Neither Stochastic Parroting nor AGI: LLMs Solve Tasks through Context-Directed Extrapolation from Training Data Priors
LLMs solve tasks not through simple pattern matching but via 'context-directed extrapolation.' This means they use knowledge from their massive training data (priors) and guide that knowledge using specific instructions or examples provided in the prompt. This capability allows them to perform complex reasoning, though current limitations suggest they are better at understanding than true novel application.