I've spent a couple of hours playing with ChatGPT since it was released and I am convinced people are not freaking out about it enough. It is well beyond merely retrieving compressed knowledge; I see a lot of capability for synthesis and what I can only call 'understanding'. I think a lot of people are getting tripped up by the fact it's trained to be very conservative in terms of what topics it will discuss. It's ea…
I’m still confused by just how good its responses and writing style are. I understand that it was trained on a large data set, but I feel like some training samples must have been weighted more heavily than others. Did the training data incorporate how popular (e.g. likes or upvotes) each sample was as a proxy for quality? Or can you achieve this performance just by looking at averages on a large enough data set?
See also https://en.wikipedia.org/wiki/Attention_schema_theory (unrelated to the notion of "attention" used in ML)