I mean that an Ai could easily pass it with little issues (a smart model like GPT 5.5) if they are given a single tool, for example their main tool which is a coding playground, no internet no nothing. An LLM isn’t quite capable of thinking like we do by going step by step simulating something in detail with just their brains, and like we use notes to extend our memory via tools they extend their limited (but advanced don’t confuse lack of tools with lack of intelligence) thinking via tools mainly coding like they do for arithmetic. So to prove that I am right or wrong you can describe ARC AGI 3 levels and problem without hinting at solutions and let it think through it and how would it approach it while being allowed to code. When AI asked ChatGPT it perfectly described how it would code a smaller machine to use Monte-Carlo Tree search (for people unfamiliar it’s the major algorithm used in chess engines) to find good moves. It was in no way a perfect experiment. If anyone wants to check it with greater accuracy just take a model and make it go code a smaller machine optimally limit it as for it to not make just another smaller neural network that can just solve it by itself with near 0 input, and then run it whilst allowing the AI to use its code to support itself through the test. The only criticism could be that their use of tools and ours aren’t the same which I partially agree with but only in the contexts of us with stone tools and them with coding but that would be just a wrong context, but I am open to discussion. submitted by /u/Worldly_Beginning647
Originally posted by u/Worldly_Beginning647 on r/ArtificialInteligence