DeepMind's Andrew Trask: LLMs Are Like Libraries Without an Index
iamtrask · x · 2026-07-30
DeepMind researcher Andrew Trask uses a vivid analogy to explain the working mechanism and architectural evolution of LLMs.
- Current Mechanism: He compares models like GPT-3 to a library without an index. To answer a question, the model almost needs to "read" every neuron (like every page of every book) just to output a single token.
- Future Evolution: If all knowledge is ultimately compressible, the model might eventually become "one book." However, if knowledge is inherently distributed, the underlying data structure will ultimately have to change to balance cost and accuracy.
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