Comment by kroaton
9 hours ago
I think it mostly shows that there is no moat and the only advantage the U.S companies have over the Chinese is more compute. Qwen Max, Kimi K3, GLM 5.3 are really close to Opus/Sol/Fable/Astra and they are open weights.
From my experience with complex coding tasks (AI infra), I don't think these open weight models are close.
You can argue that TSMC has no moat since Intel and Samsung are also able to eventually make a node as good as TSMC - just a few years later and at smaller scale.
And no one would say that about TSMC.
So there is clearly a moat there somewhere.
No. In the semiconductor industry, the "catch-up" player isn't normally spending less in absolute R&D terms.
Comparing the R&D costs of creating GPT-4o vs. DeepSeek V3 (the latest gen for which we already have good accurate numbers) it looks like the latter cost 1/20th as much to create.
If Samsung could catch up with TSMC for 1/20th of the cost, people definitely would say that TSMC has no moat.
Why do you think Chinese models cost 1/20th to train?
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Yeah, I'm not sure if "no moat" analogy stands for chip manufacturing. Even if foundries acquire lithographic nodes, the procedures (temperature, duration, etc) are for them to figure out and are usually kept secret. This secret could be the "moat" that differentiates each foundry's operational capabilities.
bringing the price down b.c. competition != no moat.
There's not 100 frontier labs, it's not like airline companies
About the same, 5-10, when you consider major (aka frontier) airlines.
Actually not a bad comparison. Both burn massive amounts of up front capital to protect an oligopoly in the hopes their commodity product eventually pays off.
The "moat" is the "harness", the app.
For most people, the app IS the AI.
And even for its wonkiness, ChatGPT has had the best UX/UI of them all.
The way to win the AI wars in the eyes of the common folk is through the frontend, to be the Apple of AI, as it were.
this basically says you don't believe there is real AI.
they don't have moat in hardware either
Chinese counterpart like CXMT and Huawei is begin producing their own chip
You cant block an entire nation level effort with tariff
I think the moat that China has is energy costs. It's taking learnings from the Bitter Lesson. If you role up scale and compute to the next level, it's energy resources. China has it and sharing open weight models is an effective means of removing the tech moat. This idea has been floating around for a bit now (I'm not taking credit for it).
It's not energy costs. The US produces about 70% more electricity per capita. Chinese households do pay less than half what US households pay for electricity, but that's because the NDRC sets prices below costs for households. They make it up by charging industry more, and the industrial electricity prices in China are roughly 34% higher than in the US.
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They also benefit from the commodification of software/knowledge work since they own manufacturing
If there was no moat, nvidia and meta would have SoTA models too.
Nvidia does have one of the best completely open models. Open weights are nice but Nemotron is open training data too.
Meta is awfully close.
lol! Good one...
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It is not in nvidia’s interest to be too good at model creation
But it is in their interest that their customers can use their models as a base for post-training and LoRAs.
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Why not? Commoditize your complement, and all that.
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why so much negativity and certainty?
They have a lot of moat, i'm not sure what youa re talking about. Only amatures are using Qwen, open source stuff that is 3-8 weeks behind. Plus OpenAI has some verticals that keep people in there.
In what way do they have a moat? A cursory look at https://artificialanalysis.ai/models/gpt-6-astra#intelligenc... it lands at 61, only a single point above glm 5.3 while costing significantly more.
The only moat they appear to have is by hoarding compute, and the current trajectory of hardware shows that isn't permanent either for very long
I wish people could see how some of this reads. You are an “amateur” using a model 6-8 weeks behind? Really? Sigh.