Secure, private LLMs in your cloud with Anyscale Endpoints
summary
Anyscale shows a deployable LLM stack built on Ray that runs in your AWS account and on Inferentia/Trainium, with optimizations like speculative decoding and continuous batching, autoscaling, model multiplexing and fast S3 model loads. Customers report concrete wins: Samsara halved inference costs, Pinterest cut training costs 40%, Instacart trains 12× faster on 100× more data. A fine‑tuned LLaMA‑2 7B reaches 86% SQL accuracy vs GPT‑4’s 78% at roughly 1/300th the cost, and Private Endpoints keep models and data in your cloud.
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chapters (7)
- 0:00Introduction to Ray
- 2:22Challenges in AI adoption
- 7:46Solving AI infrastructure
- 9:50Anyscale product offerings
- 12:14Optimizing with endpoints
- 15:18Fine-tuning benefits
- 17:39Private endpoints and close
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