The Neuron: AI Explained

BONUS: A Total Beginner’s Guide to AI Agents & Automation

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 with No 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 Comes After GPUs? Great Sky’s Bet on Brain-Like 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.

BONUS: Building Real-Time AI Voice Agents with LiveKit's Ben Cherry

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 users And 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, LiveKit LiveKit: https://livekit.com/ Ben on LinkedIn: https://www.linkedin.com/in/bcherry-product-engineer Ben on GitHub: https://github.com/bcherry Subscribe 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/

The AI Trying to Solve Math’s Biggest Mystery w/ Tudor Achim of Harmonic

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.

BONUS: Can AI Actually Be Your Therapist? We Ask the CEO Building One

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 Podcast The 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