See how it's apparently newsworthy that a simple chess engine on the C64 can beat ShitSkibidi. It was fucking obvious, to us. Like that random.randint(0, 10) is much worse at figuring out the sum of 2 and 4 than just calculating 2+4. However, it was not as obvious to the people that don't understand how ML/DL fundamentally works.

Similarly, it's sad to see a lot of projects that have to do with Machine Leaning being essentially killed and made worthless by people just throwing everything at ShitSkibidi instead of generating/collecting training data themselves and training a purpose built model, not text based. I see that in private as well as at work. They want to use "AI" in risk management now. Will that mean they'll use all their historical data on customers, the risks they identified and the final result to build two or more specific models? Most likely, no. They'll just throw all data at the internal ShitSkibidi wrapper, expect the resulting data to be usable at all, and then ask it how they should proceed. And then expect humans to actually fact check everything it returned.