[Danox]

They could, but they don’t have to. The Chinese have beaten them to it, and the rest of the world will benefit from it and the circle will be complete once the models get a little bit faster/smaller and the localized hardware does the same and it will, it is inevitable.

The one thing that is sort of ironic or bad is that between Russia and the Ukraine there’s a large number of mathematically inclined people that if it wasn’t for the Putin war, their brain power working on AI models would have probably pushed open source down the road, even faster…

[chasd00]

> The Chinese have beaten them to it, and the rest of the world will benefit from it and the circle will be complete once the models get a little bit faster/smaller and the localized hardware does the same and it will, it is inevitable.

This reads just like "AGI is 2 years away", I'll go set my calendar...

[idontwantthis]

But I still don't get it. Like China could be come the world's leading producer of chocolate...if they started giving away chocolate for free. Would we be having this conversation saying that Switzerland lost because they were greedy and protectionist and didn't decide to give away their chocolate for free first (I realize Switzerland probably isn't actually the world's top producer of chocolate).

[gmerc]

How did the US become the leader in SaaS

[randbyte]

Long history of open source projects already have answers on how to monetize a free and complex open source product.

- Low development cost: collaborative efforts from open source contributors, innovative model training and serving for llm (Chinese models costs a fraction to train and their local chip design and manufacturing are catching up, plus cheap electricity)

- monetizing by selling hosted services, while leaving the core product free to tinker with / self host. China’s gdp is 2/3 of the US and it’s already a huge market for AI - which OAI and A\ don’t enter.

- for (the US) market that they can’t enter, let the US cloud providers to do free marketing / advocacy for them. Gaining share of mind. It costs them nothing.

[yorwba]

The idea that Chinese models cost less to train seems to be based on that one time DeepSeek estimated the training cost for their V3 model at GPU rental rates as $5 million, and comparing this to other companies' entire R&D budgets. Yet DeepSeek raised $7 billion of fresh money last month, enough to train more than 1000 such models. What gives?

- You need to train lots of experimental models to dial in the training process just right for the one model that actually gets released in the end. Fortunately, these can be smaller.

- However, everyone is training much bigger models now, and doing a lot of RL rollouts on top.

- You can't get the GPUs for this piecemeal at rental rates because they need to be wired together using high-bandwidth interconnects.

- Nvidia GPUs are much more expensive in China, and local alternatives are still immature and not as efficient. Some companies have gotten around this using data centers in Singapore, which should tell you that electricity prices are not the primary consideration.

- The one line item where Chinese companies can probably save quite a bit of money is salaries for rank-and-file researchers.

In any case, they need to make back that money somehow. Giving away freebies isn't going to cut it.