《推理工程》：从 CUDA 到 Kubernetes 的生产 AI 指南
Philip Kiely 的 256 页《Inference Engineering》梳理运行时、基础设施与工具三层技术栈，覆盖用例和预算、模型架构、GPU 硬件、CUDA/框架/推理引擎、量化与推测解码、KV cache、并行与解耦、多模态 serving 及生产运维。完整图书介绍、章节路线、作者、FAQ、读者评价和 20 张原图已本地归档。
Inference Engineering
Philip Kiely's 256-page guide maps the runtime, infrastructure, and tooling layers of production AI inference—from use cases and budgets through model architecture, GPU hardware, CUDA/frameworks/engines, quantization, speculative decoding, KV-cache reuse, parallelism, disaggregation, multimodal serving, and production operations. The full landing page, chapter map, author bio, FAQ, reader reactions, and 20 original images are archived locally.
https://www.baseten.co/inference-engineering/
Baseten
Inference Engineering | Baseten Books
Inference Engineering by Philip Kiely is your guide to the hardware, software, techniques, and infrastructure required to run AI models in production.
August 23, 2026 7
