Tibo 在 2026年9月9日的推文

Happy to be building here with you all. Lots to explore

1,357 回复 · 95 转推 · 7,188 赞

回复 @TheHolyCoder

@TheHolyCoder @GergelyOrosz What’s in the box doesn’t matter, but what the box invariants are does (in/out contract, data access, security guarantees, …)

16 回复 · 1 转推 · 70 赞

There was a bit of a kerfuffle this morning with some banked resets not fully applying when used in ChatGPT Work and Codex. Everyone who used one in the affected time window is getting another one and an email to apologize.

2,210 回复 · 251 转推 · 10,235 赞

Worth clarifying that this is flatly false and the two options are just two independent ways to opt-out. We respect our users' choice whether to use their data to “improve our models for everyone” regardless of where they express that choice. Users can opt out in the in-app settings or indeed also in our privacy portal. They do not need to opt out in both places, and we will make this clearer in our Help Center. https://t.co/sv4uFuHC3W

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回复 @theo

@theo Good luck Theo 🫡

77 回复 · 1 转推 · 498 赞

回复 @MatthewBerman

@MatthewBerman @sama Was I just the stepping stone

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Demand for Astra is really unprecedented. We're pulling all the levers possible to sustain the demand, but I've not seen anything like it until now and we went through very steep growth before. Priority will always be to keep excellent service for existing users, but we might have to pause new Pro subscriptions for a bit if this continues.

3,319 回复 · 1,107 转推 · 21,947 赞

回复 @DennisonBertram

@DennisonBertram @OpenAI Astra on `ultra` and /fast?

344 回复 · 6 转推 · 1,109 赞

See you at the Astra party. Excited to meet some of you https://t.co/WOICELwSrQ

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回复 @thsottiaux

I am pleased to see that Ant’s new Claude Code has a version of background computer use on par with the version from Codex from last May this year. Nice work! Shipping great features first turns out to be a great way to encourage other labs to ship too. We will continue to do this until other labs pay more attention to shipping. This is good for everyone and there is a lot of room left to go! We solved computer use in practice for GPT models about four months ago. But computer use is a significantly awesome thing no matter what model you use, and it is important that the industry similarly spends more effort to train their models to be great at computer use, among other elements of model capabilities. As models become more capable and central to businesses and economies, the value of computer use only increases. We should be taking it seriously, and doing the right thing for our customers and the world.

413 回复 · 179 转推 · 6,138 赞

I for one am glad prompt injection is getting solved across the industry and that Astra is not only our most capable, but also our most aligned model to date. But also ... https://t.co/w1gWiDKkOC

282 回复 · 92 转推 · 4,083 赞

Look! A fish! https://t.co/ad1hYM6s7s

354 回复 · 72 转推 · 2,987 赞