But to be fair nobody does anything from scratch. Most people were in school at least for a few years. If you code, you’ve probably read a lot of code and documentation, if you draw you probably saw a lot of drawings, if you play chess you probably studied a lot of different games.

Ad for an ad-blocker. Genius 🤣

Feel free to use floppy disks. Btw if you are online, you use WebP and PNG all the time 🤣

Would completely defeat the purpose of making a new smaller file format if we prefix if with the old format.

Only in the US 🤣

That’s intended. Look at the second hand for a minute. It goes 1, 2, 3, etc. like on a real clock but the numbers are distributed differently. That’s also why the hands sometimes have to move faster to reach their target in time. It goes (backwards) if it’s closer.

Here you are: https://jsfiddle.net/2o97k6vz/6/

Because an image is a bit to lazy IMHO for “prgrammer” humor. I programmed a clock that actually works. Have fun 🤣

https://jsfiddle.net/gjpwf5oq/2/

Btw: you can change the order of the clock-face if you want.

Update: Supports arbitrary text now (example roman numerals): https://jsfiddle.net/2o97k6vz/6/

Update: And with Months because why not 🤣 https://jsfiddle.net/2o97k6vz/7/

Play tic tac toe a few times against Chat-GPT. Wouldn’t trust an LLM that can’t win tic tac toe against four year olds with production code 🤣

It still can panic/abort and deadlock/wait infinitely long on most fp languages because that’s typically implied. And there isn’t actually a way around that because computation almost always can fail or block indefinitely - and if you have a total language you can implement waits for billions of years, which for all practical purposes is “infinitely” long on human time scales.

Thanks for pointing that out, haven’t tried that.

I can’t select the text on this article (mobile). I’m not sure if that’s on purpose or just ironic?

I think the most hilarious thing was their public Copilot demonstration working on the .NET source code. They basically showed the world that copilot isn’t ready for serious work.

I didn’t say they have no knowledge, quite the opposite. Here a quote from the comment you answered:

LLMs are extremely knowledgeable (as in they “know” a lot) but are completely dumb.

There is a subtle difference between intelligent and knowledgeable. LLM know a lot in that sense that they can remember a lot of things, but they are dumb in that sense that they are completely unable to draw conclusions and put that knowledge into action in any other means besides spitting out again what they once learned.

That’s why LLMs can tell you a lot about about all different kinds of game theory about tic tac toe but can’t draw/win that game consistently.

So knowing a lot and still being dumb is not a contradiction.

But wouldn’t you point still be true today that the best AI video models today would be the onces that are not available for consumers?

Coding isn’t special you are right, but it’s a thinking task and LLMs (including reasoning models) don’t know how to think. LLMs are knowledgeable because they remembered a lot of the data and patterns of the training data, but they didn’t learn to think from that. That’s why LLMs can’t replace humans.

That does certainly not mean that software can’t be smarter than humans. It will and it’s just a matter of time, but to get there we likely have AGI first.

To show you that LLMs can’t think, try to play ASCII tic tac toe (XXO) against all those models. They are completely dumb even though it “saw” the entire Wikipedia article on how xxo works during training, that it’s a solved game, different strategies and how to consistently draw - but still it can’t do it. It loses most games against my four year old niece and she doesn’t even play good/perfect xxo.

I wouldn’t trust anything, which is claimed to do thinking tasks, that can’t even beat my niece in xxo, with writing firmware for cars or airplanes.

LLMs are great if used like search engines or interactive versions of Wikipedia/Stack overflow. But they certainly can’t think. For now, but likely we’ll need different architectures for real thinking models than LLMs have.

I don’t see how that follows because I did point out in another comment that they are very useful if used like search engines or interactive stack overflow or Wikipedia.

LLMs are extremely knowledgeable (as in they “know” a lot) but are completely dumb.

If you want to anthropomorphise it, current LLMs are like a person that read the entire internet, remembered a lot of it, but still is too stupid to win/draw tic tac toe.

So there is value in LLMs, if you use them for their knowledge.

Totally agree with that and I don’t think anybody would see that as controversial. LLMs are actually good in a lot of things, but not thinking and typically not if you are an expert. That’s why LLMs know more about the anatomy of humans than I do, but probably not more than most people with a medical degree.

I can’t speak for Lemmy but I’m personally not against LLMs and also use them on a regular basis. As Pennomi said (and I totally agree with that) LLMs are a tool and we should use that tool for things it’s good for. But “thinking” is not one of the things LLMs are good at. And software engineering requires a ton of thinking. Of course there are things (boilerplate, etc.) where no real thinking is required, but non-AI tools like code completion/intellisense, macros, code snippets/templates can help with that and never was I bottle-necked by my typing speed when writing software.

It was always the time I needed to plan the structure of the software, design good and correct abstractions and the overall architecture. Exactly the things LLMs can’t do.

Copilot even fails to stick to coding style from the same file, just because it saw a different style more often during training.

There actually isn’t really any doubt that AI (especially AGI) will surpass humans on all thinking tasks unless we have a mass extinction event first. But current LLMs are nowhere close to actual human intelligence.