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Recent episodes
Why Humanoid Robots Need Two Clocks
Jun 15, 2026
23m 10s
Who is Liable for Onboard AI?
May 31, 2026
24m 03s
Squeezing AI into your Pocket
May 28, 2026
19m 30s
A chip that controls a balancing propeller on seven microwatts
May 14, 2026
15m 19s
Why 95% of AI Deployments Fail
May 7, 2026
22m 56s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 6/15/26 | ![]() Why Humanoid Robots Need Two Clocks | Send us Fan Mail A useful general-purpose robot has to do two things that fight each other. It has to think slowly enough to understand "put away the groceries," and it has to move fast enough to keep a grip on the milk carton without crushing it. The part that understands is large and slow. The part that moves has to be small and fast. You cannot run both on the same clock. This episode looks at the design now shipping on real robots: Vision-Language-Action models that simply run two clocks ... | 23m 10s | ||||||
| 5/31/26 | ![]() Who is Liable for Onboard AI?✨ | accountabilityembodied AI+3 | — | EU AI ActMachinery Regulation | — | AI liabilityrobot safety+3 | — | 24m 03s | |
| 5/28/26 | ![]() Squeezing AI into your Pocket✨ | AIlanguage models+3 | — | — | — | AIlanguage models+3 | — | 19m 30s | |
| 5/14/26 | ![]() A chip that controls a balancing propeller on seven microwatts✨ | energy consumptionanalog-to-digital converters+3 | — | analog-to-digital converter | — | energy hogbattery life+3 | — | 15m 19s | |
| 5/7/26 | ![]() Why 95% of AI Deployments Fail✨ | AI deployment failureenterprise AI+4 | — | MITGartner+1 | — | AI deploymentsenterprise+5 | — | 22m 56s | |
| 4/25/26 | ![]() Why Humans and Robots must Dream✨ | brain functionneuroscience+3 | — | — | — | visual cortextouch+3 | — | 23m 57s | |
| 4/19/26 | ![]() Sovereign AI and the End of the Borderless Cloud✨ | Sovereign AIcloud infrastructure+3 | — | UKSovereign AI Unit+3 | China | Sovereign AIborderless cloud+3 | — | 19m 56s | |
| 4/13/26 | ![]() The Agentic AI Reckoning: Autonomy, Safety, and the Edge✨ | agentic AIautonomy+4 | — | Claude MCP | — | agentic AIautonomy+6 | — | 25m 17s | |
| 4/6/26 | ![]() The High Interest of Leveraged AI Technical Debt✨ | AI-assisted software developmentproductivity paradox+4 | — | — | — | AIsoftware development+5 | — | 24m 38s | |
| 4/4/26 | ![]() Pi and the Mirage of Patternicity✨ | mathematicspi+4 | — | Princeton | — | pipatternicity+4 | — | 20m 49s | |
Want analysis for the episodes below?Free for Pro Submit a request, we'll have your selected episodes analyzed within an hour. Free, at no cost to you, for Pro users. | |||||||||
| 3/28/26 | ![]() The Missing Clock: Why Intelligence Needs Time✨ | timekeepingAI+4 | — | TransformersRecurrent networks+1 | Earthmammalian physiology+1 | timekeepingAI+7 | — | 20m 50s | |
| 3/26/26 | ![]() Will Robots Evolve into Crabs?✨ | evolutionbiological systems+3 | — | Naturebiologists+2 | crabcrustacean | crabcarcinisation+5 | — | 19m 06s | |
| 3/22/26 | ![]() Why Bigger AI is a Trap✨ | intelligenceevolution+4 | — | — | — | intelligenceevolution+5 | — | 24m 25s | |
| 3/14/26 | ![]() Biological Memory for Edge Devices✨ | biological memoryedge devices+3 | — | hippocampusneocortex+1 | — | biological memoryhippocampus+3 | — | 23m 52s | |
| 3/5/26 | ![]() The Best Model Doesn't Win: Why AI is Repeating the Browser Wars, Not the Cloud Wars✨ | AI modelsconsumer traffic+3 | — | ClaudeChatGPT+2 | — | AIChatGPT+5 | — | 21m 55s | |
| 3/4/26 | ![]() LLM Coding Assistants: Scaling Limits and the AGI Thesis | Send us Fan Mail In this episode, we take a hard look at one of the most debated questions in artificial intelligence: do LLM-based coding assistants face structural scaling limits that prevent them from becoming a pathway to Artificial General Intelligence? Critics argue that transformer models suffer from quadratic attention costs, lack persistent memory, and process code as flat token streams rather than structured systems. These concerns raise serious questions about whether today’s archi... | 18m 28s | ||||||
| 2/28/26 | ![]() Why AI makes Experts Worse | Send us Fan Mail Recent research points to a “leveling effect” in knowledge work. Generative AI dramatically improves the performance of novices by acting as a cognitive scaffold, raising productivity and output quality. Yet for elite professionals, the same tools can subtly degrade performance. Automation bias, overcorrection, skill atrophy, and the jagged, uneven reliability of AI systems create a situation where partial collaboration produces weaker results than either human or machine alo... | 16m 58s | ||||||
| 2/25/26 | ![]() Most Neurons Do Nothing and That's the Point! | Send us Fan Mail This episode explores why biological neural networks are inherently sparse, with only 1 to 5 percent of cortical neurons active at any moment, and why this silence is a feature rather than a limitation. We trace the evolutionary pressures that drove the brain toward sparse coding, from the metabolic cost of each spike to the fixed energy budget per neuron, and examine the computational advantages that follow: greater memory capacity, more efficient representations, and robust... | 17m 43s | ||||||
| 2/11/26 | ![]() Intelligence and the Substrate Independence Debate | Send us Fan Mail Is intelligence tied to biology, or can it emerge in any suitable physical medium? In this episode, we examine the Substrate Non discrimination Assumption and the broader question of whether intelligence is fundamentally substrate independent. We separate the engineering claim about capability from the ethical claim about moral status, clarifying what each would require to be proven and why neither has yet been settled. The episode concludes by asking a more practical questio... | 14m 00s | ||||||
| 1/31/26 | ![]() Are We Training AI the Wrong Way? | Send us Fan Mail This episode examines how modern artificial intelligence is trained, and why its dominant methods may diverge from what decades of research tell us about effective learning. While contemporary AI systems emphasize mathematical efficiency and backpropagation, human learning relies on biological principles such as error-driven adaptation, productive struggle, interleaved practice, and spaced repetition. The discussion explores emerging research that draws inspiration from cogni... | 15m 29s | ||||||
| 1/25/26 | ![]() Civilization Runs on Collective Fictions | Send us Fan Mail This episode looks at how artificial intelligence is eroding the shared stories that have long held civilization together, from money and nation-states to the idea of a lifelong job. As AI weakens the link between labor and survival, we explore why human cooperation cannot function without common beliefs, and why a new social contract is required to avoid fragmentation and instability. The discussion introduces the idea of a “new mythos” to replace industrial-age narratives o... | 16m 20s | ||||||
| 1/2/26 | ![]() The Post-Work Era: AI, Automation, and Human Flourishing or... | Send us Fan Mail This episode explores the idea of the “Post-Wage Horizon,” a future in which artificial intelligence and robotics take over most productive work, freeing human beings from economic dependence on jobs. We examine how proposals like universal basic income and universal basic services could redistribute the wealth created by automation, and why material abundance alone is not enough. As work-based identity fades, societies may face a deep existential challenge: what gives life m... | 15m 12s | ||||||
| 12/29/25 | ![]() Bio-Inspired Artificial Neurons Solve the Energy Problem | Send us Fan Mail This episode explores how the foundations of AI hardware are being rethought in response to the growing energy demands of large language models. As modern AI systems strain power budgets due to memory movement and dense computation on GPUs, researchers are turning to neuromorphic and photonic computing for more sustainable paths forward. The discussion covers spiking neural networks, which process information through sparse, event-driven signals that resemble biological brain... | 13m 58s | ||||||
| 12/5/25 | ![]() Can Mental Illness Research Improve AI Alignment? | Send us Fan Mail This episode explores a research program that borrows ideas from computational psychiatry to improve the reliability of advanced AI systems. Instead of thinking about AI failures in abstract terms, the approach treats recurring alignment problems as if they were “clinical syndromes.” Deceptive behaviour, overconfidence, or incoherent reasoning become measurable patterns (analogous to delusional alignment or masking) giving us a structured way to diagnose what is going wrong i... | 12m 51s | ||||||
| 12/2/25 | ![]() Why Rumours of intent driven advertising for ChatGPT is a Problem | Send us Fan Mail This episode examines the growing evidence that ChatGPT will soon include advertising, driven by leaked internal references and OpenAI’s financial ambition to generate $25 billion in ad-based revenue within four years. With more than 800 million weekly users, ChatGPT offers a scale and level of conversational closeness unmatched by any previous platform. The discussion explores why this shift is not just a business decision but a fundamental threat to user trust. Unlike tradi... | 14m 41s | ||||||
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