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ARC-AGI is redefining how to measure progress on the path to AGI - focusing on reasoning, generalization, and adaptability instead of memorization or scale.
At NeurIPS 2025, YC's @sdianahu sat down with @arcprize President @GregKamradt to find out why most AI benchmarks fail, how ARC-AGI reveals the limits of today’s models, and why measuring intelligence may be harder than building it.
00:11 — What ARC Prize is and why it exists
00:38 — François Chollet’s definition of AGI
01:48 — What ARC-AGI Actually Tests
02:25 — When LLMs Failed the ARC Benchmark
03:38 — ARC-AGI Becomes the Standard
04:49 — False Positives in AI Progress
06:06 — The Evolution of ARC-AGI
08:55 — Measuring Intelligence beyond just accuracy
10:25 — What happens if a model solves ARC-AGI?
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