Subject: Robotaxis, AI, and bubbles
Repost from the Fool

https://apple.news/AwJQWh3F8Sq...

Why AI Investors Should Worry About the Self-Driving Car Crash

● Robotaxis were supposed to be the easy part of automation. The failure of GM’s effort shows how far the industry is from living up to its wild promises.

Story is from Bloomberg News:

What was presented as a strategy shift was also a profound admission of failure. For years, Barra—like many executives in the tech and auto industries—spun a fantastical vision of the future in which fleets of so-called robotaxis would imminently replace normal cars. The technology was already developed, according to GM’s boss; the only thing left to do was scale it up. “We’re here. It’s happening now,” she boasted at the 2023 South by Southwest Conference in Austin. She routinely claimed that GM, which had revenue of roughly $50 billion in its most recent quarter, would make an additional $50 billion per year from robotaxis by 2030.

This sounds remarkably like the rantings of another “self driving car” proponent, doesn’t it?

These predictions turned out to be outlandishly optimistic, relying on questionable data and technical kludges that made the company’s software look more sophisticated than it actually was. Perhaps more unsettling, amid a boom in artificial intelligence technologies that has companies large and small contemplating replacing large numbers of human workers with modified chatbots, Cruise was hardly alone in overpromising. The company’s failure not only offers a cautionary tale for others attempting to sell robotaxis, especially [Elon Musk]’s Tesla Inc. and Google’s parent, Alphabet Inc., but it also suggests that the wild promises of operators of AI chatbots (and the companies that depend on these chatbots to justify their sky-high valuations) should be met with caution, if not outright skepticism. After all, autonomous driving was supposed to be the [easy part] of AI.

Despite its failure, Cruise got as close as almost any company has to operating a viable commercial driverless car service. The problem was, it wasn’t very close at all.

I post this story not only for its inherent interest, but also as a cautionary tale for those who have decided that autonomous robots are just around the corner, and that all that remains to be done is, you know, tweak a few things and learn how to train them.

The failure to successfully train computers to get anywhere close to the capabilities of any Uber driver (after 15 years of sending cars loaded with sensors onto millions of miles of road) should give pause to some of the same companies as they attempt to use a similar technology to supplant humans in performing more complicated tasks. Driving—unlike, say, writing news stories or doing customer service for a bank—is fairly straightforward, an activity governed by clearly defined rules that are more or less the same no matter where you are.

Conclusion:

And like robotaxis, the chatbots cost more to run than anyone is willing to pay, causing some, such as Jim Covello, head of equity research at Goldman Sachs, to suggest that the AI boom is actually a speculative bubble. With an implied valuation of almost $160 billion, OpenAI is the richest startup of all time, but it’s losing billions of dollars a year.

Having lived through the dot-com bubble, the real estate bubble, and even having been alive during the Nifty-50 bubble (although unaware of it at the time), I’m thinking a realistic evaluation of this stuff might conclude that AI is real, there will be some winners, but at this point it is entirely unclear what those might be and which investments are likely to be the superstars of the new field.