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by jazzyjackson16 hours ago |
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upvoteby marcosdumay6 hours ago|
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The name you are looking for is "fixed points", not "eingevalues".
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upvoteby ajkjk10 hours ago|
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that's not really how eigenvalues work... they specifically also model the case where the result keeps changing exponentially.
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upvoteby mjburgess10 hours ago|
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The claim is that the RSI operation is just finding a fixed point of improvement,

RSI(LLM) = RSI(LLM) -- for an optimal LLM* which is a fixed point of RSI

As for eigenvalues/vectors, they're fixed points of (1/val)A or A*val

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upvoteby ekidd8 hours ago|
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Eigenvectors represent fixed directions, not fixed magnitudes. From Wikipedia:

> More precisely, an eigenvector v of a linear transformation T is scaled by a constant factor lambda when the linear transformation is applied to it: Tv = lambda v .

In other words, repeated multiplication of an eigenvector by a matrix can still create exponential growth.

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upvoteby fuzzfactor16 hours ago|
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>AI "recursively" improving itself in some exponential fashion until there is a bright flash of white light

Sounds like repetitive stress to me.

>loop forever using output as input but at some point the result will stop changing

Running in place will eventually wear you out too. Plus with some things it can be difficult to know for sure if that's where you are at the time.

Even worse may be if you were almost running in place, it could be orders of magnitude more difficult to discern, especially if the scale was massive to an unprecedented degree.

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