86. RAG: Giving Language Models Long-Term Memory
📰 Dev.to · Akhilesh
Learn how RAG gives language models long-term memory, enabling them to recall information from a large database of text, making them more knowledgeable and accurate
Action Steps
- Build a RAG pipeline using a large language model and a retrieval database
- Configure the retrieval database to store relevant text information
- Train the language model to use the retrieval database to recall information
- Test the RAG model on a variety of tasks to evaluate its performance
- Compare the results with a baseline language model without RAG
Who Needs to Know This
NLP engineers and researchers can benefit from this knowledge to improve the performance of their language models, while product managers can use it to design more effective chatbots and virtual assistants
Key Insight
💡 RAG enables language models to recall information from a large database of text, making them more knowledgeable and accurate
Share This
🤖 RAG gives language models long-term memory! 📚 Learn how to build a RAG pipeline and improve your language model's performance #RAG #LanguageModels #NLP
Key Takeaways
Learn how RAG gives language models long-term memory, enabling them to recall information from a large database of text, making them more knowledgeable and accurate
Full Article
Large language models know a lot. They do not know everything. They were trained on internet text up...
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