S1 (and R1 tbh) has a bad smell to me or at least points towards an inefficiency. It's incredible that a tiny number of samples and some inserted tokens can have such a huge effect on model behavior. I bet that we'll see a way to have the network learn and "emerge" these capabilities during pre-training. We probably just need to look beyond the GPT objective.
can you please elaborate on the wait tokens? what's that? how do they work? is that also from the R1 paper?
S1: A $6 R1 competitor?
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Re: S1: A $6 R1 competitor?
#72> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster. This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost t…
Define "intellect".
Re: S1: A $6 R1 competitor?
#73Earlier quoted context omitted.
Matt Levine tangentially talked about this during his podcast this past Friday (or was it the one before?). It was a good way to value these companies according to their compute size since those chips are very valuable. At a minimum, the chips are an asset that acts as a collateral.
I hear this a lot, but what the hell. It's still computer chips. They depreciate. Short supply won't last forever. Hell, GPUs burn out. It seems like using ice sculptures as collateral, and then spring comes.
In my experience CPU/GPU power is used up as much as possible. Increased efficiency just leads to more demand.
Re: S1: A $6 R1 competitor?
#74Re: S1: A $6 R1 competitor?
#75Re: S1: A $6 R1 competitor?
#76This thing that people are calling “reasoning” is more like rendering to me really, or multi pass rendering. We’re just refining the render, there’s no reasoning involved.
Re: S1: A $6 R1 competitor?
#77Earlier quoted context omitted.
This is pure speculation on my part but I think at some point a company's valuation became tied to how big their compute is so everybody jumped on the bandwagon.
Matt Levine tangentially talked about this during his podcast this past Friday (or was it the one before?). It was a good way to value these companies according to their compute size since those chips are very valuable. At a minimum, the chips are an asset that acts as a collateral.
Are they actually, though? Presently yes, but are they actually driving ROI? Or just an asset nobody really is meaningfully utilizing, but helps juice the stocks?
Re: S1: A $6 R1 competitor?
#78This thing that people are calling “reasoning” is more like rendering to me really, or multi pass rendering. We’re just refining the render, there’s no reasoning involved.
Re: S1: A $6 R1 competitor?
#79Earlier quoted context omitted.
I'm not convinced. This is using the tooling and paradigms invented by humans.
Science is a paradigm invented by humans. If a human uses this paradigm to invent something he is considered intelligent but if an ai uses it it’s not? All humans use human paradigms and they are intelligent. If a human uses such a paradigm to success it is the same.
Re: S1: A $6 R1 competitor?
#80This thing that people are calling “reasoning” is more like rendering to me really, or multi pass rendering. We’re just refining the render, there’s no reasoning involved.