Artificial General Ideas
The abstract reasoning corpus (ARC) challenge by Francois Chollet has gained renewed attention due to the 1M prize announcement. This challenge is interesting to me because the idea of “abstraction” as “synthesizing cognitive programs” is something my team has worked on and published, even before ARC was popularized. Because of this background, I think I have some insights about ARC that might be missed in a casual examination.
Let’s start by looking at Figure 1 of our paper (https://www.science.org/doi/10.1126/scirobotics.aav3150). You can see that ARC’s premise is the same — (A) from input-output image examples, infer the abstract concept that is conveyed. The concept can then be applied to a new image to create an answer image (B). Our setup went one step further, on being able to transfer this concept to real-images (C) and even being able to execute that concept on a robot (D).
We called this conceptual world “Tabletop world” (TW). More examples of concepts from the tabletop world are shown below, along with an induced program to solve a concept.
