Current LLM architecture doesn't learn - and you're right this is a huge piece that normal folks fail to understand, since in many ways, it's the opposite of what years of AI research has been trying to create.
However, I think it's important to remember that LLMs are embedded in larger systems, and those larger systems do learn.
If I was a frontier lab and I solved continual learning, as of today I would absolutely not release it - the society isn't ready for this; society isn't even ready for widespread diffusion of current publicly available frontier models.
If however I was a frontier lab who solved continual learning and my competitor also solved and released it, I would release mine immediately, obviously.
The point is, continual learning might be solved already, we just don't know and those who might know would rather keep their mouths shut. It isn't my base case (financial situation of frontier labs is such that they'd probably release immediately as long as they have inference compute to serve this revolutionary capability), but it isn't impossible.
You're not a frontier lab, the shareholders own those. And if shareholders get a private briefing about an unprecedented breakthrough in continual learning, they would announce it from the rooftops to take credit for the progress ASAP and reap the rewards for their stock value.
The only lab that I can exempt from this is DARPA.
Shareholders are not insiders. Public companies do secret projects all the time of which shareholders know absolutely nothing about and may never learn the details of them if they get cancelled.
No youre missing the point of the poster - disclosures in private markets are different than public, especially in the context of large commitments - the company has no choice.
The implications are very different if everyone owns them even if they aren’t public. They may have no choice whether to share, but the owners which have the privilege to know (not everyone because earlier owners aren’t stupid) don’t act the same, right?
And let’s be honest - rules get bent all the time, especially when valuations are 9 figures. Stakeholders at this point won’t risk killing a golden goose.
However, I think it's important to remember that LLMs are embedded in larger systems, and those larger systems do learn.