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Comment by worldsayshi | Hacker News Reader

I see at least two potential positives in this:

- The frontier AI companies have realized they won't be able to count on gaining ground and earning more in the future through sheer moat. They have to start earning right now.

- The playing field on the market got a whole lot more even as a result. Now everyone is competing on cost and quality - while there are still a lot of competition. AI suppliers can't easily get away with subsidizing their own product and enshittify later.

I might be missing something obvious here? It feels to me that if the frontier AI companies thought they could gain a lot more moat they wouldn't raise their prices this much this early? And their current moats/head start doesn't seem insurmountable?

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The idea probably was to pour billions into technologies powering these LLMs, and gain a moat. It then turns out that this isn't as hard a problem as expected, it's just very expensive. So as long as you have money, you can be an AI company, the money is the moat (unless you take a shortcut, like DeepSeek) and money is running out.

I don't think you're missing anything, but I am surprised that the forces behind the AI companies did. They do need to start making money, but I don't think anyone has a plan as to how they are going to do this. As for enshittification, that was always on the table for the free tier, it was also going to be the drug deal strategy, were the first hit is free.

The cost of AI is still to high, datacenters aren't being completed, the hardware is to expensive, electricity is to expensive, the technology is good, but requires hand-holding. We're going to see AI being deploy more sparingly and more targeted, so the cost is justified.

> They do need to start making money, but I don't think anyone has a plan as to how they are going to do this.

Doesn't this just mean price increase ? What is not clear is how much the price needs to increase for AI companies to break even some time. 3x increase ? 10x increase ? Even more ? No one seems willing to give a clear number.

You can only increase the price so much. With every price increase you're going to lose customers, which could lead to further price increases.

I'm not entirely convince that the AI companies can raise prices and keep enough of their customer base to make their current strategy commercially viable.

They could also lower their production cost, but that runs counter to building/buying new datacenter capacity. Realistically I think they need to look for applications where cheaper models are just as good and niches that where the ROI on AI is more clear.

Realistically they can't go that much above the actual cost for inference since the customer can always switch to self hosted or inference only providers. Or their models have to be significantly better than the open source models for the foreseeable future. They will never be able to charge much more for their lower tier models.

They already do it. Antropic hiked prices several times, Google just hiked prices in April/May by a lot (by lowering limits in plans a lot). It will continue regularly. I remember when 200$/m plan was first unveiled there were screams about insanity of it all. Today, if anyone complains about own LLM experience, the first question from the comments would be "are you "at least" paying 200$/m plan, for the poors?" like that is the baseline now and 1000$/m is a serious consideration. And looking at Google, they are slowly shifting whole features upwards in tiers. As does Antropic.

> Doesn't this just mean price increase ?

Have you heard about Deepseek? In a world were it (and other Chinese open models) didn't exist, OpenAI and Anthropic would be profitable already

> In a world were it (and other Chinese open models) didn't exist, OpenAI and Anthropic would be profitable already

How so? The existence of e.g. DeepSeek doesn't lower the cost for OpenAI. OpenAI have almost a billion users, or so they claim. Adding even another billion users isn't going to help them, unless they can keep cost under control.

>AI can't easily get away with subsidizing their own product and enshittify later.

They have to do it in reverse order which seems to be maybe impossible. I contend that SOTA models are still quite bad at what their companies claim them to be good at. They remain confidently wrong more often than they should be. The public also is tired of 'slop' and will continue to push back on it.

the moat always has been and will be compute

and we are fast approaching limits which will be hard to overcome - electricity, chips

Don't you think that we will eventually get more specialized hardware that will greatly improve efficiency? Running neural networks on GPU:s seem like quite wasteful?

we will, but data centers will compete for that hardware with retail consumers

Such competition will only turn into a moat of the hardware suppliers never manage (or choose) to fully adapt to increased demand?

But then the real moat should be on the hardware side anyway?

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