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Who's afraid of Chinese models?

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Re: Who's afraid of Chinese models?

#161

Post by skeptic_ai »

wordpad wrote: post #132
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…

I think everyone understands models will be a commodity. Its the user base (with ads and upselling) and proprietary wrappers which will make money for typical customer. Even enterprise customers arent going to be spending a lot on tokens. Once labs no longer have to subsidize trainings tokens costs will drop 10x and once models get burned on chips costs will drop 10x more and you physically won't be able to burn sign…

[dead]

Re: Who's afraid of Chinese models?

#162

Post by spenvo »

c0decracker wrote: post #154
spenvo wrote: post #148

"Anthropic and OpenAI likely have among the lowest costs per unit of frontier-quality intelligence" That's a big claim that his whole thesis rests on but is largely not backed up. Where are the apples-to-apples tokens-to-answer benchmarks that he's using - doesn't look like there are any, just a handwavy implication that US models are more token efficient, which they may be. But how is there so little effort in estab…

But.. if you are running Chinese model in the US, what difference does it make? Isn't the whole "scare" (khm khm) with Kimis is that now I don't need Claude, cause I can run Kimi on my own hardware in my own datacenter and it's maybe not as good as Claude July edition but it's is as good as Claude January edition.

Sure, and I think that flexibility further undercuts his "frontier labs will be fine" take, which depends on top US labs having pricing power.

Re: Who's afraid of Chinese models?

#163

Post by nekusar »

matheusmoreira wrote: post #142
vrm wrote: post #110

Earlier quoted context omitted.

good luck running a 2.4T model on any local hardware. it’s not gonna happen. the arrow is to specialized hardware at least for the smartest models

I have hope it'll happen one day, even if not now.

Already is possible. On a machine with 32GB ram, and NO gpu. Just need a large SSD or NVME. Streams from disk to memory.

https://github.com/JustVugg/colibri

Re: Who's afraid of Chinese models?

#164

Post by bushbaba »

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…

agreed, my F500 company switched off claude code to copilot in 30 days. All 5k+ engineers. That is the fastest migration i've ever witnessed. This includes switching all our agents from Claude SDK to Copilot SDK.

Re: Who's afraid of Chinese models?

#165

Post by abernard1 »

ignoramous wrote: post #155
abernard1 wrote: post #118

Earlier quoted context omitted.

" - The highest tier Chinese models are not more economical than US frontier models. Try GLM 5.2 and see how much it costs to do real work. I did, and it was more expensive than GPT 5.6." This is a flatly false statement for most things powering backend applications. The AI consumer "doing real work" model, either for analysis, chat, or coding could well be more cost effective with closed frontier models. But most of…

> "The highest tier Chinese models are not more economical than US frontier models. Try GLM 5.2 and see how much it costs to do real work. I did, and it was more expensive than GPT 5.6." This is a flatly false statement. It may not be false but may be a "category error" [0]. Reserved GPU pricing & bulk inference pricing is 3x to 6x cheaper than "API rates", but renting your own GPU cluster (in this crunch) to run a 6…

Fair. Too strong a statement.

But much like Ben's point that commoditization is a relatively novel concept to many in tech, it's not the consumer AI applications at risk of commoditization. They have distribution there.

It's the literally millions of engineers who are updating codebases with tools replacing workers partially or wholly. It's the supply-side where there's compression, and no need for distribution.

I would argue, given the enormity of the existing SaaS stack and how it integrates with the human machinery of personnel, that's where volume is. And that is clearly cheaper and a home run.

Commoditizing a ~$100B AI consumer market is no small feat. Commoditizing 20% of the $500B SaaS market, to say nothing of the underlying systems in the who-knows-how-many trillions "Big Tech" market (you're obligated to say that like the Kool Aid man), is shocking.

Re: Who's afraid of Chinese models?

#166

Post by hamandcheese »

onesociety2022 wrote: post #129
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.

Cheap tokens only benefits SaaS that depends on AI. Otherwise, cheap tokens means it is only more cost effective than it already is to cut out the SaaS and build instead of buy.

Re: Who's afraid of Chinese models?

#167

Post by ineedaj0b »

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…

Not sure most of money is from VCs.

Re: Who's afraid of Chinese models?

#168

Post by techpression »

solumunus wrote: post #35
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…

The valuations are unjustified even at the prices they’re charging now. They’re going to try their best to offload these investments into our pensions before the inevitable crash.

Apparently it’s already happening to a degree, wether it continues or not (or even is relevant) is not really my area of expertise.

https://finance.yahoo.com/markets/stocks/articles/goldman-sa...

Re: Who's afraid of Chinese models?

#169

Post by zuzululu »

My thinking is that with the current narratives out of washington we are on track for a ban on Chinese models and possibly sanctions against Chinese AI companies

I think it is the right move to protect American interests

Re: Who's afraid of Chinese models?

#170

Post by dansquizsoft »

OleksandrC wrote: post #6

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 perspect…

Facts, I was able to code a personal self improving harness in a weekend (something a bit more similar to Hermes or OpenClaw at the time but with a more expansive set of features for my use cases and requirements) and it works great for 90% of the tasks I would use Claude Code or Codex (now ChatGPT App) for, with the remaining 10% being able to be implemented with a few more prompts from within the harness itself.

For this reason alone I would also argue that the idea about an agent harness being sticky is a non-starter long-term.

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