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Access to frontier AI will soon be limited by economic and security constraints

writing.antonleicht.me

181–190 of 227 posts

Re: Access to frontier AI will soon be limited by economic and security constraints

#181
post #33
post #22

Earlier quoted context omitted.

I wish it was true. I would gladly use a GPT 5.2 high model equivalent for coding (6 months old) if it was offered cheaper by Deepseek or Kimi. And I'm sure that's an extremely prevalent opinion by the millions of Claude and Codex users who are bothered by the costs. However, they just don't perform that well in practice. That's the real issue. You can actually see it when you move away from open benchmarks. Deep see…

I 100% agree with you, but I've been convinced over the last year that it's a time and scale issue, not anything fundamental. The Chinese models right now are in a weird spot. Compared to the frontiers, both their pre and post training is woeful - tiny, resource constrained in every dimension including human, slow. I'd compare it to OpenAI 5 years ago except I think even then OpenAI had way more! But they "cheat" qui…

> I'd compare it to OpenAI 5 years ago except I think even then OpenAI had way more!

Say what? 5 years ago OpenAI had received around $139 million in funding, and they’d just come out with GPT3 with 175B parameters, a 2048 context window, trained on 300B tokens on a 10,000 V100 cluster which would have cost maybe $4-13 million at the time for their training run.

Meanwhile Deepseek V3’s famously frugal training was $5M, and Chinese AI companies are raising billions in funding. Sure American AI companies are raising tens (and maybe hundreds in the case of OpenAI, if you count their circular funding rounds) of billions but they’re grossly inefficient, and we’ve already hit the limits of the scaling laws where there’s little point in increasing the number of parameters of a model.

Re: Access to frontier AI will soon be limited by economic and security constraints

#182
post #22
post #8

I am no-where near as concerned by this as I was a year ago, when I was expecting the axe to fall at any moment before the Chinese labs achieved some sort of escape velocity. I now think it's too late, all the cats are out of all the bags, there's no moat except maybe a temporal one of a few months, the genie is out of the bottle. There is no secret sauce the US labs have that the Chinese ones don't, or won't have so…

I wish it was true. I would gladly use a GPT 5.2 high model equivalent for coding (6 months old) if it was offered cheaper by Deepseek or Kimi. And I'm sure that's an extremely prevalent opinion by the millions of Claude and Codex users who are bothered by the costs. However, they just don't perform that well in practice. That's the real issue. You can actually see it when you move away from open benchmarks. Deep see…

If you want something close to claude, use glm 5.1 with claude code. Their subscription price is no longer x10 times cheaper now though (at best 2 times cheaper)

Re: Access to frontier AI will soon be limited by economic and security constraints

#183
post #8

I am no-where near as concerned by this as I was a year ago, when I was expecting the axe to fall at any moment before the Chinese labs achieved some sort of escape velocity. I now think it's too late, all the cats are out of all the bags, there's no moat except maybe a temporal one of a few months, the genie is out of the bottle. There is no secret sauce the US labs have that the Chinese ones don't, or won't have so…

Which is why, I believe, the big AI companies are starting to focus and roll out vertical products more. They know that the models themselves aren't sticky, people can easily switch between different models with not much hassle.

I think the big AI companies are trying to transform into the next Microsoft. Completely capture both enterprise and consumers.

Re: Access to frontier AI will soon be limited by economic and security constraints

#184

I think we'll know this is true when deepseek becomes illegal in the US. I tried to sign up for deepseek API access directly from the company out of gratitude for the open source contribution (deepseek.com) but payments are blocked by US government rules.

The point of open weight models is not having to rely on specific providers for them.

Re: Access to frontier AI will soon be limited by economic and security constraints

#185
post #8

I am no-where near as concerned by this as I was a year ago, when I was expecting the axe to fall at any moment before the Chinese labs achieved some sort of escape velocity. I now think it's too late, all the cats are out of all the bags, there's no moat except maybe a temporal one of a few months, the genie is out of the bottle. There is no secret sauce the US labs have that the Chinese ones don't, or won't have so…

Which is why, I believe, the big AI companies are starting to focus and roll out vertical products more. They know that the models themselves aren't sticky, people can easily switch between different models with not much hassle. I think the big AI companies are trying to transform into the next Microsoft. Completely capture both enterprise and consumers.

"I think the big AI companies are trying to transform into the next Microsoft. Completely capture both enterprise and consumers."

That is going to be a failing strategy though. Whatever OpenAI or Anthropic implement, Microsoft and Google can trivially copy and provide to their existing customers that are already deeply invested in their platforms.

Re: Access to frontier AI will soon be limited by economic and security constraints

#186

When intelligence is a commercial commodity, it is only bound to happen that the rich gatekeep it to secure their socioeconomic status. But, I think, with every revolution, hierarchies have only historically fallen only for the former serfs to rise. The industrial revolution, the renaissance -> all were marked by an massive shift in the socioeconomic status and the rise of the middle class. I think AGI, when it happe…

I mean what if this is an inverse revolution?

Re: Access to frontier AI will soon be limited by economic and security constraints

#188
post #64
post #4

No mention of open weights anywhere in the piece, which is weird. Qwen, Llama, DeepSeek are months behind frontier, not years. If you're a European startup worried about getting cut off from Anthropic's API in 2027, the real question is what the open-weight frontier looks like then. Probably pretty capable. That undercuts most of the doom scenario. Also, he concedes Mythos-level capabilities will be cheap next year,…

Open weights will remain open only if they’re significantly worse than the frontier weights. Before you challenge with benchmarks, consider the labs which release open weight models have internal testing and unpublished results.

> Open weights will remain open only if they’re significantly worse than the frontier weights.

This makes the assumption that you earn more money by selling access to the model than by releasing the weights. That might be true for a company, but a US adversary might profit more from tanking the US economy. NVIDIA's stock dropped by 17% in a single day after DeepSeek-R1 was released, and the share of tech companies in the S&P 500 has only risen since then.

Re: Access to frontier AI will soon be limited by economic and security constraints

#189
post #58

Earlier quoted context omitted.

It would be awful if running models locally became the primary way of using LLMs. On dedicated servers sharing GPUs across requests, energy usage and environmental impact is way lower overall than if everyone and their mother suddenly needs beefy GPUs. It’s the equivalent of everyone commuting alone in their own car instead of a train picking up hundreds at once.

Maybe people would target their use more appropriately, then.

Just like people would drive their car as little as possible out of concern for the environment..?

Re: Access to frontier AI will soon be limited by economic and security constraints

#190
post #58

Earlier quoted context omitted.

It would be awful if running models locally became the primary way of using LLMs. On dedicated servers sharing GPUs across requests, energy usage and environmental impact is way lower overall than if everyone and their mother suddenly needs beefy GPUs. It’s the equivalent of everyone commuting alone in their own car instead of a train picking up hundreds at once.

You can batch requests when running locally too, if you're using a model with low-enough requirements for KV-cache; essentially targeting the same resource efficiencies that the big providers rely on. This is useful since it gives you more compute throughput "for free" during decode, even when running on very limited hardware.

That’s still orders of magnitude less efficient, and also not how most people use AI, or probably will use AI.
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