cover of episode Need More Relevant LLM Responses? Address These Retrieval Augmented Generation Challenges

Need More Relevant LLM Responses? Address These Retrieval Augmented Generation Challenges

2024/1/5
logo of podcast Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

Shownotes Transcript

This story was originally published on HackerNoon at: https://hackernoon.com/need-more-relevant-llm-responses-address-these-retrieval-augmented-generation-challenges-part-1). we look at how suboptimal embedding models, inefficient chunking strategies and a lack of metadata filtering can make it hard to get relevant responses from you Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning). You can also check exclusive content about #retrieval-augmented-generation), #vector-search), #vector-database), #llms), #embedding-models), #ada-v2), #jina-v2), #good-company), and more.

        This story was written by: [@datastax](https://hackernoon.com/u/datastax)). Learn more about this writer by checking [@datastax's](https://hackernoon.com/about/datastax)) about page,
        and for more stories, please visit [hackernoon.com](https://hackernoon.com)).
        
            
            
            we look at how suboptimal embedding models, inefficient chunking strategies and a lack of metadata filtering can make it hard to get relevant responses from your LLM. Here’s how to surmount these challenges.