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Here we are in New Hampshire, in the center of the universe,
in my barn, where so many things have happened.
And we're talking about some of the stuff
you guys are working on.
Palantir has had many iterations, where
we build products and we have to standardize them
because our clients rely on them,
especially in the national security context.
Each time, we have a cascading thing,
where you have this maximally creative focus
and then it has to be standardized.
And you guys are in the beginning
of the cascading, chaotic, creative process.
So I'm Rob Imig, Software Engineer Lead.
Been at Palantir about 10 years.
AIP -- what's the technical challenge we're actually
solving?
Why is it important?
Yeah, so the big change is shifting compute to the edge.
So instead of bringing your data back into a Foundry or a Gotham
and making your decisions on some ground environment
or cloud environment, we're actually moving the logic
and moving AI --
but not only AI -- also transforms, physics, math.
But moving that logic out to the edge
to actually run on aircraft, on boats, satellites,
ground vehicles.
We've deployed this--
And what -- moving transforms and logic to the edge, what--
why is that difficult?
Yeah, so--
From a technical perspective.
It's difficult from a technical perspective
because you don't have all the power of a Foundry or a Gotham
there.
So you have to figure out how to build an engine, per se,
that can run in these very (typically) low-power,
disconnected environments where you don't have good network
access, you're usually running on somewhere between 10 and 50
watts --
is typically where we deploy -- you don't have this big rack
of servers but you have a very small device that has to run
all of your code.
So we've been deploying to these sorts of environments
and basically building this logic up and building
these algorithms up in Foundry.
And then once you have confidence there
in that algorithm, in that model, on the way
it's performing, then you can push it out to the edge
so it can operate completely disconnected
in a low-latency environment, potentially feeding back
into the system so you could have an autonomous platform.
And there's a lot of benefits to that, especially in Defense,
that we've seen.
And my way of explaining it to outsiders is you have two
problems: one, that you have low energy source --
so batteries --
and not endless supply; and two, that you have to somehow have
the semantic layer reduce the complexity
to the problems you can solve.
Is the second problem also real?
Or is that -- just my imagination?
Yeah, it is.
Yeah, because the difficult thing is you basically
have to build the tools that you're
going to need in this edge environment
and you have to know those before you land there.
So you have to know a lot about the sensors that
are producing the data, what that data looks like,
and a rough shape of what you want to do to that data
so that when you get it in real-time, you already have
what you need.
Because in Foundry, you can do data integrations.
You can get data that looks like whatever
and you may have never seen it before.
And you have the tools to be able to work with it
and to manipulate it into a format
that you can make sense of.
But at the edge, you kind of have to know that.
You have to have it structured a little bit more,
where you can know what that sensor is
going to be outputting.
And you have the right--
[INTERPOSING VOICES]
So maybe, also, a bastardization lay
version would be, in Foundry, we have unlimited supply of power,
unlimited ability to integrate the data on the back end.
But here, we have limited data and, de facto,
you're pre-integrating the data you're allowed
to integrate on the edge.
Here's to Palantir's future.
Yeah, thank you.
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