Thanks for sharing that. What I find interesting here is that the summary is essentially all the ideas I already had from reading HN and trying out ChatGPT twi

Thanks for sharing that. What I find interesting here is that the summary is essentially all the ideas I already had from reading HN and trying out ChatGPT twice. i.e. nothing new (new compared someone casually following the last few month's AI news). This seems similar to peoples' accounts of getting ChatGPT to generate boilerplate code for them. Such a summary may useful to people who're not following news regularly. Wolfram's article might provide useful detail, but I can't tell from reading the summary if it's worth me reading the article. So how is any of this useful (the summarisation, or Wolfram's article?) Assuming Wolfram is far ahead of the curve, did GPT miss the depth and nuance, because it's only been trained on data that ends at 2021? Is Wolfram too subtle in his thinking that it's impossible to summaries effectively? Or are both his article and the summary just different flavours of "now"? Are my expectations of AI power & creativity, and my expectations for constant change too much? Are we seeing AI's current limits, or its eventual limits?