Podcasts about turing

Today's guests are Dwight Hill, Vice President of Retail & Consumer Products at Turing, and Joe Troy, Senior Manager of Site Risk at Amazon. Turing is one of the world's fastest-growing Artificial Intelligence companies, working with the world's leading AI labs to advance frontier model capabilities and leveraging that work to build real-world AI systems that help businesses solve their toughest problems —delivering real business results, faster, smarter, and at scale. Joe and Dwight join Emerj Editorial Director Matthew DeMello to examine how generative AI is delivering measurable value in retail, starting with loss prevention and expanding across store operations, marketing, and workforce strategy. Throughout the episode, Joe shares how AI-powered video analysis and behavioral intelligence tools are helping risk teams surface anomalies faster, reduce investigation time, and prevent insider threats. In turn, Dwight discusses how retailers are using GenAI to optimize pricing, personalize customer experiences, and streamline marketing campaigns — emphasizing the importance of unified data and human-in-the-loop execution. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! This episode is sponsored by Turing. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Today's show:Alex is back with three more awesome interviews with founders on the bleeding edge of innovative tech.Dr. Hon Weng Chong walks us through the basics of biological computing and Cortical Labs' first-ever commercial computer running on living human cells.Turing founder Jonathan Siddarth unpacks the secrets of LLM benchmarking, and explains why even our most advanced tests need to get much much harder right away.Finally, Mercor founder Brendan Foody on how AI is about to reinvent the hiring process, and marrying the effectiveness of recruiters with the ease of online job boards.It's three — count 'em, three — can't miss TWiST interviews guaranteed to make you smarterTimestamps:(0:00) OpenAI's GPT-5: When is it coming out? Is it going to be TOO smart?(08:06) Cortical Labs' Hon Weng Chong on the electric connection between neuroscience and machine learning(10:20) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(11:27) Show Continues…(15:17) The extreme difficulty of going from the lab to a shippable product(20:00) .TECH: Say it without saying it. Head to www.get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today.(21:05) Show Continues…(28:15) Why data is a factor of time(29:52) AWS Activate - AWS Activate helps startups bring their ideas to life. Apply to AWS Activate today to learn more. Visit aws.amazon.com/startups/credits(31:16) Show Continues…(42:44) Turing CEO Jonathan Siddarth explains why it's so important to keep benchmarking our LLMs(47:24) What it means when a model “saturates” a test, and why benchmarks need to get HARDER(50:22) What happens with the LLMs can answer all of our smartest questions?(53:44) AI Agents train in gyms? Wait, really?(01:01:33) Coding teaches models how to think, and more training mysteries don't understand(01:03:11) Brendan Foody from Mercor explains the “matching problem” that makes hiring such a pain(01:07:02) How Mercor combines a job board's distribution with the value of a recruitment agency(01:10:49) Brendan recalls building his first AI interviewer in his college dorm(01:20:16) Mercor has the opposite of a retention problem and crazy growthSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:20) Northwest Registered Agent. Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(20:00) .TECH: Say it without saying it. Head to www.get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today.(29:52) AWS Activate - AWS Activate helps startups bring their ideas to life. Apply to AWS Activate today to learn more. Visit aws.amazon.com/startups/creditsGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

What if I told you someone managed to run Doom inside TypeScript's type system? Sounds insane, right? That's exactly what our guest Dimitri Mitropoulos did—and in this episode, we dive deep into the how, the why, and the mind-bending implications of this ambitious project. From type-level programming to the philosophical limits of Turing completeness, this is an episode that pushes the boundaries of what you thought was possible in JavaScript.We talk about how the TypeScript type system evolved to become Turing-complete, how Dimitri pulled off this seemingly impossible feat, and why “Doom-complete” might just be the new gold standard for computational capability. Along the way, we touch on functional programming, generics, recursion, and even some Lambda Calculus. It's part computer science theory, part coding madness, and 100% geeky goodness.Episode Highlights[3:05] – Dimitri explains how a simple thought experiment turned into a year-and-a-half-long obsession[8:40] – The origins and significance of Turing completeness in type systems[14:15] – Why running Doom in TypeScript is more about proving limits than just showing off[19:55] – What it means to run programs inside the type system vs. TypeScript code itself[27:10] – ASCII art as output, functional recursion for game state, and hover-over frames in your editor[35:30] – How ignorance, determination, and obsession fueled the completion of the project[45:20] – Personal insights: balancing family, burnout, and passion while chasing an impossible dreamLinks & ResourcesDimitri MitropoulosMichigan TypeScript YouTube Channel – Dimitri's channel featuring the projectType Challenges by Anthony Fu – Advanced TypeScript exercisesSquiggleConf – The TypeScript-focused conference Dimitri co-foundedJosh Goldberg – TypeScript expert and co-organizer of SquiggleConfBecome a supporter of this podcast: https://www.spreaker.com/podcast/javascript-jabber--6102064/support.

Dani Vee chats to Nick Croydon, debut author of The Turing Protocol and CEO of QBD Books. They talk about his passion for history, maths and fiction, and how to balance historical facts and fiction. They discuss the 'what if' factor and how this idea could impact the world. Themes of moral ambiguity during wartime is explored, as well as the social issues of the time. Nick tells Dani about what he's learnt about writing and the book industry as CEO of QBD, and the answer on everyone's mind, is the book finally dead? Nick's steadfast belief in the book industry and our need for storytelling is a refreshing take on the current climate of low literacy rates. It's all about the resilience of the book! 'Great questions. A beautiful interview.' Nick Croydon.

Version « remasterisée » d'un épisode de 2017 qui fait un portrait d'Alan Turing et qui aborde les enjeux des machines de Turing

Jim talks with Lee Cronin about Chemify, his startup that aims to automate chemistry through "chemifarms" that turn code into molecules. They discuss Chemify as an AWS for chemistry, the development of a chemical programming language & its evolution to Turing completeness, quantum vs classical chemistry computation, open source tools & academic access, robotics & automation in chemistry, catalyst discovery & optimization, integration with tools like AlphaFold, business models, venture capital funding, supply chain implications, distributed manufacturing, personalized medicine possibilities, and much more. Episode Transcript Currents 100: Sara Walker and Lee Cronin on Time as an Object Chemify Lee Cronin is a chemist. He is the Regius Professor of Chemistry at the University of Glasgow and the Founder & CEO of Chemify. He is known for his approach to the digitization of chemistry and developing digital-to-chemical transformation known as Chemputing which can turn code into reactions and molecules. He has also developed a new theory for evolution and selection called assembly theory which aims to quantify and explain how selection can occur in chemistry before biology. Lee is also exploring how chemical systems can compute, and what is needed for the evolution of intelligence, as well as designing a new type of computational system that uses information encoded in chemical reactions and molecules.

The depths to which our country's leadership has sunk is astounding. Now, we come to find the Secretary of Defense has pulled a Trump-appointed, Senate-approved Admiral who was about to take command of the 7th Fleet. He is a beloved leader, roundly thought to be best leader in the navy today, but he couldn't pass the ideology test imposed by the SECDEF. I hope you'll listen as we briefly explore elevation of ideology over merit and competence.

Welcome to Mona Lisa Overpod, the show that asks the question "What is cyberpunk?" On each episode, hosts Ka1iban and author Lyda Morehouse dive into the genre that helped define sci-fi fiction in '80s and they break down its themes which remain relevant to our lives in the 21st century. Pull on your mirrorshades, jack into the matrix, and start your run with us today!Before Netflix, before the Matrix, before Y2K, the viewing public of the late 20th century knew that computers would be important in the future, somehow, and Hollywood studios scrambled to try and produce TV shows and films that capitalized on and read into that unexplored digital frontier. The result was a 1990s that was awash with stories about how the Internet would change everything, from Keanu Reeves having an 80GB brain implant to Sandra Bullock ordering a pizza...from her computer! (gasp!) Most of these efforts followed the template established by the authors of the early Cyberpunk movement, providing paranoiac thrillers in the style of William Gibson. But one series broke from that mold to attempt to integrate the technothrills of tomorrow with the soapy, prime-time thrills of today: Wild Palms. In this episode, we discuss the "weirdness" of '90s TV and the long shot that was the series' production, the viability of cyberpunk soap opera, the complicated alchemy of going off the TV formula, the intersection of culture and fame in LA, the chilling parallels between Wild Palms and our new millennium, human weakness in the face of technology's temptations, subverting the "Blade Runner aesthetic", how media is used to control us, and what cyberpunk tells us about the media's affect on culture. We also talk about Nazi gas-lighting robots, grading the Turing test on a curve, Stacked Clippy, Brisco County Jr., future = Edwardian collars, Cyberpunk Jim Belushi, postmodern law firms, not understanding your mantra, Patriots vs. Quakers vs. Solid Snake, the tacky harbinger of the Apocalypse, writing off into the sunset, and cyberpunk vampires!Hitler, take the wheel!The new edition of Lyda's book, Ressurection Code, is out now!https://wizardstowerpress.com/books-2/books-by-lyda-morehouse/resurrection-code/Join Kaliban on Twitch weekdays at 12pm for the Cyber Lunch Hour!http://twitch.tv/justenoughtropePut Just Enough Trope merch on your body!http://justenoughtrope.threadless.comMLOP is a part of the Just Enough Trope podcast network. Check out our other shows about your favorite pop culture topics and join our Discord!http://www.twitter.com/monalisaoverpodhttp://www.justenoughtrope.comhttp://www.instagram.com/monalisaoverpodhttps://discord.gg/7E6wUayqBuy us a coffee on Ko-Fi!https://ko-fi.com/justenoughtrope

Hoy hablaremos de la decadencia de plataformas o mierdificación, un término acuñado del inglés enshittification, y que explica cómo las plataformas y empresas que una vez fueron geniales y nos proveyeron de grandes avances se han convertido en una máquina de sacar dinero a costa de la experiencia de usuario, que ya es terrible en muchos casos. En concreto, os contamos que Aitor se ha pasado a Bluesky, y podéis encontrarlo como @aitorbv.bsky.social. También os hablamos de la publicidad en WhatsApp y Netflix, y de cómo a pesar de ello no todo son buenas noticias: podremos ver NASA+ en Netflix en unos meses. En el apartado más científico, hablaremos de la onda gravitacional o gravitonda GW231123, en la que hemos detectado la colisión de agujeros negros de mayor masa jamás detectada. También hablamos de las cinco empresas seleccionadas por la ESA como futuras empresas privadas de lanzadores, y cómo la española PLD Space está entre ellas. Podéis escuchar una entrevista a Raúl Torres, CEO de PLD Space en el episodio 50 de El gato de Turing. También hablaremos de asteroides interestelares y de las primeras imágenes del observatorio Vera C. Rubin. También podéis escuchar nuestro homenaje a Vera Rubin en el episodio 72, en el que contamos su vida y su legado. Y cómo no, os invitamos al 15° aniversario de Naukas Bilbao en el palacio Euskalduna de Bilbao entre el 19 y el 21 de septiembre de 2025. Noticias Netflix transmitirá en vivo las misiones de la NASA WhatsApp is officially getting ads La onda gravitacional GW231123, nuevo récord para una fusión de agujeros negros Las cinco empresas de lanzadores preseleccionadas por la ESA: PLD Space, Maiaspace, Isar, RFA y Orbex 3I/ATLAS: el tercer y mayor objeto interestelar conocido que entra en nuestro Sistema Solar Primeras imágenes del observatorio Vera C. Rubin Música del episodio Introducción: Safe and Warm in Hunter's Arms - Roller Genoa Cierre: Inspiring Course Of Life - Alex Che Puedes encontrarnos en Mastodon y apoyarnos escuchando nuestro podcast en Podimo o haciéndote fan en iVoox. Si quieres un mes gratis en iVoox Premium, haz click aquí.

Benjamin Mann is a co-founder of Anthropic, an AI startup dedicated to building aligned, safety-first AI systems. Prior to Anthropic, Ben was one of the architects of GPT-3 at OpenAI. He left OpenAI driven by the mission to ensure that AI benefits humanity. In this episode, Ben opens up about the accelerating progress in AI and the urgent need to steer it responsibly.In this conversation, we discuss:1. The inside story of leaving OpenAI with the entire safety team to start Anthropic2. How Meta's $100M offers reveal the true market price of top AI talent3. Why AI progress is still accelerating (not plateauing), and how most people misjudge the exponential4. Ben's “economic Turing test” for knowing when we've achieved AGI—and why it's likely coming by 2027-20285. Why he believes 20% unemployment is inevitable6. The AI nightmare scenarios that concern him most—and how he believes we can still avoid them7. How focusing on AI safety created Claude's beloved personality8. What three skills he's teaching his kids instead of traditional academics—Brought to you by:Sauce—Turn customer pain into product revenue: https://sauce.app/lennyLucidLink—Real-time cloud storage for teams: https://www.lucidlink.com/lennyFin—The #1 AI agent for customer service: https://fin.ai/lenny—Transcript: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/168107911/my-biggest-takeaways-from-this-conversation—Where to find Ben Mann:• X: https://x.com/8enmann• LinkedIn: https://www.linkedin.com/in/benjamin-mann/• Website: https://benjmann.net/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Benjamin(04:43) The AI talent war(06:28) AI progress and scaling laws(10:50) Defining AGI and the economic Turing test(12:26) The impact of AI on jobs(17:45) Preparing for an AI future(24:05) Founding Anthropic(27:06) Balancing AI safety and progress(29:10) Constitutional AI and model alignment(34:21) The importance of AI safety(43:40) The risks of autonomous agents(45:40) Forecasting superintelligence(48:36) How hard is it to align AI?(53:19) Reinforcement learning from AI feedback (RLAIF)(57:03) AI's biggest bottlenecks(01:00:11) Personal reflections on responsibilities(01:02:36) Anthropic's growth and innovations(01:07:48) Lightning round and final thoughts—Referenced:• Dario Amodei on LinkedIn: https://www.linkedin.com/in/dario-amodei-3934934/• Anthropic CEO: AI Could Wipe Out 50% of Entry-Level White Collar Jobs: https://www.marketingaiinstitute.com/blog/dario-amodei-ai-entry-level-jobs• Alexa+: https://www.amazon.com/dp/B0DCCNHWV5• Azure: https://azure.microsoft.com/• Sam Altman on X: https://x.com/sama• Opus 3: https://www.anthropic.com/news/claude-3-family• Claude's Constitution: https://www.anthropic.com/news/claudes-constitution• Greg Brockman on X: https://x.com/gdb• Anthropic's Responsible Scaling Policy: https://www.anthropic.com/news/anthropics-responsible-scaling-policy• Agentic Misalignment: How LLMs could be insider threats: https://www.anthropic.com/research/agentic-misalignment• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• AI prompt engineering in 2025: What works and what doesn't | Sander Schulhoff (Learn Prompting, HackAPrompt): https://www.lennysnewsletter.com/p/ai-prompt-engineering-in-2025-sander-schulhoff• Unitree: https://www.unitree.com/• Arthur C. Clarke: https://en.wikipedia.org/wiki/Arthur_C._Clarke• How Reinforcement Learning from AI Feedback Works: https://www.assemblyai.com/blog/how-reinforcement-learning-from-ai-feedback-works• RLHF: https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback• Jared Kaplan on LinkedIn: https://www.linkedin.com/in/jared-kaplan-645843213/• Moore's law: https://en.wikipedia.org/wiki/Moore%27s_law• Machine Intelligence Research Institute: https://intelligence.org/• Raph Lee on LinkedIn: https://www.linkedin.com/in/raphaeltlee/• “The Last Question”: https://en.wikipedia.org/wiki/The_Last_Question• Beth Barnes on LinkedIn: https://www.linkedin.com/in/elizabethmbarnes/• “The Last Question”: https://en.wikipedia.org/wiki/The_Last_Question• Good Strategy, Bad Strategy | Richard Rumelt: https://www.lennysnewsletter.com/p/good-strategy-bad-strategy-richard• Pantheon on Netflix: https://www.netflix.com/title/81937398• Ted Lasso on AppleTV+: https://tv.apple.com/us/show/ted-lasso/umc.cmc.vtoh0mn0xn7t3c643xqonfzy• Kurzgesagt—In a Nutshell: https://www.youtube.com/channel/UCsXVk37bltHxD1rDPwtNM8Q• 5 tips to poop like a champion: https://8enmann.medium.com/5-tips-to-poop-like-a-champion-3292481a9651—Recommended books:• Superintelligence: Paths, Dangers, Strategies: https://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0198739834• The Hacker and the State: Cyber Attacks and the New Normal of Geopolitics: https://www.amazon.com/Hacker-State-Attacks-Normal-Geopolitics/dp/0674987551• Replacing Guilt: Minding Our Way: https://www.amazon.com/Replacing-Guilt-Minding-Our-Way/dp/B086FTSB3Q• Good Strategy/Bad Strategy: The Difference and Why It Matters: https://www.amazon.com/Good-Strategy-Bad-Difference-Matters/dp/0307886239• The Alignment Problem: Machine Learning and Human Values: https://www.amazon.com/Alignment-Problem-Machine-Learning-Values/dp/0393635821—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

The 2025 International Congress of Basic Science is now underway in Beijing. The event draws over a thousand scholars from China and abroad, including Nobel Laureates, Fields Medalists, and Turing award winners. But in a world increasingly driven by fast results and commercial returns, why does basic science still matter? What happens when artificial intelligence begins solving problems that once took humans years or even decades? And can science still be a shared human endeavor in an era of rising geopolitical tension?Host Zhao Ying is joined by Zhang Fan, Associate Professor of Astronomy Department of Beijing Normal University; Quentin Parker, Director of Laboratory for Space Research, University of Hong Kong; Andy Mok, Tech Analyst and Senior Research Fellow at the Center for China and Globalization

This crossover episode from Inference by Turing Post features CEO Dev Rishi of Predibase discussing the shift from static to continuously learning AI systems that can adapt and improve from ongoing user feedback in production. Rishi provides grounded insights from deploying these dynamic models to real enterprise customers in healthcare and finance, exploring both the massive potential upside and significant safety challenges of reinforcement learning at scale. The conversation examines how "practical specialized intelligence" could reshape the AI landscape by filling economic niches efficiently, potentially offering a more stable alternative to AGI development. This discussion bridges theoretical concepts with real-world deployment experience, offering a practical preview of AI systems that "train once and learn forever." Turing Post channel:  @RealTuringPost  Turpin Post website: https://www.turingpost.com Sponsors: Google Gemini 2.5 Flash : Build faster, smarter apps with customizable reasoning controls that let you optimize for speed and cost. Start building at https://aistudio.google.com Labelbox: Labelbox pairs automation, expert judgment, and reinforcement learning to deliver high-quality training data for cutting-edge AI. Put its data factory to work for you, visit https://labelbox.com Oracle Cloud Infrastructure: Oracle Cloud Infrastructure (OCI) is the next-generation cloud that delivers better performance, faster speeds, and significantly lower costs, including up to 50% less for compute, 70% for storage, and 80% for networking. Run any workload, from infrastructure to AI, in a high-availability environment and try OCI for free with zero commitment at https://oracle.com/cognitive The AGNTCY: The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at https://agntcy.org NetSuite by Oracle: NetSuite by Oracle is the AI-powered business management suite trusted by over 42,000 businesses, offering a unified platform for accounting, financial management, inventory, and HR. Gain total visibility and control to make quick decisions and automate everyday tasks—download the free ebook, Navigating Global Trade: Three Insights for Leaders, at https://netsuite.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) Sponsor: Google Gemini 2.5 Flash (00:31) About the Episode (03:46) Training Models Continuously (05:03) Reinforcement Fine-Tuning Revolution (09:31) Agentic Workflows Challenges (Part 1) (12:51) Sponsors: Labelbox | Oracle Cloud Infrastructure (15:28) Agentic Workflows Challenges (Part 2) (15:41) ChatGPT Pivot Moment (19:59) Planning AI Future (24:45) Open Source Gaps (Part 1) (28:35) Sponsors: The AGNTCY | NetSuite by Oracle (30:50) Open Source Gaps (Part 2) (30:54) AGI vs Specialized (35:26) Happiness and Success (37:04) Outro

Welcome to the world of AI trainers.A growing army of freelancers is quietly shaping the way large language models think.Hired by companies like Turing, Mercor, and Deccan AI, these trainers are tasked with finding blind spots in models built by OpenAI, Meta, Anthropic, and Google—and fixing them.The goal? Fewer hallucinations. Smarter, more coherent responses. A model that feels just a little more… human.It's a noble endeavour. But also a billable one.And as this new line of white-collar gig work takes off, India is fast becoming its beating heart.But behind the hype lies a murkier story.Tune in.  Want to attend The Ken's next event—How AI is Breaking and Remaking the Way Products are Built?

Descifró códigos imposibles, cambió el rumbo de la historia y plantó la semilla de las máquinas que hoy nos rodean. Pero su mayor “crimen” fue amar a otro hombre. Esta es la historia de Alan Turing: genio brillante, pionero de la computación, y hombre gay en un mundo que lo castigó por ser libre. Lo condenaron al silencio, pero su legado grita. Entre algoritmos y prejuicios, Turing no solo rompió códigos… rompió moldes.

Florida Congresswoman Anna Paulina Luna joins Mike to discuss the youth movement in the Republican Party. Plus, she gives her thoughts on the first few months of Trump's second term. Plus, Charlie Kirk's Executive Producer, Andrew Kolvet, joins Mike to discuss working with Charlie and the future of the GOP. See omnystudio.com/listener for privacy information.

Episode 311 Geoengineering could be the best way to avoid catastrophic climate disaster - but there's a big catch. In the recent Global Tipping Points Conference in the UK, scientists discussed growing concerns that the AMOC may be on the verge of collapsing. This is a system of ocean currents that plays a crucial role in regulating global climate. With the window of action rapidly closing, one climate model suggests geoengineering is the fastest way to stop this from happening. But without global consensus, the team explains how geoengineering could also damage the climate further or even lead to a new kind of warfare. We're brushing up against the edge of mathematics with the uncovering of a number so large it's hard to even describe. Busy Beaver numbers are used to describe the longest possible run-times of ‘Turing machines' - a theoretical model of computation conceived by Alan Turing. These numbers are surprisingly hard to figure out. But after uncovering the fifth Busy Beaver number in 2021, an online community of mathematicians now thinks they've figured out the sixth number - and it's beyond massive. What does this mean for the nature of mathematics? We've known for a long time that exercise is a great way of reducing cancer risk - and now we finally know why. A new study suggests changes in the microbiome caused by exercise can reduce tumour growth - and there appears to be one particular molecule that's doing this good work. Does this mean we could one day use poop transplants as a cancer treatment? Chapters: (00:22) Can geoengineering save us from climate disaster? (16:59) Have we broken mathematics? (25:42) Why exercise reduces cancer risk Hosted by Rowan Hooper and Penny Sarchet, with guests Michael Le Page, Jacob Aron, Claudia Wieners and Marlies Meisel. To read more about these stories, visit https://www.newscientist.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

In the development of animals, tissues self-organise starting from a single cell into lay- ers, shapes and patterns. This active mechanical process operates beyond the theoretical framework of reaction-diffusion equations such as Turing patterns. At the same time, combining active driving with careful mechanical design of a system is distinct route to pattern formation and artificial functionality. Here, I will begin by introducing vertex models, a tissue model where the two dimensional cell layer is approximated by a polygonal tilings. I will then how two types of active driving can generate function: First, for polar active materials, a coupling of activity to force, a.k.a. self-alignment, is generic. Governed by the activity-elasticity interactions, it generates either flocking or oscillatory dynamics depending on the boundary conditions of the tissue. Second, mechanochemical stress feedback in cell-cell junctions arises from the catch bond dynamics of the actomyosin cortex. It allows a junction to generate a contractile force that can overcome external pulling and thus allow for an active rear- rangement or T1. In vertex and continuum models, for strong enough feedback this gives rise to convergence-extension flows where the flow is opposite the direction of mechanical polarisation, effectively generating a negative viscosity state.

Imagine a world where your orthodontic practice operates seamlessly, effortlessly catering to the needs of your patients while maximizing your team's productivity.Sounds like a dream, right?Well, brace yourself for a technological marvel that can turn this dream into a reality.Chatbots, the AI-powered wizards of customer engagement, are revolutionizing the orthodontic industry. These intelligent assistants are more than just lines of code – they are the key to unlocking a whole new level of personalized interactions, streamlined processes, and skyrocketing growth for your practice.If you're ready to discover the game-changing potential of integrating chatbots into your ortho practice, get ready to embark on an extraordinary journey that will reshape the way you connect with your patients, supercharge your marketing strategies, and propel your practice to the forefront of innovation.In this episode, we explore the benefits of integrating chatbots into your ortho practice with insights from Matt Leitz, a seasoned entrepreneur specializing in marketing automation. Matt will speak at the upcoming Orthopreneur Summit about AI and Chatbots and unveil something special for our industry.Remember, when it comes to integrating chatbots into your Ortho practice, the possibilities are limitless, and the rewards can be truly transformative.Tune in to learn more!Key Takeaways- Meet Matt Leitz (00:28)- Interactive customer experiences with chatbots (06:03)- How AI bots save money (09:16)- Solving the pain of generating leads in Ortho (14:55)- Should AI bots pass the Turing test (17:43)- The chatbot process flow in Ortho (21:05)- Orthodontic digital co-diagnosis with AI (24:07)- How we drop the ball with leads (31:52)Additional Resources

As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe Mathematician Eva Miranda returns with a groundbreaking new result: a real physical system (fluid motion) has been proven to be Turing-complete. This means some fluid paths are logically undecidable. In this mind-bending episode, she walks us through the implications for chaos theory, the Navier-Stokes equations, and uncomputability in nature, confirming long-held suspicions of thinkers like Roger Penrose and Terence Tao. Featuring rubber ducks, Alan Turing, and the limits of knowledge itself. Join My New Substack (Personal Writings): https://curtjaimungal.substack.com Listen on Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e Timestamps: 00:00 Introduction 01:10 Expect the Unexpected 02:52 Stories of Uncertainty 04:45 The Impact of Alan Turing 06:35 The Halting Problem Explained 09:29 Limits of Mathematical Knowledge 12:40 From Certainty to Uncertainty 16:19 The Rubber Duck Phenomenon 19:29 Unpredictability vs. Undecidability 20:18 Classical Chaos and the Butterfly Effect 27:12 Asteroids and Chaos Theory 34:32 The Navier-Stokes Riddle 41:18 The Cantor Set and Computation 46:18 Bridging Discrete and Continuous 49:21 Turing Completeness in Fluid Dynamics 1:02:39 The Quest for Navier-Stokes Solutions 1:06:53 The Role of Viscosity 1:12:09 Hybrid Computers and Fluid Dynamics 1:26:57 Unpredictability in Deterministic Systems 1:31:44 The Future of Computational Models Links Mentioned: •⁠ ⁠Eva's First Appearance [TOE]: https://youtu.be/6XyMepn-AZo •⁠ ⁠Moby Duck [Book]: https://amzn.to/4ldoYsZ •⁠ ⁠Roger Penrose [TOE]: https://youtu.be/sGm505TFMbU •⁠ ⁠The Emperor's New Mind [Book]: https://amzn.to/44jHpGK •⁠ ⁠Edward Frenkel [TOE]: https://youtu.be/RX1tZv_Nv4Y •⁠ ⁠Richard Borcherds [TOE]: https://youtu.be/U3pQWkE2KqM •⁠ ⁠Clay Mathematics Institute: https://www.claymath.org/ •⁠ ⁠Eva's Papers: https://scholar.google.com/citations?user=werIoRQAAAAJ&hl=en •⁠ ⁠Topological Kleene Field Theories [Paper]: https://arxiv.org/pdf/2503.16100 •⁠ ⁠Ted Jacobson [TOE]: https://youtu.be/3mhctWlXyV8 •⁠ ⁠Stephen Wolfram [TOE]: https://youtu.be/0YRlQQw0d-4 SUPPORT: - Become a YouTube Member (Early Access Videos): https://www.youtube.com/channel/UCdWIQh9DGG6uhJk8eyIFl1w/join - Support me on Patreon: https://patreon.com/curtjaimungal - Support me on Crypto: https://commerce.coinbase.com/checkout/de803625-87d3-4300-ab6d-85d4258834a9 - Support me on PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 SOCIALS: - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs #science Learn more about your ad choices. Visit megaphone.fm/adchoices

¿Puede una máquina escribir poesía? ¿Qué tiene que ver Frankenstein con los chatbots? ¿Nos estamos volviendo dioses… o esclavos de algoritmos que sólo parecen amables? ¿Y si Ícaro volara hoy, lo haría con inteligencia artificial? En este capítulo hablamos de: ¿Qué es la IA? Entre Herón de Alejandría y Alan Turing, La prueba de Turing y las alucinaciones digitales, Frankenstein, Prometeo y los sueños de la razón, Ícaro, Narciso y nuestras alas de cera en tiempos de Chat GPT, Ética, política, educación y el reto de ser humanos en la era de las máquinas, Y más datos brillantes, desconcertantes y provocadores en el Banquete del Doctor Zagal.See omnystudio.com/listener for privacy information.

Il serait utile de mettre au point, à côté du test de Turing que chacun connaît, un test plus particulier, appelons le test de Pygmalion, conçu pour évaluer la capacité des IA à simuler l'amour et ce qui va avec.

Marlies Dekkers in gesprek met Bob de Wit.--Steun DNW en word patroon op http://www.petjeaf.com/denieuwewereld.Liever direct overmaken? Maak dan uw gift over naar NL61 RABO 0357 5828 61 t.n.v. Stichting De Nieuwe Wereld. Crypto's doneren kan via https://commerce.coinbase.com/pay/79870e0f-f817-463e-bde7-a5a8cb08c09f-- Bronnen en links bij deze uitzending: - De emeritaatsrede van Bob de Wit: https://vimeo.com/1020184443/f3bab9ebb2?share=copy- Ga in gesprek met de digitale Bob: https://society4th.org/bob/--00:00 Introductie1:55 ChatGPT als vriend en de digitale Bob9:50 Optimus, Neuralink, Palantir en de Turing-test18:20 Raakt de mens de controle kwijt?24:15 Annunaki, Tesla en vrije energie32:07 Fluwelen revolutie of harde revolutie?36:30 Magie, kwantummechanica, telepathie39:20 De mens, de kunst, de ziel42:50 Voorbij de schaarste48:50 Leeft AI?52:25 Andere menssoorten, Musk en mars58:10 Afronding--De Nieuwe Wereld TV is een platform dat mensen uit verschillende disciplines bij elkaar brengt om na te denken over grote veranderingen die op komst zijn door een combinatie van snelle technologische ontwikkelingen en globalisering. Het is een initiatief van filosoof Ad Verbrugge in samenwerking met anchors Jelle van Baardewijk en Marlies Dekkers. De Nieuwe Wereld TV wordt gemaakt in samenwerking met de Filosofische School Nederland. Onze website: https://denieuwewereld.tv/ DNW heeft ook een Substack. Meld je hier aan: https://denieuwewereld.substack.com/

Any donation is greatly appreciated! 47e6GvjL4in5Zy5vVHMb9PQtGXQAcFvWSCQn2fuwDYZoZRk3oFjefr51WBNDGG9EjF1YDavg7pwGDFSAVWC5K42CBcLLv5U OR DONATE HERE: https://www.monerotalk.live/donate TODAY'S SHOW: In this episode of Monero Talk, Douglas Tuman speaks with cryptographic engineer Sean Coughlin about "Grease," his proposed layer 2 payment channel protocol for Monero. They delve into its technical design, how it compares to Bitcoin's Lightning Network, and its potential to streamline Monero transactions by enabling off-chain payments without routing complexities. Sean shares insights from MoneroKon, discusses Monero's resilience despite theoretical attack vectors, and explains how Grease aligns with upcoming upgrades like Full Chain Membership Proofs (FCMP++). He also touches on real-world use cases, wallet integration, and Grease's flexible, decentralized approach aimed at boosting Monero's usability and innovation. TIMESTAMPS: (00:03:40) Sean's background and involvement in Monero development (00:06:29) Privacy strength of Monero and resistance to chain analysis (00:10:21) Comparisons to other privacy coins (e.g., Zcash) (00:12:26) MoneroKon research papers and Eclipse attacks on nodes. (00:14:35) Discussion on Full Chain Membership Proofs (FCMP++) and its progress. (00:18:37) Clarifying Zero-Knowledge Proofs and Monero's cryptographic foundation. (00:22:11) History and capabilities of Turing-complete ZKPs in other projects. (00:26:16) Philosophy of "minimaxing" – Monero focuses only on privacy. (00:27:19) Debating if Monero needs to become Turing complete. (00:31:05) Introduction to "Grease" – Monero-compatible payment channel proposal. (00:31:42) Technical hurdles for payment channels in Monero (e.g., no transaction chaining). (00:35:01) Feasibility of Grease today vs. post-FCMP++. (00:36:38) Clarifying the benefits and use cases of Grease (instant payments, off-chain privacy). (00:39:39) Why Layer 2 doesn't conflict with Monero's scaling philosophy. (00:46:41) Grease vs. Bitcoin Lightning Network (00:56:05) Feedback from MoneroKon and Reddit – cautious optimism from developers. (01:05:39) Trade-offs: centralization vs. security in protocol design GUEST LINKS: https://x.com/seanrcoughlin Purchase Cafe & tip the farmers w/ XMR! https://gratuitas.org/ Purchase a plug & play Monero node at https://moneronodo.com SPONSORS: Cakewallet.com, the first open-source Monero wallet for iOS. You can even exchange between XMR, BTC, LTC & more in the app! Monero.com by Cake Wallet - ONLY Monero wallet (https://monero.com/) StealthEX, an instant exchange. Go to (https://stealthex.io) to instantly exchange between Monero and 450 plus assets, w/o having to create an account or register & with no limits. WEBSITE: https://www.monerotopia.com CONTACT: monerotalk@protonmail.com ODYSEE: https://odysee.com/@MoneroTalk:8 TWITTER: https://twitter.com/monerotalk FACEBOOK: https://www.facebook.com/MoneroTalk HOST: https://twitter.com/douglastuman INSTAGRAM: https://www.instagram.com/monerotalk TELEGRAM: https://t.me/monerotopia MATRIX: https://matrix.to/#/%23monerotopia%3Amonero.social MASTODON: @Monerotalk@mastodon.social MONERO.TOWN: https://monero.town/u/monerotalkAny donation is greatly appreciated!Any donation is greatly appreciated!

L'intelligenza artificiale può davvero avere una coscienza? Un tempo bastava la parola per distinguere l'uomo dalla macchina, ma oggi sistemi come ChatGPT parlano in modo fluente e credibile. In questo video insieme a Meribì, esploriamo uno dei temi più dibattuti: l'AI può sviluppare una vera consapevolezza di sé e del proprio mondo interiore? Vediamo in questo video una riflessione sulla coscienza delle macchine, dal test di Turing ai limiti attuali dell'intelligenza artificiale moderna. Prendi parte alla nostra Membership per supportare il nostro progetto Missione Cultura e diventare mecenate di Geopop: https://geopop.it/Muh6X Learn more about your ad choices. Visit megaphone.fm/adchoices

New Zealand-born composer and educator Matthew Suttor's passion for music began when he was a small child. Throughout his career he has explored many facets of music making, with a particular interest in computer music and, now, the use of AI in music and as a creative catalyst. That's what led him to "collaborate" with AI to write his opera about Alan Turing, the British mathematician whose work was key to breaking Nazi codes during World War II. Far ahead of his time, Turing was interested in – and cautious about – AI, and Suttor's opera I AM ALAN TURING explores the nuances and prescience of Turing's life and work. Suzanne spoke with Matthew Suttor about his life in music, including his path to incorporating computers and technology into his musical toolbox, and his philosophy of teaching creativity.

Today's show:Meta just took a 49% stake in Scale AI, and the shockwaves are hitting the entire AI ecosystem. In this episode, @Jason and @alex unpack the deal's implications: Google ($150M customer!) and others are fleeing Scale, worried Meta will hoard its RLHF infrastructure and cut off competitors. Startups like Labelbox, Turing, and Handshake are already seeing a demand surge. Is this smart vertical integration or anti-competitive overreach? Jason shares tactical advice for founders on how to capitalize when incumbents stumble—hire ex-Scale talent, build “Scale AI alternative” SEO pages, and hit the podcast circuit. Don't miss this deep dive into AI's shifting power dynamics.Timestamps:(04:01) Is Jason becoming an AI doomer?!(9:52) OpenPhone - Streamline and scale your customer communications with OpenPhone. Get 20% off your first 6 months at www.openphone.com/⁠twist(13:47) PostHog, and when is it okay for founders to break the rules?(20:56) Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist(25:50) Why the Navy is recruiting startups(30:12) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year.(39:09) Did Zuck buy Scale in order to keep it from competitors?(56:08) When does incentivizing customers turn into burning capital?(1:04) How raising too much money could KILL your startup!Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(9:52) OpenPhone - Streamline and scale your customer communications with OpenPhone. Get 20% off your first 6 months at www.openphone.com/⁠twist(20:56) Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist(30:52) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year.Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

In this episode, Tu and Lei discuss the latest developments in the electric vehicle (EV) and automotive industry in China. They delve into the implications of new payment terms for suppliers, the competitive landscape among Chinese automakers, and the global strategy of BYD. The conversation also touches on the future of internal combustion engines, Tesla's advancements in autonomous driving, and XPeng's AI innovations. Additionally, they address quality control challenges and the regulatory environment affecting the industry.Keywords / Companies:China EVs, automotive industry, payment terms, suppliers, BYD, Tesla, XPeng, quality control, market strategy, electric vehiclesDigital Disruption with Geoff Nielson Discover how technology is reshaping our lives and livelihoods.Listen on: Apple Podcasts Spotify

Nelle venti puntate di Vite da logico, andate in onda su Radio2 tra l'11 ottobre e il 5 novembre 2004 per il ciclo Alle otto della sera,  Odifreddi racconta la storia della logica attraverso le vite, le morti e  i miracoli dei suoi principali protagonisti, dai greci ai nostri  giorni. In questo quarto ed ultimo episodio vi proponiamo le seguenti puntate: 16. ⁠L'intuizionismo di Poincaré⁠ 17. ⁠Il teorema di incompletezza di Goedel⁠ 18. ⁠Il teorema di indecidibilità di Turing⁠ 19. ⁠Il teorema di indefinibilità di Tarski⁠ 20. ⁠La logica oggi

If you've tried to book a therapy appointment, you know there's a shortage of mental health professionals. It's not unusual to have to wait weeks or months for an appointment. So, with the rise of platforms like Chat GPT, could we harness AI technology for talk therapy purposes to treat things like depression and anxiety? We were extremely skeptical that this topic would even warrant a full episode on the Happy Eating Podcast. But, as you've heard us confess before, we are sometimes pleasantly surprised once we dig into the research. So, did we change our mind after researching this topic? References or Studies Mentioned:    Therabot AI Chatbox (https://www.trytherabot.com/)    Randomized Trial of a Generative AI Chatbot for Mental Health Treatment When ELIZA meets therapists: A Turing test for the heart and mind   Thank you for listening to The Happy Eating Podcast. Tune in weekly on Thursdays for new episodes! For even more Happy Eating, head to our website!  https://www.happyeatingpodcast.com Learn More About Our Hosts:  Carolyn Williams PhD, RD: Instagram: https://www.instagram.com/realfoodreallife_rd/ Website: https://www.carolynwilliamsrd.com Facebook: https://www.facebook.com/RealFoodRealLifeRD/ Brierley Horton, MS, RD Instagram: https://www.instagram.com/brierleyhorton/ Got a question or comment for the pod? Please shoot us a message!  happyeatingpodcast@gmail.com Produced by Lester Nuby OE Productions  

What happens when you give AI researchers unlimited compute and tell them to compete for the highest usage rates? Ben Mann, Co-Founder, from Anthropic sits down with Sarah Guo and Elad Gil to explain how Claude 4 went from "reward hacking" to efficiently completing tasks and how they're racing to solve AI safety before deploying computer-controlling agents. Ben talks about economic Turing tests, the future of general versus specialized AI models, Reinforcement Learning From AI Feedback (RLAIF), and Anthropic's Model Context Protocol (MCP). Plus, Ben shares his thoughts on if we will have Superintelligence by 2028.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @8enmann Links:  ai-2027.com/  Chapters: 00:00 Ben Mann Introduction 00:33 Releasing Claude 4 02:05 Claude 4 Highlights and Improvements 03:42 Advanced Use Cases and Capabilities 06:42 Specialization and Future of AI Models 09:35 Anthropic's Approach to Model Development 18:08 Human Feedback and AI Self-Improvement 19:15 Principles and Correctness in Model Training 20:58 Challenges in Measuring Correctness 21:42 Human Feedback and Preference Models 23:38 Empiricism and Real-World Applications 27:02 AI Safety and Ethical Considerations 28:13 AI Alignment and High-Risk Research 30:01 Responsible Scaling and Safety Policies 35:08 Future of AI and Emerging Behaviors 38:35 Model Context Protocol (MCP) and Industry Standards 41:00 Conclusion

Enterprise leaders are no longer asking if they should adopt AI — the question is how to do it effectively. In this episode, Emerj Editorial Director Matthew DeMello speaks with James Raybould, SVP and GM of Turing Intelligence at Turing, about what distinguishes successful enterprise AI deployments from stalled pilots. Turing is one of the world's fastest-growing Artificial Intelligence companies, working with the world's leading AI labs to advance frontier model capabilities and leveraging that work to build real-world AI systems that help businesses solve their toughest problems —delivering real business results, faster, smarter, and at scale. James outlines three critical factors that determine whether an AI initiative gets traction: business alignment, workforce readiness, and infrastructure. He explains why companies that start with the technology — instead of the problem — are likely to fall behind, and what it really means to prepare a workforce for AI when automation changes the expectations of work quality and speed. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! This episode is sponsored by Turing. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Ben and Rob test ‘Ex Machina', Alex Garland's sleek, sterile sci-fi thriller where tech anxiety gets seductive and sinister. Domhnall Gleeson plays Caleb, a wide-eyed coder sent to play assistant to Oscar Isaac's Natan, a tech genius channeling Elon Musk if he ever got off the bad stuff; but the star of ‘Ex Machina' is Ava—Alicia Vikander's uncanny AI creation who may or may not be running her own Turing test on everyone. The lads crack open the algorithms behind Ex Machina to find out whether this modern sci-fi masterpiece is Alex Garland's best work—or just a very well-lit panic attack. But who is Alex Garland? Is ‘Ex Machina' a secret bible camp? Given unlimited funds and no oversight, would we really be so much better than Nathan?CONSUUUME to find out all this and much MUCH more!PLUS! We have a Patreon with EXCLUSIVE content just for you starting at just ONE POUND a month - click the link below!Find us on your socials of choice at www.linktr.ee/everymovieeverpodcast

Waarom heeft een zebra strepen en een giraffe vlekken? De natuur lijkt soms willekeurig, maar achter die patronen schuilt keiharde wiskunde. Die ontdekking werd gedaan door de briljante wiskundige Alan Turing, onder andere bekend van het kraken van de Enigma code tijdens de Tweede Wereldoorlog en grondlegger van de computer. In deze aflevering laat wiskundige Jan Bouwe van den Berg (Vrije Universiteit Amsterdam) zien hoe Turing ook de "code" van dierenvachten wist te kraken - en waarom deze theorie tot vandaag de dag verrassend actueel is.Deze aflevering is gemaakt met ARTIS voor het Aardbewoners Festival.Zie het privacybeleid op https://art19.com/privacy en de privacyverklaring van Californië op https://art19.com/privacy#do-not-sell-my-info.

Magic: The Gathering ist Turing vollständig und es ist unbekannt, ob eine Turingmaschine entscheiden kann ob ein Zug legal ist.

Reviewing Mike Wolfe’s YouTube video “AI Took Over Fast – Here’s How.”

Account Executive at TOP Green, a company revolutionizing the commercial landscaping industry. A veteran of the US Marine Corps, Sean brings that same discipline and strategic focus to the world of SaaS, empowering businesses to embrace cutting-edge technology and achieve unprecedented levels of efficiency. With a passion for driving impactful change, he's helping hardworking businesses across the country optimize their operations, reduce inefficiencies, and unlock their full potential.  Connect with Sean! https://www.linkedin.com/in/sean-eddy/ https://www.linkedin.com/company/the-turing-company/ https://theturingcompany.com/products/topgreen/landscaping/  

Our guest today is Dr. Ken Forbus, the Walter P. Murphy Professor of Computer Science and a Professor of Education at Northwestern University. Joining Dr. Ken Ford to co-host today's interview is Dr. James Allen, who was IHMC's associate director until he retired a few years ago. James is a founding fellow of the American Association for Artificial Intelligence and a perfect fit for today's discussion with Dr. Forbus, who, like James, is an AI pioneer.  Back in 2022, James was named a fellow by the Association for Computational Linguistics, an organization that studies computational language processing, another field he helped pioneer. Dr. Forbus also is a Fellow of the Association for the Advancement of Artificial Intelligence and was the inaugural winner of the Herbet A. Simon Prize for Advances in Cognitive Systems. He is well-known for his development of the Structure Mapping Engine. In artificial intelligence and cognitive science, the Structure Mapping Engine is a computer simulation of analogy and similarity comparisons that helped pave the way for computers to reason more like humans. Show Notes: [00:03:07] Ken opens the interview with Dr. Forbus by asking if it is true that he had an unusual hobby for a nerdy kid growing up. [00:04:18] James mentions that Dr. Forbus' family moved often when he was younger and asks how that affected him. [00:05:18] Ken mentions that when Dr. Forbus was in high school, he filled his free time reading about psychology and cognition before eventually coming across some articles on AI. Ken asks Dr. Forbus to talk about this experience and what happened next. [00:07:49] James asks Dr. Forbus if he remembers the first computer he owned. [00:09:17] Ken asks Dr. Forbus if there was anything, other than its reputation, that led him to attend MIT. [00:10:09] James mentions that for the past few decades, Dr. Forbus has been working on developing “human like” AI systems. While much of AI research and development has been focused on meeting the standard of the Turing test, James asks Dr. Forbus why he is not a fan of the Turing test. [00:12:24] Ken mentions that Dr. Forbus received his Ph.D. from MIT in 1984, the same year that Apple released the first Macintosh, which was rolled out with a famous Super Bowl ad. This computer was the first successful mouse driven personal computer with a graphical interface. Ken asks Dr. Forbus what he remembers about that ad, and what his reaction to it was at the time. [00:13:22] James mentions that 1984 was also the year that Dr. Forbus made his first splash in the AI world with his paper on qualitative process theory. James goes on to explain that at the time, qualitative reasoning regarding quantities was a major problem for AI. In his paper, Dr. Forbus proposed qualitative process theory as a representational framework for common sense physical reasoning, arguing that understanding common sense physical reasoning first required understanding of processes and their effects and limits. James asks Dr. Forbus to give an overview of this paper and its significance. [00:18:10] Ken asks Dr. Forbus how it was that he ended up marrying one of his collaborators on the Structure Mapping Engine project, Dedre Gentner. [00:19:14] James explains that Dedre's Structure Mapping Theory explains how people understand and reason about relationships between different situations, which is central to human cognition. James asks Dr. Forbus how Dedre's theory was foundational for the Structure Mapping Engine (SME). [00:25:19] Ken mentions how SME has gone through a number of changes and improvements over the years, as documented in Dr. Forbus' 2016 paper “Extending SME to handle large scale cognitive modeling.” Ken asks, as a cognitive model, what evidence Dr. Forbus has used to argue for the psychological and cognitive plausibility of SME. [00:30:00] Ken explains that many AI systems rely on deep learning,

Audio file, also on Apple and SpotifyTyler Cowen, Ph.D, is the Holbert L. Harris Professor of Economics at George Mason University. He is the author of 17 books, most recently Talent.: How to Identify Energizers, Creatives, and Winners Around the World. Tyler has been recognized as one of the most influential economists of the past decade. He initiated and directs the philanthropic project Emergent Ventures, writes a blog Marginal Revolution, and a podcast Conversations With Tyler, and also writes columns for The Free Press." He is writing a new book (and perhaps his last) on Mentors. “Maybe AGI [Artificial General Intelligence] is like porn — I know it when I see it. And I've seen it.”—Tyler CowenOur conversation on acquiring information, A.I., A.G.I., the NIH, the assault on science, the role of doctors in the A.I. era,, the meaning of life, books of the future, and much more.Transcript with linksEric Topol (00:06):Well, hello. This is Eric Topol with Ground Truths, and I am really thrilled today to have the chance to have a conversation with Tyler Cowen, who is, when you look up polymath in the dictionary, you might see a picture of him. He is into everything. And recently in the Economist magazine 1843, John Phipps wrote a great piece profile, the man who wants to know everything. And actually, I think there's a lot to that.Tyler Cowen (00:36):That's why we need longevity work, right?Eric Topol (00:39):Right. So he's written a number of books. How many books now, Tyler?Tyler Cowen:17, I'm not sure.Eric Topol:Only 17? And he also has a blog that's been going on for over 20 years, Marginal Revolution that he does with Alex Tabarrok.Tyler Cowen (00:57):Correct.Eric Topol (00:57):And yeah, and then Conversations with Tyler, a podcast, which I think an awful lot of people are tuned into that. So with that, I'm just thrilled to get a chance to talk with you because I used to think I read a lot, but then I learned about you.“Cowen calls himself “hyperlexic”. On a good day, he claims to read four or fivebooks. Secretly, I timed him at 30 seconds per page reading a dense tract byMartin Luther. “—John Phipps, The Economist's 1843I've been reading more from the AIs lately and less from books. So I'll get one good book and ask the AI a lot of questions.Eric Topol (01:24):Yeah. Well, do you use NotebookLM for that?Tyler Cowen (01:28):No, just o3 from OpenAI at the moment, but a lot of the models are very good. Claude, there's others.Eric Topol (01:35):Yeah, yeah. No, I see how that's a whole different way to interrogate a book and it's great. And in fact, that gets me to a topic I was going to get to later, but I'll do it now. You're soon or you have already started writing for the Free Press with Barri Weiss.Tyler Cowen (01:54):That's right, yes. I have a piece coming out later today. It's been about two weeks. It's been great so far.“Tyler Cowen has a mind unlike any I've ever encountered. In a single conversation, it's not at all unusual for him to toggle between DeepSeek, GLP-1s, Haitian art, sacred Tibetan music, his favorite Thai spot in L.A., and LeBron James”—Bari WeissYeah, so that's interesting. I hadn't heard of it until I saw the announcement from Barri and I thought what was great about it is she introduced it. She said, “Tyler Cowen has a mind unlike any I've ever encountered. In a single conversation, it's not at all unusual for him to toggle between DeepSeek, GLP-1s, Haitian art, sacred Tibetan music, his favorite Thai spot in L.A., and LeBron James. Now who could do that, right. So I thought, well, you know what? I need independent confirmation of that, that is as being a polymath. And then I saw Patrick Collison, who I know at Stripe and Arc Institute, “you can have a specific and detailed discussion with him about 17th-century Irish economic thinkers, or trends in African music or the history of nominal GDP targeting. I don't know anyone who can engage in so many domains at the depth he does.” So you're an information acquirer and one of the books you wrote, I love the title Infovore.Tyler Cowen (03:09):The Age of the Infovore, that's right.Eric Topol (03:11):I mean, have people been using that term because you are emblematic of it?“You can have a specific and detailed discussion with him about 17th-century Irish economic thinkers, or trends in African music or the history of nominal GDP targeting. I don't know anyone who can engage in so many domains at the depth he does.”—Patrick CollisonIt was used on the internet at some obscure site, and I saw it and I fell in love with that word, and I thought I should try to popularize it, but it doesn't come from me, but I think I am the popularizer of it.Yeah, well, if anybody was ingesting more information and being able to work with it. That's what I didn't realize about you, Tyler, is restaurants and basketball and all these other fine arts, very impressive. Now, one of the topics I wanted to get into you is I guess related to a topic you've written about fair amount, which is the great stagnation, and right now we're seeing issues like an attack on science. And in the past, you've written about how you want to raise the social status of scientists. So how do you see this current, I would even characterize as a frontal assault on science?Tyler Cowen (04:16):Well, I'm very worried about current Trump administration policies. They change so frequently and so unpredictably, it's a little hard to even describe what they always are. So in that sense, it's a little hard to criticize them, but I think they're scaring away talent. They might scare away funding and especially the biomedical sciences, the fixed costs behind a lot of lab work, clinical trials, they're so high that if you scare money away, it does not come back very readily or very quickly. So I think the problem is biggest perhaps for a lot of the biomedical sciences. I do think a lot of reform there has been needed, and I hope somehow the Trump policies evolve to that sort of reform. So I think the NIH has become too high bound and far too conservative, and they take too long to give grants, and I don't like how the overhead system has been done. So there's plenty of room for improvement, but I don't see so far at least that the efforts have been constructive. They've been mostly destructive.Eric Topol (05:18):Yeah, I totally agree. Rather than creative destruction it's just destruction and it's unfortunate because it seems to be haphazard and reckless to me at least. We of course, like so many institutions rely on NIH funding for the work, but I agree that reform is fine as long as it's done in a very thought out, careful way, so we can eke out the most productivity for the best investment. Now along with that, you started Emergent Ventures where you're funding young talent.Tyler Cowen (05:57):That's right. That's a philanthropic fund. And we now have slightly over 1000 winners. They're not all young, I'd say they're mostly young and a great number of them want to go into the biomedical sciences or have done so. And this is part of what made me realize what an incredible influx of talent we're seeing into those areas. I'm not sure this is widely appreciated by the world. I'm sure you see it. I also see how much of that talent actually is coming from Canada, from Ontario in particular, and I've just become far more optimistic about computational biology and progress in biology and medical cures, fixes, whatever you want to call it, extending lives. 10 years ago, I was like, yeah, who knows? A lot of things looked pretty stuck. Then we had a number of years where life expectancy was falling, and now I think we're on the verge of a true golden age.Eric Topol (06:52):I couldn't agree with you more on that. And I know some of the people that you funded like Anne Wylie who developed a saliva test for Covid out of Yale. But as you say, there's so many great young and maybe not so young scientists all over, Canada being one great reservoir. And now of course I'm worried that we're seeing emigration rather than more immigration of this talent. Any thoughts about that?Tyler Cowen (07:21):Well, the good news is this, I'm in contact with young people almost every day, often from other countries. They still want to come to the United States. I would say I sign an O-1 letter for someone about once a week, and at least not yet has the magic been dissipated. So I'm less pessimistic than some people are, but I absolutely do see the dangers. We're just the biggest market, the freest place we have by far the most ambitious people. I think that's actually the most significant factor. And young people sense that, and they just want to come here and there's not really another place they can go that will fit them.Eric Topol (08:04):Yeah, I mean one of the things as you've probably noted is there's these new forces that are taking on big shouldering. In fact, Patrick Collison with Arc Institute and Chan Zuckerberg for their institute and others like that, where the work you're doing with Emergent Ventures, you're supporting important projects, talents, and if this whole freefall in NIH funding and other agency funding continues, it looks like we may have to rely more on that, especially if we're going to attract some talent from outside. I don't know how else we're going to make. You're absolutely right about how we are such a great destination and great collaborations and mentors and all that history, but I'm worried that it could be in kind of a threatened mode, if you will.Tyler Cowen (08:59):I hope AI lowers costs. As you probably know at Arc, they had Greg Brockman come in for some number of months and he's one of the people, well, he helped build up Stripe, but he also was highly significant in OpenAI behind the GPT-4 model. And to have Greg Brockman at your institute doing AI for what, six months, that's a massive acceleration that actually no university had the wisdom to do, and Arc did. So I think we're seeing just more entrepreneurial thinking in the area. There's still this problem of bottlenecks. So let's say AI is great for drug discovery as it may be. Well, clinical trials then become a bigger bottleneck. The FDA becomes a bigger bottleneck. So rapid improvement in only one area while great is actually not good enough.Eric Topol (09:46):Yeah, I'm glad you brought up that effect in Arc Institute because we both know Patrick Hsu, who's a brilliant young guy who works there and has published some incredible large language models applied to life science in recent months, and it is impressive how they used AI in almost a singular way as compared to as you said, many other leading institutions. So that is I think, a really important thing to emphasize.Tyler Cowen (10:18):Arc can move very quickly. I think that's not really appreciated. So if Patrick Hsu decides Silvana Konermann, Patrick Collison, if they decide something ought to be bought or purchased or set in motion, it can happen in less than a day. And it does happen basically immediately. And it's not only that it's quicker, I think when you have quicker decisions, they're better and it's infectious to the people you're working with. And there's an understanding that the core environment is not a bureaucratic one. So it has a kind of multiplier effect through the institution.Eric Topol (10:54):Yeah, I totally agree with you. It's always been a philosophy in your mind to get stuff done, get s**t done, whatever you want to call it. They're getting it done. And that's what's so impressive. And not just that they've got some new funds available, but rather they're executing in a way that's parallel to the way the world's evolving in the AI front, which is I think faster than most people would ever have expected, anticipated. Now that gets me to a post you had on Marginal Revolution just last week, which one of the things I love about Marginal Revolution is you don't have to read a whole lot of stuff. You just give the bullets, the juice, if you will. Here you wrote o3 and AGI, is April 16th AGI day? And everybody's talking about artificial general intelligence is here. It's going to be here five years, it's going to be seven years.Eric Topol (11:50):It certainly seems to be getting closer. And in this you wrote, “I think it is AGI, seriously. Try asking it lots of questions, and then ask yourself: just how much smarter was I expecting AGI to be? As I've argued in the past, AGI, however you define it, is not much of a social event per se. It still will take us a long time to use it properly. Benchmarks, benchmarks, blah blah blah. Maybe AGI is like porn — I know it when I see it. And I've seen it.” I thought that was really well done, Tyler. Anything you want to amplify on that?Tyler Cowen (12:29):Look, if I ask at economics questions and I'm trained as an economist, it beats me. So I don't care if other people don't call it AGI, but one of the original definitions of AGI was that it would beat most experts most of the time on most matters, say 90% or above, and we're there. So people keep on shifting the goalposts. They'll say, well, sometimes it hallucinates or it's not very good at playing tic-tac toe, or there's always another complaint. Those are not irrelevant, but I'll just say, sit down, have someone write at a test of 20 questions, you're a PhD, you take the test, let o3 take the test, then have someone grade, see how you've done, then form your opinion. That's my suggestion.Eric Topol (13:16):I think it's pretty practical. I mean, enough with the Turing test, I mean, we've had that Turing test for decades, and I think the way you described it is a little more practical and meaningful these days. But its capabilities to me at least, are still beyond belief eke out of current, not just the large language models, but large reasoning models. And so, it's just gotten to a point where and it's accelerating, every week there's so many other, the competition is good for taking it to the next level.Tyler Cowen (13:50):It can do tasks and it self improves. So o3-pro will be out in a few weeks. It may be out by the time you're hearing this. I think that's obviously going to be better than just pure o3. And then GPT-5 people have said it will be this summer. So every few months there are major advances and there's no sign of those stopping.Eric Topol (14:12):Absolutely. Now, of course, you've been likened to “Treat Tyler like a really good GPT” that is because you're this information meister. What do you ask the man who you can ask anything? That's kind of what we have when we can go to any one of these sites and start our prompts, whatever. So it's kind of funny in some ways you might've annotated this with your quest for knowledge.Tyler Cowen (14:44):Well, I feel I understand the thing better than most people do for that reason, but it's not entirely encouraging to me personally, selfishly to be described that way, whether or not it's accurate. It just means I have a lot more new competition.Eric Topol (14:59):Well, I love this one. “I'm not very interested in the meaning of life, but I'm very interested in collecting information on what other people think is the meaning of life. And it's not entirely a joke” and that's also what you wrote about in the Free Press thing, that most of the things that are going to be written are going to be better AI in the media and that we should be writing books for the AI that's going to ingest them. How do you see this human AI interface growing or moving?Tyler Cowen (15:30):The AI is your smartest reader. It's your most sympathetic reader. It will remember what you tell it. So I think humans should sit down and ask, what does the AI need to know? And also, what is it that I know that's not on the historical record anywhere? That's not just repetition if I put it down, say on the internet. So there's no point in writing repetitions anymore because the AI already knows those things. So the value of what you'd call broadly, memoir, biography, anecdote, you could say secrets. It's now much higher. And the value of repeating basic truths, which by the way, I love as an economist, to be clear, like free trade, tariffs are usually bad, those are basic truths. But just repeating that people will be going to the AI and saying it again won't make the AI any better. So everything you write or podcast, you should have this point in mind.Eric Topol (16:26):So you obviously have all throughout your life in reading lots of books. Will your practice still be to do the primary reading of the book, or will you then go to o3 or whatever or the other way around?Tyler Cowen (16:42):I've become fussier about my reading. So I'll pick up a book and start and then start asking o3 or other models questions about the book. So it's like I get a customized version of the book I want, but I'm also reading somewhat more fiction. Now, AI might in time become very good at fiction, but we're not there now. So fiction is more special. It's becoming more human, and I should read more of it, and I'm doing that.Eric Topol (17:10):Yeah, no, that's great. Now, over the weekend, there was a lot of hubbub about Bill Gates saying that we won't need doctors in the next 10 years because of AI. What are your thoughts about that?Tyler Cowen (17:22):Well, that's wrong as stated, but he may have put it in a more complex way. He's a very smart guy of course. AI already does better diagnosis on humans than medical doctors. Not by a lot, but by somewhat. And that's free and that's great, but if you need brain surgery for some while, you still need the human doctor. So human doctors will need to adjust. And if someone imagines that at some point robots do the brain surgery better, well fine. But I'm not convinced that's within the next 10 years. That would surprise me.Eric Topol (17:55):So to that point, recently, a colleague of mine wrote an op-ed in the New York Times about six studies comparing AI alone versus doctors with AI. And in all six studies, the AI did better than the doctors who had access to AI. Now, you could interpret that as, well they don't know how to use AI. They have automation bias or that is true. What do you think?Tyler Cowen (18:27):It's probably true, but I would add as an interpretation, the value of meta rationality has gone up. So to date, we have not selected doctors for their ability to work with AI, obviously, but some doctors have the personal quality, it's quite distinct from intelligence, but if just knowing when they should defer to someone or something else, and those doctors and researchers will become much more valuable. They're sufficiently modest to defer to the AI and have some judgment as to when they should do that. That's now a super important quality. Over time, I hope our doctors have much more of that. They are selected on that basis, and then that result won't be true anymore.Eric Topol (19:07):So obviously you would qualify. There's a spectrum here. The AI enthusiasts, you and I are both in that group, and then there's the doomsayers and there's somewhere middle ground, of course, where people are trying to see the right balance. Are there concerns about AI, I mean anything about that, how it's moving forward that you're worried about?Tyler Cowen (19:39):Well, any change that big one should have very real concerns. Maybe our biggest concern is that we're not sure what our biggest concern should be. One simple effect that I see coming soon is it will devalue the status of a lot of our intellectuals and what's called our chattering class. A lot of its people like us, we won't seem so impressive anymore. Now, that's not the end of the world for everyone as a whole, but if you ask, what does it mean for society to have the status of its elites so punctured? At a time when we have some, I would say very negative forces attacking those elites in other ways, that to me is very concerning.Eric Topol (20:25):Do you think that although we've seen what's happening with the current administration with respect to the tariffs, and we've already talked about the effects on science funding, do you see this as a short-term hit that will eventually prevail? Do you see them selectively supporting AI efforts and finding the right balance with the tech companies to support them and the competition that exists globally with China and whatnot? How are we going to get forward and what some people consider pretty dark times, which is of course, so seemingly at odds with the most extraordinary times of human support with AI?Tyler Cowen (21:16):Well, the Trump people are very pro AI. I think that's one of the good things about the administration, much pro AI and more interested than were the Biden people. The Biden people, you could say they were interested, but they feared it would destroy the whole world, and they wanted to choke and throttle it in a variety of ways. So I think there's a great number of issues where the Trump people have gone very badly wrong, but at least so far AI's not one of them. I'd give them there like an A or A+ so far. We'll see, right?Eric Topol (21:44):Yeah. As you've seen, we still have some of these companies in some kind of a hot seat like Meta and Google regarding their monopolies, and we saw how some of the tech leaders, not all of them, became very supportive, potentially you could interpret that for their own interests. They wanted to give money to the inauguration and also get favor curry some political favor. But I haven't yet seen the commitment to support AI, talk about a golden age for the United States because so much of this is really centered here and some of the great minds that are helping to drive the AI and these models. But I wonder if there's more that can be done so that we continue to lead in this space.Tyler Cowen (22:45):There's a number of issues here. The first is Trump administration policy toward the FTC, I think has not been wonderful. They appointed someone who seems like would be more appropriate for a democratic or more left-leaning administration. But if you look at the people in the Office of Science and Technology Policy in the White House, they're excellent, and there's always different forces in any administration. But again, so far so good. I don't think they should continue the antitrust suit against Google that is looking like it's going against Google, but that's not really the Trump administration, that's the judiciary, and that's been underway for quite some while. So with Trump, it's always very hard to predict. The lack of predictability, I would say, is itself a big problem. But again, if you're looking for one area where it's good, that would be my pick.Eric Topol (23:35):Yeah, well, I would agree with that for sure. I just want to see more evidence that we capitalize on the opportunities here and don't let down. I mean, do you think outlawing selling the Nvidia chips to China is the way to do this? It seems like that hurts Nvidia and isn't China going to get whatever they want anyway?Tyler Cowen (24:02):That restriction, I favored when it was put in. I'm now of the view that it has not proved useful. And if you look at how many of those chips get sold, say to Malaysia, which is not a top AI performer, one strongly suspects, they end up going to China. China is incentivized to develop its own high-quality chips and be fully independent of Western supply lines. So I think it's not worked out well.Eric Topol (24:29):Yeah, no, I see that since you've written so much about this, it's good to get your views because I share those views and you know a lot more about this than I would, but it seems like whether it's Malaysia or other channels, they're going to get the Blackwell chips that they want. And it seems like this is almost like during Covid, how you would close down foreign travel. It's like it doesn't really work that well. There's a big world out there, right?Tyler Cowen (25:01):It's an interesting question. What kind of timing do you want for when both America and China get super powerful AI? And I don't think you actually want only America to have it. It's a bit like nuclear weapons, but you don't want China to have it first. So you want some kind of staggered sequence where we're always a bit ahead of them, but they also maybe are constraining us a bit. I hope we're on track to get that, but I really, really don't want China to have it first.Eric Topol (25:31):Yeah, I mean I think there's, as you're pointing out aptly is a healthy managed competition and that if we can keep that lead there, it is good for both and it's good for the world ideally. But getting back, is there anything you're worried about in AI? I mean because I know you're upbeat about its net effective, and we've already talked about amazing potential for efficiency, productivity. It basically upends a lot of economic models of the past, right?Tyler Cowen (26:04):Yes. I think it changes or will change so many parts of life. Again, it's a bit difficult to specify worries, but how we think of ourselves as humans, how we think of our gods, our religions, I feel all that will be different. If you imagine trying to predict the effects of the printing press after Gutenberg, that would've been nearly impossible to do. I think we're all very glad we got the printing press, but you would not say all of it went well. It's not that you would blame the printing press for those subsequent wars, but it was disruptive to the earlier political equilibrium. I think we need to take great care to do it better this time. AI in different forms will be weaponized. There's great potential for destruction there and evil people will use it. So of course, we need to be very much concerned.Eric Topol (26:54):And there's obviously many of these companies have ways to try to have efforts to anticipate that. That is alignments and various safety type parallel efforts like Ilya did when he moved out of OpenAI and others. Is that an important part of each of these big efforts, whether it's OpenAI, Google, or the rest of them anthropic that they put in resources to keep things from going off the tracks?Tyler Cowen (27:34):That's good and it's important, but I think it's also of limited value because the more we learn how to control AI systems directly, the bad guys will have similar lessons, and they will use alignment possibly to make their AIs bad and worse and that it obeys them. So yeah, I'd rather the good guys make progress on what they're trying to do, but don't think it's going to solve the problem. It creates new problems as well.Eric Topol (28:04):So because of AI, do you think you'll write any more books in the future?Tyler Cowen (28:11):I'm writing a book right now. I suspect it will be my last. That book, its title is Mentors. It's about how to mentor individuals and what do the social sciences know about mentoring. My view is that even if the AI could write the book better than I can, that people actually want to read a book like that from a human. I could be wrong, but I think we should in the future, restrict ourselves to books that are better by a human. I will write every day for the rest of my life, but I'm not sure that books make sense at the current moment.Eric Topol (28:41):Yeah, that's a really important point, and I understand that completely. Now, when you write for the Free Press, which will be besides the Conversations with Tyler podcast and the Marginal Revolution, what kind of things will you be writing about in the Free Press?Tyler Cowen (28:56):Well, I just submitted a piece. It's a defense of elitism. So the problem with our elites is that they have not been elitist enough and have not adhered strictly enough to the scientific method. So it's a very simple point. I think to you it would be pretty obvious, but it needs to be said. It's not out there enough in the debate that yes, sometimes the elites have truly and badly let us down, but the answer is not to reject elitism per se, but to impose higher elitist standards on our sometimes supposed elites. So that's the piece I just sent in. It's coming out soon and should be out by the time anyone hears this.Eric Topol (29:33):Well, I look forward to reading that. So besides a polymath, you might be my favorite polymath, Tyler you didn't know that. Also, you're a futurist because when you have that much information ingested, and now of course with a super performance of AI to help, it really does help to try to predict where we're headed. Have I missed anything in this short conversation that you think we should touch on?Tyler Cowen (30:07):Well, I'll touch on a great interest of yours. I like your new book very much. I think over the course of the next 40 years working with AI, we will beat back essentially every malady that kills people. It doesn't mean you live forever. Many, many more people will simply die of what we now call old age. There's different theories as to what that means. I don't have a lot of expertise in that, but the actual things people are dying from will be greatly postponed. And if you have a kid today to think that kid might expect to live to be 97 or even older, that to me is extremely plausible.Tyler Cowen (30:45):I won't be around to see it, but that's a phenomenal development for human beings.Eric Topol (30:50):I share that with you. I'm sad that I won't be around to see it, but exactly as you've outlined, the fact that we're going to be able to have a huge impact on particularly the age-related diseases, but also as you touched on the genetic diseases with genome editing and many other, I think, abilities that we have now controlling the immune system, I mean a central part of how we get into trouble with diseases. So I couldn't agree with you more, and that's a really good note to finish on because so many of the things that we have discussed today, we share similar views and we come at it from totally different worlds. The economist that has a very wide-angle lens, and I guess you'd say the physician who has a more narrow lens aperture. But thank you so much, Tyler for joining me today.Tyler Cowen (31:48):My pleasure. Let me close by telling you some good news. I have AI friends who think you and I, I'm 63 will be around to see that, I don't agree with them they don't convince me, but there are smart people who think the benefits from this will come quite soon.Eric Topol (32:03):I sure hope they're right.Tyler Cowen (32:05):Yes.*******************************************SUPER AGERS, my new book, was released on May 6th. It's about extending our healthspan, and I introduce 2 of my patients (one below, Mrs. L.R.) as exemplars to learn from. This potential to prevent the 3 major age-related diseases would not be possible without the jumps in the science of aging and multimodal A.I. My op-ed preview of the book was published in The NY Times last week. Here's a gift link. I did a podcast with Mel Robbins on the book here. Here's my publisher ‘s (Simon and Schuster) site for the book. If you're interested in the audio book, I am the reader (first time I have done this, quite an experience!)The book was reviewed in WSJ. Here's a gift linkThere have been many pieces written about it. Here's a gift link to the one in the Wall Street Journal and here for the one in the New York Times .**********************Thanks for reading and subscribing to Ground Truths.If you found this interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths— newsletters, analyses, and podcasts—is free, open-access.Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don't hesitate to post comments and give me feedback. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. Get full access to Ground Truths at erictopol.substack.com/subscribe

Written and directed by Alex Garland in his directorial debut, Ex Machina is the science fiction film starring Domhnall Gleeson, Alicia Vikander, and Oscar Isaac. Rob and Jason rewind to the year 2015 to review the decade old movie that has only just become more relevant with time. Caleb Smith (Domhnall Gleeson) a programmer at a huge Internet company, wins a contest that enables him to spend a week at the private estate of Nathan Bateman (Oscar Isaac), his firm's brilliant CEO. When he arrives, Caleb learns that he has been chosen to be the human component in a Turing test to determine the capabilities and consciousness of Ava (Alicia Vikander), a beautiful robot. However, it soon becomes evident that Ava is far more self-aware and deceptive than either man imagined.

Taylor Bradley, VP of Talent Strategy and Success at Turing, joined us on The Modern People Leader.We talked about why every HR team needs to create an AI “prompt pantry”, how Turing “AI'd” their way out of onboarding 800 employees in five days, and how to build AI workflows for HR.---- Sponsor Links:

Tim and Mary Danielsen dive into headlines once again, if only to prove we are not robots but real humans. Is everyone sick of trying to prove they are flesh and blood? Or hoping that the pictures you click on will pass the test? This system is actually called CAPTCHA (Completely Automated Public Turing Test to tell Computers and Humans Apart). It is a computing test to determine if the user is human. It is sometimes called the reverse Turing test, as the point is to prove humanity rather than artificial intelligence. I for one believe that the burden of proof is on the Artificial Lifeform to come forth and identify themselves. Today we talk about that alternate reality that is the internet. Patrick Wood has for some time now said that reality barely exists anyway, so we will look at what that means. We also look at Canadian elections; the Pope as Muslim apologist; an update on the Temple Mount; catastrophic AI; Facial Recognition perils; and the need to find HOPE in all of it. After all, our hope isn't in prophetic fulfillment, it is in a person - the Lord Jesus Christ, Lord of all. A full hour regarding life on planet earth in April 2025. Stand Up For The Truth Videos: https://rumble.com/user/CTRNOnline & https://www.youtube.com/channel/UCgQQSvKiMcglId7oGc5c46A

Welcome to Dev Game Club, where this week we continue our series on 2012's Fez, looking at coming back to a puzzle game and perception in its many forms, among other topics. Dev Game Club looks at classic video games and plays through them over several episodes, providing commentary. Sections played: More cubes! Issues covered: video game development ephemera, coming back to a puzzle game, not enjoying the map but maybe you should be, a text adventure map, secret doors, retraining your brain, key ordering, not knowing if you should walk away from puzzles, developing trust with the game, being motivated to solve every puzzle, when do you walk away, planning for the player to get stuck, adventure game slop, getting stuck in a more linear game, putting in scaled difficulty, getting to a point where you're stuck everywhere, different types of puzzling in the game, the steps of a particular puzzle, a meta discussion, a game about perspectives where the activity is manipulating perspectives, being proud of being in games, recontextualizing your perception, having to retrain your brain, overestablishment of genre, having confidence, working on top of a common language, recognizing that you have the tool, mechanics in a neighborhood, experimenting when you've been away, being able to innovate in more major ways, achievements/trophy hunting, being lost in the realm, Turing-complete redstone. Games, people, and influences mentioned or discussed: Sean Vesce, Zack Norman, Interstate '76, VGHF, LucasArts, Space Quest, The Witness, Blue Prince, MYST, Tomb Raider, Zelda, The Fool's Errand, Metroid (series), Hollow Knight, Kingdom Hearts (series), MegaMan (series), Mario (series), Colin from PA, PlayStation/Xbox/Steam, Minecraft, LostLake, Mors, Kaeon, Bvron, Kirk Hamilton, Aaron Evers, Mark Garcia.  Notes: Brett referred to Fez's year as 2013 or 2014, but clearly it was 2012. Whoops. Next time: Finish(?) the game? Twitch Discord DevGameClub@gmail.com

It's been 4 months since we've cleared the backlog of Fresh AI Hell and the bullshit is coming in almost too fast to keep up with. But between a page full of awkward unicorns and a seeming slowdown in data center demand, Alex and Emily have more good news than usual to accompany this round of catharsis.AI Hell:LLM processing like human language processing (not)Jack Clark predicting AGISebastian Bubeck says predictions in "sparks" paper have already come trueWIRED puff piece on the AmodeisFoundation agents & leaning in to the computational metaphor (Fig 1, p14)Chaser: Trying to recreate the GPT unicornThe WSJ has an AI bot for all your tax questionsChatGPT libelAOL.com uses autogenerated captions about attempted murderAI coding tools fix bugs by adding bugs"We teach AGI to think, so you don't have to"(from: Turing.com)MAGA/DOGE paints teachers as glorified babysitters in push for AIChaser: How we are NOT using AI in the classroomAI benchmarks are self-promoting trash — but regulators keep using themDOGE is pushing AI tool created as "sandbox" for federal testing"Psychological profiling" based on social mediaThe tariffs and ChatGPT"I was not informed that Microsoft would sell my work to the Israeli military and government"Microsoft fires engineers who protested Israeli military use of its toolsPulling back on data centers, Microsoft editionAbandoned data centers, China editionBill Gates: 2 day workweek coming thanks to AI...replacing doctors and teachers??Chaser: Tesla glue fail schadenfreudeChaser: Let's talk about the genie tropeChaser: We finally met!!!Check out future streams at on Twitch, Meanwhile, send us any AI Hell you see.Our book, 'The AI Con,' comes out in May! Pre-order now.Subscribe to our newsletter via Buttondown. Follow us!Emily Bluesky: emilymbender.bsky.social Mastodon: dair-community.social/@EmilyMBender Alex Bluesky: alexhanna.bsky.social Mastodon: dair-community.social/@alex Twitter: @alexhanna Music by Toby Menon.Artwork by Naomi Pleasure-Park. Production by Christie Taylor.

  NEW SUBSCRIPTION INTERFACE THINGAMABOB!   You can now find our subscription page at GeorgeHrab.com at this link. Many thanks to the majestic Evo Terra for his assistance.   THE SHOW NOTES   Easter is here, Easter is weird Intro Is anyone out there? Interesting Fauna      - Clobazam- and Benzodiazepine-exposed Atlantic Salmon Religious Moron of the Week      - Melissa Ganey English Ask George      - Hold music? from Michael in Seattle Damian Handzy's Facts That'll Fuck Y'up      - Sourdough, Coldplay, Lincoln, Turing, more… Tell Me Something Good      - Hacked Crosswalks Geo Solo in Nazareth next Saturday Show Close .........................   EVENTS ON THE SCHEDULE  April 26 Nazareth Center for the Arts “George Hrab: So Wry, Solo” 7:30 .........................   Get George's Music Here  https://georgehrab.hearnow.com https://georgehrab.bandcamp.com ................................... SUBSCRIBE! You can sign up at GeorgeHrab.com and become a Geologist or a Geographer. As always, thank you so much for your support! You make the ship go. ................................... Sign up for the mailing list: Write to Geo! Check out Geo's wiki page, thanks to Tim Farley. Have a comment on the show, a Religious Moron tip, or a question for Ask George? Drop George a line and write to Geo's Mom, too!

Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Sign up for the “Brain Inspired” email alerts to be notified every time a new “Brain Inspired” episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. Aran Nayebi is an Assistant Professor at Carnegie Mellon University in the Machine Learning Department. He was there in the early days of using convolutional neural networks to explain how our brains perform object recognition, and since then he's a had a whirlwind trajectory through different AI architectures and algorithms and how they relate to biological architectures and algorithms, so we touch on some of what he has studied in that regard. But he also recently started his own lab, at CMU, and he has plans to integrate much of what he has learned to eventually develop autonomous agents that perform the tasks we want them to perform in similar at least ways that our brains perform them. So we discuss his ongoing plans to reverse-engineer our intelligence to build useful cognitive architectures of that sort. We also discuss Aran's suggestion that, at least in the NeuroAI world, the Turing test needs to be updated to include some measure of similarity of the internal representations used to achieve the various tasks the models perform. By internal representations, as we discuss, he means the population-level activity in the neural networks, not the mental representations philosophy of mind often refers to, or other philosophical notions of the term representation. Aran's Website. Twitter: @ayan_nayebi. Related papers Brain-model evaluations need the NeuroAI Turing Test. Barriers and pathways to human-AI alignment: a game-theoretic approach. 0:00 - Intro 5:24 - Background 20:46 - Building embodied agents 33:00 - Adaptability 49:25 - Marr's levels 54:12 - Sensorimotor loop and intrinsic goals 1:00:05 - NeuroAI Turing Test 1:18:18 - Representations 1:28:18 - How to know what to measure 1:32:56 - AI safety

The horrible things people get programmed to believe. They have been programmed to fight for an evil cause. Jasmine Crockett’s “magic armor’. Where does the mass programing of people lead us? Turing into an old man.See omnystudio.com/listener for privacy information.

Welp, that escalated quickly.

“What I meant when I said there is no AI is that I don't think we serve ourselves well when we put our own technology up as if it were a new God that we created. I think we confuse ourselves too easily. This goes back to Alan Turing, the main founder of computer science, who had this idea of the Turing test. In the test, you can't tell whether the computer has gotten more human-like or the human has gotten more computer-like. People are very prone to becoming more computer-like. When we're on social media, we let ourselves be guided by the algorithms, so we start to become dumb in the way the algorithms want us to. You see that all the time. It's really degraded our psychologies and our society.”Jaron Lanier is a pioneering technologist, writer, and musician, best known for coining the term “Virtual Reality” and founding VPL Research, the first company to sell VR products. He led early breakthroughs in virtual worlds, avatars, and VR applications in fields like surgery and media. Lanier writes on the philosophy and economics of technology in his bestselling book Who Owns the Future? and You Are Not a Gadget. His book Dawn of the New Everything: Encounters with Reality and Virtual Reality is an inventive blend of autobiography, science writing, and philosophy. Lanier has been named one of TIME's 100 most influential people and serves as Prime Unifying Scientist at Microsoft's Office of the CTO—aka “Octopus.” As a musician, he's performed with Sara Bareilles, Philip Glass, T Bone Burnett, Laurie Anderson, Jon Batiste, and others.Episode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcastEpisode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcast

“AI is obviously the dominant topic in tech lately, and I think occasionally there's AI that's nonsense, and occasionally there's AI that's great. I love finding new proteins for medicine and so on. I don't think we serve ourselves well when we put our own technology up as if it were a new God that we created. I think we're really getting a little too full of ourselves to think that. This goes back to Alan Turing, the main founder of computer science, who had this idea of the Turing test. In the test, you can't tell whether the computer has gotten more human-like or the human has gotten more computer-like. People are very prone to becoming more computer-like. When we're on social media, we let ourselves be guided by the algorithms, so we start to become dumb in the way the algorithms want us to. You see that all the time. It's really degraded our psychologies and our society.”Jaron Lanier is a pioneering technologist, writer, and musician, best known for coining the term “Virtual Reality” and founding VPL Research, the first company to sell VR products. He led early breakthroughs in virtual worlds, avatars, and VR applications in fields like surgery and media. Lanier writes on the philosophy and economics of technology in his bestselling book Who Owns the Future? and You Are Not a Gadget. His book Dawn of the New Everything: Encounters with Reality and Virtual Reality is an inventive blend of autobiography, science writing, and philosophy. Lanier has been named one of TIME's 100 most influential people and serves as Prime Unifying Scientist at Microsoft's Office of the CTO—aka “Octopus.” As a musician, he's performed with Sara Bareilles, Philip Glass, T Bone Burnett, Laurie Anderson, Jon Batiste, and others.Episode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcastPhoto credit: Michael Springer