Google is working on a tool that teaches code to write and rewrite itself.
The project was spun up at Alphabet’s moonshot unit, X, and moved into Google Labs this year.
It’s part of a broader push in the field of generative artificial intelligence.
Google is working on a secretive project that uses machine learning to train code to write, fix, and update itself.
This project is part of a broader push by Google into so-called generative artificial intelligence, which uses algorithms to create images, videos, code, and more. It could have profound implications for the company’s future and for developers who write code.
The project, which began life inside Alphabet’s X research unit and was codenamed Pitchfork, moved into Google’s Labs group this summer, according to people familiar with the matter. By moving into Google, it signaled its increased importance to leaders. Google Labs pursues long-term bets, including projects in virtual and augmented reality.
Pitchfork is now part of a new group at Labs named the AI Developer Assistance team run by Olivia Hatalsky, a long-term X employee who worked on Google Glass and several other moonshot projects. Hatalsky, who ran Pitchfork at X, moved to Labs when it migrated this past summer.
Pitchfork was built for “teaching code to write and rewrite itself,” according to internal materials seen by Insider. The tool is designed to learn programming styles and write new code based on those learnings, according to people familiar with it and patents reviewed by Insider.
“The team is working closely with the Research team,” a Google representative said. “They’re working together to explore different use cases to help developers.”
The original goal of Pitchfork was to build a tool that could update Google’s Python programming language codebase to a newer version, a Google representative confirmed. “The idea was: How do we go from one version to the next without hiring all these software engineers?” said a person familiar with the early stages of the project.
The project’s goals shifted over time to a general-purpose system that could still reduce the need for humans to write and update code while maintaining code quality. In job postings for X from late last year, Hatalsky said she was working on a team “building the future of software engineering.”
Employees who spoke with Insider did so on condition of anonymity because they weren’t permitted to speak with the press. Their identities are known to Insider.
The generative-AI boom
Google and other tech companies have made already big strides in generative AI.
GitHub, which is owned by Microsoft, launched a tool called Copilot that suggests snippets of code and functions as developers type. Developers are using Copilot to generate up to 40% of their code, and GitHub expects that number to double within five years, Bloomberg reported earlier this month.
Google is working on several other AI code projects. Its fellow Alphabet subsidiary DeepMind has a system named AlphaCode that uses AI to generate code but is currently focused on competitive coding, or writing programs at a competitive level.
Google is also working on a tool similar to GitHub’s Copilot that uses machine learning to generate code-snippet suggestions as developers type. Google’s senior research director Douglas Eck said at an event in New York earlier this month that the tool had improved coding iteration times by 6% among Google employees who had used it.
Google’s AI Developer Assistance program goes further by training systems to do more of the work themselves. The project is still early, and Google will still need to consider tricky ethical considerations around how these models are trained, such as biases and potential copyright issues.
A class-action lawsuit was filed against GitHub earlier this month, alleging the Copilot tool committed “software piracy on an unprecedented scale” by using AI to reproduce open-source code, The Verge reported.