Person
AI researcher, creator of the Keras deep-learning library, and co-founder of the ARC Prize benchmark for measuring machine intelligence.
Google DeepMind's Gemini 4 Argon scored 97.5% on ARC-AGI-3 at a $4,800 run cost in ARC Prize testing, second to GPT-6 Astra's 99.9%. The score depends on vendor-specific harness features, so it says less about a team's own workload than the headline implies.
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Artificial Analysis scores the same model level with its predecessor, and OpenAI charges two and a half times as much per token, so the ranking you inherit is a claim about a test mix that is not yours.
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Greg Brockman told the GPT-6 Astra launch that the AGI era had begun. The benchmark behind the claim returns a different score depending on whose testing software runs it, and the researcher who built it says it does not prove AGI.
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Anthropic and OpenAI have promised outside evaluators permanent, employee-level access to their systems. Neither has published the terms, and the first volunteer is mid-acquisition by a would-be anchor investor in Anthropic's IPO.
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ARC Prize ran GPT-6 Astra under two scaffolds and published both, 62.7% through its own minimal interface and 99.9% through OpenAI's Provider Adapter, which cost less. An eval that leaves the harness loose is scoring plumbing.
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Mithil Vakde's from-scratch transformer landed one point behind TRM on the public eval. His own ablations put 20 of those 44 points on two representation choices rather than on any amount of compute.
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