Polymathic AI's Mission to Boost Scientific Discoveries
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Exploring Pre-Trained Models and Computational Costs in Scientific AI
This chapter explores the use of pre-trained or foundation models in scientific research, emphasizing the need for AI models that can handle diverse data sets across various scientific fields. It discusses the importance of understanding numbers as numerical entities and addresses concerns about computational costs through collaboration with the Simon's Foundation.
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