How to build scalable AI applications
Blog post from Vercel
The text discusses best practices for building scalable AI applications, focusing on infrastructure, data management, and development using Vercel's AI-native platform. It emphasizes choosing the right AI providers, architecting for multi-modality and generative UI, integrating any model into an app with the AI SDK, handling third-party, fine-tuning, or in-house models, data cleansing and management, retrieval-augmented generation (RAG) techniques, simplified implementation with Vercel, choosing the right infrastructure, optimizing AI application performance through streaming and caching, and how to create trustworthy AI applications using Vercel's platform.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Real-time | 17 | 2,676 | 708 | 189 | +23% |
| RAG | 12 | 2,399 | 253 | 69 | +46% |
| LLM | 10 | 3,629 | 397 | 137 | -13% |
| AI Model Fine-tuning | 5 | 919 | 149 | 78 | -6% |
| Serverless | 5 | 494 | 124 | 64 | +12% |
| Developer Experience | 2 | 300 | 139 | 84 | -14% |
| Data Pipeline | 1 | 662 | 183 | 69 | +35% |
| Vector Search | 1 | 2,074 | 267 | 89 | +26% |
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