5 ways to immediately improve your AI models
Blog post from Retool
Enterprise AppGen introduces AI-powered app generation that promises to be fast, secure, and production-ready, but deploying AI models like pre-trained large language models (LLMs) requires additional refinement to meet specific business contexts. The text explores several techniques to enhance AI models, such as Retrieval-Augmented Generation (RAG) which combines retrieval models and generation techniques to provide context-specific responses, and fine-tuning, which adapts a model to specific domains by training it on a domain-specific dataset. Prompt engineering is discussed as a crucial skill for crafting effective AI prompts to generate desired outputs. Model switching is mentioned as a method to find the best AI model for a given use case by testing and comparing different models. Multimodality, the ability to generate both text and images, is highlighted as a way to create engaging multimedia content. Retool is presented as a platform that facilitates these enhancements, allowing for easy integration, manipulation, and testing of AI models to improve their performance and applicability.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Model Fine-tuning | 15 | 806 | 111 | 60 | +94% |
| RAG | 9 | 1,081 | 177 | 62 | +40% |
| LLM | 8 | 2,718 | 331 | 130 | +3% |
| Real-time | 1 | 2,305 | 607 | 180 | +15% |
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