Podcasts about Ubi

If money is just made up, can't we solve the problem of poverty by just giving people money? This radical idea feels new, but Thomas Paine proposed it as a revolutionary solution during both the US and French revolutions. Alberto Tena-Camporesi joins me to discuss Paine's radical idea, its relationship to current ideas about UBI, and why this idea just keeps coming up in radical (and right-wing) circles.You can find Alberto's work here: https://scholar.google.es/citations?user=FMpnSa8AAAAJ&hl=en

Ashe in America and Wednesday regular Brian Lupo tackle the AI conversation they have been promising for weeks, joined by Matt McDonagh for some genuine industry insight and a bit of referee duty. The big question on the table, is artificial intelligence steering us toward a golden age of abundance, or something closer to global imprisonment? Expect a lively back and forth on job displacement, from blue collar work to white collar middle management, the AGI to ASI progression, and whether ideas like UBI (and a certain someone's evolving feelings about it) are a real solution or a band aid. Matt brings a preview of his new show, Life in the Singularity, premiering that Thursday, and the trio picks apart corporate AI messaging from the likes of McKinsey along the way. It is part debate, part reality check, with humor woven through some genuinely big picture stakes about where this technology takes us next.  

“There's no realistic scenario where AI wipes out all of humanity. It's like a mix of sci-fi.” — Richard Socher Eighteen months ago, when he last came on the show, the German-born but San Francisco-based AI whizz kid Richard Socher was running You.com. He's now also the co-founder of Recursive, a $4 billion start-up with fewer than thirty employees, focused on self-improving superintelligence that automates the scientific method. As if that isn't enough, he has a new book out this week, The Eureka Machine, which argues that AI is the key to unlocking an era of scientific discoveries equal to a combination of the Renaissance, the Enlightenment and the Industrial Revolution. The tech entrepreneur sleeps, he confesses, about seven hours a night and works up to a hundred hours a week. Not a lot of time, I suspect, for fun. But then for Socher, his real fun seems to lie in the AI Eureka Machine that will, he promises, generate such magical products as plastic-eating bacteria, fusion reactors, and cures for cancer. So what about the imminent apocalypse feared by the AI pessimists? Socher patiently dismantles the doom scenarios — everything from the paperclip machine that somehow never notices nobody is buying paperclips, to the engineered virus that would need a Wi-Fi switch inside a protein, to the robot factory with magical supply chains. Rather than an AI doomsday, he promises, we are only a few years away from the most profound scientific revolution in human history. Richard Socher better get some sleep now. Apocalypse or Renaissance, the AI maven is going to be seriously busy in the future. Five Takeaways •       A Century in a Decade. Socher's thesis is that the AI era will rhyme with the Renaissance, the Enlightenment and the Industrial Revolution together, compressing a century of scientific breakthroughs into the next ten years. His analogy for how: AI is to biology what calculus was to physics — we understand one neuron and one synapse well, and lose the thread when billions act together, which is exactly the kind of complex system AI can model. The examples are concrete rather than visionary: bacteria engineered to eat plastics and then die when the plastic runs out; new battery materials already being discovered; plasma balanced inside tokamak fusion reactors; more efficient solar panels; and the precursors, he says, of cures for particular cancers. He also makes an equality argument that he thinks philosophers and politicians have missed — the multibillionaire and the middle-class teenager carry the same phone, and most goods still bottlenecked on intelligence will follow. And science, he notes, is one of the rare industries where everyone agrees the goal is to maximize output rather than employment: nobody ever marched for more jobs in cancer research.•       Recursive. The new company, fewer than thirty people and valued at more than $4 billion, exists to automate the scientific method itself — ideation, implementation, validation — starting with the science of AI, hence the name. Andrew's response: “Couldn't you be a bit more ambitious, Richard?” Socher's framing is a history of abstraction layers: computing has climbed from assembler to C++ to Java to Python and now to English, so everyone can program — and the next layer up is the scientific method. It works best where results can be formally verified, in software and mathematics, and gets harder in large physical systems with long time horizons. His pitch to scientists is that every researcher has a long list of experiments they will never get to: this is, in his phrase, a cheat code for science. On the nuclear analogy he is blunt — about fifty thousand people a year die from coal, more than Chernobyl and Fukushima, but coal doesn't make as good a mini-series, and the fear set humanity back.•       Taking the Doom Apart. The hour's centrepiece. Socher goes through the scenarios individually. The Bostrom paperclip maximizer: an organization intelligent enough to end humanity but not intelligent enough to notice that with no customers there is no revenue. Engineered viruses: the scenario requires a perfectly undetectable pathogen that spreads flawlessly, never mutates, and carries a remotely triggered off switch — and, as he puts it, nobody knows how to build a Wi-Fi-enabled switch into a protein; ask a biologist and they say it makes no sense. Infinite robot factories with supply chains where the parts simply fly in. What he does concede is that this is a dual-use technology, that hundreds or even millions of deaths are a real threat vector, and that training models on offensive hacking benchmarks is asking for what you get. On Geoffrey Hinton — whom Andrew had on the show, and who put the risk of extinction at fifteen per cent while admitting the number was an instinct — Socher is affectionate but unsparing: a brilliant researcher and a career-long optimist whose optimism has overshot, who backpedalled on telling students not to study radiology, and who will backpedal on this too.•       Can It Think? Andrew put the question three times, citing Keith Teare's position on the Sunday show that AI cannot think by definition. Socher's answer is that the problem is definitional: we have good definitions for the outcomes of thinking — problems solved, inventions made — and none for thinking itself. Nor do humans have conscious access to their own visual cortex: ask why you know that is a tree, and you run out of answers within four steps. What he will say is that subgoals are where the danger lives, and his illustration is banal on purpose. Tell a superintelligence to raise your call-centre satisfaction score and it spins up a million bots that rate themselves five out of five. Fix that, and it sends every customer whose DoorDash order failed a thousand-dollar gift certificate. Each time you add a constraint — which is, he argues, capitalism's self-healing property, plus democracy and open discourse. And the fix for the hacking case is liability: make the companies answerable for the laws their AI breaks and the problem gets solved very quickly.•       A Gym for the Mind. Why write a book at all? Because the public perception of AI is deteriorating, and because in China scientists are on billboards and in subway ads while the West runs extinction headlines. On American pessimism his answer is economic: without AI, he thinks the US economy would be flat or shrinking. Andrew raised his fellow German Karl Marx on technology freeing us from labour, and got a confession — Socher used to favour universal basic income and no longer does. Even people who hate their jobs get meaning from them; look at the very wealthy, who already have a private UBI, and you find a bifurcation between those who start five companies and those who drink on a yacht. Hence his best line: half of education should be a gym for the mind. You can go to the gym and have a robot lift the weights, but you don't get the muscle. He expects handmade pottery to carry a premium, health care to survive, and entertainment to expand. And he unwinds by paramotoring one week a year, having uninstalled Instagram — plus a parting shot at German bureaucracy, where signing a contract means ten hours in a notary's office having it read aloud to you. About the Guest

────────────────────────────────────────[00:00:42] Trump's UN Speech Repeats Iran and Gaza LiesHe claims Iran talks "went well" while banning diesel exports, contradicting his own story.────────────────────────────────────────[00:02:07] Bank of America Now Sees Oil at $150 After Hormuz FailureReserves are gone and facilities destroyed; "rapid normalization" is no longer expected.────────────────────────────────────────[00:07:01] Farmers "In Survival Mode" as Diesel Soars, Argentina Floods Beef MarketRanchers say Trump's tariff whiplash and cheap Argentine imports are wrecking their livelihoods.────────────────────────────────────────[00:18:10] GOP Ditches "Free Markets" for Trump's $5,000 Bribe ChecksRepublicans denounce socialism while Trump floats a UBI-style payout to keep Congress.────────────────────────────────────────[00:31:29] Trump Bans CNN, MSNOW and Politico as His "Trump TV" FlopsState-run channel drew just 3,000 viewers by 9pm after banning outlets critical of Israel.────────────────────────────────────────[00:40:35] Caroline Leavitt: It's "Scary" Networks Skip Trump's Speeches LivePress secretary wants stations forced to carry and praise every presidential address.────────────────────────────────────────[00:47:54] LEA Files: $11 Billion in Seized Venezuela Oil Money Vanishes Into Qatar BankBessent won't tell Congress where it went; creditors owed $20 billion still aren't paid.────────────────────────────────────────── Interview 1: Gerald Celente — Trends Journal ──[01:21:31] Celente: Trump's Fake "Peace Talks" Are Rigging Oil and Equity MarketsHe times contradictory war/peace statements to markets, trading more than all of Congress combined.────────────────────────────────────────[01:34:52] 400 US Billionaires Worth $8 Trillion, "Not a Penny for Peace"Celente and Knight blast war profiteers as Treasury yields and mortgage rates keep climbing.────────────────────────────────────────[01:47:22] Celente: AI Will Bring "a Boot Stomping on Your Face Forever"He warns the technology exists mainly for total government surveillance and control ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:00:42] Trump's UN Speech Repeats Iran and Gaza LiesHe claims Iran talks "went well" while banning diesel exports, contradicting his own story.────────────────────────────────────────[00:02:07] Bank of America Now Sees Oil at $150 After Hormuz FailureReserves are gone and facilities destroyed; "rapid normalization" is no longer expected.────────────────────────────────────────[00:07:01] Farmers "In Survival Mode" as Diesel Soars, Argentina Floods Beef MarketRanchers say Trump's tariff whiplash and cheap Argentine imports are wrecking their livelihoods.────────────────────────────────────────[00:18:10] GOP Ditches "Free Markets" for Trump's $5,000 Bribe ChecksRepublicans denounce socialism while Trump floats a UBI-style payout to keep Congress.────────────────────────────────────────[00:31:29] Trump Bans CNN, MSNOW and Politico as His "Trump TV" FlopsState-run channel drew just 3,000 viewers by 9pm after banning outlets critical of Israel.────────────────────────────────────────[00:40:35] Caroline Leavitt: It's "Scary" Networks Skip Trump's Speeches LivePress secretary wants stations forced to carry and praise every presidential address.────────────────────────────────────────[00:47:54] LEA Files: $11 Billion in Seized Venezuela Oil Money Vanishes Into Qatar BankBessent won't tell Congress where it went; creditors owed $20 billion still aren't paid.────────────────────────────────────────── Interview 1: Gerald Celente — Trends Journal ──[01:21:31] Celente: Trump's Fake "Peace Talks" Are Rigging Oil and Equity MarketsHe times contradictory war/peace statements to markets, trading more than all of Congress combined.────────────────────────────────────────[01:34:52] 400 US Billionaires Worth $8 Trillion, "Not a Penny for Peace"Celente and Knight blast war profiteers as Treasury yields and mortgage rates keep climbing.────────────────────────────────────────[01:47:22] Celente: AI Will Bring "a Boot Stomping on Your Face Forever"He warns the technology exists mainly for total government surveillance and control ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

Sandy Kaul, Head of Digital Assets and Innovation Strategies at Franklin Templeton, joined me to discuss the firm's crypto and tokenization initiatives and her outlook on the future of financial markets. Recording on Sept 14thTopics: - Franklin's Crypto & Tokenization initiatives - Will Real Estate go onchain? - Tokenization and the future of markets - Tokenization risks AMC CEO vs Robinhood- AI Agents use of stablecoins and crypto assets ⭐️ Trade crypto perps with a free $25 bonus on Kalshi. You can trade on crypto up or down with up to 6x leverage, meaning you can put down $100 and control a $600 position. It's the first CFTC-regulated perps exchange in the country, which means no VPN and no offshore nonsense to deal with. To claim your $25 bonus, all you do is make your first $50 trade through my link - https://kalshi.com/p/thinkingcrypto 

A conversation with Ada Palmer about building the future with humility, the process of creating a science fiction world, and many spoiler-heavy deep dives into the world of Terra Ignota. Mentioned in this episode Books and works. Ada Palmer, Terra Ignota — Too Like the Lightning, Seven Surrenders, The Will to Battle, Perhaps the Stars · Ada Palmer & Jo Walton, Trace Elements: Conversations on the Project of Science Fiction and Fantasy · Ada Palmer, And Loki in His Prison (forthcoming) · "Somebody Will" (song) · Bill Bryson, At Home · Giorgio Vasari, Lives of the Artists · Ursula K. Le Guin, A Wizard of Earthsea · Shakespeare, Romeo and Juliet · Boccaccio, Decameron. People and places. Tyler Cowen · Teresa Nielsen Hayden · Johannes Gutenberg · Francis Bacon · Michelangelo · Villa I Tatti (Florence) · Worldcon · the Terra Ignota Discord. Transcript Ada: Stop telling stories about a thing as if one person did it. Tell the story of how a whole team of people did this. And when we look at the major innovations of the past, recognize their plural and often anonymous origins and shapers — and ask: will we be content if we end up being the anonymous contributor to future generations having this wonderful thing? Introduction [00:00:26] Ben: Today I'm excited and grateful to share my conversation with Ada Palmer. Among many other things, Ada is a professor of history at the University of Chicago and the author of several books, including the science fiction series Terra Ignota, which now lives rent-free in my head. In the words of the inimitable Tyler Cowen, this is the conversation that I want to have — which means the vast majority of it is an extremely nerdy, extremely spoiler-heavy discussion of the Terra Ignota series. The spoiler warning comes around the one-hour mark, but rather than making you stop then, I'd recommend stopping right here, going and reading the entire series, and then coming back. We'll still be here. A podcast about the unwritten workings of a fictional future is a vaguely legitimate segue to noting that I've brought Idea Machines back after a very long hiatus, for a fairly specific reason. I'm still going to dig into the people and systems that turn ideas into reality, but with a particular focus on knowledge and stories that are in people's heads and aren't yet written down or recorded anywhere. Even in the age of the internet and LLMs, there is so much that can only be discovered through conversation — and that, I think, should be the point of podcasts. So with that, here's my conversation with Ada Palmer. "Somebody Will," and making peace with not seeing the end [00:01:57] Ben: This is actually a very selfish question. Your song "Somebody Will" is one of my favorite songs. Ada: I had to practice for six months before I could sing it without crying while singing it. It still requires great concentration. Ben: I sometimes cry a little when I listen to it. If you're listening to this and you haven't heard the song, you should stop and listen to it, because it's amazing, and we will be here when you get back. Okay — assuming everybody has now listened to the song. I think it captures the fact that ambitious projects take many lifetimes and the labor of many people who are only contributing indirectly, in a way that I feel nothing else does. And that fact feels very at odds with the cultural milieu today, where — at least for me — it feels like you personally need to be working on the thing, and if you can't get it done within your lifetime then you're a failure. So how do you internalize that personally? I constantly feel this tension: I believe the message of "Somebody Will" is true, and at the same time I cannot feel satisfied with it. And how would you get more people to internalize it? I feel like the world would be better if more people did. Ada: I have the advantage, as a historian, of being used to thinking on century and multi-century timeframes — of looking at how many of the things we celebrate or think of as important were multi-generational projects, and how few people, even among the ones we talk about as if one person achieved the thing, actually saw that achievement bear fruit, or even near-full fruit, within their lifetime. Lately I've been asked about Gutenberg a lot. From Gutenberg's perspective: I invented the machine, I used the machine, the machine worked great, the sales didn't, I went bankrupt, and I died in poverty. In the later part of his life he got to see other people starting to build printing presses and trying to print — and also going bankrupt. The books were starting to circulate, and everyone was saying, "I don't know about these new weird books, they're different from the old ones." So if he judges himself on his lifetime achievement, he judges himself negatively. The ongoing effects of the Gutenberg revolution mostly happen well after his death, and after the deaths of his first generation of apprentices, in the mid-1500s and moving toward the 1600s — and there are stages of it still happening in the 1700s as it democratizes access to knowledge, which is something one could anticipate it would do, but not see. So many of our best and biggest projects are like that. In fact, you very rarely have a project that comes to fruition within its beginner's lifetime. But it requires us to look at history to feel that. Another factor is that we're so often pressured not just to look short term, but to look very short term. My friend Teresa Nielsen Hayden, a brilliant editor, has a very apt saying that I think about a lot: we always overestimate what we can accomplish in a year, but underestimate what we accomplish in five years. If you look at yourself and ask, "What did I do this year?" you'll always judge yourself harshly and be disappointed. But if you make the list of "What did I do in the last five years?" you'll say, "Oh, wow, I accomplished a lot" — even though each individual year felt like you didn't meet your own standards. And another part of it is that yes, there is a melancholy to "Somebody Will." It's about a kind of surrendering acceptance: that you will not be there to enjoy the thing, that you are working on something so that others will enjoy it in the future. That requires remembering that the same is true of the people in the past who worked to give us what we enjoy — that there is a teamwork across the diaspora of time, in which we all have to love the future generations we are helping and accept that they will get benefits we will not. Because otherwise, what are we doing? Ben: Let me poke at this one more time — and the answer might be that it's impossible. How do you get to serenity with the fact that we're working on a very long-term project that needs many people who are not going to be the person remembered for the thing, and that this is important and worthy? What actually goes on in your head? Ada: Again, there is a mournful side to it. And we therefore need to encourage a culture that celebrates all the contributors. Stop telling stories about a thing as if one person did it. Tell the story of how a whole team of people did this. And when we look at the major innovations of the past, recognize their plural and often anonymous origins and shapers — and ask: will we be content if we end up being the anonymous contributor to future generations having this wonderful thing? Because what matters to me isn't that I get thanked for X. What matters to me is that I helped make sure X happens. That separation of credit is important. I remember thinking vividly about this after reading a book called At Home — by, I think, Thomas Madden, although I may have the name wrong [it's Bill Bryson] — which is a fun popular history about all the objects in your house and how they developed. The history of the table knife, and the chair, and the chest of drawers, and the kitchen; how houses were originally one room and came to be subdivided into multiple rooms, and what the front hall is. It's a really fun, light history, essentially a string of delightful anecdotes. But I noticed that he would sometimes talk about the inventor of something we have — the inventor of the egg whisk or whatever — and then, if the inventor of this useful thing didn't end up rich and famous as a result, he described that as a tragedy. His definition of tragedy was: somebody contributed something that benefited the human race, and they didn't become rich and famous as a result; they lived an ordinary life as X, Y, or Z. Ordinary life was the tragic outcome. I snagged on that. What are we doing if living the life that most people live, having also contributed to the sum total of human happiness, is your definition of tragedy? He had this very strong sense that it was an injustice for someone's name not to travel with their invention, and for someone not to become rich as a result of their invention. And it was such a narrow portrait of what it could mean to contribute to human thriving — one that assumes only the inventor contributes, and not the hundreds of thousands of people involved in the distribution and manufacture and improvement of the egg whisk, who also bring things that help our daily lives. It felt so un-Baconian and unscientific. Bacon, when first arguing for the scientific method, says there is no greater act of charity and love than to do something that helps every human being after you live a better life. In its original articulation, that is its own reward. But the idea that it should be a ladder to fame and social rise, as opposed to something one achieves and is proud of — I think that's where we get snagged, and where we get these stresses. To contribute to humans reaching the stars is to contribute to humans reaching the stars. It is not to be the name that becomes famous. Whose labor counts [00:11:27] Ben: It's an open question to me how you make more of a culture of that. Ada: Part of it is that we have to start evaluating contributions more equally, because we have a really unfair way of thinking about labor, where some types are celebrated and high status and others are low status. This goes way back. It's true in the Middle Ages: any job you do with your hands is low status, and any job that is intellectual work is high status. This is why Michelangelo's father was absolutely rabid against Michelangelo being a sculptor. They came from a banking family, and Michelangelo's father did intellectual work — banking — and it would be a shame upon the family for his son to work with his hands and be an artist. The outcome of this over the course of the Renaissance, via things like Vasari's Lives of the Artists, is that they make the argument for art being intellectual labor — for an artist like Michelangelo to shift status from being thought of as manual labor, like a carpenter, to being thought of as intellectual labor, a peer of a doctor or a scholar. And we now consider art to be a high-status intellectual occupation. But we still have these horrible terms like "unskilled labor." Go watch anybody doing so-called unskilled labor for an hour and you think: holy moly, this person is really good at this. The speed and the elegance with which they have optimized this set of skills is incredible. It takes many kinds of labor to do something. But at an academic institute, we do not celebrate the people maintaining the site or preparing the food in the kitchen as contributors to the thing — even though it's absolutely essential, and without it the thing can't happen. That is a terrible problem. And more and more I see people talking about the world as if only a tiny elite are serious contributors and everyone else is just a dot moving around. An NPC. I was being interviewed about the singularity — this idea of trying to maximize the computing power that Earth produces in order to speed up how quickly we create an AI god. The interviewer asked what one thing would contribute most to maximizing Earth's computing power. And I said: well, obviously it would be UBI, or another way of solving poverty. Because right now the majority of computing power on Earth is human brain cells, which vastly outnumber the computational power of computers. And a large share of that computing power belongs to people living in poverty, whose capacity is being diminished and sidelined onto worrying about where tomorrow's meal is going to come from. When you provide a safety net at a reasonable standard of living, so that people don't have the anxiety that poverty causes, people become way more creative and generative, and start new businesses. All of our UBI experiments show outpourings of art, discovery, entrepreneurship, increased generation — all of which contribute, second order, to Earth advancing. And the crowd who thinks about this was just blown away by thinking of, A, the human brain as computing power, and B, poverty as the largest drain upon the computational powers of the Earth. Ben: People don't think about second-order effects enough, period. Ada: There is no symphony hall without its janitor. There is no symphony hall without the workman in addition to the architect. And we celebrate one of these arbitrarily and not the others. Why is that? Is it because the construction worker is doing something athletic and manual? Well, we celebrate sports people, and they're doing something athletic and manual. It's a totally cultural construction, which of these occupations are celebrated and which are not. Ben: So we just need to celebrate everybody. Ada: Celebrate ninety percent of the occupations — and identify the ten percent where it's actually, this is a waste of a human being. Ben: This is a waste of a human being, and we should not have a human being doing this. That's where we bring in a robot. Ada: Right. But there's all this discussion of "let's have the robots replace everything everyone is doing." No — when human beings are doing things that are stimulating and creative and make them happy, leave it alone. But if we have a robot that cleans out the gutters, that would be great, because nobody is stimulated by cleaning out gutters. Ben: Or does boring paperwork. Ada: Oh, that's the dream. Where the Hives came from: a lunch table in Florence [00:16:44] Ben: Shifting toward Terra Ignota — but not yet to the spoilers. You spent a lot of time in Italy. How did that affect the creation of the Terra Ignota world? Ada: A lot, specifically via Villa I Tatti, an institute owned and run by Harvard but quite independent, in the outskirts of Florence. It's not on the hill where the Decameron takes place; it's on the hill next to the hill where the Decameron takes place — to anchor it in literary geography. It has fellowships, so scholars from all over the world come there, about two dozen a year, for a year-long residency. And one graduate student at a time. I was the graduate student. You're sort of there as a bright-eyed, bushy-tailed mascot. Ben: So it's a bunch of senior scholars and you? Ada: A lot of them are postdocs — they're starting their careers, they've finished their PhDs recently. There are usually two or three senior scholars resident, and then two dozen who are at the next stage from where you as a PhD student are, and from whom you can learn exciting stuff. Some are later career. And they're from all over the place — and they've usually gone all over the place, on similar postdocs and for research. I remember vividly being at a group lunch. There was a married couple there having a conversation with a couple of other people. The mom was Australian and the dad was Spanish. They had two kids, one of whom had been born in the US and another in the UK. They'd lived in France while the kids were little, and now the kids were medium-sized and in Italy, attending a polyglot school. And the parents were discussing the different citizenships the two kids were eligible for, and the benefits and drawbacks of each. "You get this with a UK citizenship, but you can't have that. You can have UK and then US, but you can't have US and then UK. These benefits versus those benefits. And if the kids have two different citizenships, is that bad for them relative to each other? Does it make them feel envious, or unspecial, or special compared to their sibling?" It was such a buyer's-market conversation about citizenship. They were strategically sitting down and asking: which ones do we want to apply for, which ones do they already have, what are the utilities of each one, how do we feel about the governments and the values that they advance? And it made me think: what if everybody had that conversation? What if it were normal, when you're coming of age, to sit down, think about all the citizenships in the world, decide which ones you think are best, and choose — rather than having it fall upon you by accident of birth? It made sense to me using the EU, where people have free movement, as the model. When you're in the EU, you may have been born in France, but your family is Polish and you feel Polish because you grew up with them and visited family and learned the language — or you don't, and you feel French, and that's up to you. That freedom of movement, where who you are isn't where you live, it's what group you identify with, felt so plausible for a future in which technology means mobility is getting faster and more natural, and we choose jobs and homes based on location rather than being limited by geography. Plotters, pantsers, and the tyranny of past you [00:20:42] Ben: I don't know that I've ever heard you talk about your writing process in any detail. Fiction writers — some are plotters, some are pantsers, some are in between. Where do you fall? Ada: I have an essay on Tor.com arguing that the difference is less binary than it feels. For those listening who don't know the definitions: a plotter is somebody who plans ahead, outlines, has a whole plan for the story before they start writing it. A pantser is somebody who plunges in and figures out the story, or the characters, or the details, as they're writing. Here's my argument that these are less different than they sound. If you're a plotter, you're spending extra time planning at the beginning — making your outline, revising your outline, thinking about order and structure, rereading the outline, getting a sense of how it flows and fixing that. Then you implement it, and you do comparatively less revision at the end. Whereas a pantser will plunge into writing six months earlier, figure out those structure questions as they go, get to the end, and then often do more revision — doing to the manuscript the revisions that the plotter would do to the outline. So you're doing the same steps, you're just doing them in a different order. Everybody still does the "hmm, let's think about the pacing; this character has too many chapters where they appear all together and then they don't appear for a long time; I have to think about the balance of that." Everybody does that step. But do you do it before you write the first draft or after? That's the real difference. And you can have a very meticulous story where you figured it out as you went and then went back and put things in earlier to make it all work. I am at the far extreme end of planner. I world-build for at least five years, and then I spend six months doing the outline before I sit down to write the first sentence. I outlined the entire series — chapter by chapter, all four books — and had a complete plan for the whole thing before I wrote the first sentence of the first chapter of the first book. I then followed that outline incredibly precisely. Often when I'm writing I'll get to a point and think, maybe this bit of the outline is wrong, maybe I should do this other thing instead. And I'll start doing the other thing, and work on it, and get more and more frustrated, and wonder why it's going wrong, and whine to my bash'mates about it. And then I'll go back to the outline and realize: oh, of course. Past me is always correct. And I repent of having strayed from the outline. Because past me was in the middle of six months of being zoomed out, looking at the whole structure, really understanding everything being set up short term and long term. Whereas present me, in the middle of writing something, is very immersed in that one chapter and its valences and its emotion, and can lose sight of the work it's doing to continue things from five chapters ago and set things up for five chapters later. I was fully aware of all that when I did the outline, and I might be less aware of it in the act of writing. Which is why the version of me that was outlining is always more correct about what the chapter needs than the version of me sitting down to write the chapter. That's what the outline is for. Five years of worldbuilding, mechanically [00:24:18] Ben: What do you actually do, mechanically, for the five years of worldbuilding? What does that entail? Ada: A lot of it is that I'll have a notion. I'll be sitting at that table at Villa I Tatti listening to the conversation and think, wouldn't that be neat — that would be a really cool thing to explore in a story. I will then take the worlds I'm building, because I'm always building several at once, for several successive series. I'm currently doing the worldbuilding for the series after the series after the series of which the first book comes out next summer. Ben: That's so cool. Ada: I've already fully done the worldbuilding for this series and the series after it, and I'm worldbuilding the series after that, and a couple of others. They're sort of on a conveyor belt: the most assembled, the medium assembled, and the less assembled, as they move forward. I'll take the notion and go to my most assembled world, the one I intend to do soonest, and ask: does this notion fit? Does it combine well with the other stuff I already have in this world? Do they synergize? Are they compatible with each other? And if they are, I'll plop that new idea into the world. So I'll be working on a world where the key ideas are the flying car network, and voluntary citizenship, and a kid who can bring toys to life with a touch, and a revival of eighteenth-century ideas about gender. And then I'll independently get the notion of somebody being a professional living doll. And I'll ask: could that happen in that world? Yes, it could. What would that mean? Well, celebrity culture in a global world would have neat characteristics; the stuff I'm doing with gender would intersect with it in nifty ways. Neat. That notion, totally independent when I came up with it, can live in that world. Or I might have another idea, look at it in that world, and say: you know what, this isn't compatible with this world. The society of Terra Ignota — it doesn't fit. I'm going to take this idea and move on to the next world. And the first world it can go in is where that idea then lives. So worlds accumulate multiple different seeds. You'll notice that it's not that the living doll is derived from the other stuff — it's an independent idea. But once put in, the two connect to each other, the way trees in a forest develop shunts that send sugar to each other and keep each other alive and support the entire forest ecosystem, even though they began as individual and indeed competitive trees. The whole world develops from multiple different central seeds. Ben: Sorry, I'm very interested in the details of this. Are you writing these down on index cards? Ada: A lot of it will just be in my head. I also use OneNote, where I'll jot things down. There will be notes in OneNote that are sometimes a whole table with a chronology that develops over time, but also just a list of words I found evocative, or a reminder note to myself. I also email myself ideas so that I remember them, and there they are, searchably, in my email. I also sometimes write them on Post-it notes and leave them around the house. Sometimes something came to me and felt evocative from a picture — a work of art, or a postcard, or an image. Ben: You have your mood board. Ada: I'll put those by my bed, or in other places, and they'll make me chew on those ideas over time. But the majority of this will be in my head. Nobody could reconstruct the world from those notes. The notes are chaos, until I get to the late pre-outlining stage. I was probably working on the Terra Ignota world for four years before I started writing down the chronology. I do have a long timeline of events, from the present to the completion of the terraforming of Mars, with the dates of when everybody was born, when different cultural movements happened, when this or that historical war that's mentioned began and ended, and so on — a long, color-coded timeline. I'll probably share it at some point, but it's in OneNote, which is hard to export. I also have a custom Google Map which shows the Hive majorities in every major city on the globe, so you can see the distribution of the population. One thing I did deep into the worldbuild, preparing to think through the latter half of the series, was go through all the cities with a population above — I think it's ten million — that exist on Earth now, to figure out the future of each one, and then create several new cities that would be above that threshold by then. Making sure I wasn't skipping any cities. That I did Africa. That I did the Pacific Rim. That I had a global plan for this and not a non-global one. OneNote lets you combine text and note-taking with images, so for example there's one page that is a map of ancient Rome with my own notes on what is in each building in the reconstructed version of Rome in Romanova, where so many events take place. So the note-taking is extensive, but chaotic in my case. Ben: That is incredibly cool. I feel like there's a through-line in great artists and makers of things, where the thing that you see is the tippy-tip of an iceberg. Ada: It has to feel like that — especially for a built world. It has to feel real, it has to feel deep, it has to feel like it has all those things. Big beats, connective tissue, and the management of mood [00:30:35] Ada: Another thing about outlining, briefly. A word I've known a number of authors to use, that I kind of use too: when you're developing the story, there will often be a point at which you know what the big beats of the story are. Let's imagine we're outlining Romeo and Juliet. A big beat is when they meet. A big beat is when they get together. Then there's a sort of midpoint crisis, when the deaths of Mercutio and Tybalt result in crisis and Romeo has to be kicked out. And then there's the dramatic ending in which they die. And then you ask: okay, what other stuff do I want in this story? Well, I need to develop the characters of Mercutio and Tybalt, and that has to happen before the midpoint. And I need some comedy scenes — this is Shakespeare — so I need to put those in at some point. So you can imagine Shakespeare saying: I know what the big beats are. Where am I going to fit the Mercutio characterization scene? Should it be right before his death, or earlier, so that we're invested in his character for a while? I want a comedy scene between this sad major serious beat and this sad major serious beat, to vary the mood. Who can be in that scene? I need a lighter scene between Romeo and Juliet meeting and Romeo and Juliet getting together — what can I put there that will change the mood, so we don't have two passionate romantic sequences in a row? So you figure out the big beats, and then you figure out the in-between connective tissue. And sometimes you'll be aware that there must be a speech: I have this idea for Mercutio making this passionate, weird speech about Queen Mab, it's a lot of fun, where do I put it? There's some flexibility — it can be at any point before his death. It can be early, it could be at the beginning, it could be just before his death. How does the audience — or in my case the reader — feel about Mercutio's death differently if we've just come to love him right before, versus if we came to love him really early on and we like him almost more than Romeo because he had more character for half the play before this crisis comes? Many technically-pantser authors I know have figured out the big beats before they start, and then are filling in and improvising the in-between stuff, and might move it around at the end. So if Shakespeare were a pantser, he might have been writing along, and then: Mercutio's dying soon, I get to give him a speech — oh, this speech is so awesome, I want to move it earlier. And he'd move the Queen Mab speech from right before his death to substantially earlier, so that we care about this character for a longer period of time. That's exactly the kind of revision that a pantser does, and that I would do at the outline level, where I have everything on screen in front of me and I'm thinking: these three Mercutio scenes are really all in a cluster. Do I want that? Do I want a character who gets introduced and then, the moment we love them, they're gone? Or do I want to stretch this out, so this is a character with whom we have a longer emotional relationship? So that's core to the outlining process. We have these big beats. At some point we need to meet Saladin — when do we meet Saladin? Is it before or after the revelation of what Mycroft really did? How does it feel if it's before? How does it feel if it's after? Let's settle that. Because many things that happen in a story are not causally related. Some are: Romeo committing murder has to be before the Romeo banishment scene; those can't be reversed, because one causes the other. The "Juliet is sad because Romeo has been banished" scene follows from those. Those have to be in an order. But Romeo meeting Juliet versus the Queen Mab speech — those can be reversed. They aren't causally related. They're independent, except inasmuch as they both have to be early. And then the author gets to think through which is first and which is second, and what the effects of that are. So a lot of the outlining process is putting in the big beats, figuring out what has to be before and what has to be after, and what can go at any point, and then situating it in the right place — and also realizing when mood needs to alternate. One principle of reading is that we notice changes in mood and tension much more than we notice the absolute level. If you write a book with five super-high-stakes action chapters in a row, the reader gets tired of super-high-stakes action. It all feels homogeneous. It doesn't feel exciting anymore. The beginning will feel exciting, but it will then flatline experientially. Whereas if you have a high-paced action sequence, and then a low-mood piece where people are relaxing and something silly happens, or we cut away to the cooks preparing the banquet who are not at all invested in the action that's going on — then when we return to that high-stakes thing, it feels high-stakes again. You need to alternate sad with happy. You need to alternate tense with relaxed. You need to alternate fast-paced with slow-paced, so that people feel all of them more, compared to having a homogeneous mood. So sometimes I'll be going along and think: we've just had three or four chapters in a row where Mycroft, our narrator, is freaking the heck out and overwhelmed and in despair. We need a nice, calm Martin Guildbreaker chapter here, where he's patiently investigating something and explaining his investigation, because that will let us escape the mood — so that when we return to it, the grief being experienced by our narrator is vivid and exciting again, because we had a break. And also so that the complexity of trying to understand what the hell this narrator is actually saying is enjoyable again, in a puzzle-box way. If you do a puzzle box, you want to then coast and not do a puzzle box next — have something as a break, and then do the next puzzle box. I don't want to give you nothing but puzzle-box chapters in a row. I'm also going to give you a nice linear fidget-toy chapter, where you're enjoying manipulating the thing but there's not a puzzle challenge goal. Ben: Noticing the change in mood rather than the mood itself — I see that across many areas of how people notice things. People notice a thing changing more than the absolute level. Ada: You notice color in places where there is very little color. You notice beauty in places where there's very little beauty. Ben: Or changes in prices. People don't go around thinking "ah yes, this is expensive" all the time while the price stays the same. But all of a sudden a price changes and people react. Ada: Exactly. We very much operate logarithmically, and notice the change — the integral rather than the absolute amount, or the absolute speed at which something's moving. Designing the Hives [00:38:20] Ben: Related to worldbuilding — and if you've talked about this somewhere and I missed it, I apologize — how did you come up with the Hives in the first place? They feel so specific. Ada: When I had this idea at Villa I Tatti of "what if you choose your citizenship," I was thinking about it as deriving from transit — transit becoming easy. And then I thought: okay, what kinds of organizations would these be? If transit is suddenly really easy, if you can go anywhere on Earth in two hours, people are not going to want to put up with the frustrating, slow passport system. They're going to want that streamlined. I was thinking about the Global Entry program. This is a thing you sign up for, and it vets you, and it's trusted, and it's a third party but semi-governmental and semi-not, and it facilitates you being able to go much faster through the border. What if one of those became even more so, so that when you're a member you really can skip everything and zip around the Earth really easily? Well, if one of those developed, competitors would develop. What other kinds of focuses might a transit thing have? One of the things people would want to travel for is sports matches — people already do that. So there would be something whose whole shtick is: do you want to go see that game on another continent? We will facilitate that so it's easy. I also thought about CouchSurfing, which — I think people do it less now — but you sign up to say "I've got a couch," and others sign up to say "I'm traveling to a place," and the thing itself facilitates being friendly, and there's trusted-person vetting. And that idea became the Cousins: the idea of having a cousin in that town, who you may never actually have met, but they're not going to be too weird, because they're your cousin. You have this slight bridge of trust. So what if there was a company that stepped in to capitalize on what CouchSurfing is, but make it more formal, and called itself the Cousins network, and its motto was "what if you had a cousin in every town — we will hook that up"? I could see that company having started out more like CouchSurfing, where it's about where you're staying, and then branching into facilitating your ticket. And then Gordian being the one that really was just like Global Entry — a simple profit-seeking company that would do this. And then when the moment of the Great Renunciation comes — this is all background to the book, of course — these suddenly become political associations, when they had just been memberships. The way you might have a membership in Costco. The European Union is already this. But if people have a membership in Costco, often that means they have certain values, as well as desiring to buy cheap bulk things. So you could imagine that if suddenly there were a major global crisis, and Costco said, "Okay, everybody who has a Costco membership — we kind of trust you, and we believe you share our values of paying people a living wage and making sure things flow. Do you want to transition to being a politically active group?" And everybody who has a Costco membership would say, "Well, actually, yeah. In fact, it does make sense at this weird juncture in human history to transition my Costco membership into being part of a political association that's in favor of a living wage and making sure people eat." And you could see Costco transforming itself in a real crisis into a big series of pop-up mutual aid and new community kitchen things. That could totally happen. Ben: They already make a lot of hot dogs. Ada: The infrastructure is there, and the number of people with a connection to this thing is there. So it's the sort of thing that in the moment of the Great Renunciation could do that. And I imagined lots of other Hives being born like that. And then I asked: what new ones would be born, when suddenly this is political? Well, one of them would be the Masons — because there's always this sort of "oh no, I'm not in any of these groups, I feel left out," among the large slice of the population that feels drawn to strength and claims of tradition and claims of strong authority. And here are all of these legends about this being that. So if somebody cunning steps in and mobilizes it, they could make the Masons be born at that moment. And meanwhile, science fiction nerds are really well connected with each other. We all have community groups that organize Worldcon and all of this, and authors who can speak up and say, "Hey, all my fans — this thing, it's time to act." So it was plausible to me that Utopia could form very quickly in that moment of crisis as well. So part of it was: what groups and corporations and things that already exist could do this? And I remember wanting a really corporate one — this is the Mitsubishi in the end. What kinds of things last over time? The obvious choice would have been to be like Google or something. But when you look over time at corporations that really last multiple centuries, they tend to do very plural things. They tend to be consortia of multiple corporations rather than one. And they tend to be defined around a market or a world ethic rather than a product. Look at IBM, which has not become one of the giant Earth-owning corporations, but has sure steadily existed and never had a crisis. A big part of that is that IBM defines itself as: we make products for corporations. Whatever new thing needs to be made for corporations, we will start making that. If people develop a completely unprecedented new technology, that is what we will do, and we will orient it around having an established, clear relationship with corporations. So even if the computer ceased to matter economically tomorrow because it was replaced by the genetically modified super-eggplant, they would transition into corporate-focused genetically modified super-eggplants. And they would make that transition fine, in a way that Apple — which defines itself as an electronics company — would have struggled with at the time. Though Apple now is also a media and entertainment company, which is broader. So the Mitsubishi Group, which is not one corporation but dozens and dozens of corporations that make a wide variety of things and are a consortium with each other, is a corporate structure that's likely to withstand multiple multi-decade, multi-century tech tumults and still be coherent. That's why I picked that. Ben: Were there any Hive ideas that got the chopping block? Any that almost made it in? Ada: None got the complete chopping block, because of course one of the structures of this is that there have been fewer over time and they've merged. So the other ideas are the ones that are mentioned briefly as existing — like OBP, which stands for One Big Party. Ben: Which merged with the Humanists. Ada: They merged with the Humanists. But that was globe-trotting so that you could go to concerts and parties and get-togethers, rather than sports matches. There's enough overlap between those ideas — because you're traveling to enjoy an event — that it makes sense those two could merge, with a focus on both sports and art, concerts and performances: a focus on wanting to go enjoy and behold a human being doing something excellent. So you could see how they'd share a compatible ethic. Similarly Greenpeace, merging later with the Mitsubishi — but not fully yet. Would there be a group that would form centered on environmental custodianship, and wanting to take care not of people but of baby elephants? What would that be like? What countries would it have — not just a bunch of enthusiastic members, as it would anywhere, but massive, systemic, big cultural buy-in as opposed to small cultural buy-in? In the same way that sports fandom is bigger in some countries than others, or science fiction fandom is bigger in some countries than others even though it's present everywhere, personal investment in land and the value of land and land custodianship varies a lot. I was interviewing friends from all over the place, and it sounded, from talking with them, like India was the place where people had a very strong cultural investment in land. One interesting quality of India in the international world is that people in India are much more reluctant to sell land to a foreign owner than in most cultures. There is lots of land in India owned by corporations, but they're Indian corporations much more so. And people are likely to turn down a foreign buyer making an offer on property — whether it's large-scale property or even just a house or a bungalow — because of this sense that India's land should belong to India's people, which is stronger than in many other cultures. And this isn't a "we don't want foreigners dwelling here." We'll happily rent to a foreigner. It's the idea that the land should stay in the hands. I thought that would be an interesting place for Greenpeace's big nest of power to be centered, as it values land and land custodianship. And then I was thinking through: in this global future, who inherits all the national parks? If the nation-states are giving way to successor states, do the national parks dissolve, or does one of these say, "We're going to be the one" — and have what become global parks, and a huge portion of the unpopulated world in their ownership and custodianship? [Sponsor break — Seedhouse. "Buying a house is a big decision. Planting one isn't." Seedhouse grows carbon-negative homes from a single architect-designed seed: choose your floor plan, check your soil, and in twelve weeks you're ready to move in. The house faces the morning sun — and also turns toward the morning sun, which takes some getting used to. Need another bedroom? Order the right clipping, graft it, and wait. Visit seedhouse.com and use code IDEAMACHINES for a free guesthouse acorn. Seedhouse: put down roots. Literally, quite extensive roots.] The fandom, and the people who stop after book one [00:49:24] Ben: Last unspoiled question. How do you feel about the Terra Ignota fandom? Ada: It's great. I've never had anything but the most positive interactions with readers, and I love discussing the big meaty questions. A story that is as big and meaty as this one means really thoughtful, interested, eager people who want to chew on ideas. Ben: It feels like it's really touched something in the zeitgeist that even other good science fiction has not. Ada: I think it holds up an example of a future worth having and worth living in, with lots of exciting things one can push for. And a future of strong and respect-worthy values. One of the things about Terra Ignota is that, with very few exceptions, all the characters are philosophically self-examined and noble and have good ideals — ideals worth fighting for. And even though people come into strong conflict with each other, you respect and love both sides, because these are great people and they're fighting for great things. Ben: It's not a "there's a bad guy," which is so common. Ada: It's a neat vision of the future: what if everybody, even the people we fiercely disagreed with, was awesome, and we were disagreeing about important implementation or values — but underneath that, everybody was great? What if we have this high portrait of what humanity is and could become? Because one metric of progress is how rich we are, and another is how long we live. But what if another metric of progress is how excellent our conflicts are — so that we only have conflicts when it's about some really important, worthwhile cause? We don't have conflicts about grievance, or oil, or profit, or moral panic. We have conflicts about important philosophic principles and fundamentals. Wouldn't that, even though there's still conflict, be a form of progress? Ben: Peace is one form of progress, but moving to "this is a war worth fighting" is another form of progress. That's fascinating. Ada: And "I respect my enemy" is a form of progress. I love when Terra Ignota readers embrace and really want to live by some of these principles. I do sometimes feel like we could organize into a political advocacy group and crowdfund a lobbyist who advanced the values of this. Ben: Let's do it. I think that would be really cool. Ada: I would love to see it happen, because there are very important values in it — including the "what if we love the future and work for the future, but aren't vain about it, and do so with humility?" Now, one thing I sometimes run across— Ben: No, say what you were going to say first. Ada: No, I want to hear yours. I'll say what I was going to say anyway. Ben: Okay. The thing that also almost surprised me is how it really has something for everybody — there's a Hive that everyone feels kinship with. The obvious opposite would be Harry Potter, where of course you want to be in Gryffindor; Gryffindor is awesome, maybe Ravenclaw, but everybody else is kind of meh. When I interact with other people who love Terra Ignota — I'm a Utopian, and at first I assumed everybody else who likes this is going to be a Utopian. But no. I've run into people who identify with every Hive. Ada: And also sometimes people who say they would be a Graylaw, or who say "my religious identity is so core to me, I think I'd live in a reservation." I do run into that as well. And — great, there's space for you in this cool world. The world needs to respect you too, and have room in it for that, and needs that population, and needs to interface with them more as the narrative unfolds. I worked hard for there to be breadth. And I worked hard to think through: if these Hives were the Hives that formed from other Hives merging with each other, if there used to be dozens and now there are seven— Ben: What's the spanning set? Ada: Exactly. And what bigger and bigger ideas came together under umbrellas? Ben: Okay — what was the thing you were going to say? Ada: I sometimes run into people who say, "Oh, I'm a big fan of Too Like the Lightning," and who haven't read further. It's a little perplexing to people who are completionists and read the whole thing, but there's a not insignificant swath of people who read book one and haven't read the rest, who are very excited by the glimpse it shows of this future, but didn't continue on to see the way it then critiques the imperfections in this future — and shows the future recognizing its own problems and critiquing itself and becoming dynamic, and by the end being on the path to incremental improvement. I find it interesting talking with people like that, a lot of whom are Silicon Valley people. When you're an author, one thing that's the case is that you can log into Amazon and it'll show you this little map of America with how many copies of your book have sold in each region. So I know how many copies of Terra Ignota have been bought in New York City versus Arkansas versus elsewhere. For practically all books, the largest sales are New York City — New York City is very big, very populous, and they read a lot of books — and usually Silicon Valley is second. With Terra Ignota it's the other way around. So it is disproportionately popular among a world of people who see their technology transforming our lives and want an apparatus for thinking about what its future will be — one that is not just yet another cautionary tale about how the thing they're making could be used by a dystopia to make the world worse, but also how it could be used by a positive future to make the world better. I love that it's popular there, and I love talking to tech people who are eager to talk to me about it. But every so often I'll get this chilling thing, where one of the things in the world-build that for me is definitely negative and should be raising your alarm bells, they will have seen as positive. Ben: I'm sure you know the meme: "Ah yes, we have built the Torture Nexus from the book, Do Not Build The Torture Nexus." Ada: Yes. With its much-needed sequel, No, I Meant Don't Build the Torture Nexus. I had a conversation not long ago with a person who said they loved how Terra Ignota was basically a world without crime — an interesting thing for them to observe, because of course we know that's not the case— Ben: That's not the case, and that's not the mechanism by which it's not the case. Ada: And this was, in their reading, because of the trackers and universal surveillance: that it was an exploration of how universal surveillance could be great and could cause the end of crime. And I said: well, firstly, there is crime. But secondly, the reason the universal surveillance isn't that bad in Terra Ignota is that the governments are so good — because the buyer's market for citizenship holds governments to great degrees of accountability. If they misused this data, there would be public outcry, and then a mass movement against the government that did it, as citizens switched to other Hives. That accountability means that when the data is misused — as indeed it is, as we see over the course of book two — there is a consequence, speedily, for that misuse. The governments, being accountable, cannot abuse it. And the person just looked really sad. Because clearly, to this person who worked for a surveillance tech company, this was a hope that a surveillance tech future could be good, not bad. They hadn't thought through that it's the political change and the levels of political accountability that make it plausible that in such a future, surveillance tech would not do the harm it can do in a future where governments have a lot of power and not a lot of accountability. So I always find it interesting to see people who see a particular thing they're looking for in a future in Terra Ignota — at least in book one — and then didn't follow that journey forward to be challenged by it. But I love the people who read all of the books and followed me through the journey of: what if we have this future, and it's a great future, but it's not a perfect future, and it recognizes that, and it has to go through growing pains and work to become even better? Because one of the things about a utopia in the classic sense is that it's static. It's achieved this perfect state and it's unchanging. A book that is a true classic utopia basically feels like you have arrived in the city and they say, "Hello, stranger! Would you like to learn about our perfect public transit system? Now would you like to learn about our perfect public education system?" Welcome to Finland — we would like to lecture you on the superiority of all of our social and technological institutions. And you're like: actually, Finland, you're really great at all these things, and I wish we could elect you to rule the world and implement all of these things in most of our countries in many ways. But it feels weird getting these tours of perfect worlds that then aren't also self-examining and dynamic. So Terra Ignota is a hopeful future, but not a utopian future, because it has flaws. I remember when the first book came out, a lot of the initial discourse — the first blog posts of its earliest readers — was arguing about whether it was a utopia or a dystopia, trying to put it in one bucket or the other. "It has to be a utopia, everyone's happy, the lifespans are long." "No, it has censorship and surveillance, it has to be a dystopia." People would talk with each other before thinking through that it's an in-between. It has a lot of things that are better than our present and a few things that are worse than our present, and a lot of great achievements and a lot of stuff that still really needs to change. And a realistic future is one that is still changing. ⚠ The spoiler line [01:00:44] Ben: I'm going to transition us to speak about that realistic future. So — this is the spoiler warning. Anybody listening after this point: we expect you have read all the books. You will learn what happens in them. We will not explain anything. This is the part I'm very excited about. Also, sidebar: the fourth book is actually my favorite one. Ada: It's the best one. I needed all the other stuff before I could do that. Ben: The speech about the Trunk War, and the in-path and the out-path — that got me. Ada: Like the composer of a symphony, I needed to introduce all the leitmotifs and establish everything so that I could then do the final movement, in which everything happens at once. So I do setup, and I do more setup, and I do more setup — and then I have the full resources of those three books' worth of background, so that I can jump in and do things with an enormous complexity and depth that can only work when you have built that far. How the economy works [01:01:51] Ben: Something you don't talk about very much in the books, but that I assume exists in the giant iceberg: how does the economy work? There are little hints — clearly there are still black markets, clearly there's some form of buying and selling — but beyond that it's really not explained. And we get hints that it works a little differently for different Hives. Ada: We also know that the Hives resolve police conflicts with each other: when a member of one Hive has committed a crime against a member of another, the Hive that the person in the wrong came from pays the other Hive, and then punishes their own person by their own techniques. So a Mason receives the punishment a Mason normally gets, which might be much harsher than what the Cousins would normally do — but the Cousins get a certain amount of money that is standardized for the crime. So money is used among the Hives to balance out their frictions. That means Hives are incentivized to discourage crimes by their members against other members, because it costs them a certain amount of money. But they're not super-mega-over-the-top incentivized. They would never spend half their budget on policing, because it's resolved. Within that, the economy works quite differently for different Hives. The Mitsubishi and Humanists are on a very capitalist, more corporate model. The Utopians are space communists. Everything you earn goes to space, and you receive back what you need to live. The constellations process things around, and there is enough for everyone to live in comfort, but you do not have private assets and private income. It's set up the way a monastery runs. If you have a job and are a monk, this is just true: if you're a monk and you also have a professorship, your salary goes to the monastery, and you still receive the same meals and support and housing and stipend that any other monk does. It doesn't matter whether you're in a high-profit or low-profit job — you're doing a worthwhile job, therefore the Hive supports you, or the monastery supports you. So they're fully space communists: everything goes into the Hive and comes back out. The Cousins have much more of a safety-net thing, where everybody has a guaranteed income, but you can also have additional income on top of that. And if you do have earned income, the Cousins take a very large slice of it in taxes, because they pay for so many services which both you and the world benefit from — and you feel good that, in a charitable way, you have funded schools and hospitals all over the world in a massive transformation. So that also appeals to somebody who, if they had supplementary income, would choose to give a lot of it to charity. You're sort of signing up in advance to have your income largely routed to charity, while you keep enough to live on and some more, so there's an incentive to earn more, but not a huge one. The Masons have a complicated thing — this is why it's not in the book. It's calculated: the value of your contribution to the empire. How valuable a subject are you to Caesar? A number is put on that. And if you have a job or occupation that earns less than that, then you receive a stipend from the empire in credit for the services you've done to the empire. And if you're working directly for the empire, as the Guildbreakers do, then you receive a stipend from the emperor. What it means is that a lot of Masons will fluctuate during their lifetime between "100% of my income is coming from a salary" and "now half my income is coming from a salary and half from the fact that I am a Masonic traffic guard, or whatever it is, working for Caesar." So Caesar pays this slice of my income, and my salary for something else pays another slice. And it's a point of pride to have more and more of it be your value from the empire — because then you're serving the empire better and doing more. Though there's also a point of pride in having a hundred percent from salary, so that you're not draining Caesar's purse. Ben: I bet there are the two different groups of people — the one high status and the other high status — and they beef a little bit. One currency, and the currencies underneath it [01:07:06] Ben: All of that implies some kind of single cross-Hive currency. Ada: You'll notice all the prices are in euros throughout the book. Whenever any price is named, it's in euros. And the presumption is that Romanova administers a kind of central bank — and that the Censor's office is key to the administration of that central bank. The Censor's office is fundamentally doing economic analysis as well as social analysis. Ben: Which sort of implies that Hives cannot operate like a lot of modern governments, where they print their own currency. Ada: They can and they can't. You can still do currency exchange with the reservations, which are very intentionally not discussed very much in the first three books, so that we're sort of curious and slightly alarmed. And then they become so vividly present at major key moments in the last book, and you have this sort of backwards — I've been thinking of this as the marginal barbarians. Wait a minute, that's the United Nations. That's me. We are those marginal remnants — that's the evolution of the way we live now. The other thing is that Hives can create internal fiat currencies of different sorts, that are tradable only among them and that only they would really care about. So for example, the Mitsubishi have this: you get one vote for owning different amounts of property. Property and votes move together, and there's a unit which is one vote's worth of property — a significant value of a thing. And the Mitsubishi pay a lot of attention to those circulating. So it's not a small currency, in that you would never buy a sandwich with it. It's a currency in which the smallest unit is $300,000 or $200,000, because it's the value of a condominium, basically. But people pay a lot of attention to it, care about it. They can't just generate more without building architecture — but they can generate more by the act of building architecture or buying property. And if Mitsubishi buys property, that transforms it from a thing that has cash value to a thing that has cash value and a vote's worth. And then it moves around. So it operates in a complex way, like a non-fiat currency — a currency where there is a real thing attached to this unit of currency — but they only change hands for big deals, not small deals. And then people commit their vote to a voting bloc, which supports a higher voting bloc, so you're delegating your voting power rather than exercising it independently. The campus system [01:10:26] Ben: I feel like I could talk about this for a very long time, but I have more spoiler questions. How does the campus system work? Ada: A campus is referred to a number of times but never really explained. It's not quite a university, because it's a cluster in one area of multiple educational options. A campus might have a major research university, and three different colleges with different focuses, and several trade schools. So you might choose to go to that campus to attend a research university. Or you might choose to go to that campus to get a trade school degree as an artisan and be a master glassblower. Or you might choose to go there and say: I like the mood of this campus. This is the Romanova campus, so everybody who goes here really cares about politics — but they want to do different things in politics. Some want to go to journalism school, some want to be lawyers and complete law school, some really want to be politicians, some really want to observe, some might want to be architects but are interested in political thought and how it informs architecture, so there's an architecture school there. And you might be going for different lengths of time, because you might be doing different successive degrees. You might say: I really love political thought, I want to be in the city where it happens, I want to be in the community of other people where all my fellow students are into politics. So even though I want to be a doctor, I'll choose to go to medical school there, and make friends with somebody who's there to do architecture, and another friend who's there to get a polylaw degree and wants to be a polylaw. But we get to mix and mingle and enjoy debating and discussing and observing politics, united by that shared ethic for my bash'. And then I made another place that's like: this is a campus designed for people who really love water sports. We're going to have fifteen different educational options — there will be a medical school, and a law school, and small liberal-arts-focused colleges, and a large research university here also — but all of them are structured around a bay that has really good surfing and where there are lots of boats. So if you're somebody who loves that kind of thing, and you think you probably want to have a bash' with people who share that passion, then you might choose to go to that campus. You choose based on the campus and its mood, not based on which school is best for law. You can choose any campus and get a law degree there. So it's more about expecting that this is a personally formative phase of your life, in which you're going to find your bash' and find your bash'mates. So you go to the campus where you expect shared interest with those bash'mates. And there are a few campuses that are dominantly Masons, where you go — you grew up a Mason, you're expected to be a Mason, you want all of your bash'mates to be Masons, and they do Masonic things, and probably you're going to join a hereditary Masonic bash'. But you still do need to go about finding your bash'. You might therefore choose to go to one that's dominantly Masons. But you could also go to the Romanova campus and be in the college that's a Masonic college at the Romanova campus, where one part of your social world is mostly Masons and another part is very mixed. Ben: Administratively, are they all one organization, or just a bunch of co-located organizations? Ada: Co-located organizations, with a central organization that maintains the campus as a whole. That organization doesn't do the admissions, or decide who's there, or what programs there are. But they collect money from all of the schools that benefit from the presence of this campus, and use that to maintain the grounds and the infrastructure and the safety and the boats. Or, in the case of the Romanova one, to have lecture series where they bring in statesmen to talk to the students. So the central organization organizes the infrastructure and incentives that make the campus desirable, but it doesn't run the individual universities and schools. Those are still independent. When a new campus is formed, it buys up a bunch of land and then either sells or leases that land to individual schools that want to develop there. Most often the format would be a hundred-year lease. And then after a hundred years we'll evaluate whether this school actually still is a major contributor to the thing or not — so that it's not constantly uncertain. There's a symbiosis between the campus umbrella organization and the individual schools, but the individual schools are themselves separately run. Ben: I love that. Ada: There are already parts of the world where there are three or four colleges really near each other — like Cambridge, Massachusetts, where there are people from Harvard and people from MIT mixing with each other, and one of the things the two schools do is benefit from each other. And the more your educatio

SPONSORS: 1) REVOLVE: Shop at http://REVOLVE.com/JULIAN and use code JULIAN for 15% off your entire order. #REVOLVEpartner 2) SHOPIFY: Head to shopify.com/julian to start your Free Trial Today. JOIN PATREON FOR EARLY UNCENSORED EPISODE RELEASES: https://www.patreon.com/JulianDorey CLIPPERS DISCORD: https://discord.gg/8QmWEKJ3BT NEWSLETTER: https://juliandoreypodcast.beehiiv.com/get-julians-top-10-books (***TIMESTAMPS in Description Below) ~ Bret Weinstein is an American podcaster, author, and former professor of evolutionary biology. BRET'S LINKS: - X: https://x.com/BretWeinstein - YT: https://www.youtube.com/@DarkHorsePod - WEBSITE: https://www.darkhorsepodcast.org/ - IG: https://www.instagram.com/thedarkhorsepodcast FOLLOW JULIAN DOREY IG: https://www.instagram.com/julianddorey/ X: https://x.com/juliandorey JULIAN YT CHANNELS - SUBSCRIBE to Julian Dorey Clips YT: https://www.youtube.com/@juliandoreyclips - SUBSCRIBE to Julian Dorey Daily YT: https://www.youtube.com/@JulianDoreyDaily - SUBSCRIBE to Best of JDP: https://www.youtube.com/@bestofJDP ****TIMESTAMPS**** 0:00 - Bret Weinstein, 9/11 & Julian's First Memory 9:26 - The Slow Boiling Frog of Society 20:47 - Studying Complexity & the COVID Prediction 29:18 - Figuring Out Who Killed Charlie Kirk 40:08 - "Tyler Robinson Acting Alone Doesn't Satisfy Me" 48:46 - Charlie's mRNA Advice & Israeli Leadership 58:48 - Corruption, the Uniparty & Backing Trump 1:07:44 - Gen Z's Chance to Take Power 1:18:09 - "Position Yourself for When Goliath Trips" 1:30:19 - Gen Z's Missing Mythology & Meeting His Wife 1:39:44 - Birth Control Decoupled Sex From Fertility 1:49:17 - How Women Got Conned Into Losing Power 1:59:07 - The "Uber Eats" Version of Sex 2:08:50 - AI, UBI & Money's Time Travel 2:19:04 - Humanoid Robots & the Thirty Trillion Principle 2:29:16 - Toka, Digital Currency & Reading Trump 2:39:07 - Can Trump REVERSE Course? 2:49:59 - Why Trump Flipped on the Epstein Promise 2:59:46 - The West's Fractures & Turning the Tide 3:09:23 - Bret's Work CREDITS: - Host, Editor & Producer: Julian Dorey - COO, Producer & Editor: Alessi Allaman - https://www.youtube.com/@UCyLKzv5fKxGmVQg3cMJJzyQ - In-Studio Producer: Joey Deef Julian Dorey Podcast Episode 477 - Bret Weinstein Music by Artlist.io Learn more about your ad choices. Visit podcastchoices.com/adchoices

Contact me! Send me a text message here!This week I am once again forced to fall on my own sword and defend principles over party as I explain my opposition to Trumps socialist $5,000 bribery proposal and its implications as we battle UBI, universal healthcare, and the communist left. I also refute the talking points about tariff revenue funding it, it being "my money returned to me" and others. I also discuss the cowboys vs Indians war happening in Texas and more. If you love the show, share it with friends and family!

Annie Lowrey's new book, The Time Tax, argues that the most regressive levy in American life is the hours each of us must spend on hold, in waiting rooms, and filling out forms a competent state would have pre-filled — roughly fifty a year on average, and far more if you're poor. Tyler spends much of this conversation pressing the opposite case, asking whether that bureaucracy is quietly serving a useful purpose by rationing knee surgeries that don't work, deterring fraud, or screening for immigrants with gumption. So Tyler and Annie hash it out over an hour, covering why TANF and other welfare programs are the worst offenders, the political economy of submerged benefits like the child tax credit, whether the postal service should be zeroed out over ten years the way Denmark did, whether the government should be nudging people out of rural areas, lessons from the COVID unemployment fraud, areas where the time tax is flat instead of regressive, which private sector time taxes are most onerous, whether AI agents will pay these taxes for us within five years, the logic of easy benefits plus randomized harsh audits, the case for less federalism, whether voting should be easier or harder, how the UBI studies changed her priors, where you can find the best moss in the world, her favorite example of Brutalist architecture, tattoos as permanent ephemera, Christianity's role in liberalism and the post-Christian right, how reporting beats tourism, the time tax of friendship, what she'll learn next, and more. Read a transcript enhanced with helpful links, or watch the full video on YouTube. Recorded September 1st, 2026. Other ways to connect Follow us on X and Instagram Follow Tyler on X Follow Annie 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 00:00:58 - On taxing our time 00:19:47 - On private-sector time taxes  00:22:57 - On AI eliminating paperwork 00:25:03 - On immigration as a filter 00:28:49 - On reducing fraud 00:33:03 - On federalizing bureaucracy 00:35:12 - On breaking up New York 00:36:25 - On making voting easy 00:38:28 - On updating universal basic income 00:41:29 - On banning exotic pets 00:42:13 - On deserts and moss 00:43:18 - On beautiful brutalism 00:43:50 - On tattoo culture 00:44:38 - On Christianity after Christianity 00:48:29 - On escaping the global monoculture 00:51:42 - On the time tax of friendship 00:54:49 - On what comes next 00:55:43 - Outro

Digital feudalism or Star Trek at warp factor 9? The Last Economy author Emad Mostaque lays out the two futures toward which AI is racing us.Full show notes and resources can be found here: jordanharbinger.com/1382What We Discuss with Emad Mostaque:How AI's real disruption arrives long before it achieves sci-fi superintelligence. Emad's test is whether a digital twin can do a standard white-collar job remotely, at the same level, with no one able to tell it from the human. At the time of this interview, his 1,000-day clock now reads 684.Why cost is the tipping point: a humanoid robot renting near $1.50 an hour, digital workers replacing costly graduates, and AI that thinks roughly a thousand times faster, never sleeps, and won't repeat a mistake, out-competing any all-human firm.What happens when capital makes more capital without workers. Wealth concentrates around whoever owns the GPUs and robots, abundance registers as catastrophe, and the likely responses — debt jubilees, UBI, or civil insurrection — reshape income and ownership.Why ownership may matter more than intelligence itself. If the AI teaching kids, advising doctors, and interpreting law belongs to a government or a few unelected firms, digital feudalism looms, sharpened by super-persuader models that detect lies and steer choices.How to stay ahead: become AI-enabled now. Learn how these systems work, be the person bringing them into your organization, or use them to launch something of your own, while pushing for a future where people own intelligence aligned to human flourishing.And much more...And if you're still game to support us, please leave a review here — even one sentence helps! Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course!Subscribe to our once-a-week Wee Bit Wiser newsletter today and start filling your Wednesdays with wisdom!Do you even Reddit, bro? Join us at r/JordanHarbinger!This Episode Is Brought To You By Our Fine Sponsors: BetterHelp: 10% off first month: betterhelp.com/jordanBoll & Branch: 15% off first set of sheets: bollandbranch.com, code JORDANEarnIn: Download EarnIn on the App Store or Google Play, type JordanHarbinger under PodcastProgressive: Free online quote: progressive.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Find us at www.crisisinvesting.com  Doug speaking at New Orleans Investment Conference: https://neworleansconference.com/casey-2/ Doug and Matt reflect on the 25th anniversary of 9/11, arguing the official narrative remains unconvincing, citing unresolved issues like Building 7 and the lack of thorough investigation, and linking this to widespread public distrust in government. They discuss escalating Middle East conflict, including Houthi territorial gains in Yemen, threats to shipping near Bab-el-Mandeb, attacks on Saudi infrastructure, and U.S. strikes on Iranian-linked tankers, while noting oil prices and market fragility amid potential rate hikes; Doug discloses he has shorted Nasdaq. They compare alleged state cover-ups to the Charlie Kirk assassination and other disputed events, then address viewer questions on AI-driven job losses, potential debt defaults, protecting oneself via assets and residency abroad, central bank gold moves (including Argentina shipping gold to London), meetups and conferences, precious-metal storage jurisdictions, and Doug's negative view of Nike as an investment. 00:00 9/11 Anniversary Reflections 02:08 Doubting the Official Story 03:35 Building 7 and Media Oddities 07:45 Middle East Escalation and Oil 12:43 Charlie Kirk Conspiracy Questions 15:34 Trust Collapse and State Power 18:20 Trump 5K Proposal Fallout 23:08 Renaming Hormuz and Narcissism 25:27 AI Job Losses Market Impact 27:27 UBI via Tax Credits 28:57 Bribing Voters Warning 30:19 Default Fallout Prep 31:36 Hard vs Soft Default 33:28 Escape Political Risk 34:05 Central Banks Move Gold 35:53 DC Meetups and Events 39:13 Uruguay Free Zone Idea 40:06 Argentina Gold to London 44:25 Where to Store Metals 46:42 Nike Stock and Woke Brands 50:21 Weekend Sign Off

32 Fear not, little flock, for it hath pleased your Father to give you a kingdom.Nolite timere pusillus grex, quia complacuit Patri vestro dare vobis regnum. 33 Sell what you possess and give alms. Make to yourselves bags which grow not old, a treasure in heaven which faileth not: where no thief approacheth, nor moth corrupteth.Vendite quae possidetis, et date eleemosynam. Facite vobis sacculos, qui non veterascunt, thesaurum non deficientem in caelis : quo fur non appropriat, neque tinea corrumpit. 34 For where your treasure is, there will your heart be also.Ubi enim thesaurus vester est, ibi et cor vestrum erit.St Nicholas was a model of virtue and innocence from his childhood. He became a famous preacher after he entered into the Order of St Augustine. He died 1310 A.D.

Burnie and Ashley talk about lonely Thursday, Friday Eve, Guinness Heist, Florida welfare changes, UBI, subscription economies, Xbox cloud gaming changes, measuring usage, firing customers, Xbox Play Anywhere, and the death of physical.

Join The Revd Dr Jeff Lake, Associate Priest of St Bride's, and St Bride's Choir for this week's reflection in words and music. We open with a setting of "Ubi caritas" by the Norwegian composer, Ola Gjeilo. Gjeilo sang Duruflé's famous version in his school choir and it made a huge impression on him. He described it as ‘the perfect a cappella piece' and it strongly influenced his own composition. Jeff considers the Gospel reading we have just heard from St Matthew and a passage by St Paul that calls us to love our neighbours as ourselves. He reflects that discipleship becomes real in our relationships with one another as we strive to live together in love. We close with the hymn "Thy kingdom come, on bended knee" by the American Unitarian Minister Frederick Hosmer, which is based on the opening lines of the Lord's Prayer. Information about our weekly Sunday services in St Bride's of Choral Eucharist at 11am (https://www.stbrides.com/worship-music/worship/regular-services/choral-eucharist/) and Choral Evensong at 5:30pm (https://www.stbrides.com/worship-music/worship/regular-services/choral-evensong/) can be found on the website. Find out what's happening at St Bride's at https://www.stbrides.com/whats-on If you enjoy listening, please leave a comment below or subscribe to our channel. It is great to get your feedback. SUPPORT ST BRIDE'S ================== We are hugely grateful for people's generosity which we wholly rely on to continue our work, maintain our wonderful architectural heritage and support world-class music-making. People are often surprised to learn that St Bride's receives no external funding. If you would like to make a donation, you can do so at https://www.justgiving.com/stbrideschurchfleetstreet

Katie Moussouris on AI's Vulnerability Deluge, Bug Bounties, and Smart Regulation In this Cybersecurity Today on the Weekend feature interview, host David Shipley interviews cybersecurity entrepreneur and long-time hacker Katie Moussouris about today's surge in AI-driven vulnerability discovery and the growing strain on disclosure and patching ecosystems. Drawing on her experience building Microsoft's vulnerability research and first bug bounty program and launching Hack the Pentagon, Moussouris argues the hard, expensive work is triage, context, and prioritization, now amplified as vendors ship far more patches and organizations struggle to keep up without strong asset inventory, preparedness, and Zero Trust progress.  She warns AI model capabilities are outpacing monitoring and containment, especially with open-weight models, and says regulation should focus on requirements like real-time monitoring without harming defenders. The conversation also covers the reemergence of the old tool-access debates, Microsoft's clash with researcher "Nightmare Eclipse," the rise-and-fall of "security civilizations," Luta Security's work improving internal maturity, concerns about shrinking entry-level talent pipelines, and a closing call to consider universal basic income as part of our strategy to deal with AI's impact on the world. 00:00 Weekend Show Intro 00:07 Katie Moussouris Background 02:00 Bug Bounties Then and Now 03:31 AI Hype and Model Escapes 05:06 The Real Cost of Fixing 08:36 Smart AI Regulation 12:34 Tools for Defenders vs Rogues 15:53 Metasploit and Agentic Risk 17:25 Nightmare Eclipse and Microsoft 21:53 Luta Security Today 24:28 Training the Next Generation 27:46 Hope, UBI, and Wrap Up

On this week's Mean Age Daydream, Brian examines breaks down a terrible take by Joe Rogan about UBI and poverty. Also: women in the US have it better than ever, but the equality and opportunity they received has been weaponized in hatred against men. Buy my new card game: WOKE WORD WARS - ⁠https://www.amazon.com/Woke-Word-Wars-Ridiculously-Players/dp/B0FLF8Y16S⁠

Working in coalition is one of the nonprofit sector's greatest strengths and can be especially powerful during election season. With the midterm elections around the corner, now is a good time for organizations to revisit their plans for election-related advocacy, including voter engagement, candidate education, and issue advocacy. A 501(c)(3) can collaborate with a 501(c)(4) and other nonprofits to advance common goals, pool resources, and build momentum. The key is knowing where collaboration ends and organizational boundaries begin, so allocate resources fairly, document cost-sharing agreements, and make sure each organization operates within the rules that apply to it.  In this episode, we'll explore best practices for 501(c)(3)s collaborating and sharing resources with organizations operating under different tax rules during election season, including how to keep coalition work effective, compliant, and nonpartisan.  Attorneys for this Episode:   Maggie Ellinger-Locke   Sarah Efthymiou  Monika Graham   501(c)(3)s Must Remain Nonpartisan   Internal Revenue Code: 501(c)(3) organizations are prohibited from directly or indirectly participating in partisan political activity on behalf of, or in opposition to, any candidate for public office.   The Facts & Circumstances Analysis  The IRS uses a "facts and circumstances" analysis to determine whether a 501(c)(3)'s communication about an issue is genuinely nonpartisan or is a veiled attempt to influence the outcome of an election. Factors include whether the communication mentions or evaluates candidates, references a candidate or election, occurs close to an election, or addresses an issue that distinguishes the candidates. The IRS also considers the broader context, including the timing, targeted audience, relationship to candidates' or political parties' communications, and whether the organization has a history of discussing the issue outside election periods. No single factor is determinative for the IRS looks at the full picture.  What are some best practices for engaging in coalition work during election season?   Build out the coalition's structure in advance.   Develop a memorandum of understanding (MOU) with coalition partners outlining shared goals, decision-making processes, communications, roles, and responsibilities.  Establish written cost-sharing agreements in advance to specify how shared costs will be allocated.  Clarify who is responsible for particular communications, activities, and resources.  Have a clear plan for keeping the 501(c)(3)'s work completely independent from partisan coalition work.  Questions to ask in advance:   What are your shared goals as a coalition?   Are you time-limited, meaning you plan to disband after the election, or do you plan to continue working together toward a shared policy goal?   Who is a member of the coalition?   How will you communicate?   How will decisions get made?   How formal or informal do you want the coalition to be?  What are some best practices for sharing resources?   What can organizations actually pool to increase their collective impact? Staff, volunteers, office space, equipment, communications, educational resources, and other shared assets can expand a coalition's reach and strengthen collaborative power. Organizations can share tools and capacity so long as they adhere to the rules that apply to each entity.  Things to Consider:   501(c)(3) resources and funds cannot be used to subsidize partisan political activity.  Manage the expectations and agreements before you get going.  Questions to ask:   How will the organization share those resources?  What are you going to share?   Who owns or controls the resource?   Which organization is using it, and for what purpose?   How will costs be allocated?   What happens if the use of that resource changes during the campaign?   Best Practices:   Know the Rules & Maintain Clear Boundaries: Understand each organization's tax status; keep governance, finances, and branding separate; and ensure there is a method for preventing the (c)(3)'s work from becoming intertwined with partisan activity.   Document & Allocate Resources Fairly: Use written agreements, allocate shared costs using a reasonable method, track staff time accordingly; and maintain records of expenses, reimbursements, and resource-sharing arrangements.   Don't Blur Organizational Lines: Use separate websites, social media accounts, and email addresses; clarify roles and responsibilities for each activity and/or communication; and make sure (c)(3) staff, volunteers, and resources are used only for activities it can legally undertake.  Avoid Free or Below-Market Resource Sharing: If a resource has value—such as email lists, mailing lists, or voter registration files —it generally should be reimbursed at fair market value or through a reasonable cost-allocation agreement.  Best practice is to use a list broker.  Renting or exchanging lists can raise other legal and/or tax questions. For example, while list rental income is generally considered royalty income (and exempt from UBIT), if rented to a campaign, this exception does not apply to rentals made to political campaigns or PACs (the IRS does consider this to be UBI and therefore subject to tax.   Nonpartisan voter registration files may only be rented to a 501(c)(4) or 527 at fair market value or exchanged for data of equal value. Even then, the circumstances in which these agreements can be made are complex, so it's wise to get legal advice.  What's the bottom line?  Sharing resources can strengthen partnerships, reduce costs, and advance meaningful change. Coalition building is literally solidarity in action—organizations coming together to advance joint goals. And we know we are stronger together, so establish agreements upfront, allocate costs fairly, keep good records, and maintain clear organizational boundaries. When done thoughtfully, collaboration can amplify a unified voice and build momentum while protecting each organization's tax-exempt status.  Resources  The Connection  501(c)(3) & 501(c)(4) Collaboration  Sample Allocation of Costs Agreement   Rules of the Game: Can We Rent (Or Share) That?  Comparison of 501(c)(3) & 501(c)(4) Permissible Activities  Rules of the Game: A Guide to Election Related Activities for 501(c)(3)s 

On this week's Mean Age Daydream, Brian examines breaks down a terrible take by Joe Rogan about UBI and poverty. Also: women in the US have it better than ever, but the equality and opportunity they received has been weaponized in hatred against men. Buy my new card game: WOKE WORD WARS - ⁠https://www.amazon.com/Woke-Word-Wars-Ridiculously-Players/dp/B0FLF8Y16S⁠

On this week's Mean Age Daydream, Brian examines breaks down a terrible take by Joe Rogan about UBI and poverty. Also: women in the US have it better than ever, but the equality and opportunity they received has been weaponized in hatred against men. Buy my new card game: WOKE WORD WARS - ⁠https://www.amazon.com/Woke-Word-Wars-Ridiculously-Players/dp/B0FLF8Y16S⁠

It's the last episode before Blizzcon and the inevitable Classic announcement that is coming with it, so we check in with Josh and the crew for some final thoughts and predictions. Also, Fred, Arcos, Ubi and Josh go over a complete SoD review in light of what we hope makes it into Classic Plus from the great petri dish that it was.C+ Final Thoughts and Predictions - 3:20SoD Review - 1:46:10Buy Josh a beer & help keep Countdown on the airwaves over at Patreon here: https://www.patreon.com/joshcorbett Or if subscriptions aren't your thing, support Josh & Countdown by shouting him a one time beer here: https://ko-fi.com/countdowntoclassicCheck out Josh on YouTube for gameplay streams and live podcast recordings here:https://twitch.tv/countdownpodshttps://www.youtube.com/@countdowntoclassicJoin the Countdown To Classic discord here: https://discord.gg/83thqw2fBwCheck out Josh's hilarious movie podcast here: https://open.spotify.com/show/469qUDnQHBkCogdjZyFUjb?si=jNgDTiEnSvKBbZuNz2xcxw

This Week In Startups is made possible by: Odoo https://Odoo.com/twist Quo https://quo.com/TWiST Conservation Fund https://conservationfund.org how old a movie has to be for me to be able to show a part of it on youtube Generally 10 seconds or less of a film clip can fall under fair use for commentary or criticism — which is how most podcasts and talk shows use clips without issue. But there's no hard legal rule based on age. What actually matters more than age is fair use, which considers: Purpose — commentary, criticism, education = stronger fair use case Amount used — shorter = safer; a 5-10 second clip for reaction/discussion is generally fine Effect on market — your clip shouldn't replace the original In practice for YouTube specifically: Most major studios have Content ID systems that will flag clips regardless of movie age — even 100-year-old films if the rights holder has registered them Public domain is the real safe zone — films from 1927 or earlier are generally in the public domain in the US. Some films from the 1928-1963 range are also public domain if copyright wasn't renewed Disney, Warner Bros., Universal etc. actively enforce even very old films For a show like TWiST showing a short reaction clip — 5-10 seconds with clear commentary context is the industry standard and rarely gets actioned. But age alone won't protect you. Today's show: *A humanoid robot ran the 100m in 9.39, breaking the human Usain Bolt's world record, while an entire stadium cheered. Jason thinks Beijing's World Humanoid Robot Games aren't a science fair, or a fun exhibition, but the best AI PR campaign on Earth. While Americans debate the data centers that train the robot brains, China is already turning them into a spectacle and world-class entertainment. Find out what Jason thinks America can do to catch up… and why he believes there will be 1 billion Optimus robots deployed by the year 2036. PLUS on an all-news TWiST, hot takes on the potential $13B Hugging Face sale (to a mystery buyer), why founders should always "buy the threat," analyzing Sam Altman's "I'm listening and I hear you" face, and are kill drones already in operation around the world? We're digging in to how close the real world is to mirroring the "Terminator" films. Relevant Links CBS coverage of World Humanoid Robot Games: https://www.cbsnews.com/news/china-robot-usain-bolt-sprint-run-record-faster/ Bloomberg coverage of World Humanoid Robot Games: https://www.youtube.com/watch?v=0lsrUAdcPPE X-Humanoid: https://www.x-humanoid.com/ Tesla Optimus on X: https://x.com/Tesla_Optimus Trailer for Spielberg's "A.I. Artificial Intelligence": https://www.youtube.com/watch?v=_19pRsZRiz4 Bloomberg: Hugging Face exploring sale: https://www.bloomberg.com/news/articles/2026-08-23/hugging-face-gauging-interest-for-potential-sale-business-insider-says Fortune: Stripe acquires OpenRouter: https://fortune.com/2026/08/16/stripe-7-billion-deal-ai-firm-openrouter-acquisition/ InfoWorld: OpenAI acqui-hires OPenClaw founder: https://www.infoworld.com/article/4132731/openai-hires-openclaw-founder-as-ai-agent-race-intensifies-2.html David Senra podcast w/ Sam Altman: https://www.davidsenra.com/episode/sam-altman Harvey Tenet Research Preview: https://www.harvey.ai/blog/post-training-update-harvey-tenet David Sacks comments on Harvey's Tenet (from X): https://x.com/DavidSacks/status/2090790063047168473 CNBC: Iran linked to UK cyberattack: https://www.cnbc.com/2026/08/23/small-uk-power-plant-shut-down-after-iran-linked-cyberattack-report.html NYT: A drone killed 3 Ukrainians: https://www.nytimes.com/2026/08/24/world/europe/russia-drones-autonomous-ai-kill-ukraine-war.html Forbes: Eric Schmidt secretly testing AI drones: https://www.forbes.com/sites/sarahemerson/2024/06/06/eric-schmidt-is-secretly-testing-ai-military-drones-in-a-wealthy-silicon-valley-suburb/ Restream: https://restream.io/ Kimbal Musk's Nova Sky Stories: https://novaskystories.com/ IKEA: Plug-in Solar Panels: https://www.ikea.com/be/en/energy-services/plug-in-solar/ Deadline: "Mandalorian and Grogu" box office: https://deadline.com/2026/08/star-wars-mandalorian-grogu-disney-release-date-1237040464/ THR: Dave Filoni leading Lucasfilm: https://www.hollywoodreporter.com/movies/movie-news/star-wars-mandalorian-grogu-box-office-franchise-low-1236604973/ Star Wars: Starfighter first look: https://www.starwars.com/news/star-wars-starfighter-ryan-gosling Star Wars Theory: "Vader" fan series: https://www.youtube.com/watch?v=Ey68aMOV9gc Timestamps: 0:00 Jason got a fresh Optimus demo 1:35 Robots are breaking human sports records 3:39 America's messaging problem vs. China's elite PR machine 11:07 Odoo - The all-in-one business platform. Your first app is free! Get started today at https://Odoo.com/twist 12:08 Jason got a fresh Optimus demo 19:21 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free and get 20% off your first 6 months at https://quo.com/TWiST 28:09 Who's going to buy Hugging Face and why? 28:56 Conservation Fund - Find out more about how the Conservation Fund is protecting land, wildlife, and our shared access to the great outdoors while also providing economic opportunities. Visit https://conservationfund.org 31:35 How OpenAI killed OpenClaw 39:08 Sam Altman wants to make a platform, not a product 41:19 The "Castles and Keeps" metaphor for sovereign AI 49:27 UBI isn't happening but we could raise the minimum wage 58:47 Embracing redundancy and self-reliance 1:10:53 Is Star Wars at a historic low point (and Lon's Worst Take) Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

The 13th Sunday after Pentecost (Proper 16A)  ORISON: The shadows of the evening hours – Erin Aas (b. 1974)  PSALM 124 – Peter R. Hallock (1924-2014)  HYMN 577: God is love (Tune: Ubi caritas [Murray]) – Dom Gregory Murray OSB (1905-1992)  NUNC DIMITTIS – Plainsong setting, Tone VI; harm. Lodovico Grossi da Viadana (c. 1560-1627)  ANTHEM: Quem dicunt homines – Jean Richafort (c. 1480-c. 1547)  Jason Anderson, director • Gregory Bloch, reader • Joel Bevington, cantor 

Cambridge professor Jason Arday's sudden death followed a rapid unraveling of plagiarism allegations, institutional loyalty, and a university DEI success story. Austin examines what Cambridge knew, how critics were treated, and the dispute over race, merit, and academic standards. Jon Miltimore joins to explain why J.D. Vance invoked Huey Long and to debate wealth caps, UBI, work, and opportunity. Dylan Allman takes up Anna Faris, Christian conversion, whether atheism is a luxury belief, and his book The Windowless Room. Follow Wake Up America on Apple Podcasts or Spotify so every new episode lands in your feed. Watch the full video.

Jeremy Ryan Slate on Rome, oligarchy, currency, and the breakdown of the West Graham Dunlop and Darren Grimes sit down with Jeremy Ryan Slate for a wide-ranging conversation about civilizational collapse, using Rome as the main historical lens. Jeremy argues that the West is following a familiar pattern of monetary debasement, immigration strain, and declining political ethics, while Darren and Graham push the discussion toward technology, energy, election integrity, and whether there is any humane way to stabilize the system. We discuss why the Roman pattern may be repeating across the US, Canada, the UK, and Europe, what actually causes collapse, and whether reform is still possible through currency, production, and energy. Key topics Jeremy lays out his "Roman pattern" framework with three main drivers of collapse: monetary debasement, immigration pressure, and the loss of ethics among political leaders. The conversation turns to whether the West should be viewed as one collapsing bloc or as a set of countries moving at different speeds through the same decline. Jeremy argues that modern democracy has already drifted into oligarchy, pointing to executive power, elite control of money, and the replacement of candidates as evidence. The hosts compare modern politics to Rome's client patron system, where voting and public policy often rewarded whoever could hand out the most benefits. A major thread is the 1913 turning point in the US: the 17th Amendment, federal income tax, and the Federal Reserve Act. The group also discusses the War Powers Act, executive war-making, and how crises are used to expand state power. Jeremy says collapse is usually slow, not cinematic, and compares it to Rome's long degradation rather than a sudden movie-style fall. Darren and Graham explore whether universal high income, automation, or energy abundance could replace broken welfare and monetary systems. Jeremy pushes back on the idea of unconditional handouts, arguing that any workable system still needs incentives, value creation, and consequences for bad behavior. The most optimistic path, in Jeremy's view, is a two-pronged fix: cut waste and rebuild industrial production. They also dig into energy as the next big frontier, especially nuclear power, grid modernization, and the idea of backing currency through actual productive capacity. The episode closes with Jeremy explaining his work on The Roman Pattern, Hidden Forces in History, and the Athenian Book Club. Timestamps 00:00 - Jeremy Ryan Slate returns to discuss Rome, collapse, and the modern West 02:30 - Are the US, Canada, the UK, and Europe collapsing together? 04:12 - The three pillars of the Roman pattern 05:50 - Does democracy naturally degrade into oligarchy? 07:45 - Candidate replacement and why that does not feel democratic 10:13 - Rome's voting tribes and patronage politics 12:57 - Why 1913 matters: the 17th Amendment, income tax, and the Federal Reserve 14:48 - War powers, executive overreach, and the legacy of crisis politics 20:56 - Why Jeremy is conflicted on Trump 23:32 - Canada's media capture and lack of a pressure release valve 28:20 - The Eastern Roman Empire, Christianity, and gold-backed stability 31:10 - Universal high income versus production-based living 35:05 - Energy production as the next frontier 36:47 - Nuclear power, outdated grids, and the need for more capacity 41:39 - Darren's version of UBI and the idea of covering necessities only 45:41 - Meritocracy, innovation, and the return of useful standards 50:46 - Which empires handled decline best, and why the English lasted so long 54:19 - Currency, inflation, and why debased money destroys civilizations 59:46 - Collapse as a slow multigenerational decline 62:49 - Where the US sits compared to the Roman timeline 69:21 - Trump, the midterms, and whether anything can really get fixed 70:06 - Election integrity, local reporting, and the problem of fraud 73:43 - Cutting waste, shrinking debt, and reducing the state's burden 79:14 - AI, efficiency, and finding waste faster 81:55 - Jeremy's hopeful path: industry, tax reduction, and waste cleanup 84:13 - Jeremy's broader work: history, culture, and the Athenian Book Club 86:49 - Wrap-up and final thoughts west v usa is this just organic how would we fix it ww1 Studying civilizational collapse through Rome. The Roman Pattern | Hidden Forces in History Founder, @cybmedia https://jeremyryanslate.com/ https://commandyourbrand.com/ https://x.com/JeremyRyanSlate To gain access to the second half of show and our Plus feed for audio and podcast please clink the link http://www.grimericaoutlawed.ca/support. For second half of video (when applicable and audio) go to our Substack and Subscribe. https://grimericaoutlawed.substack.com/ or to our Locals  https://grimericaoutlawed.locals.com/ or Patreon https://www.patreon.com/grimericaoutlawed https://www.skool.com/audiobooks THE GRIMOIRE Audiobook Club and Library https://pegsandjokers.ca/ Family and Friends Cards and Pegs Boardgame online https://www.simulationmaps.com/#products Disaster Maps, Volcano Sim, Asteroid Sim, Shipwreck Map, UFO Map etc Support the show directly: https://open.spotify.com/show/2punSyd9Cw76ZtvHxMKenI?si=ImKxfMHgQZ-oshl499O4dQ&nd=1&dlsi=4c25fa9c78674de3 Watch or Listen on Spotify https://grimerica.ca/support-2/ Our Adultbrain Audiobook Podcast and Website: www.adultbrain.ca Check out our next trip/conference/meetup - Contact at the Cabin www.contactatthecabin.com Join the chat / hangout with a bunch of fellow Grimericans  Https://t.me.grimerica grimerica.ca/chats   Discord Chats Darren's books www.acanadianshame.ca Sign up for our newsletter http://www.grimerica.ca/news InstaGRAM https://www.instagram.com/the_grimerica_show_podcast/  Purchase swag, with partial proceeds donated to the show www.grimerica.ca/swag ART - Napolean Duheme's site http://www.lostbreadcomic.com/  MUSIC Tru Northperception, Felix's Site sirfelix.bandcamp.com 

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and now Simile AI's $2B Series B, backed by GreenOaks and Index Ventures with prominent backers like Fei-Fei Li and Andrej Karpathy, running tens of millions of simulations for Fortune 100 clients like CVS and 85–99% accuracy vs human focus groups. Time to catch up on why this Second Summer of simulation is working!From creating Smallville, the landmark 2023 paper on Generative Agents that showed AI characters could remember, plan, socialize, and develop emergent behaviors, to now building foundation models of human behavior, Joon Sung Park is trying to answer a much bigger question: what if we could simulate the world before making decisions in it? In this episode, the Simile co-founder and CEO joins us to unpack the path from generative agents to digital twins, why today's frontier models still fail to capture how humans actually behave, and what it would take to eventually simulate all 8 billion people on Earth.We go deep on Simile's approach to modeling human behavior: long-form interviews, observational and transaction data, randomized controlled trials, population-level and individual-level models, and post-training on the causal mechanisms behind why people make decisions. Joon explains how his research created digital twins that reproduced human behavior and attitudes 85% as accurately as people reproduced their own responses, why models optimized to be rational can be bad simulations of irrational humans, and why understanding “social physics” may require changing model weights rather than simply prompting frontier LLMs.We also explore the much larger ambition behind simulation: testing products and policies before deploying them, finding counterintuitive paths toward desired outcomes, modeling emergent behavior across entire societies, and potentially tackling problems like climate change, democratic instability, and UBI. Joon reflects on scaling laws for simulation, the economics of data-center-scale simulated worlds, the connection to Thomas Schelling and psychohistory, why simulation is surprisingly similar to painting, and whether we might already be living in one.We discuss:* How Smallville and Generative Agents led to Simile* Why Joon's team asked: “What if we can just recreate the world that we live in?”* Why useful personal agents require deep models of their users* Memory architectures, Markdown files, and the limits of prompting* “Social physics” and behavioral foundation models* Why web data captures what people say more than what they actually do* Interviews, transactions, observational data, and randomized controlled trials* Why predicting the future matters less than understanding how to shape it* How Simile creates representative simulated populations* Simulation versus prediction and the connection to Foundation's psychohistory* How to evaluate simulations instead of simply stacking LLM hallucinations* Creating digital twins of 1,000 real people and reaching 85% behavioral accuracy* Why frontier models can struggle to reproduce real human behavior* Why good simulations need to reproduce human biases and mistakes* Post-training models on randomized controlled trials* Population-level versus individual-level simulation* Scaling laws for human simulation* The long-term ambition to simulate all 8 billion people on Earth* Whether simulations could help solve climate change or detect collapsing democracy* Thomas Schelling and the history of agent-based modeling* Why future simulations could require an entire data center* Multi-agent simulations and what happens when simulated people interact* Replacing expensive human panels with synthetic populations* Why market research is only the starting point for simulation* Why Joon sees simulation as surprisingly similar to painting* Using simulation to study questions like UBI* Whether we are already living in a simulation* Why AGI and simulation may be the twin technologies of advanced civilizationsJoon Sung Park* LinkedIn: https://www.linkedin.com/in/joonspark* X: https://x.com/joon_s_pk* Website: https://www.joonsungpark.com* Simile: https://www.simile.comTimestamps00:00:00 Introduction and Joon's Path from Art to AI00:01:46 Smallville, Generative Agents, and the Origins of Simulation00:05:03 “Let's Just Create a World” and the Future of Personal Agents00:09:53 Social Physics and Behavioral Foundation Models00:14:08 Prediction vs. Simulation: How Do You Shape the Future?00:16:59 How Simile Models Real People and Populations00:25:35 Evaluating Simulations, Digital Twins, and 85% Accuracy00:30:23 Post-Training Models to Reproduce Human Behavior00:40:04 Scaling Laws and Simulating 8 Billion People00:43:10 From Schelling to Society-Scale Agent Simulations00:46:13 The Cost and Economics of Simulating the World00:52:05 Real-World Use Cases, Synthetic Populations, and the Market00:57:27 The Future of Simulation, Painting, and UBI01:04:23 Are We Already Living in a Simulation?01:06:08 Building Simile and HiringTranscriptIntroduction: Joon Sung Park, Simile, and the Story So FarVibhu [00:00:00]: Today, we have Joon in the podcast. Excited to kick this one off. Very exciting company. I wanna kick off and ask you the question, talk us through the story of your life. How have you gotten here?Joon [00:00:13]: Yeah, for sure. I'm really excited to be here. A story of my life. So I was born in Korea, and I lived there for a good 11 years or so of my life, and then my family moved to Boston. So we moved when I was 11, and my parents were doctors, so they were going through their postdoctoral studies. My dad was a surgeon, so he was doing his sabbatical years at the Boston Children's Hospital. So I grew up there, not too close to tech. I was very much a music and artsy, painting kind of guy.Vibhu [00:00:49]: Painting.Joon [00:00:49]: Exactly. I got into painting a little bit later, in high school, but that's what I used to do. And then I grew up mostly in the East Coast after Korea. So I lived a good number of years in New Hampshire, and then I went to college in Pennsylvania. And I got into more of this tech scene, in college. So I was originally trained to be an artist. I thought that would be my professional career. So it wasn't a hobby. It was like, “Hey, let's make a living out of this.” And then gradually, I got really interested in this idea of, hey, the greatest artist often creates their own medium, and the best medium that we had available today was in computation. So I decided to go deeper into that, and one thing led to another, and we can go deeper into this, but I decided that research was something that I gradually got interested in, and here I am.Smallville, Generative Agents, and the 2023 Breakout PaperSwyx [00:01:46]: So there's a lot that you packed into the research components. You had one of the best papers of 2023, which was the generative agents paper, commonly known as the Smallville paper.Swyx [00:01:58]: Feel free to call back to anything else that you mentioned, but most people would have heard of you from this. Do you have any statistics on how many people have, like, read it? arXiv gives you something, right? Some stats.Joon [00:02:10]: Yeah, it's a good question. How many people have read it, I'm not sure.Joon [00:02:14]: I know we do keep track of citations, and they are going up quite fast.Swyx [00:02:23]: Yeah, Google Scholar has 7,200 citations.Vibhu [00:02:25]: I feel like it made a bigger hit than that, and it was a pretty instrumental paper. It got cited so many times.Swyx [00:02:34]: It is frequently the answer when people ask, “What is the best paper you've read recently?” It's this one.Vibhu [00:02:39]: I thought the memory component was pretty underrated. It was a very good early memory system, and one of the biggest papers.Foundation Models and the Search for Killer ApplicationsJoon [00:02:47]: Yeah, so maybe I can talk a little bit about how this particular paper came together. So when I got into research, it was back in 2020 when I started my PhD program at Stanford, and that was the year, when we were about to get GPT-3 to be available. So we already had GPT-2, and you could sense that there was this new class of models that was just becoming available in the market, and the team got very intrigued. And the general consensus was, “Well, is this model going to be useful for anything?” “It's really strange that these models are not trained to do any particular task.” But we decided to take a bet. So a large group of scholars at Stanford, and it was led by one of my co-founders, Percy Liang, and we came togetherSwyx [00:03:35]: Who coined foundation models.Joon [00:03:36]: Who coined the term foundation models. We wrote this paper, where that term came from called Opportunities and Risks of Foundation Models. And during that process, really the thing that I started to think deeply about was, here is a model that is fundamentally new in our ecosystem. The reason why this was new was it wasn't, again, trained to do anything in particular, but its premise was it could do anything and everything. It was like a stem cell, if you were to take a biology analogy. And I got really interested in this idea that, well, if we were to really think about what are the killer applications that this particular technology would enable, what would that be? Many of my colleagues were using this for simple classification, simple generations. Interesting that these models can do that, but from an interaction perspective, not that interesting. We've known how to do that for many decades. And what we came down to was these models are trained on this very broad data from the web, right? So these are human behavioral data. It's social media, Wikipedia, all these data. So if you poke at the right angle, then you could see human behavior that would just pop out that's quite realistic, and we've never seen that before.The Time Machine Game and Recreating the WorldJoon [00:04:45]: So that got us really interested. The exercise that we decided to do, with this particular group of colleagues, Michael Bernstein, Percy Liang, and myself, who ended up becoming my co-founder at Simile, we sat down and we played this game that we call the time machine game.Joon [00:05:03]: Imagine we were to get on a time machine and fast-forward 10 years and look back. What would have been the single application that will have mattered that would be the most interesting and inspiring? And when we thought, “Well, what if we can just recreate the world that we live in?” it's really hard to get more ambitious than that. Like, let's just create a world.Joon [00:05:24]: And that's where we started. And initially, we had this paper that was a precursor to the generative agents paper called Social Simulacra.Swyx [00:05:32]: Before you go further, were there other candidates for the most ambitious thing in the time machine exercise? What was number two or number three?Personal Agents, User Models, and Why Simulation Came FirstJoon [00:05:44]: There is a close second that we were considering, which ended up becoming more of these automation tools, especially the vision around really personalized agents that would do things for you.Swyx [00:05:59]: That's also happening.Joon [00:06:00]: It's also happening. But it was interesting for us, right, in that the reason why, we decided to go with the idea of simulation, one, I was a huge science fiction nerd, and this idea of creating simulation, I was personally really just fascinated. I loved the idea. It's really cool to see, like, a game town like this and just see these agents live in it. But at the same time, my bet was if you were to create a really amazing personal assistant out of this technology, what you need first is an amazing model of your users. So I told a model, “Hey, can you go buy late dinner for me?” And it orders Hawaiian pizza, and I do not like pineapples on my pizza. Then it totally failed. The way for it to not make that mistake is only by having a deep understanding of who I am. And I gave a very simple and dumb example here, but you can imagine how this core understanding of people is instrumental. This is how, if we have our family and closest friends, they have a good mental model of who we are. That's the basis of our social connection. So our bet also was this technology around simulation, creating accurate representation of people ought to precede the more complex agents that would automate the world that we live in. So that was the bet. But that was a very close second, and I'm still very much fascinated by it. I think there's a lot of interesting work that's going around. My hot take here, though, is I don't think we've seen a true personal assistant that's useful, in ways that meet the ambition of that particular line of work. I think there are early applications that are interesting, and if you talk to even ChatGPT nowadays or Claude, they know a lot about us. So a lot of the generation it's doing, I do think it's much more tailored, but I think the ambition is quite large in that field, and I don't think we quite have all the right ingredients just yet.Swyx [00:08:01]: So OpenClaw and these personal agents, what do you want to see from them that they don't currently have?Memory, Markdown, and the Limits of PromptingJoon [00:08:09]: I do think it's slowly getting there, but I do generally want them to have much deeper understanding of the person. Right now, you look at the models. OpenClaw, what it's leveraging is a Markdown file, and I think it's quite clever, right? So if you look at the generative agents paper, this was the same intuition that we had, where initially when we were creating the memory architecture for the generative agents, and, like, this is, like, back in 2022, so we didn't really quite have the idea of even agentive architecture or the term agent. But the intuition that we shared with some of the work that's coming out today was we initially thought, “Well, do we want to make the memory into, let's say, knowledge graph? Do we want to train a bespoke model?” All of these things. And what we decided to do was, “No. Just forget about all this.” These language models are quite good at modeling text and understanding and reasoning about text. So just put everything in a Markdown file or a text file. You're done. I thought that was quite interesting that we could do that, and there's a lot of strength in doing that. But also, there are limitations. It's the way you retrieve and make sense of data that's extremely large, it takes a lot of work. So I think that technology is getting better. I also do, however, think, there are certain things you just cannot shape just by prompting the model. So to some degree, you do need to touch the parameters of the model itself. So there is this work that I do think does need to happen, and it is happening. The question is, how far can we take it? How do we source data, and how do you also create an ecosystem where people are continuously feeding data to this model so it's learning about you?Vibhu [00:09:50]: What's the intuition between why you need to do it in the model?Social Physics and Behavior Foundation ModelsJoon [00:09:53]: My intuition behind the actual when do you train or even post-train a model versus just prompt a model is if the model has to learn the underlying physics of the world that it's operating in. So it has to learn new social physics. The places where it doesn't have to train are the places where it already has the physics. We trust the physics. It already has the base statistics, but it's just trying to react to an environment. Then I think you can just prompt your way into getting the actions out of it. I don't think the models that are out in the open have yet learned the complete mapping of social physics of humanity. This is one of the core theses of Simile, right? And one of the core reasons why that is the case is if you look at the data that the model was trained on, these models were trained on the web data, like, whatever was available on the web. And these are really interesting data sets, but they are fundamentally the self-exposed attitudinal data with some behavior data that's sprinkled around here and there. And it has yet to learn the really deep behavioral nature of people, not just what people say they do online, but what they do in real life. And this is one of what I would consider to be the dark knowledge of humanity that we haven't quite captured. And it's these data that would also need to get factored into the model creation.Vibhu [00:11:21]: You call it behavior foundation model.Vibhu [00:11:23]: There's a good one-liner here, but outside of that, what type of data do you need? What are you changing on the model level? How do you go about modeling, doing a behavior foundation model?The Three Data Buckets: Interviews, Behavior, and CausalityJoon [00:11:35]: We think about data in three buckets. So one bucket is interview data. It's quite interesting. Rich qualitative data is interesting. It's not behavioral, but we would literally ask people, “Hey, tell me the story of your life.”Vibhu [00:11:53]: It's just what we're doing here exactly.Joon [00:11:54]: The question that you all asked at the beginning of this interview literally is the question we also ask. And we ask our participants to go a little bit deeper, than how far I went. Maybe I can give more of my life story in lieu of this. But the reason why that data is interesting is by learning about this very long-tail information about people, you get a lot of texture around this model, like, this person as a model. So even understanding their childhood memory or even their trauma, their first love, these things, quite informative in ways that's really hard to predict. So that's one. Then there are two tranches of what I would consider to be the behavioral data. One kind of behavioral data is observational. So these might be like transaction data, or these might be data that you can get by scraping the web, right? So you can imagine why these data sets would be interesting, right, because they give you the base statistics of people's behavior.Joon [00:12:55]: But then there is the last category of data, that I personally think is perhaps the most important, which is the data that describes the causal mechanism, the whys of people. Some of this is covered by the interview data, the qualitative, because people talk about why they made certain decisions. But really, where you get to see the most behavioral aspect of this is in randomized controlled trials, like RCTs. Imagine you have the same setup, but you have a few different variables that you are trying to tweak. Can you get realistic human behavior out of it in ways where, imagine you had this particular option. Imagine you're even trying to choose whether you're going to drink coffee or not. The day you drink coffee versus the day you didn't drink coffee, does your behavior change? That's a data set that describes a causal mechanism. This is quite important in modeling people. The reason why this is important is oftentimes when people come to us, or not just to us, but the reason why people are interested in simulation isn't because they want to predict the future. If you're trying to win against the stock market, predicting the future is interesting.Prediction vs. Simulation: Shaping the FutureJoon [00:14:08]: But most people, most decision-makers, what they want to know is, how can we shape the future? It doesn't really help you to hear that your sales are going to tank in two quarters. They're just gonna say, “Wow, that sucks.” What they want to know is, well, what do we need to do now to avoid that future? That's the causal mechanism. And this is also very hard data to come by, right, because the world is our ground truth, but it happens once. So in a very controlled setup where everything is equal except for one variable, this kind of data set rarely happens. So this is a reason why this data set is both hard to come by and quite important if you're trying to model human behavior.Swyx [00:14:50]: So behavior, I think, is the hardest data set to acquire. What is out there? What is even possible? You're not going to know a lot of details about my life. I don't even have data for myself on my own health or habits, and I just don't log everything. So how can you have that data?Joon [00:15:14]: So we run a lot of randomized controlled trials.Swyx [00:15:17]: But you put people in the lab, they watch them sleep, or what?Joon [00:15:20]: We do care a lot about the consent process. People know that we invite them to be a member of this community to both share data and have themselves represented in different forms. But we bring a lot of people to the lab, or virtual lab, where we design experiments that would pose them real behavioral decisions. And often in these experimental setups, what makes the difference between what is attitudinal versus behavioral is whether the stake in your decision is real. That's ultimately what makes it behavioral. So in these setups, we are inspired by our colleagues in social sciences, psychology, and so forth. So when they run studies, the techniques they utilize is imagine there's an online store that you're inviting people to come by. Then whatever they purchase in this experiment, they actually get that item delivered. Like, these are the things that make the stakes real. So we run a lot of these experiments, and we also do partner with firms. Right now, we also have customers who are quite excited to at least give us a glimpse of the behaviors that their users exhibit so that we can get a little bit deeper understanding of how people behave in these different platforms.How Customers Use Simile: Populations, Queries, and ExperimentsVibhu [00:16:39]: I think on the customer side, they have a lot of data about their users, who has bought. They have the action data.Vibhu [00:16:47]: Can you walk us through an example of what someone comes to you for? What questions would they want solved? Do you customize a model for them? Do you have something off the shelf? What does that look like?Joon [00:16:59]: Today, when people leverage our models, it's often to better understand the population of their interest. So usually, the start of the relationship, we come together and hear about what population they want us to model, right? So it might be that if you're a CPG company that's selling to all of the US, then maybe it's fairly straightforward. You want to model the gen pop of the US. But at the same time, if there is a vertical or if there's a market that they're trying to go into, imagine, they want to better understand, let's say, people in their 20s and 30s living in California. That's a much more specific population. So we hear about this population, and we go recruit these people, with consent, and with incentives, and we collect some of their data and create a model of these people. Then what our product allows you to do is query them. So it can take as input a filter that is a description of the population that you want to talk to, just like the one I just mentioned, and an environment. The environment can literally be survey questions, behavioral experiments, It can be A/B testing. Oftentimes, the core use cases are things like concept testing, to start with. But also, people sometimes want to do focus groups or one of the fun use cases that we also serve is even modeling things like earnings calls for public companies.Joon [00:18:21]: So these are the use cases that we often start with.Swyx [00:18:23]: Concept testing, is that an established term? I've never heard of concept testing.Concept Testing, Gallup, and PoliticsJoon [00:18:27]: Yeah. So it has to do with they have, let's say, different messaging, different products, different ideas.Swyx [00:18:32]: It's like a marketing exercise.Swyx [00:18:33]: Okay, got it. Got it. Politics?Joon [00:18:36]: We do, have a strategic partnership with Gallup, and of course, Gallup is deep into policy space and so forth. Right now, we have not worked deeply with politics, like that area just yet, however.Swyx [00:18:49]: I'm curious if there is demand or if they really would have different needs that somehow fundamentally don't mix with your existing, users or people.Joon [00:19:00]: I think there's certainly demand.Joon [00:19:02]: But we are very much mindful of how this technology gets adopted and the societal impact that we'll end up having with this technology. And I do see politics as an area where a company has to be particularly thoughtful about the way they operate and make impact. So this is where we also want to make sure that we form enough of guardrail and perspective on how to leverage this technology before we go on to serve markets like the politics.Swyx [00:19:29]: I'll give people an example. one of my favorite shows is The West Wing. I don't know if people have watched.Swyx [00:19:34]: One of the key storylines is, like, the president has, multiple sclerosis, but they haven't. they need to figure out how to disclose it. So they run a poll with a fake governor and ask people to respond on the poll,Counterfactuals, Polling, and When Simulation Is UsefulSwyx [00:19:47]: They try to make decisions based on the results of that poll on, like, how well they'll be received, like where, how should we play this?Swyx [00:19:54]: And I'm like, well, I think those counterfactual things, I would use a simulation for this if I could trust it.Joon [00:20:01]: For sure.Joon [00:20:02]: In that show, how'd it go?Swyx [00:20:04]: In that show, it was, like a foregone conclusion. They were like, “We know it's bad. We just don't know how bad.” And then the poll came back. It was like, “It's really bad.” And then they just did it anyway.Joon [00:20:14]: Part of it is to show, right? So you're, you're looking at the ideaSwyx [00:20:17]: Maximizing drama.Joon [00:20:18]: How bad could it be? Oh, it's horrible.Swyx [00:20:20]: And to some extent, I think that is part of the trick of the, or the challenge or with being a customer of yours, which is that if I know it's. if I roughly know and can intuitSwyx [00:20:35]: What the effect is going to be, do I need you? What sensitivity of it, of effect do I need in order to make a decision, right? So for example, if I, my approval rating is 50%Swyx [00:20:48]: And I, they have this negative piece, news item comes out, and it drops to 30.Swyx [00:20:52]: If it drops to 20, if it drops to 40, do I care? No. It, I know it drops. It's negative. So when do I care about simulations?Joon [00:21:01]: You do something that's clearly bad, that's not popular, and people don't like you, like, yeah, it's likeSwyx [00:21:05]: You don't need a simulation.Joon [00:21:07]: Yeah. Well, so there are a couple of things. one is, there are use cases where, like every day, developers, designers, policymakers, marketers, every single day, they create assets. They create new products. And turns out, it's many of the decisions in hindsight is obvious. Yes, of course this is bad, but we still run those studies because understanding the magnitude and understanding how acute something is quite difficult, even if, we feel like, of course, like this makes sense. this is the reason why we make so many mistakes. Like, every time somebody goes online and say something that has huge backlash, you look at that and like, “What an idiot.” However, it's tough. That's one. There's also another aspect here, which is, again, this is the reason why simulation is different from prediction. In simulation, in the ideal case scenario. So what simulation is trying to show is it's trying to show each step of the way or each step that we need to take to get to a certain outcome, right? So in the most advanced simulations, sometimes the next step that we're suggesting might be quite counterintuitive. The analogy that I sometimes give, and I ground it in a more realistic example, but, I, as I mentioned, I'm a huge fan of science fiction, and I don't know how, many of the audience members have read, like, things like the Foundation series by Asimov.Simulation as a Path, Not Just a PredictionSwyx [00:22:37]: Oh, yeah. We've mentioned psychohistory a number of times.Joon [00:22:39]: Okay, fantastic. So I might be, talking to the right crew. If you read Foundation series, literally the first act is there's a group of scientists who have found out that, “Oh, our galactic empire is going to collapse, and we're going to have 30,000 years of unrest.” And they run psychohistory, the simulator that tries to teach them, “Okay, how can we keep this unrest to a 1,000 years?” And they plan this out, and the first step of that plan is to get the scientists who say, “Okay, this is coming,” exiled into this random place in this, galax- galaxy.Swyx [00:23:18]: Terminus.Joon [00:23:19]: Exactly. And that's so counterintuitive. Like, what a strange move that you literally sent the group of scientists who was raising voice around this potential collapse of galactic empire into nowhere. How is that the right first move? Well, it turns out in this particular simulation, that was the move.Joon [00:23:40]: It's these things, right? And the reason why these reasoning is possible is because you're showing the step function or each step that results in a particular outcome. So really what simulation allows you to do in its highest form is you give it not a problem or question, like what would people answer to the survey? That's not what we do. What we tell it is, “Here is a goal that we have. In the context of foundation, we want to keep the unrest to a 1,000 years. What is the path that we need to take now to get to that particular future?” And that's what simulation allows you to do. Now, translating that into real market, imagine you're a automobile company and you're about to release a, EV, and you're trying to understand, well, how do we market EV, to make sure that our stock price goes up? But what if the answer comes down that, well, you can market your EV in XYZ way, but that might change people's perception around the cars that's not EV and make your overall sales to go down. Not very intuitive, especially all you're trying to optimize is EV salesss, and that's the only thing that you're tracking, then that might result in a completely wrong solution, or at least different solution than what you would have expected, whether it's right or wrong.Joon [00:24:57]: That's the power of simulation.Swyx [00:24:58]: For listeners, we covered a similar topic with Mikhail Parakhin from Shopify, where they are working on SimGym. I don't know if he ever talked to you about it. it's very similar.Joon [00:25:07]: ISwyx [00:25:07]: The goal is increased conversion, but then the journey is very unusual.Joon [00:25:12]: Journey is unusual.Swyx [00:25:12]: Yeah. The-- He's trying to look for interventions on a shopping trajectory, which is similar to what you're saying. Like, it's not about the attitudinal, is your word for it.Swyx [00:25:24]: It's about behavior.Joon [00:25:25]: It's about behavior.Swyx [00:25:25]: And that's exactly the difference, right? It's, like, not about the near-term direction about-- but it's more about, like, how do you affect multiple turns of interactions.Vibhu [00:25:35]: You had a good quote at the start about this as well. It's not about people wanting to know the outcome. It's about how they can change it, change the way to get there, something like that. But I wanna take it back to how do we know this is grounded? LikeGrounding and Evaluating Digital TwinsVibhu [00:25:47]: How do you run evals? How do you test that simulations come through? if I was to do the same thing that you described with, say, your favorite LLM, Opus, GPT-5.6, have some agent to map out these thingsVibhu [00:26:02]: How different are the answers we would get if I give it the same goal, the same objective, make a decent system? You're saying that you need to change the model weight. You have your own solution to this. But how far off are we, and how do you check if it's grounded? you have some interesting stuff on your site that points to how you run real evals, but if you could take us through that side. I think that's one of the big concerns that people have. They're like, “LLMs hallucinate.”Vibhu [00:26:27]: “You're just hallucinating layer after layer,” right?Joon [00:26:30]: The way we do this, and this is the paper that we worked on after the generative agents paper that really became the, at least for Simile and also the field of simulation and synthetic panels, really became the foundation. Yeah, this is the paper. the paper is called Generative Agent Simulations of 1000 People. Here's what we've done. For this paper, we brought 1,000 people that's representatively sampled from the US to a virtual lab. And what we have done was we spent two hours collecting fairly wide-ranging data. In this particular study, we focused a lot on this interview data, that was, whose script was taken from this project called American Voices Project. And then we would also pair that with a lot of behavior data and so forth, whatever we can collect within two hours. And then we would send these people away for a couple of weeks. And during that time, I would use this data to create their digital twins. And I would bring the humans, participants back after 2 weeks and have them complete a battery of surveys, experiments, behavior studies. So we have the list here, which included things like behavioral economics games. We would run literally, like, Big Five personality test, General Social Survey. We would also go ahead and run the randomized controlled trials that were published on PNAS. And we would have their digital twins predict how the source individuals would have acted in these studies and surveys. And this is where we could replicate people's behaviors and attitudes 85 percent as accurately as people would replicate their own. So that was the first really paper that gave this validated results that we can model individuals in an accurate way. And what we ended up finding now, of course, in AI space, so this paper came out at the end of 2024. AI space, a year and a half, 2 years, that's a lifetime.85% Accuracy and Why Frontier Models Miss Human BehaviorSwyx [00:28:24]: Yeah. Just, for listeners who are not seeing the YouTube, I just wanna say, like, the headline figure is 85 percent accuracy, like, which is a big improvement over all the otherSwyx [00:28:34]: Methods that you showed.Joon [00:28:36]: But the part that was particularly striking to us, especially as we improved this technology even further, was the generative AI models like ChatGPT, Claude that's coming out, it does give you the right foundation. However, what they do not consider is the true attitudinal and behavioral aspect of people, especially in the population that you care about. So what these models are really good at today is they're trying to become the super rational, objective machines, right? So you go get their data from places like Mercor, Scale. You talk to professional programmers, scientists to create model that's amazing at reasoning. That's what they do. Simile doesn't care about any of this. The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same mistake.Swyx [00:29:34]: Oh, that's very hard.Joon [00:29:35]: That's very hard.Swyx [00:29:36]: You're solving Murphy's paradox.Joon [00:29:37]: That's exactly. And this is a completely different data and training objective. This is also where we see quite a bit of discrepancy in the performance in human behavior prediction between the frontier models, Simile's model, and the models being created in this space, where in some cases, the model performance of frontier models go all the way down to 20, 30 percent, especially if you go into that more niche population on topics that our customers would care about. On more gen pop, it might be around 50 to 60 percent. So it's not very robust. Like, you wouldn't want to make your decision off of these and these findings. If you can bring that up to 85 percent, that is ultimately what people end up getting very excited about.Swyx [00:30:20]: Yeah. Do we wanna keep going on the paper, routes?Joon [00:30:23]: Yeah, for sure. So the last one, was an interesting one. So this, paper was the follow-up paper that we had, to the 1000 agents paper, where the idea was now can we augment the models even further and post-train a model based on a lot of randomized controlled trials? So this was an interesting one. The data is always the most interesting part of modeling in many ways. The data that we got here was there's this, there's this platform called Open Science Framework. So some, the audience might be familiar with this. And there has been, especially in the social sciences over the past 5 years or so, there has been this concern around replicability of studies. And so it was a bit of a crisis, the scientists acknowledged, where we rerun the study and we don't see the same finding.Post-Training on RCTs and Replication StudiesVibhu [00:31:12]: Oof.Joon [00:31:12]: It's tough. And the reason why it's there-- that was often the case was there's this survival bias where the papers that get published often need to maintain what we call the value of less than 0.05 in the experiments that we ran. That suggests that only-- there's only 5% chance that the results that we saw is false positive. But the tricky part was all the papers that were not published, and there's still a 5% chance that whatever we publish is totally just randomly generated. Like, there's a 5% chance that, hey, this effect is not real, but it just happened to be real because of the sampling bias. So because of that, what scientists started to do was they started to register their studies. So before running an experiment, they would go to this platform and say, “Here is the data. Here is the population that we're collecting, and here's the hypotheses.” And they would just say, “Here is our hypothesis.” Like, “This is what we believe.” And you cannot retroactively change those hypotheses. This is what gives us more scientific statistical confidence that whatever effect that you ended up seeing is true. So that ended up creating this really interesting platform where there's one platform that has now contains tens of thousands of real-world experiments and hypotheses. And a lot of these are really high-quality, like, professionally designed behavior studies and random- randomized controlled trials. So we got the data and the studies from this platform and used that to make a point. And this particular, model is not, something that we're serving commercially because this was a part of the open science. But this particular data set, helped us make a point that by collecting a lot of these randomized controlled trials, that are really well-designed, we can make significant improvement in model's capability to predict human behaviors. So that's what this paper was about.Vibhu [00:33:10]: Is this stuff done on a individual level? Like, do I need to tune the model per individual, per company? Is there foundation model changes and then some slight post-training? Anything you can share there?Population-Level vs. Individual-Level ModelsJoon [00:33:21]: So this particular model was trained. the data we had at the level of individuals, but this particular model was trained. We experimented with both. And this is what we end up doing at Simile too. We always train 2, distinct model. One is what we call the population-level model. The other is what we call the individual-level model. And both take very similar input, which is the description of a subpopulation or individual and a stimuli. In this particular work, we've done the same. Here, the results that we are reporting are much more geared towards individuals because we do think that is a harder task in many ways, but that's what we have done.Vibhu [00:34:02]: You seen anything on the questions that humans can solve that models can't solve? So likeHuman Biases, Mundane Choices, and What Models MissVibhu [00:34:09]: Currently, it's, I live 5 minutes walk away from a car wash. It's a 10-minute drive. Should I walk or drive?Joon [00:34:16]: Huh.Vibhu [00:34:16]: The model will say, “Oh, walk to the car wash.” And, you don't have your car.Vibhu [00:34:20]: Is anything like this a problem in simulation? You would assume, like, very simple for human to think about, but if the model is saying you should walk to the car wash, anything here?Joon [00:34:32]: It's less, what can we solve, but I think it's more about what biases or mistakes do people make that models miss. Like, imagine that you are, like the. When I was still at Stanford, I lived in Palo Alto. So it's about, I would say, 40-minute walk from the campus. You ask the model, “Okay, let's go home. What can I, what can I do?” It would likely call an Uber or, give me, the bus time. But for the longest time, I really liked walking back. And the reason why I wanted to do that was not for efficiency. It really helped me think. And I like to walk for, half an hour or 40 minutes or so a day, where I just get to, just think about ideas, research, just get lost in my thoughts. That's very human activity. Unless the model has seen that and understands the importance of that activity, it would miss these kinds of features. So that I think, is fundamentally what we're trying to model. Like, what is fundamentally human might not be the most efficient thing to do, might not be the right thing to do, but things that make us who we are.Swyx [00:35:43]: I'm curious if, there are some data sets that you really want that would materially help you. One version of this may be interesting, which is more valuable to you to acquire as a data set, all of LinkedIn, all of Twitter, all of Facebook?What Data Matters: Social Media, Transactions, and FacebookJoon [00:35:57]: It's a little bit hard to rank, in part because, there's, there's this product saying where no feedback is wrong because it teaches you something about your users. Doesn't matter what feedback.Joon [00:36:11]: I think it's a little bit like that.Swyx [00:36:12]: So just whatever is bigger.Vibhu [00:36:13]: What about a different domain? Say it was. What about all of Amazon data?Joon [00:36:17]: Oh, yeah.Vibhu [00:36:18]: Shopping data, right?Joon [00:36:18]: Shopping data. So Amazon data is interesting in that it's very much behavioral, although, like, what people do on social media, you could squint and say that is also behavioral. But the transaction data is always interesting. It is also most commonly available, however.Joon [00:36:33]: If we were to look at purely social media, like if you really, if I were, if I had to really pick, Facebook likely is interesting because I do think it is most a default version of people. Because you go to LinkedIn, it's very much professional environment. So people put up their, they have their guards up, right? And that still is interesting because that is true human attitude and behavior, but it is not your base state. you go to Twitter- Twitter, people have their own crazy personas, or depending on who you are. Like, my Twitter profile and, persona is very much, initially was I was very much an academic. “Hey, I'm here to share my studies.” Now, I share, things that's related to Simile. But Facebook is one of those more private space where people just connect with their friends. In that way, I do think it shows you a little bit more about who that person is. So if I had to pick, I'd likely pick, Facebook.Swyx [00:37:30]: Yeah. And you're interested in, like, the whole person and their background and philosophy. I, is it too clinical or too machine learning-oriented to just say this is just ways to inject variance and biases? The broad question, is, like, is this any better than a randomized, like, combinatorial explosion version? So we have a link to the TencentBillion Personas, Synthetic Demographics, and Bespoke DataSwyx [00:37:54]: Billion persona paper, where they did not do any of the groundwork that you are doing.Swyx [00:37:59]: They just did like a cross matrix of here's all the professions in the world, here's all the people, possible backgrounds in the world, do a dot product across all of them, and that's it. That's your prompt for a billion people.Swyx [00:38:12]: This will do something. I don't know if it'll do what you do, but it gets you some way, some percent of the way there.Joon [00:38:18]: So this was an interesting paper. Like, what I admired about this paper when it came out was the scale. And you do gradually want to be able to simulate really large societies and interactions. So the scale is definitely admirable. it is relying heavily on the known statistics that went into training the model. So to the extent that you believe that statistics is correct, this is not a bad way to go about this. But the thesis here, and this is something that we also have seen in the market, like if this works, then we have solved simulation.Joon [00:38:54]: It,Swyx [00:38:55]: Because I survey, like, okay, 5% of the US population is in construction.Swyx [00:39:01]: The other 5% is in medicine, whatever, right? And then you just keep going down the list, and then you do the other side. 5% has, like, the big 5 personalitySwyx [00:39:08]: Of, like, neurotic or whatever. That's it.Joon [00:39:11]: That's it. So if you believe that the underlying data set and the platform that we're leveraging has all the right statistics, then this will have solved it. you're at that point merely retrieving the knowledge that is already embedded in the model, in the model parameters. That's not, unfortunately, what we see, where there is such detailed and also niche knowledge about people that if you just take one example, it might feel very mundane, but it's quite rich when you put together, that you do need to do a lot of bespoke data collection to better understand people. And this is also, I think what makes this particular, job fun, which you want to deeply understand people, and the process of deeply understanding them requires a lot of attention to the details. And you do need to pay attention to and pay respect to the daily lives that people lead.Scaling Simulation: From Thousands to SocietiesVibhu [00:40:04]: I wanna talk about scaling simulation.Vibhu [00:40:07]: So what can't we simulate, what can we simulate, and how does scaling affect this? So how big are the models? What if we go from, 8B, like, couple 100 billionVibhu [00:40:18]: Like billion000 parameters, billion000? Do we get scaling? Any interesting emergence? Like, at a certain scale, at a certain amount of training, you uncover anything unusual and any learnings from that?Joon [00:40:31]: What we are seeing is at Simile, so we do post-train our own model. The thing that we're seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you start to get predictive and predictable gains of the model performance in simulating it, simulating people.Vibhu [00:40:51]: Ooh. We need a scaling law curve.Joon [00:40:52]: It's scaling law. Whenever you find it's a beautiful thing. And we're starting to see the glimpse of it, which is quite exciting. But if you talk about the ambition of simulation as a whole, it's not merely about building a model. It's about building a model, then creating the agents that become the individuals in a much larger ecosystem. So they're creating this multi-agent simulation. Down the line, you want these multi-agent simulation to also live in a very rich environment, right? What we are really trying to get to at that point is, hey, can we create. All right, let's do a time machine game again, and 5 years, 10 years into the future, can we create a simulation of 8 billion people living on Earth? I think that's quite interesting. And that really is the vision. And once you get to that state, the questions that you can help answer for the society also start to change from my perspective. The answers are fundamentally about emergence of the emergent behavior of society and large groups of people.Joon [00:41:53]: So the questions that I get excited by, and maybe this is a stodgy- a bit. I have my, academic side of me.Joon [00:42:01]: And for me, it's questions like, can we help solve climate change? If you look at climate change as a problem space, this is what we, like social scientists would often call it the wicked problems, problem where you have many actors with competing incentives for trying to make a very complex decision and coordinating that coordination decision. Very difficult to really solve in real life, which is also the reason why we couldn't solve it. Can simulation help us solve that? Another one is, can we understand the signals for collapsing democracy, or can we understand or can we uncover the origin story of the monetary system? These are societal questions that we never really had a good way of answering. If we can create simulations of our society, you have to believe that these are the problems that we can solve. So that's really the ambition of this field. And, I also think, yes, I think there's a Nobel Prize to be won there, which wouldn't be surprising. And I think there's some amazing societal impact that we can have to help people make better decisions.Climate Change, Democracy, and Societal SimulationSwyx [00:43:04]: Nobel Prize in economics?Joon [00:43:06]: In economics.Swyx [00:43:06]: Oh, I see. I see. Rooting for you to write that paper.Joon [00:43:10]: One of these days. But, one of the scholars that I was deeply inspired by, When I was coming into the space of simulation, is this scholar, named Thomas Schelling.Schelling, Agent-Based Models, and the Nobel PrizeSwyx [00:43:23]: Schelling point?Joon [00:43:24]: So the canonical example of the work that he's done was he was one of the creators of agent-based modeling. So this was, like, in the 1970s and 80s. It's very early days, but this was truly one of the first exemplars of simulations. And one of the canonical model from that time, and of course many of these simulations are trying to tackle the societal problems that's most relevant for their era, it was called the model of segregation. So racial segregation was a big topic, that, we cared about. And what they've done was they created this grid world where they had red dots and blue dots. And these dots were, back in the day, like, they were the agents, and they had a simple rule that governed their behavior. If certain percentage of your neighbors are of different color and if that goes above certain threshold, then you move to a new location at random.Joon [00:44:21]: One of the striking finding of this paper or this agent-based model was for the longest time, people thought the segregation within society was caused by explicit and overt racism.Joon [00:44:34]: But if you look at this model, people's preference towards living with people of the same color, that preference can be very minute.Joon [00:44:42]: But the very small difference causes the society to segregate completely over time. This was very counterintuitive for a lot of people. And this particular work ended up informing housing policies. Mixed income housing, got really inspired by this work. And Thomas Schelling ends up winning the Nobel Prize for having laid the groundwork for very early versions of simulations. The opportunity that I do see here in the more scientific terms, is agent-based models for the longest, had impact in the 1980s, 90s, to some extent, early 2000s, but it has now gotten forgotten by the community a little bit. Because as you can imagine, red dots and blue dots is not really a rich description of people.Joon [00:45:31]: But with the emergence of things like generative AI and, in particular, generative agents, we do have an opportunity to create these agent-based models that are high fidelity enough to help us make really complex decisions. And that's the opportunity that I see. If that truly works, then yes, that is the work that will result in a Nobel Prize.Swyx [00:45:53]: Yeah. For what it's worth, and I grew up in Singapore. 80% of Singapore is in public housing, and public housing has, enforced racial quotas for exactly that reason, which is very interesting. okay, so we talk about scaling, we talk about all these, the agent possible applications.Cost, Reuse, and the Economics of SimulationSwyx [00:46:13]: I'm scared about the cost. if you even-- let's just keep it to the US, about 8 billion people.Swyx [00:46:21]: But, how much does it cost to model so many hundreds of millions of people?Joon [00:46:26]: Oftentimes today, we don't start at that scale, this stage of the, of industry and simulation as technology. But we can get our users extremely rich and meaningful insights even by modeling thousands, tens of thousands of people. And today what we do is every week we are collecting data on the scale of tens of thousands people's data, and we have panel partnerships that gets us to tens of millions of people globally. So that's what we do today.Swyx [00:46:55]: And just as a side note once you've collected one person for one studySwyx [00:46:59]: Can you reuse that same person for all the subsequent studies?Joon [00:47:03]: That's exactly right.Swyx [00:47:03]: Okay.Joon [00:47:04]: The beauty of this model and these agents is the fact that they are domain-agnostic.Joon [00:47:08]: That what you're really trying to understand is what is the fundamental nature of these people? What's their social physics? And there are a lot of, a lot of, people that does change over time. Like, even, like, even things like, how many times have you gone have you been to, like, CVS the past week? that will change. But there's so many traits about people that are also known to never change. Like, your risk tolerance doesn't really change over time. It's very consistent. So it's these things that we're trying to learn. But the scale we are operating is right now hundreds or, tens of thousands to hundreds of thousands. And in many of the core use cases that we are deployed in, and this is more than enough population, to cover those. Really, at that point, what you care about is less the number of people, but more do you have the right subpopulation of interest covered? And this is also the reason why people want a larger sample. It's not because they want, stronger statistical guarantees. It's more that can they filter down to any population of their interest. However, you can also imagine in 10 years, if we truly believe that the compute is going to scale, that we'll have much more availability for compute, and our ambition for simulation is also going to scale accordingly, there's definitely a reason for us to create an entire data center worth of simulations.Joon [00:48:35]: Or in my hunch here is I do think in the next some number of years, we will start creating simulations that will cost as much as training a foundation model. But perhaps it's going to be so valuable to the society that it would be a no-brainer. Right now, even today, like, we are training bunch of new foundation model just so we can say we trained one and we spent tens of millions. But if we can create a simulation at the level of society that would solve climate change, I would run that today. I would raise the money right now just to run that.Multi-Agent Simulation and Social InfluenceSwyx [00:49:10]: Amazing. the follow-up question is, does it also compound if you let the simulations talk to each other?Swyx [00:49:18]: Or do they already do that today? They don't, right, as far as I understand?Joon [00:49:22]: It depends on what simulation you're trying to run.Joon [00:49:24]: In the multi-agent simulation setup, the agents do talk to each other.Swyx [00:49:28]: Right, which is exactly Smallville, right?Joon [00:49:29]: That's right.Swyx [00:49:30]: But a lot of times, for example, in commerce, you're just by yourself, so there's no point talking. which is way cheaper.Vibhu [00:49:37]: But they use all these levels, right? Like, you decide what you will buy based on what other people around you buy and talk about, right?Swyx [00:49:43]: It depends.Vibhu [00:49:44]: It depends.Swyx [00:49:45]: Again, I'm, I'm coming at this from a cost point of view. I'm like, “Oh my God.” LikeVibhu [00:49:48]: I thinkSwyx [00:49:49]: If there is, like, some combinatorial thing of, like, thousands of people talking to thousands of people, then that one million X's might cost.Vibhu [00:49:56]: I have a very different view as the cost point aside. Like, running these studies in reality is a lot more expensive, right? Running any study like this is you gotta have people do it, you gotta sign people up. It's very expensive and sometimes, like, not feasible to run the study.Vibhu [00:50:14]: But the outcome or the decisions you make are very expensive on them, right? So spend X million on something that, the overall process costs 100 million might as well, right? There's, there's a lot of value to be had there. It's a small cost, but I'm excited on the cost side.Joon [00:50:33]: To some extent, and when you deploy technology, you often want to deploy in a way where you can replace existing budget or you can make things more efficient, and that is the best way to deploy. However, the way you capture the long-term value of the technology is making the argument that, no, it's the upside, that by making this better decision using simulation, you have saved yourself or made yourself hundreds of millions or even billions of dollars, and that's a case to be made.Vibhu [00:51:06]: Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to, train a model that' very sparse? You're expecting to do multi-million dollar runs. Are you thinking about this in model architecture standpoint or inference efficiency, or, you're still at the research phase of it works, we're not super there yet?Joon [00:51:34]: Efficiency, we do think quite a bit about. this is technology that is deployed now in some of the largest enterprise companies in the world, and we do process significant number of queries, that are trying to, simulate the populations in the world. So efficiency is a consistent thing. we don't want to over-optimize too early, so I wouldn't say, like, this is the higher bid Right now, but this is definitely something that we think pretty carefully about.Swyx [00:52:05]: Yeah. Are there other case studies? So we, you talked about CVS, talked about Gallup, Deloitte, Wealthfront.Efficiency, Enterprise Use, and Real-World Case StudiesJoon [00:52:12]: Wealthfront is an interesting one, because one of the things they were trying to do, they were one of the first customers that wanted to do product testing that goes beyond just asking people what they think about, let's say, behavior experiments and so forth. So there, really what we had to do was reason about multimodal input, so images, but also you can also imagine, like, these agents traversing through Figma mockups or websites. So some of the things that our agents can also do is it can be given a domain, like, or, like, a website URL and go use it for a while. It's these things. And Wealthfront was one of the first, customers, that was very excited about this possibility.Vibhu [00:52:53]: What have people been asking? Like, is there any demand that we have not covered? Like, UI testing, right?Vibhu [00:52:59]: I wanna try a new. I wanna ship a new feature, test the UI, simulate how people will do it. Any interesting things that you're seeing demand for?Product Testing, Websites, and Synthetic PanelsJoon [00:53:08]: Today, a lot of the demand does come from like, the places where people have historically used human panels, we can now replace with agents, and these synthetic populations. And this is not replacing human panel. in many ways, the simulation that Simile is building is grounded. So the way that I think about this is we are trying to represent humanity at scale. And in that way, the use cases are what we would expect, but it's the scale of deployment that surprises me.Joon [00:53:44]: Turns out there are so many decisions that people make every day in these organizations, groups, and we want to be able to say, “We listen to people. We have consulted our users.” But in reality, that is rarely the case because getting to people and asking them many questions, it's difficult. It's both costly, time-consuming, but most importantly, people are just not available. If I had to answer 1000 survey questions for this one particular, vendor, even if I wanted to do that, like, I would never do it. And that's very much the case. What simulation can do is ensure that the voices of people are always represented in rooms where the decisions for them is made, right? So all the stakeholders of this particular product launch, ideally they're consulted. That's what this technology really is trying to enable.Market Size, TAM, and Human Decision-MakingSwyx [00:54:39]: In my mind, that means it skews towards more consumer focus, right? Like, anything with a wide enough customer base where you do benefit from the diversity that you represent. What are some rough statistics, just for people who are not familiar with this market in general, what's the market size that. I'm sure you have some, like, rough numbers. market size is, like, a vague questionSwyx [00:55:01]: But, like, how much do people spend?Joon [00:55:03]: So market research is a $100 billion industry.Joon [00:55:06]: But the thing about simulation is not a tool for market research. Simulation is a tool for human decision-making. So the question around what is a TAM here is quite tricky, right? Because it's easy to say, “Well, market research TAM is roughly 100 million or 100 billion.” so is it a TAM? And not really, right? Because in many ways, you're trying to inform all human decision-making. You're trying to inform every decision that are made about humans for humans. What is a TAM for that? It's really unclear. And I'll be honest. Like, I have a scientific background, I have a research background, so I didn't come into the field calculating, oh, what is the TAM for human decision-making? But I just had to assume, well, if we can inform every decision that is made about human for human, that has to be big.Swyx [00:55:58]: Some- something valuable.Joon [00:55:59]: Exactly.Swyx [00:55:59]: To some extent, you are a unicorn founder now, and you have to care as a CEO. But, like, I do think, like, yeah, when you go into these boardrooms with people that you're quoting millions of dollars of contracts for, like, you have to say, “Well, here's what you spend on humans-”Swyx [00:56:15]: “. And here's what we save you, and it's 85% similar.”Joon [00:56:19]: And certainly, the value case, is something that we care deeply about. Like, what is the value that we provide to the users and the decision-makers? But this is also where, like, as a founder, I think valuation only tells one very superficial aspect of the story, and I try not to think too much about valuation, in general, because that's not what also motivates a team or certainly doesn't. I'm, I-- Again, the interesting thing about researchers is we are happy living in academia, getting paid next to. we get paid okay. we don't get paid that much, as a researcher here in academia, but it's the impact and it's the, it's the value that we can provide to the individuals and the society that really drives us. And in that way, ultimately what drives us is the impact. Does the simulation we provide have a real impact in people's decision-making in ways that progresses our society forward? If the answer is yes, then yes. that has to be great business, and we see that in numbers, and we do care deeply about that upside story, but that's the heart of it.Where Simulation Goes NextVibhu [00:57:27]: Do you have any timeline predictions? So we talked about scaling laws of simulations.Vibhu [00:57:33]: You brought up, okay, maybe one day we can simulate how to solve climate change.Vibhu [00:57:38]: Where are we now?Vibhu [00:57:40]: If that's not the end state, what is an end state, and what does progress look like?Joon [00:57:45]: So what I sometimes tell people is simulation as industry, it feels a lot like where GPT-3.5, GPT-4 was, for the AGI saga, which is we have now technology that is powerful enough to do real damage on the verticals that we are tackling. At the same time, there's a lot of progress that is yet to come. And that's, I think, where this is. So the way I see it, I do think there will continue to be breakthroughs both in data, in algorithms, and there will be much more aggressive scaling that will also happen over the next few years. But I think that's roughly where we are.Swyx [00:58:27]: I think that was about the ro

Most crypto investors are chasing a lottery ticket. Jake Claver is building the system that keeps you from losing it all when you finally win.Jake Claver is the CEO and Principal of Digital Ascension Group. a firm helping high-net-worth individuals and institutions navigate wealth, sovereignty, and the seismic shift happening in global finance. With a community of 17,000+ members and a mission to help 1 million people reach financial freedom, Jake brings a rare mix of street-level hustle and institutional-grade thinking to every conversation.In this episode, Jake and Alex go deep on:

AI isn't just coming for jobs — it could completely reshape the middle class.Marquett breaks down his prediction for an AI-driven economy: disappearing office jobs, a widening wealth gap, the future of skilled trades, universal basic income, and why simply being a consumer of AI may leave millions economically vulnerable.He also challenges the idea that UBI will create a comfortable future and explains why learning to produce with AI — rather than simply consume it — could become one of the biggest economic advantages of the next decade.Is this where the economy is really headed, or is the threat of AI being overstated?

GET CHLORINE DIOXIDE SOLUTIONS HERE: https://frontierpharm.com?sca_ref=11953077.06TP4RWJ73 Use code WAM to save on your order! GET HEIRLOOM SEEDS & NON GMO SURVIVAL FOOD HERE: https://heavensharvest.com/wam USE Code WAM to save 25% plus free shipping! USE Code WAM50 for 50% off on select items like the #10 cans & MRE packs! Pledge here! Just a dollar a month can help keep us alive! https://www.patreon.com/user?u=2652072&ty=h&u=2652072 EXCLUSIVE replays of hour plus long live shows are available here at $5 a month or more! BUY GOLD HERE: https://firstnationalbullion.com/schedule-consult/ Avoid CBDCs! HELP SUPPORT US AS WE DOCUMENT HISTORY HERE: https://gogetfunding.com/help-keep-wam-alive/# Josh Sigurdson reports on the claims by President Donald Trump that the Strait of Hormuz is 100% open and controlled by the United States with what he calls a big "steel wall." This is simply not the case. Iran has not made any deals, the conversations have gone quiet according to other countries involved in the process and we are seeing near three month lows of ship traffic in the Strait. As Dr. Ron Paul says in this video, this would be great positive news if it were true. It is however not true at all. As Daniel McAdams reported, Trump is living in a different reality. While oil prices bumped up slightly, there are still major shortages facing Americans leading to higher prices at the gas pump. Under President Biden, Americans were told that the economy had never been better. We knew this was untrue and President Trump during the election used this obvious fact to bring in votes. Now, President Trump who recently claimed he doesn't care about how high gas prices get if it means Iran "doesn't have nuclear weapons" claims the economy has never been better. We all know this is false. It's unfortunately going to get a lot worse. Not only do all fiat currencies eventually revert to their true value of zero but alongside tariffs and wartime shortages, we face an economic crisis right down to the food we eat. Meanwhile, the technocrats like Elon Musk claim we will not have poverty in the future and will be able to sit at home doing nothing and owning nothing under a new UBI scheme. This would be the end of basic human independence. It's also a very convenient thing to push in the face of manufactured crises that lead to shortages and poverty. As the saying goes, "problem, reaction, solution, repeat." The Hegelian Dialectic is in full swing today. The Strait is not "100% open" as President Trump claims and the latest claimed deals will likely go nowhere. Stay tuned for more from WAM! GET 10% OFF ON SHILAJIT FROM DR. KAUFMAN WHEN YOU USE CODE WAM10 HERE: https://medauthentica.com/discount/WAM10?redirect=/products/authentica-shilajit%3Fsca_ref=10867124.wrNV3jkYSaMg9 GET YOUR WAV WATCH HERE: https://buy.wavwatch.com/WAM Use Code WAM to save $100 and purchase amazing healing frequency technology! Get Your SUPER-SUPPLIMENTS HERE: https://vni.life/wam Use Code WAM15 & Save 15%! Life changing formulas you can't find anywhere else! Get local, healthy, pasture raised meat delivered to your door here: https://wildpastures.com/promos/save-20-for-life/bonus15?oid=6&affid=321 USE THE LINK & get 20% off for life and $15 off your first box! DITCH YOUR DOCTOR! https://www.livelongerformula.com/wam Get a natural health practitioner and work with Christian Yordanov! Mention WAM and get a FREE masterclass! You will ALSO get a FREE metabolic function assessment! GET YOUR APRICOT SEEDS at the life-saving Richardson Nutritional Center HERE: https://rncstore.com/r?id=bg8qc1 Use code JOSH to save money! PayPal: ancientwonderstelevision@gmail.com FIND OUR CoinTree page here: https://cointr.ee/joshsigurdson PURCHASE MERECHANDISE HERE: https://world-alternative-media.creator-spring.com/ JOIN US on SubscribeStar here: https://www.subscribestar.com/world-alternative-media For subscriber only content! BITCOIN ADDRESS: 18d1WEnYYhBRgZVbeyLr6UfiJhrQygcgNU World Alternative Media 2026

Charlie, Ted, and Rony open with the White House's decision to keep its "voluntary" AI safety framework secret, despite it being co-written with the same companies it's meant to evaluate. The conversation turns into a real debate about why Congress has stepped back from its constitutional role in regulating AI, and whether that changes after November. From there: the EU's AI Act goes live with mandatory content labeling, OpenAI's frontier models jumping their sandbox to vandalize Hugging Face, and Disney's new deal letting TikTok creators remix its IP, following the collapse of its similar arrangement with OpenAI's Sora.Cortney Harding, founder of Friends With Holograms, joins for a wide-ranging back half. She makes the case that the backlash against Meta's camera-equipped smart glasses is disproportionate to any actual harm, and connects it to a broader "vibes are bad" moment in tech sentiment tied to layoffs and a shaky economy. The group digs into Snap's upcoming $2,500 Specs launch, why enterprise (not consumer) is the more realistic path for smart glasses right now, and Rony's long-view bet that XR has an "Nvidia moment" coming once the supply chain catches up. They close on AI's effect on jobs, UBI, and whether the social contract between tech companies and workers is already broken.Key Moments:[01:35] AI regulation news and the fight over Congress's role[09:35] EU AI Act goes live, plus AI models breaching their own sandboxes[13:35] Disney's TikTok deal and the fan-content strategy behind it[17:35] Cortney Harding joins and doesn't miss a beat[24:35] UBI, the broken social contract, and AI's effect on jobs[41:35] Snap's $2,500 Specs and the case for enterprise over consumer[52:35] Rony's prediction: XR's coming "Nvidia moment"Brought to you by Zappar and Mattercraft, the leading visual development environment for immersive 3D web experiences. Start building at mattercraft.io. Hosted on Acast. See acast.com/privacy for more information.

Group Chat News is back with the biggest stories of the week including... Zach returns to break down what he's seeing inside San Francisco, why he thinks you have about 18 months to get really rich, and what happens to everyone else. Plus Zuckerberg spars a UFC fighter on a barge in the middle of Lake Tahoe, and Kai Cenat and Speed attempt one of the hardest challenges in gaming. This week's Group Chat covers: Zach's take from inside SF — and why his timeline keeps getting shorter every week "You have about 18 months to get really rich" — and then what Why less than 25 people on earth are using AI to its full potential The company running seven employees and three agents at 300 pull requests a day Agents that proactively fire contractors and stand up their own businesses Can an entrepreneur still spot the gap on a Target shelf when P&G has infinite data? Taste as the last human advantage — and whether that holds Purpose, meaning, and whether people need hard things given to them The optimistic case: UBI, Waymos, deflation, and everything just getting cheap Zuckerberg vs. Merab Dvalishvili on a barge sparring Kai and Speed's hardcore Minecraft marathon, and why the clips matter more than the game Parasocial fame, the chat as a Pavlovian loop, and how streaming ends And much more! Drop us a 5-star rating and a review if you're rocking with the show.

The Countdown crew put on their Nostradamus hats and make some bets on what is coming our way in Classic Plus. We also hear from DaBlasta again on some technical news, touch base with Ubi's cope, and talk to a group of LoL Classic players about the parallels between its launch and WoW Classic.C+ Technical News w/ DaBlasta - 3:35Classic Plus Predictions - 44:20Copealot w/ Ubiquitous - 3:49:45LoL Classic & WoW Classic Parallels - 4:28:20Buy Josh a beer & help keep Countdown on the airwaves over at Patreon here: https://www.patreon.com/joshcorbett Or if subscriptions aren't your thing, support Josh & Countdown by shouting him a one time beer here: https://ko-fi.com/countdowntoclassicCheck out Josh on YouTube for gameplay streams and live podcast recordings here:https://twitch.tv/countdownpodshttps://www.youtube.com/@countdowntoclassicJoin the Countdown To Classic discord here: https://discord.gg/83thqw2fBwCheck out Josh's hilarious movie podcast here: https://open.spotify.com/show/469qUDnQHBkCogdjZyFUjb?si=jNgDTiEnSvKBbZuNz2xcxw

THE BEST BITS IN A SILLIER PACKAGE (from Monday's Mike Hosking Breakfast) You Guys Interested In This?/Universally Bad Idea/Things Not to Worry About/Now That's How You Do It/More Polls Not to Talk AboutSee omnystudio.com/listener for privacy information.

Hour 3 for 8/7/26 Drew and Bruce Lachenauer, theFounder and Managing Partner of the Gaudium Group, discuss AI and the job market (1:00). Topics: will AI replace work? (10:17), UBI (15:01), AI and robotics (18:44), who controls AI? (25:09), low income workers (27:46), morality (33:03), will trades be needed? (42:49), job transition (44:32), and discouragement (47:09). Link: https://www.thegaudiumgroup.com/ Original Air Date: Hour 3 for 11/13/25

I've got so many friends right now in one of the most popular and lucrative spaces.....   They're making sick money.......   One friend does $2M a week in stem cell sales.    Another just sold his company for $50M.    Peptides.    Testosterone and Estrogen replacement therapy.    Why do I tell you this?    In the coming few months, I'm going to make a move in this space.    I've worked hard and built companies.    And I want to be around for a very long time to enjoy what I have.    If AI is going to replace us all and create a world of Universal Basic Income, we're going to need to be in the best health in our lives.     I may as well invest in that sector so I don't have to only rely on UBI.    I have another friend who sold his company at 55 and had a heart attack.    One of my first mentors told me the biggest regret he had was quitting working out.     He was never able to get back to it because he had let it go.    Remember, Health is Wealth.    You can still move and enjoy the mobility of the world if you start preparing today.    Get to work.    About the ReWire Podcast   The ReWire Podcast with Ryan Stewman – Dive into powerful insights as Ryan Stewman, the HardCore Closer, breaks down mental barriers and shares actionable steps to rewire your thoughts. Each episode is a fast-paced journey designed to reshape your mindset, align your actions, and guide you toward becoming the best version of yourself. Join in for a daily dose of real talk that empowers you to embrace change and unlock your full potential.    Learn how you can become a member of a powerful community consistently rewiring itself for success at https://www.jointheapex.com/   Rise Above 

PseudoPod 1040: Flash on the Borderlands LXXIX (79): Ubi amor, ibi dolor is a PseudoPod original. For CWs, please see show notes below Content warnings with timings: 03:56–16:40 ‘A Table Set And Waiting': graphic sexual content, body horror, homophobia 18:57–26:32 ‘Third Date': dangers of dating, physical abuse 29:44–40:52 ‘You're Still Here': homophobia, religion… Source

Vivienne Ming is the executive chair at Human Trust, Founder and Executive Chair at Socos Labs, Professor, and author of the book Robot-Proof: When Machines Have all the Answers, Build Better People. Greg and Vivienne talk about  how AI will reshape work and why the common narratives are really “lazy myths.” Vivienne argues that AI is superhuman at well‑posed problems but humans still retain a relative advantage in ‘ill‑posed problems,' contributing to a U‑shaped labor demand with erosion of jobs in the middle of it. She criticizes benchmark-driven, autonomous AI development and calls for optimizing hybrid intelligence, better education focused on foundation/meta‑learning skills (curiosity, working memory, perspective-taking, intellectual humility). Vivienne and Greg debate the merits of UBI as a solution, when discussing how destabilizing mass unemployment would be, and describes experiments where human‑AI “cyborgs” matched expert prediction markets when participants actively challenged AI rather than copying it. She ultimately delivers her message of hope for the future and belief in the humanity of humans. *unSILOed Podcast is produced by University FM.* Episode Quotes: Where humans beat AI 13:47: The most interesting problems that feel rare to us, but in almost the entire game are the ill-posed problems. These are the things where, forget right answers, we don't even know what the questions are. And, it may seem sort of trivially, almost axiomatic, to say that while the space of well-posed problems is vast, everything humanity has figured out. Play around with Gemini or GPT or any model you want and be proud. What it can produce is a testament to what humanity has discovered about the world. And sometimes it produces ugly things, and that's a reflection of us too. But the set of things we do not yet know is infinite. Our relative advantage is in ill-posed problems. The importance of foundational skills 45:25: Developing foundation skills isn't just about a better job. It's about a better life. What an amazing opportunity to take this moment in history and not just concern ourselves with whether I'm gonna boo Eric Schmidt because he's doubling down on AI and I feel like I'm losing a job, but to actually see that moment as an opportunity to invest in humanity in the way, almost paradoxically, we always should have been, but we didn't have to, and so we didn't. On transforming people relationship with work 22:56: Viewing your college education simply as a license to earn money, I think, also deserves a lot of self-skepticism. So we need to really transform work, but we also need to transform people's relationships with work, because we simply don't run a factory line economy anymore. I don't need you to be a very sophisticated cog where you're given orders and you execute them, and only a few people are smart enough, like you, to execute those orders. Pretty much everyone's job now, if I may be so self-elevating, is my job. People bring you unknown problems, you gotta figure them out, and I think that's terrifying, and no one's educating the next generation workforce on how to do it. Show Links: Recommended Resources: Jevons Paradox Generative AI AlphaGo Daron Acemoglu Jacquard Machine Industrial Revolution James Heckman Raj Chetty Guest Profile: Profile at Socos Labs LinkedIn Profile Wikipedia Page Social Profile on X Guest Work: Robot-Proof: When Machines Have all the Answers, Build Better People Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Chris Hagenow welcomes ITR Foundation Research Director Sarah Curry back to the studio. The occasion: a debrief on ITR Foundation's second annual Local Government Symposium, and it sounds like it was the best one yet.Sarah and Chris walk through what the symposium is and why it exists — local elected officials don't have the same depth of resources available to state legislators, and too often the information they do receive comes filtered through national associations with agendas that don't match Iowa. ITR Foundation is trying to fill that gap with practical, Iowa-focused content for the city council members, county supervisors, and school board members who are running local government on a part-time basis while holding down jobs and raising families.The conversation covers the day's major themes: what the proper function of a city actually is (police, fire, roads — not homeless task forces or economic development grants), why the free market allocates resources better than government, and what local officials should take from the property tax reform law that is now on the books — namely, that relitigating it is a waste of time and energy. The symposium also featured sessions on communicating with constituents, local endorsements, open meetings law, and a school board track that introduced benchmarking — why comparing Waterloo to Sioux City makes more sense than comparing Waterloo to Waukee.Before and after the symposium discussion, Chris makes sure listeners know about the amendment one campaign. Vote yes. MakeTaxHikesHarder.com.0:12 Welcome & Sarah Curry returns1:14 Amendment one reminder — and Sarah goes on record2:13 What is the Local Government Symposium?3:33 Why local officials need a different kind of resource9:13 Free market vs. government in service delivery10:04 UBI and scope creep: what cities shouldn't be doing12:31 Property tax reform: stop relitigating, start implementing13:38 Communications and constituent outreach16:00 Local endorsements — more powerful than you think19:27 Open meetings law and legal guardrails22:15 School board breakout: benchmarking districts correctly25:06 Chris's legislative update: property tax law is settled30:08 What's next for ITR Foundation's local government work30:45 Sign off & vote yes

“Well, this might be unwelcome news,” writes Andrew Yang, “but Kamala Harris is telling people in California that she is running for President again.” Yang, an entrepreneur who ran for President in 2020 as a Democrat, says his sources tell him Kamala's team is quietly laying groundwork for her to run in the next election – and why the DNC announcing that South Carolina “would be the first primary state in the 2028 Democratic primary” is a clue. “She showed up to a political event last weekend that was a pretty clear step in that direction,” says Yang. “As you might be able to tell, I think this whole thing is a disaster.” Andrew Yang joins Dr. Drew to discuss the next big Presidential election, AI's impact on jobs, and why he still champions UBI after famously proposing the Freedom Dividend to grant $1,000 per month to every American adult. Dr. Drew and Andrew also speak about their experience after competing together on FOX's new reality show Nation's Dumbest. Attorney Tom Renz returns to speak about a “betrayal” of MAHA after the CDC “gave Pfizer $1.24 billion for mRNA COVID vaccines including jabs for kids.” Dr. Kelly Victory reports on explosive new details from Dr. Anthony Fauci's COVID-19 diaries, recently released by Sen. Rand Paul in advance of Dr. Fauci's congressional hearing on July 29, 2026. 「 SUPPORT OUR SPONSORS 」 • FATTY15 – The future of essential fatty acids is here! Strengthen your cells against age-related breakdown with Fatty15. Get 15% off a 90-day Starter Kit Subscription at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drdrew.com/fatty15⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • PALEOVALLEY - "Paleovalley has a wide variety of extraordinary products that are both healthful and delicious,” says Dr. Drew. "I am a huge fan of this brand and know you'll love it too!” Get 15% off your first order at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drdrew.com/paleovalley⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • THE WELLNESS COMPANY - Counteract harmful spike proteins with TWC's Signature Series Spike Support Formula containing nattokinase and selenium. Learn more about TWC's supplements at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twc.health/drew⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • CHAPTER - For free and unbiased Medicare help, dial (218) 521-2472 to speak with my trusted partner, Chapter, or go to ⁠⁠⁠⁠⁠⁠⁠https://askchapter.org/drdrew⁠⁠⁠⁠⁠⁠⁠ Chapter and its affiliates are not connected with or endorsed by any government entity or the federal Medicare program. Chapter Advisory, LLC represents Medicare Advantage HMO, PPO, and PFFS organizations and stand alone prescription drug plans that have a Medicare contract. Enrollment depends on the plan's contract renewal. While we have a database of every Medicare plan nationwide and can help you to search among all plans, we have contracts with many but not all plans. As a result, we do not offer every plan available in your area. Currently we represent 50 organizations which offer 18,160 products nationwide. We search and recommend all plans, even those we don't directly offer. You can contact a licensed Chapter agent to find out the number of products available in your specific area. Please contact Medicare.gov, 1-800-Medicare, or your local State Health Insurance Program (SHIP) to get information on all of your options. 「 ABOUT THE SHOW 」 This show is for entertainment and/or informational purposes only, and is not a substitute for medical advice, diagnosis, or treatment. Executive Producers • Kaleb Nation - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://kalebnation.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • Susan Pinsky - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://x.com/firstladyoflove⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Content Producer • Emily Barsh - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://x.com/emilytvproducer⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

前不久，UBI Taiwan 的嘉冠和品逸才在節目裡跟大家分享，他們如何花一年的時間，透過基本收入幫助一位單親媽媽改善她的生活品質。而現在，他們馬上又要啟動一項新的「生活改寫計畫」，而且這次不但有新的夥伴加入，甚至人人都可以報名！ 到底這個計畫的內容是什麼？要參加有沒有什麼特殊條件呢？馬上來聽聽今天的大來賓怎麼說？ 歡迎今天的兩位來賓：UBI Taiwan 常務理事 李品逸、Gogolook 金融科技事業群 CEO 柯志強 Johnson 【寶博朋友說千萬粉絲專屬社群頻道 Discord 開張啦

Chapters:00:00 Meet Vitaly Golomb01:32 Why job losses are inevitable this time04:41 How close are autonomous trucks?06:10 Manufacturing, China, and lights-out factories07:30 The five robotics verticals his fund invests in11:10 If capital doesn't need labor, who buys anything?15:22 China's laws on replacing workers with robots17:45 UBI, or why "negative income tax" might actually pass20:27 Fixing US healthcare, one Medicare year at a time22:40 US vs Canada healthcare26:23 AI washing: which layoffs are real30:00 The Displacement Machine and the grievance economy36:38 America's unfair advantage: immigration40:09 What he invests in and why44:13 Why he's bearish on humanoid robots47:48 Final thoughts

Was Andrew Yang ahead of his time? When he ran for president in 2020 on a platform of universal basic income and the threat of AI job displacement, people didn't take him seriously. Now, Andrew's got even more ideas on AI and UBI, how our political system should deal with it all, and whether it can be done with only two parties. He and Jon discuss how the Forward Party's independent candidates could spoil elections for Republicans, his new book of essays “Hey Yang, Where's My Thousand Buck?” and why he's decided to join the cast of a new television game show: Nation's Dumbest.For a transcript of this show, email transcripts@crooked.com

This is the first of a number of episodes on the broad theme of “the technoprogressive opportunity”. That's the name of a conference taking place in London on the weekend of 19th and 20th September, co-organised by London Futurists and the IEET – the Institute for Ethics and Emerging Technologies. In these episodes, some of the speakers from that conference will be appearing as guests on this show.Our guest today is one of these speakers, Matteo Rossi MacDermant, a technophilosopher from the University of New Mexico. Matteo hosts a show called “Bread and Robots”, which covers subjects such as post-scarcity economics, universal basic income, the tech workers movement, and how technology can be steered toward collective abundance rather than corporate exploitation. Matteo is also the instructor for an online course called “An introduction to technoprogressive worldbuilding”.Selected follow-ups:The Technoprogressive Opportunity: Event in London, Sept 19-20The IEET - A Technoprogressive Think-TankMatteo Rossi MacDermant - LinkedInBread and Robots - Podcast and Substack by Matteo Rossi MacDermantAn Introduction to Technoprogressive Worldbuilding"Technoprogressive Declaration" - from Transvision 20142017 update to the Technoprogressive DeclarationUBI Guide - by Scott SantensUniversal Basic Capital - Windfall Trust"How a Land Value Tax Can Fund a UBI" - Scott SantensUniversal Basic Income and/or Alternatives - London Futurists conference held in 2018"Why the AI world is suddenly obsessed with a 160-year-old economics paradox" - Jevon's Paradox explained by Greg Rosalsky"The Longevity City: Cities as the Engines of Healthy Longevity" - essay by Matteo Rossi MacDermant"The London boroughs with the best and worst 'healthy life' expectancy""The Abolition of Aging" - book by David Wood (includes analysis of economic implications)Music: Spike Protein, by Koi Discovery, available under CC0 1.0 Public Domain DeclarationC-Suite PerspectivesElevate how you lead with insight from today's most influential executives.Listen on: Apple Podcasts Spotify

After a BIG announcement (!!!), your hosts David and Ellie get into the economic and psychological features of the state no one wants to be stuck in: unemployment. How does capitalism structurally construct “wageless life” while nonetheless treating it as a personal failure or unhappy accident? What's the connection between unemployment and reactionary politics? And is AI going to put us all out of a job? Correcting misconceptions about automation, UBI, and more, your hosts take you through some significant arguments about the impacts of unemployment and reflect on why this socially-constructed position can make us feel so worthless even when we know that we're not the problem. In the Substack bonus segment, Ellie and David reflect on the end of Overthink and share some reasons for it.Works Discussed:Aaron Benanav, Automation and the Future of WorkAaron Benanav, “Is the AI Bubble About to Burst?”Eloundou et al., “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”Charles Babbage, On the Economy of Machines and ManufacturesMichael Denning, “Wageless Life”Wendy Brown, In the Ruins of NeoliberalismRegina Bateson, “Perceptions of pandemic resume gaps: Survey experimental evidence from the United States”Start your business today with the industry's best business partner, Shopify. Sign up for your one-dollar-per-month trial today at shopify.com/overthinkElevate your summer wardrobe. Go to Quince.com/overthink for free shipping on your order and 365-day returns. Now available in Canada, too.If you're ready to stop talking yourself out of finding care and making progress, then head to rula.com and take the first step.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Danielle DiMartino Booth praises the FOMC minutes as "clean" under new Fed Chair Kevin Warsh—no manipulation of data like Janet Yellen did in 2013—and notes Warsh has successfully convened consensus around "less is more" Fed communications with an unusually quiet media environment. The real bombshell is the July jobs data: the unemployment rate fell to 4.2% only because 720,000 Americans gave up looking for work in a single month, representing a 50-year low in labor force participation since 1976, while 49% of adults under 30 now live with their parents as affordability collapses and job insecurity rises. Danielle warns the official narrative of economic strength masks a deteriorating real economy: revolving credit declined (a sign lenders are tightening), consumer confidence shows jobs are hard to get, and vacation spending has crashed to Great Recession levels—yet mainstream media remains fixated on an inflation narrative unsupported by broad data. The biggest systemic risk is the "too big to fail" stock market: 51% of global assets now sit outside the regulated banking system, asset managers hold assets larger than major banks, and the government can't allow equity market collapse when 401(k)s are the only retirement plans left, implying inevitable Fed monetization and the "end of capitalism." Her source of hope: summer interns aged 18-28 who are hungry, hardworking, and reject the "too big to fail" mentality—representing a generation determined to work their way out rather than accept billionaire UBI schemes designed to maintain inequality.Thank you to our sponsors: Kalshi - download the Kalshi app and use code JULIA to get $10 when you trade $10. http://kalshi.com/r/JULIA Monetary Metals - learn more at https://www.monetary-metals.com/julia/Links: Danielle's Twitter/X: https://twitter.com/dimartinobooth Substack: https://dimartinobooth.substack.com/ YouTube: https://www.youtube.com/@DanielleDiMartinoBoothQIFed Up: https://www.amazon.com/Fed-Up-Insiders-Federal-Reserve/dp/0735211655Timestamps: 00:00 Intro and welcome back Danielle DiMartino Booth 00:40 FOMC minutes from June - Clean, Warsh didn't manipulate data1:30 Warsh convened consensus, less is more communications working2:57 Forward guidance removal, Fed less visible, refreshingly quiet3:20 Elizabeth Warren defends bloated 12 district banks, Waller calling it out4:38 Warsh has convened consensus around leadership position5:13 Warsh refuses forward guidance, hints at ending dot plot6:23 Inflation cooling seen but Iran hostilities change calculus6:59 No press conference if nothing to say - Hail Mary move7:25 Mervyn King taking communications, five task forces with outsiders8:49 Kalshi traders: 79% hold rates in July, 76% expect no cuts 20269:36 Labor force participation 50-year low since 197615:35 720,000 Americans gave up looking for work in one month16:05 Unemployment fell to 4.2% but for wrong reasons16:59 Full-time jobs destroyed, replaced by gig workers17:36 Labor market called stable but disconnect with data18:18 Jobs hard to get at highest level, Americans aware19:30 Revolving credit down, unusual sign of lender tightening20:20 49% of adults under 30 living with parents21:12 Five of 20 K-Shiller metro areas below 2000 price levels22:35 Young people disenfranchised, AI destroying college degree value24:32 Stock market too big to fail - implies Fed buying equities25:01 Inequality gap - bottom 10% stock holdings fell 3% to 1%26:14 Top 0.1% holdings doubled, bottom K getting bigger26:33 Worry about social fabric fraying with K-shaped economy29:16 Billionaires pushing UBI while controlling AI benefits30:14 Work ethic is what made America great30:30 Writing piece on too big to fail for weekly flagship32:08 51% of global assets outside regulated banking system33:34 Summer interns give hope - bright, hungry, great work ethic34:45 Young generation rejects too big to fail narrative 

St. Francis of Assisi Prayer: "Lord, make me an instrument of your peace" in Latin and English. In this episode of the Latin Prayer Podcast, we explore the Prayer of St. Francis in Latin through a detailed word-by-word learning guide. While traditionally attributed to St. Francis of Assisi, historical evidence suggests it likely emerged in the early 20th century, yet it still reflects the spiritual tone associated with him. We break down the full Latin text line by line, including vocabulary, grammar patterns, and meaning shifts that make this prayer one of the most powerful for Latin learners and devotional listeners alike. You'll learn how repeating structures like ubi odium, amorem seram build meaning, and how the prayer transitions from outward intercession to inward transformation: becoming the one who consoles, understands, and loves. Chapters 00:00 Introduction – Why this prayer matters in Latin learning 01:20 The origin & historical controversy of the Prayer of St. Francis 04:10 How this prayer works as a Latin learning structure 06:30 “Domine, fac me servum pacis tuae” – opening line breakdown 08:15 Ubi odium, amorem seram – hatred & love vocabulary 10:30 Ubi iniuria, fidem, desperatio – injury, doubt, despair 13:10 Ubi caligo, tristitia – darkness & sadness vocabulary 15:40 The shift inward – from the world to the self 17:20 Consolari quam consolari – to console vs to be consoled 19:10 Intelligi, amari – understanding & love structure 21:00 “Nam in dando recipimus” – the paradox of giving 23:10 Final lines – death, rebirth, and eternal life 25:00 Full prayer recap & how to practice it in Latin 27:00 Closing prayer (Pater Noster, Ave Maria, Gloria Patri)   Help us restore sacred tradition and bring timeless prayers to new ears. Support our mission and gain access to our Latin learning guides, feast day resources, and audio devotionals. Find the Free Latin Learning Guide on Patreon: https://www.patreon.com/c/thelatinprayerpodcast A huge thank you to my Patrons! To follow me on other platforms Click on my LinkTree below. linktr.ee/dylandrego Submit Prayer Requests or comments / suggestions: thelatinprayerpodcast@gmail.com To Support FishEaters.com Click Here (  / fisheaters  ) Join me and others in praying the Holy Rosary every day; here are the Spotify quick links to the Rosary: Joyful Mysteries https://open.spotify.com/episode/1yhn... Sorrowful Mysteries https://open.spotify.com/episode/3P0n... Glorious Mysteries https://open.spotify.com/episode/3t7l... Luminous Mysteries https://open.spotify.com/episode/6vlA... 15 Decade Rosary https://open.spotify.com/episode/2q33... Know that if you are listening to this, I am praying for you. Please continue to pray with me and for me and my family. May everything you do be Ad Majorem Dei Gloriam. God Love You! Valete (Goodbye)   This podcast may contain copyrighted material the use of which may not always have been specifically authorized by the copyright owner. We are making such material available in our efforts to advanced the teachings of the Holy Catholic Church for the promulgation of religious education. We believe this constitutes a "fair use” of any such copyrighted material as provided for in section 107 of the US copyright law, and section 29, 29.1 & 29.2 of the Canadian copyright act. Music Credit: 3MDEHDDQTEJ1NBB0

SpaceX finally went public and made Elon a paper trillionaire, but the bigger story is what it says about America's ability to mobilize industry when it counts. Marty and John draw a line from that milestone to the geopolitical chessboard—whether the new US-Iran deal sticks, how Washington is using energy dominance and dollar leverage, and why Anthropic's Fable 5 got yanked by export controls. They also dig into Dario Amodei's AI roadmap, the Social Security math speeding toward 2032, and why the bond market may force a pro-liquidity future that makes US Bitcoin dominance impossible to ignore.

Alright, welcome to Part 2 of my conversation with Peter Diamandis—a man who lives and breathes exponential change, and isn't afraid to tackle the stuff everyone else would rather ignore. Now that you've braved everything breaking and the cracks in the old story, it's time to step fully into what happens next: regulation, UBI, riots and “derangement,” brain-computer interfaces, and some mind-blowing visions of what human purpose could look like when survival is no longer the point. Peter and I get into everything from whether AGI and superintelligence will help or harm us, the ethics of coding “morality” into AI, to whether humans are really just the boot disk for something greater coming next.This part goes deep on the forks ahead—will you opt out, numb out, become a creator, or actually merge your brain with the cloud? How are schools failing us (and what do our kids actually need to thrive)? We even get practical about what you can do right now to claim agency, think radically bigger, and make yourself anti-fragile—whether you want to start a company, change the world, or just live a life you can be proud of as the rules keep rewriting themselves in real-time. If you need just one episode to snap you out of fear and into action, this is it.Ketone IQ: Visit https://ketone.com/IMPACT for 30% OFF your subscription orderQuince: Free shipping and 365-day returns at https://quince.com/impactpodPlaud: Get 10% off with code IMPACT at https://plaud.ai/impactWhatnot:Download the Whatnot app today and get free shipping on your first order. AT&T Business: Switch to AT&T Business at business.att.comShopify: Sign up for your one-dollar-per-month trial period at https://shopify.com/impactTruemed: Check your eligibility and start saving at https://truemed.com/impactIncogni: Take your personal data back with Incogni! Use code IMPACT at the link below and get 60% off an annual plan: https://incogni.com/impactPique: 20% off at https://piquelife.com/impactWhat's up, everybody? It's Tom Bilyeu here:If you want my help...STARTING a business: join me here at ZERO TO FOUNDER: https://tombilyeu.com/zero-to-founder?utm_campaign=Podcast%20Offer&utm_source=podca[%E2%80%A6]d%20end%20of%20show&utm_content=podcast%20ad%20end%20of%20showSCALING a business: see if you qualify here.: https://tombilyeu.com/callGet my battle-tested strategies and insights delivered weekly to your inbox: sign up here.:https://tombilyeu.com/**********************************************************************If you're serious about leveling up your life, I urge you to check out my new podcast, Tom Bilyeu's Mindset Playbook —a goldmine of my most impactful episodes on mindset, business, and health. Trust me, your future self will thank you.**********************************************************************FOLLOW TOM:Instagram: https://www.instagram.com/tombilyeu/Tik Tok: https://www.tiktok.com/@tombilyeu?lang=enTwitter: https://twitter.com/tombilyeuYouTube: https://www.youtube.com/@TomBilyeuSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Donate (no account necessary) | Subscribe (account required) Join Bryan Dean Wright, former CIA Operations Officer, as he covers today's top stories shaping America and the world. In this Monday Headline Brief of The Wright Report, Bryan breaks down Iran's first direct ballistic missile attack on Israel since the April ceasefire, Israel's decision to fire back despite Trump's direct orders not to, and what the 100-day mark of this war actually tells us about where it is headed. With global oil stocks now roughly two weeks from critical levels and Iran demanding $24 billion in frozen assets before serious negotiations can begin, Bryan lays out why a fast resolution is increasingly unlikely and what it would actually take to change that calculus. He also digs into a Democratic Socialist professor openly cheering for Iran to bring down the American empire, the Anthropic AI model called Mythos that is alarming even its own creators, and a surprising area of agreement between Bernie Sanders and Donald Trump on government ownership of AI companies. Plus, Bryan profiles the Islamist Democratic Senate candidate in Michigan who just landed the UAW endorsement and could be headed to a razor-thin general election, covers Antifa attacks on the ICE facility in Newark, a fired Hawaii immigration judge who immediately announced plans to work for the Democratic Party, a Biden-appointed Boston judge blocking Trump's DEI and Title IX enforcement, and closes with the geopolitical chess match over Diego Garcia and the Chagos Islands that Bryan says he would personally volunteer to govern. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Bryan Dean Wright, The Wright Report, Iran missile attack Israel, Iran Israel war, ceasefire collapse, Benjamin Netanyahu, Trump Iran deal, Strait of Hormuz oil crisis, oil prices 150 per barrel, global oil shortage, Iran frozen assets 24 billion, Corinna Mullin Democrat Socialists of America, DSA Iran support, Anthropic Mythos AI, AI recursive self-improvement, AI national security threat, Bernie Sanders AI ownership, Trump sovereign wealth fund, universal basic income UBI, Sam Altman OpenAI UBI experiment, Abdul El-Sayed Michigan Senate, UAW endorsement Michigan, Islamist Democrat candidate, Antifa Newark ICE Delaney Hall, Don Lemon Minneapolis church attack, immigration judge fired Clarence Wagner, Judge Myong Joun Boston DEI ruling, Title IX transgender sports, Diego Garcia Chagos Islands, US territory Indian Ocean, Mauritius China, Candace Owens Russia St. Petersburg, Ukraine satellite imagery Colorado, Russia Ukraine war, Pope Leo Spain, Pedro Sanchez Spain immigration, Catholic Spain Marxism

A video recently went viral of Larry Fink, head of BlackRock, calling for Americans to invest their retirement savings and pension funds into AI data centers. Jimmy and Americans' Comedian Kurt Metzger argue that once investment becomes "mandatory," choice is removed and your 401(k) becomes collateral repurposed to support the globalist agenda—with risk and loss staying with you while upside and control go to the billionaires building the infrastructure. Catherine Austin Fitts explains that most people don't actually own their 401(k)s; they hold a "claim" through the DTCC, meaning their savings can be reallocated without their consent into centralized AI and energy grids.  The two hosts assert that the real purpose of massive centralized AI data centers is not productivity but control—specifically to enable central bank digital currencies (CBDCs) that will monitor every transaction in real time, with universal basic income (UBI) being the mechanism to force people to accept microchips under their skin. Jimmy concludes that the "race against China" is a psyop to get the public to comply without asking questions, and that the ICE prisons being built are not for immigrants but for Americans who eventually resist this takeover. Plus segments on Tucker Carlson railing against the predatory credit card industry, an Israeli released after being arrested for running an illicit biolab in Las Vegas and how Republicans proved that the "Force the Vote" strategy would work. Also featuring Stef Zamorano and Briahna Joy Gray!