GitHub Copilot, every mention

10 scenes (2023), the whole family · ← back to GitHub Copilot

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Verbatim, from the transcripts: the passages where GitHub Copilot comes up

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▶ 15:26 Yimei Fan Um, I want everyone walk away and thinking this is not GitHub co-pilot. 2 times in the scene

▶ 2:14 Eiso Kant And we had a lot of the things running things that today that look like copilot where you could, you know, get code suggestions for based on natural language instructions.
▶ 13:49 Eiso Kant But in terms of what we're delivering to the end user, we're starting with a direct competitor to get up Copilot X.

▶ 40:26 Sharon Zhou It's a very hard thing to be able to deploy these models quickly because it's a new piece of technology, but I will say all of the customers who do deploy fast, uh, essentially will reap the benefits of it because even if you launch…

▶ 4:43 Aravind Srinivas And, uh, GitHub Copilot
▶ 6:15 Aravind Srinivas The biggest hit at the time was GitHub copilot and Dolly two. 2 times in the scene

▶ 1:19 Mathew Lodge Uh, so if we think about generative AI, everyone's heard of ChatGPT and Copilot for the most part, which are large language model based approaches. 4 times in the scene
▶ 27:56 Matt Turck And how do people perceive the fact that it's, uh, fully autonomous, like versus again, uh, you know, copilot, uh, which, uh, as the name indicates, has more of that copilot, uh, kind of, uh, 2 times in the scene
▶ 34:26 Mathew Lodge And, and so, and that's, that's essentially what people are talking about with prompt engineering, because what, what Copilot is doing is basically doing, it's doing a lot of behind the scenes, doing a lot of work on the prompt to try and…

▶ 12:07 Gideon Mann You know, so, so far the most, um, widely deployed application of the large language models is probably Copilot. 6 times in the scene

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