In the next tutorial, the author plans to demonstrate how to use Graphlit to build a RAG copilot and compare its performance with the models tested in this article. The author also highlights the importance of considering the costs associated with each model when selecting one for your own chatbot or copilot, with the newer GPT-4 Turbo 128K model being significantly more expensive than the GPT-3.5 Turbo 16K model.
Key takeaways:
- The article compares several Retrieval Augmented Generation (RAG) based chatbots and copilots, including OpenAI Assistant with GPT-4 Turbo 128K and GPT-3.5 Turbo 16K models, Anthropic Claude 2.1, Perplexity, OpenGPTs with GPT-3.5 Turbo, and Chatbase with GPT-3.5 Turbo.
- Each model has its strengths and weaknesses, and the cost associated with each model should be considered when selecting one for your own chatbot or copilot.
- OpenAI Assistant (GPT-4 Turbo 1106) and Claude 2.1 performed best in the comparison, especially when summarizing the episode transcript.
- Despite the advancements in Large Language Models (LLMs), there is still configuration and tuning needed to get the best results out of any RAG solution.