Source URL: https://cloud.google.com/blog/products/ai-machine-learning/gemini-models-on-github-copilot/
Source: Cloud Blog
Title: Gemini models are coming to GitHub Copilot
Feedly Summary: Today, we’re announcing that GitHub will make Gemini models – starting with Gemini 1.5 Pro – available to developers on its platform for the first time through a new partnership with Google Cloud. Developers value flexibility and control in choosing the best model suited to their needs — and this partnership shows that the next phase of AI code generation will not only be defined by multi-model functionality, but also by multi-model choice.
In the coming weeks, developers using GitHub Copilot will be able to use Gemini 1.5 Pro, which excels in common developer use cases such as code generation, analysis, and optimization.Gemini 1.5 Pro is natively multimodal and features a long context window of up to two million tokens — the longest of any large-scale foundation model — so developers can process more than 100,000 lines of code, suggest helpful modifications, and explain how different parts of the code work.
Developers will soon be able to select Gemini 1.5 Pro in GitHub Copilot’s new model picker to assist in coding related use cases.
Developers will be able to select Gemini 1.5 Pro during conversations with GitHub Copilot Chat on github.com, Visual Studio Code, and with Copilot extensions for Visual Studio in the coming weeks.
Gemini models support developer experiences across many of the most popular platforms and environments today — via the Gemini API, Google AI Studio and Vertex AI, or through assistance directly in Google Cloud, Workspace, Android Studio, Firebase and Colab. In addition, Google’s own code-assistance tool, Gemini Code Assist, helps developers complete code as they write across popular integrated development environments (IDE) like Visual Studio Code and JetBrains IDEs (like IntelliJ, PyCharm, GoLand, WebStorm, and more).
Read more about our new partnership with GitHub here.
AI Summary and Description: Yes
Summary: GitHub has partnered with Google Cloud to introduce Gemini models, starting with Gemini 1.5 Pro, to enhance AI code generation capabilities through GitHub Copilot. This development provides developers with a multimodal AI that excels in code generation and supports extensive code analysis, redefining AI-assisted coding.
Detailed Description: The announcement highlights a significant partnership between GitHub and Google Cloud aimed at enhancing the AI coding experience through advanced models. Key points include:
– **Introduction of Gemini Models**: GitHub will debut Gemini models, specifically Gemini 1.5 Pro, on its platform. This model is designed to improve AI-assisted coding processes.
– **Multi-Model Functionality**: The partnership emphasizes flexibility, allowing developers to choose from multiple models tailored to various coding needs. This is a shift toward providing more choices in AI tools.
– **Capacities of Gemini 1.5 Pro**:
– It supports common use cases such as code generation, analysis, and optimization.
– The model is capable of handling richly informative tasks with a very long context window, accommodating up to two million tokens. This length surpasses that of any existing large-scale foundation model.
– It enables developers to analyze extensive codebases, offering helpful suggestions and elucidating the roles of different code components.
– **User Experience Enhancements**:
– Developers using GitHub Copilot will have access to the new model picker for easy selection of the Gemini 1.5 Pro model.
– It will be available in various environments, including GitHub Copilot Chat and popular IDEs such as Visual Studio Code.
– **Integration with Google Tools**: The Gemini models enhance experiences within multiple platforms, including Google Cloud services, Workspace, Android Studio, Firebase, and Colab, ensuring compatibility and superior performance across various environments.
The introduction of Gemini models marks a pivotal advancement in AI-enabled development, enabling a more nuanced and powerful coding assistant for developers, thus significantly impacting the landscape of AI in software development and infrastructure security.