This is a very appropriate thread to wish you a happy cake day!

Okay, i think there is quite a misunderstanding here.

Some older versions of LLMs (chatgpt3.5-turbo-instruct) can play chess relatively well (around 1750 Elo) : here is a link to an article studying that.

Some points :

• it is of course way worse than almost any algorithm designed for chess
• one of the reason we cannot get these result back (at least not that good, here is a link to a blog post of someone making recent LLMs chatbots better at chess) could be that we do not have access to pure completion mode on models trained on selected data (where they could purposefully choose only good chess matches), and those are now hidden behind a chatbot layer instead.
• it seems to reveal that models have a somehow accurate representation of the chess board when predicting chess moves
• it seems to have a quite unique feat that is : if you feed them a prompt that say they play as a very good player, and then the beginning of a game with a blatant bad move (giving away a queen for example), they sometimes play the entire game with moves that purposefully give away pieces, as if they guess that the only reason they would lose a piece that easily is by purposefully losing them. It has close to zero utility, but it’s interesting anyway.

I think i do not, but my gf loves raw cabbages and cannot stand it when it’s cooked in any form.

Here is the main blog post that i remembered : it has a follow up, a more scientific version, and uses two other articles as a basis, so you might want to dig around what they mention in the introduction.

It is indeed a quite technical discovery, and it still lacks complete and wider analysis, but it is very interesting for the fact that it kinda invalidates the common gut feeling that llms are pure lucky random.

Oh yes, cost of training are ofc a great loss here, it’s not optimized at all, and it’s stuck at an average level.

Interestingly, i believe some people did research on it and found some parameters in the model that seemed to represent the state of the chess board (as in, they seem to reflect the current state of the board, and when artificially modified, the model takes modification into account in its playing). It was used by a french youtuber to show how LLMs can somehow have a kinda representation of the world. I can try to get the sources back if you’re interested.

Actually, a very specific model (chatgpt3.5-turbo-instruct) was pretty good at chess (around 1700 elo if i remember correctly).

In case you were thinking the opposite, i think we can safely assume that neither this meme nor the comments support capitalism.

Law. I was pretty hyped up when i went to university to study it, but the more i learnt on the foundations of it and discovered the people it created, the more i hated it. Now I’m doing completely different things, and i’m glad my parents didn’t force me to keep doing it.

I mean, resources can also include time, energy, contacts, social abilities, all of which are much more important than money when organizing a protest, especially a ‘small’ one. Ofc, your argument still stands that thz best way to get something is to work for it to be done, but it is reasonable to think that someone might miss resources in the broad sense as above, making it much more work relatively speaking.

I’ll just say autumn makes me horny to complete the circle

Toi aussi tu veux te payer le Groenland O.o ?

Blague à part, je suis d’accord avec toi sur le principe “ce n’est pas l’argent en lui-même qui rend con”. Par contre, je pense qu’on peut faire survivre le problème si on considère que l’argent est entendu ici non pas comme une somme de monnaie concrète, mais comme un ensemble de transactions qui organise notre société. Ce n’est plus alors l’utilisation du billet de 1 dollar qui peut rendre con/méchant, mais ce qu’on ferait pour en obtenir d’autre, ou pour ne pas le perdre, etc. A ce titre, on peut agir de manières qui ne sont cohérentes que si on les prend du point de vue de l’argent (comme des achats compulsifs pendant les soldes), ce qui peut faire dire que l’argent rend con/méchant en introduisant des mécaniques qui nous font prendre des décisions cons/méchant.

Crêpes-party ! Cook a bunch of crêpes and prepare some stuff to put in : either salty (meats, cheeses, cream, smoked fish,…) or sweet (chocolate sauce, caramel, jelly, fruits spread, sugar,…). You can ask people what they like before hand, so that everyone has something they appreciate. If you need a vegan option, you can swap milk for plant milk and eggs for a mix of starch and water.

I agree, having experienced this especially on mathematics pages. But on the other hand, from my experience, the whole article is very technical in those cases : I’m not sure making a summary would help, and im not sure you can provide a summary both correct and easily understandable in those cases.