"If NVDA has to provide the capital that becomes its revenues in order to maintain growth, the whole ecosystem may be unsustainable"

Lucent did this in the late 90s, covering up their ruse with clever accounting that wasn't so clever when it was discovered. This tanked the company and the stock. However, what Lucent did is more like AMD's recent deal rather than what Nvidia's deal with OpenAI. Neither Lucent nor AMD did quid pro quo deals but rather a large outright gift to the customer just so they could technically record a large sale. Nvidia's deals are also geared towards pushing sales. However, instead of giving away NVDA shares, they are receiving OpenAI shares, more like a quid pro quo.

"We are in a phase of the build-out where the entire industry's got to come together and everybody's going to do super well," OpenAI CEO Sam Altman told the Wall Street Journal on Monday.

This makes no sense. There is no emerging market where "everybody's going to do super well." That's always a lie. There will be a bloodbath, which has been true of every single emerging market ever. Most players today will fail. Only a few will eventually remain, and they will be the only ones that will do "super well."

OpenAI is way behind its main competitors (the hyperscalars) because it loses money and has no cash flow cow. OpenAI is likely one of the ones that will fail unless there is a significant paradigm change.

Perhaps there was disdain for Nvidia SoCs in gaming consoles. However, the feeling was mutual, as the profit margins on these chips are significantly lower than for discrete GPUs. For that profit, significant engineering resources were required. Nvidia's feeling was that it was a competitive advantage to have AMD stretch engineering resources to gaming consoles in addition to CPUs and discrete GPUs, all with fewer total employees than Nvidia, which was focusing almost solely on discrete GPUs, especially after the realizing about ten years ago that its SoC forays into phones and tablets were never going to amount to much.

The study mentions covariates, including income, ethnicity, and maternal education and gives population descriptions for some of these covariates. However, the report then almost completely fails to discuss covariates for the remainder of the paper, including in the discussion. The only statement in the results is that the results were "adjusted" for covariates.

Kudos to the study authors for tabulating covariates and a huge minus for asking the reader to just trust them that they did "the right thing" in considering covariates. Absent the covariate analysis, it's not clear that the results mean anything. If income, ethnicity, and maternal education weren't correlated with test scores, that would be surprising. The question is how strong the screen time and test score correlation is after accounting for the covariates. If the results are after accounting for covariates, then the authors needed to devote a significant portion of the paper to that analysis.

Also, boiling everything down to tidy little numbers usually masks the more interesting and insightful parts of the data. I would rather see scatter plots of the the covariates along with screen time and test scores to see what the distributions are.

Why isn't more favorable tax treatment a reason for moving? Because these people have so much money that they can hire lawyers and accountants to give them favorable tax treatment without moving abroad.

Moving abroad for investment opportunities seems suspect. Seems like it's not hard to invest in foreign countries without moving one's residence. Same with better educational opportunities. People who are already rich don't worry about their resumes like ordinary people, and if they want to learn, they know there are better and faster ways to learn without moving to a new country.

The only plausible reason is the desire for better quality of life.

Ideally carbon production would be avoided on the first place. Secondarily, it would be nice to capture and sequester carbon at the source. However, there are so many sources that it's simply impractical due to price and scaling constraints. Carbon capture from the general environment bypasses the need to identify carbon producers and to engage their cooperation.

Furthermore, it could be philosophically argued that the world is already engaged in mass terraforming with the extreme carbon release of the last few countries and certainly the last few decades.

Perhaps a nitpick, but neither China nor the US cares about free trade as much as they care about favorable trade. Both countries employ various tactics to restrict trade to their advantage. All countries use subsidies. We're seeing countries use strategic export controls and even embargoes. Also dumping, import restrictions, forced technology starting or transfer or theft, industrial espionage and more.

Free trade rhetoric is just marketing/propaganda. All countries are for free trade when it benefits them but cry foul when it's a disadvantage.

Seems like the lamentations are about how people aren't being laid off. Shouldn't the goal be getting the same people to be more efficient and do more work in the same amount of time or at least with less mundane effort? AI that summarizes emails or reports saves time for a worker, but it wouldn't make any sense to let go of someone because of that time savings. Similarly for things like code generation. No, AI won't write a complex piece of software by itself, but it can reduce typing and creating the simple, straightforward parts and allow for time and effort to be concentrated on the more complicated parts.

I had the opposite experience. To me, a workstation was a linux/unix machine. When I finally got a laptop (big and slow Toshiba), it was a Windows machine. Of course, starting about 20 years ago, the workstations went away. I had servers and workstations in the lab, and those all ran linux, but the office desktop went away and was replaced by a Windows laptop with a docking station and a monitor.

This is an interesting twist. This is not purely a matter of government intrusion but rather more about corporate intrusion. An optomist might say that the university is trying to balance getting funding and jobs for its graduates from these companies in exchange for squelching the rights of its students. Perhaps an even more difficult question is whether the protesting students would be willing to trade off their rights to free expression against the loss of jobs from the related companies.

"Meta's Mark Zuckerberg has complained about managers managing managers since 2023."

So, what does Mark do? Maybe manage managers that manage other managers?

Of course, I simplify his myriad responsibilities. For example, being a visionary in pushing forward things like the Metaverse and AI glasses. Also, having lunch with Trump. And lifting restrictions on Trump's social media accounts, ending third-party fact-checking, and scrapping DEI at Meta.

No, companies do not do this all the time. I can't recall a single company negotiating a $10 billion sale by offering to give $30 billion in free money/stock. No sane company does this. This smacks of extreme desperation. That's why Nvidia stock didn't tank or even drop because it's obvious that this sale was not an arms-length sale. If we eventually see a $10 billion arms-length GPU sale, that means that Nvidia's dominance for AI accelerators will have been breached, and that would prompt a massive drop in the Nvidia stock price.

Yes, this. We're not talking about a huge amount of money or physical space ... for a national government. Furthermore, why do 28 thousand government workers each need 30GB of disk space? Usually information that is either critical or even just functional is stored in a database or a repository to allow access to team members or even just to survive the end of employment for that worker. This seems like a badly designed system.

"Renaissance Macro Research estimated in August that the dollar value contributed to GDP growth by AI data-center buildout had surpassed U.S. consumer spending for the first time. Consumer spending makes up two-thirds of GDP. Tech giants including Microsoft, Google, Amazon, Meta and Nvidia poured tens of billions of dollars into building and upgrading data centers."

The US GDP is around $30 trillion. Consumer spending is two-thirds of the $30 trillion, or around $20 trillion. AI data-center spending is in the hundreds of billions, which is far smaller than consumer spending. The summary should have said, "the dollar value contributed to GDP growth by AI data-center buildout had surpassed **the GDP growth from** U.S. consumer spending for the first time." That's a completely different statement and much more believable.

The owners that bought those historical equipment thought at the time that they could make their workers more efficient, but their primary objective was to simply cut costs. There is no competent owner that doesn't think this way. If that efficiency resulted in more orders and work to be done, then the workers would be kept or even more hired, but if the same amount of work continued, then the workforce could be reduced.

It will be the same with AI, robots, etc. If the amount of work remains the same, workers will be let go. If the amount of work increases, more workers will be hired, even with greater efficiency per worker.

It is interesting that the two extremes of anti-AI sentiment are diametrically opposed. For both camps, AI is to be avoided. Some think that AI is a illusory bubble and that the technology will never do anything useful. Others think that AI is inevitably all-powerful and that what we currently see with AI is the tip of the iceberg that is the singularity.

Inference per request is relatively less demanding than something else like training. However, millions and billions of these small requests collectively turns into a total energy workload that is far higher than training.