Limitations of Language Models and the Need for Compression

Language models are limited in size and have a fixed number of parameters, forcing them to compress knowledge by storing reusable bits of programs. This compression leads to generalization as the models attempt to express new programs with existing knowledge. However, the intrinsic limitation lies in the model's parametric curve structure, restricting it to local generalization. To achieve broader generalization, a different model, such as discrete program search or program synthesis, is required.

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