mik09

i think in the long term the problem is going to be this: a great small model always come from a greater large model, but the larger base model keep getting larger and more closed sourced

so long as there's no algorithm breakthrough

try qwen 3.7 or glm 5.2 or one of the larger gemma models

"Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers."

as AI become more agentic i think this will be gradually replaced by AI buying stuff from other AI...

either people + AI is better so people just merge with AI or pure AI is better and AI takes over

either ai closes the loop which is unlikely or ai is not good and a small group of people manage to resist the urge to talk to it and take over everyone that does eventually

Saw a similar youtube video decide to make it myself.

i feel like we are using ai to solve virus detection in many cases, and in theory this is the same complexity as the halting problem.

evolutionary search is better than hard coded algorithms at finding solutions to np problems and this is similar to that. ai will be better security engineers than humans.

but simpler explanation work until they don't all of a sudden

yeah anthropic tries to address this through mechanistic interpretation but not sure they are progressing as fast in that domain as their model development

it might have broken a couple metrics since if you get above 90 percent it might be that the metric can not measure you well anymore right?

a lot of times people cry wolf for a couple of times before wolf actually comes.

i feel like theres a good chance that this is the actual wolf coming here. cause i was using opus for a lot and it's really good.

So, did LLM (namely Gemini-Flash) helepd with the combinatorial optimization process? I'm sure not all of their discoveries (one on kissing numbers, etc.) have previous solutions in some other form, but yeah these findings looks more like very large combinatorial optimization tasks.

multi-layer perceptrons are more complex than that lol

'coming again to save the motherfucking day yeah!'

its nice to know even people like google are treated like this. even people with management roles.

same. its hard to write on reddit these days. even 'pulp' alternatives like 9gag is a lot more welcoming somehow.

sometimes o1-preview start hallucinating halfway through a good solution. it can get the intuition and the 'main' direction for a problem wrong too. but then problem solving is just a series of rephrasings and translating into different math domains is used by mahtematicians for solving problems.

what if someone invented it before 1905

saw similar project on an AI subreddit that got a lot of upvotes

that sounds dystopian if its true

what is a good place to get a pulse on general sentiment then?

iirc, the official story from the mainland was that during around 1957 in order to boost literacy the govt simplified the characters, something like that...

today i learnt

r/machine learning comment thread has some interesting ideas, one of them linking this one with similar work in CV: https://www.reddit.com/r/MachineLearning/comments/1g0lnij/r_...

is this the same reason why fp4 with more parameters beats fp16 with less?

how long before it solves the last two problems?

my first reaction as well

used an exploit to get vpn working on router...

c dominates every other language again...https://github.com/dannyvankooten/1brc#submitting