Next.js Hacker News
Fast KV Compaction via Attention Matching
63 points by cbracketdash 17 hours ago | 15 comments
  • WarmWash
    Considering the insanity of the AI arms race going on now, and the incredible sums of money be thrown at any slight advantage, is there any reason to believe that any meaningful AI breakthrough would be openly published for anyone to leverage?
    • 542458
      These folks are MIT, so citations are valuable to them. Citations convert into prestige, academic career progression, or a favorable exit from academia into industry.

      Also, I don't see why you couldn't patent this if you wanted to monetize it.

      • BetaDeltaAlpha
        > Also, I don't see why you couldn't patent this if you wanted to monetize it.

        We all just saw the prior art published for the public. That will preclude patenting this work. Further reduction to practice is required.

        (I am not a lawyer).

    • jph00
      Yes there is. Lots of researchers are more interested in making a contribution to societal flourishing than in making incredible sums of money. That’s why there’s still lots of top AI researchers in academia.
    • abeppu
      I do sometimes wonder -- if the transformers paper wasn't published, what would the industry be like? Would the same ideas have been put together in almost the same way weeks or months later somewhere else?
    • mikodin
      I would say yes.

      The reality is that the money being thrown = the time of humans. I guess compute as well, but in terms of people doing innovation - openly published things are the same thing, minus the money.

    • gdiamos
      I know the frontier “labs” are holding back publications.

      I don’t think it will last among researchers who think beyond production LLMs

    • cma
      The inventor's grace period under first to file changes still gives them/their university a year to file if they publish openly.
  • cadamsdotcom
    Superficially it sounds like this could create a bit more of a move toward doing compaction on some continuous basis, or compacting in batches once you hit the context limit, rather than starting fresh with a summary and system prompt..

    Feels like high fidelity, fast compaction could be a path to “solving” long context.

  • cs702
    This looks promising. I've added it to my reading list.
  • speedping
    This is big for long-horizon tasks
  • esafak
    None of the compaction accuracies look impressive.
    • yorwba
      I think matching or exceeding the original cache at 20% compacted size is fairly impressive.
      • esafak
        The original cache had 70% accuracy, and the alternatives were only worse.
        • yorwba
          It sounds like you looked at figure 1 but not figure 3.