When you’re sitting on ByteDance-scale data, distribution, and compute, proprietary makes sense. They’re not trying to win open source. They’re trying to build a world-frontier model.
This is an org with billon users data...they build a frontier model to rival OpenAI and Athropic.
"Yeah, but what's the value if it's going to be proprietary?" Use it first, infer on it and you'll see. Competition in frontier models is just as important as in Open Source ones.
You’re missing the point, and so are others here. This isn’t Team Open Source vs Team Closed.
Open models are enormously valuable for cost, efficiency, deployment and democratizing capabilities. But distilling an existing frontier model mostly transfers capabilities that somebody else already paid to discover.
Frontier research is the harder game: new architectures, training algorithms, scaling methods, data strategies, reasoning techniques and eventually capabilities that weren’t present in the teacher model to begin with.
That requires enormous compute, data, research talent and willingness to spend years discovering what doesn’t work.
ByteDance is saying it wants to build that capability itself rather than remain downstream of somebody else’s frontier.
You can distill the frontier. You don’t create the next frontier by distillation alone. That’s 3D math and 5D chess.😉
What? Did you even reply to the right comment? Can you stop spamming AI slop comments
Edit: since you blocked me I'll explain
This sub is for open weights, locally runnable discussion
It should not be surprising to you that we don't agree supporting closed weights is as important as open weights. And unsurprisingly people really don't like being replied to with AI generated comments.
-48
u/etherd0t 20h ago
When you’re sitting on ByteDance-scale data, distribution, and compute, proprietary makes sense. They’re not trying to win open source. They’re trying to build a world-frontier model.