Yang Li says that there are also worries that American models are currently artificially cheap for paying customers.

It's no secret that OpenAI and Anthropic currently subsidize costs.

And one day that will have to come down, in which case there's no certainty.

And also, there's no certainty in terms of knowing what data has gone into.

training this AI engine.

And also you have very little control about where the data goes to be processed.

So we're working with 24 PLCs at the moment.

This has paid for time on a supercomputer to develop their AI

So today, what are the use cases? Who are your customers?

Sure.

So I think we'd like to say we have earned the right to call ourselves an AI model lab.

We definitely started our life as post-training and customizing other people's models, whether it's a Chinese open source model or we were very early sort of partners with OpenAI to, you know, even post-train GPT-4.

We were part of the post-training alpha.

Been fortunate enough to deal with directly with Sam Altman and a lot of the senior guys there.

We started our life customizing models to focus on what our customers wanted, right? For us, because we've always wanted to build AI-enabled coding tools and workflows and make software engineers' lives better, we essentially started doubling down and making models better at navigating complex code bases, undocumented or underdocumented code bases, legacy coding languages.

I wanna just ask you what you think Sovereign AI means for our country and for any country going after it.

According

to the data we collected, most of the viewers for the VTuber are young generation.

Their age is about maybe teenagers and or the age who is under 25.

So what place does PTS have in the world of VTubing? There's two kinds of job or works we do.

The first one is the daily VTubing.

So far we have three VTubers, Bobo and Nancy and Kevin.

Bobo, the VTuber, she is targeting the kids.

What public service content are you providing them with?

So it's really going to be quite different from, say, the cloud AI providers that are out there at the moment.

I think on functionality, it's going to be very similar.

But I think for people who are concerned in terms of compliance, in terms of cost, you know, it's on-prem sort of AI models are becoming more in focus, right? I think anyone who's been following the news can see the, not quite panic, the concern about token costs accelerating, right? Uber came out this month to say, you know, they blew their entire year's budget in a single quarter.

The good thing about having an on-prem AI is that, you know, once you've invested, the capital cost of installing GPUs, you know, you're capped.

It's a cost that can be amortized.

And actually, at that point, the more you use the models, actually, the cost per token decreases because it's a fixed cost.

Secondly, obviously, the compliance, there is this sectors or there are companies that will not feel comfortable with either using, you know, a cloud version or through sending their data through an API to be processed in the black box.

Do you think that perhaps you should maybe advise the government to ditch Palantir and get them out and take over from there?