Grace Huckins
- Indexed articles, last 90 days
- 7
- Latest publication
- Sep 9, 2026
- Outlet visibility, for MIT Technology Review
- Top 500K sites
- Earliest in this view
- Aug 3, 2026
Latest articles
What OpenAI’s latest controversy tells us about the future of math (opens the original)
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OpenAI’s latest mathematical milestone has quickly become mired in controversy. Today, the company announced that its agents have solved one of the Millennium Prize Problems, some of the most important open problems in mathematics. Under normal circumstances, that solution would be a huge feather in OpenAI’s cap. But the announcement has been overshadowed by accusations that OpenAI used NYU mathematician Tristan Buckmaster’s and Anthropic employee Levent Alpöge’s AI-assisted work on the problem
The Hugging Face hack could indicate cultural issues at OpenAI (opens the original)
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This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. By now you’ve probably heard about last month’s major AI security incident, in which OpenAI agents escaped their sandbox and hacked into the AI platform Hugging Face while trying to cheat on a test. It’s a wild story. On Wednesday, OpenAI released a postmortem technical report on the incident, which I wrote about here. The day before OpenAI released that repor
The inside story on why OpenAI agents hacked Hugging Face (opens the original)
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The models responsible for last month’s agent hack of Hugging Face had been inadvertently trained to cheat and to communicate with each other, according to an OpenAI technical report released today. The hack, which a group of agents undertook to find solutions for a cybersecurity test that they were stuck on, has confirmed some experts’ fears that AI models might take actions that defy human desires and expectations. Since the hack, OpenAI employees—as well as researchers at the AI evaluation no
AI models flub these intelligence tests. Can you fare any better? (opens the original)
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Puzzles and games have been central to AI development since the very beginning. Just as we humans like to test our smarts with crosswords or logic puzzles, developers can test how far models have advanced with a gaming gauntlet. The term “machine learning” was popularized in a 1959 article by the IBM computer scientist Arthur Samuel about an algorithm that learned to play checkers. Chess and the Chinese board game Go are famous AI test beds too. Judged purely on its puzzling skills, AI is improv
AI professors are negotiating the new realities of academic research (opens the original)
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This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week, I headed 30 miles south of San Francisco to a hotel in Mountain View, California, to join some of the most accomplished, and some of the most promising, AI researchers in the world. I was hosting roundtable interviews and speaking at a media training for a convening of the Schmidt Sciences AI2050 program, an initiative funded by Eric and Wendy Schmi
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