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Exploring Model Performance at Large Scale
Research effort and compute allocation in the industry is uncertain, especially in terms of model performance at large scales. The exploration of high quality data and curation for models like GPT has not been fully realized. Fine tuning, LHF, and RAG methods are discussed as ways to optimize models for specific tasks. Open AI's consideration of these approaches is a significant development.