points by nilkn 1 day ago | 0 comments
Their moat is their research capability. It's a combination of proprietary internal technology and models and infrastructure, people, organizational structure, and culture. As long as they maintain the best and fastest research capability, they have a durable advantage, at least for the time being. If we start to saturate all economically useful outcomes that can be reached via greater research productivity attainable to us, then this moat will start to fall apart. It could also fall apart if safety issues force a premature halt or major slowdown to further research.
[–] labcomputer 21 hours ago
> Their moat is their research capability.
That doesn't seem like much of a moat. What happens when a couple researchers go on new parent leave at the same time, or someone's productivity drops for a quarter because a parent passed, or gets divorced, or whatever?
Continually staying 6 months ahead of the distilled open-weight models means you need to keep flipping heads (nobody goes on vacation) until the end of time. The geometric distribution describes that, and it ain't pretty for the expectation value of these companies.
[–] honr 1 day ago
How long till that "research capability" becomes just 5 people with many AI agents, and no other humans in the main research loop?
[–] nilkn 1 day ago
I don't know and can't answer or predict that. But that's exactly what it could become (although probably not that extreme), where the agents doing much of the internal work are proprietary, conferring a research advantage.
[–] honr 1 day ago
My point is that it is not a real moat if other players can hire people from core research teams, and get a foothold that easily. And when/if models are good enough, you don't even need many people to form a fully functioning team.
[–] nilkn 1 day ago
It may actually get harder to replicate with time, not easier, even if the number of people needed to run the operation goes down. As the largest labs move towards internal RSI, the most important IP for doing that will transition into their proprietary internal infrastructure and models, none of which will ever be released and which increasingly won't be fully known or understood by the humans you might hire away.
[–] tensor 1 day ago
That's not that big of a moat though, as we've seen with DeepSeek and even smaller teams doing edge model work.
[–] nilkn 1 day ago
It's very hard to measure exactly how large it is, because there aren't good pre-existing metrics for it. You can measure in time (e.g., how far behind open weight models are from the best frontier models commercially available), but it's plausible that what seems like a relatively small time advantage (months) might mask a considerable difference in internal research sophistication. What we've seen repeatedly is simply that there does seem to exist a durable advantage in research productivity, at least for now.
[–] james_marks 1 day ago
I’m not sure I’d call maintaining the fastest research program a “durable advantage”.
If company X has a better model than company Y, do you use it? Well, that depends: will Y take two years to catch up? If so yeah, you buy X.
But if Y is just as good a few months later, you purchase based on other factors, because you know you can live without the brilliant research X is doing ... since you'll have it soon enough.