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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 rea
by kroaton 29d 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.
- tonyhart7 29d agothey 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
- astrobiased 29d agoI 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).
- spartacusnacho 29d agoThey also benefit from the commodification of software/knowledge work since they own manufacturing
- rgbrenner 29d agoIt'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.
- haldujai 29d ago> The US produces about 70% more electricity per capita. And consumers use 4x as much per capita. Industrial generation per capita China comes out ~2x > industrial electricity prices in China are roughly 34% higher than in the US For which industrial customer and where? Chinese compute hubs are on par to slightly cheaper on pure electricity costs. Conversely the US makes it more expensive with interconnect and upgrade fees as well as hefty take or pay contracts. A 1GW datacenter in VA for example would add 5-10c kWh and a 12 year take or pay deal
- thinkthatover 28d agoper capita seems the wrong metric given the difference in population sizes and America's wealth. They have roughly 4x the people and have added 10x new power capacity in the last 10 years, not to mention lapping us in renewable and long distance transmission lines added.
- VirusNewbie 29d agoIf there was no moat, nvidia and meta would have SoTA models too.
- seunosewa 29d agoMeta is awfully close.
- dansquizsoft 29d agolol! Good one...
- nwienert 29d agoWent from years behind to months pretty quick.
- amazingamazing 29d agoIt is not in nvidia’s interest to be too good at model creation
- david-gpu 29d agoWhy not? Commoditize your complement, and all that.
- angulardragon03 29d agoAnd if they get too good, they risk harming or otherwise killing their golden geese (their customers), who they are heavily invested in.
- david-gpu 29d agoHow? Imagine an open-weight model comes out that is somehow better than proprietary solutions. Now the marginal cost for the consumer is just the cost of renting the inference hardware, without having to pay the overhead of the owner of a proprietary model. And because it is cheaper, more customers want to use it, and Nvidia will sell the providers the inference hardware that they need.
- davidguetta 29d agobringing the price down b.c. competition != no moat. There's not 100 frontier labs, it's not like airline companies
- haldujai 29d agoAbout 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.
- keeganpoppen 29d ago[flagged]
- asa123 29d agowhy so much negativity and certainty?
- Razengan 29d agoThe "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.
- tw1984 29d agothis basically says you don't believe there is real AI.
- Razengan 28d agoRead the second line guy There are people all over the world who have no computer skills but they use ChatGPT on their phones daily They don't know/care shit about models and all that For them, if the app sucks, the AI sucks.
- m3kw9 29d agoThey 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.
- scronkfinkle 29d agoIn what way do they have a moat? A cursory look at https://artificialanalysis.ai/models/gpt-6-astra#intelligence 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
- bitexploder 29d agoI wish people could see how some of this reads. You are an “amateur” using a model 6-8 weeks behind? Really? Sigh.
- aurareturn 29d agoI think it mostly shows that there is no moat 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.
- coolandsmartrr 29d agoYeah, 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.
- saithound 29d agoNo. 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.
- aurareturn 29d agoWhy do you think Chinese models cost 1/20th to train?
- saithound 29d agoThat's the ratio the widely published numbers give [1]. One does not have to believe the numbers [2], but those who do believe them are then justified to conclude that there's no moat. Which numbers you believe is of course going to affect whether you think there's a moat or not. That's largely orthogonal to your TSMC/Samsung analogy I responded to. If you think the "moatists" are wrong because they believe the wrong numbers, that's fine, but then there's no need for the analogy. [1] https://galileo.ai/blog/llm-model-training-cost https://galileo.ai/blog/llm-model-training-cost [2] https://medium.com/@theiand/how-can-deepseek-a-5-6-million-llm-outperform-openai-and-meta-38e995b35140 https://medium.com/@theiand/how-can-deepseek-a-5-6-million-l...
- treefry 29d agoFrom my experience with complex coding tasks (AI infra), I don't think these open weight models are close.
- akie 29d agoNot sure if I agree, I tried GLM5.3 and it was pretty decent. Ok, it's not Opus, but maybe it's Sonnet?