ARC as a stepping-stone for AGI? For me, ARC has lost all credibility. Your white paper that introduced it claimed that core knowledge priors are needed to solve it, yet all the systems that have any non-zero performance on ARC so far have made no attempt to learn or implement core knowledge priors. You have claimed at different times and in different forms that ARC is protected against memorisation-based Big Data approaches, but the systems that currently perform best on ARC do it by generating thousands of new training examples for some LLM, the quintessential memorisation-based Big Data approach.

I too, believe that ARC will soon be solved: in the same way that the Winograd Schema Challenge was solved. Someone will finally decide to generate a large enough dataset to fine-tune a big, deep, bad LLM and go to town, and I do mean on the private test set. If ARC was really, really a test of intelligence and therefore protected against Big Data approaches, then it wouldn't need to have a super secret hidden test set. Bongard Problems don't and they still stand undefeated (although the ANN community has sidestepped them in a sense, by generating and solving similar, but not identical, sets of problems, then claiming triumph anyway).

ARC will be solved and we won't learn anything at all from it, except that we still don't know how to test for intelligence, let alone artificial intelligence.

The worst outcome of all this is the collateral damage to the reputation of symbolic program synthesis which you have often name-dropped when trying to steer the efforts of the community towards it (other times calling it "discrete program search" etc). Once some big, compensating, LLM solves ARC, any mention of program synthesis will elicit nothing but sneers. "Program synthesis? Isn't that what Chollet thought would solve ARC? Well, we don't need that, LLMs can solve ARC just fine". Talk about sucking out all the air from the room, indeed.