Surely a company as large as Microsoft is actively attempting to build their own models. They couldn't possibly have expected to stake the future of their software development on the conditions of a third party company?
This is a warning to any company, not building their own AI, that AI assisted development could become really expensive really fast and most likely won't pay off. What Microsoft is suggesting is that the current price is to high, but it's still not high enough for e.g. Anthropic to be profitable, or AI coding tools are only as good as the developers using them. So you can't meaningfully do layoffs by replacing the developers with AIs, because the cost is to high.
How does Microsoft plan to fix CoPilot, so that the cost will be so much lower than Claude, that budget overruns won't be a problem for their own customer?
Smaller companies will have departments that distill larger models into something more specifically manageable and useful for them. At least, that's my personal prediction :)
I do think your prediction makes sense, because the AI really isn't the product, it needs to be baked into something and licensing the models saves you the R&D and cost of implementing your own.
In order to do that they'd have to make a concrete business case to justify the headcount and compute costs. They'd be facing the same fundamental economic problems Anthropic, OpenAI, MSFT, etc are facing just at a department level instead of a megacorp level. I hope they try it, sunlight is the best disinfectant.
However, when the pressure is turned up and people have to actually show results--and, like, be accountable--instead of just buying a subscription and externalizing the accountability, I don't think we'll see so much enthusiasm about AI coding. Whether or not an engineer is actually more or less productive with AI (not merely whether they feel more productive) will begin to matter a lot more. I don't see how people continue using AI in this hypothetical small company under those adverse conditions.
There may be a spot of “good enough to pay for and make a profit” that exists.
The frontier model space costs 1000x as much to develop as the small language models, and is only 1.5 years ahead.
Factually, the frontier models have not paid for themselves. So, if you're MSFT and Apple, you don't need to run in a race where even the winner loses massively.
You can try to train models 1.5 years behind that are highly likely to be profitable, given your market position.
The average person is lagging behind what AI is capable of by 3+ years anyway...
So you can save 1000x on training and 10x on inference and just use SOTA small models.
Why spend $5B training a model that's for sure not going to make $5B (after inference costs) when you can spend $5M building one that WILL make far more than that after inference costs?
At one point there were rumours that they'd do that. They also have the rigts to oAI models for a few more years still, so they could always use that but apparently they're also compute starved (like anyone else).