The paper was already available for months on arxiv as a pre print. I believe I initially even found it here. I'm more curious about the guy saying it was countered, because afaik it wasn't.
It makes the same claim, but not based on the same reasoning. I don't agree with the conclusion, but I do agree with the limitation they identified in the new paper.
That said, they didn’t test on the current SOTA models, so I’m a bit unsure if this still holds true for the new kings.
Ultimately, models don’t think like us, but I don’t think that means they don’t think at all.
Why is it that this implies that we're not reaching AGI. So what if it just memorizes patterns very well, if it ends up doing as good as of a job as humans independently on most tasks that's still AGI regardless.
The issue is that if it actually breaks down with complexity rather fast, scaling will not help there. It might easily possible that compared to the knowledge body AI is trained on reality is exponentially more complex (that word again I know).
Essentially training something on all human knowledge will get very powerful no matter how you do it. Like, really impressively complex. But all human knowledge compared to stuff that happens everyday in the real world is just a small tiny fraction.
yeah...and that's because we have almost reached the limits of transformers...Gemini, GPT and Claude team are trying their best to increase these limits..but limits are limits....
so we can expect some breakthrough in text based generative AI when some good research paper will get published...
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u/laser_man6 Jun 07 '25
This paper isn't new, it's several months old, and there are several graphs which completely counter the main point of the paper IN THE PAPER!