Gary Marcus challenges GPT-6 Astra AGI claims: without continual learning it's still jagged intelligence
GaryMarcus · x · 2026-09-04
- Gary Marcus, quoting Michal Ford, weighs in on OpenAI's new GPT-6 Astra: reports suggest a genuine advance, but calling it AGI is premature.
- Key argument: even a system that passes Demis Hassabis's new "Turing test" (independently rediscovering general relativity) lacks human-level continual "on the job" learning, making it jagged intelligence — it could discover relativity yet not automate Einstein's patent-office job.
- He argues the lack of continual learning partly explains why AI impact on white-collar work remains limited beyond entry level.
- Marcus also sees vindication: OpenAI explicitly builds and manipulates symbolic world models, supporting his decade-long neurosymbolic push — but robustness of that capability remains the open question, and ARC-AGI success is not proof of AGI.
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