Large language models typically answer questions based on their training data, which is static and has a knowledge cutoff. To overcome this limitation, techniques like retrieval-augmented generation (RAG) are employed, allowing AI models to access and incorporate real-time information before generating a response. This approach enhances the accuracy and relevance of AI-generated answers by enabling them to consult external knowledge sources, similar to how WebGPT and Microsoft Bing integrate search capabilities. AI
IMPACT Enables AI models to provide more accurate and up-to-date answers by accessing external information.
RANK_REASON The item discusses a technique for improving LLM responses rather than a new model release or product launch.
Read on Medium — fine-tuning tag →
- Google DeepMind
- GPT-3
- Microsoft
- Microsoft Bing
- OpenAI
- Palm
- retrieval-augmented generation
- WebGPT: Browser-assisted question-answering with human feedback
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