[matusp]

I don't think this is only about efficiency. The model I have here is that this is similar to when we beat chess. Yes, it is impressive that we made progress on a class of problems, but is this class aligned with what the economy or the society needs?

Simple turn-based games such as chess turned out to be too far away from anything practical and chess-engine-like programs were never that useful. It is entirely possible that this will end up in a similar situation. ARC-like pattern matching problems or programming challenges are indeed a respectable challenge for AI, but do we need a program that is able to solve them? How often does something like that come up really? I can see some time-saving in using AI vs StackOverflow in solving some programming challenges, but is there more to this?

[edanm]

I mostly agree with your analysis, but just to drive home a point here - I don't think that algorithms to beat Chess were ever seriously considered as something that would be relevant outside of the context of Chess itself. And obviously, within the world of Chess, they are major breakthroughs.

In this case there is more reason to think these things are relevant outside of the direct context - these tests were specifically designed to see if AI can do general-thinking tasks. The benchmarks might be bad, but that's at least their purpose (unlike in Chess).

[lugu]

ARC is designed to be hard for current models. It cannot be a proxy for how useful they are. It says something else. Most likely those models won't replace human at their tasks in their organization. Instead "we" will design pipeline so that the tasks aligns with the ability of the model and we will put the human at the periphery. Think of how a factory is organised for the robots.

[spamlettuce]

okay, but what about literal swe-bench. O3 scored 75% eval