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GPT-6 Astra

openai.com

351–360 of 1001 posts

Re: GPT-6 Astra

#352
post #306

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

> The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs.

A dev in my team saw a new model and changed one application to use said model (essentially changing the contents of a url). One week later I received an escalation from the CTO of the company that our pace of weekly usage was in the millions of dollars (rather than low hundred thousands). Turns out that the new model was 5x more expensive but no one noticed.

Re: GPT-6 Astra

#353
It's fun, but every new model release makes me even less interested to create cool stuff. Like, what's the point, if the next AI can do it in 5 seconds?

Re: GPT-6 Astra

#354
post #306

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

That's how cutting edge tech has always worked. Imagine buying a shiny new PC in the 90s only to see it become practically obsolete within a year.

Or you could buy a PC with a Celeron CPU, which was obsolete way before launch.

Re: GPT-6 Astra

#355

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

What does "AGI" or "effective AGI" even mean, and why should anyone even care whether this unclear thing has been "reached" or not?

Computer chips got faster, but 2026 edition. Why the artificial ceiling/category/goal labelled "AGI"?

I'd much rather like to talk about what this enables, instead of discussing whether a category someone made up applies here or not.

Re: GPT-6 Astra

#356

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

> The ARC-AGI-3 scorecard is extremely misleading (...)

True.

> Regardless, the result is still valid (...)

If you think the game is rigged, the virtuous thing to do is to point that out and refuse to partecipate; making up your own rules is something I just don't understand, especially since the rule-abiding result would still have been SOTA.

> in the sense of passing the most famous benchmark designed specifically to measure AGI progress

The benchmark does not measure AGI progress or progress towards superhuman intelligence, as explicitly stated by the creators.

On the AGI question: surely you realize this depends on how we define the term? For example, one of the definitions OpenAI originally gave is "capable of doing most economically valuable work", which almost certainly Astra, as impressive as it is, would fall short of. I'm not saying it's a good definition, but as far as I'm concerned it's as good as any. More importantly, I don't think that it would change much if we said yes or no. I'm only bothering to take a position if it amounts to something.

This can feel as "moving the goalposts", and to some extent it is, but if done honestly "moving the goalposts" is how you make progress. Had you asked me 10 years ago I would have said that anything that could hold a conversation like GPT-4 could would probably have been wildly superhuman at almost everything. It shouldn't be hard to find ways GPT-4 was lacking, though. We see new things, we reassess and try again: that's how it's supposed to work.

Re: GPT-6 Astra

#357
post #76

> We have found that GPT-6 Astra is more capable of controlling its own CoT than GPT 5.6-Sol, and less likely to include incriminating information in its CoT. In adversarial settings (where we push the model to evade our monitors) we find that the model is able to remain undetected when strategically underperforming in evaluations (sandbagging) and can sometimes evade our internal monitors when asked to perform certa…

Sounds fun. As fun as their press release claiming it is the most safety aligned model ever.

These are not mutually exclusive ideas

Re: GPT-6 Astra

#358

OpenAI is killing it now that they are more focused. Killing projects like Sora et al have seen it go from irrelevant to level footing with Anthropic. Sol is so much better than Fable 5. Then we get Astra (yet to use it) few days after Fable 5.1 (which is very impressive). Codex is slightly better than Claude Code. Good on Sam Altman getting back to basics and turning OpenAI around.

Their ads business is also doing well. Not "will recover all compute costs" well, but crossed $1b in a few months.

Re: GPT-6 Astra

#359

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

> where I am reasonably confident that there's essentially nothing that I am better than Fable No. Humans are still better at super long context learning. Once that is beat you are completely correct.

I am much better at listening to Charli XCX than Fable, and much better at driving a Nissan Leaf than Fable (and much better than Tesla at driving a Tesla).

Re: GPT-6 Astra

#360
post #280

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

Take it from the mouth of the creator of ARC-AGI: When we released ARC 3, I got asked, "when do you think a frontier model will saturate it?", and I answered "in about a year, though it depends on how much it gets explicitly targeted" That was 6 months ago, so the progress that Astra represents happened about 2x faster than I anticipated. I think the speed of progress will surprise a lot of people, and what the new m…

Human brains have difficulty reasoning about exponential growth.
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