Explore the July edition, featuring prompts, tips, and use cases for GitHub Copilot.
Software developers are most productive when software development is inclusive and accessible. At GitHub, we conduct research in machine learning, design, and infrastructure to make sure everyone can do their best work with the next generation of developer tools and workflows.
This research can take considerable time to reach you, our end users, if it reaches you at all. We rigorously evaluate products for stability, performance, and security. And many experiments don’t meet our success criteria for product release, even when they present a path forward for future innovation.
Although we can’t share everything we do, we’ve launched a collection of demonstrations highlighting our most exciting research projects—and the ideas behind them—with Experiments. We hope these will not only give you insight into our research but inspire you to think audaciously about the future of software development.
For our first demo, we’ve chosen Semantic Code Search. We’ve used machine learning to build semantic representations of code that allow you to use natural language to search for code by intent, rather than just keyword matching. See our blog post for additional detail on how this works.
We’re just getting started, so stay tuned for more examples. If this research excite you as much as they excite us, why not join our team?