The blog post from Replit discusses their efforts in building large language models (LLMs) specifically for code repair, integrating AI deeply into the developer environment. They train models with a mix of source code and related natural languages, aiming to make AI tools more powerful for developers. Replit focuses on code repair as a significant area for AI application, using operational transformations and session events to create a dataset for training. The goal is to fine-tune models that can automatically suggest fixes for common coding errors, leveraging the vast amount of data from LSP diagnostics within Replit [❞].

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