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Notes -
Yeah about that...
On the other hand, we have both Dario Amodei from Anthropic and Altman from OAI extolling the virtues of test-time compute in the vein of o1 (as the article acknowledges).
Personally, while I find the recent relative stagnation in LLMs to be annoying, it's only been what, two years since GPT-4? There are open source models that beat the OG GPT-4 while being much smaller (Llama 405B versus likely a trillion for 4), and models like Sonnet 3.5 are a small but appreciable improvement. I'm not going to call scaling out until we've spent either another year or a hundred billion USD on it, and we'll have to see how test time compute pans out.
Besides, even Ilya says they're working on their own secret sauce solution. We'll see when we see, it's far far too early to call AGI out of the cards.
Sure, I agree with all of that. It would be silly for skeptics of LLMs to “declare victory” now. I say give it another 5 years at least. The main reason I brought it up is because Ilya’s the one who’s saying it, which lends quite a bit more authority to the claim.
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He's saying that we'll have to scale up something else - inference time is the most obvious choice. Synthetic data is also widely used. Ilya wouldn't be founding his own 'making superintelligence' company if he thought it wasn't possible.
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