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This work develops a conception of understanding fit for polyphonic AI that centres on sound circuitry that is reliably and correctly recruited and in control of outputs, and can do the work of guiding trust in AI.
TaxiGPT, a transformer trained on random walks through Manhattan whose failures have been interpreted as evidence of an incoherent internal map, is demonstrated, through mechanistic analysis and causal interventions, that the model represents intersections and streets, tracks its position, and uses a goal compass to na...
The resulting framework explains both the appeal and the limits of compressionist accounts of understanding while shedding light on the inscrutability of AI systems.
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