GitHub Copilot 🤖 The future of software development?
click here, Sign up for the early beta. GitHub and OpenAI have launched a technical preview of a new AI tool called Copilot, which lives inside the Visual Studio Code editor (as an extension) and autocompletes code snippets. It works best with Python, JavaScript, TypeScript, Ruby, and Go, according to a blog post from GitHub CEO Nat Friedman.
Some might say this is an evolution of pair programming, in which two coders work on the same project to catch each other's mistakes and accelerate the development process. One of those coders is virtual with Copilot.
Copilot is based on the OpenAI Codex algorithm, which OpenAI CTO Greg Brockman describes as a descendant of GPT-3. OpenAI Codex generates code, whereas GPT-3 generates English. Later this summer, OpenAI plans to release a version of Codex via its API, allowing developers to create their apps using the technology. The codex was trained using terabytes of publicly available code from GitHub, as well as English language examples.
GPT-3 is OpenAI's flagship language-generation algorithm, capable of producing text that is sometimes indistinguishable from human writing. Its size of 175 billion parameters, or adjustable knobs that allow the algorithm to connect relationships between letters, words, phrases, and sentences, allows it to write so convincingly.
While the site's testimonials laud the productivity gains provided by Copilot, GitHub indicates that not all of the code used was tested for bugs, insecure practises, or personal data. The company has implemented a few filters to prevent Copilot from generating offensive language, but it may not be perfect.
“Due to the pre-release nature of the underlying technology, GitHub Copilot may sometimes produce undesired outputs, including biased, discriminatory, abusive, or offensive outputs,” Copilot’s website says.
Given the criticisms levelled at GPT-3's bias and abusive language patterns, it appears that OpenAI has not found a way to prevent algorithms from inheriting the worst elements of their training data.
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