Tag: LLM inference
Transformer Efficiency Tricks: KV Caching and Continuous Batching in LLM Serving
KV caching and continuous batching are essential for efficient LLM serving. They reduce compute by 90% and boost throughput 3.8x, making long-context responses feasible. Without them, deploying LLMs at scale is prohibitively expensive.
- Mar 22, 2026
- Collin Pace
- 8
- Permalink
Confidential Computing for Privacy-Preserving LLM Inference: How Secure AI Works Today
Confidential computing enables secure LLM inference by protecting data and model weights inside hardware-secured enclaves. Learn how AWS, Azure, and Google implement it, the real-world trade-offs, and why regulated industries are adopting it now.
- Jan 21, 2026
- Collin Pace
- 8
- Permalink