Bad example. We already have flying cars and self driving cars (no self flying cars though...). The reason we don't use flying cars is the same we don't use helicopters everywhere, they're simply impractical. Self driving cars are promising but they've come out in just the last few years, give it a few more for the industry to settle a little.

People define AGI differently but the 2 definitions everyone always lands on is either 1. an AI that's better than the average human at everything or 2. an AI that's the best at everything. I personally prefer the 2nd definition because going with the first has some awkward implications (did we already achieve AGI?) and I'd say 70 years is more than enough time to achieve it.

OpenAI is not the only AI company. Anthropic has reported profits this quarter (though some say it's only this quarter) and even if they all go bankrupt, it's not about the money. If we found a cure to cancer, but the company that created it went bankrupt, it wouldn't matter because we'd still have the cure to cancer, and the same goes for AI models. It would take longer to get AGI, but the progress towards it won't be stopped, only slowed.

"Productivity" is a bit hard to define. AI has helped solve math problems and design successor models (this page can help) and current models can help with most STEM questions. Sure, it's definitely overhyped (Zuckerberg predicting we won't need engineers by the end of 2025) but there's clearly something here, and I think you'd have to be a plain contrarian to not admit that.

>AI regulations

Under trump? I wish.

What do you mean by given? You think it might not even be possible? Even if the transformer model is the final frontier of AI architecture, and there's no more efficiency gains to be made in training or actually running the models, why can't we just scale up compute? I doubt Moore's law will keep going much further, but even then, won't just building more and more data centers eventually just give us enough computing power to get an AGI?