Retrieval-Augmented Generation With Claude Sonnet 3.5 & Pgvector
Blog post from Tiger Data
The AI chatbot race initiated by OpenAI with the release of ChatGPT is seeing new competitors like Gemini, Cohere, and many others. Anthropic, a prominent AI research company dedicated to developing safe and ethical AI systems, is making waves in the field with its Claude family of large language models (LLMs). The new Claude launch is a notable upgrade from its predecessor and claims it can surpass OpenAI's GPT-4o model on key benchmarks like GPQA (Graduate-Level Google-Proof Q&A), multilingual math (MGSM), and more. In this article, we discussed Claude Sonnet 3.5, its strengths and usefulness, and compared it to other models in the Claude family. We also used Sonnet 3.5 and pgvector to build a retrieval-augmented generation (RAG) application.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 45 | 3,721 | 295 | 94 | +59% |
| RAG | 32 | 1,977 | 263 | 84 | -21% |
| LLM | 8 | 4,126 | 494 | 151 | +3% |
| Kubernetes | 2 | 1,448 | 201 | 90 | +5% |
| AI Agents | 1 | 776 | 115 | 53 | +109% |
| AI Coding Assistant | 1 | 706 | 110 | 47 | +46% |
| AI Model Fine-tuning | 1 | 691 | 164 | 77 | -30% |
| Real-time | 1 | 4,436 | 999 | 233 | +49% |
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