GitHub, the online developer platform that allows users to create, store, manage, and share their code, has been on a generative AI (genA) journey since before ChatGPT or Copilot was widely available to the public.
Through an early partnership with Microsoft, the dev platform adopted Copilot two-and-a-half years ago, tweaking it to create its own version — GitHub Copilot.
The genAI-baed conversational chat interface is now used as a tool for both GitHub users and internal employees to assist in code development, as well as an automated help desk tool.
There are people who believe as genAI continues to evolve and can produce more code based solely on user requests, developers will no longer be needed. As Nvidia CEO Jensen Huang last week said, because of AI, “everybody in the world is now a programmer. This is the miracle of artificial intelligence.”
Instead of software development, Huang believes humans should focus on more important skills such as biology, education, manufacturing, or farming, and the language of programming is now the human language.
GitHub
GitHub’s COO Kyle Daigle
Kyle Daigle, who’s worked at GitHub for 11 years, took over as its COO about a year ago. He’s been part of a genAI development strategy that’s focused on discovering how the technology can benefit its roughly 3,000 employees — developers and non-developers alike — and its external developer community of users. So far, genAI is making developers 55% more productive, he said.
Daigle spoke to Computerworld about the various ways genAI has created efficiencies and helps both developers and non-developers. The following are excerpts from that interview:
When did you deploy Copilot. Why? And what has it enabled GitHub to do? “We’ve been on a journey with Copilot for about two and a half years now. We started working on Copilot when we got early access to the OpenAI models through our partnership with Microsoft. Similar to a lot of companies now, the main question was how do we put these LLMs to good use? It took us a little while to figure out the secret sauce that’s now Copilot. Originally, when we were using the models, we thought we were going to be building tools that documented code. You know, you give it your repository and it would spit out what that code did.
“But through experimentation, the idea of Ghost text — the sort of completion model of what Copilot does, where it shows you the entirety of a single message versus a single line — was kind of a big breakthrough for being able to get the most out of a powerful tool. And so, fast forward and now we’ve got more than a million GitHub users using Copilot every day. Our stats show it’s making them 55% more productive, and it’s writing about 60% of code; we expect that to get up to about 80% of code over time in many languages.
We do find it actually makes people more productive, happier and ultimately removes their toil.
“I think most importantly, and…
2024-03-10 03:41:02
Article from www.computerworld.com
