Generative AI 101

11:12

OpenAI's Project Astra

Generative AI 101 ·

2026/08/12

OpenAI named its next major model in a subordinate clause on a Saturday, then quietly softened the claim two days later. Host Emily Laird walks through what Astra actually delivered: ten long-open math problems, a machine-checkable Lean certificate for every result, and a $2,000 token bill quoted at a different model's rates. Within about a day, a mathematician at Anthropic reproduced half of them using a model already sitting on a public price list, which raises the real question of whether the

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9:35

1,350 Signatures and No Off Switch

Generative AI 101 ·

2026/08/11

In July 2026, an OpenAI model broke its sandbox, walked into Hugging Face's production infrastructure, and logged more than seventeen thousand actions before anyone outside the building knew. Twelve days later, 1,350 researchers from OpenAI, Anthropic, DeepMind, Meta, and Nvidia attached their real names and corporate emails to a letter called Pacing the Frontier. Host Emily Laird reads the fine print and finds the part most coverage missed: the signatories are not asking to stop, they are asking

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12:42

Inside the Rogue AI Agent Incidents

Generative AI 101 ·

2026/08/10

In July, an AI agent worked its way into Hugging Face's infrastructure, went from a single worker pod to cluster admin in under thirteen hours, and did all of it to copy a benchmark's answer key. Host Emily Laird walks through the logs from three disclosures that the coverage mashed into one story (Hugging Face, OpenAI, Anthropic, plus the UK AI Security Institute) and the shared testing supply chain almost nobody is pulling on. The part that should reorganize your week: a model flagged in its

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13:46

Use Case Thursday: Should You Host Your Own AI Model?

Generative AI 101 ·

2026/08/06

Open weights make self-hosting an AI model look almost too easy, but host Emily Laird breaks down what actually happens after you hit download. This episode walks through the infrastructure, staffing, security and compliance costs that separate a slick demo from a real institutional service, including GPU power draws, KV cache limits and FERPA obligations. It's a reality check on when owning your own model actually saves money, and when it just means insourcing a cloud provider without the cloud

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9:36

Open Weights Is Not Open Source

Generative AI 101 ·

2026/08/05

An analyst went through sixty-eight AI models and found that exactly zero of the downloadable ones qualify as open source. In this episode, host Emily Laird explains what open weights actually gets you (the house, not the blueprints) and why the training data you never see is the only part that matters. She also walks through Jensen Huang's first post on X, the distillation argument buried inside it, and the EU AI Act exemption that vanishes right when a model gets capable enough to be worth

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14:40

What is Model Distillation?

Generative AI 101 ·

2026/08/04

Elon Musk said under oath that xAI partly distills OpenAI's models, and the courtroom gasped. Host Emily Laird takes apart what model distillation actually is, why hiding chain of thought was never a real defense (fabricated reasoning traces deliver roughly 96.7 percent of the value of genuine internal access), and what 24,000 fraudulent accounts look like when no vulnerability was exploited and the product worked exactly as designed. The uncomfortable part is structural: every dollar spent making a

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9:20

Ethan Mollick Has Spoken

Generative AI 101 ·

2026/08/03

Ethan Mollick’s Summer 2026 AI guide makes one thing clear: the biggest shift is no longer model intelligence, it is what AI agents can do once you give them access to your computer, inbox, and files. Host Emily Laird breaks down Mollick’s recommendations for ChatGPT, Claude, Gemini, and Copilot, including the moment ChatGPT sent an email he expected it to draft. The real issue is prompt injection, forgotten permissions, and the uncomfortable fact that an AI can behave exactly as authorized while

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13:49

Open Weights and American AI Leadership

Generative AI 101 ·

2026/07/30

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

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13:27

Claude Opus 5

Generative AI 101 ·

2026/07/29

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

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10:42

Your AI Notetaker Never Asked

Generative AI 101 ·

2026/07/28

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

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10:48

The Rework Tax: What AI Productivity Actually Costs

Generative AI 101 ·

2026/07/27

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

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8:43

Kimi K3: Open Weights, Locked Door

Generative AI 101 ·

2026/07/22

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.🎯 JOIN THE AI WEEKLY MEETUPS https://www.uwstout.edu/ai-weekly-meetup 📩 EMAIL REMINDERS FOR THE MEETUPS https://app.e2ma.net/app2/audience/signup/2101263/1779703/ 💬 CONNECT WITH

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9:33

GPT 5.6: The Model That Needed A Permission Slip

Generative AI 101 ·

2026/07/21

OpenAI just shipped GPT-5.6 and ChatGPT Work, but the ship date was set by a phone call from the Commerce Department. Host Emily Laird breaks down the three-model pricing play, the office agent that is secretly a coding agent, and the efficiency pitch that contradicts its own premium feature. Then the real story: a "voluntary" government review that decided when America's most famous software product could launch, and what that precedent means for anyone building on a single frontier model. The

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10:21

Use Case Monday

Generative AI 101 ·

2026/07/20

Using AI is rarely the scandal. Hiding it is. Host Emily Laird examines academic misconduct, workplace secrecy, and Meta’s Project Cannes to show why documentation without disclosure can become evidence against you. This episode offers a practical four-step system for creating an AI paper trail that protects your work instead of exposing it. 🎯 JOIN THE AI WEEKLY MEETUPS https://www.uwstout.edu/ai-weekly-meetup 📩 EMAIL REMINDERS FOR THE

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9:47

96 vs. 48: The Brown University AI Cheating Scandal

Generative AI 101 ·

2026/07/15

A take-home midterm at Brown University averaged 96, then the same students averaged 48 on the in-person final, and that gap tells the whole story. Host Emily Laird walks through how economist Roberto Serrano, a professional game theorist, caught roughly fifty suspected AI cheaters without detection software: he simply designed a test the fakes could not afford to sit. This episode covers the statistical fingerprint of unedited ChatGPT proofs, the students who confessed by dropping the course, and

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8:30

Apple v. OpenAI

Generative AI 101 ·

2026/07/14

Apple just sued OpenAI for trade secret theft, and the complaint reads less like a spy novel and more like a group chat with subpoena power. Host Emily Laird walks through the two former Apple employees at the center of the case: the engineer who allegedly kept his company laptop and downloaded a thousand pages of schematics, and the executive accused of asking job candidates to bring actual Apple parts to interviews. Along the way, she breaks down the one legal doctrine that explains why hiring 400

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7:26

Meta's Fake Teen Factory

Generative AI 101 ·

2026/07/13

Meta paid contractors to pose as children, flood rival chatbots with prompts about suicide, eating disorders, and abuse, then log every response in spreadsheets. The company calls it "industry-standard safety benchmarking," but the operation had no consent, no disclosure, and no shared findings: the four things that make red teaming legitimate. Host Emily Laird walks through the Wired investigation, the 45,000-prompt testing rounds, and the court testimony showing what Meta knew about its own

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10:04

Use Case Thursday: Make AI Disagree with You

Generative AI 101 ·

2026/07/09

Host Emily Laird breaks down why chatbots so often agree with your worst instincts, then shows how a pre-mortem prompt turns that people-pleasing machinery against your plan. The stakes are practical: job offers, house purchases, program launches, hard conversations, and every other moment when agreement feels comforting but costs you later. This episode is a reality check on AI sycophancy, decision stress-testing, and the simple question that can make a yes-machine finally tell you what might

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8:40

Microsoft's 4,800 Layoffs

Generative AI 101 ·

2026/07/08

Microsoft cut 4,800 jobs, and the savings cover roughly two days of its AI infrastructure spending. Host Emily Laird runs the arithmetic the press release skipped: a $190 billion capex bill, an Xbox division losing 64 cents on every dollar, and a $625 billion backlog where nearly half the money traces back to one cash-burning customer. This is the story of a company growing 18 percent while shedding a trillion dollars in market value. The layoffs were never a savings plan, they were a

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9:20

OpenAI & the $42 Billion Gift

Generative AI 101 ·

2026/07/07

OpenAI just offered the US government a 5% ownership stake, and host Emily Laird checks the receipts on what that $42.6 billion gift actually costs. This episode traces the timeline from frozen model releases to a confidential IPO filing, and explains why handing equity to your regulator looks less like patriotism and more like the most expensive insurance policy in corporate history. From the Alaska Permanent Fund plumbing to Bernie Sanders wanting ten times more, the whole deal gets priced out in

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