Podcasts about neural networks

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!

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

As AI systems move from simple chatbots to complex agentic workflows, new security risks emerge. In this episode, Donato Capitella unpacks how increasingly complicated architectures are making agents fragile and vulnerable. These agents can be exploited through prompt injection, data exfiltration, and tool misuse. Donato shares stories from real-world penetration tests, the design patterns for building LLM agents and explains how his open-source toolkit Spikee (Simple Prompt Injection Kit for Evaluation and Exploitation) is helping red teams probe AI systems.Featuring:Donato Capitella – LinkedIn, XChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:ReversecSponsors: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!

You haven't used ChatGPT's Apps yet?

Discover how WebAI is revolutionizing AI by enabling powerful models to run directly on devices.About the episode:Nataraj chats with David Stout, founder of WebAI, about bringing AI infrastructure to edge devices. David shares his journey from a Michigan farm to pioneering techniques for compressing AI models onto phones, laptops, and even airplanes. They discuss the importance of data privacy, real-time processing, and the shift from cloud-based AI to a web of interconnected, specialized AI systems working across devices. Learn about WebAI's vision for the future of AI and how they achieved a $700 million valuation.What you'll learn- Understand the limitations of cloud-based AI and the advantages of edge computing for data privacy and real-time processing.- Discover how WebAI compresses and optimizes large AI models to run efficiently on everyday devices like phones and laptops.- Learn about the potential of a decentralized “web of models” and how it could revolutionize various industries.- Explore the key factors driving WebAI's success, including their focus on horizontal technology and support for diverse AI models.- Gain insights into the future of AI hardware and software.About the Guest and Host:Guest Name: David Stout, Founder of WebAI, pioneering AI infrastructure for edge devices.Connect with Guest:→ LinkedIn: https://www.linkedin.com/in/davidpstout/ → Website: https://www.webai.com/Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.→ LinkedIn: https://www.linkedin.com/in/natarajsindam/→ Substack: ⁠https://startupproject.substack.com/⁠In this episode, we cover(00:01) Introduction and Guest Introduction(01:35) David's Journey in AI and Machine Learning(03:51) Bringing AI Models to Devices(05:49) Applications of AI on Devices(08:10) The Thesis for Starting Web AI(11:16) Optimizing for Specialized Models(15:02) Web AI's Customers and Use Cases(17:00) Hardware Optimization for Web AI(19:12) Lightweight Personal Models(22:55) The Trajectory of Foundational Model Companies and AGI(31:48) Emergent Behavior and Intelligence(35:17) Prompts Don't Pay Bills(41:22) Meta's Approach to Recruiting and Spending(44:51) Form Factors in AI(51:04) Surprising AI Products(52:42) Breakthroughs in AI Research(56:31) XAI's Models(01:03:24) The Future of Google and Search(01:06:39) Finding David and WebAIDon't forget to subscribe and leave us a review/comment on YouTube Apple Spotify or wherever you listen to podcasts.#AI #EdgeComputing #MachineLearning #DataPrivacy #WebAI #ArtificialIntelligence #DecentralizedAI #AIInfrastructure #Startup #Technology #Innovation #Podcast #Entrepreneurship #TechStartups #DeepLearning #ModelCompression #AIModels #Inference #NatarajSindam #StartupProject

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Daniel sits down with Chelsea Linder, VP of Innovation and Entrepreneurship at TechPoint, to explore the what AI innovation and impact look like on the ground.  They discuss Chelsea's journey from the VC world into economic development/ innovation, the growth of an AI innovation network in Indiana (funded by the SBA), lessons learned from fostering AI communities, and how businesses are actually adapting to AI. Chelsea also shares insights from Techpoints AI workforce impact study, which explored AI related job creation and levels of AI adoption among other things.Featuring:Chelsea Linder – LinkedIn Daniel Whitenack – Website, GitHub, XLinks: TechpointSponsors: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!

A near-death crash leaves Paul seeing strange, sheet-like entities that drift between life and death—and follow him home.L.N. Hunter's comic fantasy novel, ‘The Feather and the Lamp,' sits alongside works in anthologies such as ‘The Monsters Next Door' and ‘Best of British Science Fiction 2022' as well as Short Édition's ‘Short Circuit' and the ‘Horrifying Tales of Wonder' podcast. There have also been papers in the IEEE ‘Transactions on Neural Networks,' which are probably somewhat less relevant and definitely less fun. When not writing, L.N. unwinds in a disorganised home in rural Cambridgeshire, UK, along with two cats and a soulmate.You can read "Shadows" at https://www.kaidankaistories.com.Website: kaidankaistories.comPlease feel free to contact me through the website contact form.Follow us on: InstagramFacebookBlueskySubstack

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Longtime friend of the show Rajiv Shah returns to unpack lessons from a year of building retrieval-augmented generation (RAG) pipelines and reasoning models integrations. We dive into why so many AI pilots stumble, why evaluation and error analysis remain essential data science skills, and why not every enterprise challenge calls for a large language model.Featuring:Rajiv Shah – LinkedIn Daniel Whitenack – Website, GitHub, XUpcoming 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!

We need AI systems to synthesise new knowledge, not just compress the data they see. Jeremy Berman, is a research scientist at Reflection AI and recent winner of the ARC-AGI v2 public leaderboard.**SPONSOR MESSAGES**—Take the Prolific human data survey - https://www.prolific.com/humandatasurvey?utm_source=mlst and be the first to see the results and benchmark their practices against the wider community!—cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the cybernetic economyOct SF conference - https://dagihouse.com/?utm_source=mlst - Joscha Bach keynoting(!) + OAI, Anthropic, NVDA,++Hiring a SF VC Principal: https://talent.cyber.fund/companies/cyber-fund-2/jobs/57674170-ai-investment-principal#content?utm_source=mlstSubmit investment deck: https://cyber.fund/contact?utm_source=mlst— Imagine trying to teach an AI to think like a human i.e. solving puzzles that are easy for us but stump even the smartest models. Jeremy's evolutionary approach—evolving natural language descriptions instead of python code like his last version—landed him at the top with about 30% accuracy on the ARCv2.We discuss why current AIs are like "stochastic parrots" that memorize but struggle to truly reason or innovate as well as big ideas like building "knowledge trees" for real understanding, the limits of neural networks versus symbolic systems, and whether we can train models to synthesize new ideas without forgetting everything else. Jeremy Berman:https://x.com/jerber888TRANSCRIPT:https://app.rescript.info/public/share/qvCioZeZJ4Q_NlR66m-hNUZnh-qWlUJcS15Wc2OGwD0TOC:Introduction and Overview [00:00:00]ARC v1 Solution [00:07:20]Evolutionary Python Approach [00:08:00]Trade-offs in Depth vs. Breadth [00:10:33]ARC v2 Improvements [00:11:45]Natural Language Shift [00:12:35]Model Thinking Enhancements [00:13:05]Neural Networks vs. Symbolism Debate [00:14:24]Turing Completeness Discussion [00:15:24]Continual Learning Challenges [00:19:12]Reasoning and Intelligence [00:29:33]Knowledge Trees and Synthesis [00:50:15]Creativity and Invention [00:56:41]Future Directions and Closing [01:02:30]REFS:Jeremy's 2024 article on winning ARCAGI1-pubhttps://jeremyberman.substack.com/p/how-i-got-a-record-536-on-arc-agiGetting 50% (SoTA) on ARC-AGI with GPT-4o [Greenblatt]https://blog.redwoodresearch.org/p/getting-50-sota-on-arc-agi-with-gpt https://www.youtube.com/watch?v=z9j3wB1RRGA [his MLST interview]A Thousand Brains: A New Theory of Intelligence [Hawkins]https://www.amazon.com/Thousand-Brains-New-Theory-Intelligence/dp/1541675819https://www.youtube.com/watch?v=6VQILbDqaI4 [MLST interview]Francois Chollet + Mike Knoop's labhttps://ndea.com/On the Measure of Intelligence [Chollet]https://arxiv.org/abs/1911.01547On the Biology of a Large Language Model [Anthropic]https://transformer-circuits.pub/2025/attribution-graphs/biology.html The ARChitects [won 2024 ARC-AGI-1-private]https://www.youtube.com/watch?v=mTX_sAq--zY Connectionism critique 1998 [Fodor/Pylshyn]https://uh.edu/~garson/F&P1.PDF Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis [Kumar/Stanley]https://arxiv.org/pdf/2505.11581 AlphaEvolve interview (also program synthesis)https://www.youtube.com/watch?v=vC9nAosXrJw ShinkaEvolve: Evolving New Algorithms with LLMs, Orders of Magnitude More Efficiently [Lange et al]https://sakana.ai/shinka-evolve/ Deep learning with Python Rev 3 [Chollet] - READ CHAPTER 19 NOW!https://deeplearningwithpython.io/

Jimmy Secretan, CTO of JustWin, explores the latest innovations in privacy-preserving neural networks, and explains how JustWin is leveraging AI to help small businesses win government contracts. He also explores the future directions of AI, and the impact of AI on user autonomy and privacy. Key Takeaways: Technological advancements shaping the future of secure and ethical AI applications The significance of open-endedness in AI How to build while balancing both innovation and privacy Why AI solutions are a good fit for winning RFPs GPT-5 and predictions for its future impact Guest Bio: Jimmy Secretan, CTO of JustWin, holds a Ph.D. from the Machine Learning Lab at the University of Central Florida, where he specialized in large-scale, privacy-safe neural networks. Having previously served as Chief Scientist at Korrelate, VP of Engineering of Sonobi, and CTO of Roadtrippers, Jimmy has architected privacy-safe AI/ML data pipelines, scaled infrastructure to hundreds of billions of requests per month to power predictive media planning, and led the creation of the AI-driven future of travel data. As VP of Ads and Premium Services at Brave, Jimmy helped launch Brave's global private ad network; led the development of premium functionality for the Brave browser; and managed initiatives like Brave News and Brave Talk. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

In this episode, we dive into the evolving landscape of industrial AI, starting with a lively Oktoberfest recap before shifting gears to the latest breakthroughs in physics-informed neural networks and user interfaces. We discuss the real-world impact of Europe's AI Act, featuring insights from industry leaders and an in-depth interview with Sampo Leino of MinnaLearn on building AI literacy for enterprises. As we unpack strategic investments, robotics trends, and the challenges of compliance, we question what it means to use AI safely and competitively. Throughout the conversation, we keep it grounded in everyday experience—how regulation, technology, and practical learning are shaping the factories and workplaces of tomorrow. Tune in to hear how we're navigating this complex, fast-moving frontier and what it means for anyone working with AI today.

In this episode, Daniel and Chris are joined by Chris Aquino, software engineer at Thunderbird to hear the story of how they developed a privacy-preserving AI executive assistant. They discuss various design decisions including remote (but confidential) inference, local encryption, and model selection. Chris A. does an amazing job describing the journey from "let the big LLM do everything" to splitting apart the workflow to be handled by multiple models. Featuring:Chris Aquino – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: ThunderbirdThunderbird ProSponsors: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: 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!

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Friedemann Zenke's 2019 paper, and its related coding tutorial SpyTorch, made it possible to apply modern machine learning to spiking neural networks. The innovation reinvigorated the field.

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In this Fully Connected episode, we dig into the recent MIT report revealing that 95% of AI pilots fail before reaching production and explore what it actually takes to succeed with AI solutions. We dive into the importance of AI model integration, asking the right questions when adopting new technologies, and why simply accessing a powerful model isn't enough. We explore the latest AI trends, from GPT-5 to open source models, and their impact on jobs, machine learning, and enterprise strategy. Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: The GenAI Divide: State of AI in Business 2025MIT Report: 95% of generative AI pilots at companies are failingSponsors:Miro – 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.comShopify – 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: 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!

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AI Daily Rundown: September 09th, 2025Hello AI Unraveled listeners, and welcome to today's news where we cut through the hype to find the real-world business impact of AI.Today's Headlines:

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Today Lee Sharkey of Goodfire joins The Cognitive Revolution to discuss his research on parameter decomposition methods that break down neural networks into interpretable computational components, exploring how his team's "stochastic parameter decomposition" approach addresses the limitations of sparse autoencoders and offers new pathways for understanding, monitoring, and potentially steering AI systems at the mechanistic level. Check out our sponsors: Oracle Cloud Infrastructure, Shopify. Shownotes below brought to you by Notion AI Meeting Notes - try one month for free at ⁠⁠⁠⁠https://⁠⁠notion.com/lp/nathan Parameter vs. Activation Decomposition: Traditional interpretability methods like Sparse Autoencoders (SAEs) focus on analyzing activations, while parameter decomposition focuses on understanding the parameters themselves - the actual "algorithm" of the neural network. No "True" Decomposition: None of the decompositions (whether sparse dictionary learning or parameter decomposition) are objectively "right" because they're all attempting to discretize a fundamentally continuous object, inevitably introducing approximations. Tradeoff in Interpretability: There's a balance between reconstruction loss and causal importance - as you decompose networks more, reconstruction loss may worsen, but interpretability might improve up to a certain point. Potential Unlearning Applications: Parameter decomposition may make unlearning more straightforward than with SAEs because researchers are already working in parameter space and can directly modify vectors that perform specific functions. Function Detection vs. Input Direction: A function like "deception" might manifest in many different input directions that SAEs struggle to identify as a single concept, while parameter decomposition might better isolate such functionality. Knowledge Extraction Goal: A key aim is to extract knowledge from models by understanding how they "think," especially for tasks where models demonstrate superhuman capabilities. Sponsors: Oracle Cloud Infrastructure: Oracle Cloud Infrastructure (OCI) is the next-generation cloud that delivers better performance, faster speeds, and significantly lower costs, including up to 50% less for compute, 70% for storage, and 80% for networking. Run any workload, from infrastructure to AI, in a high-availability environment and try OCI for free with zero commitment at https://oracle.com/cognitive Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive

Daniel and Chris sit with Citadel AI's Rick Kobayashi and Kenny Song and unpack AI safety and security challenges in the generative AI era. They compare Japan's approach to AI adoption with the US's, and explore the implications of real-world failures in AI systems, along with strategies for AI monitoring and evaluation.Featuring:Rick Kobayashi – LinkedInKenny Song – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Citadel AIRegister for upcoming webinars here!

In this podcast, I called the US a Technocracy, BUT I believe a new word is needed for what is really happening, which is a government ran by AI. Thus, moving forward, I'll be calling a government run by AI as a Neuracracy. Thus, referring to the Neural Networks used by AI.SummaryIn this episode, Clayton Cuteri delves into the complexities of consciousness and spirituality, while also addressing pressing political issues such as the Ukraine war, foreign interventions, and the ethical implications of civilian casualties. He critiques the current state of American identity amidst technological control and raises concerns about the future of humanity, urging listeners to consider their role in shaping a pro-human political landscape.Clayton's Social MediaLinkTree | TikTok | Instagram | Twitter (X) | YouTube | RumbleTimecodes00:00 - Intro01:03 - Political Dynamics: Zelensky, Trump, and the Ukraine War04:47 - The Consequences of Foreign Interventions08:32 - Civilian Casualties and the Ethics of War12:24 - America's Identity Crisis and Technological Control17:14 - The Future of Humanity: Pro-Human or Anti-Human?Intro/Outro Music Producer: Don KinIG: https://www.instagram.com/donkinmusic/Spotify: https://open.spotify.com/artist/44QKqKsd81oJEBKffwdFfPSuper grateful for this guy ^Send Clayton a text message!Support the showNEWSLETTER - SIGN UP HERE

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Join me for a podcast summary looking at Ai in orthodonticsand its clinical application. A growing topic in orthodontics, and one of themost featured topics at this years AAO. This summary is based on 3 lectures fromthis year's summer meeting by Juan Francisco Gonzalez & Jean Marc Retrouvey,Tarek ElShebiny , Jonas Bianchi and Lucia Cevidanes. We will look whatAi is, the way it works and its clinical application, as well as a criticalview on this young field.  What is Ai: 1.       Technology that enables computers and machinesto simulate human intelligence, perform 1 task very well, e.g. voice command, Youtuberecommendations2.       Predictive modelling, makes calculations,  convert information into numbers or categoriesand recognise patterns  Levels of Ai: Machine learning, Neural Networks and Deep Learning1.       Machine learninga.       The ability for a machine to learn from data andpast experience to identify patterns and make predictions  2.       Neural Networks  a.       Specific model which relies on interconnectednodes, which perform a mathematical calculation of associations , patterns, andprobabilities 3.       Deep learninga.       Is a complex version of neural networks Virtual patient·     CBCT segment + STL file – segmentation of theteeth and roots, with labelling of different stuctureso  Can print model, visualise ideal vector andcalculate ideal vectoro  However clinician still required to establish biomechanics ·     CBCT integration for aligner cases, Unpublishedthesis Khalid Alotaibi:o  Treatment planning confidence increased 50%, leastchange was treatment planning modification  Diagnostic data:·     Ai cephalometric tracingo  46% of 24 landmarks 2.0mm withino  4 different programmes  Iortho, Webceph, Orthodc, cephxo  All landmarks had good overall agreement butvariation in identification  ·     Facial Analysis·     Automated 3D facial asymmetry analysis usingmachine learning  Adel 2025o  Study – 7 landmarks o  Identified manually and with deep learning o  5 accurate, 2 significant difference but notclinically relevant Diagnostic accuracy of photos·     Clinical photos assessment by Ai, and comparedto clinical examination·     Sensitivity 72%, specificity 54% Vaughan & Ahmed2025  Growth prediction·     Poor agreement age 9  Comparison between direct, virtual and AI bonding·     DIBs – uses Ai for bonding·     Compare Ai Vs user modified indirect bonding Vsdirect bonding (gold standard), 0.5mm significant ·     Incisors accurate·     Premolars and lower laterals inaccurate  Monitoring Previous podcast exploring the accuracy of remote monitoringo   with Ferlito 2022 80%repeatability from 2 scans 44.7% repeatability and reproducibility  Bracket removal from scan and retainer fitTarek Assessment of virtual bracket removal by artificialintelligence and thermoplastic retainer fit AJODO 2024o  Retainers for both – clinically acceptable    FDA approval of Ai in dentistry·     FDA - Software of Medical Diagnosis § 4  dental:·     Dental Monitoring·     Ray Co ·     X-Nav technologies·     Densply Sirona    What's next·     More data learning to train AI model·     Robotics customising appliances per patient    

Dan and Chris break down Winning the Race: America's AI Action Plan, issued by the White House in July 2025.  Structured as three "pillars" — Accelerate AI Innovation, Build American AI Infrastructure, and Lead in International AI Diplomacy and Security — our dynamic duo unpack the plan's policy goals and its associated suggestions — while also exploring the mixed reactions it's sparked across political lines. They connect the plan to international AI diplomacy and national security interests, discuss its implications for practitioners, and consider how political realities could shape its success in the years ahead. Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Press Release: White House Unveils America's AI Action PlanPaper: America's AI Action PlanSponsors: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/practicalaiRegister for upcoming webinars here!

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Allegra Guinan of Lumiera helps leaders turn uncertainty about AI into confident, strategic leadership. In this conversation, she brings some actionable insights for navigating the hype and complexity of AI. The discussion covers challenges with implementing responsible AI practices, the growing importance of user experience and product thinking, and how leaders can focus on real-world business problems over abstract experimentation.Featuring:Allegra Guinan – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:LumieraSponsors: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/practicalaiRegister for upcoming webinars here!

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.

Dan sits down with guests Mark Daniel Ward and Katie Sanders from The Data Mine at Purdue University to explore how higher education is evolving to meet the demands of the AI-driven workforce. They share how their program blends interdisciplinary learning, corporate partnerships, and real-world data science projects to better prepare students across 160+ majors. From AI chatbots to agricultural forecasting, they discuss the power of living-learning communities, how the data mine model is spreading to other institutions and what it reveals about the future of education, workforce development, and applied AI training.Featuring:Mark Daniel Ward – LinkedInKatie Sanders – LinkedInDaniel Whitenack – Website, GitHub, XLinks:The Data MineSponsors: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/practicalaiRegister for upcoming webinars here!

Prioritizing brain health in children is crucial, as their brains continue to mature until around age 20, making them particularly susceptible to manipulation before reaching full cognitive development. In our present technology, a digital detox has been shown to provide effective coping mechanisms for our neural networks, enabling us to better regulate our emotions and adapt to real-life situations.. To seek the antidote for the rise of device addiction and the decline of human connection, Harvesting Happiness Podcast Host Lisa Cypers Kamen talks with Dr. Carl D. Marci, a leader in the field of social and consumer neuroscience, about the impact of digital technology on brain health. Dr. Marci talks about how our devices can cause addiction and who is most susceptible. He also shares tips on how to consciously complete a digital detox and prepare ourselves and our children for the next wave of AI technology, as well as concrete findings from his book, REWIRED: Protecting Your Brain in the Digital Age.This episode is proudly sponsored by:BetterHelp—Offers convenient and affordable professional therapy made simple. Listeners get 10% off their 1st month at BetterHelp.com/HarvestingHappiness Like what you're hearing?WANT MORE SOUND IDEAS FOR DEEPER THINKING? Check out More Mental Fitness by Harvesting Happiness bonus content available exclusively on Substack and Medium.

We unpack how AI is reshaping hiring decisions, shifting job roles, and creating new expectations for professionals — from engineers to marketers. They explore the rise of AI-assisted teams, the growing compensation bubble, why continuous learning is now table stakes, and how some service providers are quietly riding the AI wave.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows."Register for upcoming webinars here!

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In this episode, Chris sits down with Igor Nikitin, CEO and co-founder of Nice Technologies, to explore how AI and modern engineering practices are transforming the actuarial field and setting the stage for the future of actuarial modeling. We discuss the introduction of programming into insurance pricing workflows, and how their Python-based calc engine, AI copilots, and DevOps-inspired workflows are enabling actuaries to collaborate more effectively across teams while accelerating innovation. Featuring:Igor Nikitin – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:Nice TechnologiesSponsors: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/practicalai

In this episode of Practical AI, Chris and Daniel explore the fascinating world of agentic AI for drone and robotic swarms, which is Chris's passion and professional focus. They unpack how autonomous vehicles (UxV), drones (UaV), and other autonomous multi-agent systems can collaborate without centralized control while exhibiting complex emergent behavior with agency and self-governance to accomplish a mission or shared goals. Chris and Dan delve into the role of AI real-time inference and edge computing to enable complex agentic multi-model autonomy, especially in challenging environments like disaster zones and remote industrial operations.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:ROS - Robotic Operating SystemGazeboHugging Face Agents CourseSwarm Robotics | WikipediaChris'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 BensonSponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.

Wired 04.12, December 1996: https://archive.org/details/wired-magazine-04.12-1996-decemberShow notes with page numbers for everything we discuss: https://tinyurl.com/techpod-295-wired-dec-96 Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

In this episode of the Crazy Wisdom Podcast, I, Stewart Alsop, sit down with returning guest Brian Ahuja to explore a thought-provoking idea he's been stewing on—could we one day build a robot capable of true partner dancing? From the biomechanics of salsa to the possibilities of AI embodiment, we unpack what it would take to engineer fluid, responsive movement and how that intersects with everything from artificial muscles to the intimacy of tactile feedback. We also touch on Brian's long-term vision for a potential lab or foundation to tackle this challenge. You can follow Brian and future developments on Twitter @brianahuja.Check out this GPT we trained on the conversationTimestamps00:00 – Brian Ahuja returns to discuss AI embodiment, sparked by his experience in ballroom dance and curiosity about translating physical intelligence into robotics.05:00 – They explore robotics in partner dancing, touching on the difference between choreographed motion and improvisational, responsive movement.10:00 – Brian breaks down human biomechanics, emphasizing that hip motion in dances like salsa originates from knees and feet—not the hips directly.15:00 – The conversation shifts to balance, proprioception, and ocular reflexes, linking them to movement stability in dance.20:00 – They compare robot vs. human movement, noting robots' jerky motions and the absence of muscle-based initiation.25:00 – The need for haptic feedback is discussed, with Brian detailing how partner dancing depends on tactile signals and real-time response.30:00 – They touch on robotic form factors, questioning whether humanoid robots are the best approach and pondering the design of artificial muscles.35:00 – Brian proposes the idea of the Ahuja Test, gauging if a robot can move so fluidly it's indistinguishable from a human, using dance as the standard.Key InsightsPartner Dancing as a Frontier for Robotics: Brian Ahuja proposes that partner dancing could be a benchmark for robotic embodiment, where success would indicate a robot's ability to replicate fluid, responsive human movement. This task is far more complex than solo choreography—it requires real-time tactile feedback, improvisation, and nuanced physical communication.Movement Origin in Humans vs. Robots: A critical difference lies in how movement is generated. Human motion begins with muscle contraction, not at the joints. Robots, however, typically initiate movement at joint points, missing the layered interplay of muscles, tendons, and fascia that create smooth, lifelike motion.Haptic Feedback and Improvisation: Real partner dancing involves subtle cues, like pressure through fingertips, to signal direction and timing. For a robot to follow or lead a dance, it would need a highly sensitive haptic feedback system capable of interpreting and responding to these nonverbal signals in real time.The Limits of Current Robotics: Even with advanced robots like the Tesla bot, current movement still appears jerky and lacks the fluidity needed for partner dancing. The mechanical design—especially the lack of artificial musculature—may impose fundamental limits on how closely robots can mimic human motion.Applications Beyond Dance: The implications of this inquiry stretch beyond dance into fields like physical therapy, elder care, and domestic robotics. A robot that could move like a human could handle tasks requiring adaptability, precision, and physical sensitivity.Vision and Systems Thinking: Brian frames the challenge as a systems problem that might start with a lab or foundation. He emphasizes not needing to do everything alone, recognizing the value of building knowledge iteratively through conversations, research, and community.The Ahuja Test: Inspired by the Turing Test, Brian coins the idea of the “Ahuja Test”—a way to measure if a robot can move indistinguishably from a human. He suggests partner dancing could serve as the ultimate proving ground for such a test, given its demand for embodied intelligence and nuanced coordination.

Ofir Bibi grew up in Jerusalem, and is where he is today because of his love for photography. He has always been a tinkerer, taking apart of radios and such, and was drawn to the early days of training neural networks and computational photography. He spent a number of years in academia, but eventually was drawn outside of that world. Outside of tech, he is married with 3 boys who play sports. His family is surrounded by nature, so they enjoy biking and walking as much as they can.In 2012, a company was formed around bridging the gap between imagination and creation, through video, apps, and studio grade tools. Ofir recently celebrated 10 years with the company, and came in with the title "Neural Networks" guy.This is Ofir's creation story of Lightricks.SponsorsPaddle.comSema SoftwarePropelAuthPostmanMeilisearchLinkshttps://www.lightricks.com/https://www.linkedin.com/in/ofirbb/Our Sponsors:* Check out Kinsta: https://kinsta.com* Check out Vanta: https://vanta.com/CODESTORYSupport this podcast at — https://redcircle.com/code-story/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy