Raw LLM Responses

All this stuff where we train a computer to do one job that a human can do as well as a human can do completely ignores that it also costs money to train and run a computer and you can't just train it once and let it go forever. Not only do you have to pay for electricity and internet bandwidth, you need to maintain servers or pay for cloud services and you need expensive employees to make the software, do maintenance, blah blah blah. And since software and hardware and car companies need to make money you need to keep paying for all new stuff and pay people to do the upgrades. You could instead just underpay a bunch of people with the one simple skill you're trying to emulate, but that doesn't get investors excited. At some point you have to ask why we're doing this. I don't believe there's any benefit, even to companies trying to save money on wages. If it isn't cheaper the only selling point is that you don't have to interact with a person which is only a selling point for people with social anxiety. I really think that the only reason for the investor and public interest in it is that it's cool and feels very futuristic. We want to believe this is the future and investors want to believe it's going to make them a bunch of money and I just don't see it. Tech should be focused on making things that are actually new and do things better than a person, but we're now stuck on generalized tech that can only ever imitate people. It's stupid. Everyone loves to use anaolgies to make predictions about how whatever new tech is going to change the world, but cars aren't horses. None of this is a streetcar on rails. Things that are unprecedented happen all the time. The whole rental scooter thing blew up for like a year and then 70% of them vanished overnight because of backlash and no profit for the businesses. And in that case it DID have a selling point, WAS somewhat convenient, and wasn't just trying to replade a human employee. It just got too expensive. Self driving taxis could end up just like that. Nobody can say until it happens.