Live data from Hacker News

Unpredictable abilities emerging from large AI models

quantamagazine.org

51–60 of 326 posts

Re: Unpredictable abilities emerging from large AI models

#51
post #34

Earlier quoted context omitted.

Can you elaborate on fundamental limits?

I’m guessing one is data. The limit would be once you’ve trained a LLM on all public (or even private) data. Sure you can still make some improvements or try to find some additional private data but still, a fundamental limit has been reached.

Is it even feasible any time soon to train an LLM on all of YouTube?

Re: Unpredictable abilities emerging from large AI models

#52

There is a startling acceleration of innovation in the field that GPT-4 illustrates. According to NVidia, LLM sizes have been increasing 10X per year for the last few years. This tech is going to hit every aspect of society like a sledgehammer over the next 48 months.

I guess you perception of society is severely limited if you think a fancy autocomplete is capable of changing every aspect of it.

"""

That riled me, but I held my temper as I asked, “What’s the matter with you?” He bellowed: “There’s nothing the matter with me. It’s you! You’re crazy if you think this fool contraption you’ve been wasting your time on will ever displace the horse.”

"""

- https://www.saturdayeveningpost.com/2017/01/get-horse-americ...

Re: Unpredictable abilities emerging from large AI models

#53
post #29

Earlier quoted context omitted.

So on the one hand, these newly publicized models can render convincing representations of realities we used to get from deterministic processes. On the other hand, it's probabilistic and fails to conform to logic quite often, and in a confident way. We're building systems capable of programing computers non-deterministically. I think this is huge. But not because ChatGPT23 will be a CEO or a politician. But because…

I'm sort of glad to be retiring soon. I have a feeling everything I enjoy about programming is going to be going away.

I get the feeling. But I've always enjoyed the abstract puzzles more then anything. Computers attracted me as a form of very complex abstract puzzles.

But when it comes down to it everything in life is just nth dimensional tensor puzzles. What I really cherish computers for giving me is fast and clear feedback.

Re: Unpredictable abilities emerging from large AI models

#54
post #50

Disclaimer : I did not test GPT 4 myself. I think those emerging abilities are really interesting from a philosophical point of view, especially on the matter of consciousness. It seems it really reinforce the illusionist point of view on the hard problem of consciousness, eg it doesn't really exist. It seems to reinforce most functionalist theories in fact. I would be really interested in what Chalmers think of thos…

The illusionist point of view is false by definition, although their definition of "illusion" or "exist" sounds like it might not be how I'd define those words.

Re: Unpredictable abilities emerging from large AI models

#56
post #32

Earlier quoted context omitted.

You'll enjoy this AI generated spoken version: https://on.soundcloud.com/1tHgY

Is that by ElevenLabs? This induces the nervous sort of excitement in me.

Yeah, ElevenLabs. We've been using it for doing podcasts, voice overs and such. It's shockingly good if you dial it in right.

Re: Unpredictable abilities emerging from large AI models

#57
post #45

I'm still convinced I'll be able to get GPT4 to solve all these difficult problems for me that I'm having trouble solving on my own. So far it hasn't been so great at doing it, but it's fun to at least try. For context I'm trying to get it to help me learn how to implement scalable multiplayer game servers in NodeJS. It's a tough code organization problem, it becomes a tough system design problem as well the bigger y…

It's probably going to struggle with things it hasn't seen before?

> It's probably going to struggle with things it hasn't seen before?

It wont.

It'll just lie through its teeth and produce a very nice, very believable story which will unfortunately shatter when confronted with the real world.

Re: Unpredictable abilities emerging from large AI models

#58

This caught my attention as I found it implausible: > One DeepMind engineer even reported being able to convince ChatGPT that it was a Linux terminal and getting it to run some simple mathematical code to compute the first 10 prime numbers. Remarkably, it could finish the task faster than the same code running on a real Linux machine. Following the link, there's a screenshot to a screenshot [0] of a code-golf solutio…

So it sounds like the mechanism is something like stochastic memoisation?

I don't think "memoisation" is an accurate word for this; it implies doing the computation once, and storing the result in cache to return later. It's more like replacing your Python code with a SQL query of the LLM's understanding of what it's supposed to do, which may or may not be correct, and executing it on its "database" of knowledge, which may or may not have the correct data.

Re: Unpredictable abilities emerging from large AI models

#59
I'd like to see posts on LLMs written from a different perspective. For me, the surprise comes not from the sudden emergent capability of language models, but that the understanding (and synthesis!) of ideas encoded in language has succumbed to literally nothing more than statistical analysis. Or at least come that much closer to doing so.

That it bears so close a resemblance to actual thinking says more about the importance of language to cognition than the other way around.

Re: Unpredictable abilities emerging from large AI models

#60

This caught my attention as I found it implausible: > One DeepMind engineer even reported being able to convince ChatGPT that it was a Linux terminal and getting it to run some simple mathematical code to compute the first 10 prime numbers. Remarkably, it could finish the task faster than the same code running on a real Linux machine. Following the link, there's a screenshot to a screenshot [0] of a code-golf solutio…

So it sounds like the mechanism is something like stochastic memoisation?

this is new to me but.. a quick read of Wikipedia [1] later, it appears that this decades-old method takes a goal, and then uses branching and recording to find paths that differ the least from the goal. The article mentions that the curse of dimensionality is so bad here that approximations are often used in practice. Does that capture it?

[1] https://en.wikipedia.org/wiki/Stochastic_dynamic_programming

Post reply on HN