Oh? What else have they said? I didn’t know there was a reputation for fibbing.

Yeah, but they were talking about building out WhatsApp third party compatibility on top of it.

There already was Element One, which bridged to a bunch of things for a small subscription fee, although it had to break E2EE to do so. I’m just finding a lot of broken links now, though.

Wow, I’m surprised they got it up that high in a practical application.

They let OpenWhisper do the underlying protocol, so it’s solid. Beats the shit out of a plain text message anyway, and people IRL might actually have it.

Wasn’t Element going to integrate into it as well?

TIL. In the movies they just pull out their Luger.

Wow, Portugal way ahead of the curve. Iceland too, but that might be a size thing.

Did Germany ever do guillotining on it’s own, or was it just in the French occupation zone?

It’s a popular theory about why dogs were domesticated so much earlier than everything else. Wolves have a remarkably similar lifestyle to human hunter gatherers, and so early dogs could live either in parallel or in close proximity as conditions demanded. With other creatures, like pigs or horses, humans had to run a program and do so consistently for domestication to work. In some places, semi-feral dogs are still a common sight.

Shut up and take my venture capital money! And maybe 2/3 of the whole market cap in stock options! /s

Of course, this takes all words as equiprobable; results would be different if including the odds of a word appearing in the text into the maths.

I feel like it works more like 90% of the time when it comes up, so maybe this. And could it be that the words where “ie” appears are more ambiguous somehow, like don’t fit neatly into some existing pattern?

I don’t remember the “after c” bit ever being of use, though, so that part totally makes sense.

Edit: For an example, I’d never forget the spelling of “either”, because it’s so common and initial letters are more memorable. But, “piece” is tricky - “peice” is my first instinct, and I literally say “i before e” in my head when I write it now.

I wouldn’t go that far. Sometimes I’m not sure which way around they go, and that will usually lead you the right way.

Isn’t this basically an implementation of spaghetti sort? I’ve seriously taken the delay approach before in distributed memory situations.

Thank you, yes I do. And like I said in OP it seems to be crapping out pretty good at it’s current level of ability - maybe it’s not a Ponzi scheme, but it is a giant overvalued bubble.

The internet can’t hurt you, you don’t have to lie to us. And it kinda pisses me off when people do anyway, because it makes it worse for everyone.

Ah yes, Lemmy, beloved by politicians. /s

Any comments on how you attempted to lie to us all there? To win an internet argument?

It is. It’s one that has hidden layers, as opposed to a shallow neural net which does not. Shallow neural nets aren’t really a thing anymore, so it’s usually omitted, but historically things like the perceptron go back further, and they’re conceptually simpler to update during training. They also can’t really deal with anything nonlinear.

And that paper’s name? Albert Einstein. I can’t find anything on Weizenbaum and Turing authoring together. Weizenbaum seems to have written mostly prose and code, even - he’s not really thought of for his mathematical innovations, although obviously math was his original field.

Back in the 50’s people thought conventional algorithms, like everybody here has worked with, were going to reach human intelligence. They could play chess, and chess is smart guy stuff, so obviously recognising a bird should be easy, right? Well, they figured out that wasn’t right, and so began the first AI winter.

The tech of deep neural nets is in fact fairly new. Like, arguably it didn’t become a thing until the Cold War was ending, although there were a lot of precursors, and it kind of arrived gradually.

Hmm. I’m not sure what you’re referring to. Do you have a link?

I mean, nitpick, but if you blamed mathematics you actually would be. The observation that AI/LLMs are highly unreliable and don’t appear to be getting any better is empirical.

Now that I’ve actually looked at the study, what they did is make an apparatus with continuously adjustable distance to display and try to get people to distinguish scaled, fairly similar clips until they couldn’t anymore.

Actual maximum pixel-per-visual-degree values varied quite a bit based on colours involved and the like. And like @GenderNeutralBro@lemmy.sdf.org said, they framed the results the opposite way to the article - human vision can distinguish more than previously thought.

A link to the study, because I don’t think I see one in this very clickbait-feeling source.