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Who's afraid of Chinese models?

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Re: Who's afraid of Chinese models?

#121

Post by VulgarExigency »

lemax wrote: post #64
mediaman wrote: post #62

Earlier quoted context omitted.

The (quite excellent) article discusses several of your points. If you haven't read it, I recommend it. - Commodity market profitability is determined by marginal cost of production. LLMs have marginal cost; traditional software does not. - Models are not free. Downloading them is free. Running them is not. This has manufacturing economics, not software economics; the idea that they are "free" is an economic category…

But this assumes Chinese models will not achieve token cost optimization. Intelligence needs are fairly flat for many tasks, and the Chinese models have caught up on this front. Next they achieve greater token cost efficiency and we don’t need OpenAI.

The model that is most optimized around token cost is, in fact, Chinese. DeepSeek is astoundingly cheap by default, but if you use it from Reasonix (the harness optimized around its cache), it becomes even cheaper.

Re: Who's afraid of Chinese models?

#122

Post by blfr »

andersonpico wrote: post #106
Aurornis wrote: post #92

Earlier quoted context omitted.

For personal use I agree. For companies, these decisions are very sticky. Companies go through a lot of red tape to get anything purchased and approved, then they discourage change because it's a lot of work. So the product that gets a foothold in a company sticks for a long time. Then a couple years later a sales person convinces an exec that they can save some money by switching, so the switching game begins. Not n…

Every company that I've worked with that provided models internally did so through LiteLLM and offered both Anthropic and OpenAI models so it was trivial to switch between them.

Most companies just get you a Claude team sub and maybe a couple of skills.

Re: Who's afraid of Chinese models?

#124

Post by titanomachy »

throwa356262 wrote: post #10

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

> open models are inherently decelerationist

I’m struggling to understand this perspective. Is he using the words accelerationist/decelerationist in a sense other than the obvious one?

EDIT: I searched his twitter history and discovered that his argument is basically “if you drive down costs, then OpenAI will have less money to invest in development, slowing down the overall rate of AI progress.” IMO this take betrays an overwhelmingly stupid degree of exceptionalism, but I guess that’s what I’d expect from someone working at OpenAI.

Re: Who's afraid of Chinese models?

#125

Post by andrewf »

nl wrote: post #99
wxw wrote: post #14

> 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 swit…

Have you ever worked with a non-programmer and helped them setup their AI workflows? You install MCP connectors, specific skills, work around model/harness quirks, set security boundaries etc. It's a lot of work, and most people will never want to change it once they have it working.

It strikes me as like setting up an IDE. People have preferences, switching is possible, but there are advantages to saying "we are a Visual Studio + Resharper shop" or "everyone uses IntelliJ to work on this project".

Re: Who's afraid of Chinese models?

#126

Post by favouritemartin »

nl wrote: post #99
wxw wrote: post #14

> 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 swit…

Have you ever worked with a non-programmer and helped them setup their AI workflows? You install MCP connectors, specific skills, work around model/harness quirks, set security boundaries etc. It's a lot of work, and most people will never want to change it once they have it working.

Skills are quite interoperable, and you can easily ask Codex / Claude to help you with switching the MCP connectors or any other things specific to your previous workflow. It's been quite low friction in my experience.

Re: Who's afraid of Chinese models?

#127

Post by onesociety2022 »

hexator wrote: post #57

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

You don't need mass surveillance to enforce such a ban. Once the US Govt declares Chinese AI models are banned, no US business will use them nor distribute them. Any cloud service that rents out GPUs in the USA will explicitly prohibit the use of Chinese open model weights in their terms of service (you open yourself to a lawsuit if you violate their ToS). Any Tokens-as-a-Service provider will refuse to serve those tokens to customers in the US.

Sure as an indie hacker, you could go download the weights for a Chinese model with a VPN, and then attempt to run it at home by building your own GPU cluster but these large models require quite expensive hardware to run on and so it makes it less likely than anyone would invest that much capital to do something that is illegal. There's no way for them to sell a legal service using those tokens. So it can only be strictly for personal use (the Govt won't care because very few people will have that kind of money and risk appetite). The other option will be that there will be some shady third-party providers in foreign countries who are willing to sell tokens from these models to US consumers knowingly.

Re: Who's afraid of Chinese models?

#128

Post by wmf »

alizaki wrote: post #117

There is no “Chinese LLM”. Each “lab” is distinct and their models behavior is as unique as those from OpenAI and Anthropic

Somehow a certain set of labs are all releasing open weights and a certain other set of labs are closed weights.

Re: Who's afraid of Chinese models?

#129

Post by onesociety2022 »

tristanj wrote: post #29

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…

But there a ton of other VCs who poured money into SaaS businesses. They have the opposite incentive. They want tokens to be cheap like a commodity so the value accrues in the SaaS/app layer.

Re: Who's afraid of Chinese models?

#130

Post by bg24 »

I think in general rest of the world needs to take notice (not saying afraid), starting with the US. It cannot be taken for granted that China's frontier labs will be a few months behind. They might be at par or exceed.

The lessons from steel, solar and EV needs to be learned by all lawmakers. You have to respect and learn from how China Government puts the system in place for complete industry takeover and they have been very good at it. The problem with AI is that democracies will be inherently slow in adopting AI, unless something changes in the system.

At minimum, every democratic Government (US, Europe, India) need to build long-term AI vision and execute that no matter which party comes to power. Additionally, be ruthless about protecting domestic labs. It can only be possible if the intelligence pricing by domestic labs per productive task is in the similar range as open-weights models. Right now, it is not the case, even if the article gives the example of Sol vs K3.

Protecting domestic labs means not bailout, but fast track to cheapest energy, fast track approval for data centers, enforce some guardrails so customers get to use the open weights models only hosted in the country by US (or Europe) businesses. Without these protections, it might be a slow death.

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