Well sure, but the more complex your measurements are the worse you make it. Rather than looking for more nuance, we should look for stricter approaches to avoid those issues.

> Inflation is easily gamed by manipulating the basket of goods used to determine it.

Just turn the tariffs on and off again.

do you live in the same reality as me?

Tons of articles posted here talk about economy topics but not inflation or GDP or unemployment

As to banks, there's a LOT more stuff considered in monetary policy, like domestic consumption/investment, gov spending/taxes, net exports/imports.

populist politics focus on unemployment and inflation but even Trump campaigned on reducing government spending which in fact is bad for unemployment but apparently more important to Americans regardless

Because they probably would have to pay a lot more to make this profitable at the levels current valuations and investments indicate. And the barrier for private persons to pay is much larger than for companies. I don't think anyone has a really solid handle on the economics here yet, as the field is changing very quickly.

But there is a big difference here compared to most software companies. The product does cost significant money per additional customer and usage.

There is a real product here. And you can likely earn money with it. But the question is "how much money?", and whether these huge data center investments will actually pay off.

Because all numbers point towards it being incredibly far away from being profitable? We also pay for Google Workspace and at 10 euro a month we get Gemini Pro. So while we might pay for it, it’s more of a free addon, we would’ve paid 10 without it too.

You can also do a simple analysis on the Anthropic Max plan and how it successively gets more and more limited, they don’t have the OpenAI VC flow to burn so I believe it’s a indicator of what’s to come, and I could of course be wrong.

We would also need to know how many people are willing to pay for it, on a consumer level. Additionally business will need to see real ROI for using it.

At the moment everyone is trying their best to implement it, but it remains to be clear if it actually increases a company's profitability. Time will tell, and I think there are a lot of things obfuscating the reality right now that the market will eventually make clear.

Additionally the economics of training new models may not work out, another detail that's currently obfuscated by venture capital footing the bill.

It becomes feasible when people are willing to pay more than it costs to run it. But I think this will be a pretty uphill battle, as many use cases are hard to monetize (eg proofreading) and for many use cases you will feel pressure from smaller models (you don't need the most expensive SOTA model to generate an email). There is probably just a very limited amount of use cases that are in the goldilocks zone with their difficulty so that people will be willing to pay for them, AND AI is able to solve them. I think programming might be one of them.

You don't think it's a bigger assumption that plowing hundreds of billions of dollars into a novel and often misunderstood technology is going to net out positive? We're not talking "people like feeds of cat photos" money and risk here, we're talking about a bubble with the potential to tank the entire economy. On top of that, it's also a higher disruptive technology that should it ramp as quickly as it might will lead to massive amounts of societal strife at a time where we're already stretched a little thin to say the least. "What do you mean Credit Default Swaps don't work? They've been functioning perfectly well these past few years and so far the impacts have only been positive. Tons of people are getting mortgages on houses they weren't in the past, it's the American dream!"

I'm not saying they won't, it's just that datacentre growth is not the same as AI growth. It's related, but it is, by definition, temporary as datacentres are soon completed.

There's obviously evidence people use LLMs. That's not necessarily the same as people paying a noticeable fraction of all their money to use them. And even if "normal" people do start taking out $50 subscriptions as a matter of course, commoditisation will push that price down as will "dumping" of cheap models from overseas. A breakthrough in being able to run "good enough" models very cheaply, or even locally, would also make expensive cloud AI subscriptions a hard sell. And expensive subscriptions are the only way this pans out.

It hasn't yet been shown that AI is a gas that will fill all the available capacity, and keep it filled. If bread were 10 times cheaper, would you buy 10x as much? That has more or less happened to food availability in the West over the last 200 years and OpenBread and BunVidia don't dominate the economy.

None of that is sure to happen, and maybe the AI hype train is right and LLMs specifically are worth, say, 0.2*GDP forever. But if it isn't, and it turns out $5 a month gets you all people actually need, it's going to be untidy.

> GPUs aren't built in the US, though. I wonder, what percentage of all the stuff in a typical datacenter is actually made in the US

Does that matter? So many things these days aren't physically made in the US. So US companies don't get the profits and aren't needed?

The actual "made in" part is a small fraction of the total earnings. See how much an iPhone costs to make vs how much it gets sold for.

The margins collected by Nvidia end up in the US. And Nvidia and its employees get paid in the US. Only a small part of the revenue is outside the US.

I’m not saying don’t tax them or let them influence politics.

I’m saying letting them go to space or turning sand into intelligence is infinitely better than buying land and charging us rent (what most rich people have done in history).

The slop is real. Especially when I see promoters of platforms for vibe coders. They don't understand the implications of lack of security in potentially viral apps. It's easy to consider them as WMDs.

People have the same password across services. They share personal information. In a geopolitical climate as today's, where the currency of war is disruption, it can wreak havoc.