What I'm seeing in this thread is that OpenAI is actually diminishing the appetite for AGI, or muddying the waters in terms of what AGI even means. Most of the commenters here, as knowledge workers, should be well aware of the value real AGI would bring to the table (assuming, of course, that it is more cost effective than hiring a real human -- even if it's quite cheap, humans may be cheaper in some parts of the world -- not that I condone such inequity).
Nevertheless, regardless of whether OpenAI is close to AGI (I don't think so) or what value LLMs bring to the table (definitely non-zero), the problem is that LLMs are being increasingly commoditized and no one has a real moat here. I think that's why these firms are so desperate to kickstart regulations and are trying so hard to somehow pull the ladder up behind them.
OpenAIs fears don't come from "no one understands LLMs", but rather, that too many people do, and that large models have already fallen into the hands of the community who can do more with it in a week than OpenAI can hope to do in a year. Ever larger models might be out of the reach of the public, but real world value is more likely to come from a well prepared, smaller model (cf. vicuna) that doesn't cost an arm and a leg to run inference with -- and building these is cheaper than most might think.
If I had to point to a company and call it as a market leader here, I would point to Meta, not OpenAI. Meta has a huge workforce working for free on its model, after all, and they have made progress at a rate that bigtech cannot match in their wildest dreams.
There are also far too many eyeballs on this, in my opinion. For a company to truly dominate a market it needs a bit of air cover for a while building what will eventually be its moat.