Deepseek showed us very well that openAI at the very least does not have a significant moat. Also, that the ridiculous valuations dreamt up for AI companies are make-believe at best.

If - and that's a big if - LLM-Tech turns out to be the path to true (not the OpenAI-definition) AGI, everybody will be able to get there in time, the tech is well known and the research teams notoriously leaky. If not, Another AI winter is going to follow. In either case, the only ones who are going to make a major profit there are the ones selling shovels during the gold rush - nvidia. Well, and the owners who promised investors all kinds of ridiculous nonsense.

Anyway, the most important point, in my opinion, is that it's a bad idea to believe people financially incentivized to hype their AIs into unrealistic heights.

It seems increasingly likely that LLM development will follow the path of self-driving cars. Early on in the self-driving car race, there were many competitors building similar solutions and leaders frequently hyped full self-driving as just around the corner.

However, it turned out to be a very difficult and time-consuming process to move from a mostly-working MVP to a system that was safe across the vast majority of edge cases in the real world. Many competitors gave up because the production system took much longer than expected to build. However, today, a decade or more in to the race, self-driving cars are here.

Yet even for the winners, we can see some major concessions from the original vision: Waymo/Tesla/etc have each strictly limited the contexts you can use self-driving, so it's not a 100% replacement for a human driver in all cases, and the service itself is still very expensive to run and maintain commercially, so it's not necessarily cheaper to get a self-driving car than a human driver. Both limitations seem like to be reduced in the years ahead: the restrictions on where you can use self-driving will gradually relax, and the costs will go down. So it's plausible that fleets of self-driving cars are an everyday part of life for many people in the next decade or two.

If AI development follows this path, we can expect that many vendors will run out of cash before they can actually return their massive capital investment, and a few dedicated players will eventually produce AIs that can handle useful subsets of human thoughtwork in a decade or so, for a substantial fee. Perhaps in two decades we will actually have cost-effective AI employees in the world at large.

There are plenty of real applications that Nvidia is fueling. Things that make money. There will be a reckoning for the hype men, but there is a good amount of value still there.

(As always, the task of the hype man isn’t to maintain the bubble indefinitely, but just long enough for him to get his money out.)

There are more fundamental issues at play, where I see stock price fairly divorced from actual, tangible value, but the line still goes up because people are going to keep buying tulips forever, right?

It sucks because I think investing in the stock market takes away from dynamic investment in innovative startups and real R&D, and shift capital towards shiny things.