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Who's afraid of Chinese models?

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Re: Who's afraid of Chinese models?

#221

Post by jjfoooo4 »

solumunus wrote: post #37
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…

I think they stickiness is less about the difficulty of switching and more about the lack of desire. I’ve been using Claude since day one, it works well and I’m happy, I like it. I’m sure Codex is good too. Switching from one to the other certainly isn’t going to be a game changer, the discourse shows me the differences are marginal. Probably the only reasons I would seek change are economical.

A sticky product is one that switching away from creates a major hassle. Which means the user will pay more to avoid said hassle.

“I don’t really have a strong preference between the two” is another way of saying “the product isn’t sticky”, which is another way of saying “this provider has very little room to increase margins”

Re: Who's afraid of Chinese models?

#222

Post by 0x38B »

Excellent article; the argument towards the end for allowing distillation for US companies is compelling:

> To that end, here’s an even more interesting question around 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?

> In fact, this paradox is the solution. I believe that open weight models are good for innovation (and, per the above, I think that labs on the frontier will be fine), 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. Stopping distillation — which is literally just querying the API — is nearly impossible; the U.S. should go the other way and lean into a new copyright policy that both indemnifies the labs and also guarantees that what they learned fuels further innovation for everyone else.

Re: Who's afraid of Chinese models?

#224

Post by exhilaration »

Aurornis wrote: post #92
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…

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…

I'm confused, I work at a big giant Fortune 500, we all get GitHub Copilot subscriptionsn - we can switch between OpenAI and Anthropic models with just a click in Visual Studio. There's no stickiness at all. They just made us go through a training after the price hikes about how to choose between models for the best cost/benefit ratio.

Re: Who's afraid of Chinese models?

#225

Post by Ericson2314 »

hamandcheese wrote: post #166
onesociety2022 wrote: post #129

Earlier quoted context omitted.

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.

Yeah maybe *both" sass and training companies are wiped, imagine that!

Re: Who's afraid of Chinese models?

#226

Post by horacemorace »

ChaitanyaSai wrote: post #215
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…

The thing I do not understand here because it seems obvious: AI will be a commodity market and you simply cannot have a large PE multiple. So the valuations imagine a global commodity monopoly or duopoly coupled with the increased intelligence still disallowing other suppliers from becoming competitive? Without any network effects to help?

Perhaps to moneymen the difference between “ChatGPT” and the technology behind it isnt’t obvious. I’ve been very surprised at how few otherwise smart people are completely in the dark about how capable current models are.

As soon as manufacturing starts building this stuff more, it will commoditize. The hardware prices won’t be terribly larger than the original. We’ll have a “Bambu labs” style company to make the AI OS, whatever that is.

Re: Who's afraid of Chinese models?

#227

Post by analyte123 »

ehnto wrote: post #219
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…

US running costs are higher than in China, because the US lags behind in energy, has higher real estate costs, and wage costs are higher. Eventually we will hit a "good enough for cheap enough" and frontier models will hit diminishing returns (if they haven't already for a lot of types of work) Don't think the rest of the world will sit on their hands while the US soaks up chips either, demand gets filled and if the…

The US does not lag behind in energy. Industrial electricity prices in most places in the US are competitive with China, or even cheaper.

Re: Who's afraid of Chinese models?

#228

Post by larrysalibra »

mediaman wrote: post #62
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 (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…

Ben's article "distills" down to 2 reasons that US frontier labs shouldn't be "afraid":

1. US frontier lab unit economics are better 2. US frontier labs are moving up the stack making tools that are "stickiness" and will prevent users from switching.

For 1...he doesn't provide any evidence for US lab unit economics being better...the major input to unit economics is electricity...which is cheaper in China. And building data centers and connecting them to electricity is both cheaper and an order of magnitude faster in China. The main input that US labs might have an advantage in is in cost/access to chips, but that given the level of chip investment in China it seems unlikely to hold.

For 2...there's little evidence these tools are sticky. At least in programming, the trend seems to be tools like opencode that support multiple models and providers.

And even when they are sort of sticky, as we know on hacker news, people figure out how to point the tools they like to competing models even when the app doesn't official support it.

And every improvement in model capability makes it increasingly easier to make your own tools.

Wrote more on this in a blog post that has an earlier HN discussion: https://news.ycombinator.com/item?id=48982061

Direct link: https://larrysalibra.com/ben-thompson-is-wrong-us-frontier-l...

Re: Who's afraid of Chinese models?

#229

Post by Ericson2314 »

nl wrote: post #95
chrsw wrote: post #55

Earlier quoted context omitted.

Correct. We need open weights, open code and open data. If nobody else can reproduce what someone did there will always be security questions. Even if we can reproduce it there could still be security concerns but it's more realistic to investigate yourself.

I'm all for open models, but people seem to misunderstand what they are. They aren't the same thing as open source code! > open weights, open code and open data Even if you have all these things you still can't replicate a model because of randomness. You can backdoor a model with less than 1000 examples and it is impossible to detect.

Deterministic seed

Re: Who's afraid of Chinese models?

#230

Post by protocolture »

0x38B wrote: post #222

Excellent article; the argument towards the end for allowing distillation for US companies is compelling: > To that end, here’s an even more interesting question around 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 ex…

Very good point.

That would prevent the facebook strategy of sucking up MySpace users and then defending TOS that prevent other social media apps from doing the same to them.

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