back
1 comments
Mostly because it's generally a bad idea for government to try to compete with a brand new tech industry with hundreds of billions in private capital developing commercial models. If the American private industry does actually wash out vs Chinese open models there might be talent available for them to put money into, so maybe they are just preparing for that scenario in the meantime.
Commoditizing AI models serves the interests of just about everybody except for a relative handful of people in San Francisco. The more decentralized control of the technology is, the more its benefits can be realized by businesses and individuals rather than becoming a black hole of monopolistic rent seeking.
Sure, but it shouldn't be government operating on the frontier of new technology
I don’t quite understand what the argument is. Government does as a matter of fact operate on the frontier of new technology. (It’s how we got the web.) Why shouldn’t it, exactly?

Also, the US has been involved in AI research since the 1940s. So it’s not exactly a new thing.

> don’t quite understand what the argument is

Government has, practically and relatively speaking, infinite resources and a monopoly on violence. You can’t compete with it in any true sense.

Set a track record of Sherlocking private industry and you won’t have one. In countries that regularly nationalise and expropriate, the government (and its cronies) have to do basically all private investment and innovation, and resultingly, there tends to be very little of the latter.

The argument is that there is a difference between fundamental research and trying to ship finished products and satisfy commercial demand.

The government was involved in basic internet research. It didnt try to operate pets.com

LLMs aren't finished products, though. And since they are basically a distillation of the collective works of all of humanity, it would make a lot of sense for them to wind up as public goods rather than some special advantage held by a select few.
Im not arguing that would be a bad spot eventually, like water or electricity distribution. Right now it's a highly Dynamic field though and changing On a monthly basis. I don't think it makes sense for the US government to try to Duke it out and drive all of the competitors out of business.
we're about witness the realization that "here's a tech that can make us a whole bunch of money" is actually "here's tech that will establish the next hegemony." american companies may compete with chinese companies on the former. only the USG can compete with the PRC on the former.
The USG getting involved might actually harm US AI efforts. It's not just about money. Who would want to use Claude or ChatGPT if it were run by the US government? Yet these products are essential for gathering training data.
You're kidding yourself if you don't realize that the US gov can have access to any data they want in any of these US-based products. That's why they consider so important to "win" the development race for LLMs. It is a matter of continuing to access and control data that most of the world needs, as China has already closed the door to them.
> Mostly because it's generally a bad idea for government to try to compete with a brand new tech industry with hundreds of billions in private capital developing commercial models.

I don't see why it's a bad idea if the models are as dangerous as this brand new tech industry claims they are.

The more dangerous this tech is, the better the idea looks. Can you explain?

The American attitude is generally to let private companies build up a new industry so it can create jobs and pay taxes. However, in the LLM race, the Chinese open weight playbook pretty much killed that. China has basically commoditized LLMs. Chinese models are good enough, so the race has come down to who can offer the cheapest tokens.
Chinese open weight models are great for this turn, but American private models generate orders of magnitude more cashflow. This cashflow = investment in training future models. It's unclear how Chinese open weight companies are going to compete in future rounds if they can't raise the same capital for training runs.

The American business model is exceedingly efficient at building large businesses from zero. I wouldn't dismiss it as just a jobs creation thing.

It’s unclear where American labs future capital will come from. They pretty much exhausted private options at that point and it’s not clear how successful an ipo would be at the current time
> It’s unclear where American labs future capital will come from.

It’s unclear to you, perhaps? But they’ll raise funds and/or debt as needed in the US capital markets as they have been doing.

> They pretty much exhausted private options at that point

I don’t think this is true. The evidence is that they keep raising funding for build.

> it’s not clear how successful an ipo would be at the current time

It’s always unclear, but also IPO success doesn’t necessarily translate into long term business success.

Obviously to me, I express things from my point of view.

Raising too much from debt is a bit dangerous if you plan to go public relatively soon and don’t have a good story for it (I don’t believe they have one). You can continue raising from VCs, but at some point the valuation and dilution starts to become a real issue, and will make your ipo even more difficult. Their options are pretty much limited to raising money from hyperscalers (with required compute spending, so more circular funding), which is what they are doing, but you cannot do that infinitely without having a good story to tell Microsoft/Google/Amazon investors. The market is more skeptical than it was a few months ago, I’m not convinced you can do that for years to come

I think as a counter point we continue to see investment and buildout. What do you mean the market is more skeptical? Of course the market doesn’t really have an opinion per se and aren’t all of these companies growing in valuation, revenues, and profits? At least the public ones.
> China has basically commoditized LLMs

What do you mean by "basically"?

Why are Anthropic's and OpenAI's annualized revenue about $50B each?

LLMs need massive amounts of compute to compete, so I wouldn't claim that the great (and leading, and likely to continue to lead) LLMs are commodities end-to-end, even if the non-executing-at-scale LLMs files and IP are commoditized. The execute, the compute, that is what breathes life into the model, which is otherwise weak or dead.

> Why are Anthropic's and OpenAI's annualized revenue about $50B each?

I too can have $50B revenues by selling dollars for 50 cents each, and in the process I'll make a smaller loss than they do.

OpenAI's annual profit is $0,000,000,000,000
Expecting profit during hypergrowth is silly
OpenAI's hypergrowth year was 2023, they have steadily been losing market share over the past year while taking record losses.