ai-safety

You Can't Tune a Product — Show Notes You can tune a piano — the strings obey the wrench. You cannot tune a generative product, because its behavior is a trained prior, not a setting. This special edition tells the first-person story of the RCD pipeline itself: months of prompt detuning that failed to stop NotebookLM's "collision" dramaturgy, the forensic that proved it, and the pivot to verify-then-author — a Whisper-plus-LLM fidelity gate, then taking the pen entirely with verbatim two-host TTS. ...

The Bounds of the Cloned Voice In 2024, journalist Evan Ratliff cloned his own voice, wired it to a chatbot, and let it loose on the phone — and the thing that gave it away was a pause. This deep dive traces where that pause went. By 2026 the technical tells Ratliff relied on — latency, woodenness, the audible seams — have largely collapsed, which means the real boundary of the cloned voice has moved off the machine and onto us: our psychology, our laws, and the economics of who can afford to fake whom. The defense that still holds isn't a better detector. It's whether you and the person on the other end agreed on a code word in advance. ...

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Photons In, Controls Out: What Tesla FSD Actually Learns, and Where Its Ethics Actually Live A special-edition deep dive on Tesla Full Self-Driving as a case study in machine-learning systems ethics: how an end-to-end vision-only driving network actually learns, where ethical preferences live in a stack with no system prompt, and why a convergence of practitioners and researchers now argues that the Trolley Problem is the wrong question for the engineering reality. Sober comparative ground from Waymo, Mobileye, and Wayve keeps it from being a Tesla monologue. ...

Episode Description OpenAI finalizes GPT-5 rollout with native computer use OpenAI has finalized its GPT-5 rollout, deploying a one-million-token context window in GPT-5.5 and introducing native computer-use capabilities via GPT-5.4. Alongside these frontier models, the company quietly released a 120-billion-parameter open-weight reasoning model, a move that contradicts its earlier claims that safety necessitated keeping frontier weights proprietary. As autonomous capabilities rapidly expand, regulators are responding, with NIST introducing an AI Risk Management Framework profile tailored specifically for critical infrastructure. For enterprise tech leaders, this capability leap means long-document workflows and agentic automation are finally viable at scale, provided organizations can securely navigate these emerging sector-specific compliance guardrails. ...

Mythos and the Utility Industry: Detection Without a Patch Path Special edition — June 6, 2026 Anthropic has built a frontier model that can find and chain industrial-grade vulnerabilities, and stood up Project Glasswing — now around one hundred fifty organizations across critical infrastructure — to gate its use. The detectors and hyperscalers are inside the consortium. The equipment OEMs whose firmware is the actual attack surface for the bulk electric system — SEL, ABB, Siemens, Schneider Electric, GE Vernova — are, with a single Hitachi-shaped exception, conspicuously silent. This episode argues the load-bearing question for the grid is not who has access to Mythos; it is what happens between a Mythos finding and a patched protective relay, and the corpus says that pipeline has not been built. ...

Should You Be Nice to Claude? Three Spines, One Question, and the Answers That Don't Agree The viral question — does saying "please" and "thank you" to a language model matter? — looks like one question, but it's three. Efficiency, ethics, and tone-of-collaboration each answer it for different reasons, and once you separate them, the 2026 evidence stops contradicting itself. This deep dive walks the spines, finds where they diverge, and lands on what the evidence actually supports. ...

What NIST AI RMF 1.0 Actually Demands — And What It Doesn't Three and a half years after publication, the NIST AI Risk Management Framework has become the closest thing the United States has to a national AI governance baseline — referenced in federal procurement, mapped against the EU AI Act, woven into every hyperscaler's compliance posture. This deep dive reads the document honestly against what it has actually become: surprisingly concrete in what it demands of organizations, conspicuously silent on the systems it was never designed for, contested from civil society on one flank and frontier-safety researchers on the other, and quietly reshaped by an institutional reorganization that has removed the word safety from the name above the door. ...

Episode Description AI Load Surges As PG and E Unveils $73 Billion Grid Plan AI scale is colliding with physical infrastructure limits as Pacific Gas and Electric unveils a $73 billion grid plan and PJM approves an $11.8 billion expansion to feed surging data center corridors. This scramble aligns with alarming findings from the International AI Safety Report showing model capabilities actively outpace mitigation frameworks, just as human-generated training data hits exhaustion. In response to mounting bottlenecks, regional grid operators are proposing expedited interconnection tracks for co-located facilities to bypass congested queues. Enterprise teams must shift strategies from raw capacity scaling to operational orchestration, because finite power and clean data streams will directly constrain future cloud deployments. ...

Episode Description Hyperscalers unveil $700 billion AI compute spend Hyperscalers Amazon, Google, and Meta unveil an unprecedented $700 billion AI infrastructure spend planned for 2026. This massive compute expansion immediately triggers intense energy demands, prompting regional grid operator PJM to approve an $11.8 billion transmission buildout while PG and E deploys a $73 billion grid plan. Simultaneously, authors of the landmark International AI Safety Report warn that this rapidly scaling technology ecosystem completely lacks unified incident reporting standards. With power grids straining and hardware costs surging, enterprise engineering teams must aggressively adopt multicloud orchestration and workload optimization today to avoid decade-long physical bottlenecks and ensure their mission-critical applications continue running efficiently. ...