Visual Studio Code 1.112, released March 18, expands Copilot agent autonomy, adds MCP server sandboxing on macOS and Linux, enables in-editor web app debugging, and broadens monorepo support for agent ...
This hands-on PoC shows how I got an open-source model running locally in Visual Studio Code, where the setup worked, where it broke down, and what to watch out for if you want to apply a local model ...
VS Code 1.112 adds native image support for agents, and I used it on three Microsoft AI Foundry leaderboard screenshots to see whether it could turn chart-heavy visuals into a useful developer summary ...
Microsoft's new Azure Skills Plugin bundles curated Azure skills, the Azure MCP Server, and the Foundry MCP Server into a single install that gives AI coding agents both the expertise and execution ...
Microsoft is expanding GitHub Copilot's deepest Visual Studio integration to C++, giving the AI assistant compiler-backed insight into entire C++ codebases so it can refactor and modify projects ...
Quadratic regression is a classical machine learning technique to predict a single numeric value. Quadratic regression is an extension of basic linear regression. Quadratic regression can deal with ...
Microsoft's AI Toolkit extension for VS Code now lets developers scaffold a working MCP server in minutes. Here's what that looks like in practice -- including the parts that don't work, and a simpler ...
VS Code 1.111 Autopilot is not just a no-prompts mode. In testing, it handled a blocking question that still stopped Bypass.
Microsoft recently advanced .NET MAUI to General Availability status, but many developers have complained about half-baked functionality that was shipped too soon. .NET Multi-platform App UI went GA ...
Microsoft has officially begun decommissioning its IntelliCode suite, marking the end of a multi-year effort to provide local, machine-learning-assisted code completions. The move, executed alongside ...
Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...
When using the PyTorch neural network library to create a machine learning prediction model, you must prepare the training data and write code to serve up the data in batches. In situations where the ...
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