Context: ARC Prize 2024 just wrapped up yesterday. ARC Prize's goal is to be a north star towards AGI. The two major categories of this year's progress seem to fall into "program synthesis" and "test-time fine tuning". Both of these techniques are adopted by DeepMind's impressive AlphaProof system [1]. And I'm personally excited to finally see actual code implementation of these ideas [2]!We still have a long way to go for the grand prize -- we'll be back next year. Also got some new stuff in the works for 2025.
Watch for the official ARC Prize 2024 paper coming Dec 6. We're going to be overviewing all the new AI reasoning code and approaches open sourced via the competition [3].
[1] https://deepmind.google/discover/blog/ai-solves-imo-problems...
[2] https://github.com/ekinakyurek/marc
[3] https://x.com/arcprize
aithrowawaycomm|1 year ago
The point of the contest is to measure intelligence in general-purpose AI systems: it does not seem in the spirit of the contest that this AI would completely fail if the test was presented on a hexagonal grid.
0x1064|1 year ago
razodactyl|1 year ago
The real pressure is the private hold-out set and the variations that can be added to counter this aspect.
A true AGI would be able to solve anything thrown at it which is where the authors are trying to lead AI engineering towards since LLMs have pretty much taken over.
If it starts getting too easy, they just reconsider and add harder problems.
It's like how we don't talk about the Turing Test anymore as it's no longer the best metric to determine real intelligence.
The authors are signalling to the industry that new ideas are needed and the monetary aspect is to show how serious they are about it.
It's good because as per above we have research being thrown at it which means we can iterate until we perhaps find another breakthrough.
benchmarkist|1 year ago