The problem I've seen is that, maybe like the author has been writing, it's making sh*t up. That's not untrue, sometimes I didn't give it all dependent classes and it tried to think sometimes correctly, sometimes incorrectly what those were (such as method signatures, instance members, etc.) I wish it would have asked me some details rather than trying to figure things out. The guys at OpenAI have still a lot to do, but the current status is very impressive
it doesn't understand anything, it doesn't make deductions
it's a probability model, and I understand how it's implemented perfectly well, thank you
The point being, you can choose to laden the word “understand” with the meaning of human-like thinking, in which case humans will always be superior by definition. Or you can choose a “many ways to Rome” definition of understanding that is purely focused on results.
Large language models understand language in their own way. Currently their results are inferior to humans’ but one day the results may be superior.
This is data at a scale OpenAI did not have access to before.
presumably they've already fed it all the code in the world (including a load they probably aren't licensed to)