I’m not sure I understand these references. The banks were too big to fail specifically because they were banks involved with the finances of every major industry and government, not simply because their (arguably specious) valuations, or even market caps, had a ton of zeroes on them. What’s the argument for OpenAI being so inherently critical and interweaved with the rest of the economy that it can’t be allowed to fail? What’s the argument for how such a bailout would result in greater economic outcomes? The banks that got bailed out continued lending and immediately resumed profitable business, how will the AI companies offer value towards such a proposition?
Moreover what would a bailout even look like? The banks got loan guarantees from the government essentially.
But like what happens if the government guarantees open ai's loans if the company is structurally unprofitable? Does the government create an operating subsidy?
Inference is cheap, only the training is expensive. Both Bernie and Trump have suggested doing a partial government takeover of the big AI companies to start a sovereign wealth fund.
So it would look like the government taking ownership, letting investors lose their stake, and then operating as inference-only, which would turn a profit
That's obviously how the AI labs are trying to position themselves. But slop generators are not integral to anything. They most definitely should be left to fail, and if the market so dictates, the hundreds of billions invested should go to zero.
High growth scenario and medium growth scenario (Graph 2). I feel like an idiot asking - aren't we missing some, or at least one, scenario? Is "medium growth" for the next 4 years really the worst people can think of?
Essentially yes? The stock market operates entirely on the assumption that the lines will keep going up. As soon as they flatten the whole thing collapses onto itself.
Flatten would mean there is a profitable business model. It's been years since people have been too tired of repeatedly asking "where will the profit come from?" with no answer. This shit has exactly one direction it will end and it's not flat or up.
Can't you see how much money is being pumped into this lunacy? Of course it's going to succeed. Graphs for failire are such a bummer too and are bad for the economy...
if growth doesn't materialize, then the infrastructure build out plays out exactly like the dot com bubble. the biggest difference this time around is the earnings. if those fall, the rest crubmles.
In the dot-com situation earnings "didn't matter" as long as there was growth. We[1] all believed profit would come eventually. The lesson learned from that experience was that earning do sort of matter. It turns out there is a limit to selling dollars for dimes. Since then revenue, profit and unit-economics ("fundamentals") have gotten almost as much attention as they deserve.
[1] a broad and poorly defined group of "we" - typically investors and tech-bro types.
Usefulness aside, I see little evidence AI is making money (profit, not revenue) for any firm whose profit doesn't come from the AI itself or the infrastructure, including supply chain. I'd love to hear a counterexample. One such example would be of a hypothetical company that does translations for payment, and with AI they now are making more profit because they use AI to do the translation rather than pay a translator.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
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AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
Translator services usually get paid because they offer an accreditation or certification that the humans doing the translation are trained and are not randos / computers. I could imagine these services becoming marginally more efficient but no dramatically improving profits.
The risk here is that either AI commoditizes the software "why ask duolingo to ask chatgpt when I can do so directly?" or simply adds cost to an existing service "why does every costco employee now cost 10% more?"
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
AI has been making a ton for advertisers for decades. Think Facebook ads, Google search ads, etc.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
Thinking out loud, is productivity the ultimate macro benefit of AI? Should we expect macro AI investment to be a leading indicator of macro productivity gains?
For example, did macro investment in factory automation predict future productivity gains?
I've seen other reports that suggest the level of investment for eclipses the internet buid out in 2000 and the railroad boom more than a century earlier. I wonder if they use different ways of landing on these wildly different assessments
Yes. In inflation adjusted dollars spending on AI dwarfs previous "megaprojects". But as a fraction of GDP it's fairly modest -- comparable to the Apollo Project.
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
You seem to be implying that railway spending was "over 10% of GDP for a few decades" in the late 1800s. If yes then can you trace that back to a methodology? I tried and found much lower numbers, around 3% average over the peak decade.
Your estimate of current AI spending is also low. Hyperscaler capex alone is around 2% of US GDP, not including other costs (neoclouds, employee comp, etc.).
Yeah but taxing 50% of all earnings below $100k could also do that. What money can be spent on is fine but I think we’ve got a good system where people can have reward for economic output and they can use that to allocate money where they want. There are places with central planning and I don’t like them.
Personally, I’d rather the money be spent on datacenters. And as it goes, the guys with the money also would prefer that.
https://www.bis.org/publ/arpdf/ar2026e.htm
But like what happens if the government guarantees open ai's loans if the company is structurally unprofitable? Does the government create an operating subsidy?
So it would look like the government taking ownership, letting investors lose their stake, and then operating as inference-only, which would turn a profit
We have absolutely 0 hard proof of this. We have a lot of wishful thinking but no hard numbers, audited numbers from any public entity.
I'd love to see them if they are available.
At this point anything less than "medium growth" will crash the economy. We'll have bigger problems if that happens (think 2000 or 2008)
[1] a broad and poorly defined group of "we" - typically investors and tech-bro types.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
---
AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
It is. We are talking about LLMs here.
For example, did macro investment in factory automation predict future productivity gains?
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
https://news.ycombinator.com/item?id=44805979
Your estimate of current AI spending is also low. Hyperscaler capex alone is around 2% of US GDP, not including other costs (neoclouds, employee comp, etc.).
Good to see GDP growing.
The amount of money we are talking about could have given the entire US high speed commuter rail.
Or treatment programs for addicts. There are a lot of economic benefits to helping folks on the lower side of the income spectrum.
Personally, I’d rather the money be spent on datacenters. And as it goes, the guys with the money also would prefer that.