UC Berkeley computer scientist Stuart Russell has warned that the AI industry's commitment to scaling large language models could become a $10 trillion wrong turn if the approach cannot deliver the safety guarantees required for powerful AI systems. The claim shifts the debate from whether a single frontier model should be delayed to whether the dominant training recipe can ever make highly capable AI reliably controllable.
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