Anyscale

Anyscale is an AI application platform that offers scalable compute for AI and Python. It provides a unified compute backend for machine learning and deep learning platforms, allowing users to improve performance, fault tolerance, scalability, latency, and cost efficiency of large workloads.

Key Features:

1. Ray: The most popular open-source framework for scaling and productionizing AI workloads.

2. Performance: Time to scale up to 1000 nodes in just 60 seconds.

3. Cost-effective: Transition to cheaper spot instances across multiple regions and clouds while minimizing steady-state costs.

4. Elasticity: Scale CPU compute and GPU compute elastically and independently.

5. LLMs (Large Language Models): Train your own LLMs or fine-tune open source models securely with more privacy control using Anyscale Endpoints.

Use Cases:

1. OpenAI uses Ray to train their largest models including ChatGPT

2. Cohere uses Ray as the unified compute backend for their machine learning platform

3. Ant Group deployed Ray Serve on 240k cores during Double 11 online shopping day

4. Samsara scaled training of deep learning models by hundreds of millions of inputs using Ray

Anyscale's powerful features make it easier than ever before to develop, run, deploy, scale AI applications at a fraction of the cost while leveraging recent advances from the open-source community instantaneously across multiple clouds with rapid time-to-market benefits throughout the entire AI lifecycle making it an ideal choice for businesses looking to optimize their workflows efficiently without compromising quality or speed