undefined | Better HN

0 pointsthephyber1mo ago0 comments

Not all AI companies are the same.

Some are piling on masses of debt to built capacity (eg. Oracle). Others are just reinvesting the profits from the rest of their company (eg. Google, Meta).

Anthropic’s moat is their best tool, Claude Code.

OpenAI’s moat is the brand of ChatGPT, once the fastest growing app in the history of the world.

It’s possible that open weight models keep pace, but it’s also possible that the investment to train them becomes prohibitively expensive and open weight models cease to keep pace with the large foundation model companies.

0 comments

6 comments · 2 top-level

2ndorderthought1mo ago· 3 in thread

I really don't think open models will lose. I think they are cheaper to train because they have to be more efficient than the monstrosities we have now.

There is no theory that says the current frontier models cannot exist in models with 1/100th the compute waste ;). When we start trending in that direction, and oh wow we truly are, there will be no reason for these services. You could run them on your own hardware without serious investments.

The moat openai and anthropic have is them among others have attempted to buy all of the computer hardware for the next two years. That's intentional. They know the only existential threat to them is anyone coming up with a way to do this better than them. It's already happened and it's going to become more and more divergent.

drivebyhooting1mo ago

I’m interested in learning more about your theory that these models can be trained more cheaply. Is anyone doing it from scratch, rather than adversarial distillation?

2ndorderthought1mo ago

It is a lot cheaper to train a 27b model such as qwen3.6 which you can even vibe code or agentic code with than it is to train a 1t+ parameter model. It runs on a single commodity GPU for goodness sake

It's not a theory. These smaller models that are coming out are huge advances for the field.

I can't comment on companies training practices. That would be proprietary stuff I guess. I think the claims that the advances being made are due to distillation alone are completely unfair. The advances alone are not just data.

freeone30001mo ago

It almost doesn’t matter if it’s trained using adversarial distillation - if it’s nearly as good, and one-hundredth the cost, the choice is obvious.

matthewdgreen1mo ago· 1 in thread

Open weight models will keep pace because capable open-weight models are China's strategy for preventing a closed takeover of AI by the West.

thephyberOP1mo ago

US megatechs stole copyrighted data to train their. Hyper expensive models.

Chinese megatechs stole copyrighted data AND trained their models on derivative / synthetic data that came from the US foundation models.

I’m happy Chinese foundation model trainers were able to use Huawei (homegrown) hardware to train their models (also because having Nvidia dominate that sector is terrible for competition), but if Chinese megatech companies are just deriving their open weights models from US companies, then this is just an IP theft exercise.

j / k navigate · click thread line to collapse