Replying to @KLoaec
wen bubble pops you'll have shit loads of sub thousand 32gb gpus.
let's wait a year or so.
Replying to @xi32515
la question est rhétorique, ça ne sert à rien d'y répondre.
Replying to @sc_cath
frédéric bastiat au XIXème siècle en parlait déjà.
alberto brandolini nous explique pourquoi c'est épuisant.
Replying to @Sardoche
être fonctionnaire, être de gauche, être égalitariste et vouloir un régime d'exception pour les fonctionnaires.
le statut de fonctionnaire est intrinsèquement fasciste.
I wonder who they'll put in his place.🤔
I imagine the next person will have to deal with the end of the euro.
I have just informed my colleagues that I will step down as @ECB President on 7 February 2027.
It has been a source of great pride to serve this institution.
I thank all of those who have supported me on this journey over the past seven years.
Replying to @epelboin @C_Barbier
une écharpe, ça se voit pas quand on la retourne.
weedcoder🏴 retweeted
🚨🇨🇳 A Chinese glass company just turned the RIOTS in France into FREE advertising!
Hengxinfeng filmed NOTHING, just posted a video of its unbreakable windows on social media, and went VIRAL.
EPIC TROLLING!
weedcoder🏴 retweeted
Bitcoin Core v32.1 was released!
It is available from: bitcoincore.org/en/download/
Release notes: bitcoincore.org/en/releases/…
c'est marrant.
tout ceux qui crient que les LLMs ne sont pas intelligents vont bientôt devoir dire la même chose des humains.
Chomsky was wrong.
Researchers found your brain doesn’t store language the way every textbook since 1957 claims.
For decades, the undisputed rule of linguistics, led by Noam Chomsky, was that human language is hierarchical.
We were told our brains process language using complex "grammar trees." That we secretly build deep, abstract, mathematical rules in our heads before we speak.
This new paper proves that is completely wrong.
Researchers at Cornell University analyzed how people actually process and produce language in real time.
They found sequences. Linear chunks.
When we speak, we aren't calculating deep syntactic rules. We are just predicting the next most logical sequence of words based on the context of the words right before it.
We string linear chunks together.
If this sounds familiar, it should.
This is exactly how Large Language Models like ChatGPT work.
For years, critics have dismissed AI as "just a next-token predictor." They said it isn't truly intelligent because it doesn't understand deep grammatical hierarchies like humans do.
But this paper suggests humans don't use those hierarchies either.
We are just predicting the next chunk.
Language isn't a rigid tree of mathematical rules. It's a linear stream of contextual predictions.
We thought we were building AI to mimic the complexity of the human brain.
It turns out, the human brain was just running a simpler algorithm all along.











