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A Note from James:In the last episode, we talked about whether Martin Shkreli really deserves the label “most hated man in America.” My conclusion was no, and I hope you came to the same conclusion after hearing his perspective.In this episode, we shift gears completely. We talk about Bitcoin, crypto, AI, energy, optical computing, and what the future of technology might actually look like.Martin has a very unusual combination of skills—finance, biotech, programming—and I always enjoy hearing how he connects ideas across different fields. That's what this conversation is about.Episode Description:What happens when AI demand collides with the limits of computing power and energy?In Part 2, Martin Shkreli and James explore the future of technology—from crypto vulnerabilities to optical computing, GPU scaling, and the potential energy crisis driven by artificial intelligence.They discuss whether Bitcoin can survive quantum computing, why stablecoins solve real-world financial problems, and how computing architecture may shift beyond traditional silicon chips. The conversation then moves into AI economics: why companies might spend billions on compute to make better decisions, how energy constraints could shape innovation, and why optical computing could become the next major breakthrough.This episode isn't about controversy—it's about technological leverage, incentives, and where computation is heading next.What You'll Learn:Why quantum computing could eventually threaten Bitcoin's encryptionThe real-world advantages of stablecoins and decentralized paymentsHow AI demand could create massive new energy constraintsWhy optical (photonic) computing may outperform traditional silicon chipsHow businesses might use large-scale AI compute for strategic decisionsTimestamped Chapters:[00:02:00] Bitcoin, Encryption & Quantum Computing Risks[00:03:02] A Note from James[00:03:34] Crypto Markets: Speculation vs. Utility[00:05:23] Banking Control, Debanking & Stablecoins[00:07:40] Moore's Law, Huang's Law & The Limits of Silicon[00:08:45] Optical Computing Explained[00:09:12] NVIDIA, Parallelization & Power Consumption[00:10:24] Energy Constraints & The Electrical Grid[00:11:41] AI Energy Demand vs. Countries[00:12:24] Corporate AI Decision-Making at Scale[00:13:37] The Coming Explosion of AI Compute[00:14:20] Energy Efficiency vs. Speed[00:15:17] GPU Efficiency Improvements & Jevons Paradox[00:17:00] Why AI Is Different from Traditional Computing[00:17:47] Optical vs. Quantum vs. DNA Computing[00:18:19] Why Optical Computing Fits AI Perfectly[00:19:28] Precision, Bits & Neural Networks[00:21:24] Error Tolerance in AI Systems[00:22:00] Fiber Optics & Existing Infrastructure[00:23:16] New Computing Paradigms Beyond Silicon[00:24:00] Matrix Multiplication & AI Workloads[00:24:53] Closing ThoughtsSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Send a textTom Griffiths, Henry R. Luce Professor at Princeton University, joins the show to explore the surprising science behind how we actually think. His new book, The Laws of Thought, bridges computational cognitive science and AI—challenging assumptions about decision-making, neural networks, and the path to artificial general intelligence.Show NotesTimestamps 01:21 – Meet Tom Griffiths 05:27 – Tom's Book 06:58 – A Neural Network 09:55 – AGI? 19:10 – Writing the Book 20:45 – The Laws of Thought 27:24 – The Neural Network Surprise 31:33 – Learning from Experts 35:19 – Decision Making vs. Probability 42:36 – Government AI ConsiderationsLinks LinkedIn: linkedin.com/in/tom-griffiths-7b31a0364 Book: The Laws of Thought – Macmillan#TheLawsOfThought, #CognitiveScience, #ArtificialIntelligence, #AGI, #NeuralNetworks, #DecisionMaking, #Probability, #AIResearch, #Princeton, #TechPodcast, #MakingDataSimple, #AIGovernment, #MachineLearningWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
Send a textTom Griffiths, Henry R. Luce Professor at Princeton University, joins the show to explore the surprising science behind how we actually think. His new book, The Laws of Thought, bridges computational cognitive science and AI—challenging assumptions about decision-making, neural networks, and the path to artificial general intelligence.Show NotesTimestamps 01:21 – Meet Tom Griffiths 05:27 – Tom's Book 06:58 – A Neural Network 09:55 – AGI? 19:10 – Writing the Book 20:45 – The Laws of Thought 27:24 – The Neural Network Surprise 31:33 – Learning from Experts 35:19 – Decision Making vs. Probability 42:36 – Government AI ConsiderationsLinks LinkedIn: linkedin.com/in/tom-griffiths-7b31a0364 Book: The Laws of Thought – Macmillan#TheLawsOfThought, #CognitiveScience, #ArtificialIntelligence, #AGI, #NeuralNetworks, #DecisionMaking, #Probability, #AIResearch, #Princeton, #TechPodcast, #MakingDataSimple, #AIGovernment, #MachineLearningWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
How did we go from digital computers to AI seemingly everywhere? Neil deGrasse Tyson, Chuck Nice, & Gary O'Reilly dive into the mechanics of thinking, how AI got its start, and what deep learning really means with cognitive and computer scientist, Nobel Laureate, and one of the architects of AI, Geoffrey Hinton. Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
In this episode of the Crazy Wisdom podcast, host Stewart Alsop sits down with Markus Buehler, the McAfee Professor of Engineering at MIT, to explore how seemingly different systems—from proteins and music to knowledge structures and AI reasoning—share underlying patterns through hierarchy, self-organization, and scale-free networks. The conversation ranges from the limits of current AI interpolation versus true discovery (using the fire-to-fusion example), to the emergence of agent swarms and their non-linear effects, to practical questions about ontologies, knowledge graphs, and whether humans will remain necessary in the creative discovery process. Markus discusses his lab's work automating scientific discovery through AI agents that can generate hypotheses, run simulations, and even retrain themselves, while Stewart shares his own experiences building applications with AI coding agents and grapples with questions about intellectual property, material science constraints, and the future of human creativity in an AI-abundant world.Timestamps00:00 - Introduction to Marcus Buehler's work on knowledge graphs, structural grammar across proteins, music, and AI reasoning05:00 - Discussion of AI discovery versus interpolation, using fire and fusion as examples of fundamental versus incremental innovation10:00 - Language models as connective glue between agents, enabling communication despite imperfect outputs and canonical averaging15:00 - Embodiment and agency in AI systems, creating adversarial agents that challenge theories and expand world models20:00 - Emergent properties in materials and AI, comparing dislocations in metals to behaviors in agent swarms25:00 - Human role-playing and phase separation in society, parallels to composite materials and heterogeneity30:00 - Physical world challenges, atom-by-atom manufacturing at MIT.nano, limitations of lithography machines35:00 - Synthetic biology as alternative to nanotechnology, programming microorganisms for materials discovery40:00 - Intellectual property debates, commodification of AI models, control layers more valuable than model architecture45:00 - Automation of ontologies, agent self-testing, daughter's coding success at age 1150:00 - Graph theory for knowledge compression, neurosymbolic approaches combining symbolic and neural methods55:00 - Nonlinear acceleration in AI, emergence from accumulated innovations, restaurant owner embracing AI01:00:00 - Future generations possibly rejecting AI, democratization of knowledge, social media as real-time scientific discourseKey Insights1. Universal Patterns Across Disciplines: Seemingly different systems in nature—proteins, music, social networks, and knowledge itself—share fundamental structural patterns including hierarchy, self-organization, and scale-free networks. This commonality allows creative thinkers to draw insights across disciplines, applying principles from one domain to solve problems in another. As an engineer and materials scientist, Buehler has leveraged these isomorphisms to advance scientific understanding by mapping the "plumbing" of different systems onto each other, revealing hidden relationships that enable extrapolation beyond what's observable in any single domain.2. The Discovery Versus Interpolation Problem: Current AI systems, particularly large language models, excel at interpolation—recombining existing knowledge in new ways—but struggle with genuine discovery that requires fundamental rewiring of world models. Using the example of fire versus fusion, Buehler explains that an AI trained on combustion chemistry would propose bigger fires or new fuels, but couldn't conceive of fusion because that requires stepping back to more fundamental physics. True discovery demands the ability to recognize when existing theories have boundaries and to develop entirely new frameworks, something current AI architectures aren't designed to achieve due to their training objective of predicting the most likely outcome.3. The Role of Ontologies and Knowledge Graphs: While some AI researchers argue that ontologies are unnecessary because models form internal representations, Buehler advocates for explicit knowledge graphs as essential discovery tools. External ontologies provide sharp, analytical, symbolic representations that complement the fuzzy internal representations of neural networks. They enable verification of rare connections—like obscure papers that might hold key insights—which would be averaged away in standard AI training. This neurosymbolic approach combines the generalization capabilities of neural networks with the precision of formal knowledge structures, creating more powerful discovery systems.4. Emergent Properties and Agent Swarms: Just as materials science shows that collections of atoms exhibit properties impossible to predict from individual components, AI agent swarms demonstrate emergent behaviors beyond single models. When agents are incentivized not just to answer questions but to challenge each other adversarially, propose theories, and test hypotheses, they can spawn new copies of themselves and evolve understanding beyond their initial programming. This emergence isn't surprising from a materials science perspective—dislocations, grain boundaries, and other collective phenomena only appear at scale, fundamentally determining material behavior in ways unpredictable from studying just a few atoms.5. The Commoditization of Intelligence: The fundamental AI models themselves are becoming commodities, as evidenced by events like the Moldbug phenomenon where people built agents using various providers interchangeably. The real value is shifting from who has the smartest model to how models are orchestrated, integrated, and deployed. This parallels historical technology adoption patterns—just as we moved past debating who makes the best electricity to focusing on applications, AI is transitioning from a horse race over model capabilities to questions of infrastructure, energy, access speed, and agent coordination at the systems level.6. Human-AI Collaboration and Creative Control: Rather than wholesale replacement, AI enables humans to operate in an intensely creative space as orchestrators sampling from vast possibility spaces. Similar to how Buehler's 11-year-old daughter now builds sophisticated applications that would have required professional developers years ago, AI democratizes access to capabilities while humans retain the creative judgment about direction and meaning. The human role becomes curating emergence, finding rare connections, playing at the edges of knowledge, and exercising the kind of curiosity-driven exploration that AI systems lack without embodied stakes in their own survival and continuation.7. Technology as Evolutionary Inevitability: The development of AI represents not an unnatural threat but the next stage of human evolution—an extension of our innate drive to build models of ourselves and our world. From cave paintings to partial differential equations to artificial intelligence, humans continuously create increasingly sophisticated representations and tools. Attempting to stop this technological evolution is futile; instead, the focus should be on steering it ...
As AI accelerates innovation and adoption, leaders are facing rising cognitive load, shifting systems, and new emotional realities inside their organizations. In this episode, Deloitte's Chief Innovation Officer Deborah Golden joins us to explore how AI is reshaping leadership, why vulnerability and empathy are critical in this moment, and how anti-fragility, not just resilience, will define the future of work.Featuring:Deborah Golden – LinkedIn Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:DeloitteSponsor: Framer - The website builder that turns your dot com from a formality into a tool for growth. Check it out at framer.com/PRACTICALAIUpcoming Events: Register for upcoming webinars here!
AI is moving fast from research to real-world deployment, and when things go wrong, the consequences are no longer hypothetical. In this episode, Sean McGregor, co-founder of the AI Verification & Evaluation Research Institute and also the founder of the AI Incident Database, joins Chris and Dan to discuss AI safety, verification, evaluation, and auditing. They explore why benchmarks often fall short, what red-teaming at DEF CON reveals about machine learning risks, and how organizations can better assess and manage AI systems in practice.Featuring:Sean McGregor– LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:AI Verification & Evaluation Research InstituteAI Incident Database38th convening of IAAIBenchRiskState of Global AI Incident ReportingUpcoming Events: Register for upcoming webinars here!
AI agents are moving from demos to real workplaces, but what actually happens when they run a company? In this episode, journalist Evan Ratliff, host of Shell Game, joins Chris to discuss his immersive journalism experiment building a real startup staffed almost entirely by AI agents. They explore how AI agents behave as coworkers, how humans react when interacting with them, and where ethical and workplace boundaries begin to break down.Featuring:Evan Ratliff – LinkedIn, XChris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:Shell GameUpcoming Events: Register for upcoming webinars here!
As AI increasingly shapes geopolitics, elections, and civic life, its impact on democracy is becoming impossible to ignore. In this episode, Daniel and Chris are joined by security expert Bruce Schneier to explore how AI and technology are transforming democracy, governance, and citizenship. Drawing from his book Rewiring Democracy, they explore real examples of AI in elections, legislation, courts, and public AI models, the risks of concentrated power, and how these tools can both strengthen and strain democratic systems worldwide.Featuring:Bruce Schneier – XChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: Schneier on SecuritySponsors:Framer - The website builder that turns your dot com from a formality into a tool for growth. Check it out at framer.com/PRACTICALAIZapier - The AI orchestration platform that puts AI to work across your company. Check it out at zapier.com/practicalUpcoming Events: Register for upcoming webinars here!
As 2026 gets underway we know that many take time around this new beginning to improve not only their physical, but also their mental health. With that in mind, we're rerunning an episode with Leanne Williams on the future of depression care. Leanne is an expert on clinical depression and is working on new ways to more precisely diagnose depression in order to develop more effective treatment. For anyone who has suffered from depression or knows someone who has, it's an episode that provides hope for what's on the horizon. We hope you'll take another listen and also share this episode with anyone who you think may benefit from the conversation. Episode Reference Links:Stanford Profile: Leanne WilliamsConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest Leanne Williams, a professor of Psychiatry and Behavioral Science at Stanford University.(00:01:43) What Is Depression?Distinguishing clinical depression from everyday sadness.(00:03:31) Current Depression Treatment ChallengesThe trial-and-error of traditional depression treatments and their timelines.(00:06:16) Brain Mapping and Circuit DysfunctionsAdvanced imaging techniques and their role in understanding depression.(00:09:03) Diagnosing with Brain ImagingHow brain imaging can complement traditional diagnostic methods in psychiatry.(00:10:22) Depression BiotypesIdentifying six distinct biotypes of depression through brain imaging.(00:12:31) Cognitive Features of DepressionHow cognitive impairment plays a major role in certain depression biotypes.(00:14:11) Matching Treatments to BiotypesFinding appropriate treatments sooner using brain-based diagnostics.(00:15:38) Expanding Treatment OptionsPersonalizing therapies and improving treatment outcomes based on biotypes.(00:19:03) AI in Depression TreatmentUsing AI to refine biotypes and predict treatment outcomes with greater accuracy.(00:22:15) Psychedelics in Depression TreatmentThe potential for psychedelic drugs to target specific biotypes of depression.(00:23:46) Expanding the Biotypes FrameworkIntegrating multimodal approaches into the biotype framework.(00:27:29) Reducing Stigma in DepressionHow showing patients their brain imaging results reduces self-blame and stigma.(00:29:38) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
Think you know the story of AI's rise and fall? This episode upends conventional wisdom with guest historian Thomas Haigh, who reveals why the infamous "AI winter" might just be a myth and why the field's biggest failures fueled today's breakthroughs. Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI NVDA, GOOGL, META: AI Spending Forecast to Hit $2.53 Trillion This Year Nvidia, Eli Lilly just say yes to making drugs together, using Vera Rubin GPUs Claude Cowork Exfiltrates Files We put Claude Code in Rollercoaster Tycoon How Generative AI is destroying society - by Gary Marcus Anthropic rewrites Claude's guiding principles—and entertains the idea that its AI might have 'some kind of consciousness or moral status' Claude's new constitution Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Thomas Haigh Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: bitwarden.com/twit monarch.com with code IM
As generative AI moves into production, traditional guardrails and input/output filters can prove too slow, too expensive, and/or too limited. In this episode, Alizishaan Khatri of Wrynx joins Daniel and Chris to explore a fundamentally different approach to AI safety and interpretability. They unpack the limits of today's black-box defenses, the role of interpretability, and how model-native, runtime signals can enable safer AI systems. Featuring:Alizishaan Khatri – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XUpcoming Events: Register for upcoming webinars here!
Send us a textWelcome back Rounds Table Listeners! We are back today with a solo episode with Dr. John Fralick. This week, he discusses a recently published trial examining the effect of a Mediterranean diet, compared with traditional dietary advice, on irritable bowel syndrome (IBS). Here we go!The Mediterranean Diet for Irritable Bowel Syndrome: A Randomized Clinical Trial (0:00 – 4:50).The Good Stuff (4:51 – 5:57):3Blue1Brown's Neural Network educational video series: Check out the playlist on YouTubeQuestions? Comments? Feedback? We'd love to hear from you! @roundstable @InternAtWork @MedicinePods
Traditional vulnerability management is simple: find the flaw, patch it, and verify the fix. But what happens when the "asset" is a neural network that has learned something ethically wrong? In this episode, Sapna Paul (Senior Manager at Dayforce) explains why there are no "Patch Tuesdays" for AI models .Sapna breaks down the three critical layers of AI vulnerability management: protecting production models, securing the data layer against poisoning, and monitoring model behavior for technically correct but ethically flawed outcomes . We discuss how to update your risk register to speak the language of business and the essential skills security professionals need to survive in an AI-first world .The conversation also covers practical ways to use AI within your security team to combat alert fatigue , the importance of explainability tools like SHAP and LIME , and how to align with frameworks like the NIST AI RMF and the EU AI Act .Guest Socials - Sapna's LinkedinPodcast Twitter - @CloudSecPod If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-Cloud Security Podcast- Youtube- Cloud Security Newsletter If you are interested in AI Security, you can check out our sister podcast - AI Security PodcastQuestions asked:(00:00) Introduction(02:00) Who is Sapna Paul?(02:40) What is Vulnerability Management in the Age of AI? (05:00) Defining the New Asset: Neural Networks & Models (07:00) The 3 Layers of AI Vulnerability (Production, Data, Behavior) (10:20) Updating the Risk Register for AI Business Risks (13:30) Compliance vs. Innovation: Preventing AI from Going Rogue (18:20) Using AI to Solve Vulnerability Alert Fatigue (23:00) Skills Required for Future VM Professionals (25:40) Measuring AI Adoption in Security Teams (29:20) Key Frameworks: NIST AI RMF & EU AI Act (31:30) Tools for AI Security: Counterfit, SHAP, and LIME (33:30) Where to Start: Learning & Persona-Based Prompts (38:30) Fun Questions: Painting, Mentoring, and Vegan Ramen
THE AI WINTER Colleague Gary Rivlin. The history of Frank Rosenblatt's neural networks, their dismissal by Marvin Minsky in favor of rules-based computing, and the decades-long "winter" before the resurgence of machine learning. NUMBER 11
In this start-of-year FC episode, Chris and Daniel break down what really mattered in AI in 2025, and what to expect in 2026. They explore the rise of AI agents, the practical reality of multimodal AI, and how reasoning models are reshaping workflows. The conversation dives into infrastructure and energy constraints, the continued value of predictive models, and why orchestration (not just better models) is becoming the defining skill for AI teams. The episode wraps with grounded 2026 predictions on where AI systems, tooling, and builders are headed next.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsor:Framer - The enterprise-grade website builder that lets your team ship faster. Get 30% off at framer.com/practicalaiUpcoming Events: Register for upcoming webinars here!
Adam Marblestone is CEO of Convergent Research. He's had a very interesting past life: he was a research scientist at Google Deepmind on their neuroscience team and has worked on everything from brain-computer interfaces to quantum computing to nanotech and even formal mathematics.In this episode, we discuss how the brain learns so much from so little, what the AI field can learn from neuroscience, and the answer to Ilya's question: how does the genome encode abstract reward functions? Turns out, they're all the same question.Watch on YouTube; read the transcript.Sponsors* Gemini 3 Pro recently helped me run an experiment to test multi-agent scaling: basically, if you have a fixed budget of compute, what is the optimal way to split it up across agents? Gemini was my colleague throughout the process — honestly, I couldn't have investigated this question without it. Try Gemini 3 Pro today gemini.google.com* Labelbox helps you train agents to do economically-valuable, real-world tasks. Labelbox's network of subject-matter experts ensures you get hyper-realistic RL environments, and their custom tooling lets you generate the highest-quality training data possible from those environments. Learn more at labelbox.com/dwarkeshTo sponsor a future episode, visit dwarkesh.com/advertise.Timestamps(00:00:00) – The brain's secret sauce is the reward functions, not the architecture(00:22:20) – Amortized inference and what the genome actually stores(00:42:42) – Model-based vs model-free RL in the brain(00:50:31) – Is biological hardware a limitation or an advantage?(01:03:59) – Why a map of the human brain is important(01:23:28) – What value will automating math have?(01:38:18) – Architecture of the brainFurther readingIntro to Brain-Like-AGI Safety - Steven Byrnes's theory of the learning vs steering subsystem; referenced throughout the episode.A Brief History of Intelligence - Great book by Max Bennett on connections between neuroscience and AIAdam's blog, and Convergent Research's blog on essential technologies.A Tutorial on Energy-Based Learning by Yann LeCunWhat Does It Mean to Understand a Neural Network? - Kording & LillicrapE11 Bio and their brain connectomics approachSam Gershman on what dopamine is doing in the brainGwern's proposal on training models on the brain's hidden states Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe
As AI reshapes the workplace, employees and leaders face questions about meaningful work, automation, and human impact. In this episode, Jason Beutler, CEO of RoboSource, shares how companies can rethink workflows, integrate AI in accessible ways, and empower employees without fear. The discussion covers leveraging AI to handle routine tasks (SOPs or "plays") and reimagining work for smarter, more human-centered outcomes.Featuring:Jason Beutler – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsor:Framer – Design and publish without limits with Framer, the free all-in-one design platform. Unlimited projects, no tool switching, and professional sites—no Figma imports or HTML hassles required. Start creating for free at framer.com/design with code `PRACTICALAI` for a free month of Framer Pro.Upcoming Events: Register for upcoming webinars here!
It's faster than a speeding bullet. It's smarter than a polymath genius. It's everywhere but it's invisible. It's artificial intelligence. But what actually is it?Today we ask this simple question and explore why it's so damn hard to answer.Special thanks to Stephanie Yin and the New York Institute of Go for teaching us the game. Mark, Daria and Levon Hoover Brauner for helping bring NETtalk to life. And a huge thank you to Grant Sanderson for his unending patience explaining the math of neural nets to us. To learn more about how these 'thinking machines' actually think, we highly recommend his wonderful youtube channel 3Blue1Brown (https://www.youtube.com/watch?v=aircAruvnKk).EPISODE CREDITS: Reported by - Simon AdlerProduced by - Simon AdlerOriginal music from - Simon AdlerSound design contributed by - Simon AdlerFact-checking by - Anna Pujol-Mazzini Sign up for our newsletter!! It includes short essays, recommendations, and details about other ways to interact with the show. Signup (https://radiolab.org/newsletter)!Radiolab is supported by listeners like you. Support Radiolab by becoming a member of The Lab (https://members.radiolab.org/) today.Follow our show on Instagram, Twitter and Facebook @radiolab, and share your thoughts with us by emailing radiolab@wnyc.org.Leadership support for Radiolab's science programming is provided by the Gordon and Betty
Chris and Daniel talk with returning guest, Ramin Mohammadi, about how those seeking to get into AI Engineer/ Data Science jobs are expected to come in a mid level engineers (not entry level). They explore this growing gap along with what should (or could) be done in academia to focus on real world skills vs. theoretical knowledge. Featuring:Ramin Mohammadi – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiUpcoming Events: Register for upcoming webinars here!
The dataset contains images of children's faces downloaded from websites about autism, which sparked concerns at Springer Nature about consent and reliability.
This week Thinking Out Loud with Friends of SoundBroker welcomes Devin Sheets, owner of Alpha Labs who is making waves with their cutting-edge audio software, zero-latency DE-FEEDBACK V1 plugin, which promises to revolutionize live sound by eliminating feedback and room reverb.We'll discuss the development of DE-FEEDBACK, tips, and tricks, and actual hands-on experiences. This your opportunity to ask Devin questions and share your own experiences.AN OPEN CONVERSATION WITH FRIENDS THAT LOVE THE WORLD OF CONCERT AND SPECIAL EVENT PRODUCTIONSJoin our current events support zoomcast show hosted by Jan Landy and his knowledgeable affable panel of friends and colleagues for an entertaining robust discussion offering opinions on anything related to a working professional life in general.Our ZoomCast isn't just a fountain of knowledge; it's also a opportunity to laugh. Think of it as therapy, but with more jokes and fewer couches. Join us and share your thoughts. Stay updated on life and world events, and enjoy multiple good chuckles along the way.
ReferencesJCI Insight .2023. May 22;8(10):e164921.J Diabetes Investig . 2024 Mar;15(3):282-284Mozart WA. 1788. Divertimento Trio in E flat Major. K 563https://music.youtube.com/watch?v=E8c83bpOVXo&si=no6hE0__w7tx5lVH
ReferencesJ Diabetes Investig.2019 Nov; 10(6): 1430–1437J Diabetes Investig. 2010 Apr 22;1(1-2):8–23J Diabetes Investig. 2016 Mar 14;7(Suppl 1):20–26EMBO Rep(2025)26: 5154 - 5171Davies, D.1970 Strangers. Kinkshttps://music.youtube.com/watch?v=p9TD5qn3fm4&si=csVw0acg0WfDyEbiJoel, B. 1977 The Strangerhttps://music.youtube.com/watch?v=X3kpaSJtaDE&si=ljQxauyI721yFs8qMorrison/ Krieger/Densmore 1967. Strange Days lphttps://music.youtube.com/playlist?list=OLAK5uy_nQKdoZqyfOqKrkHKvBqOYBm4m1YpWyKY4&si=KkLFoDVXGhfoV05s
Chris and Daniel unpack how AI-driven document processing has rapidly evolved well beyond traditional OCR with many technical advances that fly under the radar. They explore the progression from document structure models to language-vision models, all the way to the newest innovations like Deepseek-OCR. The discussion highlights the pros and cons of these various approaches focusing on practical implementation and usage.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiFramer – Design and publish without limits with Framer, the free all-in-one design platform. Unlimited projects, no tool switching, and professional sites—no Figma imports or HTML hassles required. Start creating for free at framer.com/design with code `PRACTICALAI` for a free month of Framer Pro.Upcoming Events: Register for upcoming webinars here!
Smart technology designed to help rovers and drones is now revolutionizing quality control in food production factories on Earth.
ReferencesJ Neurophysiol. 1993 Aug;70(2):742–757.J Clin Immunol. 2025 Oct 1;45(1):141. Front Immunol. 2025 Sep 4;16:1660161.Guerra, DJ.2025.Unpublished LecturesJ Physiol. 2016 May 29;594(20):5791–5815Bach, JS 1717- 1723. Violin Concerti E, D A and Ghttps://music.youtube.com/playlist?list=OLAK5uy_lmUKX_Xp0OkaA5DCja6iviqbI7z28pW68&si=6rqmiT-6Ng64Tb7M
The AI revolution of the past few years is built on brain-inspired neural network models originally developed to study our own minds. The question is, what should we make of the fact that our own rich mental lives are built on the same foundations as the seemingly soulless chat-bots we now interact with on a daily basis?Our guest this week is Stanford cognitive scientist Jay McClelland, who has been a leading figure in this field since the 1980s, when he developed some of the first of these artificial neural network models. Now McClelland has a new book, co-authored with SF State University computational neuroscientist Gaurav Suri, called "The Emergent Mind: How Intelligence Arises in People and Machines." We spoke with McClelland about the entangled history of neuroscience and AI, and whether the theory of the emergent mind described in the book can help us better understand ourselves and our relationship with the technology we've created.Learn More New book sheds light on human and machine intelligence | Stanford ReportHow Intelligence – Both Human and Artificial – Happens | KQED Forum From Brain to Machine: The Unexpected Journey of Neural Networks | Stanford HAIWu Tsai Neuro's Center for Mind, Brain, Computation and TechnologyMcClelland, J. L. & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review, 88, 375-407. [PDF]Rumelhart, D. E., McClelland, J. L., & the PDP research group. (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Volumes I & II. Cambridge, MA: MIT Press.McClelland, J. L. & Rogers, T. T. (2003). The parallel distributed processing approach to semantic cognition. Nature Reviews Neuroscience, 4, 310-322. [PDF]McClelland, J. L., Hill, F., Rudolph, M., Baldridge, J., & Schuetze, H. (2020). Placing language in and integrated understanding system: Next steps toward human-level performance in neural language models. Proceedings of the National Academy of Sciences, 117(42), 25966-25974. [Send us a text!Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience. We want to hear from your neurons! Email us at at neuronspodcast@stanford.edu Learn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn.
This episode is a special crossover between the Practical AI podcast and The Changelog podcast. Chris was recently invited by longtime friends Jerod Santo and Adam Stacoviak, cohosts of The Changelog, to join them on the show. They discuss AI, drones, robotics, swarming technology, and the rise of high-performance edge computing with Rust. Chris points out that open source software, small AI models, and affordable hardware are making home automation and local AI accessible to everyone. From automating household functions to experimenting with drones and single-board computers, Chris describes how hands-on maker projects are shaping a bright future for physical AI, on small budgets and right from the comfort of your own home.Featuring: Jerod Santo – LinkedInAdam Stacoviak – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XSponsors: Miro – Get the right things done faster with Miro's Innovation Workspace. AI Sidekicks, instant insights, and rapid prototyping—transform weeks of work into days. No more scattered docs or endless meetings. Help your teams get great done at Miro.com.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiUpcoming Events: Register for upcoming webinars here!This week we have extended show notes below from Chris!Swarming & Fully Autonomous Multi-Agent UxV SystemsChris's Definition of Swarming (anchor link in show notes)Chris's definition of Swarming“Swarming occurs when numerous independent fully-autonomous multi-agentic platforms exhibit highly-coordinated locomotive and emergent behaviors with agency and self-governance in any domain (air, ground, sea, undersea, space), functioning as a single independent logical distributed decentralized decisioning entity for purposes of C3 (command, control, communications) with human operators on-the-loop, to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.”© 2025 Chris BensonConceptual FoundationsSwarm Robotics – WikipediaHigh-level overview of swarm robotics as decentralized robot collectives.https://en.wikipedia.org/wiki/Swarm_roboticsSwarm Robotic Platforms – WikipediaSurvey of hardware platforms used in swarm robotics research.https://en.wikipedia.org/wiki/Swarm_robotic_platformsSwarm Intelligence – WikipediaBroader algorithms and theory behind collective intelligence (beyond robots).https://en.wikipedia.org/wiki/Swarm_intelligenceAnt Robotics – WikipediaNature-inspired “ant-like” robotics as a special case of swarm robotics.https://en.wikipedia.org/wiki/Ant_roboticsOpen Research & Multi-Robot Resources (Stepping-Stones Toward True Swarms)Programming Multiple Robots with ROS 2 (online book)Free book on multi-robot systems, ROS 2, and the Robot Middleware Framework (RMF).https://osrf.github.io/ros2multirobotbookSimulation with ROS 2 & Gazebo (ROS 2 Humble tutorial)Official tutorial on connecting ROS 2 to Gazebo simulation.https://docs.ros.org/en/humble/Tutorials/Advanced/Simulators/Gazebo/Gazebo.htmlSpawning Multiple Robots in Gazebo with ROS 2Hands-on tutorial to launch N robots in Gazebo, each with its own namespace.https://www.theconstruct.ai/spawning-multiple-robots-in-gazebo-with-ros2ROS 2 Multi-Robot Simulation Best Practices (Discourse thread)Discussion of patterns for multi-robot systems (domains, namespaces, Nav2, etc.).https://discourse.openrobotics.org/t/multi-robot-simulation-best-practices/38987Getting Hands-On: Consumer Robotics, ROS 2 & GazeboROS 2 (Robot Operating System 2)Official ROS 2 Documentation – Humble (LTS)Main docs for ROS 2 Humble (recommended distro) with tutorials and APIs.https://docs.ros.org/en/humbleROS 2 Installation Guide (Humble)Step-by-step install on supported platforms.https://docs.ros.org/en/humble/Installation.html“From Zero to Robotics Hero: A Beginner's Guide to ROS 2” (article)Beginner-friendly overview with ideas for where to go next (MoveIt, Nav2, multi-robot, etc.).https://riyagoja.medium.com/from-zero-to-robotics-hero-a-beginners-guide-to-ros-2-90ac9c3b87baROS 2 Tutorial for Beginners (2025 guide)Up-to-date intro that walks you from install to simulating your first robot in 2025.https://www.timesofexplore.com/2025/10/ros2-tutorial-beginners-build-first-robot-2025.htmlGazebo SimulationGazebo Sim – Official SiteModern Gazebo (Ignition) simulator; models, worlds, and docs.https://gazebosim.orgGetting Started with Gazebo (Docs)Official “start here” guide for using Gazebo and Gazebo Fuel assets.https://gazebosim.org/docs/latest/getstartedClassic Gazebo Tutorials (still useful for fundamentals)https://classic.gazebosim.org/tutorialsmicro-ROS (ROS 2 on Microcontrollers)micro-ROS – ROS 2 for MicrocontrollersOfficial site for running ROS 2 on tiny embedded boards.https://micro.ros.orgmicro-ROS GitHub OrganizationRepositories, examples, and tutor...
Episode: 3343 Frank Rosenblatt's perceptron and the quest to design machines that can learn. Today, the origin of learning in artificial neural networks.
Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
Machine learning using neural networks has led to a remarkable leap forward in artificial intelligence, and the technological and social ramifications have been discussed at great length. To understand the origin and nature of this progress, it is useful to dig at least a little bit into the mathematical and algorithmic structures underlying these techniques. Anil Ananthaswamy takes up this challenge in his book Why Machines Learn: The Elegant Math Behind Modern AI. In this conversation we give a brief overview of some of the basic ideas, including the curse of dimensionality, backpropagation, transformer architectures, and more.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/11/24/336-anil-ananthaswamy-on-the-mathematics-of-neural-nets-and-ai/Support Mindscape on Patreon.Anil Ananthaswamy received a Masters degree in electrical engineering from the University of Washington, Seattle. He is currently a freelance science writer and feature editor for PNAS Front Matter. He was formerly the deputy news editor for New Scientist, a Knight Science Journalism Fellow at MIT, and journalist-in-residence at the Simon Institute for the Theory of Computing, University of California, Berkeley. He organizes an annual science journalism workshop at the National Centre for Biological Sciences at Bengaluru, India.Web siteAmazon author pageWikipediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Episode: 3341 How Warren McCulloch and Walter Pitts laid the foundation for current AI research. Today, the origin of artificial neural networks.
Fireflies CEO, Krish Ramineni shares how the company is transforming AI-powered note-taking into a deeper layer of knowledge automation. He breaks down the technology behind real-time functionality like Live Assist, the user behavior patterns driving product evolution, and how Fireflies is innovating far beyond meetings. Krish also shares insights on future trends in AI and the potential for hardware integration, emphasizing the ongoing evolution of AI in knowledge work.Featuring:Krish Ramineni – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Fireflies AISponsors:Miro – Get the right things done faster with Miro's Innovation Workspace. AI Sidekicks, instant insights, and rapid prototyping—transform weeks of work into days. No more scattered docs or endless meetings. Help your teams get great done at [Miro](https://miro.com).Framer – Design and publish without limits with Framer, the free all-in-one design platform. Unlimited projects, no tool switching, and professional sites—no Figma imports or HTML hassles required. Start creating for free at [framer.com/design](https://www.framer.com/design/) with code `PRACTICALAI` for a free month of Framer Pro.Upcoming Events: Register for upcoming webinars here!
How is your brain like an ant colony? They both use simple parts following simple rules which allows the whole to be so much more than the sum of the parts. Listen as neuroscientist and author Gaurav Suri explains how the mind emerges from the neural network of the brain, why habits form, why intuition often knows before language does, and why our post-hoc explanations can mislead us. The conversation then grapples with free will and responsibility without mysticism. Ultimately, Suri remains in awe of the emergent mind and at the end of the conversation makes the case for the essential importance of kindness and forgiveness.
Waymo's VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.Featuring:Drago Anguelov – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Waymo ResearchNew Insights for Scaling Laws in Autonomous DrivingAI in MotionSponsors: Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Register for upcoming webinars here!
Dan and Chris unpack whether today's surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation?Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: Powell says that, unlike the dotcom boom, AI spending isn't a bubble: ‘I won't go into particular names, but they actually have earnings'Sponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!
In this episode, we explore the intriguing balance between innovation and data privacy as we approach the AI Age. How will future technologies like AI, digital neural networks, and large language models reshape our world by 2045 or 2050? We'll dive into the implications of EU AI regulations and GDPR, discussing how they impact digital trust and ethics. Join host Punit Bhatia as he shares insights on how leaders are tackling these pressing issues in privacy laws and AI technology. Tune in for a thought-provoking discussion on the future of privacy that will keep you informed and engaged.KEY CONVERSATIONS 00:02:29 How do you see the future in 2045 or 2050? Will it all be digital? 00:13:27 How does one balance privacy and innovation? 00:19:39 Hypothetical question: An option to embed a chip on yourself, would you take it? 00:21:39 Understanding Digital Neural Network 00:27:06 About Nicola's Book: Artificial Intelligence, Neural Networks & Privacy 00:34:53 Where can we people get Nicola's current and upcoming books ABOUT THE GUEST Nicola Fabiano is a distinguished Italian lawyer with a rich background in data protection, privacy, and artificial intelligence (AI) regulation. As an adjunct professor at Ostrava University in Rome and a former President of the San Marino Data Protection Authority, he brings a wealth of expertise to the table. Nicola has served as a national expert for the Republic of San Marino on key committees of the Council of Europe, including those focused on Convention No. 108 and the Ad hoc Committee on Artificial Intelligence. With his extensive experience as a government advisor for drafting legislation on personal data protection and his innovative contributions such as the Data Protection and Privacy Relationships Model (DAPPREMO), Nicola is at the forefront of shaping AI policy and ethics. He is a certified professional in various domains including security management, data protection, and privacy assessment. Nicola's memberships in prestigious organizations like the European AI Alliance and his role as a technical expert for the European Data Protection Board further highlight his influence in the field. With numerous publications to his name, Nicola Fabiano continues to be a leading voice in the intersection of law, technology, and ethics. ABOUT THE HOST Punit Bhatia is one of the leading privacy experts who works independently and has worked with professionals in over 30 countries. Punit works with business and privacy leaders to create an organization culture with high privacy awareness and compliance as a business priority. Selectively, Punit is open to mentor and coach privacy professionals. Punit is the author of books “Be Ready for GDPR'' which was rated as the best GDPR Book, “AI & Privacy – How to Find Balance”, “Intro To GDPR”, and “Be an Effective DPO”. Punit is a global speaker who has spoken at over 30 global events. Punit is the creator and host of the FIT4PRIVACY Podcast. This podcast has been featured amongst top GDPR and privacy podcasts. As a person, Punit is an avid thinker and believes in thinking, believing, and acting in line with one's value to have joy in life. He has developed the philosophy named ‘ABC for joy of life' which passionately shares. Punit is based out of Belgium, the heart of Europe. RESOURCES Websites www.fit4privacy.com,www.punitbhatia.com, https://www.linkedin.com/in/nicfab/, https://www.fabiano.law/en/ , https://growskills.store/ Podcast https://www.fit4privacy.com/podcast Blog https://www.fit4privacy.com/blog YouTube http://youtube.com/fit4privacy
In this episode, we explore the intriguing balance between innovation and data privacy as we approach the AI Age. How will future technologies like AI, digital neural networks, and large language models reshape our world by 2045 or 2050? We'll dive into the implications of EU AI regulations and GDPR, discussing how they impact digital trust and ethics. Join host Punit Bhatia as he shares insights on how leaders are tackling these pressing issues in privacy laws and AI technology. Tune in for a thought-provoking discussion on the future of privacy that will keep you informed and engaged.KEY CONVERSION 00:02:29 How do you see the future in 2045 or 2050? Will it all be digital? 00:13:27 How does one balance privacy and innovation? 00:19:39 Hypothetical question: An option to embed a chip on yourself, would you take it? 00:21:39 Understanding Digital Neural Network 00:27:06 About Nicola's Book: Artificial Intelligence, Neural Networks & Privacy 00:34:53 Where can we people get Nicola's current and upcoming booksABOUT THE GUEST Nicola Fabiano is a distinguished Italian lawyer with a rich background in data protection, privacy, and artificial intelligence (AI) regulation. As an adjunct professor at Ostrava University in Rome and a former President of the San Marino Data Protection Authority, he brings a wealth of expertise to the table. Nicola has served as a national expert for the Republic of San Marino on key committees of the Council of Europe, including those focused on Convention No. 108 and the Ad hoc Committee on Artificial Intelligence. With his extensive experience as a government advisor for drafting legislation on personal data protection and his innovative contributions such as the Data Protection and Privacy Relationships Model (DAPPREMO), Nicola is at the forefront of shaping AI policy and ethics. He is a certified professional in various domains including security management, data protection, and privacy assessment. Nicola's memberships in prestigious organizations like the European AI Alliance and his role as a technical expert for the European Data Protection Board further highlight his influence in the field. With numerous publications to his name, Nicola Fabiano continues to be a leading voice in the intersection of law, technology, and ethics. ABOUT THE HOST Punit Bhatia is one of the leading privacy experts who works independently and has worked with professionals in over 30 countries. Punit works with business and privacy leaders to create an organization culture with high privacy awareness and compliance as a business priority. Selectively, Punit is open to mentor and coach privacy professionals. Punit is the author of books “Be Ready for GDPR'' which was rated as the best GDPR Book, “AI & Privacy – How to Find Balance”, “Intro To GDPR”, and “Be an Effective DPO”. Punit is a global speaker who has spoken at over 30 global events. Punit is the creator and host of the FIT4PRIVACY Podcast. This podcast has been featured amongst top GDPR and privacy podcasts. As a person, Punit is an avid thinker and believes in thinking, believing, and acting in line with one's value to have joy in life. He has developed the philosophy named ‘ABC for joy of life' which passionately shares. Punit is based out of Belgium, the heart of Europe.RESOURCES Websites www.fit4privacy.com,www.punitbhatia.com, https://www.linkedin.com/in/nicfab/, https://www.fabiano.law/en/ Podcast https://www.fit4privacy.com/podcast Blog https://www.fit4privacy.com/blog YouTube http://youtube.com/fit4privacy
Dan and Chris sit down (again) with Jared Zoneraich, co-founder and CEO of PromptLayer, to discuss how prompt engineering has evolved into context engineering (and while loops with tool calls). Jared shares insights on building flexible AI applications, managing tool calls, testing and versioning prompts, and empowering both technical and non-technical users in AI development. Along the way, they dive into coding agents and the “crawl-walk-run” approach to AI deployment.Featuring: Jared Zoneraich – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:PromptLayerUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!
Constellations, a New Space and Satellite Innovation Podcast
With more than 50% of the Earth covered in clouds on any given day, the ability to provide real-time insights about what is happening on the ground becomes complicated and nearly impossible. Listen in as Aubrey Dunne – co-founder and CTO at Ubotica - shares his knowledge on AI-based intelligence, cloud detection and removal for Earth observation satellites that deliver insights about what's happening on Earth now.
Neural Networks and AI have a keen ability to generate the monster of HP Lovecraft, probably because these cosmic horrors are described by inconceivable colors, surreal visages, and non-Euclidean shapes. These are also often our descriptions of the underworld, netherworld, upsidedown, and spirit realm. We reach it in dreams, NDEs, via certain substances, or through other unintentional but natural methods. It appears that technology can allow us to tap into this world, too, implying that it is both a real place and an extension of the mind, perhaps another reality that consciousness can explore - or the backend of a computer program. The geometry and therianthropes of the shaman can be seen abstractly in AI-Lovecraft, which appears etheric, ghost-like, and not well-defined, precisely the descriptions our ancestors gave of the changing seasons - especially Halloween. *The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below underneath the show description.FREE ARCHIVE (w. ads)SUBSCRIPTION ARCHIVEX / TWITTER FACEBOOKWEBSITEBuyMe-CoffeePaypal: rdgable1991@gmail.comCashApp: $rdgable EMAIL: rdgable@yahoo.com / TSTRadio@protonmail.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-secret-teachings--5328407/support.
In this fully connected episode, Daniel and Chris explore the emerging concept of tiny recursive networks introduced by Samsung AI, contrasting them with large transformer based models. They explore how these small models tackle reasoning tasks with fewer parameters, less data, and iterative refinement, matching the giants on specific problems. They also discuss the ethical challenges of emotional manipulation in chatbots.Featuring: Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Less is More: Recursive Reasoning with Tiny NetworksResearchers detail 6 ways chatbots seek to prolong ‘emotionally sensitive events'Sponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Fabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiMiro – The innovation workspace for the age of AI. Built for modern teams, Miro helps you turn unstructured ideas into structured outcomes—fast. Diagramming, product design, and AI-powered collaboration, all in one shared space. Start building at miro.comUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!
In this engaging podcast episode of SuperPsyched, host Dr. Adam Dorsay interviews Dr. Louis Cozolino, a leading psychologist and professor at Pepperdine University, about the effectiveness and mechanisms of psychotherapy. They delve into how psychotherapy works, its impact on the brain, and the roles of various therapeutic modalities. Dr. Cozolino shares personal anecdotes and insights into his journey into psychology, the importance of feeling both safe and challenged in therapy, and the significance of neuroplasticity in mental health. The episode also discusses the therapeutic process, the value of listening, and the balance between challenge and support in effective therapy.00:00 Welcome to SuperPsyched00:29 The Evolution of Therapy01:02 Introducing Dr. Louis Cozolino02:17 Lou's Journey to Psychology04:57 The Impact of Books06:03 Understanding Psychotherapy Modalities09:43 Neuroplasticity and Therapy12:46 The Power of EMDR20:04 Choosing the Right Therapist28:41 The Subjectivity of Therapy29:48 The Role of Workbooks in Therapy30:46 The Magic and Mystery of Therapy31:39 Core Beliefs and Rewriting Narratives32:22 Buddhist Philosophy and Neuroscience33:44 Therapy and Childhood Memories35:46 The Costs and Benefits of Reconnecting36:45 Neural Networks and Symptomatic Behavior38:09 The Role of Parents and Environment39:19 The Complexity of Therapy41:41 Feeling Felt in Therapy44:33 Balancing Safety and Challenge49:16 The Importance of Listening53:32 Final Thoughts and ResourcesHelpful Links:Dr. Louis Cozolino WebsiteDr. Louis Cozolino PepperdineThe Neuroscience of Psychotherapy: Healing the Social Brain Book
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What is life? What is intelligence? What is… complexity? Neil deGrasse Tyson, Chuck Nice, and Gary O'Reilly learn how complexity science, chaos theory, and emergence help us understand our place in the universe with David Krakauer, president of the Santa Fe Institute.NOTE: StarTalk+ Patrons can listen to this entire episode commercial-free here:https://startalkmedia.com/show/emergence-explained-with-david-krakauer/Thanks to our Patrons teonie, Dixie Gamoning, Greg Meyer, Mike Bilodeau, Mitchell Keesler, john hutt, Karen Buss, The Merry Widow, Casandra Martin, Swaraj Jaiswal, Hoang Nguyen, Knooble Gooble, Panainte Victor, Peter Jensen, Rajesh Bhaidasna, Victor Pomales, George Mulder, Life Space and the Lot, RandomBrian423, blitzgrub, Travis Bridges, Sreya Kumpatla, Erik Scheirer, Natalie Tabor, SwaZam!, KILOCREAMYY, Lisa Peldiak, Tosin Awofeso, Joe Buzz, daevon pearson, Amie Christy, Simone Adair, Philippe, Logan Davis, Ted Parsons, Macs Ton, Ben, Quentin Ferguson, Ash De Zylva, Evalena Marie, Nancy Bijok, Jacob Garcia, The Preschool Doctor, Amber Shaw, Erin, ilya, Kevin Nguyen, Austin Weets, and Alan G for supporting us this week. Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus.
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