> I'm hearing more and more people outside the tech world talk about the AI bubble, and predicting it's going to pop

I'm juuust about old enough to remember the end of the Lisp Machine bubble (we had one or two at uni in the early 90s, and they were archaic by then). But obviously Lisp machines were the wrong way to go, even if they were a necessary step - obviously, hardware-mediated permanent object storage is the way forwards! POP! Ah, maybe not. Okay but can't you see we need to run all this on a massive transputer plane? POP! Oh. Okay how about this, we actually treat the microcode as the machine language, so the user-facing opcodes are like 256 bits long, and then we translate other instruction sets into that on the fly, like this - the Transmeta Crusoe! It's going to revolutionise everything! POP! Ah, what? Okay well how about...

And we're only up to the early 2000s.

It's bubbles, all the way back. Many of these things were indeed necessary steps - if only so We Learned Not To Do That Again - but ultimately are a footnote in history.

In 30 years' time people will have blog posts about how in the mid-2020s people had this thing where they used huge sheds full of graphics cards to run not-working-properly Boolean algebra to generate page after page after page of pictures of wonky-looking dogs and Santa Clauses, and we'll look at that with the same bemused nostalgia as we do with the line printer Snoopy calendars today.

Lisp machines, Transputers, Transmeta, even RISC were all academic-driven bubbles. They were spun out of university research projects. (Transmeta went indirectly via Bell Labs and Sun, but it was still based on academic ideas.)

The culture was nerdy, and the product promises were too abstract to make sense outside of Nerdania.

They were fundamentally different to the dot com bubble, which was hype-driven, back when "You can shop online!" was a novelty.

The current AI bubble is an interesting hybrid. The tech is wobbly research-grade, but it's been hyped by a cut-throat marketing engine aimed at very specific pain points - addictive social contact for younger proles, "auto-marketing team" for marketers, and "cut staffing and make more money" promises for management.