Yup. The hookers make $500k/year, so it can't be them.

(the oldest profession will outlive AI replacement)

Eh.... I'd call that FinTech. Financial Engineering is more... optional.

When I'm worried my phone doesn't turn itself off, I just use a small flyswatter.

(And by small, I mean large.)

(And by flyswatter, I mean hammer.)

Works every time though!

(But it's expensive! I really ought to try this long press thing one day.)

When did it become acceptable to treat Dr Evil's henchmen poorly? I blame a lack of Austin Powers remakes in cinemas. Are you listening, Hollywood? Won't someone _please_ think of the children (and wives)?

These are not Markov chains. They're neural nets. They work via extremely complex chained fuzzy logic on superpositions of conceptual states.

They are, by definition, Markov chains. It's a Von Neumann architectural Finite State Machine processing a string of bytes, outputting bytes that get fed back in. That's a Markov chain.

Don't get hung up on bullshit about "extremely complex blah blah blah.". That's just designed to confuse you.

It matters quite a lot if someone sues you. Or if a propagandized public and their leaders get into a war over it.

A feature of Linux is anyone can code what they care about.
Charity carries no obligation.

Users merely use. We should remember how little we matter, and that if we want something different we're free to learn to code what we want.

In a real sense, the back end recognition that Flock does is exactly stalking on a massive scale.

It's not a matter of not being seen or even not being photographed every now and then. That level of privacy is not available in public.

But even in public, until Flock and it's ilk came along, we had the privacy of being just a face in the crowd. The people who saw you on main street were different from the people that saw you on 2nd street, were different from the people who saw you leaving your home. There was no database and no recognition software to stitch all of the sightings together to form a coherent record of your movements.

It's that tracking and recording that people object to.

The US Supreme Court, and supreme courts in general, are not "triggered." You appeal to them to hear your case. They may do so if they feel that your case is somehow relevant to wider issues.

The US Supreme Court might hear this case if they wanted to interpret the constitution in such a way as to set upper limits placed on fines, or wished to issue a judgement on the idea that fraud is still fraud if nobody gets hurt.

Yeah, that's a good example. Also "the actual thinking process as opposed to the correlational hallucinations that constitute all LLM 'thought'."

Two different sides of the same hubris.

A little tutorial if you know a little bit of Python:

https://numpy.org/numpy-tutori...

And a book with more detail if you're more into math:

https://www.deeplearningbook.o...

Everything else is pretty much scaling up and introducing some restrictions on the basic model.

You see it in the way you just used the word "you." Model "collapse" is a misnomer. It's drift, which you see in humans in literally everything they do, and you can demonstrate to yourself just by repeatedly generating random numbers and calculating the mean.

Bullshit. The fundamentals of modern AI models can be understood by anyone with a basic knowledge of algebra, which you should have picked up in junior high. They're piecewise linear approximations and use exactly the same equation as the linear regression you learned in high school or first year university. The more advanced stuff is hacky restrictions on that basic design to tone down the model's flexibility and make it easier to fit.

The reason it's hard to understand is because a) people who have no idea what they're talking about try and handwave their way through it; b) people explaining it want you to think it's really, really sophisticated and hard to understand, c) you're using "understand" in an unrealistic way or d) some combination of the above.

I think there is room to argue though, that distillation might violate copyright while training on large volumes of large material does not.

Nope. There is an argument about whether training a model on source material violates copyright or not. Current court decisions in the US say that the training does not, but you must have acquired the material legally in the first place.

Current court decisions in the US say that the raw output of a model is not copyrightable. Never mind that the people doing the distilling have paid for that output so even if it were copyrightable they'd own it.

The only thing happening is violation of terms of service which haven't been tested in court and would (hopefully) fail that test. Otherwise good luck with any software you use to produce anything, compilers included. And that's why these companies are directly lobbying the US government to do, uh, something, about it. They're trying to turn a bug in their business model into a geopolitical issue.