Hassabis Proposes an 'Einstein Test' for AGI: Can a Model Produce Genuinely Novel Science?

DeepMind CEO Demis Hassabis outlined a test for AGI that goes beyond benchmarks — asking whether a model can produce scientific discoveries equivalent to what Einstein did, work that couldn't have been derived from training data alone.

Demis Hassabis has proposed what he's calling the 'Einstein test' for AGI, and it's a deliberate departure from the benchmark-driven definitions that dominate the industry. As @rohanpaul_ai reported in a viral thread, the test asks whether an AI system can produce genuinely novel scientific contributions — the kind of insights that couldn't have been interpolated or recombined from existing training data.

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