The US is significantly behind China in the development of competitive open-weight AI models, though new American 'neo-labs' are beginning to emerge.

31:42the deliverer of that to those models. Do do you feel a sense of responsibility for that? >> So we we do feel a responsibility to have safe access for all these models. Like um customer trust is like our you know, paramount goal. Uh if if one of these models is unsafe to use, you know, generally considered unsafe, we pull it from the platform. If there's like a way to use it in an unsafe way, I mean

32:09there's a way to use like all the models in an unsafe way. And then we believe in using technology to make it safe and to like work with the model labs themselves to figure out how they're doing it on their side so that we can be state of the art or better. We spend an enormous amount of time um making sure that like that our practices like match with the best

32:36things that we're seeing coming out of the the labs or better. Um and because we're like a very good because we're we're a way of like exploring all the models and finding them for the first time. Um we're a good focal point for like deploying safety measures across your whole company. For example, we have prompt injection protection. You can just turn it on and immediately flag prompts that look

33:02like prompt injection um that's trying to happen. Um we have PII reduction. We have uh we have like a couple different things that you can automatically just turn on with a click and and get an added safety layer on top of all of your inference. Um and we build that so that enterprises feel like they can safely like deploy new models and that their their um employees can try them out. I think of

33:27the models a little bit like the internet. You know, you can't you you you can't just like ban the internet at your company because there are there's some like bad things on the internet. Um you can create guardrails and you should. You need to use AI to build the best possible guardrails that you can. So, that's what we're doing. >> you actually know what's going on within

33:51Moonshot or Alibaba with Kuan? Like these are these are incredibly secretive organizations in the depths of China. >> Can't pretend I know like what's going on inside of them. As a US company, like we're going to follow like like the best practices of what happens in the US to make sure that we're not doing something irresponsible. >> What do you think US companies are more nervous of, frontier models or Chinese

34:17models? >> I think they're they're more nervous about frontier models usually. Part because there's just like a a much there's much more confusion around the data policy about what's like actually happening to the prompts they're sending and um where they're being stored and how they're being looked at. Um and you can't run them on your own machine or in a provider of your choice. Uh and so that just immediately creates

34:46all of this uncertainty in a lot of enterprises. And [snorts] it's uncertainty that they can also pattern match. It's very similar to like you know, running on their own infra versus running in their VPC. Um and and knowing like who can see the data. Um so like >> exactly? Like they're more nervous of like US companies headquartered in Silicon Valley where you can see and touch and