Less than a year to destroy Arc-AGI-2 - wow.
ARC-AGI-3 has a nasty combo of spatial reasoning + explore/exploit. It's basically adversarial vs current AIs.
But i'm not sure how to give such benchmarks. I'm thinking of tasks like learning a language/becoming a master at chess from scratch/becoming a skill artists but where the task is novel enough for the actor to not be anywhere close to proficient at beginning--an example which could be of interest is, here is a robot you control, you can make actions, see results...become proficient at table tennis. Maybe another would be, here is a new video game, obtain the best possible 0% speedrun.
Arc-AGI score isn't correlated with anything useful.
It's also interesting because it's very very hard for base LLMs, even if you try to "cheat" by training on millions of ARC-like problems. Reasoning LLMs show genuine improvement on this type of problem.
>can u make the progm for helps that with what in need for shpping good cheap products that will display them on screen and have me let the best one to get so that i can quickly hav it at home
And get back an automatic coupon code app like the user actually wanted.
You would need to check to see if everyone is having mistakes on the same 20% or different 20%. If its the same 20% either those questions are really hard, or they are keyed incorrectly, or they aren't stated with enough context to actually solve the problem.
It happens. Old MMLU non pro had a lot of wrong answers. Simple things like MNIST have digits labeled incorrect or drawn so badly its not even a digit anymore.
But the idea of automation is to make a lot fewer mistakes than a human, not just to do things faster and worse.
The problem is that if the automation breaks at any point, the entire system fails. And programming automations are extremely sensitive to minor errors (i.e. a missing semicolon).
AI does have an interesting feature though, it tends to self-healing in a way, when given tools access and a feedback loop. The only problem is that self-healing can incorrectly heal errors, then the final reault will be wrong in hard-to-detect ways.
So the more wuch hidden bugs there are, the nore unexpectedly the automations will perform.
I still don't trust current AI for any tasks more than data parsing/classification/translation and very strict tool usage.
I don't beleive in the full-assistant/clawdbot usage safety and reliability at this time (it might be good enough but the end of the year, but then the SWE bench should be at 100%).