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by mwernolagoo9 hours ago |
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upvoteby D-Machine9 hours ago|
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upvoteby mlyle9 hours ago|
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I understand linear algebra. It seems like he probably does, too.

Are you sure you have read and understood his point?

It seem quite possible that the flattened-model-weights ingested into a model have a much greater fidelity of representation in a similar model's KV cache than they do in a human's working memory, and that being able to loop and digest and chunk makes it unsurprising that models can excel at this type of task.

I think that's the point the person is making. Do you disagree? If so, why?

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upvoteby D-Machine8 hours ago|
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upvoteby tomrod7 hours ago|
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A vector is a type of a matrix is a type of a tensor.
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upvoteby mlyle7 hours ago|
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> Bringing up the KV cache is a sign you don't understand what you are talking about here. The KV cache is a computational efficiency thing and has no impact on how these models actually work (and isn't needed at all). The vague analogy to human working memory also just takes the cake here.

You seem to really like to tell people that they don't know what they're talking about more than you seem to be parsing what they're actually saying.

I remember when I used to look for reasons to pounce on people for not knowing what they were talking about based on a superficial thing or two rather than try to understand what they were saying. I mostly got past it as a teenager, though.

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upvoteby D-Machine7 hours ago|
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upvoteby mlyle6 hours ago|
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If you care about the quality of HN: produce the high quality content you want; don't demean others.

There's not really a point in talking back to abuse. Think what you will.

I will point out that your comment was the first reply ever to someone completely new to HN, though.

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upvoteby maxrev176 hours ago|
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I really am not surprised someone is such an arse around this place. Being totally factually right is the most important thing in life always, right?!
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