As a helper, GitHub Copilot is supposed to come up with and complete code on its own . Today, GitHub’s AI (artificial intelligence) is still in the testing phase, as it is always error-prone. Over time, however, it should become more effective.


  1. GitHub: what is it?
  2. GitHub Copilot: what is it?
  3. GPT-3: the basis of GitHub Copilot
  4. How to activate GitHub Copilot?
  5. Does the AI ​​work?
  6. What issues remain with GitHub Copilot?
  7. Who can benefit from GitHub’s AI?
  8. In summary: a lot of potential, but a disappointing start

GitHub: what is it?

To fully understand the usefulness and the different functionalities of GitHub Copilot, it is first necessary to take an interest in GitHub. GitHub is a collaborative version control software . The company that edited it is based in the United States and has been owned by Microsoft since 2018. GitHub was designed to allow large teams to work on code, either collaboratively or independently . All the versions are thus saved, and it is possible to combine the modifications at will.

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GitHub Copilot: what is it?

Since 2021, the company has offered GitHub Copilot to certain users. Linked to artificial intelligence, this tool consists of an intelligent assistant designed to help developers create code. It operates primarily on the principle of autocompletion . When a user begins to enter code, GitHub Copilot suggests different proposals to complete it. To do this, GitHub Copilot is inspired by the code already available to the public , which can for example come from different repositories. GitHub’s AI goes much further; it is indeed able to recognize many Internet programming languagessuch as Go, Java, JavaScript, Python, Ruby, and TypeScript. Over time, the artificial intelligence improves, as do its suggestions.

This therefore means that today , GitHub Copilot can and must still evolve . The company itself recognizes that the code offered by the tool is not yet perfect. Furthermore, the success rate of its proposals so far is very clear. Users should therefore assume that the proposed code is not yet fully operational and that some of the proposals cannot even be used. However, Github Copilot can already provide you with useful pointers, or even suggestions that you can actually use.

GPT-3: the basis of GitHub Copilot

GPT-3 is the voice production system that GitHub Copilot relies on. Published in 2020 by OpenAI, it is based on deep learning strategies to complete human texts or write your own texts. For this purpose, the AI ​​uses different algorithms  ; it collects large volumes of data and uses it to create new content that normally differs little from text written by humans.

The rule remains the same: the more you “feed” your AI, the more its results improve. Thus, GPT-3 has already been used to attempt to create code from so-called “learned” structures. Subsequently, Microsoft invested heavily in OpenAI and GPT-3. The knowledge already acquired by this system is now at the service of GitHub Copilot.

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How to activate GitHub Copilot?

As of now, GitHub Copilot is not yet available for free . Only a few hand-picked people can currently test the AI ​​and make suggestions to improve this tool. In the more or less long term, the goal is to transform GitHub Copilot into a real commercial software that can be used by developers for their daily work on new projects. However, no one knows yet when the AI ​​will be ready. During the entire learning and testing phase, only a first preview is available to interested users. Visual Studio Code, Neovim and JetBrains IDEs like PyCharm or IntelliJ IDEA are currently supported.

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Does the AI ​​work?

If the first analyzes are promising, GitHub Copilot does not seem to be ready for a market launch yet. For the moment, its success rate is on the whole not very high, and the quality of its proposals remains clearly perfectible. Most of the time, the code cannot be used yet , because it leads to errors in many cases.

In the future, the commercialization of this solution will depend above all on the learning capabilities of the AI ​​and the quality of the source code made available to it. To date, GitHub Copilot does not hesitate to integrate errors into its basic content, as well as a syntax that is at the very least approximate. Once the learning phase is over, however, his results should improve.

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What issues remain with GitHub Copilot?

We have already mentioned the problems relating to the relevance of the proposals or the perfectibility of the syntax , but some people also warn about the fundamental margin of error of the codes which are currently created using GitHub Copilot or which will be by the following.

As the basis on which the AI ​​acquires its knowledge is often wrong or, at the very least, unverified , the final result too often remains uncertain. If it is specified that all data from AI must be verified, developers are currently unlikely to derive any real benefit for their daily work in the long term. Early testing has often resulted in poor results for GitHub Copilot code.

Some developers are also concerned that using GitHub Copilot will constitute copyright infringement if the AI ​​just takes over entire blocks of code. There are different rules around fair use, but where AI learning activities fit in is controversial, to say the least. This subject is all the more sensitive as GitHub Copilot could eventually be used for commercial purposes. The company guarantees that to date, few source codes have already been taken over without modification, whether in whole or in part. The more AI learning improves, the more this figure should continue to fall.

Who can benefit from GitHub’s AI?

GitHub Copilot is still only a “gadget” whose added value remains limited. However, if AI improves its learning, it could significantly ease the workload for developers. As a first step, it could suggest workarounds and provide appropriate syntax examples by eliminating time-consuming searches among different documents. As a second step, it should eventually be able to add individual blocks of code itself, providing developers with otherwise long lines to write .. While this would make their job easier, some basic web development knowledge would still be required. There will still be a long wait before an AI will be able to write code autonomously.

In summary: a lot of potential, but a disappointing start

GitHub Copilot is an idea that makes sense and in the future could quite naturally be integrated into working with source code. It is indeed quite promising to imagine an intelligent assistant capable of taking care of small tasks and reporting any errors . However, the AI ​​of this project is not there yet. The current test phase is only a first step in this direction; as expected, the margin of error therefore remains high. It is still impossible to give with certainty the date on which GitHub Copilot will be truly made available to all interested persons. However, the testing phase is the first step in this process.


In our digital guide, also find out what the differences between GitLab and GitHub are and which of continuous integration, continuous delivery or continuous deployment really wins out. If you’re looking for a Git tutorial or GitHub alternatives instead , we’ve got you covered as well.

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