Podcasts about neural networks

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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:

In the third episode of ourspecial podcast series, Chiranjib Sengupta sat down with  a team ofexperts from Siemens – John Nixon, Vice President of Global Strategy for EnergyChemicals and Infrastructure, Mike Houghton, Global Head of Sales, and ShivdeepGaagat, Industry Lead for Energy – to dive deep into a game-changingtechnology: physics-informed neural networks. They discuss how this powerfulnew tool can radically alter the way the industry approaches digitaltransformation. The team breaks down how the technology can improve everythingfrom predictive maintenance to grid reliability, the practical challenges ofintegrating them at scale, and why their optimal adoption can give companies amajor competitive edge.

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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!

Send us a textWhat if I told you the biggest AI breakthroughs in pathology aren't coming from ChatGPT or generative tools—but from the quiet power of predictive analytics and machine learning?In this episode, I explore the non-generative side of artificial intelligence in pathology. These are the tools that detect tumors, segment tissue, classify images, and make predictions—without generating a single word.It's the third chapter in our guided AI series, and this time we focus on the models you're more likely to use in real-world diagnostics. You'll hear about object detection, segmentation, anomaly detection, and how these models are built using supervised and unsupervised learning—plus the pros and cons of different annotation strategies.We'll also cover why no one model fits all, and how combining simple tools like decision trees with more complex neural networks is often the key to building reliable, usable AI in pathology.Whether you're training your first model, selecting an algorithm for rare disease detection, or just want to understand what “unsupervised clustering” means—you'll find something useful 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.

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

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A startup brasileira Avra criou um modelo fundacional próprio de IA para apoiar clientes do mercado financeiro a analisar e conceder crédito para PMEs. A startup já captou US$ 2 milhões em financiamento de venture capital e foi reconhecida, pela AWS, como uma das três empresas mais inovadoras da América Latina na criação de modelos fundacionais. Viviane Meister, CEO, e Bruno Alano, CTO, ambos cofundadores da Avra, explicam o que fazem e provam que o Brasil pode, sim, competir globalmente no terreno da IA.Links do episódio:O site da AvraA página do LinkedIn de Viviane MeisterA página do LinkedIn de Bruno AlanoPessoa inspiradora: Shivani Siroya, fundadora e CEO da Tala, a startup de microcrédito que entrou para a lista de 2025 das 50 Top Fintechs globais da Forbes.O blog/livro "Neural Networks and DeepLearning", criado por Michael NielsenO livro "The Master Switch: The Rise and Fall of Information Empires", de Tim WuO livro "Visionários", de Steven JohnsonO livro "Inteligência artificial a nosso favor: Como manter o controle sobre a tecnologia", de Stuart Russell   A The Shift é uma plataforma de conteúdo que descomplica os contextos da inovação disruptiva e da economia digital.Visite o site www.theshift.info e assine a newsletter

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 the first episode of an "AI in the shadows" theme, Chris and Daniel explore the increasing concerning world of agentic misalignment. Starting out with a reminder about hallucinations and reasoning models, they break down how today's models only mimic reasoning, which can lead to serious ethical considerations. They unpack a fascinating (and slightly terrifying) new study from Anthropic, where agentic AI models were caught simulating blackmail, deception, and even sabotage — all in the name of goal completion and self-preservation. Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Agentic Misalignment: How LLMs could be insider threatsHugging Face Agents CourseRegister for upcoming webinars here!

In this episode, we sit down with Joey Conway to explore NVIDIA's open source AI, from the reasoning-focused Nemotron models built on top of Llama, to the blazing-fast Parakeet speech model. We chat about what makes open foundation models so valuable, how enterprises can think about deploying multi-model strategies, and why reasoning is becoming the key differentiator in real-world AI applications.Featuring:Joey Conway – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:Llama Nemotron UltraNVIDIA Llama Nemotron Ultra Open Model Delivers Groundbreaking Reasoning AccuracyIndependent analysis of AIParakeet ModelParakeet LeaderboardTry the Llama-3.1-Nemotron-Ultra-253B-v1 model here and here

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.

Electrolytes are seemingly suddenly everywhere: on store shelves, in wellness drinks, and all over your social feed. But is adding salt to your water really the answer to fewer migraines? Or is there way more going on beneath the surface? In this episode, we're diving deep into the often-misunderstood world of sodium and potassium, and why their delicate balance can make or break your migraine symptoms. You'll discover what researchers have been uncovering since the 1950s about the way migraine-prone brains handle salt differently, and why so many women unknowingly sabotage their progress by overlooking this one powerful piece of the puzzle. If you've been curious about using electrolytes as a tool to take back control from your migraines, this will help you understand how your body processes them, how imbalance might be fueling your pain, and what you can do to live pain-free.   In this episode, you'll hear: Why migraine sufferers may process sodium differently at the cellular level What current research says about salt, potassium, and brain signaling Why the “add salt to your water” advice isn't one-size-fits-all How electrolyte symmetry is a cornerstone of the FFMM® approach Why standard electrolyte testing often misses the full picture How nutrition, sleep, movement, and mindset all play a role in your internal balance What to know before adjusting sodium or potassium levels on your own   Resources: → Ep. 77: A Closer Look at Electrolyte Tests and What They Really Tell Us Listen to it here: https://sites.libsyn.com/498553/a-closer-look-at-electrolyte-tests-and-what-they-really-tell-us → The Freedom From Migraines Method Membership®  Understanding how sodium and potassium impact your migraines is an empowering step toward finding freedom. When you start working with your body, you open the door to targeted, lasting relief. If you're tired of just getting through the day and ready to feel like yourself again, it's time to take the next step. Inside the Freedom From Migraines Method® Membership, you'll get access to science-backed tools, expert support, and a proven system that's helped thousands of women reduce migraines and reclaim their energy, clarity, and joy. Step into the membership and find relief here: https://debbiewaidl.com/the-freedom-from-migraines-method-membership-4/info   Connect with Debbie:  Instagram: https://urlgeni.us/instagram/migrainefree Women's Migraine Freedom™ Facebook Group: https://urlgeni.us/facebook/Womensmigrainefreedom LinkedIn: https://urlgeni.us/linkedin/debbiewaidl Website: https://debbiewaidl.com/   Disclaimer: The Migraine Freedom Your Way Podcast and information provided by Debbie Waidl and guests in this podcast is presented solely to provide helpful information, education, and entertainment on the subjects discussed. The use of information or resources mentioned on or linked from this podcast is at the user's own risk and discretion. This podcast is not intended to diagnose or treat any medical condition. For diagnosis or treatment of any medical problem, consult your own physician. Debbie Waidl and In The Balance Health Coaching LLC are not responsible for any medical conditions or liable for any damages or negative consequences from any treatment, action, application, or preparation to any person reading or following the information presented on this podcast. References are provided for informational purposes only and do not constitute an endorsement of any websites or other sources.  

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

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