Why you should build your AI Applications with Ray
Blog post from Anyscale
Ray is a versatile platform for building diverse, computationally intensive applications, including data and AI applications and platforms, as well as long running applications like web services. It supports both business logic and model inference seamlessly, allowing developers to build and scale microservices as if they were a single Python application. Many companies have successfully used Ray for various applications, highlighting its flexibility and scalability. Ray also provides tools for testing, deployment, and monitoring, making it an ideal choice for building distributed applications that incorporate machine learning.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Guardrails | 2 | 42 | 37 | 9 | +110% |
| Real-time | 2 | 978 | 304 | 96 | +20% |
| Serverless | 2 | 830 | 110 | 40 | +49% |
| Kubernetes | 1 | 1,158 | 148 | 57 | +13% |
| Observability | 1 | 512 | 137 | 51 | -17% |
| Reinforcement learning | 1 | 3 | 3 | 3 | +50% |
| TPUs | 1 | 4 | 4 | 3 | - |
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