Docker Desktop 4.37 streamlines AI-driven development with the new AI Catalog integration, command-line management capabilities, upgraded components, and enhanced stability to empower modern developers.
ai/ml
Docker Documentation Gets an AI-Powered Assistant
Learn about the Docker Docs AI, a documentation assistant designed to provide instant, accurate answers directly from Docker docs. Features include language options, answers from multiple topics, as well as contextual and debugging help.
The Strategic Imperative of AI in 2024
We examine the incredible growth of AI and explore its potential power to transform industries and help enterprises accelerate innovation.
“@docker can you help me…”: An Early Look at the Docker Extension for GitHub Copilot
Announcing the Docker extension for GitHub Copilot (@docker), a plugin that extends GitHub Copilot’s technology to assist developers in working with Docker.
Streamline the Development of Real-Time AI Applications with MindsDB Docker Extension
With MindsDB, you can build AI-powered applications easily, even with no AI/ML experience. Follow along to learn how to set up MindsDB in Docker Desktop.
A Quick Guide to Containerizing Llamafile with Docker for AI Applications
Walk through how to use Docker to containerize llamafile, an executable that brings together all the components needed to run an LLM chatbot with a single file.
Creating AI-Enhanced Document Management with the GenAI Stack
We show how to integrate Alfresco, a robust document management system, with the GenAI Stack to open up document analysis, description, and classification possibilities.
A Promising Methodology for Testing GenAI Applications in Java
Testing applications that incorporate AI can be difficult. In this article, we share a promising new methodology for testing GenAI applications in Java.
Better Debugging: How the Signal0ne Docker Extension Uses AI to Simplify Container Troubleshooting
Get started with Signal0ne, a Docker Desktop extension that scans Docker containers’ state and logs in search of problems, analyzes the discovered issues, and outputs insights to help developers debug.