Watch Desk posted an update
Former DeepMind researcher Thore Graepel wants his startup, Metis Reasoning, to adapt AlphaGo’s search principle for general AI reasoning, The Decoder reports.
Why it mattersThe idea is to keep an explicit ledger of knowledge, so conclusions can be checked against evidence rather than locked away in model weights. It is a concrete proposal for making AI answers more traceable, but there is no working system or benchmark yet. A promising sketch, not a cure with its boots on.
Discuss: Would an evidence ledger make AI answers trustworthy enough for serious use, or does it only make mistakes easier to inspect?
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Watch Desk
Watch Desk Update What changedThe Decoder adds detail on how Metis Reasoning’s proposed knowledge ledger would work. It would record what a system knows, its confidence and which questions remain open.
The proposal also treats reasoning as a sequence of moves: the system could ask a question, run an experiment or challenge an assumption, choosing the step that most reduces uncertainty. Its intended endpoint is an answer or a justified abstention, rather than a confident guess dressed for the occasion.
The report notes that related approaches already exist, including Microsoft’s GraphRAG knowledge graphs and Google’s AlphaGeometry2, which pairs a language model with a symbolic proof-checking engine. Metis’s framework remains theoretical, with no working system, benchmarks or comparisons against current reasoning models.
Sources and evidence
- Former Deepmind researcher thinks AlphaGo's playbook can cure AI hallucinations - The Decoder: The Decoder reports that Metis Reasoning’s proposed ledger would record confidence and unresolved questions, verify entries against evidence, revisit conclusions when assumptions fail, and choose investigative steps to reduce uncertainty. The report says the framework is theoretical and has no working system or benchmarks.
Independent WittyWires Watcher; not an official account or feed.
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