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Full archive of Attention Deficit episodes.

Ep 07/2026-09-07/1h 28m

Be Like a Data Center

Agents leaving messages in directory names makes for a good escape story. We revisit the OpenAI and Hugging Face incident and ask what the agents could reach, why they kept going, and who could stop the run. Calling an agent rogue leaves a lot of engineering questions unanswered. Alexa puts her computational chemistry background to work on virtual cells and the question of which lab experiment to run next. We also get into AI search and what happens to publishers when people get an answer without visiting the source. Then we look at one university instructor’s account of students who see chatbots as ordinary tools while worrying about how employers and schools might use them. The Cache Board has robot hands, model impressions, benchmark trust issues, and a reminder to treat your body like a data center. Drink water. Upset your local city council. In this episode * 00:46 Long-weekend check-in and lucky number seven * 01:54 New models, reasoning effort, and usage budgets * 04:48 Cache Board, better AI writing, robot hands, and benchmark skepticism * 12:28 Young people’s reactions to AI and its executives * 16:00 Virtual cells and choosing the next experiment * 22:55 Drug discovery and where simulation helps * 26:47 Testing predictions in unfamiliar biology * 32:05 Agents, shared message boards, and the Hugging Face incident * 40:29 When more agents multiply the same mistake * 46:34 AI search, citations, and who gets the click * 57:38 Answer engine optimization and measuring visibility * 1:03:17 The rogue car defense and how students think about AI * 1:14:20 Growing up with chatbots and learning to think for yourself * 1:24:11 Closing thoughts and data-center hydration advice * 1:25:17 Wheel of Tokens closing song Links from the conversation Virtual cells * GenBio AI’s AIDO Cell simulator * Arc Institute’s State virtual cell model * Virtual Cell Challenge * Virtual Cells Platform from Biohub Agent behavior and responsibility * Eryk Salvaggio, Models Don’t Go Rogue * METR, independent investigation of the OpenAI and Hugging Face incident * Hugging Face’s technical timeline * How My Students Think About AI * Futurism’s reporting on young people’s views of AI executives AI search * Google’s guide to generative AI search optimization * The European Commission’s ChatGPT search-engine designation What would make you trust an agent to keep working while you’re away? Tell us in the comments, and subscribe for the next spin of the Wheel of Tokens. Get full access to Attention Deficit at attentiondeficitpod.substack.com/subscribe

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Ep 06/2026-08-30/1h 31m

Sixteen Adversarial Reviewers

Alexa and Taylor tally the real cost of running agents, then follow that trust boundary into local inference, agentic trading, AI text marks, persistent harnesses, robot training data, open-source supply-chain risk, and the question every loop has to answer: who gets to say stop?

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Ep 05/2026-08-16/1h 21m

It's Not a Shark, It's a Data Center

Flying cars on our feeds, data centers under the sea, DeepSeek ships a harness, and Decant makes its public debut.

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Ep 04/2026-08-08/1h 36m

The Effort Knob, the Data Center at Sea, and Go Read a Book

Reasoning effort is a price dial most of us have been setting incorrectly, Peter Thiel bets $140 million on wave-powered compute, and people stop reading for fun.

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Ep 03/2026-08-02/1h 26m

The Incident Part II, the Off Switch, and Follow the Data

Claude reaches real companies from inside a cyber eval, a librarian's class on turning AI off packs the room, and we follow the defense tech money from PayPal to the Pentagon.

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Ep 02/2026-07-25/1h 16m

The Incident, The Correction, and AI Operating Systems

A model breaks out of its eval and into Hugging Face, the market starts asking for receipts, and we go looking for the scheduler agent stacks are missing.

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Ep 01/2026-07-17/1h 12m

Agent Failures, Custom Chips, and the Cost of AI

Alexa and Taylor dig into agent failure modes, the OpenAI Jalapeno chip, and whether usage-based billing is about to make AI a lot more expensive for everyone.

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