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Your argument falls apart pretty quickly when you consider that (1) open-weights model are a thing and (2) OpenAI and Anthropic are still losing money

1. If AI would bring great productivity but all that extra value is captured by closed-source model providers, then everyone would switch to open-weights models + bare metal servers, which would non-tech companies to capture most of the value. Your argument that there is great value in the use of AI, but it's all captured by OpenAI and Antrhopic falls flat on it's face here. The market would adapt quickly.

2. OpenAI and Anthropic are still losing money. Your argument is that 100$ of extra value is produced, but the closed-source model providers capture 99.9$ of that because they are "rent extractors". If you're right, and they capture 99.9 of the value created, that's a huge issue because they spend 150$ to create that value. If even after eating the whole (value creation) pie they're still unprofitable, that's the worst news for the AI industry.

I basically agree that both of your points are major-to-catastrophic problems for OpenAI and Anthropic. I suppose it is true that if the companies fall apart, then my argument also falls apart. I think I would be pretty pleased in that scenario, all things considered.

I'm not rooting for anyone to have something bad happen to them or to their business.

I'm trying to be conscious about the situation because (like everyone else here) I've money on the line in the AI sector.

I hope this whole build-out turns out to be positive for our society.

Oh. Well, I am rooting for bad things to befall them. These companies are creating enormous negative externalities for society while pursuing profit and hewing to an ideology that believes it is genuinely risking destroying the world, and believes it is justified in subjecting everybody else to this risk because if they don’t, someone else might.

While in general I commend showing generosity and charity to those we disagree with, I don’t think it’s commendable to remain generous past the point where it becomes untenable.

I thought you were gonna say "market forces"

OpenAi and anthropic hypothetically undercut each other.. each epsilon-ups one another until they get to a point where they're splitting the productivity gains with the other companies. If this doesn't happen, it's called collusion and the SEC initiates action. (Ha!)

That should theoretically happen.

If we discuss theoretical scenarios, it's less likely to happen in a scenario where we only discuss about 2 companies in an oligopoly, so the argument isn't as strong.

In a scenario where we have 2 companies AND open-weight models (Chinese, American, French), all of a sudden that process is accelerated. That's basically my first argument in the comment.

Open-weights models that need closed markets hardware... (as in the markets are closed because you can't afford it)

Fair enough, there's definitely a shortage, but there is capacity available for people that are willing to buy it. There are platforms that give easy access to GPUs for small players, while the large players can make direct contract with neoclouds or datacenter providers.

The companies discussed in the article are 493 of the biggest companies in US, so if there was value to be extracted from using bare metal + open-weight models, I am sure they would be all over it.

Everyone talks about how sophisticated those large players have become in trimming their AI spend, they're a lot more cost-conscious. Perhaps this narrative might be overblown or there is truth to it. We'll see.

Not sure how productivity and rent capture are connected here.

1) If a firm spends $99k on compute to replace a $100k engineer and produces 5x the output, how is that not a 5x increase in aggregate labor productivity?

2) In your aspirin example, why wouldn't a competitor with an identical 1¢ machine sell it for 50¢ or 10¢ to take 100% of your business? You are either making the assumption that 1 company is owning the market and no models are useable beyond that one, or that all of the models that are in the front of the market have a cartel and fix the price, which is not true either looking at API costs.

  1) If a firm spends $99k on compute to replace a $100k engineer and produces 5x the output, how is that not a 5x increase in aggregate labor productivity?

The firm is spending $99k on tokens to replace $100k in labor. The token provider is spending $ x on compute to give $ p•x productivity output to the firm. The token provider can choose x at inference time and adjust p at training time, so they control p•x . They do have to make it greater than the firm’s current output so the firm will buy from them, but otherwise their profit incentive wants to make x as small as possible - if 110% of previous output suffices, it is strictly a loss to spend more to reach 500%.

(Also, pedantically, compute is not labor - if you 5x output and 0x labor, the labor productivity statistic becomes “what’s the ratio of 5/0 to 1/1?” ie undefined. But that’s not a very interesting point.)

Note closely the “middleman” vibe of this arrangement: the firm does not spend on compute to get output; the firm spends on tokens and then the token-provider spends on compute to get output, and then hands the output back to the firm. Rather than put in x and get back f(x), they put in x and get back e(f(g(x))), where e and g are the middleman’s extractive greed functions.

  2) …why wouldn’t a competitor with an identical 1¢ machine sell it for 50¢ or 10¢ to take 100% of your business?

If they were in the business of free market value creation, they probably would! I don’t know exactly how economists would describe it, but empirically, it seems the business of rent extraction has a different dynamic - one which can roughly be summarized as “competition shrinks the size of the pie, rather than growing it”, so all participants are mutually incentivized to treat competition as a cost to be avoided.

Can you demonstrate your take on 2) happening in practice?

- You have tokens priced differently as evident by for example pricing on for example OpenRouter.

- You don't reach 100$ of Fable/Mythos output by running Deepseek for the same amount of money. How do free open source models fit in here? Do you have to run Nemotron for an infinite amount of steps to reach 1$ of Deepseek compute? If not, then the argument is not valid because the pie should be shrinking.

Collusion. A cartel. That is how they describe it. And it's ostensibly illegal.

> Forms of Collusion Most criminal antitrust prosecutions involve price fixing, bid rigging, or 2 market division or allocation schemes.

This also ignores that 5x productivity doesn't often give you 5x profit, even if it gave you 1.1x profit that sounds great - until people start looking at profit vs productivity.

...we should be seeing prices of every day goods and services(mainly) come down.

I'll hold onto my hat for now.

The incentives are there. I know reddit and HN it seems like lots of people are using models/harnesses from scrappy competitors, but IME at the enterprise level I’m in the extreme minority who is even aware of them. Virtually everybody uses Anthropic and OpenAI tools and models, with Copilot getting some scraps because of its forced inclusion in Microsoft/github ecosystem

There is no question about the benefit when things go right; a wary engineer responsibly guiding agents to build orders of magnitude more than was possible before, and always skeptical and critical of the vendor, knowing the vendors’ incentives.

But that’s not the majority, and the people approving absurd token spend are too far out of the weeds to see what’s happening - people burning 6 figures in tokens and still end up with broken systems that keep them over the weekend, but now they hardly understand what they’re troubleshooting (if at all).

This is a dream scenario for the fat-cat vendors, so there is incentive to have CC/Codex write more code, overly-complex designs. When users get upset, they jump to OpenAI to spite Anthropic, or vice versa, but always getting further locked in to the duopoly

I don't really see the bloated-code take here. With this reasoning, there should appear a non-bloated open-source tool that all knowledgeable, smart developers will migrate to in order to get things done faster, and the market will have to follow.

Also waste and token spending could very well be a short-term thing. A lot of teams had crazy AWS bills in the mid-2010s on lambda functions and workflows, then it got cut down and optimized.

> 1) If a firm spends $99k on compute to replace a $100k engineer and produces 5x the output, how is that not a 5x increase in aggregate labor productivity?

I think they are saying that with 99k pure compute you are able replace 100k engineer with equal output. Or that is the goal of the AI companies. It is worse for them if you get more productivity.

It's so interesting that sometimes people throw these wild numbers around like 10x productivity, 100x greatness, etc. but when the rubber hits the road, we see so much ambiguity, unknowns and unrealistic assumptions.

But the AI companies have no access or knowledge of how much value you produce, they would have to calibrate against some average SWE salary and some average productivity which is task-dependent. There is no way for them to control this. Even if they did, they would lose out to other companies who do not do this and let you "keep" surplus value, it feels like this again assumes a no-competition market.

I guess it just seems obvious to me that most of the major players want a no-competition market, and are working towards making that happen, and are having notable success with their efforts (the whole “pacing the frontier” was a remarkably public display of coordination between purported competitors, the government has already banned deepseek, etc).

> If a firm spends $99k on compute to replace a $100k engineer and produces 5x the output, how is that not a 5x increase in aggregate labor productivity?

It sounds like they spent 99k to replace 5 100k engineers, which means they could charge 499k for it.

This again assumes a total monopoly or a cartel which does not exist today

It's a duopoly and a cartel.

This ignores the supply side of the equation and just focuses on the demand side.

Of course every business wants to capture 99.9% of the value they offer, but competitive forces drive this down to an equilibrium.

Also, as an aside, I've noticed that there's a subset of people on hackernews who use 'weird' to describe any disagreement with their position. It's not 'weird' to have an opposing or different view and removing such language will make conversations on here more pleasant.

This only works if you are the only one selling the machined aspirin. Or you build a cartel of apirin sellers to do some price fixing.

> Or you build a cartel of apirin sellers to do some price fixing.

They are really trying to do that by getting that regulatory capture

And by buying all of the available compute.

That doesn't appear to be the only thing necessary. Grok is still much worse than other closed source models, despite access to more compute.

Conversely, DeepSeek are relatively compute starved and produce a usable model (definitely not frontier but 10x cheaper).

Different with the open weight models though - they are a margin business. And openai etc have to compete with them too

And how long will they remain open?

Once most of this debt is gone, whether through companies going bust or the debt being paid off or inflated away, AI will become cheap enough for frontier models that any productivity improvements will be visible in the user's bottom lines.

Once all of the trillions of dollars of debt is paid off…

…plus whatever healthy premium the corporation decides it is owed for so bravely taking on those trillions of dollars of debt, once that too is paid off…

…plus whatever the expectation of return on investment the lenders were persuaded by, once that has also been met…

…only then will we get to see what proportion of the gains these corporations think it fitting to let trickle down. What do you reckon they’ll let us have? 50/50? One in ten?

I don't think it will all be paid off. I said once it is gone. I think, like the Dotcom bubble, many companies will go bust and their debt will be worthless.

I hope so!

This only happens in very mature industries. AI is obviously moving extremely quickly with lots of new entrants and moving parts. That's why all the model providers are losing money fighting for market share.

For the time being, my productivity has 100x'd for a fraction of what it would have taken to hire me only a few years ago.

This doesn't apply to self hosted models though.