ARC-AGI-3 is built different, it has dumbfounded almost all regular attempts so far because it's so much harder than anything that came before. It has no rules, it's agentic and has no explicit goals, they need to be discovered.
@tufalabs won the first milestone of @arcprize
> There is no language built into the benchmark, but these guys "put the language back in", because in their view - it's the best way to climb up the notional "abstraction mountain" and effectively use many of the abstractions which have evolved over millions of years of language evolution.
> They built a novel harness "The Duck" around a 27B open weights model (Qwen 3.6) to solve extremely challenging and novel reasoning problems that require abstraction.
> This is the launch video of their winning agentic harness, "The Duck". We have also released an exclusive interview with them on MLST, just dropped.
> The million dollar question is: what will @fchollet think about how they've done it, and is this a step towards AGI?
Our winning solution to the ARC-AGI-3 Milestone 1 is now open-source: the Duck harness, built on Qwen 3.6 27B ๐ฆ๐ฅ
ARC-AGI-3 is interactive with no rules explained, the agent has to figure out the goal itself. We hit 1.21% with our lightweight harness.
Links below ๐