The mobile device market (~$500 billion annually) is comparable in scale to the AI data center market, representing a huge, largely untapped substrate of 'dark compute' for on-device intelligence.

75:30devices can can can be extremely useful and you've seen like that that market itself by the way just the mobile kind of business is $500 billion market is absolutely insane and um it is as as big as kind of the data center kind of market so you can imagine like There is there's a parallel here to be made like you know the efficient markets you know and also constrained intelligence market

75:49it's something that liquidi is going after [snorts] laptop market you know like the let's say wearables robotics manufacturing IoT kind of systems anywhere that we have like a processor inside a system liquid can bring in intelligence on top of that so the aspirational goal that I have is that like we really build an intelligence layer on top of the diverse formats of hardware that is out there and and

76:12processors that are available in the world. You know, that that would be something that I would want to have. >> I'm glad you said that stat. I had that noted to make a point of at some point. It's worth repeating. The global annual smartphone market is about $500 billion for all of the hundreds of billions that are going into the data center buildout. And it will get bigger than the

76:34smartphone market, but that's it's only now getting to the scale and getting bigger than the the annual smartphone market. So that is a that there's a lot of dark compute out there from an intelligence perspective that is not being anywhere close to maximum and that does not include the laptop market. So there's a trillion dollars generally speaking worth of compute going out into the world on an annual basis that are

76:56sitting in people's desks and pockets and it's there's a massive substrate there to >> take advantage of >> and we need to do it you know like we need to we need to take advantage of it. I mean because we don't have enough energy to host it. I feel like like we we are realizing it right now like how difficult it is like to really power this format of intelligence that we have

77:16like at scale we really have to have be work smart we cannot just do the simplest format or maybe more more constrained use cases like let's say if you have like a oneshot uh uh let's say predictive task or maybe data extraction task and stuff you don't want to call the fanciest type of intelligence like the meatless level kind of model to perform data extraction for you you can