⚡️ Workflow1111 rebuilds the AUTOMATIC1111 feature set on a single gr.Workflow canvas
Eleven media pipelines across 73 nodes, running without a GPU of its own. 22 of 36 operator nodes run in-process with no network call, every output node becomes a REST endpoint, and with mcp_server=True each one is an MCP tool.
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Eleven media pipelines across 73 nodes, running without a GPU of its own. 22 of 36 operator nodes run in-process with no network call, every output node becomes a REST endpoint, and with mcp_server=True each one is an MCP tool.
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huggingface.co
Rebuilding AUTOMATIC1111 with Gradio Workflow
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
⚡️ Environment.ProcessorCount reports process limits, not host cores, since .NET 6
Andrew Lock's platform-specific workarounds (Windows GetActiveProcessorCount, macOS sysctlbyname, Linux /sys/devices/system/cpu/online) recover the actual host processor count.
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Andrew Lock's platform-specific workarounds (Windows GetActiveProcessorCount, macOS sysctlbyname, Linux /sys/devices/system/cpu/online) recover the actual host processor count.
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Andrew Lock | .NET Escapades
Finding the total number of processors on a machine with .NET
In this post I show how to find the total number of logical CPUs on a host (not just those available to a process); something that isn't exposed in modern .NET
⚡️ Rider and ReSharper 2026.2.2 add an AI Agent Setup widget and sharper coding-agent hooks
Rider/ReSharper 2026.2.2 ships a status-bar widget for configuring MCP tools, skills and hooks, sharper inspection/reformat hook feedback for coding agents, and TUnit coverage support in dotCover.
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Rider/ReSharper 2026.2.2 ships a status-bar widget for configuring MCP tools, skills and hooks, sharper inspection/reformat hook feedback for coding agents, and TUnit coverage support in dotCover.
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The JetBrains Blog
Rider and ReSharper 2026.2.2 Are Out! - The JetBrains Blog
We’ve released version 2026.2.2 of ReSharper, Rider, and .NET tools. You can install this update from inside the tools themselves, through the Toolbox App, or on our website. Here’s what’s new in t
⚡️ Microsoft's live series builds a production AI agent in C# from scratch
A four-part live series shows the Microsoft Agent Framework harness in C#: tool calls, approval policies, file sandboxing, shell execution and OpenTelemetry tracing, with code in the MafClaw repo.
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A four-part live series shows the Microsoft Agent Framework harness in C#: tool calls, approval policies, file sandboxing, shell execution and OpenTelemetry tracing, with code in the MafClaw repo.
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⚡️ Azure Container Apps Sandboxes: an isolated microVM for an agent in seconds
Hardware-isolated microVMs with sub-second startup now run over a million agent sandboxes a day across Microsoft products, with KPMG running 30,000+ concurrent for tax work.
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Hardware-isolated microVMs with sub-second startup now run over a million agent sandboxes a day across Microsoft products, with KPMG running 30,000+ concurrent for tax work.
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Microsoft News
Designing agent-first platforms: What changes when agents do the work
Learn how you can design your platform for software that acts using Microsoft Foundry and Azure Container Apps Sandboxes.
⚡️ Transformers can now load llama.cpp GGUF quants directly via from_pretrained
Hugging Face added native GGUF support for Qwen3.5 on Apple Silicon using ggml's Metal kernels, matching llama.cpp throughput while staying inside the regular Transformers API.
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Hugging Face added native GGUF support for Qwen3.5 on Apple Silicon using ggml's Metal kernels, matching llama.cpp throughput while staying inside the regular Transformers API.
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huggingface.co
Transformers now runs llama.cpp quants
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
⚡️ AG-UI Protocol gets an official .NET SDK built on Microsoft.Extensions.AI
Microsoft shipped an official .NET SDK for the AG-UI agent-to-UI streaming protocol, built on IChatClient, interoperable with the existing TypeScript and Python SDKs.
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Microsoft shipped an official .NET SDK for the AG-UI agent-to-UI streaming protocol, built on IChatClient, interoperable with the existing TypeScript and Python SDKs.
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⚡️ GPT-6 Astra, Sol and Luna land in Microsoft Foundry, starting at $0.10 per million tokens
Three GPT-6 tiers for reasoning, general agent work, and high-volume routine tasks, priced $0.10-$75 per million tokens depending on model and direction, live across 28 regions.
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Three GPT-6 tiers for reasoning, general agent work, and high-volume routine tasks, priced $0.10-$75 per million tokens depending on model and direction, live across 28 regions.
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Microsoft News
GPT-6 Astra, Sol, and Luna: For production agents in Microsoft Foundry
Explore GPT-6 Astra, Sol, and GPT-6 Luna in Microsoft Foundry, with scalable model options for production AI agents, complex workflows, and high-volume tasks.
⚡️ Shopify compresses agent failures into model weights, cutting inference cost 96%
A continual learning loop combining SFT, GRPO and prompt compression on PyTorch and vLLM let Shopify match frontier-model quality at a fraction of the cost.
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A continual learning loop combining SFT, GRPO and prompt compression on PyTorch and vLLM let Shopify match frontier-model quality at a fraction of the cost.
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⚡️ F# Weekly #40 is out: Blazor AI components for agent chat UIs
Sergey Tihon's F# Weekly #40 is out. The highlight: experimental Blazor AI components in .NET 11 RC1 that turn an agent chat with streaming, tool calls and approvals into a single ChatPage component.
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Sergey Tihon's F# Weekly #40 is out. The highlight: experimental Blazor AI components in .NET 11 RC1 that turn an agent chat with streaming, tool calls and approvals into a single ChatPage component.
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Sergey Tihon's Blog
F# Weekly #40, 2026 – Agentic .NET UI and FSharp.CloudEdge
Welcome to F# Weekly, A roundup of F# content from this past week: Microsoft New Build Agentic UI with the new Blazor AI components Aspire 13.6: Your dashboard gets memory | Aspire Blog Bringing ri…
⚡️ Mark Seemann: LLMs speed up writing code, not how fast you actually learn
Seemann argues LLMs don't shorten the real bottleneck in learning programming -- how fast a human absorbs concepts -- and suggests asking LLMs only falsifiable, verifiable questions.
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Seemann argues LLMs don't shorten the real bottleneck in learning programming -- how fast a human absorbs concepts -- and suggests asking LLMs only falsifiable, verifiable questions.
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ploeh blog
On learning programming in an age of LLMs
Open answers to a reader's letter.