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Comment by jonpo | Hacker News Reader

Well done you seem to have liberated an open model trained on open data for blind and visually impaired people.

Code: https://github.com/microsoft/banknote-net Training data: https://raw.githubusercontent.com/microsoft/banknote-net/ref...

model: https://github.com/microsoft/banknote-net/blob/main/models/b...

Kinda easier to download it straight from github.

Its licenced under MIT and CDLA-Permissive-2.0 licenses.

But lets not let that get in the way of hating on AI shall we?

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> But lets not let that get in the way of hating on AI shall we?

Can you please edit this kind of thing out of your HN comments? (This is in the site guidelines: https://news.ycombinator.com/newsguidelines.html.)

It leads to a downward spiral, as one can see in the progression to https://news.ycombinator.com/item?id=42604422 and https://news.ycombinator.com/item?id=42604728. That's what we're trying to avoid here.

Your post is informative and would be just fine without the last sentence (well, plus the snarky first two words).

Can you clarify this a bit. I presume you are talking about the tone more than the implied statement.

If the last sentence were explicit rather than implied, for instance

This article seems to be serving the growing prejudice against AI

Is that better? It is still likely to be controversial and the accuracy debatable, but it is at least sincere and could be the start of a reasonable conversation, provided the responders behave accordingly.

I would like people to talk about controversial things here if they do so in a considerate manner.

I'd also like to personally acknowledge how much work you do to defuse situations on HN. You represent an excellent example of how to behave. Even when the people you are talking to assume bad faith you hold your composure.

Sure, that would be better. It isn't snarky, and it makes fewer uncharitable assumptions.

I don't seem to be able to edit it, apologies I will try not to let this type of thing get to me in future.

I would also like to point out that this is a fine tuned classifier vision model based on mobilenetv2 and not an LLM.

Don't you think its intentional, so as not to demonstrate the technique on potentially copyrighted data?

Author here, it would be nice to claim that I did this on purpose but I really did not know it was open source.

I was rather interested in the process of instrumenting of TF to make this "attack" scalable to other apps.

... Because if he did this with a model that's not open that's sure going to keep everyone happy and not result in lawsuit(s)...

The same method/strategy applies to closed tools and models too, although you should probably be careful if you've handed over a credit card for a decryption key to a service and try this ;)

If this is exactly the same model then what's the point of encrypting it?

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