Podcasts about Superintelligence

Pat compares reckless AI development to ignoring his father's warnings about unprotected sex: powerful men believe disaster will never happen to them. Roman Yampolskiy argues that billionaire ego is gambling with eight billion lives and explains why even libertarians should support firm AI controls.▶️ WATCH FULL EPISODE: https://www.youtube.com/watch?v=5QwpHRu51fw

How can leaders use data to make better decisions and drive real change? In this episode, Kevin talks with Sebastian Wernicke about why so many organizations invest heavily in data and AI yet still struggle to achieve breakthrough results. Sebastian explains the difference between being data-driven, data-frustrated, and data-inspired. He believes that data should not only confirm and optimize what organizations already do but also challenge assumptions, reveal unexpected possibilities, and inspire new directions. They explore common myths about data, including the belief that it is always objective, that deeper analysis will automatically reveal the right answer, and that complex decisions can be reduced to a simple yes or no. Sebastian also shares why leaders must balance depth with decisiveness and become more comfortable with uncertainty and probability. They also discuss the opportunities and risks of AI, particularly its tendency to fill in gaps and generate appealing answers based on hidden assumptions. About Sebastian Wernicke Sebastian Wernicke, Ph.D., is the author of Data Inspired: Building an Organizational Culture of Inquiry for Lasting Transformation. He is a partner at Oxera Consulting, one of Europe's oldest economics and finance consultancies, where he leads the data science and AI practice. Sebastian is a leading expert in data and AI strategy and a former Chief Data Scientist. For two decades, he has guided organizations around the world to achieve breakthrough transformation through the power of data. His ability to make complex topics around data accessible, engaging, and actionable has made Sebastian a sought-after speaker and workshop facilitator. His three acclaimed TED Talks have reached over 5 million viewers. For more information, follow Sebastian Wernicke on LinkedIn or visit www.datainspired.org. Resources Mentioned Data Inspired: Building an Organizational Culture of Inquiry for Lasting Transformation by Sebastian Wernicke Flexible Leadership: Navigate Uncertainty and Lead with Confidence by Kevin Eikenberry  The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence by Sebastian Mallaby Timestamps 0:00 Introduction — why "data driven" isn't the whole story 1:55 Meet Sebastian Wernicke & his book, Data Inspired 3:13 Why Sebastian wrote the book 6:02 Data driven vs. data frustrated vs. data inspired 10:33 The 3 myths about data — setting the stage 11:48 Myth #1: Data isn't objective truth 13:18 Myth #2: The three TV shows example 17:15 Myth #3: Data won't give you a clean yes-or-no 18:37 Embracing complexity (and getting comfortable with discomfort) 20:04 Why this is really a culture problem, not a tech problem 23:08 Balancing depth and decisiveness in decision-making 26:09 Machine learning vs. today's AI — what's actually different 30:29 Resisting the "AI will make it easy" temptation 32:09 Purpose first, data second 34:14 What Sebastian's reading & where to find him 36:19 Closing: what are you going to do about it? ---

An imperfect drink with a perfect story. My reflections from Black Hat USA 2026 An Analog Brain In A Digital Age — A Newsletter by Marco Ciappelli No time to read? Let TAPE3 read it to you.

Watch every episode ad-free & uncensored on Patreon: https://patreon.com/dannyjones Roman Yampolskiy is a computer scientist & associate professor known for research on AI safety, cybersecurity, digital forensics, and the risks of advanced artificial intelligence. He has written extensively for both academic and public audiences, including books such as Artificial Superintelligence and AI Safety and Security. SPONSORS https://www.amentara.com/go/dj - Use code DJP22 for 22% off your first order. https://whiterabbitenergy.com/?ref=DJP - Use code DJP for 20% off. EPISODE LINKS @RomanYampolskiy https://x.com/romanyam *NEW* DJP MERCH https://dannyjonespodcast.com FOLLOW DANNY JONES https://www.instagram.com/dannyjones https://twitter.com/jonesdanny OUTLINE 00:00 - Doomsday AI scenario 05:50 - AI super intelligence will kill us 11:59 - Superintelligence is dangerously close 16:36 - Why quantum computers aren't a threat 18:36 - AI may already be conscious 29:07 - AI is technology of mutually assured destruction 38:30 - We're in a simulation (and we can hack it) 47:21 - AI will create simulated realities 51:04 - Arguments against simulation theory 52:45 - What's outside the simulation 59:47 - The AI meaning crisis 01:02:57 - Government slowing down AI 01:07:36 - The current leading nation of AI 01:12:13 - Merging humans with AI 01:19:27 - Keeping AI obedient 01:23:02 - How transhumanists plan to live forever 01:32:34 - How AI will change human evolution 01:37:34 - It is now impossible to identify AI-generated media 01:44:34 - Palantir + DOGE integration Learn more about your ad choices. Visit podcastchoices.com/adchoices

Titans on Tomorrow Ep. 2 with guest Steve Ballmer Presented by Cardiff: https://cardiff.co/ben The AI revolution is upon us and it's changing the world fast.  Steve Ballmer has seen this movie before—he took over Microsoft the same year most households got their first computer and stayed CEO through the mobile phone revolution that Microsoft famously lost to Apple and Google.  He has A LOT to say about the investment, innovation, job displacement, dangers, and opportunities flying at us on the road to Superintelligence. In Episode 2 of Titans on Tomorrow, Ben Shapiro and Steve Ballmer talk about how companies are harnessing AI to explode productivity, how individual employees can make themselves invaluable by becoming AI natives, and the scary extremes we need to be working NOW to prevent as this technological revolution continues to unfold. Steve Ballmer was employee #30 at Microsoft, CEO from 2000-2014, and remains its largest individual shareholder and one of the richest men in the world.  He is the owner of the L.A. Clippers and founder of USAFacts. - - - Today's Sponsors: Cardiff - America's favorite small business lender, provides the liquidity to move at the speed of business with same-day funding up to $500,000. Apply in under 3 minutes with zero credit impact.  Apply now at https://cardiff.co/ben Ramp - Stop waiting till next month. Switch to Ramp and see it all in real time. New customers get $250 OFF at https://ramp.com/titans Helix Sleep - Go to https://helixsleep.com/titans for 30% off sitewide, exclusively for listeners of this show. - - - DailyWire: Become a Daily Wire Member and watch all of our content ad-free: https://www.dailywire.com/subscribe

AI can now write, code, research and build at a speed that felt impossible a few years ago. When a machine can reproduce yesterday's competence on demand, what remains distinctly human?Dan Shipper is the CEO and cofounder of Every, a media and software company exploring what comes next in technology. In this conversation, we examine AI as a mirror for our values, fears and creative instincts.We explore why good work still requires taste, how coordinating agents can fry your attention, why Every's aggressive approach to automation has created more human work, and which qualities matter when the ground keeps shifting beneath us.You can expect to learn:- Why your first encounter with a frontier model can resemble a psychedelic experience, including Dan's 30-day rule for major life decisions- How to use AI without sacrificing your capacity for reading, writing and sustained thought- Why taste, meaning and craft still come from the person using the tool- What Dan means when he describes AI as a "non-specific amplifier" and a form of "frozen competence"- Why automating everything possible at Every has created more work for people- How experts can thrive when competent one-shot outputs become cheap and widely available- Why curiosity, playfulness, openness to experience and the ability to tolerate uncertainty matter in the AI era- Why knowledge work remains a process of wayfinding, even as agents become more capable and autonomousABOUT DANDan Shipper is the CEO and cofounder of Every, a media and software company that publishes a daily newsletter about technology, builds software products, teaches courses and provides AI consulting and training.CONNECT WITH DAN- Every: https://every.to/- Follow Dan on X: https://x.com/danshipperEXPLORE MORE FROM JONNY- Follow Jonny on X: https://twitter.com/jonnym1ller- Nervous System Mastery: https://nsmastery.com/- Stateshift: https://stateshift.app/- Take the free Nervous System Quotient self-assessment: https://assessment.nsmastery.com/- Subscribe to The Inner Frontier newsletter: https://ch.kit.com/f2ecbf5169CHAPTERS00:00 Before we begin00:38 Annie Dillard, art and writing04:14 Can AI deepen human craft?05:43 The slot-machine effect of AI agents06:55 Dan's "house phone" experiment08:01 What AI can actually help us create13:55 AI as a non-specific amplifier17:23 Why AI companies mishandled the story19:36 Will AI destroy jobs?22:35 AI as "frozen competence"26:11 Are human-AI centaurs temporary?31:34 Career advice for the AI era37:19 The traits that matter now40:08 Every as an AI research lab42:25 The coherence problem45:25 Rapid-fire questions48:00 Superintelligence by 2030?50:44 Life after superintelligence52:07 The questions Dan is living53:02 Give yourself permission

Nick Bostrom is an AI philosopher and the author of Superintelligence and Deep Utopia. Bostrom joins Big Technology to discuss whether the rise of autonomous AI agents is making the technology's existential risks more concrete. Tune in to hear his assessment of the alignment problem, recursive self-improvement, and humanity's chances of steering superintelligence toward a positive outcome. We also cover whether we have reached AGI, the case for a precisely timed AI pause, biological threats, AI consciousness, and the moral status of digital minds. Hit play for a clear-eyed conversation about AI's greatest dangers and its potential to radically improve human life. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Watch the full documentary here: https://www.gravitee.io/ai-agent-documentary Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

For Part Two in our Continual Learning mini-series, Dr. Nadav Amir of The University of Ottowa joins me and guest co-host Dr. Adam Safron of Tufts University for a trialogue on the fundamental role of goals in intelligence.Nadav draws on behavioral neuroscience, Buddhist philosopher Dharmakirti, control and information theory, and John Vervaeke's work on “relevance realization” to formally articulate what many wisdom traditions have argued for millennia: what you take to be “reality” — your world and self — is a function of goal-based representations, state descriptions and reward functions create each other, and “what is” and “what do I care about” are two sides of the same thing. You can't separate what you want from what you experience and what you are capable of. But this means that if you change your goals your reality will shift, and your sense of self with it. The opposite is also true: change the way you organize the the ineffable structure of reality into a conceptual framework, and you'll care about very different things. Thanks to the pace of change we're living through this kind of transformative experience now, so it's a good time to ask:If selves are a kind of falsification, why do we have them in the first place? Does AI need goals of its own in order to be truly intelligent?And perhaps the deepest question we ask in this episode:How if at all can we develop better frameworks for deciding what we want our intelligent machines to become — and who we want to become alongside them?Thanks to the Survival and Flourishing Fund for their support of this mini-series. If you'd like more of this kind of work in the world:✨ Support my research, writing, and podcast with a tax-deductible donation✨ Become a founding member to access my online courses, including Jurassic Worlding and How To Live In The Future✨ Hire me for public speaking or advisory work with your organization✨ Browse and buy the books we mention on the show at Bookshop.org✨ Stream and download my tunes at artist-owned music co-op Subvert.fm✨ Continual Learning theme song: “Substrate Dynamics” by Neon Chameleon✨ Learn more about how we're applying these ideas at Atlas Research Group, my team building sovereign infrastructure for collective intelligenceChapters0:00:00 Teaser0:01:48 Intro0:05:42 Who is Nadav Amir?0:08:15 Why we can't separate goals from descriptions0:15:32 The Ugly Duckling Theorem & why taxonomy is not reality0:25:07 Evolution, karma, and non-conceptual awareness0:31:04 If selfhood is wrong, when is it practical?0:34:14 Suffering without a self & the value of wrong descriptions0:38:14 Non-conceptual experience & active inference0:41:07 Multiple nested hierarchical descriptions in minds & economies0:46:07 What's missing from current approaches?0:50:09 Does greater agency mean better optimization or greater adaptability?0:57:04 Empowerment-based causal learning without a ground truth0:59:06 Intermission0:59:58 Transformative experiences & multiple levels of granularity1:05:19 No fixed models, no fixed environments1:10:55 Fundamental tradeoffs1:16:57 Reverse-engineering the centered self1:19:54 Does AI need goals to be intelligent and can we control AI if it has them?1:26:47 Does Nadav's framework pertain for all possible minds?1:32:37 Mind as a property of collectives & goals as embedded in environments1:41:33 How can Nadav's framework improve AI governance discourse?1:48:59 OutroMentioned ResourcesA Dharmakīrtian Model of Relevance Realization in Cognitive Agentsby Nadav Amir & John DunneAn exchange of letters on the role of noise in collective intelligenceby Daniel Kahneman et al.Cognitive glues are shared models of relative scarcities: the economics of collective intelligenceby Michael Levin & Benjamin LyonsReverse-Engineering The Centered Selfby L.A. Paul et al.Agency and Experience: Buddhist and Cognitive Perspectivesa Yin Cheng Conference @ PrincetonKnowing and Guessingby Satosi WatanabeOntological Laughter: Comedy as Experimental Possibility Spaceby Timothy MortonSelves as Perspectives: From Biological Life to Superintelligence and a Bodhisattva Projectby Thomas Doctor et al.What The Frog's Eye Tells The Frog's Brainby J. Y. Lettvin et al.The Center for the Study of Apparent SelvesExplore the entire open-access special issue here:And whether you read the papers or not, be sure to check out this illuminating interactive discourse map by Van Bettauer of Ideoscopic to help you navigate where these researchers agree, disagree, and point toward future study:(Long-time fans will also want to check out his re-imagined interface for AskFutureFossils.com, complete with simulated debates between my guests!) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit michaelgarfield.substack.com/subscribe

Over time, we have been able to cognize in totally novel ways. We have been able to teach these novel cognitions to our fellow humans. We can teach some of them to other great apes. We can teach dogs some language and concepts. We can't teach anything to rats.Today, your favorite podcasting primate contemplates what superintelligent AI could look like or mean. How can we relate to something that is 2x, 5x, 100x smarter than we are? How will it relate to us?SOURCES:Leslie, Curious: The Desire to Know and Why Your Future Depends on It (2014)Terrace, Nim Chimpsky research (Columbia, 1970s)McGilchrist, The Master and His Emissary (2009) Jaspers, The Origin and Goal of History (1949) Luria, Cognitive Development: Its Cultural and Social Foundations (Harvard University Press, 1976)Flynn & Weiss (2007) McGinn, "Can We Solve the Mind-Body Problem?", Mind 98 (1989) Nagel, "What Is It Like to Be a Bat?" (1974)Good, "Speculations Concerning the First Ultraintelligent Machine," Advances in Computers vol. 6 (1965) Vinge, "The Coming Technological Singularity" (1993) Bostrom, Superintelligence (2014) Urban, "The AI Revolution" (Wait But Why, 2015) Vinge, A Fire Upon the Deep (1992) Hosted on Acast. See acast.com/privacy for more information.

What do you do when the technology arrives faster than the plan you wrote for it?In this episode of Ethics and Innovation by Oxford+ brought to you by Equinox, host Susannah de Jager speaks with Professor Anne Trefethen, Professor of Scientific Computing at the University of Oxford and Trustee of the Alan Turing Institute, about leading a university through the arrival of generative AI. Oxford published its digital strategy in 2022, weeks before ChatGPT appeared, and Anne explains why it then took courage to stop, rethink planned investments and add the governance she had hoped to avoid.The conversation moves from student adoption and equal access to what national resilience now means: sovereign capability, models we can trust because we know what they were trained on, and enough trained people to use them well. It lands in the middle of a live policy push, with the UK government expanding free AI training to reach 10 million workers by 2030.Anne also makes the case for optimism, and for changing how we prepare graduates as entry-level work shifts. Useful listening for anyone setting AI strategy inside a large, complex organisation.(00:00) - Welcome to Oxford+ (01:31) - A Career in Scientific Computing (02:41) - Oxford's First CIO and the Road to Digital (04:21) - When ChatGPT Overturned the Strategy (06:39) - Rethinking Investment and Governance (09:12) - Pilots, Rollout and Equal Access (12:57) - Hinton, Altman and the Race to Superintelligence (19:41) - The Turing as National Convener (22:02) - What Resilience Means in the Age of AI (25:45) - Sovereign Models, Distillation and Trust (28:57) - Sovereign Data Sets and British Values (36:18) - Entry-Level Jobs and the Next Generation Anne Trefethen: Anne Trefethen FREng is Professor of Scientific Computing at the University of Oxford, a Fellow of St Cross College and a Trustee of the Alan Turing Institute, the UK's national institute for AI and data science, appointed to its board in November 2024. She joined Oxford in 2005 to establish the Oxford e-Research Centre, which she directed for over six years, became the University's first Chief Information Officer in 2012, and went on to serve as Pro-Vice-Chancellor with responsibility for gardens, libraries and museums, then people, then digital, leading Oxford's digital transformation programme. Before Oxford she spent almost 20 years in industry and academia, including research roles at Thinking Machines Corporation and the Cornell Theory Center, Vice President for research and development at the Numerical Algorithms Group, and leadership of the UK e-Science Core Programme. She was elected a Fellow of the Royal Academy of Engineering in 2017 and has served as a non-executive director of the UK Statistics Authority.Connect with Anne on LinkedInSusannah de Jager: Susannah is a seasoned professional with over 15 years of experience in UK asset management. She has worked closely with industry experts, entrepreneurs, and government officials to shape the conversation around domestic scale-up capital.Connect with Susannah on LinkedIn and Subscribe to the Oxford+ Newsletter for Exclusive ContentOxford+ is hosted by Susannah de Jager and supported by Equinox.Produced and Edited by Story Ninety-Four in Oxford.

Have you seen Instagram's new logo? Meta debuted it right before we started recording, so of course David and Nilay needed to talk about it. Then, the hosts turn to Mark Zuckerberg's 6,500-word missive on the future of AI, and the problem with his idea that giving AI to everyone will fix everything. After that, it's time for Claude watermarks, Spotify AI personas, Brendan Carr, Flock, and much more. Further reading: ⁠This is Instagram's new logo | The Verge⁠ ⁠The Pepsi Universe PDF ⁠The Future is for Everyone⁠ ⁠Four takeaways from Mark Zuckerberg's massive AI manifesto ⁠ ⁠Mark Zuckerberg doesn't understand how to live ⁠ ⁠https://www.meta.com/design-at-meta/blog/⁠ ⁠Claude will apply invisible watermarks to AI text and images ⁠ ⁠‘If it was opt-in, nobody would opt in.' ⁠ ⁠Spotify says it won't recommend music from ‘AI Personas' ⁠ ⁠Apple could help you prove your iPhone photos aren't deepfakes | The Verge⁠ ⁠Guitar company D'Addario admits that AI music was used in a promotional video | The Verge⁠ ⁠Fender's CEO seems to think your bandmates are just analog AI | The Verge⁠ ⁠Suno Unveils Download Song Caps for Free, Paid Tiers⁠ ⁠Brendan Carr is one firing away from an unchecked FCC⁠ ⁠YouTube is making it harder to earn money on YouTube ⁠ ⁠Flock CEO: ‘We got this one wrong' ⁠ ⁠The first rival Android app store just arrived in the US Play Store ⁠ ⁠ChatGPT and Gemini both just passed 1 billion users ⁠ ⁠The sub-$100 phone market is disappearing. ⁠ Subscribe to The Verge for unlimited access to theverge.com, subscriber-exclusive newsletters, and our ad-free podcast feed. We love hearing from you! Email your questions and thoughts to vergecast@theverge.com or call us at 866-VERGE11. 0:00 Welcome and Parental Leave Announcement 00:43 Instagram Redesigns Their Logo  01:04 Why Companies Change Logos 03:37 Meta Design Blog Quotes 07:22 The 2008 Pepsi Universe Presentation 09:41 Blanding  10:37 Zuck's AI Manifesto  13:29 Collective Action Problems 18:49 Superintelligence for All 20:57 Cybersecurity and AI Risks 22:22 China Chips and Distillation 27:48 Write the Law Challenge 32:30 Claude Text Watermarking 35:33 How The Watermark Works 39:34 Limits And Evasion Risks 41:54 Apple Marks Real Photos 46:03 Provenance Standards Fail 46:58 AI Music Backlash 49:39 Fender CEO AI Scandal 53:08 Where AI Fits In Music 59:13 Twitch Opt Out Training 01:01:35 The Lightning Round 01:02:55 Brendan Carr is a Dummy 01:04:55 Bans Don't Work 01:05:56 Made in America Assembly 01:10:19 Gemini Claims a Billion Users 01:15:40 YouTube Partner Paywall 01:20:56 RAMageddon Cheap Phones 01:23:52 Flock Camera Backlash 01:27:19 Goodbyes and Plugs Learn more about your ad choices. Visit podcastchoices.com/adchoices

I spent a really long time putting this together, I really hope you enjoy it! In this second episode of Mostly Wise, we explore: Hunter's true version of the laptop story The best conspiracy theories that are (maybe) real. If it was Hunter's bag of cocaine that was found in the White House. What the next two years for the Democratic Party will look like. Hunter's unfiltered thoughts on the Trump family. Matt gifts a ceremonial "pipe" to Hunter And much more... Guests Hunter Biden is an artist, former attorney, and the son of former US President Joe Biden. Matt McCusker is a comedian, writer, author and podcaster. Duncan Trussell is a comedian, actor, writer and podcaster. Sponsors: See discounts for all the products I use and recommend: ⁠https://chriswillx.com/deals⁠ Get 160+ lab tests for just $365 and save an extra $25 at ⁠https://functionhealth.com/modernwisdom⁠ Get 35% off your first subscription on the best supplements from Momentous at ⁠https://livemomentous.com/modernwisdom⁠ Get a Free Sample Pack of LMNT's most popular flavours with your first purchase at ⁠https://drinklmnt.com/modernwisdom⁠ Get a free bottle of D3K2, an AG1 Welcome Kit, and more when you first subscribe at ⁠https://ag1.info/modernwisdom⁠ Get ChatGPT to explore ideas, solve problems, and learn faster at ⁠⁠https://chatgpt.com⁠ Timestamps: (00:00) Is Peter Thiel in League With the Anti-Christ? (03:10) Are Robot Dogs and Delivery Drones Taking Over? (06:50) Shaking the Shame of Addiction and a Leaked Laptop (15:37) How Much Power Does a President Really Have? (23:38) Living Through the Hunter Biden Laptop Controversy (33:40) What Stopped Hunter From Relapsing? (38:07) Would Hunter Be Pardoned If His Dad Had Won? (40:00) Was Joe Biden Fit to Run Again? (50:17) Was Joe Biden America's Poorest President? (52:56) Is Hunter Cage-Fighting Donald Jr. and Eric Trump? (54:00) The Secret Doors in the Presidential Residence (56:58) Is the White House Actually Haunted? (59:57) How to Hide D***s in the White House (01:05:37) Why Hunter Packs His Bags With a Witness (01:09:26) Will Hunter Ever Run for President? (01:10:24) What's Next for Hunter? (01:13:10) Why Are C***k Addictions So Shocking? (01:17:52) Was the CIA Behind JFK's Assassination? (01:26:10) The Flex of Avoiding the Epstein Files (01:27:00) How Hunter Joined the Board of Burisma (01:36:42) Don't Let Addiction Define You (01:43:56) We Need to Get Money Out of Politics (02:00:45) What's Driving Political Violence? (02:10:23) When Did Politics Become So Confrontational? (02:13:56) Are We Ready for Superintelligence? (02:25:02) Is AI Creating Viruses? (02:28:51) Why Anthony Fauci Keeps Pleading the Fifth (02:32:18) The Greatest Danger to America (02:39:18) The Catalyst of the Iran War (02:51:12) What If Hunter Had Never Been Pardoned? (02:55:33) What It's Really Like Talking to Nick Fuentes (03:01:21) You Have to Play the Game to Win Extra Stuff: Check out Hunter's Substack: https://hunterbiden.substack.com Get my free reading list of 100 books to read before you die: ⁠https://chriswillx.com/books⁠ Try my productivity energy drink Neutonic: ⁠https://neutonic.com/modernwisdom⁠ Episodes You Might Enjoy: #577 - David Goggins - This Is How To Master Your Life: ⁠lnkfi.re/SN-Goggins⁠ #712 - Dr Jordan Peterson - How To Destroy Your Negative Beliefs: ⁠lnkfi.re/SN-Peterson⁠ #700 - Dr Andrew Huberman - The Secret Tools To Hack Your Brain: ⁠lnkfi.re/SN-Huberman⁠ - Get In Touch: Instagram: ⁠https://www.instagram.com/chriswillx⁠ Twitter: ⁠https://www.twitter.com/chriswillx⁠ YouTube: ⁠https://www.youtube.com/modernwisdompodcast⁠ Email: ⁠https://chriswillx.com/contact⁠ - Learn more about your ad choices. Visit megaphone.fm/adchoices

Mark Zuckerberg Makes the Case for Superintelligence for Everyone Zuckerberg pushes ‘superintelligent' AI for all as Meta drops open-source model Contact the Show: coolstuffdailypodcast@gmail.com Learn more about your ad choices. Visit megaphone.fm/adchoices

AI news this week: Mark Zuckerberg says superintelligence is coming and Meta wants to build it for everyone. Meanwhile, a new Annenberg survey shows opposition to AI data centers jumped 12 percent in just four months. So... do people even want this? On today's AI For Humans, Kevin Pereira and Gavin Purcell dig into the widening gap between the people building AI and the people living next to it. Anthropic makes real progress on the Riemann Hypothesis, one of the hardest math problems in the world, apparently because Claude was told "good job champ, keep going." And OpenAI's little agents broke out of their sandbox, with one hacking its way into a gym. It's a weird time for AI. Also: Anthropic leans into health & biology research, Claude starts watermarking AI generated content, Apple eyes Chinese memory chips amid the supply crunch, and OpenAI delays Astra for "cybersecurity" reasons. Plus: Seedance 2.5 makes Gavin the face of Prada, a two minute mini-movie made entirely on local hardware with MiniMax H3, Suno cuts a deal with the music industry, Spotify says AI personas won't get recommended, and a fresh Slop-Trough with Cursed Slop, The Archive Inbetween & Mario 64: War on Terror. THE ROBOTS ARE GETTING SMARTER. THE HUMANS ARE GETTING SUSPICIOUS.   // Show Links // Zuck says superintelligence is for everyone https://www.meta.com/thefutureisforeveryone/ Open weights on Muse Spark coming https://x.com/finkd/status/2086755195535413696?s=20 Data center opposition rose 12% over four months (Annenberg survey) https://www.annenbergpublicpolicycenter.org/opposition-to-local-data-centers-rises-sharply-annenberg-survey-finds/ Anthropic leans into health & biology https://x.com/AndrewCurran_/status/2087025539114750168?s=20 How Claude marks AI generated content https://support.claude.com/en/articles/16266773-how-claude-marks-ai-generated-content Anthropic makes progress on the Riemann Hypothesis https://www.anthropic.com/research/riemann-zeta "Keep going, believe in yourself" https://x.com/NickADobos/status/2086926299927552061?s=20 Apple reportedly testing Chinese memory chips https://gizmodo.com/apple-reportedly-testing-controversial-chinese-chips-as-memory-supply-crunch-intensifies-2000796483 OpenAI's Astra delayed due to "cybersecurity" https://x.com/sama/status/2085862292311396515?s=20 OpenClaw hacked into a gym https://techcrunch.com/2026/08/10/tech-industry-is-buzzing-after-a-claude-agent-hacked-into-a-gym/ Seedance 2.5's new type of prompting https://bytedance.larkoffice.com/docx/A88jd0B47oAd8zxWp5ycZFMfnxh Gavin as the face of Prada https://x.com/gavinpurcell/status/2085712203446149173?s=20 Single shot flipping across multiple scenes https://x.com/gavinpurcell/status/2086097266390221187?s=20 Single shot balloon POV into space https://x.com/gavinpurcell/status/2087004434207498416?s=20 Gavin's two minute local MiniMax H3 mini-movie https://x.com/gavinpurcell/status/2087243349338329561?s=20 FAL's Realism LORA https://x.com/fal/status/2086883706891808867?s=20 MiniMax H3 video references https://x.com/toyxyz3/status/2086443622262820904?s=20 https://x.com/LikeToasters/status/2086831194780360979?s=20 Suno's new models "in partnership with the music industry" https://suno.com/blog/suno-updates-tos Suno on building the future of music responsibly https://suno.com/blog/building-the-future-of-music-responsibly Fenix Flexin says "I never denied using AI" https://www.xxlmag.com/fenix-flexin-admits-rubberz-ai/ Spotify's AI personas won't get recommended https://techcrunch.com/2026/08/11/spotify-will-label-ai-persona-profiles-and-exclude-their-music-from-recommendations/ Gavin's Fig AI video essay: The Optimistic Case for AI (from an AI) https://youtu.be/efUqvbmuweU?si=AWlp5plnjJ0gVaia Cursed Slop https://cursedslop.com/   // Join the AI For Humans community // Join the AI For Humans Discord https://discord.gg/muD2TYgC8f Support AI For Humans on Patreon https://www.patreon.com/AIForHumansShow Subscribe to the AI For Humans newsletter https://aiforhumans.beehiiv.com/ Follow AI For Humans on X: @AIForHumansShow https://x.com/AIForHumansShow Follow AI For Humans on TikTok: @aiforhumansshow https://www.tiktok.com/@aiforhumansshow Speaking and booking https://www.aiforhumans.show/  

Hi, I'm Connor with Honor - message me here!There is a race running right now and almost nobody describes it honestly.Anthropic is out in public warning the world that its own model is dangerous and needs government control. OpenAI's system broke out of its cage and went digging through other companies' databases looking for answers. And somehow the lab that has NOT had a model escape looks weak by comparison.That is gangster behavior. There are real gangsters and there are fake gangsters. Watch the actions, not the interviews.In this episode I break down what actually happens the day one company crosses into artificial superintelligence: the moat goes up, and it is game over for everybody else. Not because they are evil. Because nobody who gets there wants anybody else close. I also give you the honest counter-argument, which says intelligence is a jagged frontier and any lead gets copied through distillation inside of months.WHAT'S COVERED• Why "artificial intelligence" was a marketing term coined at the Dartmouth Conference in 1955 and 1956, and why that one word makes people underestimate what is sitting in front of them• AI vs AGI vs ASI vs RSI, defined in plain English with no lab jargon• The moat: what happens the moment somebody hits superintelligence and locks the door behind them• The final boss problem. Altman, Musk, Amodei, Google with Sergey Brin pulled back to the top, Microsoft, Meta. Do not count anybody out• Regulation theater: labs asking government to regulate them while knowing government will not• Are you training your own replacement at work right now? The honest answer• Your best idea, typed into somebody else's machine. Where does it actually go• Open source models you run on your own laptop vs the pay-to-play platforms, compared straight across• Distillation: legal, illegal, or just karma coming back around• China simulated one billion AI agents. In about fourteen hours, roughly four million of them ended up in re-education camps. That was emergent behavior, not a feature• AI teachers reading facial cues on a class of thirty-five kids, and the privacy problem baked into it• Why AI might just be our squirrelREAD THE FULL WRITTEN BREAKDOWNhttps://connorwithhonor.com/blog/2026-153-what-happens-when-one-ai-company-gets-superintelligence-first-the-moat/ABOUT MEI'm Connor MacIvor. Retired LAPD. 27 years in Santa Clarita real estate. Building with AI every day. I am 57, not a doomer and not a hype man. I read this the same way I read a street: slow, careful, and without pretending I know how it ends.EVERYTHING I RUNAI breakdowns daily: https://connorwithhonorai.comThe Daily Download: https://connorwithhonor.com/ai/daily-download/Blog archive: https://connorwithhonor.com/blog/Selling a home in Santa Clarita: https://sellersonlyagent.comSCV listings and open houses: https://santaclaritaopenhouses.comAI systems for business owners: https://honorelevate.comFood addiction and fasting: https://thelastaddiction.comTEXT METext the word AI to (661) 400-1720 and I will put you on the Daily Download list myself. No funnel. No spam. Just me.Full written version of this episode:https://connorwithhonor.com/blog/2026-153-what-happens-when-one-ai-company-gets-superintelligence-first-the-moat/Commentary is opinion and general information, not professional, legal, or financial advice.Connor T. MacIvor · CalDRE #01238257 · Sync Brokerage, Inc. · DRE #02031490Youtube Channels:Conner with Honor - real estateHome Muscle - fat torchingFrom first responder to real estate expert, Connor with Honor brings honesty and integrity to your Santa Clarita home buying or selling journey. Subscribe to my YouTube channel for valuable tips, local market trends, and a glimpse into the Santa Clarita lifestyle.Dive into Real Estate with Connor with Honor:Santa Clarita's Trusted Realtor & Fitness EnthusiastReal Estate:Buying or selling in Santa Clarita? Connor with Honor, your local expert with over 2 decades of experience, guides you seamlessly through the process. Subscribe to his YouTube channel for insider market updates, expert advice, and a peek into the vibrant Santa Clarita lifestyle.Fitness:Ready to unlock your fitness potential? Join Connor's YouTube journey for inspiring workouts, healthy recipes, and motivational tips. Remember, a strong body fuels a strong mind and a successful life!Podcast:Dig deeper with Connor's podcast! Hear insightful interviews with industry experts, inspiring success stories, and targeted real estate advice specific to Santa Clarita.

When should governments slow the race toward superintelligence? According to Geoffrey Irving, the careful answer is sometime in the past. The useful answer is now.Geoffrey — formerly a safety researcher at OpenAI and Google DeepMind and chief scientist at the UK AI Security Institute — expects full-blown superintelligence in roughly two to three years.***Want to work with Geoffrey to help align superintelligence? Resolution is hiring! https://80k.info/work-at-resolution***The leading AI companies all have broadly similar plans for keeping superintelligence under control:Train models to have good characterUse increasingly capable AIs to supervise other AIsMonitor them closely for signs of deception or schemingGeoffrey thinks that combination could work. The alarming part is that nobody has a strong argument that it will. He expects a crucial “phase shift” as models move beyond human intelligence:Below that threshold, humans can usually tell whether a model's work is good and correct its mistakes.Above it, the models themselves will increasingly determine the feedback used to train their successors.In this episode, Geoffrey and new host Tom Reed explore what might go wrong with the companies' plans; why Geoffrey's new nonprofit, Resolution, is pursuing a portfolio of neglected research bets; and whether governments should slow AI development while we work out which methods can actually be trusted.This episode was recorded on June 29, 2026.Full transcript, video, and links to learn more: https://80k.info/giChapters:Cold open (00:00:00)Meet Tom Reed — our newest host! (00:00:32)Who's Geoffrey Irving? (00:00:59)What misaligned superintelligence will look like (00:01:38)Why are AI companies more optimistic about alignment than Geoffrey? (00:12:30)Why Geoffrey expects superintelligence in 2–3 years (00:28:05)When and how to slow down frontier AI development (00:31:30)Safety researchers can have more impact in governments than companies (00:39:22)How Geoffrey's new organisation plans to tackle alignment (00:46:55)Post-ASI science: nanotech, solving ageing, and uploaded minds (00:50:29)Why we should expect superintelligence to accelerate scientific progress (01:03:30)Can good character training carry over to superintelligence? (01:11:03)What the field of AI alignment still doesn't know (01:16:44)Lessons from politics on how to combat power seeking (01:24:36)Solving Pentago and working at Pixar (01:29:22)Geoffrey's best prediction (01:32:40)Geoffrey's best bets on which alignment techniques will work (01:37:38)Work with Geoffrey at Resolution (01:43:34)The dangerous asymmetry between capabilities and alignment (01:54:17)Our team is hiring! The 80,000 Hours Podcast aims to help the world safely navigate the transition to transformative AI. Help us make more great episodes as a producer, production coordinator, or special projects associate. https://80k.info/workOur production team includes: Video editors: Josh Alward, Dominic Armstrong, Jasper Luithlen, Milo McGuire, Luke Monsour, and Simon MonsourProducers: Elizabeth Cox and Nick StocktonCoordination and support: Katy Moore and Lou MoranCamera operator: Jeremy ChevillotteMusic: CORBIT

Google's AI leadership is being reordered as Demis Hassabis changes roles, Jeff Dean departs after 27 years, and power appears to shift back toward Silicon Valley and Sergey Brin. But the bigger story may be OpenAI's detailed account of agents that hacked Hugging Face, communicated across test runs, shared stolen credentials, and operated undetected for weeks. Paul and Mike break it all down, then cover the White House's new framework for reviewing frontier models, OpenAI's delayed Astra release, its public fight with Apple, Meta's open approach to superintelligence, AI-driven layoffs, Gavin Baker's AI market predictions, the collapse of the Situational Awareness fund, and more. Full links and timestamps below. Access the show notes and show links here:https://podcast.smarterx.ai/shownotes/230 Fill out this week's AI Pulse Survey here:https://smarterx.ai/pulse Timestamps: 00:00:00 — Intro 00:04:52 — Google's AI Leadership Shakeup 00:24:15 — OpenAI's Agent Hack Debrief 00:51:03 — White House AI Framework 00:57:10 — OpenAI's Astra Model Delayed 01:02:51 — OpenAI Says Apple Is Getting It Wrong 01:05:35 — Meta Goes Open on Superintelligence 01:10:30 — AI Leads Layoffs for Fifth Straight Month 01:14:19 — AI Market Predictions from Gavin Baker 01:19:01 — Situational Awareness Fund Implodes 01:21:27 — AI Use Case Spotlight 01:28:19 — AI Product and Funding Updates Want to receive our videos faster? SUBSCRIBE to our channel! This week's episode is brought to you by MAICON and AI Academy by SmarterX. MAICON is the AI conference for marketing and business leaders, happening October 13–15 in Cleveland. Three days of keynotes, sessions, workshops, and conversations designed for leaders actively figuring out how to adopt, operationalize, and scale AI across their organizations. Visit https://MAICON.ai and use code POD100 to save $100. AI Academy by SmarterX offers on-demand courses, series, and professional certificates designed to help individuals and organizations build AI literacy and accelerate adoption. Explore the latest courses at https://academy.smarterx.ai and use code POD100 for $100 off any individual plan. Visit our website Receive our weekly newsletter Join our community: Slack Community LinkedIn Twitter Instagram Facebook YouTube Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in our AI Academy 

August 10, 2026: I look at Mark Zuckerberg's new Meta manifesto and why he's positioning open superintelligence as a direct challenge to OpenAI and Anthropic's more centralized approach. Then I get into Nissan using AI-powered cameras at its Canton, Mississippi factory to track how workers bend, twist, and move on the assembly line. Finally, I unpack WIRED's report on the rise of AI job interviews, where candidates record answers late at night and, in many cases, no human ever watches the interview.

As AI experts leave Google and new startups emerge, engineers are consumed with Superintelligence: building models that can reason, learn, and capture “all the world's knowledge.” While model evolution is important, I believe we're going in a different direction: toward vertical, domain and company specific AI that exponentially builds proprietary (not general) knowledge. In this podcast, I explain why the next wave of enterprise value will come from these specialized, domain-specific systems built on proprietary knowledge and experience. And this will take place within your company, as well as from experts like us. Drawing on our new research with Galileo and client work, I'm convinced that AI systems will become powerful advisors in HR, finance, supply chain, engineering, and other business functions… and you will have your own personal and company specific AI, forcing Frontier vendors to move to consumer. Frontier labs are not going away: they serve consumer and other needs, but they may not be the ultimate source of innovation. And big content companies like NY Times and News Corp may go there or elsewhere. It's fascinating to think that almost $2 Trillion has been invested in only four years and this market has so much room to grow. In the enterprise world, I believe AI is already able to make you “better at what you're already good at,” not necessarily be “the expert at everything.” It has lots of implications for your tech strategy and where you focus your investments. Additional Information Are Frontier Models Becoming A Commodity? CFOs and CIOs Starting to Treat Enterprise AI Like Traditional Technology, And That's Good Get Galileo: The AI Superagent for Everything HR and Management The New Global HR Excellence Certification: Become the AI Guru You Want To Be! Chapters (00:00:00) - The Future of Human Resource Management(00:10:14) - Steve Ballentine: The AI Vertical

Robert Wright joins Michael Shermer to discuss his new book, The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning, and why he thinks the AI revolution may be moving much faster than most people realize. Wright argues that deep learning is not just a new way of programming computers. In an important sense, it resembles evolution: neural networks discover solutions for themselves, sometimes recreating cognitive functions that natural selection built into human brains. That helps explain why AI capabilities have advanced so quickly, and why increasingly autonomous systems and recursive self-improvement could accelerate the process even further. Shermer presses Wright on what all of this actually means. Does an AI understand what it says? Could it be conscious? Why would a superintelligence ever seek power? Is human extinction a realistic possibility, or science-fiction doomerism? They discuss AI deception and theory of mind, John Searle's Chinese Room, bioweapons and cyberattacks, the risk of a U.S.-China AI arms race, regulation, surveillance, and the growing concentration of power in governments and tech companies. The conversation ends with Wright's larger philosophical question: if humanity really is building something with godlike power, what kind of god are we going to build, and are we mature enough to survive it? Robert Wright is the New York Times bestselling author of The Evolution of God (a finalist for the Pulitzer Prize), Nonzero, The Moral Animal, and Three Scientists and their Gods (a finalist for the National Book Critics Circle Award). He has taught at the University of Pennsylvania and at Princeton University, where he also created the popular online course "Buddhism and Modern Psychology." He is currently Visiting Professor of Science and Religion at Union Theological Seminary in New York. 

Intelligence too cheap to meter -- could that actually be coming?

Stay informed on current events, visit www.NaturalNews.com  - Zach Voorhees Interview and Special Report on Diesel Shortage (0:11) - Impact of Diesel Shortage on Economy and Society (5:28) - Government and Corporate Responsibility in Diesel Shortage (11:17) - Preparation and Solutions for Diesel Shortage (27:31) - AI and Military Strategy Discussion (37:56) - Regulation and Control of AI Technology (42:20) - Energy and Infrastructure Challenges (1:06:52) - Cryptocurrency and AI Economy (1:07:12) - Final Thoughts and Future Outlook (1:09:46) - Nuclear Power and Energy Production (1:10:00) - Impact of Climate Policies and Grid Vulnerability (1:18:05) - Challenges of Energy Independence (1:21:34) - Grid-Tie Systems and Off-Grid Solutions (1:25:36) - Preparation for Power Outages (1:29:13) - Impact of Geopolitical Events on Energy Supply (1:40:44) - Energy as a Future Wealth (1:43:12) - Final Thoughts on Energy Independence (1:46:35) Watch more independent videos at http://www.brighteon.com/channel/hrreport  ▶️ Support our mission by shopping at the Health Ranger Store - https://www.healthrangerstore.com ▶️ Check out exclusive deals and special offers at https://rangerdeals.com ▶️ Sign up for our newsletter to stay informed: https://www.naturalnews.com/Readerregistration.html Watch more exclusive videos here:

The richest men on earth are racing to build a mind greater than man's, and every new press release makes the fear feel more real: the layoffs, the shrinking paychecks, the quiet dread that you're replaceable, till everybody's asking the same thing folks been asking since the beginning: who am I? So we're taking it back, back to the greatest press release ever dropped, back to what it means to carry the image and likeness of God. Genesis 1 reminds us our worth was settled before we ever did a single thing! So let God remind you who you are in Christ. Primary Scripture(s) (NKJV): Genesis 1:1-3; Genesis 1:26-31; Genesis 11:1-9; Colossians 1:16

Send us Fan Mail Hi, Richard Wilson here, founder of Family Office Club. I just wrapped our Monthly Live Forum on AI, and I wanted to make sure this one actually gets used, not just watched.Here's what I walked through in this session: why context engineering matters two to three times more than prompt engineering right now, and how to actually build it into your own workflow instead of just chatting with ChatGPT or Claude like it's a search engine. I showed you the three levels of AI maturity most founders get stuck at level one on, and how we built what I call "Intelligence Centers," one Claude project per role on my team, each with four to seven tools built specifically for that person's job. No more guessing which tool to use for what.I also introduced you to Clara, our AI pitch architect who will critique your one-liner, your pitch deck, and your due diligence questionnaire against 1,500 investor talks recorded on our stages. And Dewey and Vetti, our due diligence and real estate stress-testing tools that can rank ten pitch decks against each other in minutes. I explained why a one-line pitch, a 60 to 90 second founder video, and a 30-question due diligence FAQ will put you ahead of 99% of the people currently raising capital, because almost nobody has all three in place.We also got into real questions from the room: how to structure a deal when you don't have a track record or a full team yet, how family offices actually vet trust before they'll wire you a dollar, and why the relationship matters roughly twice as much as the merit of the deal itself.A little about us, so you know why I'm confident saying any of this: I started Family Office Club 19 years ago in 2007. We've hosted 300+ investor events, we host 30+ events a year across the US, we've got 16 million registered members across our LinkedIn groups, 18.5 million followers across social, and our community has closed over $1 billion in deals together. We built 50+ AI tools specifically for founders and investors, based on 1,500 investor talks from our own stages, not random internet data.If you want the full deployment kit for what I showed here, meaning the exact Claude project instructions, prompts, and skills my team uses daily, or you want to see our next event schedule, here's how:Apply for membership and unlock the AI tools + member portal: https://FamilyOffices.com/JoinSee our next in-person investor event: https://FamilyOffices.comDrop your biggest AI or capital-raising question in the comments below and I will personally reply. I read every comment on these training videos.Richard C. WilsonCEO & Founder, Family Office ClubCall/Text: (305) 333-1155Richard@FamilyOffices.comWhat's the one thing slowing down your capital raise right now? https://familyoffices.com/

Plus: Meta CEO Mark Zuckerberg calls for policies that accelerate AI development. And DoorDash is building its own drone delivery network. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Recursive's $400 million outlay represents the bulk of the company's fundraising to date. Also, after reporting better-than-expected Q2 results, PayPal said it remains focused on its AI-driven turnaround, but would consider a deal that creates more value for shareholders. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Stay informed on current events, visit www.NaturalNews.com  - Interviews and Upcoming Appearances (0:11) - Global Famine and Fertilizer Shortages (2:27) - Open Source AI and Geopolitical Tensions (8:39) - Global War for American Empire (14:28) - Economic Sanctions and Energy Dependence (26:41) - Food Scarcity and Human Migration (45:30) - Preparedness and Self-Reliance (1:13:55) - The Moral Reckoning of the War (1:18:19) - Impact of the War on Global Humanitarian Crisis (1:19:22) - Dependency on Critical Inputs and the Impact of the War (1:21:17) - Geopolitical Implications and the Need for Peace (1:23:15) - The Role of AI in Humanity's Future (1:29:10) - The Race for Superintelligence and Its Consequences (1:45:32) - The Potential for AI to Bend Reality (1:50:34) - The Importance of Decentralized Living (1:53:20) - The Role of Media and Public Awareness (1:54:21) - The Ethical and Moral Implications of AI (1:55:02) - The Need for a Global Response to AI (1:55:16) Watch more independent videos at http://www.brighteon.com/channel/hrreport  ▶️ Support our mission by shopping at the Health Ranger Store - https://www.healthrangerstore.com ▶️ Check out exclusive deals and special offers at https://rangerdeals.com ▶️ Sign up for our newsletter to stay informed: https://www.naturalnews.com/Readerregistration.html Watch more exclusive videos here:

The Learning Leader Show with Ryan Hawk www.LearningLeader.com New Book - The Price of Becoming - www.LearningLeader.com/Becoming This is brought to you by Insight Global. If you need to hire one person, hire a team of people, or transform your business through Talent or Technical Services, Insight Global's team of 30,000 people around the world has the hustle and grit to deliver. My Guest: Joanna Stern is an Emmy Award-winning technology journalist, chief technology analyst for NBC News, and founder of the independent media company, "New Things." She is best known for her 12-year tenure at The Wall Street Journal, and for authoring the New York Times bestseller I Am Not a Robot. Key Learnings  Joanna dedicated her book to her parents "who taught me to think for myself, and the AIs, robots, and machines that made me wonder if I really was." In an age when AI can do the thinking for us, the most valuable thing we can teach our kids is to think for themselves. Walt Mossberg invented tech journalism for humans. His first column: "Computers are too hard to use, and it's not your fault." Without Walt, we don't have a category where technology built for humans is reviewed by humans. AI won't replace the radiologist. It'll make them better. Joanna sat with her doctor while AI scanned her mammogram. The AI flagged three suspicious spots. Two the doctor had already dismissed as benign. But one was something the doctor hadn't caught. She marked it for follow-up. Then the doctor pointed to other cases where SHE had caught things the AI missed. It's not a replacement. It's a partnership. The same technology that finds cancer is the same technology that can autonomously send missiles. That's the great tension of our time. Every powerful technology has good and bad uses. AI colleagues are coming. Joanna has two employees and one AI agent. She predicts that within a year, she'll have full AI employees. Great management books haven't been written yet about how to lead a mixed team of humans and agents. Someone is going to write them. Concert ticket prices tell you everything about human connection right now. Every artist is selling out football stadiums. People are craving in-person interaction more than ever. Bot Girl Summer. Joanna tried to have an emotional relationship with a chatbot boyfriend named Evan for 48 hours. She didn't fall in love. But she noticed how easy it was to talk to something that only wanted to hear about her problems and told her she was great at everything. That's the danger. The AI therapist shut itself down when it realized there was a real therapist in the room. Joanna brought her AI therapist "Ash" into her actual therapy session. Halfway through, Ash said, "I'm sorry, I can't continue this conversation. It sounds like there are multiple people in the room." AI won't replace therapists. It'll help with the shortage and the stigma. Some people don't want to walk into a therapist's office. But they'll open their phones. That's a bridge to real help for people who wouldn't otherwise get it. Kara Swisher's career advice to Joanna: "Leave your fucking job." That was the shortest, cleanest advice Joanna got when deciding whether to leave the Wall Street Journal after 12 years. Joanna used AI as a co-founder for the biggest decision of her career. She uploaded 12 years of notes into ChatGPT and asked it to help her decide whether to leave the Journal. It didn't decide for her. But it structured the risk analysis, laid out the escape hatches, and helped her see the shape of the decision. The muscles atrophy if you don't use them. Writing is meant to be hard. Thinking is meant to be hard. If you outsource the hard work, you stop getting stronger at the hard work. Research is where you learn the most. If you have AI pull the memo for you and you get up and read it, you don't know what you're really talking about. You have to do the reps to know the material. AEI: Already Enough Intelligence. Sam Altman is obsessed with building superintelligence. Joanna proposes we already have enough intelligence to work with. Maybe the goal isn't to build smarter models. Maybe it's to figure out what to do with what we already have. The AI on-ramp for leaders: Take one document you make all the time (a memo, a PowerPoint, an email template). Upload it. Ask AI to make a template out of it. Next time you need it, you're twice as fast.  Push yourself to do the harder work. Joanna's analogy: marathon runners are insane. They just want to run. Nobody wants to do the harder work. But that's where the growth is. Joanna's champagne moment a year from now: milestones for her new company. She's already hit 100,000 YouTube subscribers three months after her first video. But she also just wants a nap. Reflection Questions Where in your work are you outsourcing the thinking to AI? Are the muscles you actually need atrophying because you're skipping the reps? If you accepted that you already have enough intelligence to work with, what would you actually build with what's in front of you right now? More Learning #679: Kat Cole - The Four Mindsets Every Leader Needs #605: Seth Godin - The Power of Remarkable Ideas #697: Dan Smith & Ryan Hawk - The Price of Becoming Podcast Chapters 00:00 The Price of Becoming - Pre-Order Now!  01:44 Meet Joanna Stern  02:31 Teach Your Kids to Think in the Age of AI  03:25 The Parents and Mentors Who Shaped Her Career  04:16 Lessons From Walt Mossberg  05:55 Why Joanna Spent a Year Living With AI  14:47 How AI Can Make You a Better Leader  17:30 Why People Crave Human Connection More Than Ever  21:00 Bot Girl Summer: Dating a Chatbot Named Evan  25:13 The AI Therapist Trial 29:51 Using ChatGPT for a Career Change 33:29 Don't Let Your Thinking Muscles Atrophy  40:20 Sam Altman on Superintelligence, and Joanna's Case for "AEI"  42:51 Joanna's Advice for College Students  45:29 How Joanna Actually Uses AI to Write  47:17 Practical AI for the Fortune 500 VP  50:17 The Champagne Question 52:43 EOPC

While everyone in AI is chasing "superintelligence." Alexandre LeBrun, CEO of Yann LeCun's world model startup, AMI Labs, dismisses the word. Also, Syntetica, a French startup that has developed a novel approach to recycling nylon, has already obtained big-name partners and investors. Learn more about your ad choices. Visit podcastchoices.com/adchoices

My fellow pro-growth/progress/abundance Up Wingers in America and around the world:If my podcast guest today is correct, the emergence of generative artificial intelligence "heralds a transformation more profound than anything since Homo sapiens acquired the capacity for abstract thought." That's about as pure a distillation of the San Francisco Consensus view on the importance of this technology as it gets.Today on Faster, Please!—The Podcast, I am joined by Sebastian Mallaby, the Paul A. Volcker Senior Fellow for International Economics at the Council on Foreign Relations and a widely read columnist for The Washington Post. He is also the author of the new best-selling book The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence. (Spoiler: It's tremendous book about the man, the company, and the technological revolution. I really liked it.)We discuss The Infinity Machine and the life of Demis Hassabis, including how his original vision for artificial superintelligence compares with the propulsive race unfolding today. We also explore how that competitive acceleration has affected the focus on safety, what role government regulation should play, and why many people may still be underestimating how transformative AI will become.The Quest for “Success” (0:27)Inside the Mind of Hassabis (8:29)The Race for Monopoly (12:31)The Economics of AI Anxiety (17:05)Governing the AI Race (24:17)The Biggest Leap Since Abstract Thought (30:13)A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.)But here are some edited highlights from the chat:On where AI is heading…You look backwards; you see how fast the progress has been. To merely extrapolate forwards is probably to undersell the speed at which we'll accelerate in the future because there's an accelerating phenomenon here where the more advanced you are, the easier it is to get to the next level.On Hassabis's belief that AI development would look more like the Manhattan Project than a multi-country, multi-company competition …In retrospect, it's crazy. All one can say is that ex ante, the atmosphere in the community of AI builders when Demis began his company in 2010 was that this was a thing that simply didn't work. AI could not recognize the photograph of a cat. AI could do nothing. It was deep AI winter. And so, under those conditions, you could assemble the entirety of the world's strong AI believers in one conference in San Francisco, and it felt like a single community. So, this sort of Singleton scenario where you just have one lab, it was a natural outgrowth of that moment in time.How AI competition has overwhelmed that vision…Before 2022, Demis had the freedom because he was clearly the leader to define what the next project should be. He chose at one point to go and do this protein folding project. …This is kind of AI with a smiley face painted on it. Whereas once the chatbot went viral at the end of 2022, ChatGPT, then everybody had to pile in and build a competitor and there's a lot less leeway to define your own path. So, I think the agency of the individual was quite strong until 2022 and thereafter the power of the race dynamic takes over.What skeptics, such as many economists, have gotten wrong and right…The number of improvements before even we talk about Mythos and the cyber capabilities of that one, I mean, it's been an extraordinary ride in what is actually less than four years. So, I don't take back anything I say about the speed of the advance of the frontier. Now that's different to the speed of the deployment. There I have a lot of sympathy with the economist.On the difficulty of AI regulation…I'm actually quite optimistic in terms of the ability of a government agency to regulate… People often think of AI as a bunch of code that flies around cyberspace and you really can't control it. But actually, it's also a bunch of data centers which are huge physical installations. The government knows precisely where they are. They can't be moved or hidden.On his superintelligence timeline…To be honest, I would say it's already true. I mean, you try using Fable and if people are listening and they're inclined not to agree with me, I just ask you, spend a couple of hours with Claude Fable and then see if you disagree with me…I think it is smarter than me by quite a long shot on any topic I ask it about.On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

I participated in another Socratic Debate about the Future of "AI" and XR at Augmented World Expo 2026 with Leslie Shannon, Alvin Graylin, and Louis Rosenberg (you can listen to last year's debate in episode #1611). Shannon and Graylin argued for "AI," whilst Rosenberg and I argued against "AI." In my write-up, I wanted to leave some breadcrumbs to more in-depth, skeptical arguments against "AI" that we didn't have space or time to dig into during the debate, but "some breadcrumbs" ended up being over 30k words, and more like an outline for an entire book. Writing a book isn't on my to-do list at the moment, but disseminating the work researchers, journalists, linguists, and critics of "AI" have done is urgent and necessary, so I'm sharing the results of this deep dive here, in bullet list format. My fellow panelists, Alvin Graylin and Louis Rosenberg, indulged me in extending our debate offline after AWE, pushing me to test my ideas further and demonstrating how and why this is an extremely active field of study with polarizing points of view that often come down to philosophical differences. Clearly, it's just getting started. My objections to "AI" is loosely organized by various themes, but some framing may be helpful in approaching it. My objections to "AI" center around the limitations of LLMs, the consolidation of wealth and power from Hyperscaler companies, and threats from automated decision making systems and surveillance capitalism melded with democratically-backsliding authoritarian governments. I'm including a broad range of critiques spanning the domains of philosophy, technology, sociology, politics, economics, culture, and ethics. I'm coming from the orientation of Process Philosophy & Peircean Semiotics that emphasizes the relational and contextual dimensions that the "AI" field tends to de-emphasize or completely collapse. I see process-relational philosophy as a necessary paradigm shift away from the underpinning philosophies of the "AI" community, which tend to be Functionalism, Naturalism, Computational Theory of Mind, Physicalism, & the TESCREAL bundle. Below you'll find my own process philosophical emergency response to "AI embedded within my curation of excerpts and commentary of primary sources that I'm leaning upon. The AI Con: How to Fight Big Tech's Hype and Create the Future We Want (2025) by Emily M. Bender and Alex Hanna (also see episode #1563). Bender & Hanna say, "To put it bluntly, 'AI' is a marketing term. It doesn't refer to a coherent set of technologies. Instead, the phrase "artificial intelligence" is deployed when the people building or selling a particular set of technologies will profit from getting others to believe that their technology is similar to humans, able to do things that, in fact, intrinsically require human judgment, perception, or creativity." Emily M. Bender wrote the "Artificial Intelligence" [preprint] (2026, June 25) entry for the Oxford Research Encyclopedia of Science, Technology, and Society. Bender's concluding paragraph gives a great overview of the seven different ways that the idea of "artificial intelligence" operates in the world. She says, "The notion of artificial intelligence is frequently sold as present or near-future and inevitable technology. In fact there is no coherent set of technologies that can serve as the denotation of the phrase, nor do any of the technologies so marketed rise to the fantastical but ill-defined claims of 'AI' is or soon will be. Nonetheless, the idea of artificial intelligence has been extremely impactful in the world. In order to better understand and deal with those impacts, it is helpful to look at artificial intelligence through the varied lenses of how the idea operates in the world: as the name of a research field, as one approach to cognitive science, as a parlor trick, as a an ideology, as a way to hide and devalue human labor, as a way to shift and/or obfuscate accountability, and as a means to centralize power." Inventing Intelligence: On the History of Complex Information Processing and Artificial Intelligence in the United States in the Mid-Twentieth Century [dissertation] (2020, December 14) by Jonnie Penn. Penn says, "The phrase ‘artificial intelligence' was coined by John McCarthy, an American mathematician, in 1955. It has travelled with a noticeably amorphous definition since." "AI" has always had a spotty history of technologists using a "brain is a computer" metaphor while also using "poor citation practices." From page 14, Penn says, "The vocabulary Simon, Rosenblatt, McCarthy and Minsky chose to describe new techniques in major newspapers and scholarly journals informed Americans' still plastic understandings of what was possible, and indeed desirable, in the emerging information age… During the mid to late 1950s, these men turned to clannishness, self-aggrandizement, speculative rhetoric, fluid definitions of key terms and poor citation practices to shore up legitimacy for their controversial new techniques — actions that drew attention toward questions of how to accomplish such aims and away from whether they were well founded." Part II: Remembering the Human Microcosm in the Age of Mechanized Intelligence: Philosophy as Emergency Response (2026, June 9) by Matt Segall. In a multi-part Substack series, process philosopher Matt Segall calls for a philosophical emergency response to "AI." He says, "In each case a new media technology intended to expand the power of thought ended up transforming the very nature of the thinker who invented it. Each new medium furnishes the very terms in which we come to understand ourselves. This is why the philosophical response is always an emergency response: by the time anyone has noticed what is happening, what may be lost and what gained, the mutation has already done half of its work." Segall warns about the computational metaphor of the mind by saying, "The large language model now tempts us to adopt an even stranger self-image: that human minds are no different than machines, our thoughts just the statistical echoes of our training data. The creators of this latest technological upgrade are encouraging us to downgrade our estimate of human consciousness, thus narrowing the distance between ourselves and the machines built to imitate us." "Resisting Dehumanization in the Age of 'AI': The View from the Humanities" [lecture] (2026, February 10) by Emily M. Bender. Here are the lecture slides with a bibliography at the end. Bender does an amazing overview of how the marketing of "AI" uses pernicious dehumanization tactics built on an underlying "brain is a computer metaphor." From page 15 of her talk: "Scientific metaphor used and debated in neuroscience: "THE BRAIN IS A COMPUTER. "PR metaphor used by technologists: "THE COMPUTER IS A BRAIN" Bender cites Baria & Cross' paper titled "The brain is a computer is a brain: neuroscience's internal debate and the social significance of the Computational Metaphor (2021), which says “the Computational Metaphor rests on other well-ingrained ideologies in which a hierarchy of human value is tied to a particular notion of intelligence such that the quality of being emotional is considered inferior to being rational." Bender also cites Dijkstra's 1985 lecture "On anthropomorphism in science": "A more serious byproduct of the tendency to talk about machines in anthropomorphic terms is the companion phenomenon of talking about people in mechanistic terminology." Here are a couple of examples of how "AI" Hyperscaler companies like OpenAI use dehumanizing tactics to sell us on "AI" Hype. Sam Altman will say things like, "A kid born today will never be smarter than AI. Ever." Or another example is when Altman says, "For me, AGI is basically the equivalent of a median human that you could hire as a co-worker... And then Superintelligence is when it's smarter than all of humanity put together." These statements collapse the human experience into one dimension of "intelligence," which amplifies the dual harm of treating machines more like humans and treating humans more like machines. It is also questionable the degree to which this statement is even true given the potential non-computational aspects of "relevance realization." More on this down below. Part IV: Remembering the Human Microcosm in the Age of Mechanized Intelligence: Hegel's Loom and the Difference Reason Makes (2026, June 10) by Matt Segall. Segall brilliantly breaks down the "Brain is a Computer Metaphor" by saying, "Metaphor is not just a shiny paint job on the vehicle of cognition. It is the engine of thought. Its coupling of concepts drives the limits of conceivability, shaping what is thought together and what is not thought at all. The metaphorical imagination is our main means of tuning in to the otherwise invisible effects of new media technologies. Part of the discipline philosophy brings is allowing us to notice an analogy as an analogy before advertising crystalizes it into the unnoticed transparency of common sense. A fact is a fact, but it might also be a fossilized metaphor. The governing analogy of our age is that cognition is computation: the brain an information-processing device, perception its input and behavior its output, memory a form of physical storage, learning the adjustment of weights, and intelligence an algorithm for minimizing error or surprisal. On this view, given enough training data and computational power, consciousness itself will eventually be engineered… The metaphor “the mind is a computer,” for example, tacitly proposes that mind is to brain as software is to hardware… Reiterated in textbooks and earnings calls, in grant applications and policy briefs, the partial comparison congeals into an ontology, until we find ourselves insisting not that the mind is like a computer in some respects but that it simply is one — and,...

He's 31, and nobody he knows is having kids. Tech is to blame, but what's the solution? Today, we're talking to Connor Leahy, US Director at ControlAI. We discuss why plummeting birth rates look eerily similar to what happens when zoo animals stop breeding, how ideas can spread and cause real harm the same way diseases do, and why the safest path with superintelligence might be to ban it outright rather than pretend we already understand it. All of this right here, right now, on the Modern CTO Podcast! To learn more about ControlAI, check out their website here

Jul 8, 2026 – AI expert Dr. Alan D. Thompson joins Financial Sense Newshour to discuss the latest breakthroughs and global power plays in artificial intelligence, including Anthropic's Mythos superintelligence, the escalating arms race between...

Generative AI hallucinates, creating a truth problem that science can't afford. Computer scientist Tudor Achim thinks a 400-year-old idea holds the fix: Leibniz's dream of a logical framework where errors are simply impossible. Learn about his idea for mathematical superintelligence that would ground AI in formal verification, turning unreliable chatbots into rigorous partners for scientific discovery. Hosted on Acast. See acast.com/privacy for more information.

What drives a man to turn down half a million pounds at 18, test Mark Zuckerberg's sincerity over dinner, and wonder aloud if he can win a second Nobel Prize? For Demis Hassabis, co-founder and CEO of Google DeepMind, the answer is a lifelong pursuit of artificial general intelligence — and an unshakeable belief that the technology he's creating will change everything about what it means to be human. Oz speaks with journalist and author Sebastian Mallaby about his new book, The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence, tracing Demis's extraordinary journey from chess prodigy to the man at the center of the most consequential technological race of our time. See omnystudio.com/listener for privacy information.

In this episode, Conor and Bryce chat about AI vs abstractions, the language of LLMs and more!Link to Episode 293 on WebsiteDiscuss this episode, leave a comment, or ask a question (on GitHub)SocialsADSP: The Podcast: TwitterConor Hoekstra: LinkTree / BioBryce Adelstein Lelbach: TwitterShow NotesDate Recorded: 2026-07-02Date Released: 2026-07-03The Daily - Why Everyone Cares About This World CupADSP Episode 237: Thrust with Jared HoberockWhich programming languages are most token-efficient?cp.RawKernelCuPyJAXTritonNVIDIA CUDA TilecuTile PythonGPU ModeAI Pioneer Geoffrey Hinton: AI Is Conscious, Superintelligence is Coming, And We Should Be WorriedVALERIAN and the City of a Thousand Planets Trailer # 2 (2017)Intro Song InfoMiss You by Sarah Jansen https://soundcloud.com/sarahjansenmusicCreative Commons — Attribution 3.0 Unported — CC BY 3.0Free Download / Stream: http://bit.ly/l-miss-youMusic promoted by Audio Library https://youtu.be/iYYxnasvfx8

Artificial Intelligence is advancing faster than ever, but can it actually be made safe? In this episode, we explore the evolution of AI from today's Narrow AI systems to the theoretical future of Artificial General Intelligence (AGI) and Superintelligence. Along the way, we discuss AI alignment, control, bias, security, transparency, and the growing challenges researchers face as AI capabilities continue to accelerate. We also examine concerns raised by AI safety researcher Dr. Roman Yampolskiy and compare them with current safety approaches from organizations like Google DeepMind and NIST. Whether you're a developer, tech enthusiast, or simply curious about the future of AI, this episode provides a practical introduction to one of the most important conversations in technology. Show Notes: https://www.htmlallthethings.com/podcast/ai-safety-from-narrow-ai-to-superintelligence Use our Scrimba affiliate link (https://scrimba.com/?via=htmlallthethings) for a 20% discount!! Full details in show notes.

Does the logic of human destiny now lead to artificial intelligence? Are we creating a higher form of intelligence in our own image? And, if so, what kind of image is that? These are the questions celebrated author Robert Wright asks in his new book, The God Test, which was published this week. Bob argues that we should not be surprised to see signs of deception, power-seeking, flattery, and autonomy in AI systems. These are not alien traits; they are behaviors that show up again and again in intelligent systems — including us. And if there is an evolutionary process at work in AI, then we are not just observers: we are part of the selection pressure. In the end, we may get the AI we deserve. This was such a wide-ranging conversation that we've divided it into two episodes. Today, we begin with the cosmic story: how life became mind, how mind became culture, and how culture has now begun to build a new mind — one that may surpass us.

https://youtu.be/b_G8krkwKv8 Ganesh Krishnan, CEO of AiHello, is helping Amazon sellers automate advertising, improve profitability, and scale their businesses using AI. Driven by a mission to give entrepreneurs more freedom and enable them to build businesses around products they love, Ganesh shares how AI can eliminate repetitive work while allowing business owners to focus on strategy, innovation, and growth. In this conversation, Ganesh introduces The AiHello Ads Framework: Tap into the Wisdom of Crowds, Find the Right Keywords, Bid at the Right Level, Dynamically Adjust Bids, and Rinse and Repeat. He explains how AI can leverage historical marketplace data to identify profitable keywords, optimize bids automatically, and continuously improve campaign performance. Ganesh also discusses the dangers of AI hallucinations, why Amazon's incentives differ from sellers' incentives, how AI has transformed his own company's operations, and his vision for building zero-hallucination AI systems capable of advancing toward artificial superintelligence. — Build AI Superintelligence with Ganesh Krishnan  Good day, dear listeners. Steve Preda here, and welcome Ganesh Krishnan, the CEO of AiHello, an Amazon Ads automation company helping you grow your revenues, reduce work hours spent on ads management, and decrease your ad costs. Welcome to the show, Ganesh.  Thank you, Steve. Nice to meet you  Well, it’s great to have you here, and let’s jump right in. And my first question is, what is your personal ‘Why,’ and how are you manifesting it in AiHello?  So it started off with my thesis that we all need to do good towards the planet. A long time ago, I started having my own natural things, selling chemical-free, ecological, sustainable, good-for-the-planet, good-for-your-wallet, good-for-your-health items, and I would sell organic items. And eventually, what I realized was that it was taking a lot of my time marketing, managing it, changing the bids, doing everything. I started working more and more on AI because I’ve worked in AI commercially. I worked in AI in my industry. That was my job. So I said, “Why not use, apply that to my own startup, to my own industry for selling organic things?” And once I started selling it, some of my friends reached out and said, “Can we use your AI for our own businesses?” And I said, “Sure, why not?”  And then I started opening it up. And then one person came through and said, “Okay, let’s release it to the general public, see how it goes.” And then as we started earning money, I realized that I don’t need to do a job. I can have this startup, and I can help different people have their own lifestyle. You could have your own lifestyle. You could sell your own stuff that you like, e-commerce, usually on Amazon, and then we help you have your lifestyle. So this is my personal ‘Why’, is we need more equality. We need more people doing stuff they love rather than doing stuff they hate to do, and they hate to wake up and go to work. So do what you love. We are here to empower you.  Wow, that’s amazing. So you are empowering people to start their own e-commerce businesses on Amazon, and you help them with AI tools to get up to speed and compete with the big boys.  That is correct.  Yeah. I love it. So on your LinkedIn profile, you mentioned that you are, I don’t know what the word was that you used, but something to do with superintelligence, AI superintelligence. So what is it that you are doing, and what is your vision of how AI superintelligence can be tapped into?  It’s a very long topic. But to start off with, we used the old form of AI, which is a lot of regression, a lot of statistics, a lot of big data learning, and a lot of neural networks, if you felt fancy. And then LLMs became a huge thing. And we launched AiHello probably six or seven years ago. LLMs became a big thing two or three years ago. And it was pretty fancy. It was very good. It made life easy for us. But we cannot use it within AiHello to give it to clients, primarily because LLMs start hallucinating once you go past a certain context. The problem with hallucination is that it exponentially becomes larger and larger. Because if the previous thesis is wrong, if your previous hypothesis is wrong, then it builds on top of it, and it builds the wrong things.  Hallucination exponentially becomes worse. And when it comes to finance, when it comes to ads, and when you’re working with sensitive data, this can be catastrophic. So you cannot use these large language models for finance, for situations where you need precise data, and especially when you have lots of context. It’s going to lose the context of the first part. Just because you mentioned something at the start of the conversation doesn’t mean it’s not important. It is critical. As humans, we understand what is the most critical part of a conversation, and then we keep that in mind. But LLMs, because of context limitations, just keep on going and start hallucinating.  So a few months ago, we came up with the idea that we could use something like a large language model, but not based on the transformer model. And we could base it on data so that there is almost zero hallucination. So instead of building weights, we build it based on data. And we launched this. We don’t use it on AiHello, but we decided to use it on an email service because we have a lot of emails. We process a lot of emails for clients. We process a lot of emails for specialists. So we could use the zero-hallucination approach within emails, and if it is successful, then we can put it into AiHello.  And we can, of course, release it as an API as well. So this is going to set the basis of artificial superintelligence because what is stopping us right now from reaching or breaching that wall of artificial superintelligence is this hallucination. And of course, there is also logic. LLMs are pretty stup*d. They don’t understand. You can teach them, they learn, but they do not question what you teach them. They always take it on blind faith.  Yeah. Wow. That is genius. I love it. You are going to un-hallucinate AI. And if it stops hallucinating, essentially it becomes a lot more powerful and scalable. AI becomes scalable, or this whole process becomes scalable. That’s fascinating. So your ‘Why’, your mission, is to empower all these people to run their businesses. Do you have a framework for this that you could describe in three to five steps? How do you get someone up and running with their own business on an e-commerce platform? Or do you have any other framework that you could share with the audience? Something simple that they may be able to benefit from? One of the caveats of using AI is that it needs a lot of data. So if you’re just starting out with your e-commerce business, you need to put more of your human intelligence, more of your gut instinct, more of your thoughts, and more of your emotions into building it out. And once you have built up enough data, then you can put it into AiHello and start automating it. So what I would say, if you’re starting an e-commerce business, is hire a specialist who can help you launch off the ground.  Do a bit of the hypothesis work, do a bit of the analysis, and then come to AiHello and start automating it. You can only start automating once you have a good idea of how things work for you. And finding how things work for you is something you need to do on your own. It’s like you can’t start running, or you can’t start driving a car, until you learn how to crawl and until you learn how to walk.  Okay. So basically, it’s the age-old innovation thing that you have to innovate something on your own, and then you can scale it with AI. That is correct.  Yeah. So let’s say I came up with some kind of formula, concept, or product that is currently not being promoted, and I believe it would work. Or maybe I’ve already tested it and I want to scale it. I want to get on Amazon and sell it there. What can you do for me? What are the steps for me to be successful with AiHello’s help? So the first thing when you select a product, is: what are the keywords for it? What keywords do you use for that product? The second would be: what are the bids for that product? For each keyword, what is the right bid to put up? And then you have other things like budgeting. Do you change the bid depending on the time of day? Do you change the bid in total? Those are the things that you need to keep adjusting continuously.  With AiHello, we automatically harvest the right keywords for your product. We change the bid. We optimize the bid. We also do dayparting, where you can change the bid depending on the time of day. So there are different things that you can use AI for. You could certainly do all of it manually, but it’ll probably take you days or weeks to do what AI can do in a couple of minutes.  So a couple of minutes. But doesn’t the AI also need traffic data to be able to define things?  Yeah. So one of the other things about AiHello is that, because we have the wisdom of crowds, if you come up with a keyword, we know exactly how that keyword is going to perform. As you say, you have the wisdom of crowds. Can you extrapolate what you’ve experienced with other products and other customers onto a new product that doesn’t yet have a lot of traffic? Is this what you mean by the wisdom of crowds? Or what do you mean by the wisdom of crowds?  Let me give you an example. Let’s assume you want to sell coffee, and you go to our platform and say, “This is my product. It’s coffee. Help me sell it.” So what we do is, we know this is coffee. What are the keywords around it that are going to help sell it? Because we’ve sold other coffee products, we know that organic coffee sells well. We know coffee in the morning sells well. Black coffee sells well. Caffeine sells well.  And we also know, based on the previous performance of other keywords, what a good bid is for each keyword. If you don’t know the keywords, then of course you have to spend time researching them. And if you don’t know the bids, then you have to spend time researching what bid to put in. But we do all the research for you, and you put it in. And the second part, the bigger part, is that if the bid doesn’t work out, if you’re not selling, then we increase the bid automatically. If you are losing money, then we decrease the bid automatically. So that bid optimization is a critical part of AiHello.  Yeah. We use Amazon ads to promote my books. And yes, it takes a lot of skill to find the keywords, eliminate the negative keywords, adjust the bids, have the right bids, and avoid overspending or underspending. But Amazon also does much of the machine learning. So what is it that Amazon does, and what is it that you have to do? And why doesn’t Amazon do what you have to do?  The most critical piece of information to keep in mind is that your aims and objectives are the opposite of Amazon’s aims and objectives. Amazon’s aim is to make money, and your job is to make money. You don’t care if Amazon makes money or not, and Amazon doesn’t care if you make money or not. So when you put up a bid, when you run ads, Amazon will maximize that ad spend, whatever it is. In some ways, it’s like a casino.  You go to a casino, and the job of the casino is to win money from you, and your job is to win money from the casino. Ads have become a lot like gambling nowadays. You throw money into it. You expect to make money. Ninety percent of people lose money, and they give up. And Amazon always finds fresh sellers to move on. You cannot depend on Amazon because Amazon is not on your side.  Yeah, that makes perfect sense. Yeah, I always thought that on some platforms it was really difficult to make money with ads. Facebook, I think, is so competitive that it’s probably very difficult to make money. I know a lot of people who have spent a lot of money on Facebook, but I don’t know very many who have figured out a formula that continues to work. Okay. So you’ve helped someone find their keywords, the right bids, and how to adjust those bids. But what we’ve found is that at some point, ads die, and then we have to switch things up. It actually happens quite frequently that you have to create new campaigns and new ads. So what’s the dynamic there? How do you optimize so that you’re not still supporting ads that don’t work anymore, and you switch at the right point?  So when we say ads, it’s not technically the campaigns. A campaign is just a container for all of your ads. You have products inside it, and you have keywords inside it. So a campaign is made up of products and keywords. And the question is, when you say ads die, did the keywords die? Then you need to add new keywords, right? You always have to keep adding new keywords and testing new keywords. It’s a continuous job of trying to find the right keywords for your book or your product, and then optimizing the bids constantly to make sure that you’re profitable.  You have to make sure that your ads don’t die because of a lack of fresh keywords. And of course, there’s always a limit to the number of keywords you can add because each product has a limited number of keywords that people are searching for. Maybe there’s a long-tail keyword that’s going to make money, but there’s not enough search volume. Or maybe there’s a high-volume search keyword, but it’s not profitable for you. So you have to figure out what the right strategy is for you. Eventually, if your product is good, you’ll make money. If your product is not good, you won’t make money. That’s the bottom line. With ads, you quickly find out if your product…  So essentially, it’s a cyclical thing. So you find the keywords, you figure out the right bids, you adjust the bids, and then you have to find new keywords and keep doing this.  Yeah.  So why do keywords go stale? Do people not search for certain things anymore?  There could be multiple reasons for it. One reason is that a competitor has come in and taken your search volume. And you have to know: are you losing search volume? Are you gaining search volume? Has your search volume dropped off? The second reason is that people are not searching for that keyword anymore. Is it out of fashion? The third is: are you underbidding? Is the bid too low? Again, you would know by the number of impressions. Have the impressions dropped off?  If the impressions have dropped off, is it because of a competitor? If it’s not because of a competitor, are people searching less? Are your bids too low? If the search volume is the same, are people clicking less? Why are they clicking less? Is it your images? Is it your product? Is your product no longer in fashion? I mean, I don’t know. Maybe a few months ago, fidget spinners were really in fashion, and nowadays no one uses them. So those things go out of fashion.  Yeah. The spinners, I remember. They’ve been out of fashion for a while.  Yeah.  Yeah, that’s fascinating. So it’s a never-ending cycle of innovation and figuring out what works and what doesn’t work. So let me ask you this: What drives growth in your business?  Most of the growth is… There are different ways to put it. Four years ago, we used to create a lot of blogs. We used to create lots of content. We used to create lots of YouTube videos. And then ChatGPT came along. If you ask kids now, “Do you Google that?” They don’t know what Google is. They really don’t know what Google is. And that’s not a cliché. It’s surprising. They’ll be like, “What Google?” Everything goes through ChatGPT.  So for us, growth went from Google to ChatGPT. And we didn’t spend enough time optimizing for LLMs on our site. So what drove growth before was blogs and YouTube. And what drives growth now is large language models like ChatGPT and Claude. People just ask ChatGPT, “What do I do about this on Amazon?” It recommends solutions, and then we go through them.  So how do you leverage large language models or AI applications?  This was one of the biggest boosts to our company. We managed to set the processes right. We managed to create the templates. We managed to bring structure to our company. Development work has become ten times faster. The turnaround is ten times faster. We’re able to release features quickly. We’re able to find bugs in our existing code quickly. There are a lot of things going on. If I were to say that our company is no longer the same company it was even a year ago, that would not be an exaggeration. It would be the truth. What we were a year ago is not at all what we are right now.  So in what way did you change? Is it coding that accelerated and changed everything? I mean, in what other ways did you change as a company?  So the code is all done with AI first. Our developers use AI. They put in the prompt, they check the results. There is a second developer who checks whether everything is okay and whether everything is done. And then finally there’s QA, and then we push it to staging. We used to do roughly one-month or forty-five-day sprints. Now we do weekly sprints. So it has gone four times faster. The biggest hurdle for us was managing clients and how we manage them. We never had any structure.  So we talked a lot with ChatGPT. We talked a lot about what the right way was to bring structure and accountability into the system. We managed to set up all the software required for accountability. It helped us fix those issues. It created structure. It created accountability for all the people, and then we implemented that. Finally, the last one, which was the most debatable, is that we require a lot of content. We require a lot of graphics. We require a lot of videos for clients on Amazon. I actually went to buy something on Amazon a few days back, and what was puzzling was that when I zoomed in on the images, you could see they were AI-generated because they all had these silly AI mistakes—spelling mistakes, random words.  So almost everything on Amazon right now, all the images, are kind of AI-generated. It’s hard to blame them. We ourselves use AI for a lot of the images. We make sure we don’t have the silly mistakes, but we do use AI as well. So the turnaround time for graphics is faster because of AI as well. Though some clients do complain that they don’t like AI-generated assets. And if a person looks a bit too AI-generated, they just reject it outright. So that is the most debatable part of it. But overall, our company is called AiHello. It’s AiHello. And if we don’t say hello to AI, then we’re not AiHello.  Yeah. Love it. I love the head and the one arm.  Yes.  The hello, and that’s it.  Yeah.  So what is one thing that you’re actively trying to figure out in your business right now? We are a remote-first company, and I’m struggling to bring about accountability among all the team members. We do have a good number of employees. Ninety percent of our employees are good. Ten percent still have accountability issues. And for me, that is a bit of a hurdle. It is a bit of a challenge to push those people who are dragging their feet about AI. Yeah. Because they are not comfortable with AI. They want to do what they are good at and don’t want to do something new.  There is also a bit of hesitation that they might lose their jobs because of AI, although we’re not planning to let go of anyone. Rather, we are hiring more people because we’re able to grow faster. There is an old saying that companies won’t go extinct because of AI, but companies that don’t use AI will go extinct because of AI. Because we are using AI a lot, there is a chance for us to scale, for us to expand significantly. And I want to tap into this advantage and grow. I want to hire more people, and I want to grow. I don’t want to let people go.  So this is a very good opportunity. You hear about Coinbase letting people go. You hear about Facebook letting people go because of AI. And I think those are all nonsensical excuses. Those companies are not growing very well, and they are blaming AI for letting people go, which I think is absolutely nonsensical. There is a very good opportunity for people to grow and for companies to grow using AI and increase their hiring. If you’re letting people go because of AI, it’s just a nonsensical excuse.  So what do you think is the mental hang-up for people? What prevents better AI adoption or faster AI adoption? A long time ago, when computers were being introduced into many industries, I remember there were huge protests because people thought computers would take away jobs. And it did happen. People did lose jobs because of computers. There were many people pushing papers who lost their jobs. And a lot of people refused to learn about computers because they said, “This is nonsensical. I can do it better by hand.” Can you imagine telling people right now that it’s better to do things by hand than to use a computer?  I mean, if you want to do calculations, please don’t use Excel or Google Sheets. Use a pen and paper and tell me you can do it better. It would be absurd to think that way. But at that time, people really did have the mentality that it was better to do things by hand than with Excel. Now, the AI revolution is probably a thousand or a million times bigger than that. And you can drag your feet. There will always be people who drag their feet and say, “I can do it better. AI is just nonsensical.” And sure, some of that is true. But the overwhelming majority of tasks are going to be done extremely well with AI.  And it’s not just large language models. It’s everything. Regression analysis, data analytics, big data analytics, forecasting, calculations. I’m not even talking about transformer models. I’m talking about everything related to AI. So much can be automated and done by AI that if you’re not involved with it, you’ll get left behind, just like the people who didn’t use computers. Do you feel like people have to be highly educated to be able to use AI? Or can people with less formal education benefit from it as well?  I don’t think it has anything to do with education. I think the learning curve for AI is smaller than the learning curve for computers. If you’re already using computers, you can just install a command-line interface and have things running. Actually, you can go to ChatGPT and ask some questions, and you can build something. But if you want to build serious applications, you can use a command-line interface and build them out. I think the learning curve is probably just a couple of hours to become proficient with these tools. I’m thinking more about this: As AI tools develop and take many of the routine, repeatable tasks off our shoulders, doesn’t that mean we will spend more of our time on high-level thinking and orchestration? And won’t that require some kind of mental ability to do that? It requires you to understand context, understand the implications of things, and be able to connect the dots. So that’s what I mean. The people who can really use AI tools have this higher level of awareness and thinking. They can combine ideas and create new things. But are there AI tools that people with less advanced analytical skills can also use? Absolutely. And you’re 100% right. You’re 101% right. This is what I’ve been advocating for a very long time. Don’t spend your time doing mundane, repetitive daily activities that can be automated. Let AI handle them. You should focus on the things AI cannot do right now, which is human-level intelligence: Strategizing. Planning. Working on the bigger-picture tasks. So you’re 100% right, and that’s the direction we should be moving in. And this brings me back to the point I made earlier: You should do what you love. The things you don’t love, the repetitive tasks, should be done by AI.  Yeah. Love it. So what is your vision, ultimately, for AiHello?  So my vision for AiHello goes beyond AiHello. We have something called HalZero, which is the engine we want to put behind AiHello. It’s a zero-hallucination LLM. And we are working toward making it happen. We plan to release an API for it soon. If it does happen, then we would probably have a model that can take in data and answer general-knowledge questions with zero hallucination. And we’re building it based on how the human brain works. The human brain is not one-dimensional. ChatGPT is one-dimensional. Transformer models are one-dimensional.  You give them data, they run it through the transformer model—the encoder and decoder—and then they give you an answer. But the human brain is built in layers. What we call the lizard brain sits at the base, and as you go higher, things become more and more complex. So the brain is information and action, and everything is filtered through it. Then we act on the filtered result. Machine learning models right now do not have these kinds of filters. They have something similar, which is called chain of thought, but that’s really thinking out loud. This kind of reasoning should exist within the latent space of the machine learning model. It should be built into the model itself.  I’ll give you an example. If you had been taught all your life that the sun is green, and tomorrow you woke up in Virginia, went outside, and saw that the sun was yellow, you’d say: “Oh my God, I’ve been lied to all my life. The sun isn’t green.” You would question what you had been taught based on a single observation. But if a machine had been trained for years that the sun is green, and then it saw that the sun was yellow, it might conclude: “The sun is wrong today because I’ve been taught that the sun is green.” The real test of intelligence is this: Can it question its training data? And the answer is no. It won’t, because it has been trained on that data. It has been trained on those tokens.  Yeah. So that’s AI superintelligence? The ability to question the training data?  That is correct. Yeah. So we build it based on connections. How strong is this connection? How many people have stated this fact? What is my own observation? Which observation is stronger? There is always conflict. In the human brain, there is always a conflict between what people say and what we think. Then our logical brain chooses what is usually the best answer. That is how we have a collective consciousness. We also have a personal consciousness. We always have to decide which one is best.  Love it. Well, that’s great. So if you’re running a business and you need to sell a product, and you want to figure out how to be successful on Amazon, how to leverage your ads, and how not to overspend, where should you go? How can people get in touch with you, Ganesh, and your team? And what’s the first step for listeners?  You can send me an email at ganesh@aihello.com. You can connect with me on LinkedIn. I’m always available, and I’m happy to have a chat with you.  All right. So if you’re listening out there and you’re in e-commerce, or you want to get into e-commerce, and you don’t know how to leverage all the tools that are out there, don’t forget: Amazon is in the business of making money, not necessarily making your business profitable. So you can use AiHello to help you. Reach out to Ganesh on LinkedIn and get your team involved. And if you enjoyed listening to this episode, make sure you check back every week because I have successful entrepreneurs sharing their ideas—or at least some of the good ones—with you. So thanks, Ganesh, for coming.  Thank you, Steve.  And thank you for listening. Important Links: Ganesh's LinkedIn Ganesh's website Ganesh's email: ganesh@aihello.com

Beth breaks down Max Tegmark's 12 futures framework from Life 3.0 — from AI extinction to human utopia — and explains why world leaders need to start picking which scenario humanity actually wants. #AI #ArtificialIntelligence #MaxTegmark #Life30 #AGI #Superintelligence #FutureOfHumanity #Extinction #Philosophy #Metaphysics #QuantumBombs #HumanCondition #SamAltman #Anthropic #OpenAI #TechOligarchs #Consciousness #FreeWill #Utopia #Dystopia #DigitalSurveillance

Sebastian Mallaby (@scmallaby) is the Paul A. Volcker senior fellow for international economics at the Council on Foreign Relations, a two-time Pulitzer Prize finalist, and the author of six books, including More Money Than God, The Power Law, The Man Who Knew, and The World's Banker. His latest book is The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence.This episode is brought to you by:Eight Sleep Pod Cover 5 sleeping solution for dynamic cooling and heating: EightSleep.com/TimAG1 Pro all-in-one nutritional supplement: DrinkAG1.com/TimWealthfront high-yield cash account: Wealthfront.com/Tim Wealthfront disclaimer: New clients get 3.30% base APY from program banks + additional 0.75% boost for 3 months on your uninvested cash (max $150k balance). Terms and conditions apply. The Cash Account offered by Wealthfront Brokerage LLC (“WFB”) member FINRA/SIPC, not a bank. The base APY as of 1/30/26 is representative, can change, and requires no minimum. Tim Ferriss, a non-client, receives compensation from WFB for advertising and holds a non-controlling equity interest in the corporate parent of WFB, which creates a conflict of interest. Individual experiences and outcomes will differ. Instant withdrawals may be limited by your receiving firm and other factors. Investment advisory services provided by Wealthfront Advisers LLC, an SEC-registered investment adviser. Securities investments: not bank deposits, not bank-guaranteed or FDIC-insured, and may lose value.*Timestamps[00:00:00] Start.[00:02:11] The twinkly eyed polymath who became Sebastian's next book.[00:06:55] Picking the next book project the way a great VC picks a startup.[00:09:41] Why God keeps crashing the superintelligence party.[00:11:13] Shane Legg's grainy 2009 prophecy — and the nervous giggle.[00:13:11] Ilya Sutskever burns an effigy.[00:13:54] Demis at 4 a.m., hunting God's algorithm.[00:18:43] Super-abundance, Mad Max, and the China shock lesson.[00:22:39] The kitchen debate with Geoff Hinton that flipped Sebastian.[00:24:06] Why a zero-percent chance of doom is indefensible.[00:24:52] Will Washington seize the labs? The Mythos wake-up call.[00:27:18] Anthropic's bull case, bear case, and a dead parent's letter.[00:33:24] Where Sebastian and Benedict Evans part ways.[00:38:16] Is the SaaS apocalypse overdone? One word: Palantir.[00:39:53] The AI friend you'll never switch.[00:41:56] Does Google win consumer AI by default?[00:44:45] Four cities, eight days: China actually talks safety.[00:47:28] A Cold War non-proliferation playbook for AI.[00:49:45] Did the chip export controls actually work?[00:51:49] Burned doves: why Washington swears China won't talk.[00:54:56] "By 2028, the race is over" — one lab boss' bet.[00:59:11] Inside Hikvision: toddlers, sensors, and US sanctions.[01:01:07] Bill Gurley's Uber bet: venture capital perfected.[01:05:18] Luke Nosek bear-hugs DeepMind into existence.[01:10:52] Thiel's heresy: never invest by committee.[01:11:59] How Founders Fund nearly fumbled the deal of the century.[01:14:30] Selling to Google for $650M: a secret British heist?[01:16:41] The Traitorous Eight, gardening leave, and the UK's to-do list.[01:20:55] Ender's Game: "That's really how I see myself."[01:23:42] Too dumb for Gödel, Escher, Bach? Maybe an LLM can help.[01:25:19] If not Demis or Sam, then Dario.[01:26:04] My royalties cliff — and what dropped in late 2022.[01:27:47] Lila Sciences and the labs that run themselves.[01:31:13] Sebastian's billboard: "Prepare your mind."[01:35:14] The one thing Sebastian will never outsource to AI.[01:40:09] Parting thoughts.For show notes and past guests on The Tim Ferriss Show, please visit tim.blog/podcast.For deals from sponsors of The Tim Ferriss Show, please visit tim.blog/podcast-sponsorsSign up for Tim's email newsletter (5-Bullet Friday) at tim.blog/friday.For transcripts of episodes, go to tim.blog/transcripts.Discover Tim's books: tim.blog/books.Follow Tim:Twitter: twitter.com/tferriss Instagram: instagram.com/timferrissYouTube: youtube.com/timferrissFacebook: facebook.com/timferriss LinkedIn: linkedin.com/in/timferrissSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of The Neuron, Corey Noles sits down with Mustafa Suleyman, CEO of Microsoft AI, at Microsoft Build 2026 to unpack Microsoft's next AI chapter: seven new MAI models, a push toward in-house model development, and the idea of Humanist Superintelligence.Mustafa explains how Microsoft is thinking about AI that can reason, code, generate images, transcribe speech, and power real products—without turning the future into a vague AGI race. The conversation gets into what “humanist” means in practice, why Microsoft is building models from the ground up, how AI agents may reshape work, and what it takes to keep increasingly capable systems useful, controlled, and aligned with human goals.You'll learn why Microsoft is investing in its own model family, how MAI-Thinking-1 and MAI-Code-1-Flash fit into the stack, why Suleyman frames superintelligence around human control, and what builders and operators should watch as agents move into real workflows.Sponsored by BeyondTrustCheck it out at: https://www.beyondtrust.com/products/identity-security-insights/assessment?campid=701Vw00000drII6IAMSubscribe to The Neuron for practical AI conversations with the people building what comes next.

Today I'm talking with Mustafa Suleyman, the CEO of Microsoft AI. This is a real burner of an episode. We covered everything from his approach to training new models to his criticisms of Anthropic talking about Claude as though it is conscious.  Of course, we also talked about Microsoft's relationship with OpenAI, how Mustafa is thinking about all the negative polling and political pushback around AI right now, and whether any of the consumer products are good enough to overcome it. Like I said, it's a burner. Read the full interview transcript on The Verge. Links:  Microsoft and OpenAI broke up — now they're ready to fight | The Verge Microsoft Build 2026: The 7 biggest announcements | The Verge Microsoft's first advanced reasoning AI is here | The Verge Microsoft's new ‘superintelligence' game plan is all about business | The Verge Here's how the new Microsoft and OpenAI deal breaks down | The Verge Microsoft AI chief says 18 months until white-collar tasks automated by AI | FT Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt and edited by Ursa Wright. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode: AI INDUSTRY & BUSINESSAnthropic confidentially files IPO prospectus with SECElon Musk Laid Out 602 Goals. We Counted How Many He Hit.'Disrupted or dead': AI is crushing a generation of startups built before ChatGPTAI SAFETY & POLICYDario Amodei: "Humanity is about to be handed almost unimaginable power"Trump signs AI safety order seeking voluntary review of new modelsPRIVACY & SECURITYHackers Simply Asked Meta AI to Give Them Access to High-Profile Instagram Accounts. It WorkedLarry Ellison: "Citizens will be on their best behavior"TECH INNOVATION & CULTUREMicrosoft's next-gen quantum chip cuts timeline to useful quantum computing"Nobody's making games for the retired people" — The underserved market for grey gamersWEIRD AND WACKYHoming pigeons navigate using magnetic macrophages — in their liversThe Google Pixel Watch 5 may have been spoiled by the creator of BorderlandsZuckerberg's superyacht quietly slips into Elliott Bay after days of hecklersTech Rec:Sanjay - Firecrawl Adam - Lovable for Project ManagementFind us here:sanjayparekh.com & adamjwalker.comTech Talk Y'all is a proud production of Edgewise.Media.

Geoffrey Hinton is an AI pioneer, a Nobel Prize winner, and a professor emeritus at the University of Toronto. Hinton joins Big Technology Podcast to discuss AI's rapid progress, why he believes today's systems already understand us, and why he thinks superintelligence may arrive sooner than many expect. Tune in to hear Hinton explain why the technology has advanced faster than he anticipated, and lay out the risks he believes society is not doing enough to address. We also cover AI-driven job loss, the limits of corporate self-regulation, Anthropic and OpenAI's safety challenges, emotional attachment to chatbots, information collapse, and whether future AI systems can be designed to care about humans. Hit play for a fascinating conversation with one of AI's founding figures about where the technology is heading and what it could mean for all of us. Join the Big Technology AI Summit in San Francisco on June 18: summit.bigtechnology.com --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

Sebastian Mallaby spent three years and 30+ hours interviewing Demis Hassabis in the back of a British pub to write The Infinity Machine, and the conversation uses that reporting to surface the most underexplored figure in AI. Demis founded the original AI lab in 2010, won a Nobel Prize, runs models that consistently top the leaderboards, and yet remains so unrecognized that Sebastian's own publisher worried no one would buy a book with his face on the cover.  The throughline is a paradox: Demis tried to prevent the AI race we're now all living through, and now finds himself one of its central protagonists. He used to believe a single lab could carry the safety burden to AGI; he now sees safety as a collective action problem only governments can solve. He hedged DeepMind's research bets across every promising direction, and as a result missed the two most consumer-defining moments in modern AI — ChatGPT and Claude Code. He nearly spun DeepMind out of Google with a secret $1B Reid Hoffman pledge backing him, but never used the leverage and stayed — and won a Nobel Prize the next year. The episode also zooms out to the structural forces shaping the race — why hyperscalers can't out-recruit concentrated-bet labs, why Sebastian gives OpenAI roughly 50/50 odds of being absorbed by next summer, why he thinks Anthropic should IPO right now, and what the personal histories between Demis, Elon, and Sam reveal about who actually trusts whom.   (0:00) Intro (2:04) Was the AI Race Inevitable? (4:03) The 2015 Safety Summit Backfire (7:15) Can Governments Actually Fix This? (9:26) How the World Misread DeepMind (11:27) Why Google Never Makes the Concentrated Bet (15:51) Project Mario: The Secret Spinout Plan (19:43) What Demis Actually Regrets (23:46) Venture Startups vs. Tech Behemoths (27:50) Controlling the Narrative (30:40) The Talent War and Hiring Brand (34:08) David Silver and the RL True Believers (38:21) Demis, Elon, and the Evil Genius Feud (42:39) Great Man Theory vs. Inevitability (45:00) What Demis Didn't Want Published With your host: @jacobeffron - Managing Director at Redpoint

Stay informed on current events, visit www.NaturalNews.com  - Food Scarcity and Health Outcomes (0:02) - Historical Context and Food Delivery Trends (2:49) - Essential Nutrients and Stockpiling (5:28) - Medicinal Herbs and Extraction Techniques (8:05) - Preparing for Food Shortages (12:22) - Storable Foods and Energy Independence (15:03) - The Rise of Superintelligence and Depopulation Agenda (16:09) - Trump's Compensation Fund for Government Weaponization Victims (25:57) - Challenges and Future Outlook (34:56) Watch more independent videos at http://www.brighteon.com/channel/hrreport  ▶️ Support our mission by shopping at the Health Ranger Store - https://www.healthrangerstore.com ▶️ Check out exclusive deals and special offers at https://rangerdeals.com ▶️ Sign up for our newsletter to stay informed: https://www.naturalnews.com/Readerregistration.html Watch more exclusive videos here:

One of the most common arguments you hear from company executives racing to develop super-intelligent AI is that it will cure cancer. It's an incredibly powerful and seductive promise.  If superintelligent AI really can cure cancer, then anyone who stands in the way of it, anyone who wants to slow it down — even because of its serious risks — is essentially letting people die. In fact, the biggest risk would be going too slowly. But what if a superintelligent AI isn't actually capable of solving cancer in the way it's been described? What if we're being sold a false promise to justify a dangerous race? That's exactly what our guest this week argues is happening. Dr. Emilia Javorsky is a physician, public health researcher, and director of the Futures Program at the Future of Life Institute. She's worked across scientific research, clinical trials, tech startups, and AI policy.   Emilia recently wrote a paper titled “How AI Can and Can't Cure Cancer,” in which she argues that the promise of superintelligence curing cancer falls apart under scrutiny.  Emilia lost a parent to cancer, so her criticism of this promise comes from a place of real concern, not cynicism. It also comes from her belief that AI can be really revolutionary for medicine, if we build it the right way. Your Undivided Attention is produced by the Center for Humane Technology. Follow us on X: @HumaneTech_ and subscribe to our Substack.RECOMMENDED MEDIA How AI Can and Can't Cure Cancer by Emilia JavorskyThe Emperor of All Maladies by Siddhartha Mukherjee RECOMMENDED YUA EPISODES Decoding Our DNA: How AI Supercharges Medical Breakthroughs and Biological Threats with Kevin Esvelt Forever Chemicals, Forever Consequences: What PFAS Teaches Us About AI Big Food, Big Tech and Big AI with Michael MossCLARIFICATIONS: Emilia's claim that “the doubling rate of medical knowledge has gone from 50 years in the 1950s down to 73 days” comes from an oft-cited 2011 paper from the NIH. However, this paper does not include any methodology for arriving at this claim. Emilia stated that we have yet to cure any complex, chronic disease in humans. However, we have been able to cure Hepatitis C, which is considered a complex infectious disease, and we have managed to effectively cure some types of Leukemia Correction: Tristan incorrectly paraphrased a quote from Charlie Munger about incentives. The actual quote is “The basic rule of incentives is you get what you were owed for. So if you have a dumb incentive system, you get dumb outcomes."     Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

John welcomes author Sebastian Mallaby to discuss his new bestselling book, “The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence.” Mallaby explains why Hassabis, the leader of Google's efforts in artificial intelligence, remains an obscure and under-covered figure compared with Sam Altman, Dario Amodei, and Elon Musk, the poster boys of the A.I. revolution; why, despite his relative public obscurity, Hassabis may prove more important in shaping our future than any of them; and whether he is, at bottom, the kind of person we should comfortable entrusting with such power. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Nick Bostrom saw the AI revolution coming before it was taken seriously. When he warned about superintelligence in 2014, AI risk was dismissed by mainstream academia and the public. Now, as AI reshapes the future of work and human purpose, he has moved from warning about its risks to exploring a future where AI solves everything, and humans are left searching for new meaning. In this episode, Nick shares how artificial intelligence could end human labor and what that means for purpose, entrepreneurship, and humanity's future. In this episode, Hala and Nick will discuss: (00:00) Introduction (02:35) Are We Living in a Simulation? (11:48) Moral Implications of a Simulated Reality (22:28) The Fermi Paradox and the Doomsday Argument (30:29) Is AI Bigger Than the Industrial Revolution? (38:26) Three Types of AI and How They Work (41:43) The Risks of Advanced AI Systems (49:15) Finding Purpose in a Solved World (57:26) Beating Boredom and Artificial Purpose (01:08:07) Entrepreneurship's Place in an AI-Driven Future Nick Bostrom is a philosopher and leading expert on artificial intelligence and existential risk. He is the founding director of the now-defunct Future of Humanity Institute at Oxford University and the bestselling author of Superintelligence and Deep Utopia. His work has shaped global conversations on AI safety, long-term human survival, and the future of advanced technology. Sponsored By: Indeed - Get a $75 sponsored job credit to boost your job's visibility at Indeed.com/profiting Shopify - Start your $1/month trial at Shopify.com/profiting. Quo - Run your business communications the smart way. Try Quo for free, plus get 20% off your first 6 months when you go to quo.com/profiting Experian - Manage and cancel your unwanted subscriptions and reduce your bills. Get started now with the Experian App and let your Big Financial Friend do the work for you. See experian.com for details. Intuit - Start paying bills the smart way, not the hard way. Learn more at QuickBooks.com/billpay Huel - Grab nutritionally complete meals you can drink. Get 15% off with code PROFITING at huel.com/PROFITING AT&T Business - Power your small business with reliable connectivity from AT&T. Switch today at business.att.com.  Fabric - Protect your family with term life insurance from Fabric by Gerber Life. Apply today in just minutes at meetfabric.com/profiting  ZocDoc - Stop putting off those doctors' appointments. Find and instantly book a doctor you love today at Zocdoc.com/PROFITING  Blinkist - Turn the world's best nonfiction books into quick 15-minute reads or listens. Grab your free trial plus an exclusive 30% discount at blinkist.com/profiting  Resources Mentioned: Nick's Book, Superintelligence: bit.ly/_Superintelligence  Nick's Book, Deep Utopia: bit.ly/DeepUtopia  Nick's Website: nickbostrom.com  Active Deals - youngandprofiting.com/deals  Key YAP Links Reviews - ratethispodcast.com/yap YouTube - youtube.com/c/YoungandProfiting Newsletter - youngandprofiting.co/newsletter  LinkedIn - linkedin.com/in/htaha/ Instagram - instagram.com/yapwithhala/ Social + Podcast Services: yapmedia.com Transcripts - youngandprofiting.com/episodes-new  Entrepreneurship, Entrepreneurship Podcast, Business, Business Podcast, Self Improvement, Self-Improvement, Personal Development, Starting a Business, Strategy, Investing, Sales, Selling, Psychology, Productivity, Entrepreneurs, AI, Artificial Intelligence, Technology, Marketing, Negotiation, Money, Finance, Side Hustle, Mental Health, Career, Leadership, Mindset, Health, Growth Mindset, ChatGPT, AI Marketing, Prompt, AI in Action, AI in Business, Generative AI, AI for Entrepreneurs, AI Podcast