Optimal Inference

Optimal inference focuses on efficiently utilizing computational resources to maximize the accuracy of predictions from complex models, particularly large language models (LLMs) and those used in scientific applications like gravitational lensing. Current research emphasizes developing and comparing inference strategies, such as improved search algorithms and hybrid approaches combining physics-based and neural network summaries, to optimize the trade-off between computational cost and performance. These advancements are crucial for deploying LLMs on resource-constrained devices and improving the accuracy and efficiency of scientific data analysis, ultimately leading to more powerful and practical applications.