Um, so in other news, I know layups are top of mind, but there were also some updates this week around um and a question around employee device
tracking. So can you share more on employee device tracking? Um, I think the way that it was announced left folks Yeah. >> So okay, let's let's talk
about what we're doing. Um, you know, like Alex just said, going into what makes these AI models great,
right? There's basically a few key ingredients. There's getting the research and the architecture good. There's having good infrastructure which is
both the quantity of compute but like as important if not more is also just like how efficiently can you use it? How reliable is it? What like what is
the quality of that? And then the third piece which is in some ways it's hard to say that any of
these are more important than the other because they're all necessary is effectively the data and what knowledge it learns. Um, so we're in a phase
where basically the AI models learn from having really from watching really smart people do things. And if you're trying to get it to be able to be
able to do certain capabilities, having it be able to observe really smart people doing those things is
very important. So there are a few examples of where we're trying to do this across the company because one um one basic insight and hypothesis that
we have is that a lot of data generation across the field is done by these like contract companies. Um, and Alex knows a bunch about this because he
ran one before coming here, but um, in general, the average intelligence of the people who are at this
company is significantly higher than the average set of people that you can get to do tasks if you're working through the contract um, through these
contractors. So if we're trying to teach the models coding for example, then having people internally uh build tools that or solve tasks that um that
help teach the model how to code, we think is going to dramatically increase our model's coding
ability faster than what others in the industry have the capability to do who don't have thousands and thousands of extremely strong engineers at
their company. So that's one example. Another thing that our that our system needs to be very good at is using computers. So the way that you get a
system to be good at using computers is by having it watch really smart people use computers. So that's
basically the essence of what we are trying to do here. Um we are we're rolling it out in a way that is like you know it's like we're basically we're
not like actually no human or anything is like looking at or watching what your um what people are doing on their computers. just the content is sort
of um you know stripped out um in like as as much as is possible. Um it's like none of the data is
being used for like looking at what people are doing or surveillance or performance tracking or anything like that. It's purely just like we are using
this to feed a very large amount of content into the AI model so that way it can learn how smart people use computers to accomplish tasks. U I think
that this is going to be a very big advantage um if we can do it. So anyway, that's what we're
trying to do. Um, I think that there are going to be probably other things around the company where we basically try to enlist the fact that we have
uh just like a very high quality set of people to teach the AI systems to do different things that we need to get them to be able to do over time. Um,
so this probably isn't the last thing like this. Um, and there but I think it's this is like an
interesting strategy. I think that we want to uh we want to see how well it does. At this point it's um somewhat of a hypothesis. will actually be
able to complete the loop to see how well um these kinds of things actually improve it. If they don't, we won't do more things like it. If they do,
then we'll probably do more things like it. So, um so that's the that's kind of the basic thing. Um in
terms of how we communicate about this, I mean, this stuff is tricky. I think we're we're Yeah, I mean I I think like when I was looking through the
details of this, there's like all these things that we could have done better. So, that yes, I mean yes, acknowledged and we'll we'll try to improve
this. The the kind of core tension on this is that um we want to communicate as clearly as possible
about what we're doing while not having all of the details of things that we think are going to be strategically differentiating leak immediately to
the two competitors. And so I think part of the challenge is like we are a pretty big company. If we post stuff publicly, it leaks. Um some things
matter more if they leak than others, right? Like if we're building something in our, you know, ad
system for example or our infrastructure that's like bespoke to us and it's not something that other people are going to copy and it leaks, it's like
not that big of a deal, right? Maybe it's kind of annoying. I think we know that AI is like one of the most competitive fields, right, in like
probably in history. So anything that can give us that can make our the quality of our thing better um is
generally not something that I think it is in our strategic interest as a company to lay out the details in a lot of detail knowing the physics of the
situation is that stuff is going to leak. So I I think you will have to um we're we're just going to have to navigate that and it's going to be a
little bit different on a thing by thing basis in terms of how we communicate. But I I actually think
it is like not strategically in your interest for us to communicate everything like in all the detail that we normally would on this. Um but I think
we do need to try to make sure that we get this right. Um and and communicate enough so that people understand what's going on. So um this I think
will be a continued thing that we're trying to navigate. It's part of the complexity of trying how do we
navigate running the company through what is just this incredibly dynamic period. I think that there's like lots of things that I think people would
like more certainty on than we have. Lots of things that people would like more details on that it's not necessarily like it's not that any it's bad
for any one person to know, but it is bad if it leaks. And and I I don't know how we how we how we
exactly navigate that. So that's that's the basic situation on that.