There are many examples of this, but the most obvious is Tesla. Since 2018 they’ve been saying “next year,” and as of today they report having less than 200 “self driving vehicles” operating commercially on the roads. If they really did have a complete AI-driven self-driving car system, they would create an Uber-like app and open up their services to the millions of cars they have already sold to customers, allowing owners to send their cars off to generate revenue for them while they sleep. Instead they have 100-200 geo-fenced vehicles operating in known areas. The reason it’s not scaling is because (I argue) these cars aren’t even fully autonomous. Even in these safe, well-mapped areas that they have tuned their systems to, they still regularly get stuck and/or make mistakes and need human supervision, or regularly need an employee to connect via the internet and teleoperate the car out of whatever situation it got itself stuck in. I single out Tesla here because, believe it or not, Tesla has BY FAR the best and most well-developed “self driving” system. The situation is even more dire for the other companies in this space, who are all well behind Tesla in terms of progress and development. To see how big of an issue these companies face in actually getting this to work, you need only look to other AI systems (LLMs, which at their core run on the same transformer-like, attention-driven architecture). These latest LLMs, like Fable 5 and GPT-5.6 Sol, have upwards of 3 trillion parameters. To run those things you need an entire multi-million-dollar rack of high-powered enterprise GPUs with massive cooling infrastructure built around them. AND THEY STILL MAKE MISTAKES even in the comparatively simple domain of text generation. Ask anyone doing serious programming outside of silly webapps and they will tell you they still need babysitting and still regularly introduce bugs and unexpected or unwanted behavior that has to be caught in code review. The idea that you’re going to get an edge device running on low power in a car, which generously will have 1% of the params of these most recent LLMs driving these cars around (which is a far more complex domain than raw text generation) without any issues is crazy. Barring some wonder chip that can run multi-trillion-param models in-car, or a breakthrough in neural net architectures on par with that of Transformers from 2017, it’s just not going to happen. All you will see are these waymo like systems that can operate on rails, nothing you can safely drop down on any road and drive you anywhere no matter whats changed. submitted by /u/Organic_Rip2483
Originally posted by u/Organic_Rip2483 on r/ArtificialInteligence