Unleash the Power of Local AI with C# and .NET
Are you a C# developer looking to integrate cutting-edge AI without relying on expensive, slow, and privacy-invading cloud APIs? Book 9: Edge AI & Local Inference is the definitive guide to running Large Language Models (LLMs), Computer Vision, and Audio models directly on your user's hardware.
Move beyond Python wrappers. This volume teaches you how to architect high-performance, native .NET solutions using ONNX Runtime, LlamaSharp, and Microsoft.ML. You will learn to build applications that are offline-capable, lightning-fast, and completely private.
What's Inside:
- Local LLM Integration: Run Llama 3, Phi-3, and Mistral locally using quantized models (GGUF/ONNX).
- Offline RAG Systems: Build a private "Chat with your Data" pipeline using local vector databases and embedding models.
- Hardware Acceleration: Optimize inference using CUDA, DirectML, and NPUs directly from C#.
- Real-Time Vision & Audio: Implement YOLOv8 object detection and Whisper transcription with zero latency.
- Professional Architecture: Master asynchronous streaming, memory management for VRAM, and thread-safe UI integration (WPF/WinForms).
Whether you are building a smart IoT gateway, a privacy-focused desktop tool, or a high-throughput local server, this book provides the production-ready code and architectural patterns you need.
Stop paying per token. Start building on the Edge.
Check also the other books in this series
