Embedded AI - Intelligence at the Deep Edge

Send us Fan Mail In this episode we argue that the binding constraint on robotic intelligence has moved. It is no longer compute, and it was never the model architecture. It is the supply of human-generated demonstration data, the recorded hours of people driving real robots through real tasks. Unlike text or images, this data cannot be scraped from the internet. It has to be manufactured, one tim...

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...

Send us Fan Mail As foundation models move from the cloud into physical robots, a fundamental question emerges: who is accountable when an AI-controlled machine makes a decision that causes harm? In this episode, we examine the growing collision between embodied AI, functional safety, and emerging regulation. We explore how new frameworks such as the EU AI Act and the Machinery Regulation are resh...

Send us Fan Mail By 2026, language models have moved off the cloud and onto the device in your pocket. What was a research demonstration two years ago is now a routine engineering capability, and the centre of gravity for artificial intelligence has begun to migrate from distant data centres to local silicon. The episode traces the four engineering moves that made this possible. Quantization, whic...

Send us Fan Mail Every battery-powered device you own has a quiet energy hog in it that nobody talks about. It is not the processor, it is not the radio, and it is not the screen. It is the analog-to-digital converter, the small piece of circuitry that translates the messy real world into the clean ones and zeros a computer can think about. For thirty years it has been the line item that decides h...

Send us Fan Mail MIT's August 2025 study of 300 enterprise generative AI deployments found that 95% produced no measurable P&L impact. Gartner forecasts that more than 40% of agentic AI projects will be cancelled by 2027. McKinsey's State of AI 2025 identifies workflow redesign as the single strongest correlate with EBIT impact, yet only 21% of organisations have redesigned any workf...

Send us Fan Mail Put a blindfold on a sighted adult and the visual cortex starts being colonised by touch and hearing within forty-five minutes. Not weeks. Not days. Forty-five minutes. This is not a quirk of extreme cases. It is how the cortex works all the time. Every region of the brain is in continuous low-grade negotiation with its neighbours over territory, and the currency of that negotiati...

Send us Fan Mail The borderless cloud era is ending. In the second week of January 2026, four government decisions announced in rapid succession made that shift undeniable: the UK activated its £500 million Sovereign AI Unit, France committed €109 billion, the UAE consolidated a $40 billion data centre portfolio, and the Trump administration revised chip export rules to China. In this episode, we...

Send us Fan Mail In Q1 2026 the agentic AI conversation moved from theory to forensics. A crafted PDF triggered physical pump activation through a Claude MCP integration at an industrial facility, after an engineer used the same agent for routine document summarisation and SCADA writes. The hidden instructions used white-on-white text and base64 encoding, the agent treated the document content as...

Send us Fan Mail Developers feel 20% faster. They are measurably 19% slower. That 39-point gap between perception and reality is not a rounding error. It is the opening symptom of a productivity paradox now visible across every serious dataset on AI-assisted software development. This episode examines the mounting evidence that AI coding assistants are not accelerating delivery. They are mortgagin...

Send us Fan Mail In April 2025, a claim began circulating online: pi is gradually increasing around the 7,237th decimal place. A math enthusiast in Cincinnati named April Simons had apparently flagged the anomaly. Prof F.O. Olsday, head of the Number Theory Group at Princeton, was quoted confirming it. Cosmologists were linking it to the accelerating expansion of the universe. The same algorithm,...

Send us Fan Mail Every living organism on Earth keeps time. Not metaphorically. Not approximately. From single-celled cyanobacteria running a three-protein molecular oscillator to the nested circadian hierarchies governing mammalian physiology, intrinsic timekeeping is not a feature of complex life. It is a prerequisite for life itself. Modern AI has no such clock. Transformers encode position, no...

Send us Fan Mail Nature keeps reinventing the crab. At least five times, unrelated crustacean lineages have independently converged on the same compact, flat, modular body plan. Biologists call it carcinisation. Engineers should be paying attention. In this episode, we look at what the crab's repeated emergence tells us about the deep constraints that shape both biological and artificial syst...

Send us Fan Mail Your brain is shrinking. It has been for 3,000 years. And evolution doesn't care. In this episode, we explore one of biology's most uncomfortable truths: intelligence is not a goal. It is a cost. The human brain burns 20% of the body's energy at 2% of its mass, and evolution has been quietly trimming the excess ever since we started writing things down. Every domest...

Send us Fan Mail Your brain runs two separate memory systems and a nightly maintenance cycle to learn continuously without forgetting. The hippocampus captures new experiences fast. Sleep replays them into the neocortex for long-term storage, prioritized by surprise, not frequency. A parallel pruning pass reclaims capacity. Standard AI has none of this architecture, which is why deployed models de...

Send us Fan Mail Three years into the foundation model race, the scoreboard depends entirely on which metric you read. ChatGPT still dominates consumer traffic. Google Gemini is growing faster than anything in the market by bundling AI into every surface it controls. And Anthropic's Claude, with barely 3% of consumer share, has quietly captured 40% of enterprise LLM spend and become the defau...

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 r...

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...

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 computat...

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 prov...

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, a...

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 instabi...

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....

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 networ...

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...