Training LLMs for Software Development

Reading Google's outline of DIDACT (Dynamic Integrated Developer ACTivity), left me am both exhilarated and intrigued. The whole idea of training machine learning (ML) models with data from the software development process, rather than just the final code, is downright ingenious and novel. It's one of those things that look so obvious in hindsight.

The fact that this study was conducted in a world-class software engineering environment like Google's, affords the unique opportunity to train a model with real-world, practical scenarios, and high-quality, high-impact data.

What struck me most about DIDACT is how it doesn't learn in isolation - it learns from the collective discourse of developers, code reviewers, software architects, and development tools.

The initial results are indeed promising, showing a real potential to revolutionize the software development landscape. I am particularly excited by the prospect of DIDACT developing into a general-purpose developer-assistance agent.

Large sequence models for software development activities
Google AI

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