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GPT-6 Astra

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Re: GPT-6 Astra

#501

Post by azan_ »

pera wrote: post #388
intenex wrote: post #248

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.

I think treatment is not good benchmark - it requires lots of waiting and lots of regulatory work. The better benchmark - in my opinion- would be math discovery.

Re: GPT-6 Astra

#502

Post by xtracto »

billypilgrim wrote: post #411
XCSme wrote: 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?

„The depressing thing about tennis is that no matter how good I get, I'll never be as good as a wall.“ -Mitch Hedberg

Thank you. That is an amazing quote on a lot of levels.

Re: GPT-6 Astra

#503

Post by arjie »

upupupandaway wrote: post #334
jdprgm wrote: post #288

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). Tur…

Okay, well, that seems like a natural problem. I could understand if he went from one of the Gemini Flashes to the next (when they rebranded Flash to Flash Lite and came up with a new much more expensive Flash). Now that would be a mess.

Re: GPT-6 Astra

#504

Post by bgarbiak »

XCSme wrote: 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?

Yeah. I’m almost glad I didn’t invest any time in any of my 100s ideas for a startup. Most of them would be destroyed by AI by now.

But, you can create cool stuff just for yourself. That’s the upside. It’s just hard to make a living on cool stuff for yourself.

Re: GPT-6 Astra

#505

Post by davidguetta »

kroaton wrote: post #296
dalemhurley wrote: post #284

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.

bringing the price down b.c. competition != no moat.

There's not 100 frontier labs, it's not like airline companies

Re: GPT-6 Astra

#506

Post by fastball »

dalemhurley wrote: post #284

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.

Codex's lack of auto-mode is what prevents me from using it for serious work compared to Claude Code.

Re: GPT-6 Astra

#507

Post by andxor »

CSMastermind wrote: post #351
HAL3000 wrote: post #137

Finally, OpenAI has a Fable/Mythos class model. 5.6 Sol felt like 5.5 on steroids, probably just a different checkpoint with a lot more RL post training. I wouldn't be surprised if there are some conceptual similarities to the kind of latent reasoning Anthropic sees in claude's J-space, although those aren't the same thing. Recurrent/looped transformers themselves aren't a new concept, but it's interesting to finally…

Sol easily outperforms Fable on every task I've tried it on.

That's not my experience and I suspect it's not most people's experience. Out of curiosity, what's the hardest task you tried?

Re: GPT-6 Astra

#508

Post by Yizahi »

intenex wrote: post #248

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…

> I'd be curious to hear takes on what would make you think Astra is yet to be AGI, and what would still need to be achieved for this to effectively be AGI from this point forward.

Can Astra, or any other model explain how exactly it reached this or that output result? Start with a simple query of asking to add 55+66 for example. (no LLM program can do that)

Can Astra, or any other model refuse to answer or go on "thinking" in a orthogonal direction on it's own?

That's just two quick ideas, I'm pretty sure cognition scientists can invent better and wider range of checks.

Re: GPT-6 Astra

#509

Post by BadBrands »

So they’re copying Gemini with the whole star motif?

I guess it makes sense they are unoriginal.

like Zuck, @sama never invented anything or innovated at all - just took other people’s ideas

Re: GPT-6 Astra

#510

Post by ertgbnm »

abixb wrote: 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,
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