Switching from GPUs means installing a driver, not rewriting code

Have you ever said, we are not a good match? Like, folks reach out to you or you had the conversation and then you realize this is gonna be more like a, loving us rather than contributing.

Yeah, there's been some people like, I'm training this Frontier SLM model. And it's like, yeah, I guess that's cool, but we really want you to be weird and try to do something novel and new. In reality, we do have limited capacity. We have one server rack and we have limited power. So we can't serve a hundred people at the same time until we build our data center, spoiler alert, but.

Hmm. you

That is not to me like, we have to be bit picky. It's... Yeah.

Can you walk us through what exactly, I know you can't reveal everything, but at least if I am today, let's simulate the environment that we are having a conversation, and then you ask me to give it a chance to the scale. Why would I do this? Why would I leave my setup? I have my frustrations, of course, but then there is the over the switch costs. What is the problem that you give me? And also what is the reasoning behind your product that is gonna step by step just get better?

Yeah. Yeah. Okay, cool. So if you're a researcher, you're doing research, you're writing code in like Jax or PyTorch or whatever public ML framework. Torch is another conversation, but there's Torch MLIR and stuff, we do support it currently, but you would essentially just take your code and install our drivers and that would be it. All you have to do is click on the download button and then maybe the install button or like just do like whatever distro you're on on Linux like suda apt install on xp drivers and that's it. So for the switching cost of your software like when I spoke with OpenAI with this like they had the switching cost is like not like oh can we swap out the hardware and then play with it. It's a huge huge like investment for any AI lab to just rewrite all of the code.