Generative AI 101

Jensen Huang had an X account for years and never used it, then spent his first post on a three-page policy PDF that fifty companies have now signed. Host Emily Laird reads past the principle and into the machinery, including the one paragraph about distillation that a staffer will read aloud in a hearing room two years from now. You will also get the part the letter does not survive: free weights, expensive inference, a minimum production team that runs half a million a year, and an open ecosystem Washington would be protecting that is already substantially Chinese. Bring skepticism for the numbers, because almost none of them have been independently audited.

 

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Anthropic shipped Claude Opus 5 on July 24th at the same price as the model it replaces, and buried the interesting part in a footnote: turn the effort dial to max and the scores go down. Host Emily Laird reads the system card, separates the vendor-run benchmarks from the independently administered ones, and explains why extra test-time compute buys ambition rather than correctness. Also covered: three outages in two days, a cyber classifier that quietly routes part of your traffic to an older model, and why Anthropic's own coding guidance stops one rung short of the top setting. If your team is paying for maximum thinking, you may be paying for scope creep with a token bill attached.

 

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One in three American workers has sat in a meeting with an AI notetaker, and most of them were never asked first. Host Emily Laird traces the path from a leaked Otter transcript that killed a venture deal to a consolidated privacy suit in San Jose, where every named plaintiff was a non-customer who simply showed up to someone else's call. The twist: the awkward bot in your participant list was the warning label, and the fastest-growing corner of this market sells its removal as a feature. Bring three questions and nine seconds of nerve.

 

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AI did not save you time, it moved the bill to someone else's desk. In this episode, host Emily Laird opens the ledger on the rework tax: the workslop arriving in inboxes that looks finished but is not, the 37 percent of "saved" hours burned on corrections and clarifications, and the jagged frontier that makes wrong output read exactly like right output. She walks through the METR trial where experienced developers came out 19 percent slower and still believed they were 20 percent faster. The reality check: the colleague quietly rebuilding your draft at eleven at night is never going to tell you about it.

 

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Moonshot AI just gave away the largest open-weight model ever built, and the chip stocks still bled. Host Emily Laird breaks down Kimi K3: 2.8 trillion parameters, free to download, and completely impossible for you to actually run. The catch isn't the price of the model. It's who owns the machines that serve it.

 

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