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 | 2,981 | 786 | 222 | +25% |
| RAG | 12 | 2,503 | 269 | 80 | +39% |
| LLM | 10 | 4,019 | 457 | 163 | -12% |
| AI Model Fine-tuning | 5 | 992 | 168 | 90 | -5% |
| Serverless | 5 | 530 | 137 | 77 | +10% |
| Developer Experience | 2 | 354 | 162 | 97 | -5% |
| Data Pipeline | 1 | 690 | 197 | 79 | +34% |
| Vector Search | 1 | 2,337 | 296 | 106 | +34% |
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