←back to thread

S1: A $6 R1 competitor?

(timkellogg.me)
851 points tkellogg | 1 comments | | HN request time: 0s | source
Show context
mtrovo ◴[] No.42951263[source]
I found the discussion around inference scaling with the 'Wait' hack so surreal. The fact such an ingeniously simple method can impact performance makes me wonder how many low-hanging fruit we're still missing. So weird to think that improvements on a branch of computer science is boiling down to conjuring the right incantation words, how you even change your mindset to start thinking this way?
replies(16): >>42951704 #>>42951764 #>>42951829 #>>42953577 #>>42954518 #>>42956436 #>>42956535 #>>42956674 #>>42957820 #>>42957909 #>>42958693 #>>42960400 #>>42960464 #>>42961717 #>>42964057 #>>43000399 #
cubefox ◴[] No.42951764[source]
Now imagine where we are in 12 months from now. This article from February 5 2025 will feel quaint by then. The acceleration keeps increasing. It seems likely we will soon have recursive self-improving AI -- reasoning models which do AI research. This will accelerate the rate of acceleration itself. It sounds stupid to say it, but yes, the singularity is near. Vastly superhuman AI now seems to arrive within the next few years. Terrifying.
replies(2): >>42952687 #>>42955196 #
zoogeny ◴[] No.42955196[source]
This is something I have been suppressing since I don't want to become chicken little. Anyone who isn't terrified by the last 3 months probably doesn't really understand what is happening.

I went from accepting I wouldn't see a true AI in my lifetime, to thinking it is possible before I die, to thinking it is possible in in the next decade, to thinking it is probably in the next 3 years to wondering if we might see it this year.

Just 6 months ago people were wondering if pre-training was stalling out and if we hit a wall. Then deepseek drops with RL'd inference time compute, China jumps from being 2 years behind in the AI race to being neck-and-neck and we're all wondering what will happen when we apply those techniques to the current full-sized behemoth models.

It seems the models that are going to come out around summer time may be jumps in capability beyond our expectations. And the updated costs means that there may be several open source alternatives available. The intelligence that will be available to the average technically literate individual will be frightening.

replies(2): >>42956212 #>>42963164 #
pjc50 ◴[] No.42963164[source]
This frightens mostly people whose identity is built around "intelligence", but without grounding in the real world. I've yet to see really good articulations of what, precisely we should be scared of.

Bedroom superweapons? Algorithmic propaganda? These things have humans in the loop building them. And the problem of "human alignment" is one unsolved since Cain and Abel.

AI alone is words on a screen.

The sibling thread details the "mass unemployment" scenario, which would be destabilizing, but understates how much of the current world of work is still physical. It's a threat to pure desk workers, but we're not the majority of the economy.

Perhaps there will be political instability, but .. we're already there from good old humans.

replies(4): >>42963468 #>>42964183 #>>42965461 #>>43000641 #
1. fennecfoxy ◴[] No.43000641{4}[source]
Depends on the model I suppose. Atm everything is being heavily trained as LLMs without much capability outside of input text->output text aside from non-modelised calls out to the Internet/RAG system etc.

But at some point (still quite far away) I'm sure we'll start training a more general purpose model, or an LLM self-training will break outside of the "you're a language model" bounds and we'll end up with exactly that;

An LLM model in a self-training loop that breaks outside of what we've told it to be (a Language model), becomes a general purpose model and then becomes intelligent enough to do something like put itself out onto the Internet. Obviously we'd catch the feelers that it puts out and realise that this sort of behaviour is starting to happen, but imagine if we didn't? A model that trained itself to be general purpose but act like a constantly executing LLM, uploads itself to Hugging Face, gets run on thousands of clusters by people, because it's "best in class" and yes it's sitting there answering LLM type queries but also in the background is sending out beacons & communicating with itself between those clusters to...idk do something nefarious.