Exactly, self driving for example on paper seems like an easy task to automate, you only need to make a decision for the upcoming 2 seconds, and still sucks at it, because it needs 100% accuracy, 90% is fatal and useless
I write C all day and enjoy every second of it. I assume there are many like myself. There's just nothing new to make noise about, and that's a good thing, other than small quality-of-life improvements in the standard.
While I fully support liking one language, it wouldnt feel right for me to not mention the benefits other languages bring, such as GC for large dev teams of lower skilled devs, languages with builtin unit tests, languages with templating or less bad macros, etc.
This mantra was hammered into us before the collegiate advertising fairs. Kind of a shame that many people forget this applies to all facets of life, not just the student fairs.
it make sense, in order to come up with a base model, you will need a lot of quality training data, tons of compute.
the role of an AI startup is to come up with ideas, thus useful products.
Most of existing products pre-AI, are also front ends to existing operations systems and exiting databases, because creating the whole stack does not make sense.
At least we have state of the art open models that we can use freely