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Show HN: A 6M-token movable window on a single 46GB GPU

arxiv.org

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Re: Show HN: A 6M-token movable window on a single 46GB GPU

#6
post #3

You couldn't be bothered to write a coherent summary of what this actually is and what it does, you just let the AI write some random noise, eh?

This paper show a new tool called Galahad.Normally, AI has to think and guess the answer every time, which costs time and money.

The knowledge of the model grows next to it not the model itself and no it is not the same as cache

No fine-tuning needed

It gives the exact same right answer every time, costs zero extra tokens, and saves lots of energy

Re: Show HN: A 6M-token movable window on a single 46GB GPU

#7
post #6
post #3

You couldn't be bothered to write a coherent summary of what this actually is and what it does, you just let the AI write some random noise, eh?

This paper show a new tool called Galahad.Normally, AI has to think and guess the answer every time, which costs time and money. The knowledge of the model grows next to it not the model itself and no it is not the same as cache No fine-tuning needed It gives the exact same right answer every time, costs zero extra tokens, and saves lots of energy

So, you don't know what it is, either.

Re: Show HN: A 6M-token movable window on a single 46GB GPU

#8

100% generated. I skimmed the paper, and came out with a feeling of still not knowing what this is about.

We handeld llm like a human brain we decoupled knowledge from the memory and build a memory layer that makes redoing things free and fast, so the llm can once it learned something solves it for free the next time

Re: Show HN: A 6M-token movable window on a single 46GB GPU

#9
post #7
post #6

Earlier quoted context omitted.

This paper show a new tool called Galahad.Normally, AI has to think and guess the answer every time, which costs time and money. The knowledge of the model grows next to it not the model itself and no it is not the same as cache No fine-tuning needed It gives the exact same right answer every time, costs zero extra tokens, and saves lots of energy

So, you don't know what it is, either.

We handeld llm like a human brain we decopelled knowledge from the memory and build a memory layer that makes redoing things free and fast, so the llm can once it learned something solves it for free the next time
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