Really feels like AGIPO is here.
GPT-6 Astra
331–340 of 1001 posts
Re: GPT-6 Astra
#332I dropped my claude subscription a few months ago, though I kept some credits to do this and that with claude, thinking that claude might do better for some tasks. A few days ago they were all expired. It feels like it’s time to let claude go.
Re: GPT-6 Astra
#333I 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…
> If this is truly AGI (subject to one's definition of AGI still), then this is a very boring release of an AGI model. Hot take: These models are never going to be 'AGI'. We're just going from a GPT4 ball that's 90% round to a GPT5 that's 99% round to a GPT6 that's 99.9% etc etc etc I think that the harnesses and context management is really where the rubber meets the road, and the real gains are happening there.
We call that a sigmoid.
Re: GPT-6 Astra
#334I 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…
> If this is truly AGI (subject to one's definition of AGI still), then this is a very boring release of an AGI model. Hot take: These models are never going to be 'AGI'. We're just going from a GPT4 ball that's 90% round to a GPT5 that's 99% round to a GPT6 that's 99.9% etc etc etc I think that the harnesses and context management is really where the rubber meets the road, and the real gains are happening there.
I don't think so.
One could use gpt-4 or gpt-5 with today's harnesses and we'd see how well that goes.
Re: GPT-6 Astra
#335I 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…
It's like my RPG character putting every points to one single trait. I'll one shot everything alive but will instantly die if accidentally drink water with 6.9 pH.
Re: GPT-6 Astra
#336The FrontierCode 1.1 Extended benchmark is the only benchmark that aligns with my actual LLM experiences and Astra isn't significantly better or cheaper. All this celebration, and yet it's only on-par with an already existing model? I don't get it.
If your benchmark shows Opus 5 winning, I really question the validity of it.
Re: GPT-6 Astra
#337ARC AGI-3 saturated by Astra! https://arcprize.org/leaderboard
I think it could indicate that "semi-private" dataset likely leaked to their training data.
A dataset being as popular as their's is will contaminate the data just by people discussing it and creating their own public test sets of similar problems.
Still, probably not that much compared to employees targeting it.
Re: GPT-6 Astra
#338Is 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.
Re: GPT-6 Astra
#339The 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…
>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"
You're treating an off-hand comment by an ARC 3 researcher as some sort of a precise AI capability acceleration benchmark. Can we leave casual anecdotes (even from researchers) out of the discussions please?
Re: GPT-6 Astra
#340Can't wait for the new qwen/deepseek/kimi releases 2 weeks from now.
imagine pressure working at these labs