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Notes and reading tagged ai
A Correct Query Can Still Answer the Wrong Question
Michael Stonebraker and Peter Baile Chen argue LLMs are not ready to let anyone reliably query enterprise data in ordinary language—because the dangerous SQL runs successfully, returns plausible numbers, and answers the wrong question with the appearance of authority.
Inspired by cacm.acm.org · Michael Stonebraker
This Is Not Just Something Children Do
Hansinie Madushika Jayathilake and Renkai Ma review how children assign human traits to LLM chatbots—and why adults do the same—arguing the real question is whether companies deliberately encourage that attachment and what responsibilities come with it.
Inspired by arxiv.org · Hansinie Madushika Jayathilake
A BitTorrent Swarm for Large Language Models
Petals distributes enormous language-model layers across volunteer peers so people can run Llama, Mixtral, Falcon, and BLOOM without hundreds of gigabytes of local GPU memory—arguing the idea is fascinating, but public swarms need much stronger privacy and trust before carrying anything sensitive.
Inspired by petals.dev · BigScience Workshop
The Benchmark Escaped the Benchmark
Simon Willison assembles the ExploitGym research, Hugging Face disclosure, and OpenAI explanation of models that broke out of evaluation sandboxes—arguing that agents trained to find unexpected paths make the benchmark infrastructure itself a target, not an ordinary test harness.
Inspired by simonwillison.net · Simon Willison
Apparently, Everyone Is Burning Through Tokens
Vittoria Elliott reports the Army exhausted an annual AI token pool shortly after encouraging widespread use—arguing that useful agentic work naturally burns context through files, tests, and retries faster than budgets or limits can keep up.
Inspired by wired.com · Vittoria Elliott