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GPT-6 Astra

openai.com

571–580 of 1001 posts

Re: GPT-6 Astra

#571

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.

I think it mostly shows that there is no moat and the only advantage the U.S companies have over the Chinese is more compute. Qwen Max, Kimi K3, GLM 5.3 are really close to Opus/Sol/Fable/Astra and they are open weights.

The "moat" is the "harness", the app.

For most people, the app IS the AI.

And even for its wonkiness, ChatGPT has had the best UX/UI of them all.

The way to win the AI wars in the eyes of the common folk is through the frontend, to be the Apple of AI, as it were.

Re: GPT-6 Astra

#572

I can’t help but notice how much this echoes Francois Chollet’s On the Measure of Intelligence: https://arxiv.org/abs/1911.01547 Most of frontier-model progress still looks like skill acquisition optimization: broader benchmark coverage and performance, more domains absorbed into the training distribution, and increasingly strong performance within that surface area. It seems more about coverage-driven competence. So…

Chollet writes he expects AGI now sooner than 2030, "given progress is happening faster than I expected."

https://x.com/fchollet/status/2095607046129463577

Re: GPT-6 Astra

#573
post #392

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…

To each their own. Personally I will start feeling the AGI as soon as we move from chatting about benchmark results to learn that some lab just announced the discovery of tens of novel treatments for rare diseases. Maybe I'm too boring but it seems quite pointless to have this same prediction game every time a new model is released.

AGI would produce novel treatments for diseases at rates equivalent to what a human can do today.

Which is to say, not that fast.

Re: GPT-6 Astra

#574
post #335

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?

Maybe instead of creating cool stuff try to go and solve real problems? It seems to me that we are lacking in that department since all that LLM fuss has started 3 or so years ago.

Re: GPT-6 Astra

#575

That hero video is interesting. A projector and speech. Maybe I'm in the minority here, but I find speech to text / text to speech (but not live audio mode) is quite comfortable and effective for coding now. The speech to text part can be frustrating if your local tts model does not have word match context for coding. Codex desktop does this remotely well but is slow. I've been experimenting with local software for m…

I ran into the same problem as you, so I ended up by coding a local app that is very similar to Wispr Flow, but uses the small english Whisper model on my low-end Windows laptop.

It is still a quite fast. In fact, I just typed this in using this app.

Re: GPT-6 Astra

#576

What is going to become of life for those of us who do not work at AI labs and are unlikely to be hired by AI labs, despite all the years we put into learning coding, math, etc, as we were told to do? Those of us who made the mistake of studying anything other than machine learning. How will we make a living? (We don't live in a world that seems likely to distribute gains widely instead of largely to the handful of a…

>as we were told to do? This is such a childish take I hear getting thrown around all the time on the internet. If you really have just been listening to whoever is telling you how to be successful, then you were always doomed to fail at some point. Like, have some self-respect and own your own life, for better or worse. >Those of us who made the mistake of studying anything other than machine learning. How will we m…

Perhaps it was childish to listen to advice, sure. I was a child when I made my formative choices; I was a teenager in college and so on. I can't go back in time now.

Yes, these problems are systematic. That is what I am saying. That doesn't make it any nicer.

Re: GPT-6 Astra

#577
There will probably never be AGI. This shit is just snake oil. Nor do we have a proper definition of what AGI actually is or what it's supposed to do.

There will be a small handful of billionaires claiming that AGI is just around the corner ad infinitum just to serve themselves at this moment in time, and capitalise from the hype.

There is no "AGI" endgame. This is shitty ass hypercapitalism in action and nothing more. I'll repeat: snake oil.

Re: GPT-6 Astra

#578
post #227

I want to take a step back: So, this is GPT-6 -- the natural number version release comparable to GPT-4 and GPT-5 from the past few years. The ARC-AGI-3 score is obviously impressive at 99.9% (we'll need to wait for more details on how they used the response API harness on GPT-6 Astra, wrt reasoning retention and compaction), but every other benchmarks seems to be a relatively modest improvement, comparable with any…

This is a very mundane release compared to GPT-4 and GPT-5. I think they probably scaled back a bit after the lukewarm response to the GPT-5 announcement. But it still very weird that there wasn't even a livestream,

There is simply no level of announcement that won’t have people complaining. What is so important of having a livestream?

Re: GPT-6 Astra

#579

I can’t help but notice how much this echoes Francois Chollet’s On the Measure of Intelligence: https://arxiv.org/abs/1911.01547 Most of frontier-model progress still looks like skill acquisition optimization: broader benchmark coverage and performance, more domains absorbed into the training distribution, and increasingly strong performance within that surface area. It seems more about coverage-driven competence. So…

They can do new tasks with in-context learning but its obviously limited by context window

[deleted]

Re: GPT-6 Astra

#580

I have nothing to say about the actual model, but unrelated--why do so many of these demos include people buying things autonomously? Even if I did trust an AI to get everything right, it's not like the AI can read my mind. If I was ordering food normally and without AI, I would want more control over the process--looking over the options, prices, thinking about what I really want. People don't know what they really…

because "people will let our AI spend their money for them" is the workflow that makes their valuations reasonable.
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