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> The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new.

Sounds like it is new for ChatGPT though. That's also how it started with TV and Youtube, first on the free tier then expanding to the paid ones.

YouTube doesn't show ads on the paid plan. If you're talking about sponsored segments those would be impossible to moderate, and YouTube does offer easy skipping of those.

YouTube, Spotify, and most video steamers have zero ads on paid tiers. I never see video ads.

I don't paid anything to YouTube and I don't see any ads. Because I block ads.

Do you feel good about YouTube spending money on hosting and video producers spending time/money on content that you're paying nothing for? How is that sustainable?

The categorical imperative has been put on life support since 2016 at the latest.

Everything is smash and dash now. And nobody with the means to change it cares about externalities anymore.

I don't understand any of those sentences. How do they apply to YouTube?

Frankly? That's Google's (well, Alphabet's, I guess) problem.

They're a multibillion-dollar international monopoly with absolutely staggering amounts of money and power, actively engaging in a wide variety of activities directly aimed at making the lives of every normal person on the planet worse so that they can have more power, more control, and more money. Me blocking ads on YouTube not only costs them effectively nothing, it's also the act of a flea against a polar bear.

If Alphabet showed any signs of actually wanting to create a sustainable alternative to the surveillance economy, I might have some sympathy for them. But not only do they not do this, they are the ones who created it in the first place.

Doesn't your boycott of the ad-free model confirm to them that the only viable business model is ads?

I'm not sure where you got the idea that I'm boycotting "the ad-free model".

I'm boycotting them. After all, every cent that goes their way supports surveillance advertising (among other unsavory things).

I have other subscriptions that support ad-free creators.

If they choose to misconstrue my refusal to support them with either money or ad views, that's also their problem. (Also, that's patently never going to happen, because my signal vanishes instantly into the noise.)

YT has a Premium Lite paid tier (at least in the U.S.) that does show ads on music and in certain other areas of the app, such as shorts, searching, browsing, etc.

Most services have now light premium-tiers, where they do show ads. And then there are the rats like Amazon, who just add them to the normal tiers, and offer an additional service to not show ads.

I've never had ads in my Youtube Premium

> The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new.

This statement doesn't discount the original statement: that ads are going into GPT, which Sam called a last resort.

> The discussion about being unprofitable also repeats the reductionist view that these companies are losing money and therefore the business model doesn’t work. This happens with every VC cycle where writers don’t understand that funded companies are supposed to lose money while they grow. That’s what the investment money is for.

Usually propped-up companies don't last in the long term once the VC subsidy runs out. There's a difference between getting VC money in order to buy rocket parts, and getting VC money in order to charge $7 when you would really need to charge $10. The latter problem never goes away.

> We have very strong indicators that inference is not a money loser for these companies and is likely very profitable.

Why is OpenAI specifically losing money hand over fist then?

Training. But training costs are a smaller and smaller percentage of revenue as inference revenue grows faster than training costs.

Do you have any evidence that inference revenue is growing faster than training costs? RLVR is significantly less compute-efficient than token-prediction pretraining - especially as labs are trying to train models to achieve agentic tasks which take tens of minutes per rollout.

I don't have any evidence. You'll have to believe what Anthropic and OpenAI CEOs say publicly.

However, it seems to make a lot of sense. Anthropic literally added $6b ARR in February 2026 alone. I doubt training costs go up that fast.

But this is exactly the problem - we have to take it on faith that inference is profitable because nobody actually knows. It’s hard to even define what that would mean, and while I am suspicious of claims that frontier lab CEOs are just out-and-out liars or bad people, defining and calculating the real cost of inference would be time- and labor-intensive in its own right and there is no strong incentive to do it other than “tech reporters are curious.” Until the IPO, we just won’t know.

A lot of people know. A lot of insiders have been saying tokens are profitable. Is there a conspiracy theory for everyone to lie? Including OpenAI, Anthropic CEOs, employees, Cursor management, inference providers of Chinese models?

Profitable on what basis? They generate more revenue than the cost of electricity? Does that factor in the cost to service the massive, multi-layer cake of debt that was necessary to even begin to serve inference in the first place - not from a training perspective but from a hardware and facilities perspective?

Profitable as in every token they generate, they make some money.

And it's already mentioned that the path to profitability is that inference revenue eclipses training costs. It's already happening rapidly.

I’m not talking about training costs. I’m talking about startup costs. You have to pay for GPUs (or to rent data centers). You have to pay for the electricity that runs those data centers, and in a lot of cases these frontier labs are building the data centers on credit, so you need to pay for the construction, the materials, etc. If it was as simple as “running the GPUs costs less than we charge for it,” I might be inclined to agree. But the GPUs don’t just appear by magic.

Right now, the demand is far more than supply for GPUs. Every cloud company is saying they're leaving money on the table because they don't have enough compute to serve the demand.

It seems like you're arguing that the bubble is going to collapse soon, like the author? How can it collapse when the demand is so much bigger than supply? Do you think the demand is fake? Or that AI will stop making progress from here on out?

The demand is real. The tech is real. The economics are completely unsustainable. Switching costs and barriers to entry are too low, operating costs are too high. And if the tech improves, it actually makes it even easier for competitors to swoop in and take market share. Not long ago, an agent that was 80% as good as SOTA was not usable. A year from now, an agent that is 80% as good as SOTA will be better than the best agent is today. We have it on good authority that today’s agents are very good, very useful. Why bother paying full price?

This is deeply ironic in a way. Because the whole premise of AI labor replacement is that AI does not need to be better than human labor, it just needs to be cheaper with acceptable performance. But the same is true one step down: discount AI doesn’t need to be better than bleeding-edge AI, it just needs to be cheaper with acceptable performance.

It's definitely true that they've increased their revenue rapidly. But at the same time the 'scaling laws' that the labs were first built around require exponentially-scaling cost (10x flops for a fixed reduction in training loss).

If anything, a better look at the economics is a reason to look forward to one of them IPO-ing. I suspect the labs probably could cut R&D and turn a profit, but that might only work for one generation, until they get superseded by the competition.

There is no doubt that competition is what is driving unprofitability. So when people say AI can't be monetized, I laugh. Right now, foundational AI is unprofitable because of competition, not because they can't make money.

>The “but they’re losing money” argument never seems to be brought out against competitors that literally give away their models for free and for which we can calculate the cost of serving 400B-1T parameter open weight models.

To be fair people aren't exactly bullish on the prospects of deepseek or z.ai either, it's just they're below radar so they don't get mentioned.

Z.ai is at least owned by a public company, so there might be something in the financials.

https://en.wikipedia.org/wiki/Z.ai

>> "On 8 January 2026, Z.ai held its initial public offering on the Hong Kong Stock Exchange to become a listed company.[24][25][26] It is considered to be China's first major LLM company that went through an IPO.[26] In February 2026, JPMorgan Chase recommended to investors of purchasing stocks of the company alongside MiniMax.[27]"

https://www.zhipuai.cn/investor_relations/

But I haven't looked into it.

> companies are supposed to lose money while they grow

At what point do we declare that a company has "grown" and now must make money? OpenAI is a multi-billion dollar company right now, surely that's a point at which they should be profitable, instead of propped up by further investment and borrowing.

> We have very strong indicators that inference is not a money loser for these companies

All of the economic analysis that I've read strongly states the opposite. Running a GPU is a net loss /even for the data centre operators/. For them to break even, they currently charge OpenAI/Anthropic/Etc more than OpenAI/Anthropic/Etc make per-token.

They clearly have some vested interest/skin in the game. Not sure it's worth retorting that one.

> Having an ad-supported free tier isn’t new having ads shoved in paid tiers isn't new either

And it usually doesn't result in a market crash.

> This article tries to build upon a lot of half-truths or incorrect facts, like this:

yeah i was wondering why my bullshit detector was going off. This feels as if someone who cooks for Ramsey's kitchen is trying to predict the end of the market hike.

We have strong indicators that inference is profitable on non-economically-valuable prompts. We don't have strong indicators that inference is profitable on economically valuable prompts.

As AI companies start extracting rent from the prompting, one of two things are going to collapse - either the long tail revenue base of low-value inference is going to collapse, because people won't be using Chat GPT to get a recipe if it costs them money or if it is ad-ridden; or the cost of economically-valuable inference is going to go up - and whether it goes up to economically stable positions is a toss-up.

And I say this as an AI enthusiast with <50% probability of a bubble burst in the short term.

I've heard "They're losing money" since the 1990s. About Amazon and nearly every other tech company.

The strategy is always:

* Build something useful

* Give it away for free to get people exited

* Convince investors that this is going to rule the world

* Grow to dominate the world

* Enshittify

The difference is switching costs and the viability of alternatives. Even open source models are only a few months behind the frontier labs, which is a long time in tech but practically no time at all in the eyes of a business consumer. At best, one of the frontier labs will survive and get to flex its hegemonic muscle. But billions and billions of dollars worth of investments still get wiped out in that scenario, which I would still qualify as the bubble popping. This would be doubly true if the winner winds up being Google or Microsoft.

I don't know about others, but with Amazon specifically, it's always been very clear that their "losing money" in aggregate was purely on paper, for tax purposes: their ability to undercut everyone else was initially based on being online without the brick-and-mortar costs that other stores did, then on economies of scale, and now on being the 900kg juggernaut that just has more money than God and can blow it on running you out of business if they feel like it.