Podcasts about Turing Award

In the latest episode of Boz To The Future, Meta CTO, Head of ATA and Reality Labs, and host Andrew "Boz" Bosworth talks to Ed Catmull—co-founder of Pixar Animation Studios, former president of Walt Disney Animation Studios, Turing Award laureate, and author of the bestselling book Creativity, Inc.Ed spent 20 years turning an impossible dream—making a feature film entirely with computers—into reality with Toy Story. Along the way, he invented foundational computer graphics techniques, built one of the most innovative companies in entertainment history, and worked alongside Steve Jobs for over two decades.Together, they explore how Ed built a culture of sustained creativity at Pixar, the mechanics of the Braintrust, why failure is an investment and not a verdict, and what it was like to work with Steve Jobs. They also discuss what the intersection of technology and art means for the future of creative tools and AI.Leave Boz feedback on Instagram, X, and Threads. 

Yann LeCun, Turing Award winner and former Chief AI Scientist at Meta, joins Jacob Effron. The conversation centers on Yann's contrarian thesis that LLMs are a dead-end on the path to human-level intelligence, despite being useful products — because they can't predict the consequences of their actions, can't plan, and fundamentally can't model the messy, high-dimensional real world. He unpacks his alternative architecture, JEPA (Joint Embedding Predictive Architecture), which learns abstract representations rather than generating pixel-level predictions, and explains why this approach is essential for robotics, industrial applications, and any system that needs to operate beyond the substrate of language. Yann also reveals the real story behind his departure from Meta (he had zero technical influence on Llama, contrary to public narrative), the genesis of his Tapestry project for sovereign open-source AI, why he believes LLMs are intrinsically unsafe, where he diverges from his fellow Turing laureates Hinton and Bengio, and why he predicts the industry will recognize the paradigm shift by early 2027. Throughout, he offers candid reflections on the tension between research and product at major labs, and why he intentionally headquartered AMI Labs in Paris with zero Silicon Valley VC money.   (0:00) Introduction  (01:45) Why LLMs Aren't the Path to Intelligence  (07:51) AMI and World Models  (12:07) The JEPA Architecture Explained  (15:55) Problems with Robotics Models Today  (20:37) Silicon Valley Herd Behavior  (28:18) Tapestry: Sovereign AI for the Rest of the World  (35:49) OpenAI Is the Next Sun Microsystems  (40:51) Why Yann's Views Diverged from Hinton & Bengio  (44:32) LLMs Are Intrinsically Unsafe  (58:00) Why Yann Left Meta  (1:00:26) Reflections on FAIR  (1:12:11) Advice for PhD Students   LeWorldModel Paper: https://arxiv.org/abs/2603.19312   With your host:  @jacobeffron  - Partner at Redpoint

When the Bitcoin white paper landed in 2008, most people saw a payment system. Shaul Kfir saw a privacy problem — because he had spent years working on the zero-knowledge proof technology that would eventually make private transactions possible on blockchains.That instinct shaped everything that followed, including the Canton Network, the blockchain he co-founded that now moves trillions of dollars a month for some of the world's largest financial institutions.Shaul's path is unlike most in this space. He co-authored libsnark, the seminal zkSNARK library that helped bring zero-knowledge proofs to blockchains, studied under Turing Award winner Ron Rivest at MIT, and built one of Israel's first Bitcoin brokerages before turning his attention to the infrastructure problem that would define his career: how do you build a blockchain that institutions can actually use?In this episode, Ari sits down with Shaul to explore why privacy was a non-negotiable design principle from day one, why the industry is now at a genuine inflection point as institutions move from private to public blockchain environments, and what the beginning of institutional DeFi actually looks like in practice. They also dig into the tension between privacy and compliance and why regulators should focus on desired system properties rather than prescribing specific technologies.When he is not building financial infrastructure, Shaul is on the water — a former Israeli Navy Lieutenant Commander who still races sailboats, once captured a whale breach on his Ray-Ban Meta glasses mid-race, and finds the parallel between navigating a storm at sea and building in crypto surprisingly easy to draw.

There are no two letters more disruptive in our time than AI. We're told it will create employment yet take jobs away; invent life-saving medicines yet enable superviruses; solve the climate crisis yet deepen it. So will it save us or damn us? Is AI the ultimate disruptor?This conversation, moderated by Nahlah Ayed, was part of the 2026 Charles Bronfman's “Conversations” series.Guests in this episode:Yoshua Bengio is a professor at Université de Montreal. He also has the distinction of being the most-cited living scientist in the world, in any discipline. He's co-president and scientific director of LawZero, a nonprofit startup dedicated to creating safe AI systems. In 2018, he was a recipient of the Turing Award, often referred to as the Nobel Prize of Computer Science.Cory Doctorow is a novelist, journalist, technology activist and the author of an astonishing number of books, both nonfiction and fiction. Among them: Enshittification: Why Everything Suddenly Got Worse and What To Do About It. And the upcoming: The Reverse Centaur's Guide to Life After AI.Astra Taylor is a documentary filmmaker, cofounder of the Debt Collective, and a writer. Among her books: Democracy May Not Exist But We'll Miss It When It's Gone, and The People's Platform, which won the American Book Award. Taylor also delivered the 2023 CBC Massey Lectures called The Age of Insecurity: Coming Together as Things Fall Apart.

We're all using AI more, but how many of us actually trust it? AI is now used by more than a billion people worldwide, but trust in these systems is far from settled. In this episode of Disruptors, John Stackhouse speaks with Yoshua Bengio, Turing Award winner, founder of Mila, and Co-President and Scientific Director of LawZero, about whether AI is getting safer or more dangerous as it becomes more powerful, more agentic, and more embedded in work, public systems, and everyday life. They explore LawZero's mission to build non-agentic, trustworthy AI, including Scientist AI, and why Bengio believes the next generation of artificial intelligence should be designed to reason, evaluate, and supervise rather than independently pursue goals. John is also joined by Jaxson Khan, Senior Fellow at the Munk School of Global Affairs & Public Policy, to discuss AI sovereignty, the risks of dependence on foreign cloud and compute infrastructure, and what Canada should be thinking about as it prepares its next national AI strategy. This is a conversation about AI safety, Canadian AI sovereignty, trustworthy AI, and who should shape the systems that are increasingly shaping us. Yoshua Bengio's work through LawZero offers one of the clearest Canadian answers yet.Show notes links Episode guests and organizationsYoshua BengioLawZeroJaxson KhanMunk School of Global Affairs & Public Policy Referenced readingRBC Thought LeadershipRBC Thought Leadership on LinkedInSovereign by Design: Strategic Options for Canadian AI SovereigntyBridging the Imagination Gap: How Canadian companies can become global leaders in AI adoption Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

Big Tech just faced a courtroom reckoning, with Meta and Google found liable for platform "addictiveness" in a social media trial that could unleash a tidal wave of lawsuits. Find out why attorneys, entrepreneurs, and everyday users are suddenly on edge. • Social media addiction lawsuits hit Meta, Google, YouTube • Section 230 and First Amendment implications debated after court verdicts • Supreme Court sides with Cox; ISPs not liable for user piracy • Elon Musk's lawsuit over X (Twitter) ad boycotts thrown out • Anthropic versus Department of Defense: AI contracting dispute and retaliation claims • FCC's confusing foreign-made router ban and consumer tech fallout • Major supply chain attack: LiteLLM malware infects AI devs • The rise (and risks) of AI agents with voice, identity, and personification • Turing Award honors pioneers of quantum cryptography • Antimatter on the move: CERN's oddball truck experiment • Sci-fi and reality blur as Neal Stephenson walks away from the metaverse • Privacy and consent worries escalate with AI-powered recordings and surveillance • Digital shelf pricing arrives at Walmart and Kroger • Flipper Zero: voice-controlled hacking gadget gets an AI upgrade • Age verification laws create headaches for OS and app developers • Official White House app called out for surveillance and security blunders • Is AI progress barreling toward a dystopian tech future? Host: Leo Laporte Guests: Harper Reed, Brian McCullough, and Cathy Gellis Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: doppel.com outsystems.com/twit zscaler.com/security meter.com/twit ZipRecruiter.com/twit

- GTC postview, list of announcements - GPUs and China - DoE $293m funding RFA for technology challenges - Volume on HPC-AI-Quantum co-design, call for contributions - Turing Award goes to QKD inventors, quantum cryptography pioneers [audio mp3="https://orionx.net/wp-content/uploads/2026/03/HPCNB_20260323.mp3"][/audio] The post HPC News Bytes – 20260323 appeared first on OrionX.net.

If there is even a 1% chance that AI could destroy us, should we keep building it? Are we creating machines that will one day outthink humanity? And is the race to dominate AI accelerating us toward a future we're unprepared to face? This week, Yoshua Bengio joins Rory Stewart and Matt Clifford for an AI deep dive. A Turing Award–winning pioneer of deep learning, Bengio helped build the field, and is now one of its most urgent critics, warning that without restraint, the risks ahead could be profound. To listen to the full episode, sign up at therestispolitics.com Instagram: ⁠@restispolitics⁠ Twitter: ⁠@restispolitics⁠ Email: ⁠therestispolitics@goalhanger.com⁠ __________ Social Producer: Celine Charles Video Editor: Lorcan Moullier Producer: India Dunkley Senior Producer: Callum Hill Exec Producer: Tom Whiter Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of ACM ByteCast, Rashmi Mohan hosts 2024 ACM A.M. Turing Andrew laureates Andrew Barto and Richard Sutton. They received the Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning, a computational framework that underpins modern AI systems such as AlphaGo and ChatGPT. Barto is Professor Emeritus in the Department of Information and Computer Sciences at the University of Massachusetts, Amherst. His honors include the UMass Neurosciences Lifetime Achievement Award, the IJCAI Award for Research Excellence, and the IEEE Neural Network Society Pioneer Award. He is a Fellow of IEEE and AAAS. Sutton is a Professor in Computing Science at the University of Alberta, a Research Scientist at Keen Technologies (an artificial general intelligence company) and Chief Scientific Advisor of the Alberta Machine Intelligence Institute (Amii). In the past he was a Distinguished Research Scientist at Deep Mind and served as a Principal Technical Staff Member in the AI Department at the AT&T Shannon Laboratory. His honors include the IJCAI Research Excellence Award, a Lifetime Achievement Award from the Canadian Artificial Intelligence Association, and an Outstanding Achievement in Research Award from the University of Massachusetts at Amherst. Sutton is a Fellow of the Royal Society of London, AAAI, and the Royal Society of Canada. In the interview, Andrew and Richard reflect on their long collaboration together and the personal and intellectual paths that led both researchers into CS and reinforcement learning (RL), a field that was once largely neglected. They touch on interdisciplinary explorations across psychology (animal learning), control theory, operations research, cybernetics, and how these inspired their computational models. They also explain some of their key contributions to RL, such as temporal difference (TD) learning and how their ideas were validated biologically with observations of dopamine neurons. Barto and Sutton trace their early research to later systems such as TD-Gammon, Q-learning, and AlphaGo and consider the broader relationship between humans and reinforcement learning-based AI, and how theoretical explorations have evolved into impactful applications in games, robotics, and beyond.

The ACM A.M. Turing Award is universally recognized as the "Nobel Prize of Computing" and stands as the highest distinction in the field of computer science. Presented annually by the Association for Computing Machinery, it honors individuals whose technical contributions have had a lasting and major importance to the digital world.The award is named in honor of Alan Mathison Turing, the British mathematician and "Father of Computer Science". Turing provided the formal foundations for computation with the Universal Turing Machine and played a pivotal role in the Allied victory during World War II by leading the effort to decrypt the Enigma cipher.The most recent recipients (2024) are Andrew Barto and Richard Sutton, recognized for their groundbreaking work in reinforcement learning. Their research allows machines to learn through trial and error, serving as a central pillar for the modern AI boom and powering massive breakthroughs like AlphaGo and ChatGPT.Turing Award Fast Facts:• The Prize: Winners receive $1 million, with current financial support provided by Google, Inc..• The First: The inaugural award was given to Alan Perlis in 1966 for his influence on advanced programming and compilers.• Women in Computing: Only three women have ever received the honor: Frances Allen (2006), Barbara Liskov (2008), and Shafi Goldwasser (2012).• The Elite Network: Turing Laureates are exceptionally well-connected; on average, a winner is separated from another laureate or von Neumann Medal winner by only 1.4 co-authorship steps.• Academic Foundations: Approximately 61% of laureates hold degrees in mathematics, reflecting the discipline's deep roots in mathematical logic.• Age Trends: While the youngest winner, Donald Knuth, was only 36, the average age of recipients has trended upward toward 70 in recent years.From the invention of the World Wide Web and the C programming language to the foundations of Artificial Intelligence, the Turing Award documents the history of the information age.#TuringAward #ComputerScience #AI #AlanTuring #TechHistory #ReinforcementLearning #ChatGPT #Innovation #Coding #STEM

The ACM A.M. Turing Award is universally recognized as the "Nobel Prize of Computing" and stands as the highest distinction in the field of computer science. Presented annually by the Association for Computing Machinery, it honors individuals whose technical contributions have had a lasting and major importance to the digital world.The award is named in honor of Alan Mathison Turing, the British mathematician and "Father of Computer Science". Turing provided the formal foundations for computation with the Universal Turing Machine and played a pivotal role in the Allied victory during World War II by leading the effort to decrypt the Enigma cipher.The most recent recipients (2024) are Andrew Barto and Richard Sutton, recognized for their groundbreaking work in reinforcement learning. Their research allows machines to learn through trial and error, serving as a central pillar for the modern AI boom and powering massive breakthroughs like AlphaGo and ChatGPT.Turing Award Fast Facts:• The Prize: Winners receive $1 million, with current financial support provided by Google, Inc..• The First: The inaugural award was given to Alan Perlis in 1966 for his influence on advanced programming and compilers.• Women in Computing: Only three women have ever received the honor: Frances Allen (2006), Barbara Liskov (2008), and Shafi Goldwasser (2012).• The Elite Network: Turing Laureates are exceptionally well-connected; on average, a winner is separated from another laureate or von Neumann Medal winner by only 1.4 co-authorship steps.• Academic Foundations: Approximately 61% of laureates hold degrees in mathematics, reflecting the discipline's deep roots in mathematical logic.• Age Trends: While the youngest winner, Donald Knuth, was only 36, the average age of recipients has trended upward toward 70 in recent years.From the invention of the World Wide Web and the C programming language to the foundations of Artificial Intelligence, the Turing Award documents the history of the information age.#TuringAward #ComputerScience #AI #AlanTuring #TechHistory #ReinforcementLearning #ChatGPT #Innovation #Coding #STEM

In this episode, Dr. Arjun Jain - Founder of Fast Code AI - reveals why the AI industry's trillion-dollar bet on bigger models is failing, and what's replacing it. Dr. Arjun Jain isn't your typical AI founder. After training under Turing Award winner Yann LeCun at NYU, working on Apple's secretive autonomous vehicle project, and leading Mercedes-Benz's robotaxi AI, he returned to India to bootstrap Fast Code AI with zero venture capital. In just two years, his company grew 8x by doing what the AI giants won't: charging for outcomes instead of software seats, deploying Small Language Models that outperform GPT-4 for specific tasks, and building agents that actually work in production. He shared this contrarian journey in this candid conversation with host Akshay Datt. From explaining why "we have but one internet and we've used it all" (quoting OpenAI's Ilya Sutskever) to revealing how procurement agents train by negotiating with themselves millions of times, this episode dismantles the AI hype and shows what enterprise automation actually looks like. Whether you're a founder evaluating AI vendors, an engineer choosing between foundation model labs and application companies, or an investor trying to separate signal from noise, this is the reality check the industry needs. What You'll Learn:

This episode of the Physics World Weekly podcast features Pat Hanrahan, who studied nuclear engineering and biophysics before becoming a founding employee of Pixar Animation Studios. As well as winning three Academy Awards for his work on computer animation, Hanrahan won the Association for Computing Machinery’s A.M. Turing Award for his contributions to 3D computer graphics, or CGI. Earlier this year, Hanrahan spoke to Physics World's Margaret Harris at the Heidelberg Laureate Forum in Germany. He explains how he was introduced to computer graphics by his need to visualize the results of computer simulations of nervous systems. That initial interest led him to Pixar and his development of physically-based rendering, which uses the principles of physics to create realistic images. Hanrahan explains that light interacts with different materials in very different ways, making detailed animations very challenging. Indeed, he says that creating realistic looking skin is particularly difficult – comparing it to the quest for a grand unified theory in physics. He also talks about how having a background in physics has helped his career – citing his physicist’s knack for creating good models and then using them to solve problems.

AI pioneer YOSHUA BENGIO, Godfather of AI, reveals the DANGERS of Agentic AI, killer robots, and cyber crime, and how we MUST build AI that won't harm people…before it's too late.  Professor Yoshua Bengio is a Computer Science Professor at the Université de Montréal and one of the 3 original Godfathers of AI. He is the most-cited scientist in the world on Google Scholar, a Turing Award winner, and the founder of LawZero, a non-profit organisation focused on building safe and human-aligned AI systems.  He explains: ◼️Why agentic AI could develop goals we can't control ◼️How killer robots and autonomous weapons become inevitable ◼️The hidden cyber crime and deepfake threat already unfolding ◼️Why AI regulation is weaker than food safety laws ◼️How losing control of AI could threaten human survival [00:00] Why Have You Decided to Step Into the Public Eye?   [02:53] Did You Bring Dangerous Technology Into the World?   [05:23] Probabilities of Risk   [08:18] Are We Underestimating the Potential of AI?   [10:29] How Can the Average Person Understand What You're Talking About?   [13:40] Will These Systems Get Safer as They Become More Advanced?   [20:33] Why Are Tech CEOs Building Dangerous AI?   [22:47] AI Companies Are Getting Out of Control   [24:06] Attempts to Pause Advancements in AI   [27:17] Power Now Sits With AI CEOs   [35:10] Jobs Are Already Being Replaced at an Alarming Rate   [37:27] National Security Risks of AI   [43:04] Artificial General Intelligence (AGI)   [44:44] Ads   [48:34] The Risk You're Most Concerned About   [49:40] Would You Stop AI Advancements if You Could?   [54:46] Are You Hopeful?   [55:45] How Do We Bridge the Gap to the Everyday Person?   [56:55] Love for My Children Is Why I'm Raising the Alarm   [01:00:43] AI Therapy   [01:02:43] What Would You Say to the Top AI CEOs?   [01:07:31] What Do You Think About Sam Altman?   [01:09:37] Can Insurance Companies Save Us From AI?   [01:12:38] Ads   [01:16:19] What Can the Everyday Person Do About This?   [01:18:24] What Citizens Should Do to Prevent an AI Disaster   [01:20:56] Closing Statement   [01:22:51] I Have No Incentives   [01:24:32] Do You Have Any Regrets?   [01:27:32] Have You Received Pushback for Speaking Out Against AI?   [01:28:02] What Should People Do in the Future for Work?   Follow Yoshua: LawZero - https://bit.ly/44n1sDG  Mila - https://bit.ly/4q6SJ0R  Website - https://bit.ly/4q4RqiL  You can purchase Yoshua's book, ‘Deep Learning (Adaptive Computation and Machine Learning series)', here: https://amzn.to/48QTrZ8  The Diary Of A CEO: ◼️Join DOAC circle here - https://doaccircle.com/  ◼️Buy The Diary Of A CEO book here - https://smarturl.it/DOACbook  ◼️The 1% Diary is back - limited time only - https://bit.ly/3YFbJbt  ◼️The Diary Of A CEO Conversation Cards (Second Edition) - https://g2ul0.app.link/f31dsUttKKb  ◼️Get email updates - https://bit.ly/diary-of-a-ceo-yt  ◼️Follow Steven - https://g2ul0.app.link/gnGqL4IsKKb  Sponsors:  Wispr - Get 14 days of Wispr Flow for free at https://wisprflow.ai/DOAC  Pipedrive - https://pipedrive.com/CEO Rubrik - To learn more, head to https://rubrik.com

Sir Tim Berners-Lee is a computer scientist and the inventor of the World Wide Web. He was born in 1955, a golden year for technology innovators. Steve Jobs and Bill Gates were also born in the same year. A curious child, he learned about electronics from his train set and spent his pocket money on transistors. His first significant connecting invention was building an intercom as a teenager for the family home before moving on to build his first computer. His parents were both mathematicians and coders who met whilst building one of the first commercially available computers in the early nineteen fifties. Sir Tim came up with the idea of the World Wide Web whilst working at CERN and insisted that the technology be released to the world without commercial reward so that it would be free for everyone to use. He was knighted for his world changing invention and also appointed to the Order of Merit. In 2016 he was given the Turing Award. Sir Tim Berners-Lee divides his time between the US, the UK and Canada with his wife Rosemary, who is also a technology entrepreneur.Presenter Lauren Laverne Producer Sarah TaylorDesert Island Discs has cast many computer scientists away over the years including Dame Wendy Hall and Sir Demis Hassibis. You can hear their programmes if you search through BBC Sounds or our own Desert Island Discs website.

Judea Pearl is The Chancellor's Professor of computer science and statistics and director of the Cognitive Systems Laboratory at UCLA. He was the recipient of the Turing Award in 2011. His latest book "Coexistence and Other Fighting Words – Selected Writings of Judea Pearl, 2002-2025" was released on December 10, 2025. Link to the book: https://shorturl.at/slsf7 _______________________________________ If you appreciate my work and would like to support it: https://subscribestar.com/the-saad-truth https://patreon.com/GadSaad https://paypal.me/GadSaad To subscribe to my exclusive content on X, please visit my bio at https://x.com/GadSaad _______________________________________ This clip was posted on December 12, 2025 on my YouTube channel as THE SAAD TRUTH_1960: https://youtu.be/y4HrsBS58Ec _______________________________________ Please visit my website gadsaad.com, and sign up for alerts. If you appreciate my content, click on the "Support My Work" button. I count on my fans to support my efforts. You can donate via Patreon, PayPal, and/or SubscribeStar. _______________________________________ Dr. Gad Saad is a professor, evolutionary behavioral scientist, and author who pioneered the use of evolutionary psychology in marketing and consumer behavior. In addition to his scientific work, Dr. Saad is a leading public intellectual who often writes and speaks about idea pathogens that are destroying logic, science, reason, and common sense.  _______________________________________  

Most discourse on AI is low-quality. Most discourse on consciousness is super-abysmal-double-low quality. Multiply these - or maybe raise one to the exponent of the other, or something - and you get the quality of discourse on AI consciousness. It's not great. Out-of-the-box AIs mimic human text, and humans almost always describe themselves as conscious. So if you ask an AI whether it is conscious, it will often say yes. But because companies know this will happen, and don't want to give their customers existential crises, they hard-code in a command for the AIs to answer that they aren't conscious. Any response the AIs give will be determined by these two conflicting biases, and therefore not really believable. A recent paper expands on this method by subjecting AIs to a mechanistic interpretability "lie detector" test; it finds that AIs which say they're conscious think they're telling the truth, and AIs which say they're not conscious think they're lying. But it's hard to be sure this isn't just the copying-human-text thing. Can we do better? Unclear; the more common outcome for people who dip their toes in this space is to do much, much worse. But a rare bright spot has appeared: a seminal paper published earlier this month in Trends In Cognitive Science, Identifying Indicators Of Consciousness In AI Systems. Authors include Turing-Award-winning AI researcher Yoshua Bengio, leading philosopher of consciousness David Chalmers, and even a few members of our conspiracy. If any AI consciousness research can rise to the level of merely awful, surely we will find it here. One might divide theories of consciousness into three bins: https://www.astralcodexten.com/p/the-new-ai-consciousness-paper

Join us for an inspiring conversation with Jack Dongarra, legendary computer scientist, Emeritus Professor at the University of Tennessee, and recipient of the ACM Turing Award. In this episode, host Stephen Ibaraki explores Jack Dongarra's remarkable journey, pioneering innovations in high performance computing, and the global impact of his work—foundational to scientific research, industry, and national security.Discover the origins of essential mathematical libraries, the evolution of supercomputers, and the future of exascale, cloud, and quantum computing. Learn how Jack Dongarra built communities, mentored generations of scientists, and shaped how we solve the world's biggest problems through simulation and data analysis.If you're a CEO, investor, technologist, or simply passionate about innovation—don't miss this deep dive into the future of computing, advice for new students, and a candid look at the power of mentorship and perseverance.

SOLID: Single-Responsibility, Open-Closed, Liskovsche Substitution, Interface-Segregation und Dependency-InversionSOLID klingt nach Fels in der Brandung, fühlt sich in der Praxis aber oft nach Abstraktionspyramide an. Brauchen wir die fünf Prinzipien heute noch oder bremsen sie uns beim Time-to-Market aus? In dieser Episode gehen wir genau dieser Frage nach und nehmen dich mit von der nicht ganz offiziellen SOLID-Entstehungsgeschichte über die wichtigsten Prinzipien bis hin zur ehrlichen Einordnung zwischen Clean Code, Teamrealität und AI-Overengineering.Wir starten mit dem S wie Single Responsibility und zerlegen den klassischen UserService: Was gehört rein, was raus, warum Utils-„Mülleimer“ gefährlich sind und wieso Komposition in der Praxis oft die bessere Wahl ist. Danach das O wie Open-Closed mit zwei greifbaren Beispielen: Rabattlogik ohne if-Hölle und Zahlungsanbieter-Design zwischen Switch Case und Strategie. Beim L wie Liskov Substitution wird es historisch und konkret: Barbara Liskov, Turing Award, Rechteck–Quadrat und die Frage, warum protected so oft Kapselung sprengt. Beim I wie Interface Segregation feiern wir kleine, fokussierte Interfaces, Duck Typing und die Go-Philosophie. Und beim D wie Dependency Inversion klären wir den Unterschied zu Dependency Injection, zeigen Injection-Varianten und warum Tests dadurch so viel leichter werden.Wir ordnen ein, wo SOLID glänzt und wo es Grenzen hat: Overengineering durch zu viele Klassen, DI-Container-Magic, ORMs, Microservices als Fehlinterpretation von SRP sowie der gesunde Trade-off zwischen sauberen Contracts und schneller Lieferung. Dazu Teamkultur statt Dogmatismus, Clean Code ohne Religion und die Erkenntnis, dass gute Architektur vor allem durch Datenflüsse, Domain-Zuschnitte und klare Systemgrenzen entsteht.Am Ende bleibt ein pragmatisches Playbook: Komposition über Vererbung, kleine Interfaces, klare Contracts, Injection wo es hilft und bewusstes Brechen von Regeln, wenn der Kontext es fordert.Bonus: Side Project-Idee aus der Community-Ecke. Baue einen Fax-zu-Discord-Bot. Wir integrieren ihn. Versprochen.Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

An open letter released Wednesday has called for a ban on the development of artificial intelligence systems considered to be “superintelligent” until there is broad scientific consensus that such technologies can be created both safely and in a manner the public supports. The statement, issued by the nonprofit Future of Life Institute, has been signed by more than 700 individuals, including Nobel laureates, technology industry veterans, policymakers, artists, and public figures such as Prince Harry and Meghan Markle, the Duke and Duchess of Sussex. The letter reflects deep and accelerating concerns over projects undertaken by technology giants like Google, OpenAI, and Meta Platforms that are seeking to build artificial intelligence capable of outperforming humans on virtually every cognitive task. According to the letter, such ambitions have raised fears about unemployment due to automation, loss of human control and dignity, national security risks, and the possibility of far-reaching social or existential harms. “We call for a prohibition on the development of superintelligence, not lifted before there is broad scientific consensus that it will be done safely and controllably, and strong public buy-in,” the statement reads. Signatories include AI pioneers Yoshua Bengio and Geoffrey Hinton, both recipients of the Turing Award, Apple co-founder Steve Wozniak, businessman Richard Branson, and actor Joseph Gordon-Levitt. Pentagon personnel could soon be told to participate in new training programs designed to prepare them for anticipated advancements in biotechnology and its convergence with other critical and emerging technologies, like quantum computing and AI. House lawmakers recently passed an amendment en bloc in their version of the fiscal 2026 National Defense Authorization Act that would mandate the secretary of defense to set up such trainings, no later than one year after the legislation's enactment. Biotechnology refers to a multidisciplinary field that involves the application of biological systems or the use of living organisms, like yeast and bacteria, to produce products or solve complex problems. These technologies are expected to revolutionize defense, energy, manufacturing and other sectors globally in the not-so-distant future — particularly as they are increasingly paired with and powered by AI. And while the U.S. historically has demonstrated many underlying strengths in the field, recent research suggests the government may be falling behind China, where biotechnology research efforts and investments have surged since the early 2000s. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

The story of how Geoffrey Hinton became “the godfather of AI” has reached mythic status in the tech world.While he was at the University of Toronto, Hinton pioneered the neural network research that would become the backbone of modern AI. (One of his students, Ilya Sutskever, went on to be one of OpenAI's most influential scientific minds.) In 2013, Hinton left the academy and went to work for Google, eventually winning both a Turing Award and a Nobel Prize.I think it's fair to say that artificial intelligence as we know it, may not exist without Geoffrey Hinton.But Hinton may be even more famous for what he did next. In 2023, he left Google and began a campaign to convince governments, corporations and citizens that his life's work – this thing he helped build – might lead to our collective extinction. And that moment may be closer than we think, because Hinton believes AI may already be conscious.But even though his warnings are getting more dire by the day, the AI industry is only getting bigger, and most governments, including Canada's, seem reluctant to get in the way.So I wanted to ask Hinton: If we keep going down this path, what will become of us?Mentioned:If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI, by Eliezer Yudkowsky and Nate SoaresAgentic Misalignment: How LLMs could be insider threats, by AnthropicMachines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail.Support for Machines Like Us is provided by CIFAR and the Max Bell School of Public Policy at McGill University. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Richard Sutton is the father of reinforcement learning, winner of the 2024 Turing Award, and author of The Bitter Lesson. And he thinks LLMs are a dead end.After interviewing him, my steel man of Richard's position is this: LLMs aren't capable of learning on-the-job, so no matter how much we scale, we'll need some new architecture to enable continual learning.And once we have it, we won't need a special training phase — the agent will just learn on-the-fly, like all humans, and indeed, like all animals.This new paradigm will render our current approach with LLMs obsolete.In our interview, I did my best to represent the view that LLMs might function as the foundation on which experiential learning can happen… Some sparks flew.A big thanks to the Alberta Machine Intelligence Institute for inviting me up to Edmonton and for letting me use their studio and equipment.Enjoy!Watch on YouTube; listen on Apple Podcasts or Spotify.Sponsors* Labelbox makes it possible to train AI agents in hyperrealistic RL environments. With an experienced team of applied researchers and a massive network of subject-matter experts, Labelbox ensures your training reflects important, real-world nuance. Turn your demo projects into working systems at labelbox.com/dwarkesh* Gemini Deep Research is designed for thorough exploration of hard topics. For this episode, it helped me trace reinforcement learning from early policy gradients up to current-day methods, combining clear explanations with curated examples. Try it out yourself at gemini.google.com* Hudson River Trading doesn't silo their teams. Instead, HRT researchers openly trade ideas and share strategy code in a mono-repo. This means you're able to learn at incredible speed and your contributions have impact across the entire firm. Find open roles at hudsonrivertrading.com/dwarkeshTimestamps(00:00:00) – Are LLMs a dead end?(00:13:04) – Do humans do imitation learning?(00:23:10) – The Era of Experience(00:33:39) – Current architectures generalize poorly out of distribution(00:41:29) – Surprises in the AI field(00:46:41) – Will The Bitter Lesson still apply post AGI?(00:53:48) – Succession to AIs Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

My guest today is Vinton G. Cerf, widely regarded as a “father of the Internet.” In the 1970s, Vint co-developed the TCP/IP protocols that define how data is formatted, transmitted, and received across devices. In essence, his work enabled networks to communicate, thus laying the foundation for the Internet as a unified global system. He has received honorary degrees and awards that include the National Medal of Technology, the Turing Award, the Presidential Medal of Freedom, the Marconi Prize, and membership in the National Academy of Engineering. He is currently Chief Internet Evangelist at Google.In this episode, Vint reflects on the Internet's path from ARPANET and TCP/IP to the scaling choices that made global connectivity possible. He explains why decentralization was key, and how fiber optics and data centers underwrote explosive growth. Vint also addresses today's policy anxieties (fragmentation, sovereignty walls, and fragile infrastructures…) before looking upward to the interplanetary Internet now linking spacecraft. Finally, we turn to AI: how LLMs are reshaping learning and software, and why the next leap may be systems that question us back. I hope you enjoy our discussion.You can follow me on X (@⁠ProfSchrepel⁠) and BlueSky (@⁠ProfSchrepel⁠).

In this episode of The Geek in Review, we welcome back Pablo Arredondo, VP of CoCounsel at Thomson Reuters, along with Joel Hron, the company's CTO. The conversation centers on the recent release of ChatGPT-5 and the rise of “reasoning models” that go beyond traditional language models' limitations. Pablo reflects on his years of tracking neural net progress in the legal field, from escaping “keyword prison” to the current ability of AI to handle complex, multi-step legal reasoning. He describes scenarios where entire litigation records could be processed to map out strategies for summary judgment motions, calling it a transformative step toward what he sees as “celestial legal products.”Joel brings an engineering perspective, comparing the legal sector's AI trajectory to the rapid advancements in AI developer tools. He notes that these tools have historically amplified the skills of top performers rather than leveling the playing field. Applied to law, he believes AI will free lawyers from rote work and allow them to focus on higher-value decisions and strategy. The discussion shifts to Deep Research, Thomson Reuters' latest enhancement for CoCounsel, which leverages reasoning models in combination with domain-specific tools like KeyCite to follow “breadcrumb trails” through case law with greater accuracy and transparency.The trio explores the growing importance of transparency and verification in AI-driven research. Joel explains how Deep Research provides real-time visibility into an AI's reasoning path, highlights potentially hallucinated citations, and integrates verification tools to cross-check references against authoritative databases. Pablo adds historical and philosophical perspective, likening hallucinations to a tiger “going tiger,” stressing that while the risk cannot be eliminated, the technology already catches a significant number of human errors. Both agree that AI tools must be accompanied by human oversight and well-designed workflows to build trust in their output.Looking to the future, Joel predicts that the adoption of AI agents will reshape organizational talent strategies, elevating the importance of those who excel at complex decision-making. Pablo proposes “ambient AI” as the next frontier—intelligent systems that unobtrusively monitor legal work, flagging potential issues instantly, much like a spellchecker. Both caution that certain legal tasks, especially in judicial opinion drafting, warrant careful consideration before fully integrating AI. The episode closes with practical insights on staying current, from following AI researchers on social platforms to reading technical blogs and academic papers, underscoring the need for informed engagement in this rapidly evolving space.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Academic Papers:Weekly research for trends.scholar.google.com,ssrn.com,arxiv.orgFrançois Chollet: Balanced AI insights. x.com/fcholletfchollet.comJason Wei (OpenAI): Reinforcement learning updates. x.com/jason_d_weopenai.com/blogGeoffrey Hinton: AI research insights.x.com/geoffreyhintonRichard Sutton: Reinforcement learning and philosophical takes.incompleteideas.netReinforcement Learning: An Introduction (Book):http://incompleteideas.net/book/RLbook2020.pdfSeminal work by Turing Award winner.University of Alberta Lab: https://rlai-lab.github.ioCurrent research on scalable AI methods.Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript

Useful Resources: 1. Ben Shneiderman, Professor Emeritus, University Of Maryland. 2. Richard Hamming and Hamming Codes. 3. Human Centered AI - Ben Shneiderman. 4. Allen Newell and Herbert A. Simon. 5. Raj Reddy and the Turing Award. 6. Doug Engelbart. 7. Alan Kay. 8. Conference on Human Factors in Computing Systems. 9. Software psychology: Human factors in computer and information systems - Ben Shneiderman. 10. Designing the User Interface: Strategies for Effective Human-Computer Interaction - Ben Shneiderman. 11. Direct Manipulation: A Step Beyond Programming Languages - Ben Shneiderman. 12. Steps Toward Artificial Intelligence - Marvin Minsky. 13. Herbert Gelernter. 14. Computers And Thought - Edward A Feigenbaum and Julian Feldman. 15. Lewis Mumford. 15. Technics and Civilization - Lewis Mumford. 16. Buckminster Fuller. 17. Marshall McLuhan. 18. Roger Shank. 19. The Anxious Generation: How the Great Rewiring of Childhood Is Causing an Epidemic of Mental Illness - Jonathan Haidt. 20. John C. Thomas, IBM. 21. Yousuf Karsh, photographer. 22. Gary Marcus, professor emeritus of psychology and neural science at NYU. 23. Geoffrey Hinton. 24. Nassim Nicholas Taleb. 25. There Is No A.I. - Jaron Lanier. 26. Anil Seth On The Science of Consciousness - Episode 94 of Brave New World. 27. A ‘White-Collar Blood Bath' Doesn't Have to Be Our Fate - Tim Wu 28. Information Management: A Proposal - Tim Berners-Lee 29. Is AI-assisted coding overhyped? : METR study 30. RLHF, Reinforcement learning from human feedback31. Joseph Weizenbaum 32. What Is Computer Science? - Allen Newel, Alan J. Perlis, Herbert A. Simon -- Check out Vasant Dhar's newsletter on Substack. The subscription is free!  

He pioneered AI, now he's warning the world. Godfather of AI Geoffrey Hinton breaks his silence on the deadly dangers of AI no one is prepared for. Geoffrey Hinton is a leading computer scientist and cognitive psychologist, widely recognised as the ‘Godfather of AI' for his pioneering work on neural networks and deep learning. He received the 2018 Turing Award, often called the Nobel Prize of computing. In 2023, he left Google to warn people about the rising dangers of AI. He explains: Why there's a real 20% chance AI could lead to HUMAN EXTINCTION. How speaking out about AI got him SILENCED. The deep REGRET he feels for helping create AI. The 6 DEADLY THREATS AI poses to humanity right now. AI's potential to advance healthcare, boost productivity, and transform education. 00:00 Intro 02:28 Why Do They Call You the Godfather of AI? 04:37 Warning About the Dangers of AI 07:23 Concerns We Should Have About AI 10:50 European AI Regulations 12:29 Cyber Attack Risk 14:42 How to Protect Yourself From Cyber Attacks 16:29 Using AI to Create Viruses 17:43 AI and Corrupt Elections 19:20 How AI Creates Echo Chambers 23:05 Regulating New Technologies 24:48 Are Regulations Holding Us Back From Competing With China? 26:14 The Threat of Lethal Autonomous Weapons 28:50 Can These AI Threats Combine? 30:32 Restricting AI From Taking Over 32:18 Reflecting on Your Life's Work Amid AI Risks 34:02 Student Leaving OpenAI Over Safety Concerns 38:06 Are You Hopeful About the Future of AI? 40:08 The Threat of AI-Induced Joblessness 43:04 If Muscles and Intelligence Are Replaced, What's Left? 44:55 Ads 46:59 Difference Between Current AI and Superintelligence 52:54 Coming to Terms With AI's Capabilities 54:46 How AI May Widen the Wealth Inequality Gap 56:35 Why Is AI Superior to Humans? 59:18 AI's Potential to Know More Than Humans 1:01:06 Can AI Replicate Human Uniqueness? 1:04:14 Will Machines Have Feelings? 1:11:29 Working at Google 1:15:12 Why Did You Leave Google? 1:16:37 Ads 1:18:32 What Should People Be Doing About AI? 1:19:53 Impressive Family Background 1:21:30 Advice You'd Give Looking Back 1:22:44 Final Message on AI Safety 1:26:05 What's the Biggest Threat to Human Happiness? Follow Geoffrey: X - https://bit.ly/4n0shFf  The Diary Of A CEO: Join DOAC circle here -https://doaccircle.com/ The 1% Diary is back - limited time only: https://bit.ly/3YFbJbt The Diary Of A CEO Conversation Cards (Second Edition): https://g2ul0.app.link/f31dsUttKKb Get email updates - https://bit.ly/diary-of-a-ceo-yt Follow Steven - https://g2ul0.app.link/gnGqL4IsKKb Sponsors: Stan Store - Visit https://link.stan.store/joinstanchallenge to join the challenge! KetoneIQ - Visit https://ketone.com/STEVEN  for 30% off your subscription order #GeoffreyHinton #ArtificialIntelligence #AIDangers Learn more about your ad choices. Visit megaphone.fm/adchoices

James Copnall, presenter of the BBC's Newsday, speaks to Yoshua Bengio, the world-renowned computer scientist often described as one of the godfathers of artificial intelligence, or AI.Bengio is a professor at the University of Montreal in Canada, founder of the Quebec Artificial Intelligence Institute - and recipient of an A.M. Turing Award, “the Nobel Prize of Computing”. AI allows computers to operate in a way that can seem human, by using programmes that learn vast amounts of data and follow complex instructions. Big tech firms and governments have invested billions of dollars in the development of artificial intelligence, thanks to its potential to increase efficiency, cut costs and support innovation.Bengio believes there are risks in AI models that attempt to mimic human behaviour with all its flaws. For example, recent experiments have shown how some AI models are developing the capacity to deceive and even blackmail humans, in a quest for their self-preservation. Instead, he says AI must be safe, scientific and working to understand humans without copying them. The Interview brings you conversations with people shaping our world, from all over the world. The best interviews from the BBC. You can listen on the BBC World Service, Mondays and Wednesdays at 0700 GMT. Or you can listen to The Interview as a podcast, out twice a week on BBC Sounds, Apple, Spotify or wherever you get your podcasts.Presenter: James Copnall Producers: Lucy Sheppard, Ben Cooper Editor: Nick HollandGet in touch with us on email TheInterview@bbc.co.uk and use the hashtag #TheInterviewBBC on social media.(Image: Yoshua Bengio. Credit: Craig Barritt/Getty)

Today's conversation with Turing Award-winning computer scientist LESLIE VALIANT explores a question I find myself returning to over and over again – What makes us human? What unique abilities have allowed homo sapiens to succeed, flourish, and dominate – knowing it's not our size, strength, or speed. His new book, THE IMPORTANCE OF BEING EDUCABLE: A NEW THEORY ON HUMAN UNIQUENESS, has added timeliness, as we confront a crisis of social mistrust as well as the threats and promise of AI.Valiant-03-31-2025 Transcript

Martin Hellman is an American cryptographer known for co-inventing public-key cryptography with Whitfield Diffie and Ralph Merkle in the 1970s. Their groundbreaking Diffie-Hellman key exchange method allowed secure communication over insecure channels, laying the foundation for modern encryption protocols. Hellman has also contributed to cybersecurity policy and ethical discussions on nuclear risk. His work has The post Turing Award Special: A Conversation with Martin Hellman appeared first on Software Engineering Daily.

Martin Hellman is an American cryptographer known for co-inventing public-key cryptography with Whitfield Diffie and Ralph Merkle in the 1970s. Their groundbreaking Diffie-Hellman key exchange method allowed secure communication over insecure channels, laying the foundation for modern encryption protocols. Hellman has also contributed to cybersecurity policy and ethical discussions on nuclear risk. His work has The post Turing Award Special: A Conversation with Martin Hellman appeared first on Software Engineering Daily.

David A. Patterson is a pioneering computer scientist known for his contributions to computer architecture, particularly as a co-developer of Reduced Instruction Set Computing, or RISC, which revolutionized processor design. He has co-authored multiple books, including the highly influential Computer Architecture: A Quantitative Approach. David is a UC Berkeley Pardee professor emeritus, a Google distinguished The post Turing Award Special: A Conversation with David Patterson appeared first on Software Engineering Daily.

David A. Patterson is a pioneering computer scientist known for his contributions to computer architecture, particularly as a co-developer of Reduced Instruction Set Computing, or RISC, which revolutionized processor design. He has co-authored multiple books, including the highly influential Computer Architecture: A Quantitative Approach. David is a UC Berkeley Pardee professor emeritus, a Google distinguished The post Turing Award Special: A Conversation with David Patterson appeared first on Software Engineering Daily.

Yann LeCun, Meta's chief AI scientist and Turing Award winner, joins us to discuss the limits of today's LLMs, why generative AI may be hitting a wall, what's missing for true human-level intelligence, the real meaning of AGI, Meta's open-source strategy with Llama, the future of AI assistants in smart glasses, why diversity in AI models matters, and how open models could shape the next era of innovation Support the show on Patreon! http://patreon.com/aiinsideshow Subscribe to the YouTube channel! http://www.youtube.com/@aiinsideshow Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 0:00:00 - Podcast begins 0:01:40 - Introduction to Yann LeCun, Chief AI Scientist at Meta 0:02:11 - The limitations and hype cycles of LLMs, and historical patterns of overestimating new AI paradigms. 0:05:45 - The future of AI research, and the need for machines that understand the physical world, can reason and plan, and are driven by human-defined objectives 0:14:47 - AGI Timeline, human-level AI within a decade, with deep learning as the foundation for advanced machine intelligence 0:21:35 - Why true AI intelligence requires abstract reasoning and hierarchical planning beyond language capabilities, unlike today's neural networks that rely on computational tricks 0:30:24 - Meta's open-source LLAMA strategy, empowering academia and startups, and commercial benefits 0:36:10 - The future of AI assistants, wearable tech, cultural diversity, and open-source models 0:42:52 - The impact of immigration policies on US technological leadership and STEM education 0:44:26 - Does Yann have a cat? 0:45:19 - Thank you to Yann LaCun for joining the AI Inside podcast Learn more about your ad choices. Visit megaphone.fm/adchoices

Software Engineering Daily: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- John Hennessy is a computer scientist, entrepreneur, and academic known for his significant contributions to computer architecture. He co-developed the RISC architecture, which revolutionized modern computing by enabling faster and more efficient processors. Hennessy served as the president of Stanford University from 2000 to 2016 and later co-founded MIPS Computer Systems and Atheros Communications. Currently, The post Turing Award Special: A Conversation with John Hennessy appeared first on Software Engineering Daily.

John Hennessy is a computer scientist, entrepreneur, and academic known for his significant contributions to computer architecture. He co-developed the RISC architecture, which revolutionized modern computing by enabling faster and more efficient processors. Hennessy served as the president of Stanford University from 2000 to 2016 and later co-founded MIPS Computer Systems and Atheros Communications. Currently, The post Turing Award Special: A Conversation with John Hennessy appeared first on Software Engineering Daily.

Jeffrey Ullman is a renowned computer scientist and professor emeritus at Stanford University, celebrated for his groundbreaking contributions to database systems, compilers, and algorithms. He co-authored influential texts like Principles of Database Systems and Compilers: Principles, Techniques, and Tools (often called the “Dragon Book”), which have shaped generations of computer science students. Jeffrey received the The post Turing Award Special: A Conversation with Jeffrey Ullman appeared first on Software Engineering Daily.

Jack Dongarra is an American computer scientist who is celebrated for his pioneering contributions to numerical algorithms and high-performance computing. He developed essential software libraries like LINPACK and LAPACK, which are widely used for solving linear algebra problems on advanced computing systems. Dongarra is also a co-creator of the TOP500 list, which ranks the world's The post Turing Award Special: A Conversation with Jack Dongarra appeared first on Software Engineering Daily.

Our 202nd episode with a summary and discussion of last week's big AI news! Recorded on 03/07/2025 Hosted by Andrey Kurenkov and Jeremie Harris. Feel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai Read out our text newsletter and comment on the podcast at https://lastweekin.ai/. Join our Discord here! https://discord.gg/nTyezGSKwP In this episode: Alibaba released Qwen-32B, their latest reasoning model, on par with leading models like DeepMind's R1. Anthropic raised $3.5 billion in a funding round, valuing the company at $61.5 billion, solidifying its position as a key competitor to OpenAI. DeepMind introduced BigBench Extra Hard, a more challenging benchmark to evaluate the reasoning capabilities of large language models. Reinforcement Learning pioneers Andrew Bartow and Rich Sutton were awarded the prestigious Turing Award for their contributions to the field. Timestamps + Links: cle picks: (00:00:00) Intro / Banter (00:01:41) Episode Preview (00:02:50) GPT-4.5 Discussion (00:14:13) Alibaba's New QwQ 32B Model is as Good as DeepSeek-R1 ; Outperforms OpenAI's o1-mini (00:21:29) With Alexa Plus, Amazon finally reinvents its best product (00:26:08) Another DeepSeek moment? General AI agent Manus shows ability to handle complex tasks (00:29:14) Microsoft's new Dragon Copilot is an AI assistant for healthcare (00:32:24) Mistral's new OCR API turns any PDF document into an AI-ready Markdown file (00:33:19) A.I. Start-Up Anthropic Closes Deal That Values It at $61.5 Billion (00:35:49) Nvidia-Backed CoreWeave Files for IPO, Shows Growing Revenue (00:38:05) Waymo and Uber's Austin robotaxi expansion begins today (00:38:54) UK competition watchdog drops Microsoft-OpenAI probe (00:41:17) Scale AI announces multimillion-dollar defense deal, a major step in U.S. military automation (00:44:43) DeepSeek Open Source Week: A Complete Summary (00:45:25) DeepSeek AI Releases DualPipe: A Bidirectional Pipeline Parallelism Algorithm for Computation-Communication Overlap in V3/R1 Training (00:53:00) Physical Intelligence open-sources Pi0 robotics foundation model (00:54:23) BIG-Bench Extra Hard (00:56:10) Cognitive Behaviors that Enable Self-Improving Reasoners (01:01:49) The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems (01:05:32) Pioneers of Reinforcement Learning Win the Turing Award (01:06:56) OpenAI launches $50M grant program to help fund academic research (01:07:25) The Nuclear-Level Risk of Superintelligent AI (01:13:34) METR's GPT-4.5 pre-deployment evaluations (01:17:16) Chinese buyers are getting Nvidia Blackwell chips despite US export controls

Jason Howell returns from Mobile World Congress with some AI trends to discuss along with Jeff Jarvis. OpenAI has some pricey plans in the works, Amazon announces Alexa Plus, and more! Support the show on Patreon! http://patreon.com/aiinsideshow Subscribe to the new YouTube channel! http://www.youtube.com/@aiinsideshow Note: Time codes subject to change depending on dynamic ad insertion by the distributor. NEWS 0:04:11 - Gemini Live ‘Astra' video and screen sharing rolling out in March 0:13:52 - Deutsche Telekom and Perplexity announce new ‘AI Phone' priced at under $1K 0:16:56 - OpenAI Plots Charging $20,000 a Month For PhD-Level Agents 0:22:31 - The LA Times published an op-ed warning of AI's dangers. It also published its AI tool's reply 0:28:22 - The future of Google Search just rolled out on Labs - and AI Mode changes everything 0:35:41 - Amazon announces AI-powered Alexa Plus 0:38:06 - Judge denies Musk's attempt to block OpenAI from becoming for-profit entity 0:39:18 - Eerily realistic AI voice demo sparks amazement and discomfort online 0:45:57 - Turing Award winners warn over unsafe deployment of AI models Learn more about your ad choices. Visit megaphone.fm/adchoices

Plus: After a long reprieve, one B.C. town faces the prospect of a renewed peacock invasion. Also: A conversation with AI pioneer Richard Sutton, co-winner of this year's Turing Award.

The consciousness testCould an artificial intelligence be capable of genuine conscious experience?Coming from a range of different scientific and philosophical perspectives, Yoshua Bengio, Sabine Hossenfelder, Nick Lane, and Hilary Lawson dive deep into the question of whether artificial intelligence systems like ChatGPT could one day become self-aware, and whether they have already achieved this state.Yoshua Bengio is a Turing Award-winning computer scientist. Sabine Hossenfelder is a science YouTuber and theoretical physicist. Nick Lane is an evolutionary biochemist. Hilary Lawson is a post-postmodern philosopher.To witness such topics discussed live buy tickets for our upcoming festival: https://howthelightgetsin.org/festivals/And visit our website for many more articles, videos, and podcasts like this one: https://iai.tv/You can find everything we referenced here: https://linktr.ee/philosophyforourtimesAnd don't hesitate to email us at podcast@iai.tv with your thoughts or questions on the episode! Who do you agree or disagree with?See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Professor Yoshua Bengio is a pioneer in deep learning and Turing Award winner. Bengio talks about AI safety, why goal-seeking “agentic” AIs might be dangerous, and his vision for building powerful AI tools without giving them agency. Topics include reward tampering risks, instrumental convergence, global AI governance, and how non-agent AIs could revolutionize science and medicine while reducing existential threats. Perfect for anyone curious about advanced AI risks and how to manage them responsibly. SPONSOR MESSAGES: *** CentML offers competitive pricing for GenAI model deployment, with flexible options to suit a wide range of models, from small to large-scale deployments. https://centml.ai/pricing/ Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on o-series style reasoning and AGI. Are you interested in working on reasoning, or getting involved in their events? They are hosting an event in Zurich on January 9th with the ARChitects, join if you can. Goto https://tufalabs.ai/ *** Interviewer: Tim Scarfe Yoshua Bengio: https://x.com/Yoshua_Bengio https://scholar.google.com/citations?user=kukA0LcAAAAJ&hl=en https://yoshuabengio.org/ https://en.wikipedia.org/wiki/Yoshua_Bengio TOC: 1. AI Safety Fundamentals [00:00:00] 1.1 AI Safety Risks and International Cooperation [00:03:20] 1.2 Fundamental Principles vs Scaling in AI Development [00:11:25] 1.3 System 1/2 Thinking and AI Reasoning Capabilities [00:15:15] 1.4 Reward Tampering and AI Agency Risks [00:25:17] 1.5 Alignment Challenges and Instrumental Convergence 2. AI Architecture and Safety Design [00:33:10] 2.1 Instrumental Goals and AI Safety Fundamentals [00:35:02] 2.2 Separating Intelligence from Goals in AI Systems [00:40:40] 2.3 Non-Agent AI as Scientific Tools [00:44:25] 2.4 Oracle AI Systems and Mathematical Safety Frameworks 3. Global Governance and Security [00:49:50] 3.1 International AI Competition and Hardware Governance [00:51:58] 3.2 Military and Security Implications of AI Development [00:56:07] 3.3 Personal Evolution of AI Safety Perspectives [01:00:25] 3.4 AI Development Scaling and Global Governance Challenges [01:12:10] 3.5 AI Regulation and Corporate Oversight 4. Technical Innovations [01:23:00] 4.1 Evolution of Neural Architectures: From RNNs to Transformers [01:26:02] 4.2 GFlowNets and Symbolic Computation [01:30:47] 4.3 Neural Dynamics and Consciousness [01:34:38] 4.4 AI Creativity and Scientific Discovery SHOWNOTES (Transcript, references, best clips etc): https://www.dropbox.com/scl/fi/ajucigli8n90fbxv9h94x/BENGIO_SHOW.pdf?rlkey=38hi2m19sylnr8orb76b85wkw&dl=0 CORE REFS (full list in shownotes and pinned comment): [00:00:15] Bengio et al.: "AI Risk" Statement https://www.safe.ai/work/statement-on-ai-risk [00:23:10] Bengio on reward tampering & AI safety (Harvard Data Science Review) https://hdsr.mitpress.mit.edu/pub/w974bwb0 [00:40:45] Munk Debate on AI existential risk, featuring Bengio https://munkdebates.com/debates/artificial-intelligence [00:44:30] "Can a Bayesian Oracle Prevent Harm from an Agent?" (Bengio et al.) on oracle-to-agent safety https://arxiv.org/abs/2408.05284 [00:51:20] Bengio (2024) memo on hardware-based AI governance verification https://yoshuabengio.org/wp-content/uploads/2024/08/FlexHEG-Memo_August-2024.pdf [01:12:55] Bengio's involvement in EU AI Act code of practice https://digital-strategy.ec.europa.eu/en/news/meet-chairs-leading-development-first-general-purpose-ai-code-practice [01:27:05] Complexity-based compositionality theory (Elmoznino, Jiralerspong, Bengio, Lajoie) https://arxiv.org/abs/2410.14817 [01:29:00] GFlowNet Foundations (Bengio et al.) for probabilistic inference https://arxiv.org/pdf/2111.09266 [01:32:10] Discrete attractor states in neural systems (Nam, Elmoznino, Bengio, Lajoie) https://arxiv.org/pdf/2302.06403

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Science is enabled by the fact that the natural world exhibits predictability and regularity, at least to some extent. Scientists collect data about what happens in the world, then try to suggest "laws" that capture many phenomena in simple rules. A small irony is that, while we are looking for nice compact rules, there aren't really nice compact rules about how to go about doing that. Today's guest, Leslie Valiant, has been a pioneer in understanding how computers can and do learn things about the world. And in his new book, The Importance of Being Educable, he pinpoints this ability to learn new things as the crucial feature that distinguishes us as human beings. We talk about where that capability came from and what its role is as artificial intelligence becomes ever more prevalent.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/04/15/272-leslie-valiant-on-learning-and-educability-in-computers-and-people/Support Mindscape on Patreon.Leslie Valiant received his Ph.D. in computer science from Warwick University. He is currently the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University. He has been awarded a Guggenheim Fellowship, the Knuth Prize, and the Turing Award, and he is a member of the National Academy of Sciences as well as a Fellow of the Royal Society and the American Association for the Advancement of Science. He is the pioneer of "Probably Approximately Correct" learning, which he wrote about in a book of the same name.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Yann LeCun is the Chief AI Scientist at Meta, professor at NYU, Turing Award winner, and one of the most influential researchers in the history of AI. Please support this podcast by checking out our sponsors: - HiddenLayer: https://hiddenlayer.com/lex - LMNT: https://drinkLMNT.com/lex to get free sample pack - Shopify: https://shopify.com/lex to get $1 per month trial - AG1: https://drinkag1.com/lex to get 1 month supply of fish oil EPISODE LINKS: Yann's Twitter: https://twitter.com/ylecun Yann's Facebook: https://facebook.com/yann.lecun Meta AI: https://ai.meta.com/ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (09:10) - Limits of LLMs (20:47) - Bilingualism and thinking (24:39) - Video prediction (31:59) - JEPA (Joint-Embedding Predictive Architecture) (35:08) - JEPA vs LLMs (44:24) - DINO and I-JEPA (45:44) - V-JEPA (51:15) - Hierarchical planning (57:33) - Autoregressive LLMs (1:12:59) - AI hallucination (1:18:23) - Reasoning in AI (1:35:55) - Reinforcement learning (1:41:02) - Woke AI (1:50:41) - Open source (1:54:19) - AI and ideology (1:56:50) - Marc Andreesen (2:04:49) - Llama 3 (2:11:13) - AGI (2:15:41) - AI doomers (2:31:31) - Joscha Bach (2:35:44) - Humanoid robots (2:44:52) - Hope for the future