It took 20 years for computers to "add" to the economy.
It's not good enough to just say oreo ceos say we need to more oreos.
There's a real grey area where these tools are useful in some capacity, and in that confusion we're spending billions. Too may people are saying too conflicting things and chaos is never good for clear long-term growth.
Either that 20 years is completelly inapplicable to AI, or we're in for a world of hurt. There's no in between given the kinds of bets that have been made.
They don’t have time to wait for all the companies to pick up use of AI tooling in their own pace.
So they lie and try to manufacture demand. Well demand is there but they have to manufacture FOMO so that demand materializes now and not in 20 or 10 years.
The AI use of GPUs didn’t stem from a glut of outdated, discarded units with nearly no market value. All of those old discarded GPUs were, and still are, worthless digital refuse.
The closest analog i can think of to what you’re referring to is cluster computing with old commodity PCs that got companies like Google and Hotmail off the ground… for a few years until they could afford big boy servers and now all of those, and most current PCs on the verge of obsolescence, are also worthless digital refuse.
The big difference is that Google et al chose those PC clusters because they were cheap, commodity pieces right off-the-bat, not because they were narrowly scoped specialty hardware pieces that collectively cost hundreds of billions of dollars.
Your supposition fails to account for our history with hardware in any reasonable way.
This isn’t a normal tech expenditure— the scale of this threatens the economy in a serious way if they get it wrong. That’s 401ks, IRAs, pension plans, houses foreclosed on, jobs lost, surgeries skipped… if we took a tiny fraction of this race-to-hypeland and put towards childhood food insecurity, we could be living in a fundamentally different looking society. The big takeaway from this whole ordeal has nothing to do with semiconductors — it is that rich guys playing with other people’s money singularly focused on becoming king of the hill are still terrible stewards of our financial system.
Divorcing research from "learning by doing" is a recipe for a bureaucratic ivory tower. If you only funnel money into pure research without the messy, expensive, and often "wasteful" reality of large-scale deployment, you end up with an economy of academic metrics rather than industrial power.
The most damning evidence against the "research-only" model is the birth of the Transformer architecture. It did not emerge from an ivory tower funded by bureaucratic grants or academic peer-review cycles; it was forged in the fires of industrial practice.
History shows that a fixation on immediate social utility or "rational" cost analysis can be a strategic trap. During the same era, Qing Dynasty bureaucrats employed your exact logic, arguing that the astronomical costs of industrialization and rail were a waste of resources better spent elsewhere. By prioritizing short-term stability over "expensive" technological leaps, they missed the industrial window entirely. Two decades later, they faced an industrialized Japan in 1894 and suffered a total collapse. The "waste" of one generation is frequently the essential infrastructure of the next.
To be fair, it isn't necessarily the same people doing both at once. Sometimes there are two groups under the same general banner, where one makes the big-claims, and another responds to perceived criticism of their lesser-claim.
An even bigger problem is that people listen to them even after they say rationally implausible things. When even Yann LeCunn is putting his arms up and saying "this approach won't work," it's pretty bad.
whether or not these companies can turn a profit - time will tell. but I am betting that our massively profitable companies (which are biggest spenders of course) perhaps know what they are doing and just maybe they should get the benefit of the doubt until they are proven wrong. but if I had to make a wager and on one side I have google, microsoft, amazon, meta... and on the other side I have bunch of AI bubble people with a bunch of time to predict a "crash" I'd put my money on the former...
quite the opposite is happening as evidenced from last earnings reports…
>Many observers disagree that any meaningful "productivity paradox" exists and others, while acknowledging the disconnect between IT capacity and spending, view it less as a paradox than a series of unwarranted assumptions about the impact of technology on productivity. In the latter view, this disconnect is emblematic of our need to understand and do a better job of deploying the technology that becomes available to us rather than an arcane paradox that by its nature is difficult to unravel.
It takes time for technology to show measurable impact in enormous economies. No reason why AI will be any different.
The iPhone killer UX + App store release can be directly traced to the growth in tech in the subsequent years its release.
We might have been possibly better of actually, with the Apple walled garden abominations and user device lockdowns not being dragged into the mainstream.
Not clear that this is a helpful interpretation, other than "we're in the primordial ooze stage and the thing that matters will be something none of the current players have", but that's hard to take to the bank :-)
Personally I think AI is unlikely to go the way of NFTs and it shows actual promise. What I'm much less convinced of is that it will prove valuable in a way that's even remotely within the same order of magnitude as the investments being pumped into it. The Internet didn't begin as a massive black hole sucking all the light out of the room for anything else before it really started showing commensurate ROI.
Most idiots like Columbus died in obscurity.
The thing I'm making with the APIs is very helpful to me, maybe it'll be helpful to others, who knows.
Right now the frontier AI companies are explicitly running a kind of chicken race - increasing the burn rates so much that it gets harder and harder. With the hopes that they (and not their competitor) will be the one left standing. Especially OpenAI and Antropic, but non-AI companies like Oracle have also joined. If they keep it going, the likely outcome is that one of them folds - and the other(s) reap the rewards.
Utility (per cost) will go up the tougher the competition. Money captured by single entity possibly down with increased competition.
I think there are two layers of uncertainty here. One is, as you say, if the value is worth the investment. The other and possibly bigger issue is who is going to capture the value and how.
Assuming AI turns out to be wildly valuable, I'm not at all convinced that at the end of this money spending race that the companies pouring many billions of dollars into commercial LLMs are going to end up notably ahead of open models that are running the race on the cheap by drafting behind the "frontier" models.
For now the frontier models can stay ahead by burning heaps of money but if/when progress slows toward a limit whatever lead they have is going to quickly evaporate.
At some point I suspect some ugly legal battles as some attempt to construct some sort of moat that doesn't automatically drain after a few months of slowed progress. Google's recent complaining about people distilling gemini could be an early signal of this.
I have no idea how any of that would shake out legally, but I have a hard time sympathizing with commercial LLM providers (who slurped up most existing human knowledge without permission) if/when they start to get upset about people ripping them off.