The chapter delves into various models and strategies for optimizing natural language programs, breaking down the problem-solving process into distinct steps and utilizing specialized modules for each step. It discusses projects such as Microsoft Fi and Google DeepMind's Alpha Geometry, which combine language models and symbolic deduction engines to solve complex geometry puzzles. Furthermore, it explores the use of neural algorithmic reasoners and cross-attention mechanisms to mimic the communication between human brain functions in problem-solving scenarios.

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