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SubQ: a sub-quadratic LLM with 12M-token context

subq.ai

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Re: SubQ: a sub-quadratic LLM with 12M-token context

#5

Looks like long context isn’t a problem anymore

Neither is cost, and latency, in the long-term. LLMs ultimately become more economically viable than they are now, and broaden the scope of every existing LLM-driven application (particularly STS, conversational AI, etc, etc.)

Re: SubQ: a sub-quadratic LLM with 12M-token context

#6
I’m very surprised this isn’t getting more attention. Am I missing something?

It seems at or above SOTA on the given benchmarks, doesn’t have context rot, is orders of magnitude faster, and uses less compute that current transformer models. I suppose it’s just an announcement and we can’t test it ourselves yet.

Re: SubQ: a sub-quadratic LLM with 12M-token context

#8
post #6

I’m very surprised this isn’t getting more attention. Am I missing something? It seems at or above SOTA on the given benchmarks, doesn’t have context rot, is orders of magnitude faster, and uses less compute that current transformer models. I suppose it’s just an announcement and we can’t test it ourselves yet.

The proof is in the pudding. At this point, there have been plenty of models that overperformed on benchmarks and underperformed on real work. So my stance is that I'm curious, I'm excited to see where it goes, and I don't believe it until I can try it.

Re: SubQ: a sub-quadratic LLM with 12M-token context

#9
post #6

I’m very surprised this isn’t getting more attention. Am I missing something? It seems at or above SOTA on the given benchmarks, doesn’t have context rot, is orders of magnitude faster, and uses less compute that current transformer models. I suppose it’s just an announcement and we can’t test it ourselves yet.

I agree, it's a real architectural breakthrough if true
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