Summary
In this chapter, we covered a quick introduction to GenAI and LLMs. You learned how LLMs such as GPT work and some of their capabilities and limitations. A key takeaway is that while powerful, LLMs have weaknesses – such as the potential for false information and lack of reasoning – that require mitigation techniques. We discussed RAG as one method to overcome some LLM limitations.
These lessons provide useful background on how to approach LLMs practically while being aware of their risks. At the same time, you learned the importance of techniques such as RAG to address LLMs’ potential downsides.
With this introductory foundation in place, we are now ready to dive into the next chapter where we will explore the LlamaIndex ecosystem. LlamaIndex offers an effective RAG framework to augment LLMs with indexed data for more accurate, logical outputs. Learning to leverage LlamaIndex tools will be the natural next step to harness the power of LLMs in a proficient...
