In my experience, Claude 2 is marvellously good at sucking in massive documents and accurately generating responses to questions. I gave it the entire Georgia i

In my experience, Claude 2 is marvellously good at sucking in massive documents and accurately generating responses to questions. I gave it the entire Georgia indictment (minus a few pages of crap at the start that was irrelevant to reduce token count) and it wrote a NYTimes article based on the indictment that could be favourably compared to the actual NYTimes piece summarizing the same. There were no factual errors in its output. I imagine OpenAI is not far behind in expanding the context window of its models. The LLM companies have access to the same techniques and - in my estimation - are just choosing to focus on one aspect or another to address different market needs. For instance, Claude 2 clearly focuses on maximum context window size at the cost of speedy inference and, presumably, inference cost. By contrast, OpenAI seems to be focused on speed and low cost (GPT-3.5) and accuracy (GPT-4) rather than maximum token length.