Who's afraid of Chinese models?

_aavaa_

> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation Sounds great to me; live by the sword, die by the sword.

chews

later secondaries investors in openai/anthropic. It's like time traveling into the spacex ipo.

minraws

Me I am, so very afraid of actually decently priced inference.

OleksandrC

The article makes a point about agent harnesses being sticky (the supposed moat). I have been building my own agent harness for a while, and I can tell with confidence that the harness almost does not matter, the entirety of the AI magic is the model itself. The harness can be almost barebones (like, for example, mini-swe-agent used for benchmarks), and yet the model still does the task just fine. So from my perspective, it's doubtful that this is the moat. Besides, for example, Claude Code in particular is so buggy (and always has been).

ilamont

But it’s a problem to be dependent on China. The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation, for U.S. companies at a minimum. I'm amazed that no one is talking about proposals that are surely being discussed in Washington and pushed by SV lobbyists to restrict Chinese models on national security grounds, or other some other basis. The belief that Bytedance could engineer a finger on the algorithmic scales to serve the interests of the Chinese Communist Party led to a lot of debate in Washington, and ultimately resulted in TikTok being divested from its Chinese owners. Huawei is shut out from the U.S. market, which limits its business even in markets where it's not banned because it's effectively stamped with a scarlet letter. IMHO, Chinese models are headed for a similar fate or at least a showdown in Washington or the courts because they are supported and/or controlled by entities which ultimately serve the CCP.

jdw64

While intelligence is said to be a replaceable commodity, oil and copper can be used in nearly the same way even if you change suppliers as long as the quality grade is matched. However, I question whether two models that produce the same benchmark answers are actually interchangeable in real world use. Personally, I think models will increasingly become specialized in different areas, some good at X, others good at Y, and we might see workflows that mix multiple models.

throwa356262

According to openAI's own @deanwball: Even OpenAI isn't buying this distillation talk: https://xcancel.com/deanwball/status/2078133895766114412#m

NooneAtAll3

I don't understand the premise in the beginning how is running servers supposed to be 0 cost, while running ai inferrence isn't?

wxw

> It’s striking the extent to which Claude Code and Codex are proving to be quite sticky; whichever harness you start working with is likely to be the one you stick with, and that figures to be even more the case with non-technical users. My experience has been quite the opposite. I was using Claude Code almost exclusively this winter/spring and swapped to Codex earlier this summer. It took no time whatsoever to switch. And before Claude Code, I was using Cursor. Same story. [edit: Oh and there was also a brief interlude with Conductor, though I think they're more or less just serving the underlying Claude/Codex harness]

fellowniusmonk

The U.S. "executive" class is so obsessed with the "exploit" part of the explore/exploit cycle that it's very clear they are prematurely closing advancement. Better a little money and power for them now than a lot of money and power for their country/humanity. This has an element of stochastic improvement so it's hard to predict but the chance of the U.S. "winning" this "race" is pretty bleak. You see this all the time in communities that have internalized hierarchy as a "good", little kings of shit mountain vying for less and less at a higher and higher cost.

jmclnx

One thing I have not seen mentioned between Chinese AI vs US, population. China has a billion+ people that their AI can "study". Plus due to China's political structure, their AI has access to everyone's chats, comments and sites, scraping everyting. Here in the US, with 1/3 the population, the AI race was lost before it even began. Plus in the US, all companies and people are doing all they can to restrict AI from scraping sites and peoples chats. So I believe, China will end up owing AI.

tristanj

The people who are most afraid of Chinese models are the VCs who poured into Anthropic and OpenAI at astronomically high valuations. Anthropic is valued at $1.2T and OpenAI is targeting $850B. These astronomical valuations were built on the premise that these labs would generate massive profits from premium API pricing, but the Chinese labs are completely undercutting this strategy by releasing excellent open models for free. If the frontier labs are forced to cut prices and join the race to the bottom in token prices, these valuations are unjustified, and VCs will face enormous (paper) losses.

jke_kang

People seem to conflate "made in China" with "can't be trusted." id argue the bigger distinction is open vs. closed. An open model can be audited, fine-tuned, and technically run entirely on your own hardware. A closed model is basically "trust us."

faangguyindia

I operate an analytics site (pretty big one B2B where client's backend feeds data into our system), and we see tons of traffic originating from northwestern China (Xinjiang) from Shenzhen Tencent Computer Systems Company Limited. There are also half a dozen other companies from China continuously hammering our clients’ websites. I was wondering, what's in that cold dessert? Low and behold satellite imaging shows massive datacenter build outs, very cheap solar energy. Few months ago something happened and the Geo location on data on those IP now shows "Shanghai" or "Shenzhen". A way to cover tracks? But mapping latency still points to fact that nodes behind these IPs are still operating around Xinjaing region credit: 'You Can't Cheat Time: Finding foes and yourself with latency trilateration' https://youtu.be/_iAffzWxexA HN user: lopoc Shenzhen vs Xinxiang is hard to do using this technique but Shanghai vs Xinxiang does show difference. Assuming that China only distills is a huge mistake. It’s no longer some backward place that does low value copying. Look at companies like ByteDance and Xiaomi. Chinese companies aren’t just distilling, they’re acquiring data in the same way American companies did by paying people and crawling the internet. The way I understand it, China has a few large companies that crawl the web at a rapid rate and build corpora. The government essentially wants select few companies to do this and then make the data available to other strategic companies operating within China. Then there are data aggregators that buy data from apps, websites, and services, as well as systems like OpenRouter or Cursor, where companies can learn from the “traces” of coding agents, chats, and so on. This massively reduces costs, as smaller companies like DeepSeek don’t have to do their own crawling or acquire data from 100s of websites and coding agents etc.... There are also companies in China that buy American LLM APIs and proxy them to companies within China. So, there could be 10,000+ companies using American AI products, while China logs all of this, understands how they’re being used, and trains on their traces.

hexator

I'm worried that any ban on Chinese AI models might be an excuse to get mass surveillance.

softwaredoug

> By the same token, don’t expect China to do anything about distillation attacks on the frontier labs. I think it is mistaken to attribute all of the success of Chinese labs to distillation, but it’s just as much of a mistake to pretend like distillation doesn’t give Chinese labs a big advantage. I think we see this with Meta being paranoid about internal Claude usage, to avoid inadvertently distilling[1]. If distillation is a driver, then smaller American labs could be distilling, but are not for legal reasons. But that's a big if we just don't know for sure. 1 - https://cryptobriefing.com/meta-restricts-claude-code-codex-...

sharadov

What makes the Chinese models this good? I don't believe it's distillation alone. This from OpenAi's Head of Strategic Futures "Some observations on Kimi: It's a very good model! I don't think its performance can be explained away by distillation or anything like that" https://x.com/deanwball/status/2078133895766114412 China's strategy of spending billions on training these models and open sourcing these models away is strategic - they want to kill the US LLM industry at any cost. To win on the AI front by any means necessary.

Havoc

oh wow - hadn't realized they decided to opensource Qwen 3.8 Max. That's pretty big news.

ggm

A reminder any comment about risk FROM china, invites a "Tu Qoque" facing the other way. The paranoia here is probably fully symmetrical. I see massive risks in belief the inferences drawn from strategic information cannot be seen. So if you depend on some position remaining inside a secure facility but you drove to it from data outside that secure facilty, The likelihood that an inference model can derive the same idea is very high. Collation over public data is not inherently secret because you used a secret model or secret weights. A more simplistic take might be that the fear is not actually driven in the secrets, the fear is "the emperor has no clothes"

sjreese

Kellogg School of Business -- he said -- token as a commodity and therefore Open AI is constrained .. ha ha ha hee hee ha .. Well... you build a better mousetrap, and DeepSeek, K3, and ByteDance are just that -- just as good and fit to purpose -- What is needed is to build on top of -- not paniteir (invade privacy and kill people with the information) -- not USMC AI -- use PI's as overwatch killer drones -- but how can I make harder steel, longer-lasting, seawater-resistant concrete, faster time to build housing, better enforcement of USDA rules and FDA adverse enforcement, and better EPA water cleanup, a better FTC for consumer goods -- that is, if I buy an item, that item is safe and built to purpose -- ANYONE not talking about public protection of consumer rights usng AI, is wasting your time