Welcome to @MancerAI_ 🧙♂️☢️♟️🤖
Former physics guy now deep in ML/AI dev... And I guess officially research since my paper got accepted?
I typically (shit-)post about:
🔹Raw AI research experiments & cognition hacks
🔹Takes on frontier AI progress, efficiency (thermoputers, liquid AI approaches etc).
🔹AI art when feeling creative (or pretentious)
🔹Space exploration and news
🔹Chess (my first passion)
🔹Shitposts, memes, and hot (sometimes spicy) takes on where intelligence is headed.
🔹Occasional wild speculation on odd futures we're building toward.
If you're into demystifying how brains/minds might map to machines without the stick around. 🪄
Friendly reminder that the AI bubble
was in fact a bubble.
Based on Anthropic's S-1:
raised $141.1B (lifetime)
burned $9.4B (lifetime).
23 - June 26: free cashflow $6.7B
Currently bringing in $575M/m free cashflow.
@worldwide_yuya Regarding 2FA: there was a bug in Microsoft Authenticator for Android that could give apps access. Better check and update etc if you use it
@MIDIDesigner I think so. I haven't had a confirmed case of covid but this seems to check out. Dry cough, fever headache and so on.
Idk it sucks but it's just a bad mancold, nothing to worry about..thanks!
There were some journalist in Sweden that gave some of the leading gender "researchers" the same study (I don't remember the topic, something mundane.. groceries or something) but with opposite results/numbers.
In both cases the "experts" found a way to argue that the results show discrimination against women.
@Angaisb_ Largely agree. Arguably switch 5.3 Codex with some in the top S. That's when they took the lead and kept it through most of 2026.
Also image models deserve honorary mention
@TheSentientSun I'm not sure it has huge implications. Just shows that the way LLMs have solved language was closer to us than we thought.
Cool and interesting though
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.