
Hosted by The Neuron · EN

How do you prove there’s a real human on the other side of the screen when AI can generate faces, IDs, accounts, agents, and entire swarms of bots?Tiago Sada, Chief Product Officer at Tools for Humanity, joins The Neuron to explain why proof of human may become one of the internet’s most important trust layers. Tools for Humanity is building the technology behind World and World ID, a system designed to verify that someone is a real, unique person without requiring them to reveal their identity across the web.Tiago breaks down why CAPTCHAs, phone numbers, KYC, and AI-detection systems are starting to fail; how World ID uses in-person verification, cryptography, and zero-knowledge proofs; and why the future internet may need to distinguish between humans, bots, and agents acting on behalf of humans.We also discuss concert ticket scalping, Tinder verification, Zoom deepfake protection, enterprise fraud, gaming bots, and why AI agents may need a kind of digital “power of attorney.”Subscribe to The Neuron for clear, practical conversations about AI and the future of technology: https://www.theneuron.ai/This episode is sponsored by Guru. https://www.getguru.com/?utm_source=theneuron&utm_medium=podcast&utm_campaign=silver-bundle-june2026

AI agents and automation sound complex, but they’re really about one simple idea: helping you spend less time on repetitive work and more time on the things that need your judgment.In this beginner-friendly Neuron Live, we’ll break down what AI agents are, how automation actually works, and how to start using both without getting overwhelmed.You’ll learn:🤖 How AI agents are different from regular chatbots⚙️ What actually happens inside an automation workflow🧰 Where tools like ChatGPT, Claude, Make, ClickUp, and other AI assistants fit in💼 Practical ways to use AI at work and in everyday life🔁 How to spot tasks that are worth automating⚠️ Common mistakes beginners make with AI workflows✅ How to decide what should stay human and what AI can help withNo coding experience required. No jargon.Just a clear, practical conversation about how to make AI more useful, more responsible, and less intimidating.Join us live, bring your questions, and leave with a better understanding of how to make AI do more than just answer prompts.Subscribe to our newsletter: https://www.theneuron.ai/

What if the next big AI breakthrough is not a bigger model, but a completely different kind of computer?Jeff Shainline, co-founder and CEO of Great Sky, joins The Neuron to explain how his team is building brain-inspired AI hardware using superconductors, photonics, and analog computation. Great Sky’s architecture, called Superconducting Optoelectronic Networks, or SOENs, is designed to move beyond the traditional GPU roadmap by co-locating memory and processing, communicating with light, and mimicking some of the high-connectivity dynamics found in biological brains.In this conversation, Jeff breaks down why today’s chips can struggle with fast, multimodal inference; why transformers may be powerful but inefficient for some future workloads; how Great Sky’s system differs from quantum computing; and why early applications could include fusion reactors, particle physics, video understanding, content moderation, and eventually new model architectures that do not map neatly onto today’s hardware.Subscribe to The Neuron for grounded, practical conversations about where AI is going next—and what actually has to work before the hype becomes real.

Voice agents are moving from “cool demo” to real product infrastructure.In this livestream, we’re joined by Ben Cherry of LiveKit to break down what it actually takes to build real-time AI agents that can listen, respond, interrupt, call tools, and work in production.LiveKit is an open source framework and developer platform for building voice, video, and physical AI agents in production.We’ll talk through the stack behind real-time AI experiences, then build and test a live demo together on The Neuron.In this live demo, we’ll cover:🎙️ How LiveKit helps developers build voice, video, and physical AI agents⚡ What makes real-time agents different from normal chatbots🧠 How voice agents handle latency, interruptions, speech, and tool calls🛠️ Why production-ready AI agents are much harder than a weekend demo🚀 What builders should know before shipping voice AI to real usersAnd yes, we’re doing a live demo, which means there is at least a small chance the agent talks back at exactly the wrong time. Perfect television.Guest: Ben Cherry, LiveKitLiveKit: https://livekit.com/Ben on LinkedIn: https://www.linkedin.com/in/bcherry-product-engineerBen on GitHub: https://github.com/bcherrySubscribe to The Neuron for clear, useful AI news, demos, and explainers for people trying to understand where this tech is actually going.https://www.theneuron.ai/

What happens when AI stops simply giving answers and starts producing proofs a computer can verify?In this episode of The Neuron, Corey Noles and Grant Harvey talk with Tudor Achim, Co-Founder and CEO of Harmonic, the company behind Aristotle — a formal reasoning system built to generate machine-checkable mathematical proofs. Tudor explains why math may be the clearest test case for moving AI from “trust me” to “check me,” and why formal verification could matter far beyond Olympiad benchmarks.They discuss what “mathematical superintelligence” actually means, why Tudor thinks solving a Millennium Prize problem would be a meaningful threshold, and how Lean-based proofs could change the way mathematicians collaborate. They also explore Aristotle’s real-world use cases, from open math problems to verified software, chip design, scientific computing, and the future of AI-assisted discovery.Plus: why Tudor thinks formal math has reached a “zero to one” moment, why specs may be the bottleneck in verified software, and why humans still need to direct the questions AI systems try to solve.Subscribe to The Neuron and sign up for The Neuron Daily at theneuron.ai.

May is Mental Health Awareness Month, and as AI becomes more embedded in our daily lives, one of the biggest questions we face is whether these systems can responsibly support emotional and psychological well-being.AI chatbots are increasingly being used for emotional support, but recent lawsuits faced by OpenAI and earlier ones targeting character.ai and Google's AI Overviews, as well as clinical reports, and internal research have raised valid concerns about their impact on vulnerable users.What does it take to build an AI system specifically designed for mental health from the ground up? Is that even possible?In this LIVE episode of The Neuron Podcast, Corey Noles and Grant Harvey speak with Daniel Reid Cahn, co-founder and CEO of Slingshot AI, about Ash, an AI application purpose-built for therapeutic support. Slingshot has raised $93M from a16z, Radical Ventures, and others to develop a foundation model for psychology trained on structured therapeutic conversations across modalities such as CBT, DBT, and psychodynamic therapy.We discuss the limitations of general-purpose chatbots in mental health contexts, recent controversies surrounding AI and psychiatric risk, and what differentiates a system designed to provide structured therapeutic engagement compared to one being used in a way it was never intended to be. The conversation also explores a broader question: Can AI meaningfully expand access to high-quality mental health care, and where should clear boundaries remain? Or should we keep our counseling where we always have, on a couch with a box of Kleenex and a hug nearby?🔗 Try Ash:https://www.talktoash.com/📌 About The Neuron PodcastThe Neuron breaks down the biggest stories in AI for 580,000+ daily readers. Our podcast goes deeper with the leaders, founders, and researchers shaping the future of AI. New episodes every week.Subscribe to The Neuron newsletter — theneuron.ai

Genspark went from AI search startup to autonomous AI agent platform, hitting $250M ARR in 12 months with no paid ads until they bought a Super Bowl spot. Co-founder and COO Wen Sang joins Corey and Grant to explain what "AI employee" actually means, demos Genspark Claw live (including buying us coffee mid-interview), and lays out his big thesis: legacy software is becoming infrastructure while AI agents become the new interface between humans and work. We get hands-on with Workspace 4.0, Claw, and a custom agent built live for the show.• Genspark Workspace 4.0 announcement: https://www.genspark.ai/blog/genspark-ai-workspace-4• Genspark sb-git: https://genspark.ai/sb-git/intro• OpenAI's customer story on Genspark: https://openai.com/index/genspark/• Forbes AI 50 (2026): https://www.forbes.com/lists/ai50/• Marc Benioff on Salesforce Headless 360 (referenced by Wen): https://x.com/Benioff • Andrej Karpathy's "wiki for agents" idea (referenced as inspiration for sb-git): https://x.com/karpathy• Wen on the DealMaker Show: https://alejandrocremades.com/wen-sang/Try Genspark for free: https://genspark.aiSubscribe to The Neuron newsletter: https://theneuron.ai

New to AI and not sure where to start?Join us live Thursday for The AI Starter Kit: What to Try...and What to Ignore.This beginner-friendly session will help you cut through the noise and focus on the AI tools, habits, and prompts that actually matter. By the end, you’ll know what to try first, what not to worry about yet, and how to ask better questions when you get stuck.In this session, we’ll cover:🚀 The best first steps for AI beginners🛠️ What tools and features are worth trying now🙅 What you can safely ignore for the moment💡 Simple ways to get better answers from AI🔍 How to troubleshoot when AI gives you something unhelpfulWhether you’re brand new to AI or still figuring out how to use it well, this live session will give you a practical place to start.

Can AI move from predicting proteins to actually designing new drugs? Isomorphic Labs is trying to answer one of the biggest questions in science.In this episode of The Neuron, Corey Noles and Grant Harvey talk with Rebecca Paul, Head of Medicinal Drug Design at Isomorphic Labs, and Michael Schaarschmidt, Foundational AI Research Lead.They explain why drug discovery is so slow, expensive, and failure-prone—and why AI drug design is much more complicated than “generate a molecule and ship it.” The conversation covers AlphaFold, structure prediction, molecule generation, binding models, clinical failure rates, human trust in AI systems, and the long-term hope of designing drugs for targets once considered “undruggable.”In this episode:Why drug discovery can take more than a decadeWhat people misunderstand about “AI-designed drugs”How medicinal chemists actually use AI modelsWhy biology is harder than text, images, or codeWhat it would take to make drug discovery faster and cheaperThe dream of designing a drug candidate in one iterationWhy “undruggable” proteins may not stay undruggable foreverAdditional resources:Technical report blog Best resource for learning about the capabilities that we are buildingIsomorphic Labs websiteBest destination for learning more about Iso and joining our team in London, Lausanne or Cambridge, MASubscribe for more grounded conversations on how AI is changing science, work, and the world.For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

Join us Thursday as we break down OpenAI’s new Workspace Agents and what they mean for the future of work.We’ll cover:⚙️ What workspace agents are🤖 How they differ from regular chatbots🏢 Where they fit into real team workflows🚀 How to start working with them effectively🔄 What agentic AI means for workplace automation📈 Why teams are shifting from one-off prompts to repeatable AI-powered processesWhether you’re experimenting with ChatGPT at work, leading AI adoption, or trying to understand where OpenAI is taking agents next, this session will help you see what’s possible and what to watch for.Tune in for a practical, hands-on deep dive into the future of AI at work.Sign up for The Neuron newsletter: https://www.theneuron.ai/