> If the top 1% of companies drive the majority of VC returns
The fact that the author brings this up and fails to realize that the behavior of current staff shows we have hit or have passed peak AI.
Moores Law is dead and it isn't going to come through and make AI any more affordable. Look at the latest GPU's: IPC is flat. And no one is charging enough to pay for running (bandwidth, power) of the computer that is being used, never mind turning NVIDA into a 4 trillion dollar company.
> Meta’s multi-hundred million dollar comp offers and Google’s multi-billion dollar Character AI and Windsurf deals signal that we are in a crazy AI talent bubble.
All this signals is that those in the know have chosen to take their payday. They don't see themselves building another google scale product, they dont see themselves delivering on samas vision. They KNOW that they are never going to be the 1% company, the unicorn. It's a stark admission that there is NO break out.
The math isnt there in the products we are building today: to borrow a Bay Area quote there is no there there. And you can't spend your way to market capture / a moat, like every VC gold rush of the past.
Do I think AI/ML is dead. NO, but I dont think that innovation is going to come out of the big players, or the dominant markets. Its going to take a bust, cheap and accessable compute (fire sale on used processing) and a new generation of kids to come in hungry and willing to throw away a few years on a big idea. Then you might see interesting tools and scaling down (to run localy).
The first team to deliver a model that can run on a GPU alongside a game, so that there is never an "I took an arrow to the knee" meme again is going to make a LOT of money.
> Blitzhires are another form of an acquisition.. not everybody may be thrilled of the outcome.. employees left behind may feel betrayed and unappreciated.. investors may feel founders may have broken a social contract. But, for a Blitzhire to work, usually everybody needs to work together and align. The driver behind these deals is speed. Maybe concerns over regulatory scrutiny are part of it, but more importantly speed. Not going through the [Hart-Scott-Rodino Antitrust Act] HSR process at all may be worth the enormous complexity and inefficiency of foregoing a traditional acquisition path.
From comment on OP:
> In 2023–2024, our industry witnessed massive waves of layoffs, often justified as “It’s just business, nothing personal.” These layoffs were carried out by the same companies now aggressively competing for AI talent. I would argue that the transactional nature of employer-employee relationships wasn’t primarily driven by a talent shortage or human greed. Rather, those factors only reinforced the damage caused by the companies’ own culture-destroying actions a few years earlier.
> A group of big tech companies, including Apple, Google, Adobe, and Intel, recently settled a lawsuit over their "no poach" agreement for $324 million. The CEOs of those companies had agreed not to do "cold call" recruiting of each others' engineers until they were busted by the Department of Justice, which saw the deal as an antitrust violation. The government action was followed up by a class-action lawsuit from the affected workers, who claimed the deal suppressed their wages.
“The AI capital influx means that mega-projects no longer seem outlandishly expensive. This is good for the world!”
Is it? This whole piece just reads of mega funds and giga corps throwing ridiculous cash for pay to win. Nothing new there.
We can’t train more people? I didn’t know Universities were suddenly producing waaaay less talent and that intelligence fell off a cliff.
Things have gone parabolic! It’s giga mega VC time!! Adios early stage, we’re doing $200M Series Seed pre revenue! Mission aligned! Giga power law!
This is just M2 expansion and wealth concentration. Plus a total disregard for 99% of employees. The 1000000x engineer can just do everyone else’s job and the gigachad VCs will back them from seed to exit (who even exits anymore, just hyper scale your way to Google a la Windsurf)!
> This is just M2 expansion and wealth concentration.
I just want to point that there's no scientific law that says those two must move together.
A government very often needs to print money, and it's important to keep in mind that there's no physical requirement that this money immediately must go to rich people. A government can decide to send it to poor people exactly just as easily as to rich. All the laws forbidding that are of the legal kind.
Fwiw universities are producing less talent. They have been getting hammered with budget shortfalls thanks to Trump cutting research funding and this manifests into programs accepting fewer students and professors being able to fund fewer students.
if you're targetting $200M, then I guess each round is to hire one or two engineers for one year lol
I'm curious if you're one of these AI engineers getting 100m, do you quibble over the health insurance? I mean at that point you can fully fund any operation you need and whatever long term care you need for 50 years easily.
> mega funds and giga corps throwing ridiculous cash for pay to win
> This is just M2 expansion and wealth concentration
I actually think "throwing ridiculous cash" _reduces_ the wealth concentration, particularly if a chunk of it is developer talent bidding war. This is money that had been concentrated, being distributed. These over-paid developers pay for goods or services from other people (and pay income taxes!). Money spent on datacenters also ends up paying people building and maintaining the data-centers, people working in the chip and server component factories, people developing those chips, etc etc. Perhaps a big chunk ends up with Jensen Huang and investors in NVidia, but still, much is spent on the rest of the economy along the way.
I don't feel bad about rich companies and people blowing their money on expensive stuff, that distributing the wealth. Be more worried of wealthy companies/people who are very efficient with their spending ...
Off-topic but I'd totally read a blog from you where you use this pent-up bitterness against the current system to present bs nobody really talks about. It's quite refreshing.
> If the top 1% of companies drive the majority of VC returns, why shouldn’t the same apply to talent? Our natural egalitarian bias makes this unpalatable to accept, but the 10x engineer meme doesn’t go far enough – there are clearly people that are 1,000x the baseline impact.
These "talent wars" are overblown and a result of money having nowhere else to go. People are banking on AI and robotics for human progress to take off and that's just a result of all other ventures fizzling out with this left for capital to migrate to.
If you talked to any of these folks worth billions they arent particularly smart, their ideas not really interesting. it took us a few years to go from gpt-3 to deepseek v3 and then another few years to go from sonnet 4 to kimi k2, both being open source models on way lower funding. This hints at a deeper problem than what "hypercapitalism" suggests. In fact, it suggests that capital distribution as of its current state is highly inefficient and we are simply funding the wrong people.
Smart AI talent aren't going to out there constantly trying to get funding or the best deals. They would want to work. Capital is getting too used to not doing the ground work to seek them out. Capital needs to be more tech savvy.
VCs and corporate development teams don't actually understand the technology deeply enough to identify who's doing the important work.
I find the current VC/billionaire strategy a bit odd and suboptimal. If we consider the current search for AGI as something like a multi-armed bandit seeking to identify “valuable researchers”, the industry is way over-indexing on the exploitation side of the exploitation/exploration trade-off.
If I had billions to throw around, instead of siphoning large amounts of it to a relatively small number of people, I would instead attempt to incubate new ideas across a very large base of generally smart people across interdisciplinary backgrounds. Give anyone who shows genuine interest some amount of compute resources to test their ideas in exchange for X% of the payoff should their approach lead to some step function improvement in capability. The current “AI talent war” is very different than sports, because unlike a star tennis player, it’s not clear at all whose novel approach to machine learning is ultimately going to pay off the most.
> If I had billions to throw around, instead of siphoning large amounts of it to a relatively small number of people, I would instead attempt to incubate new ideas across a very large base of generally smart people across interdisciplinary backgrounds.
I had an interesting conversation with an investor around the power vs knowledge dynamic in the VC world and after a few hours we'd basically reinvented higher education with reverse tuition. Defining a general interest or loose problem space and then throwing money over a wall to individuals excited about exploring the area seems wasteful until you look at the scale of failed projects.
The full bodied palate of this AI market mirrors the sharp nose of 2023 AI doomerism.
The argument goes: if AI is going to destroy humanity, even if that is a 0.001% chance, we should all totally re-wire society to prevent that from happening, because the _potential_ risk is so huge.
Same goes with these AI companies. What they are shooting for, is to replace white collar workers completely. Every single white collar employee, with their expensive MacBooks, great healthcare and PTO, and lax 9-5 schedule, is to be eliminated completely. IF this is to happen, even if it's a 0.001% chance, we should totally re-wire capital markets, because the _potential reward_ is so huge.
And indeed, this idea is so strongly held (especially in silicon valley) that we see these insanely frothy valuations and billion dollar deals in what should be a down market (tremendous macro uncertainty, high interest rates, etc).
AI doomerism seemed to lack finish, though. Anyone remember Eliezer Yudkowsky? Haven't heard from him in a while.
We are not really doing anything about climate change which has maybe 0.001% of NOT happening, do you think we would do anything for the reverse? It was and it is always going to be business as usual.
> AI catch-up investment has gone parabolic, initially towards GPUs and mega training runs. As some labs learned that GPUs alone don't guarantee good models, the capital cannon is shifting towards talent.
Aren’t most of these deals locked-up stock deals? With lengthy vesting times, and performance based clauses.
The signing bonuses are probably more than enough for regular people to retire, but these researchers and execs being poached aren’t exactly average Joe’s making $50k/year prior to being poached.
Also, the people being hired now for insane sums of money, are being hired because they have deep knowledge in design / implementation of AI models and infrastructure that scale to billions of users.
In order to operate on a scale like that, you obviously need to have worked somewhere that has that magnitude of users. That makes the pool of candidates quite small.
It’s like building a spaceship. Do you hire the people that have only worked on simulations, or do you try to hire the people that have actually been part of building the most advanced spaceship to date? Given that you’re also in a race against other competitors.
> Also, the people being hired now for insane sums of money, are being hired because they have deep knowledge in design / implementation of AI models and infrastructure that scale to billions of users.
That's what they want you to believe, and in some cases that's true. Many though are just grifters. They were able to:
1. Gain access to the right people at the right levels to have the right conversations.
2. Build on that access to gain influence focused on AI hype
3. Turn that access/influence into income
That doesn't necessarily imply /anything/ about their actual delivery performance or technical prowess.
> It breaks down the existing rules of engagement, from the social contract of company formation, to the loyalty of labor, to the duty to sustain an already-working product, to the conflict rules that investors used to follow.
WTF is this guy hallucinating about? None of that ever existed.
French aristocrats didn't have trillion dollar industries brainwashing the population to be on their side, nor did they have AI powered armies to defend them when the people rose up.
Isn't this just shitty capitalism fighting shitty capitalism?
If I hire a bunch of super smart AI researchers out of college for a (to them) princely sum of $1M each, then I could go to a VC and have them invest $40m for and 1% stake.
Then since these people are smart and motivated, they build something nice, and are first to market with it.
If Google wants to catch up, they could either buy the company for $4B, or hire away the people who built the thing in a year, essentially for free (since the salaries have to be paid anyway, lets give them a nice 50% bonus).
They'd be behind half a year recreating their old work, but the unicorn startup market leader would be essentially crippled.
You might ask what about startup stock options, but those could easily end up being worthless, and for the researchers, would need years to be turned into money.
Must be nice to be able to ride such a wave and take your share. The money investors are throwing around these days is just insane. I remember it was considered a lot of money when Webvan got 400 million as investment during the .COM bubble. These days this seems nothing.
I think it's unfortunate that the term "capitalism" has been captured by the left to mean the bad kind of capitalism, where regulation is only used as a moat for the established players. Capitalism as a whole is the least bad economic system for prosperity, but the least bad version of capitalism is something like the Nordic model, with good taxation and redistribution policies and consumer protections. But the term itself is poisoned, at least in U.S. politics, to where social democrat/liberal capitalists like Bernie call themselves socialists instead.
"Silicon Valley built up decades of trust – a combination of social contracts and faith in the mission. But the step-up in the capital deployment is what Deleuze would call a deterritorializing force, for both companies and talent pools. It breaks down the existing rules of engagement, from the social contract of company formation, to the loyalty of labor, to the duty to sustain an already-working product, to the conflict rules that investors used to follow."
Stopped taking this thing seriously with blurbs like the above. If anyone thinks that Silicon Valley was somehow previously ruled by some magical altruism that has now been forsaken, they're in a little cloud of their own. The motives have always been more or less the same and even many of the people too, and there's no mysterious corrupting force that made any of that different then or now.
More money flowed in, technology developed more inroads into more people's lives and thus, the surface area over which the essential nature of tech business (like any business really) could be revealed more clearly expanded. This post is partly deluded.
There's so much here, and not necessarily in a good way. The way this guy talks sounds a lot like those old effective alturist arguments that went along the lines of "Well if there's a 1% chance we can save a billion lives a thousand years in the future, that's actually better than saving 100 lives today". Ignoring the fact that "1%" wasn't an estimate that you could have any confidence in.
Sure, if Deepmind could save a few percentage points on their data centres that would be huge! Becuase you've taken a small number you have no basis for (a few percentage points) and timesed it by the largest number you can find! Hey Presto! Big number! But then surely the guys at Google are morons right - because they only bought 1 Deepmind, they should've been throwing hundreds of millions around willy nilly! At these savings they can't afford not to!
Secondly, it might be true that it's difficult for you to compete with these companies that are hiring in teams of researchers for hundreds of millions, but what you're also doing is handing employees hundreds of millions of dollars. What are they going to do with that money other than throw it into angel investing? You're literally sowing the most fertile ground for startups in history.
I think we should actually be viewing this blow up in compensation in the context of the hangover of ZIRP and COVID. ZIRP basically made money in silicon valley free, tech companies could hire anyone they wanted at almost any comp and as long as there was growth there were no discount factors so they could effectively make infinite time horizon bets. Then covid happened and helicopter money came in to keep the economy going and Tech hired like crazy massively bloating lots of companies. But as things returned to normal, it became obvious that hiring had just been spending, and the returns weren't there for it. I think it's going to become clear over the long term that the same is happening here, Tech has tonnes of money so they're going to spend it, but 3 years down the line someone is going to do the accounting and I would bet you we end up back in the same spot that we did with Tech hiring in Covid - a long and painful unwind as companies have to return to reality.
The bottom line is that scaling requires money and the only way to get that in the private sector is to lure those with money with the temptation they can multiply their wealth.
Things could have been different in a world before financial engineers bankrupted the US (the crises of enron, salomon bros, 2008 mortgage debacle all added hundreds of billions to us debt as the govt bought the ‘too big to fail’ kool-aid and bailed out wall street by indenturing main street). Now 1/4 of our budget is simply interest payment on this debt. There is no room for govt spending on a moonshot like AI.
This environment in 1960 would have killed Kennedy’s inspirational moonshot of going to the moon while it was still an idea in his head in his post coital bliss with Marilyn at his side.
Today our govt needs money just like all the other scrooge-infected players in the tower of debt that capitalism has built.
Ironically it seems china has a better chance now. It seems its release of deep seek and the full set of parameters is giving it a veneer of altruistic benevolence that is slightly more believable than what we see here in the west. China may win simply on thermodynamic grounds. Training and research in DL consumes terawatt hours and hundreds of thousands of chips. Not only are the US models on older architectures (10-100x more energy inefficient) but the ‘competition’ of multiple players in the US multiplies the energy requirements.
Would govt oversight have been a good thing? Imagine if General Motors, westinghouse, bell labs, and ford competed in 1940 each with their own manhattan project to develop nuclear weapons ? Would the proliferation of nuclear have resulted in human extinction by now?
Will AI’s contribution to global warming be just as toxic global thermonuclear war?
41 comments
[ 4.7 ms ] story [ 56.9 ms ] threadThe fact that the author brings this up and fails to realize that the behavior of current staff shows we have hit or have passed peak AI.
Moores Law is dead and it isn't going to come through and make AI any more affordable. Look at the latest GPU's: IPC is flat. And no one is charging enough to pay for running (bandwidth, power) of the computer that is being used, never mind turning NVIDA into a 4 trillion dollar company.
> Meta’s multi-hundred million dollar comp offers and Google’s multi-billion dollar Character AI and Windsurf deals signal that we are in a crazy AI talent bubble.
All this signals is that those in the know have chosen to take their payday. They don't see themselves building another google scale product, they dont see themselves delivering on samas vision. They KNOW that they are never going to be the 1% company, the unicorn. It's a stark admission that there is NO break out.
The math isnt there in the products we are building today: to borrow a Bay Area quote there is no there there. And you can't spend your way to market capture / a moat, like every VC gold rush of the past.
Do I think AI/ML is dead. NO, but I dont think that innovation is going to come out of the big players, or the dominant markets. Its going to take a bust, cheap and accessable compute (fire sale on used processing) and a new generation of kids to come in hungry and willing to throw away a few years on a big idea. Then you might see interesting tools and scaling down (to run localy).
The first team to deliver a model that can run on a GPU alongside a game, so that there is never an "I took an arrow to the knee" meme again is going to make a LOT of money.
> Blitzhires are another form of an acquisition.. not everybody may be thrilled of the outcome.. employees left behind may feel betrayed and unappreciated.. investors may feel founders may have broken a social contract. But, for a Blitzhire to work, usually everybody needs to work together and align. The driver behind these deals is speed. Maybe concerns over regulatory scrutiny are part of it, but more importantly speed. Not going through the [Hart-Scott-Rodino Antitrust Act] HSR process at all may be worth the enormous complexity and inefficiency of foregoing a traditional acquisition path.
From comment on OP:
> In 2023–2024, our industry witnessed massive waves of layoffs, often justified as “It’s just business, nothing personal.” These layoffs were carried out by the same companies now aggressively competing for AI talent. I would argue that the transactional nature of employer-employee relationships wasn’t primarily driven by a talent shortage or human greed. Rather, those factors only reinforced the damage caused by the companies’ own culture-destroying actions a few years earlier.
2014, https://arstechnica.com/tech-policy/2014/06/should-tech-work...
> A group of big tech companies, including Apple, Google, Adobe, and Intel, recently settled a lawsuit over their "no poach" agreement for $324 million. The CEOs of those companies had agreed not to do "cold call" recruiting of each others' engineers until they were busted by the Department of Justice, which saw the deal as an antitrust violation. The government action was followed up by a class-action lawsuit from the affected workers, who claimed the deal suppressed their wages.
Is it? This whole piece just reads of mega funds and giga corps throwing ridiculous cash for pay to win. Nothing new there.
We can’t train more people? I didn’t know Universities were suddenly producing waaaay less talent and that intelligence fell off a cliff.
Things have gone parabolic! It’s giga mega VC time!! Adios early stage, we’re doing $200M Series Seed pre revenue! Mission aligned! Giga power law!
This is just M2 expansion and wealth concentration. Plus a total disregard for 99% of employees. The 1000000x engineer can just do everyone else’s job and the gigachad VCs will back them from seed to exit (who even exits anymore, just hyper scale your way to Google a la Windsurf)!
> We can’t train more people?
Of course people are being trained at Universities. Outside of The Matrix, it takes a few years for that to complete.
I just want to point that there's no scientific law that says those two must move together.
A government very often needs to print money, and it's important to keep in mind that there's no physical requirement that this money immediately must go to rich people. A government can decide to send it to poor people exactly just as easily as to rich. All the laws forbidding that are of the legal kind.
I'm curious if you're one of these AI engineers getting 100m, do you quibble over the health insurance? I mean at that point you can fully fund any operation you need and whatever long term care you need for 50 years easily.
> This is just M2 expansion and wealth concentration
I actually think "throwing ridiculous cash" _reduces_ the wealth concentration, particularly if a chunk of it is developer talent bidding war. This is money that had been concentrated, being distributed. These over-paid developers pay for goods or services from other people (and pay income taxes!). Money spent on datacenters also ends up paying people building and maintaining the data-centers, people working in the chip and server component factories, people developing those chips, etc etc. Perhaps a big chunk ends up with Jensen Huang and investors in NVidia, but still, much is spent on the rest of the economy along the way.
I don't feel bad about rich companies and people blowing their money on expensive stuff, that distributing the wealth. Be more worried of wealthy companies/people who are very efficient with their spending ...
> This is just M2 expansion
What is "M2 expansion"?
Just for your information.
https://www.youtube.com/watch?v=0obMRztklqU
If you talked to any of these folks worth billions they arent particularly smart, their ideas not really interesting. it took us a few years to go from gpt-3 to deepseek v3 and then another few years to go from sonnet 4 to kimi k2, both being open source models on way lower funding. This hints at a deeper problem than what "hypercapitalism" suggests. In fact, it suggests that capital distribution as of its current state is highly inefficient and we are simply funding the wrong people.
Smart AI talent aren't going to out there constantly trying to get funding or the best deals. They would want to work. Capital is getting too used to not doing the ground work to seek them out. Capital needs to be more tech savvy.
VCs and corporate development teams don't actually understand the technology deeply enough to identify who's doing the important work.
If I had billions to throw around, instead of siphoning large amounts of it to a relatively small number of people, I would instead attempt to incubate new ideas across a very large base of generally smart people across interdisciplinary backgrounds. Give anyone who shows genuine interest some amount of compute resources to test their ideas in exchange for X% of the payoff should their approach lead to some step function improvement in capability. The current “AI talent war” is very different than sports, because unlike a star tennis player, it’s not clear at all whose novel approach to machine learning is ultimately going to pay off the most.
I had an interesting conversation with an investor around the power vs knowledge dynamic in the VC world and after a few hours we'd basically reinvented higher education with reverse tuition. Defining a general interest or loose problem space and then throwing money over a wall to individuals excited about exploring the area seems wasteful until you look at the scale of failed projects.
The argument goes: if AI is going to destroy humanity, even if that is a 0.001% chance, we should all totally re-wire society to prevent that from happening, because the _potential_ risk is so huge.
Same goes with these AI companies. What they are shooting for, is to replace white collar workers completely. Every single white collar employee, with their expensive MacBooks, great healthcare and PTO, and lax 9-5 schedule, is to be eliminated completely. IF this is to happen, even if it's a 0.001% chance, we should totally re-wire capital markets, because the _potential reward_ is so huge.
And indeed, this idea is so strongly held (especially in silicon valley) that we see these insanely frothy valuations and billion dollar deals in what should be a down market (tremendous macro uncertainty, high interest rates, etc).
AI doomerism seemed to lack finish, though. Anyone remember Eliezer Yudkowsky? Haven't heard from him in a while.
So, no more bitter lesson?
The signing bonuses are probably more than enough for regular people to retire, but these researchers and execs being poached aren’t exactly average Joe’s making $50k/year prior to being poached.
In order to operate on a scale like that, you obviously need to have worked somewhere that has that magnitude of users. That makes the pool of candidates quite small.
It’s like building a spaceship. Do you hire the people that have only worked on simulations, or do you try to hire the people that have actually been part of building the most advanced spaceship to date? Given that you’re also in a race against other competitors.
That's what they want you to believe, and in some cases that's true. Many though are just grifters. They were able to:
1. Gain access to the right people at the right levels to have the right conversations.
2. Build on that access to gain influence focused on AI hype
3. Turn that access/influence into income
That doesn't necessarily imply /anything/ about their actual delivery performance or technical prowess.
WTF is this guy hallucinating about? None of that ever existed.
I feel like this one line captures the elephant in the room that the author is trying hard to convince himself isn't there...
If I hire a bunch of super smart AI researchers out of college for a (to them) princely sum of $1M each, then I could go to a VC and have them invest $40m for and 1% stake.
Then since these people are smart and motivated, they build something nice, and are first to market with it.
If Google wants to catch up, they could either buy the company for $4B, or hire away the people who built the thing in a year, essentially for free (since the salaries have to be paid anyway, lets give them a nice 50% bonus).
They'd be behind half a year recreating their old work, but the unicorn startup market leader would be essentially crippled.
You might ask what about startup stock options, but those could easily end up being worthless, and for the researchers, would need years to be turned into money.
Multi-year contracts north of $500m. Perhaps this is the direction we’re headed in.. there will be many that won’t make it to the majors.
Because before ChatGPT, nobody on a board of directors saw the possibility. Now, it's all they can think about.
Stopped taking this thing seriously with blurbs like the above. If anyone thinks that Silicon Valley was somehow previously ruled by some magical altruism that has now been forsaken, they're in a little cloud of their own. The motives have always been more or less the same and even many of the people too, and there's no mysterious corrupting force that made any of that different then or now.
More money flowed in, technology developed more inroads into more people's lives and thus, the surface area over which the essential nature of tech business (like any business really) could be revealed more clearly expanded. This post is partly deluded.
Sure, if Deepmind could save a few percentage points on their data centres that would be huge! Becuase you've taken a small number you have no basis for (a few percentage points) and timesed it by the largest number you can find! Hey Presto! Big number! But then surely the guys at Google are morons right - because they only bought 1 Deepmind, they should've been throwing hundreds of millions around willy nilly! At these savings they can't afford not to!
Secondly, it might be true that it's difficult for you to compete with these companies that are hiring in teams of researchers for hundreds of millions, but what you're also doing is handing employees hundreds of millions of dollars. What are they going to do with that money other than throw it into angel investing? You're literally sowing the most fertile ground for startups in history.
I think we should actually be viewing this blow up in compensation in the context of the hangover of ZIRP and COVID. ZIRP basically made money in silicon valley free, tech companies could hire anyone they wanted at almost any comp and as long as there was growth there were no discount factors so they could effectively make infinite time horizon bets. Then covid happened and helicopter money came in to keep the economy going and Tech hired like crazy massively bloating lots of companies. But as things returned to normal, it became obvious that hiring had just been spending, and the returns weren't there for it. I think it's going to become clear over the long term that the same is happening here, Tech has tonnes of money so they're going to spend it, but 3 years down the line someone is going to do the accounting and I would bet you we end up back in the same spot that we did with Tech hiring in Covid - a long and painful unwind as companies have to return to reality.
Things could have been different in a world before financial engineers bankrupted the US (the crises of enron, salomon bros, 2008 mortgage debacle all added hundreds of billions to us debt as the govt bought the ‘too big to fail’ kool-aid and bailed out wall street by indenturing main street). Now 1/4 of our budget is simply interest payment on this debt. There is no room for govt spending on a moonshot like AI.
This environment in 1960 would have killed Kennedy’s inspirational moonshot of going to the moon while it was still an idea in his head in his post coital bliss with Marilyn at his side.
Today our govt needs money just like all the other scrooge-infected players in the tower of debt that capitalism has built.
Ironically it seems china has a better chance now. It seems its release of deep seek and the full set of parameters is giving it a veneer of altruistic benevolence that is slightly more believable than what we see here in the west. China may win simply on thermodynamic grounds. Training and research in DL consumes terawatt hours and hundreds of thousands of chips. Not only are the US models on older architectures (10-100x more energy inefficient) but the ‘competition’ of multiple players in the US multiplies the energy requirements.
Would govt oversight have been a good thing? Imagine if General Motors, westinghouse, bell labs, and ford competed in 1940 each with their own manhattan project to develop nuclear weapons ? Would the proliferation of nuclear have resulted in human extinction by now?
Will AI’s contribution to global warming be just as toxic global thermonuclear war?