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Scaling Challenges in AI Model Development
This chapter explores the hurdles encountered while scaling a model from millions to billions of parameters, focusing on supercomputer constraints and outdated hardware. It highlights innovative solutions for optimizing resource use and addresses the importance of reproducibility in machine learning experiments, concluding with a commitment to open-source contributions.