alt Hacker News> 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.
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>I think that the harnesses and context management is really where the rubber meets the road, and the real gains are happening there.
True. So we did hit a wall with pure scaling alone, though no lab would admit it. It's crazy to see how harness switchout results in such vast delta in benchmark scores.
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.
We call that a sigmoid.
I don't remember where I heard this, but one of my favorite criticisms of the current AI situation is that it's wrong simply because of the size and energy required compared to the human brain. The idea is that there's still some element missing thats fundamental, and that the way we train them now is part of the solution, but not all of it. I think finding the extra missing element is going to take an entirely different approach that will also solve the sizing and resource issue. The kickers is that if they do achieve (and solve) AGI in this way all the giant data centers would be mostly useless.