Github Copilot

Github Copilot – The world’s most widely adopted AI developer coding assistant tool

What is GitHub Copilot?

Working with OpenAI, GitHub and others developed GitHub Copilot, an AI-powered code autocompletion tool. When developers create code, it offers recommendations and completions using state-of-the-art GPT (Generative Pre-trained Transformer) technology.

Official data from GitHub indicates that over a million users are currently using GitHub Copilot, which is amazing!

By providing recommendations for complete lines of code depending on the context of the author’s writing, GitHub Copilot’s primary advantage is its ability to save developers time. This is really useful with big codebases or intricate projects, where manually typing every line of code might take a lot of time.

Several integrated development environments (IDEs) and programming languages are compatible with GitHub Copilot.

With Copilot, developers can put more of their attention toward teamwork and problem solving and less of it toward boilerplate and the routine. Because of this, developers who use Copilot report up to 75% higher work satisfaction than those who do not, and they write code up to 55% more productively without sacrificing quality. All of these factors combine to produce high-quality software more quickly from motivated engineers.

Key Features of GitHub Copilot

The AI coding helper improving developer processes.

Communicate to people about your codebase. When you’re having trouble, ask GitHub Copilot for help, whether you’re trying to find a bug or creating a new feature.

• Boost the security and quality of the code. Authors of code with Copilot have greater confidence in the quality of their work. Additionally, insecure coding practices are instantly prevented by the integrated vulnerability protection system.
• Facilitate more cooperation. The newest person on your squad is Copilot. Ask questions about general programming or very specific topics related to your codebase to receive quick replies, get a feel for the place, get an explanation of an enigmatic regex, or get advice on how to make legacy code better.

Get real-time AI-based recommendations.

GitHub Based on the context and style norms of the project, Copilot converts natural language prompts into code suggestions and recommends code completions as developers type.

Pull requests with stories in them.

GitHub Copilot helps reviewers understand your modifications, maintains track of your work, and makes suggestion suggestions for descriptions.

Do you prefer custom? Adjust a private copilot to the level of precision required by businesses.

Ask for assistance right in your terminal.

Try Copilot in the CLI

Continue to soar with your preferred editor.

Coming soon to GitHub Mobile.

Maximize your use of GitHub Copilot.

• Helpful guidance, facilitated workshops, and instruction.
  • Best practices, insights, and information to support your rapid and effective adoption of GitHub.
  • Investigate GitHub Expert Services
• Get to know the businesses that use GitHub to build.
  • Prominent companies use GitHub for software planning, development, security, and release.
  • Examine client testimonials.
• Follow the most recent developments on GitHub and AI trends.
  • For advice, how-to, technical manuals, best practices, and more, visit the GitHub blog.
  • Go through the blog

GitHub Copilot Pricing plan

Copilot Business Copilot in the coding environment. $19per user/month	Copilot Enterprise Available Feb 2024 $39per user/month
– Code completions – Chat in IDE 1 and Mobile 2 – CLI assistance 3 – Security vulnerability filter – Code referencing – Public code filter – IP indemnity – Enterprise-grade security, safety, and privacy	Copilot is personalized to your organization throughout the software development lifecycle. Requires GitHub Enterprise Cloud. – Everything in Copilot, plus: – Chat personalized to your codebase – Documentation search and summaries – Pull request summaries – Code review skills – Fine-tuned models 4

Copilot Individual For freelancers and developers, code completions, chat, and more. $10per month / $100 per year

GitHub Copilot FAQ

• What distinguishes the GitHub Copilot Individual, GitHub Copilot Enterprise, and GitHub Copilot Business plans from one another?
  • GitHub Copilot offers a number of solutions for businesses as well as one for individual developers. Both code completion and chat support are included in all of the products. License management, policy management, and intellectual property indemnity are the main distinctions between the offers of the business and those of the person.
  • GitHub Copilot Business and GitHub Copilot Enterprise, which will launch in February 2024, are the options available to organizations. The main elements of GitHub Copilot Business are the IDE and CLI for the coding environment. It will also come with GitHub Copilot on GitHub Mobile in early 2024. All of the features of GitHub Copilot Business are included in GitHub Copilot Enterprise, along with an extra degree of customization for businesses and GitHub Copilot integrated into GitHub as a chat interface for developers to discuss their codebase and action buttons across the platform. In addition to providing customers with access to fine-tune custom, private models for code completion, GitHub Copilot Enterprise may index an organization’s codebase to gain a better grasp of their knowledge for more customized suggestions.
  • GitHub Copilot Individual is intended for independent developers, independent contractors, scholars, instructors, and maintainers of open source software. With the exception of organizational license management, policy administration, and IP indemnification, the plan offers every functionality of GitHub Copilot Business.
• Which systems, IDEs, and languages is GitHub Copilot compatible with?
  • Every language that can be found in public repositories has been trained for GitHub Copilot. The amount and variety of training data for each language may have an impact on the caliber of recommendations you obtain. For instance, JavaScript is one of the languages that GitHub Copilot supports the best and is widely represented in public repositories. Less represented languages in public repositories might result in fewer or weaker recommendations.
  • The JetBrains suite of IDEs, Azure Data Studio, Vim, Neovim, Visual Studio Code, and Visual Studio are among the programs that offer an extension for GitHub Copilot. While all of these extensions provide code completion functionality, the chat feature is presently limited to Visual Studio Code and Visual Studio, with a beta version being available for JetBrains IDEs. GitHub CLI provides terminal support for GitHub Copilot as well. GitHub browser and mobile will soon have native integration with GitHub Copilot.
• What kind of data was used to train GitHub Copilot?
  • Microsoft, OpenAI, and GitHub have built generative AI models that underpin GitHub Copilot. Natural language text and source code from publicly accessible sources, such as code in open repositories on GitHub, were used to train it.
• Can I “copy/paste” using GitHub Copilot?
  • No, GitHub Copilot uses probabilistic reasoning to produce ideas.
  • Understanding the inner workings of GitHub Copilot is essential when considering matters pertaining to intellectual property and open source. Though they may not contain any code, the AI models that generate Copilot’s recommendations are trained using publicly available code. They are not “copying and pasting” from any codebase when they produce a proposal.
  • Copilot starts by analyzing the code in your editor, paying particular attention to the lines immediately before and after your cursor as well as information in other files open in your editor, in order to provide a recommendation for code completion. The Copilot model receives this data in order to produce recommendations and create a probabilistic assessment of what is likely to happen next.
  • Copilot develops a Contextual Prompt by integrating two elements: (1) a “context summary” and (2) the question you send to the Copilot conversation interface in your IDE. This allows Copilot to make suggestions from conversation, such as answering a question from your chat prompt. After that, the contextual prompt is passed to Copilot’s model, which uses it to produce suggestions and make a probabilistic estimate of what is likely to happen next.
• What information is used by GitHub to generate a Contextual Prompt?
  • GitHub Copilot Chat combines two elements to form a Contextual Prompt: (1) a “context summary”; and (2) the question you pose to your editor.
  • The GitHub Copilot Chat client, for example, will automatically analyze the context from your active documents in the editor to ascertain what you mean by the word “this” if you submit “what does this method do.” Then, without requiring you to copy and paste code into the chat window, it will automatically build a relevant question to put to the GitHub Copilot Chat model, saving you time and perhaps providing a useful response.
  • The GitHub Copilot Chat client will automatically use pertinent details from your context to build the question, depending on what you ask. The data it makes use of could be:
    • The open code file in your open document
    • The document’s selection (or “code blocks for the current cursor position”)
    • summaries of connected papers that are visible in the workspace or in your editor
    • Details on the warnings, exceptions, messages, and problems in your error list
    • general workspace details, including languages, frameworks, and dependencies
    • portions of linked files in your project, workspace, or repository

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