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by michaelmior 854 days ago
Except a 100% correct implementation doesn't exist AFAIK. So if I want to do anything that makes a decision based on the type of a file, I have to pick some algorithm to do that. If I can do that correctly 99% of the time, that's better than not being able to make that decision at all, which is where I'm left if a perfect implementation doesn't exist.
1 comments
jdiff 854 days ago
Nobody's asking for perfection. But the AI is offering inexplicable and obvious nondeterministic mistakes that the traditional algorithms don't suffer from.

Magika goes wrong and your fonts become audio files and nobody knows why. Magic goes wrong and your ZIP-based documents get mistaken for generic ZIP files. If you work with that edge case a lot, you can anticipate it with traditional algorithms. You can't anticipate nondeterministic hallucination.

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duskwuff 854 days ago
Seconding this.

Something like Magika is potentially useful as a second pass if conventional methods of detecting a file type fail or yield a low-confidence result. But, for the majority of binary files, those conventional methods are perfectly adequate. If the first few bytes of a file are "GIF89a", you don't need an AI to tell you that it's probably a GIF image.

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EnigmaFlare 854 days ago
Doesn't seem all that non-deterministic. I tested the vba.html example multiple times and it always said it was VBA. I added a space between </HEAD> and <BODY> and it correctly picked HTML as most likely but with a low confidence.

So I think we can say it's sensitive to mysterious features, not that it's non-deterministic. Still leads to your same conclusion that you can't anticipate the failures. But I don't think you can with traditional tools either. Some magic numbers are just plain text (like MZ) which could legitimately accidentally appear at the beginning of a plain text file, for example.

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jsnell 854 days ago
Where are you getting the non-determinism part from? It would seem surprising for there to be anything non-deterministic about an ML model like this, and nothing in the original reports seems to suggest that either.
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TeMPOraL 854 days ago
Large ML models tend to be uncorrectably non-deterministic simply from doing lots of floating point math in parallel. Addition and multiplication of floats is neither commutative nor associative - you may get different results depending on the order in which you add/multiply numbers.
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eapriv 854 days ago
Addition and multiplication of floats are commutative.
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Gormo 854 days ago
> It would seem surprising for there to be anything non-deterministic about an ML model like this

I think there may be some confusion of ideas going in here. Machine learning is fundamentally stochastic, so it is non-deterministic almost by definition.

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