Claude 2 is very impressive with its 100k token input compared to GPT's 4 32k and its 5x cheaper API cost. It also can take in 50mb of data. Does anyone know how it works when it takes in data files? You can type in prompt text of 100k tokens but if you input a file, you can put in an entire book. When you input a file, is it making summaries of sections/chapters then deleting the original data and answering your questions from these summaries (this would be less detailed and prone to halucination), or is it interpreting all of the data at the same time (same performance if you input a small text into a prompt), or is it making summaries and keeping acess to the orignal paper for reference (like how vector index work)?

How many new scientific papers could LLama read, compare and draw conclusions from, analyzing the new information from the papers with the capabilities developed through its training by Llama? I see in the example on the website k=3 for a simple vector store. How many more could it reasonably do to be able to compare across?

Hello everyone. I am trying to follow the basic tutorial to implement a vector store index to a pdf (Lyft's 2021 10k), and I am getting an error. It is only a few lines of code and I followed the tutorial as closely as possible and am not sure why it gets this Retry Error when I run the line index = VectorStoreIndex.from_documents(documents). If anyone has any ideas please reach out!