@MatthewJBar I think you’re wrong and there’s 1,000x efficiency gains leftover in deep learning research that could lead to much smarter faster more agentic models given the same inputs

now on the eve of RSI it seems everyone is more mutual conditional pause agreement pilled than they used to be and that seems like a good development

@jrysana american models seem to be significantly better than and actually pulling away from the Chinese open source ones. I would say the American frontier models are just racing with each other mostly

having the mechanisms to slow down if needed will reduce anxiety overall and may even improve the rate of progress in the timelines where everything turns out to be good

what ML researchers do is improve compute efficiency and data efficiency. if you believe we’ve already covered most of the ground, then you’ve got little to fear. if you think we aren’t close to the “Landauer limit” (using this entirely metaphorically) of model training, then RSI can change things dramatically

@tszzl I don't think it's a good development. I continue to think that RSI is an overrated risk vector due to data and compute bottlenecks, and that slowing down AI would accomplish little at enormous cost.

@tszzl I don't think a pause is ever possible.

AI development would just get shoved into a govt black budget which would only provide the illusion to the public of a pause.

@tszzl not at a frontier lab so i trust you but looking at 5.5 "RSI" evals this doesn't seems like much progress compare to previous generation

@tszzl There's zero costs to say you are mutual conditional pause agreement pilled.

@tszzl hey bro I totally won't take that marshmallow in the middle of the table yeah you can go to the potty I won't touch it haha

@tszzl @jrysana

@sailaunderscore very true. that’s part of the beauty of it. it’s like a free lunch for reducing anxiety

@tszzl @MatthewJBar that's such a vague claim

@tszzl @MatthewJBar i agree RSI *can* change things dramatically. that's again an extremely weak claim that:

1. presupposes "RSI" exists 2. qualifies the "change things dramatically" prediction with "can" (which makes it impossible to disagree with, especially conditional on 1)

@EgeErdil2 @MatthewJBar you’re right im just giving you squishy intuitions but these are my intuitions

@tszzl @MatthewJBar in a world where r&d progress in AI is itself compute-bottlenecked, it can simultaneously be true that:

1. we're far from the "landauer limit" of efficiently using compute and data during training, inference, etc

2. we can't close the gap to it by scaling cognitive effort alone

@tszzl @jrysana yup (only https://deepswe.datacurve.ai/blog currently shows this clearly, but practitioners notice this intuitively)

@tszzl @MatthewJBar matthew is just saying RSI is overrated as a *risk vector*, as in, he thinks it's not going to happen because there are other inputs that go into improving AI systems that will become bottlenecks with abundant researcher effort

your claim doesn't respond to that at all

@tszzl unenforceable sadly. even if China agrees, when we inevitably find out they've violated it, what are we going to do? bomb their data centers and start WW3? nobody even supports stopping Iran from getting nukes. so it's just a "give China a couple years' lead" button.

@tszzl I certainly ride my bike faster knowing that the brakes work