That doesn't seem entirely fair.

What they discovered is that LLMs are extremely capital intensive, and you can only tap investors for money (and attract top-talent as an employer) for so long before they expect some kind of return on their investment, so it's either "make substantive progress" or "operate as a non-profit", but it can't be both for very long, or you eventually become unproductive and lose to an organization that has a profit-center, like Google.

So now they've found a way to continue their work by partnering with a company (Microsoft), where that company has access to a bunch of capital necessary to build better models, and a bunch of ideas about how to commercialize OpenAI's existing progress, by integrating it into their own product stack.

It's an amazing deal for both sides, seemingly, because Microsoft takes money out of its left pocket to give to OpenAI, and OpenAI puts most of it right back into Microsoft's right pocket, by renting their Azure services, which simultaneously improves the economics of that business unit, and also likely gives them amazing insight into how to be a world-class service-provider for SOTA "AI companies", in terms of hardware and software needs and optimization.

Similarly, OpenAI gives Microsoft some ownership, but they're so confident they can make them all of their money back that, if they do, they get the equity "back", which they can use to incentivize world-class engineers and academics to keep building. Since they're confident about their ability to make progress, they just get to make that progress "for free", without giving up much of anything to do it.

Luckily for OpenAI and other non-conglomerated AI startups, in the last few decades, we created a world where renting computing resources is a mature, commodified business, with a bunch of massive companies competing to drive the prices to the bare minimum.