links to the websites and documents, visit the show notes on our website.Please support our work and enable us to deliver more content by buying us a coffee or becoming a member of Athletes for Nature.Follow us on Instagram and Facebook, subscribe to this podcast, and share this episode with your friends and family.

Episode: 1604 In which hydrogen balloons bind science to technology.  Today, hydrogen -- in 1783.

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

AI was supposed to make our lives better. Instead, it's made many of us scared and angry. Communities are protesting data centers across the country, and polling shows most Americans think AI is moving too fast.In today's episode, guest host Miles Bryan talks with independent journalist Jasmine Sun, who argues that public attitudes toward AI are undergoing a fundamental shift. Jasmine argues that AI is seen not simply as a technology to adopt, but as an elite political project to resist. The two discuss “AI populism,” the parallels with the Industrial Revolution, how public opinion about AI may affect US politics, and how the leaders of Silicon Valley are unprepared for the growing backlash against AI. Guest Host: Miles Bryan, Vox reporter and senior producer Guest:Jasmine Sun, journalist Find Jasmine's Substack here: https://jasmi.news/ We would love to hear from you. To tell us what you thought of this episode, email us at thegrayarea@vox.com or leave us a voicemail at 1-800-214-5749. Your comments and questions help us make a better show. And you can watch new episodes of The Gray Area on YouTube. Listen to The Gray Area ad-free by becoming a Vox Member: vox.com/members Learn more about your ad choices. Visit podcastchoices.com/adchoices

Live July 14, 2026 | Yaron Brook Show(Season 12, Episode 123)Knowles; Iran; ICE; Immigration; antitrust; Intel; Woke; HK; Bezos; Achievement | Yaron Brook ShowThe Right's War on Progress? Michael Knowles, Iran, ICE & Why Achievement Is Under AttackHas the political right become as hostile to capitalism and progress as the left?Michael Knowles' attack on the Industrial Revolution raises a much bigger question: why are so many conservatives abandoning the values that created modern civilization? Yaron Brook examines the growing alliance between populism, anti-capitalism, and anti-technology—and explains why defending reason, innovation, and individual achievement has never been more important.The conversation expands into the latest developments on Iran, immigration and ICE, antitrust attacks on Intel, DEI's retreat, Hong Kong's future, Jeff Bezos on wealth creation, medical breakthroughs, AI, philosophy, art, psychology, and much more—followed by an extensive audience Q&A covering Objectivism, morality, physics, education, music, constitutional rights, and today's cultural decline.If you value reason, freedom, and human achievement, this episode is for you.Watch now: https://youtube.com/live/zm1efvYAFvgMain Topics:00:00 Introduction: Spain vs. France, episode preview03:09 Michael Knowles attacks the Industrial Revolution07:36 Political violence, immigration & fact-checking Knowles12:17 How industrialization transformed civilization16:00 Why conservatives increasingly reject capitalism19:23 Technology, innovation & cultural change22:56 The Unabomber argument—and what's fundamentally wrong with it28:09 The Industrial Revolution: humanity's greatest achievement?29:06 Populism and the conservative abandonment of responsibility30:15 The collapse of pro-capitalist conservatism32:26 Freedom, capitalism & individual responsibility34:07 Left-wing vs. right-wing anarchism39:53 Iran, military strategy & American foreign policy46:27 ICE, immigration enforcement & political incentives54:08 Smithsonian history battles & antitrust politics59:44 Intel, industrial policy & government intervention1:04:03 DEI retreats while Hong Kong reinvents itself1:08:59 Jeff Bezos explains wealth creation1:13:12 Breakthroughs in cancer & Alzheimer's research1:16:52 The semiconductor boom1:18:38 Crime statistics, Super Chats & updates1:21:40 Ayn Rand Institute conference previewLive Audience Questions1:28:04 Does morality require survival—or merely intelligence? AI, emergence & ethics1:28:18 Did America's 1953 Iran intervention create today's Middle East crisis?1:40:43 What truly makes a genius like Newton or Ayn Rand?1:40:45 Why haven't we produced another Einstein?1:46:18 Why do philosophers question whether reality exists?1:46:24 Nuclear power's comeback: freedom or AI necessity?1:47:45 Can justice be achieved after irreversible wrongs?1:49:23 Why does humanity need art?1:54:55 Losing family and friends to irrational ideas—what should you do?1:56:05 Immigration enforcement, rights & moral responsibility1:57:58 Is empathy selfish?1:59:36 Celebrating political deaths—is nihilism becoming mainstream?2:00:34 Does the Constitution protect illegal immigrants?2:02:20 Are destructive philosophies rooted in low self-esteem?2:04:31 Is 1980s music objectively better than today's?2:06:41 Should ARI buy Yaron a private jet?2:07:25 Why do intellectuals ignore the human cost of bad ideas?2:09:56 Will Yaron watch Christopher Nolan's The Odyssey?2:12:10 What does "working class" actually mean?2:13:42 Why is Tamara de Lempicka so overlooked?#Objectivism #Capitalism #IndustrialRevolution #MichaelKnowles #Iran #Immigration #JeffBezos #Technology #AynRand #Inflation #OilPrices #Greedflation #Economics Subscribe for daily analysis on economics, politics, philosophy, technology, investing, and current events.The Yaron Brook Show is Sponsored by[The Ayn Rand Institute](https://www.aynrand.org/starthere)[Energy Talking Points, featuring AlexAI, by Alex Epstein](https://alexepstein.substack.com/)[Express VPN](https://www.expressvpn.com/yaron)[Hendershott Wealth Management](https://www.youtube.com/watch?v=X4lfC...) &(https://hendershottwealth.com/ybs/)[Michael Williams & The Defenders of Capitalism Project](https://www.DefendersOfCapitalism.com)[Support the Show]( / yaronbrookshow )[Sponsor the Show](askyaron@yaronbrookshow.com/)[One-time donation](https://bit.ly/2RZOyJJ)Join the [Yaron Brook Show YouTube channel]( / @yaronbrook )Like what you hear? Like, share, and subscribe to stay updated on new videos and help promote the [Yaron Brook Show](https://bit.ly/3ztPxTx)Continue the discussion by following Yaron on [Twitter](https://bit.ly/3iMGl6z) and [Facebook](https://bit.ly/3vvWDDC )Want to learn more about Ayn Rand and Objectivism? Visit the [Ayn Rand Institute](https://bit.ly/35qoEC3)Become a supporter of this podcast: https://www.spreaker.com/podcast/yaron-brook-show--3276901/support.Yaron is the executive chairman of the Ayn Rand Institute and a world class speaker. He is the coauthor of the national best-seller Free Market Revolution: How Ayn Rand's Ideas Can End Big Government, Equal is Unfair: America's Misguided Fight Against Income Inequality and In Pursuit of Wealth: The Moral Case for Finance. He speaks around the world on a variety of topics including the morality of capitalism, Ayn Rand and her philosophy, finance and economics, and the value of inequality.

Attitudes around social media are changing. A Pew Research study found that about half of teens surveyed in 2024 felt that social media had a mostly negative impact on their age group. A group advocating a more considered relationship to tech held what they called a Summer of Ludd Festival, named after the Industrial Revolution era workers movement, the Luddites. The festival in New York City featured tech-free activities ranging from meditation to a workshop on how to flirt in real life. But in 2026, is it really possible to live without the tech we've become so addicted to? Guest host Manisha Krishnan, WIRED's senior culture editor, talks to Gowanus, the spokespuppet of a local Luddite movement, about the tenets of their group - and how they plan to grow it. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Violeta Bulc, former European Commissioner for Transport and coordinator of the book Leadership Challenged, featuring 24 authors from around the world. They explore the dangers of transhumanism, the misuse of artificial intelligence, and how Silicon Valley has lost its authority to lead on technology ethics. Drawing from her background as a computer engineer who worked in Silicon Valley, Bulc argues for creating global AI infrastructure with democratically agreed-upon standards—similar to how the early Internet was built. The conversation covers the manipulation of public consciousness, the importance of middle-class agency in social change, and why humanity needs to reclaim ownership of its collective knowledge before private enterprises consolidate total control. Bulc's book is available for free download at ecocivilization.earth.Timestamps00:00 Stewart introduces Violeta Bulc and her book Leadership Challenged, coordinated with 24 global authors discussing humanity's chance through better leadership approaches.05:00 Violeta explains her technology background and critiques artificial intelligence naming, arguing these are powerful data-processing tools without true intelligence, emphasizing unknown ethical standards embedded in AI systems.10:00 Discussion of transhumanism as investment buzzword serving elite agendas, comparing to previous Silicon Valley bubble while emphasizing humanity's unexplored relational, spiritual and energetic dimensions beyond industrial development.15:00 Stewart discusses mainstream culture's fragmentation since 2008, Silicon Valley's dystopian vision, and personal strategies for reducing dependency on AI tools through diversification and stepping back from reliance.20:00 Violeta explains historical civilization patterns and middle class destruction, expressing hope that emerging thoughts worldwide will eventually converge to shift current power dynamics and technological obsessions.25:00 Technology as tool versus misuse, emphasizing builders' responsibility and ethical frameworks needed, comparing AI regulation needs to automotive safety standards that weren't implemented early enough.30:00 Edward Bernays discussion revealing manipulation through public relations and psychological operations, leading to modern sock puppet armies used by nation states for narrative control online.35:00 Internet described as most democratic technological tool ever built, maintained by responsible groups preserving equality and inclusion principles through decentralized infrastructure and IP address accessibility.40:00 Proposal for global AI infrastructure with agreed rules treating applications as interfaces, questioning private enterprise ownership of humanity-generated data and advocating collective management with usage fees.45:00 Technology evolution patterns from mainframes to personal computing back to centralized cloud computing, emphasizing need to prevent domination while preserving entrepreneurship and collective decision rights.50:00 Quantum physics principles applied to human connection and responsibility, discussing EU ethical committees reviewing AI projects post-approval, emphasizing caring hearts over short-term quarterly corporate thinking.55:00 Violeta shares company transformation experiences moving away from competition models toward serving genuine market needs, concluding with book availability at ecocivilization.earth for free download.Key Insights1. Violeta Bulc argues that artificial intelligence is fundamentally misnamed because there is no actual intelligence within these systems. They are powerful computational tools capable of processing massive amounts of data and identifying patterns, but they lack genuine intelligence. What concerns her most is that this technology has owners with embedded interests and unknown ethical standards, yet society increasingly wants to build everything on these applications and even allow them to make decisions for us. She emphasizes that as someone with decades of experience in high-tech engineering, including work in Silicon Valley, she understands the architecture behind these systems and believes we must recognize them as tools rather than intelligent entities.2. During her time as European Commissioner, Bulc helped write the first European strategy on artificial intelligence, which included three critical elements she was proud of. First, there must always be a red button to switch off any application or technology when it causes harm. Second, there must be a responsible person behind every app who can be held accountable for its consequences. Third, there should be an ethical committee evaluating powerful applications to understand their potential consequences. Though these principles have been somewhat diluted over time, they represent an important framework for responsible technology development that prioritizes human oversight and accountability.3. Bulc observes that throughout human history, great civilizations have risen across all continents, not just in Europe or the Americas, and most brought themselves down through decadence, self-centeredness, and arrogance before being finished off by external forces. She believes Western civilization is currently at this point, having become accustomed to obtaining resources through force and authority while constantly readjusting moral standards to serve elite interests. The industrial revolution initially improved conditions for people because industry needed workers, which led to the emergence of a powerful middle class. However, the elite recognized that the middle class was the only segment of society truly interested in change, so they systematically worked to destroy it over the past twenty to thirty years.4. The Internet represents the most progressive democratic tool ever built in human society, according to Bulc. Its fundamental architecture, based on TCP IP protocol and packet switching, was designed to be non-hierarchical, allowing any computer with an IP address to be seen on the same level as powerful global corporations. The maintenance of Internet tables remains in the hands of people with high levels of awareness and responsibility who are faithful to its initial democratic mission. She had hoped this technology would bring the world together as the closest tool humanity has invented to support equality and inclusion, and despite the problems with applications built on top of it, the underlying infrastructure still maintains these democratic principles.5. Bulc proposes creating a global AI infrastructure with globally agreed rules and standards, similar to how the Internet functions. She argues that many AI tools currently claim ownership of humanity's knowledge, wisdom, and heritage without permission, manipulating data that rightfully belongs to all of humanity. Instead of allowing private enterprises to capture this data first and then charge people to access it, she envisions putting all of humanity's data into a commonly managed infrastructure with clear rules about who can use it, under what conditions, and with fees paid back to humanity. This approach would challenge the current fragmented network of privately owned data centers and restore collective ownership of human knowledge.6. The transhumanism movement represents an obsession rather than a thoughtful application of technology, in Bulc's view. She distinguishes between using transhumanism as a tool for exploring the universe under extreme conditions where humans cannot survive versus implementing it on Earth as a replacement for humanity. The fundamental problem is that the human characters building these machines and applications have questionable ethical models, and they will not allow the rest of humanity to coexist peacefully on the planet. She advocates for transhumanism to be used for space exploration while preserving Earth for humans who want to live as relational, spiritual, and social beings connected to the natural ecosystem.7. Bulc emphasizes that we must move beyond the competition model and think carefully about the consequences of our actions because humanity is too connected and interdependent to simply do things because we can. She applies three basic laws of quantum physics to everyday life: we are all connected and influence each other, the same ideas can emerge simultaneously around the world through entanglement, and the observer always makes a difference in any situation. The current rush to develop technology without pausing to assess consequences is a deliberate tool to prevent thinking, driven by fear of competition. However, her fourteen years of experience helping companies recover from financial trouble demonstrated that moving away from competition models and focusing on genuinely serving market needs creates sustainable, prominent players who work together with customers and local communities.

Will you be in Washington, D.C. on Wednesday July 15? I will be interviewing Francis Fukuyama about how liberalism should respond to the postliberal threat. Find out more and get your free ticket here! —Yascha Yascha Mounk and Deirdre McCloskey discuss why ideas, not capital accumulation, made the modern world rich. Deirdre Nansen McCloskey, sometimes described as “the conscience of economics,” holds the Isaiah Berlin Chair in Liberal Thought at the Cato Institute in Washington, D.C. In this week's conversation, Yascha Mounk and Deirdre McCloskey discuss why liberalism drives economic growth, how the gradual erosion of inherited hierarchy unleashed centuries of innovation, and what liberals should think about the trans debate. We're delighted to feature this conversation as part of our series on Liberal Virtues and Values. That liberalism is under threat is now a cliché—yet this has done nothing to stem the global resurgence of illiberalism. Part of the problem is that liberalism is often considered too “thin” to win over the allegiance of citizens, and that liberals are too afraid of speaking in moral terms. Liberalism's opponents, by contrast, speak to people's passions and deepest moral sentiments. This series, made possible with the generous support of the John Templeton Foundation, aims to change that narrative. In podcast conversations and long-form pieces, we feature content making the case that liberalism has its own distinctive set of virtues and values that are capable not only of responding to the dissatisfaction that drives authoritarianism, but also of restoring faith in liberalism as an ideology worth believing in—and defending—on its own terms. If you have not yet signed up for our podcast, please do so now by following ⁠this link on your phone⁠. Email: leonora.barclay@persuasion.community Podcast production by Jack Shields and Leonora Barclay. Connect with us! ⁠Spotify⁠ | ⁠Apple⁠ X: ⁠@Yascha_Mounk⁠ & ⁠@JoinPersuasion⁠ YouTube: ⁠Yascha Mounk⁠, ⁠Persuasion⁠ LinkedIn: ⁠Persuasion Community Learn more about your ad choices. Visit megaphone.fm/adchoices

The English country house has been on the brink of ruination since at least the start of World War I—or perhaps the first chug of the Industrial Revolution—or was it the end of serfdom …? Propping up this dying, decadent institution has been a favored pastime of preservationists, architecture buffs, and earls for about as long as the institution has been around. In his new book, Noble Ambitions, historian Adrian Tinniswood peels back the wallpaper to show how these ancestral piles survived both World War II and the sunset of the British Empire—and in some ways, are more relevant than they ever were. This episode originally aired in 2021.Go beyond the episode:Adrian Tinniswood's Noble Ambitions: The Fall and Rise of the English Country House After World War IIFor the completionist, his previous book: The Long Weekend: Life in the English Country House, 1918-1939Revisit the famed 1974 Victoria & Albert exhibition “The Destruction of the Country House,” or go visit Agecroft Hall and Gardens in Richmond, Virginia, one of several country homes dismantled and reassembled on this side of the Atlantic. In England? Check out Sudbury Hall, which gets a shout out in the episodeThe first bestselling nonfiction book about the country house? Mark Girouard's Life in the English Country HouseRead Sam Knight's essay about the National Trust's recent report on colonialism and slavery: “Britain's Idyllic Country Houses Reveal a Darker History”If you haven't yet, you simply must watch Downtown AbbeyTune in every other week to catch interviews with the liveliest voices from literature, the arts, sciences, history, and public affairs; reports on cutting-edge works in progress; long-form narratives; and compelling excerpts from new books. Hosted by Stephanie Bastek.Subscribe: iTunes/Apple • Amazon • Google • Acast • PandoraHave suggestions for projects you'd like us to catch up on, or writers you want to hear from? Send us a note: podcast [at] theamericanscholar [dot] org. And rate us on iTunes! Hosted on Acast. See acast.com/privacy for more information.

The future of money is already here—and the people who understand it today will be better prepared for tomorrow. On this episode of Money & Wealth, John Hope Bryant sits down with fintech expert Nicole Valentine, Director of Fintech at the Milken Institute, for a powerful conversation about artificial intelligence, digital banking, financial innovation, and the biggest economic transformation of our generation. Nicole explains why AI and fintech are creating opportunities that rival the Industrial Revolution, how digital finance is reshaping wealth creation around the world, and why entrepreneurs, investors, and everyday consumers need to pay attention now. From cybersecurity and fraud prevention to digital assets, financial inclusion, and the future of banking, this conversation breaks down complex topics into practical insights anyone can understand. Beyond technology, Nicole shares the personal lessons that shaped her leadership—from her family's remarkable history to the habits, mindset, and confidence that helped her become one of the most respected voices in global financial innovation. Whether you're building a business, investing in your future, or simply trying to stay ahead of what's next, this episode is a masterclass on preparing for the future of money.See omnystudio.com/listener for privacy information.

Joel Mokyr co-won the 2025 economics Nobel for exploring the question that traces back to the beginning of economics: how did sustained economic growth suddenly become normal? For nearly all of human history, cleverness didn't compound. What changed, according to Mokyr, was twofold: first, you need to know why something works, so that one advance can seed the next; second, you need a culture willing to tolerate the disruption. His new book contrasts Europe with China, showing how Europeans learned to cooperate with people they weren't related to, in guilds, monasteries, cities, and universities, while China organized itself around the extended clan. One path led to internal stability and peace; the other, more restless and outward-looking, was the one that decided the world could always be made better. Tyler and Joel discuss European corporations vs. Chinese clans, why the Catholic Church became obsessed with cousin-marriage, how persistent cultural trends really are, why Chinese cities became so populous relative to Europe, why it took so long for European living standards to surpass China's, why sinified invaders kept getting swallowed by the dynasties they conquered, how geography kept Europe fragmented and China unified, where India fits into the story, why the Romans never made spectacles, why British soldiers stood two inches taller than the French, what powered the sudden rise of 19th-century German science, how disruptive winning a Nobel is, and much more. Read a full transcript enhanced with helpful links, or watch the full video on the new dedicated Conversations with Tyler channel. Recorded February 20th, 2026. This episode was made possible through the support of the John Templeton Foundation. Other ways to connect Follow us on X and Instagram Follow Tyler on X Sign up for our newsletter Join our Discord Email us: cowenconvos@mercatus.gmu.edu Learn more about Conversations with Tyler and other Mercatus Center podcasts here. Timestamps: 00:00:00 - Intro 00:00:54 - Europe vs. China's Paths to Prosperity 00:10:22 - China's Growth 00:13:24 - Europe's Growth 00:18:56 - The Fall of Song China 00:21:56 - India 00:25:08 - Industrial Revolution 00:39:52 - 19th-Century German Science 00:43:37 - Being a Nobel Laureate 00:45:29 - Outro Photo Credit: Shane Collins

In a world of constant, rapid digital transformation, one industry has struggled to evolve: construction. With all the gains made in efficiency and productivity, what's holding the construction industry back?  Brian Potter is a senior fellow at the Institute for Progress and author of the book, The Origins of Efficiency which charts the history of production efficiency, examining the great leaps forward with inventions like penicillin, the light bulb, and automobiles.  Brian joins Greg to share his experience in the construction industry that prompted his research into productivity and why construction productivity appears flat compared with manufacturing and agriculture. They also discuss distinctions between labor productivity and overall efficiency, the central role of scale and fixed costs, why tacit knowledge makes process transfer hard across plants and countries, and political obstacles such as guilds and unions resisting automation, including AI. *unSILOed Podcast is produced by University FM.* Episode Quotes: A factory is like a big sociotechnical machine 16:55: A factory is like a big sociotechnical machine where some of the capability lives in the machine, and a lot of it lives in, like, the processes that have been implemented and the heads of the people that are working on the line and know exactly what they have to do to make this work effectively. And it all kind of works together as one uniform thing. A lot of that is, like, not necessarily written down any place. It's either in this knowledge of these guys' heads, it's not written down, or it's, like, an emergent property of how all these things kind of work together, and it's very hard to decompose that and transfer it to a new place. It's often quite difficult to do that.  Has scale been the primary driver of efficiency since the Industrial Revolution? 08:42: Scale is a really big part of it for a lot of reasons. One is that just scaling effects are very powerful on their own. And then two is that scaling actually ends up being like a gating mechanism for a lot of other efficiency improvements in the sense that a lot of other efficiency improvements that you might implement need some sort of level, need some sort of scale, to be able to deploy them because they operate like large fixed costs. What is the genesis of “The Origins of Efficiency” 05:59: To understand why construction is so hard to make more efficient, I need to understand what other industries are doing to get more efficient. What strategies are they employing? And then I could understand why those strategies don't work in construction or whatever. Show Links: Recommended Resources: Adam Smith and The Pin Factory Katerra Henry Ford Do Management Interventions Last? Evidence from India by Bloom, Roberts, McKenzie, and Mahajan Nicholas Bloom - The Science of Management John Roberts - The In's and Out's of Organizational Economics Scale and Scope: The Dynamics of Industrial Capitalism The Visible Hand: The Managerial Revolution in American Business Frederick Winslow Taylor Joel Mokyr Guest Profile: Fellow Profile at Institute for Progress Professional Profile on LinkedIn Guest Work: The Origins of Efficiency  Construction Physics Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

How the Industrial Revolution and foreign investment made some nations rich while others stayed poor, closing with Mises's defense of capitalism—not because capitalists are good people, but because the market economy benefits mankind and safeguards freedom.

The liberal ideal of the individual and rational, welfare-serving law, and a defense of the Industrial Revolution against the myth that early capitalism degraded the common man.

This week we're heading back to Victorian London, where the richest city on Earth was quietly drowning in its own waste.As London's population exploded during the Industrial Revolution, millions of gallons of sewage, animal carcasses and factory waste poured straight into the River Thames. The result was The Great Stink of 1858 a summer so unbearably foul that Parliament was forced to flee its own chambers, and an engineering project was launched that would transform London forever.We also look at the pioneering doctor who proved cholera wasn't spread by "bad air", the Irish labourers who built the hidden city beneath London, and the extraordinary sewer system that still serves the capital today.Plus, we finish with the astonishing true story of a Japanese husband who paid rent on his wife's murder scene for 26 years in the hope that advances in DNA technology would finally identify her killer.⚠️ Content warning: This episode contains extensive discussion of sewage, bodily waste, disease and decomposition.

Is Islam Compatible with the West? Get your discounted early bird tickets now before they sell out: https://winstonmarshall.eventbrite.co.uk I cannot wait for you to join us in London for one of the most important debates of our time.In this episode of The Winston Marshall Show, I sit down with economist, author, and columnist Tyler Cowen for a conversation on artificial intelligence, the race between America and China, cyber warfare, and why the AI revolution will reshape every aspect of modern life.We explore the growing battle between the Trump administration and leading AI companies such as Anthropic and OpenAI, the risks of AI-driven cyber attacks, national security, effective altruism, and why Cowen believes the world is entering the most significant technological transition since the Industrial Revolution. We also discuss whether AI represents a greater geopolitical challenge than nuclear weapons, how governments should regulate it, and why the coming years could be both extraordinarily dangerous and extraordinarily prosperous.The conversation also examines the future of work, economic growth, surveillance, healthcare, longevity, education, and whether AI will deepen state control or instead empower individuals. Cowen explains why he believes AI could eradicate many diseases, transform productivity, and fundamentally alter the relationship between governments, corporations, and ordinary citizens.Finally, we turn to Britain's economic decline, immigration, productivity, energy policy, debt, and why Cowen believes the UK urgently needs a new economic direction before its long-term decline becomes irreversible.WATCH THE EXTENDED CONVERSATION HERE: https://www.winstonmarshall.co.uk/Chapters 00:00 Introduction02:10 AI Cyber Warfare & Why The Next Few Years Matter05:00 Trump, Anthropic & Who Controls AI?10:20 Can Britain Defend Itself In The AI Era?15:19 Why AI Is Like World War II19:20 Effective Altruism & The Future Of AI23:23 Is AI More Dangerous Than Nuclear Weapons?27:04 Will AI Cure Disease & Extend Human Life?30:00 AI, Surveillance & The Risk Of Totalitarianism35:00 Jobs, Education & How AI Will Change Work40:31 AI, Space & The Next Global Arms Race45:00 AI, Religion & The Future Of Faith49:07 Is Britain Already In A Debt Crisis?

Had an eye opening conversation with Alex Mehr (Famous.ai) and Jeff Gunsberg—about AI Here are 5 takeaways from our talk: 1. AI isn't software. It's a reasoning utility. For the first time, businesses can add "thinking" without adding people. That changes everything—from org charts to margins. 2. Demand-limited vs. supply-limited businesses will diverge. If you're demand-limited, AI boosts profit margins. If you're supply-limited, AI unlocks explosive growth. But only if you apply it. 3. The real skill isn't prompting—it's taste. AI can produce. Humans must judge. Common sense, intuition, and knowing what good looks like are now premium skills. 4. Your future job is managing AI, not competing with it. The winners won't "do the work." They'll guide, critique, and train the systems that do. 5. Execution just got democratized. If you're an idea machine who struggled to execute—AI just removed your biggest obstacle. Ideas + action now travel at the same speed. This is an Industrial-Revolution-level shift. You don't need to panic—but you do need to adapt, learn, and think two moves ahead. Connect with Jon Dwoskin: Twitter: @jdwoskin Facebook: https://www.facebook.com/jonathan.dwoskin Instagram: https://www.instagram.com/thejondwoskinexperience Website: https://jondwoskin.comLinkedIn: https://www.linkedin.com/in/jondwoskin Email: jon@jondwoskin.com Get Jon's Book: The Think Big Movement: Grow your business big. Very Big! Connect with Jeff Gunsberg: Website: https://title-connect.com     *E - explicit language may be used in this podcast.

Live July 4, 2026 | Yaron Brook Show(Season 12, Episode 114)4th of July -- What's to Celebrate? | Yaron Brook ShowThe Radical Revolution That Changed the World—And Why America's Founding Ideals Are Worth Fighting ForAmerica didn't become exceptional because of its geography, military, or natural resources. It became exceptional because it embraced one revolutionary moral principle: the individual has the right to live for his own sake.On this special Independence Day episode, Yaron Brook explores what Americans should actually celebrate on the Fourth of July—not blind patriotism, but the radical ideas that transformed history. From the Declaration of Independence to individual rights, capitalism, entrepreneurship, and Ayn Rand's moral defense of freedom, this episode asks whether America still deserves to be called the land of liberty—and what must be done to preserve it.As America approaches its 250th anniversary, are we honoring the principles that made this country great... or abandoning them?Join the conversation live and challenge the ideas.Watch now: https://youtube.com/live/Vakv4lZ54UcTimestamps00:00 Introduction00:27 Why celebrate the Fourth of July?03:03 Is America still worth celebrating?05:33 The revolutionary idea of individual rights08:01 Why the Declaration of Independence changed history10:49 America as mankind's greatest experiment12:39 Opportunity, achievement, and American success15:06 What "all men are created equal" really means17:23 Equality before the law vs. equality of outcome20:25 Life, liberty, property & the pursuit of happiness23:01 Freedom, reason, and choosing your own life28:28 Immigration and the promise of America30:03 Why reason made America prosperous32:58 The Industrial Revolution and America's innovators44:24 Celebrating entrepreneurs—from Edison to Musk47:20 America's creed and its global impact49:50 Ayn Rand and America's founding ideals53:02 Why freedom requires a moral foundation55:33 Recommitting to the philosophy of liberty59:33 What America should celebrate this Independence DayLive Audience Questions1:07:30 Why do postmodernists reject objective truth?1:10:32 America at 250—what should we celebrate?1:11:38 Which great thinkers came from the Netherlands?1:14:57 Jefferson's original Declaration draft—better than the final?1:16:07 Has Kant finally lost his influence?1:16:38 Is conservative patriotism preferable to socialist anti-Americanism?1:19:13 Why did Yaron say Objectivism may win in 150 years?1:19:58 Thomas Paine: "Start the world over again."1:20:30 America's freethought movement and Robert Ingersoll1:21:16 Conservatives regulate; progressives redistribute?1:21:34 Why are young people drawn to Catholic aesthetics?1:22:54 Favorite Yaron quote: "That's my pie!"1:25:32 How did the Colonists defeat the British Empire?1:30:39 Did the Founders underestimate political parties?If you enjoy these discussions, become a supporter, subscribe, and share this episode with someone who believes freedom is worth defending.#america250 #FourthOfJuly #DeclarationOfIndependence #foundingfathers #AmericanHistory  #Trump #Capitalism #IndividualRights #Freedom #Liberty #AynRand #ObjectivismThe Yaron Brook Show is Sponsored by[The Ayn Rand Institute](https://www.aynrand.org/starthere)[Energy Talking Points, featuring AlexAI, by Alex Epstein](https://alexepstein.substack.com/)[Express VPN](https://www.expressvpn.com/yaron)[Hendershott Wealth Management](https://www.youtube.com/watch?v=X4lfC...) &(https://hendershottwealth.com/ybs/)[Michael Williams & The Defenders of Capitalism Project](https://www.DefendersOfCapitalism.com)[Support the Show]( / yaronbrookshow )[Sponsor the Show](askyaron@yaronbrookshow.com/)[One-time donation](https://bit.ly/2RZOyJJ)Join the [Yaron Brook Show YouTube channel]( / @yaronbrook )Like what you hear? Like, share, and subscribe to stay updated on new videos and help promote the [Yaron Brook Show](https://bit.ly/3ztPxTx)Continue the discussion by following Yaron on [Twitter](https://bit.ly/3iMGl6z) and [Facebook](https://bit.ly/3vvWDDC )Want to learn more about Ayn Rand and Objectivism? Visit the [Ayn Rand Institute](https://bit.ly/35qoEC3)Become a supporter of this podcast: https://www.spreaker.com/podcast/yaron-brook-show--3276901/support.Yaron is the executive chairman of the Ayn Rand Institute and a world class speaker. He is the coauthor of the national best-seller Free Market Revolution: How Ayn Rand's Ideas Can End Big Government, Equal is Unfair: America's Misguided Fight Against Income Inequality and In Pursuit of Wealth: The Moral Case for Finance. He speaks around the world on a variety of topics including the morality of capitalism, Ayn Rand and her philosophy, finance and economics, and the value of inequality.

It's July. America just turned 250. And Candace is pulling a powerful thread through this month's focus in Pet Boss Nation: Work Smarter, Earn More, Adapt Faster. In 250 years, this country has survived wars, depressions, booms, the Industrial Revolution, the rise of the automobile, the telephone, the internet. Entire industries disappeared. Entire industries that didn't exist a generation ago became the backbone of the economy. The pattern? The businesses that lasted weren't the ones who had it all figured out. They were the ones who kept adjusting. Who paid attention. Who weren't afraid to pivot. Candace discusses:

The sense of smell is often linked to the dark, the antisocial, the primitive—the very opposite of modernity and progress. Today we live in an almost odorless world, where everything is reduced to images. Yet smell plays a vital role in how we relate to others and our surroundings, forming our experiences and our memories. Tracing a history of smell from the first ancient cities, through medieval plagues and the Industrial Revolution to the present day, Smell: The Tale of a Fading Sense (Reaktion, 2026) is a tribute to the sense of smell in all its beauty and disgust. Along the way, Bjørn Berge introduces us to twenty iconic scents—from blood and soil to the ocean—and invites readers to reflect on and reawaken their senses. This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda's interviews on New Books with Miranda Melcher, wherever you get your podcasts.  Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

In "Ending the 60% Waste: The Radical Shift Trucking Needs Right Now," Joe Lynch and Erik Malin, Founder and CEO of Tetro, discuss how treating trucking as a function of time, rather than miles, is the only way to eliminate the massive inefficiencies plaguing drivers and future autonomous fleets. Time is the real commodity.  About Erik Malin Erik Malin is the founder and CEO of Tetro, a technology company rebuilding trucking for the autonomous era. He has spent his entire career in freight, where his conviction that the industry measures the wrong thing, miles instead of time, became the thesis behind Tetro. Previously, Erik was on the founding team at Baton, a freight-tech startup acquired by Ryder, and led operations at FreightTech unicorn Loadsmart. About Tetro Tetro is a technology company that operates its own trucking fleet to recapture lost supply chain time and build essential data assets. Because 60% of time is currently wasted in trucking, the most common job in America has suffered perhaps the greatest wage suppression in history, and autonomous technology will never reach its full potential since a driverless truck still loses that same 60%. By running its own fleet, Tetro is actively building the data asset necessary to eliminate this massive inefficiency and unlock the true potential of modern freight. Key Takeaways: Ending the 60% Waste: The Radical Shift Trucking Needs Right Now In "Ending the 60% Waste: The Radical Shift Trucking Needs Right Now," Joe Lynch and Erik Malin, Founder and CEO of Tetro, discuss how treating trucking as a function of time, rather than miles, is the only way to eliminate the massive inefficiencies plaguing drivers and future autonomous fleets. Time is the real commodity. The 60% Waste Phenomenon: The trucking industry suffers from massive systemic inefficiency, where 60% of potentially productive capacity is completely lost to time leakage across the entire system. A Utilization Issue, Not a Driver Shortage: Contrary to popular belief, the core issue in American trucking is utilization rather than a shortage of drivers. Public company financials show that drivers are often only productive for 4.5 hours out of their 11 federally regulated daily driving hours. The Flawed Legacy Framework of Miles: The industry still relies on a metric inherited from the Industrial Revolution—paying and planning by the mile rather than by time. This creates a severe misalignment between demand and capacity because the industry remains functionally blind to duration. The Autonomous Vehicle Myth: There is a flawed industry assumption that autonomous trucks will seamlessly solve supply chain issues. However, because a driverless truck will still lose that exact same 60% of dead time at facilities, autonomy cannot reach its full potential without solving the underlying time-tracking problem. Operating a Fleet as a Mobile Research Lab: Tetro operates its own trucking fleet not to simply be a carrier, but to generate the highly specific, proprietary data asset required to address this waste. You cannot infer or partner your way into this information; it requires proprietary hardware and execution tracking to create. Shifting From Miles to Time via AI: Tetro developed an AI forecasting tool that converts traditional commoditized lane rates per mile into a rate per hour before committing to freight. This reveals significant market mispricing, exposing "bad actors" (facilities that notoriously waste time) and highlighting efficient shippers trading at a hidden premium. Unlocking Trapped Facility Upside: Internal data shows that 30% to 70% of a driver's on-site time at a facility is completely dead time where nothing is happening. By quantifying this data, Tetro can partner with shippers to release that trapped time, creating faster inventory turns and reducing the need for costly secondary assets like drop trailers. Learn More About Ending the 60% Waste: The Radical Shift Trucking Needs Right Now Erik Malin | Linkedin Tetro | Linkedin Tetro The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube

Weaving in Scotland In this episode of 'Unique Scotland', John Harbour explores the history and cultural significance of weaving in Scotland, inspired by his previous interview with Clare Campbell of the Highland tartan mill, Prickly Thistle. The podcast traces Scotland's textile heritage from its earliest beginnings through industrialisation and into the modern era. He talks about the survival of hand looms in the Outer Hebrides, especially in the Isle of Harris where the woven material is legally protected. And how did one man, with a loom in his garden shed satisfy NIKE's demand for 20,000 metres of cloth. You will hear an interview with Donald John Mackay who satisfied that order. Although ancient textiles rarely survive in Scotland's climate, archaeological evidence shows that Scots were working with fibres and woven fabrics thousands of years ago. Over centuries, weaving became an essential part of rural life, with families producing cloth in homes, crofts, and villages. This domestic industry laid the foundations for Scotland's later textile evolution. Scottish weaving developed around four key fibres, each shaping different regions and communities. Wool, Scotland's most iconic fibre, was produced from sheep in the Highlands, Islands, Borders, and upland regions, leading to famous products such as tweed and tartan. Flax, used to make linen, was cultivated mainly in eastern Scotland and supported important industries in Fife, Angus, and Perthshire. Cotton, imported through Atlantic trade, fuelled the growth of textile mills in Paisley, Glasgow, Lanarkshire, and New Lanark, transforming clothing and fashion. Jute, imported from Bengal, turned Dundee into one of the world's leading industrial textile centres, producing sacks, canvas, and other durable materials. The Industrial Revolution transformed Scottish weaving by moving production from homes into mechanised mills. While industrialisation brought growth, employment, and international trade, it also disrupted traditional ways of life, reducing the role of hand spinners and weavers and creating new factory-based working conditions. Two of Scotland's most famous textiles are Tartan and Tweed. Tartan became closely associated with Highland culture, clan identity, and ceremonial dress. Tweed developed as a practical woollen cloth suited to Scotland's rugged climate before becoming internationally recognised for its quality and connection to country life. Royal patronage, particularly from Queen Victoria and Prince Albert at Balmoral, helped elevate tweed's prestige. The pinnacle of Scottish weaving tradition is Harris Tweed, produced in the Outer Hebrides. Protected by law, Harris Tweed must be made from pure virgin wool, dyed and spun in the islands, and handwoven by islanders in their homes. Its unique colours, durability, and craftsmanship have made it one of the world's most respected fabrics, demonstrating how traditional skills can thrive in modern markets. John's interview with Donald John Mackay, a Harris Weaver for 70 years, brings to life this cottage industry where Harris Tweed is protected by law. Today, Scotland's textile industry combines large-scale luxury manufacturers with smaller craft businesses and independent weavers. Companies in the Scottish Borders, Elgin, Dundee, and the Outer Hebrides continue to produce world-class fabrics, while businesses such as Prickly Thistle emphasise sustainability, local identity, and traditional craftsmanship. Ultimately, Scotland's weaving story is one of adaptation, resilience, and cultural continuity. From prehistoric fibres and cottage industries to global fashion and luxury textiles, weaving remains deeply connected to Scotland's landscape, communities, history, and identity. You will also hear an interview with Dan, an army veteran whose cancer diagnosis brought him to Scotland to make memories for his family. John, a Navy veteren himself, organised the tour and a special visit to the prestigious Army club in Edinburgh, the Royal Scots Club.

In this series, Jeff & Andy dive into a mix of useless facts, myths, forgotten stories, and strange truths.In this episode, Jeff shares facts about giraffes in spirit of the missing giraffe in Texas, and Andy tells how our sleep habits changed after the Industrial Revolution.This series is brought to you by the amazing Cedar Run Decoys.

This is The Briefing, a daily analysis of news and events from a Christian worldview.On today's edition of The Briefing, I discuss the stall on the proposal for Smithsonian Women's Museum because Democrats will not define women as biologically female and the strange legacy of Barney Frank. I answer questions about the historical parallels of the A.I. revolution, who has the authority to perform baptisms, if investing can turn into gambling, and why Jesus didn't stop King Herod from killing John the Baptist. Part I (00:14 – 08:01)A Women's Museum That Doesn't Know What a Woman Is? Proposal Stalls for Smithsonian Women's Museum on National Mall Because Democrats Will Not Define Women as Biologically FemaleHow a bipartisan women's history museum became a political football by The Washington Post (Jonathan Edwards)Let Democrats kill the women's history museum by Washington Times (Editorial Board)Part II (08:01 – 13:46)The Death of Barney Frank: The Strange Legacy of the First Self-Identified Gay Member of CongressPart III (13:46 – 18:37)Is the A.I. Revolution More Akin to the Revolution of the Printing Press Than to the Industrial Revolution? — Dr. Mohler Responds to Letters From Listeners of The BriefingPart IV (18:37 – 22:26)Who Has Authority to Perform Baptisms? — Dr. Mohler Responds to Letters From Listeners of The BriefingPart V (22:26 – 24:50)When Does Investing Become Gambling? — Dr. Mohler Responds to Letters From Listeners of The BriefingPart VI (24:50 – 27:03)Why Didn't Jesus Stop King Herod From Killing John the Baptist? — Dr. Mohler Responds to a Letter From a 7-Year-Old Listener of The BriefingSign up to receive The Briefing in your inbox every weekday morning.Follow Dr. Mohler:X | Instagram | Facebook | YouTubeFor more information on The Southern Baptist Theological Seminary, go to sbts.edu.For more information on Boyce College, just go to BoyceCollege.com.To write Dr. Mohler or submit a question for The Mailbox, go here.