Are OpenAI and Anthropic losing money on inference?

Will these companies ever stop training new models? What does it mean if we get there. Feels like they will have to constantly train and improve the models, not sure what that means either. What ncremental improvements can these models show?

Another question is - will it ever become less costly to train?

Let to see opinions from someone in the know

current way the models works is that they don't have memory, it's included in training (or has to be provided as context).

So to keep up with times the models have to be constantly trained.

One thing though is that right now it's not just incremental training, the whole thing gets updated - multiple parameters and how the model is trained is different.

This might not be the case in the future where the training could become more efficient and switch to incremental updates where you don't have to re-feed all the training data but only the new things.

I am simplifying here for brevity, but I think the gist is still there.

Updating the internal knowledge is not the primary motivator here, as you can easily, and more reliably (less hallucination), get that information at inference stage (through web search tool).

They're training new models because the (software) technology keeps improving, (proprietary) data sets keep improving (through a lot of manual labelling but also synthetic data generation), and in general researchers have better understanding of what's important when it comes to LLMs.

Sure the training can be made efficient, but how much better can these LLMs get in functionality?

There's a difference between model training and model fine tuning. Model training is not something e.g. OpenAI does a lot. The cutoff for gpt 5 was actually quite long a go. They sat on that for almost a year while they fine tuned the model. Finetuning is a lot faster and cheaper than training the full model. Training + finetuning is essentially fixed cost.

And you have to see this in proportion to the revenue. If you charge 20$/month and you have a few tens of millions of paying users and some premium tier users, that generates quite a bit of revenue.

OpenAI recently claimed they have 700 million regular users. I'm not sure how real/accurate that number is, but if one tenth of those pay for it it, that would be 1.4 billion per month coming in. That's excluding higher tiers. And I suspect they are shooting for a much larger market and are going to be nudging people to a bit higher tiers. Some have suggested that employers paying hundreds of dollars per month for AI subscriptions per employee might become normal in some sectors. That's an awful lot of money and I don't think they are done growing.

And of course with that kind of revenue, you can burn some cash on training cost. A few hundred million is basically nothing.

OpenAI has raised tens of billions of money. But they should be making 10-20 billions of revenue per year as well with some healthy growth. And they are showing very little signs of running out of money.