I don't think a bubble associated with a technology means that the technology is not incredibly useful. Rather, it's an overly aggressive inflation of value tha

I don't think a bubble associated with a technology means that the technology is not incredibly useful. Rather, it's an overly aggressive inflation of value that is nominally attributable to that technology, where much of that value later collapses. The dot com bubble did not invalidate the importance of the web. But there were all kinds of shenanigans going on around the promise of the web. People were setting up companies thinking/claiming that making a website would make the business wildly valuable, ignoring all the actual problems unrelated to the web that they'd need to solve before they would have viability. They were then successfully going public with nothing but the website built - no actual product in place. Then it collapsed. But the web carried on and some of the companies being built through that period (e.g., Amazon, eBay, Google) were quite real. I see similar things going on with AI now... An electric utility company that a friend works at has an edict to lay off all 200 customer support staff and replace them with a chatbot. They don't want to pay OpenAI, so the executives are giving the team (of 3 data scientists) 6-months to build their own in-house LLMs. They don't have the data or the infrastructure expertise to do it. But, AI! A tech company with 1-2K employees and lots of revenue that another friend works at is preparing to IPO in the next year. Executives are forcing LLMs on teams that can't find reasonable applications for them. It's being done to boost their valuation heading into the IPO because they can then call themselves "AI powered". At a FAANG that another friend works at, a non-technical VP with lots of available budget commandeered several data science and engineering teams to build something laughably bad with LLMs (LLMs would never work for this application, customers would hate the outcome, and it would create contractual problems for the company). The technical teams were tempted by the budget after a round of layoffs, but they could only stomach it for so long. After most of a year and 10s of millions of dollars spent (plus the contractual issues starting to appear), sanity prevailed, and the project was cancelled. None of these examples say that LLMs (or other ML approaches) won't continue to have life/society altering impact. They point to people trying to exploit/build the hype for short term financial gain. It's why so many ML practitioners don't like the term AI - many of them feel like AI == ML + hype. ML is just a tool, and all the hype makes people engage in science-fiction type thinking that obfuscate where the value really is. But it will all work because AI! These are only anecdotes, but what I'm seeing now feels a lot like what I saw in the dot com bubble.