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- My name is Fredrik Wikholm.
I'm a co-founder at Planethon
and I drive sort of the development
of science and business intersection.
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- So Planethon is a company that it titles
itself, planet R&D; sort of the
bridge between Earth science at large.
What we know about our
planet and business.
How we do business in this world,
because it's quite clear to
us that how we do business
needs to be deeply and
profoundly influenced
by how our Earth system works, and
we help companies at
large build their business
on how Earth works, and
what we know about it today.
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- So our sort of end users,
or clients, or partners,
however you wanna describe it,
is one part like companies where we'll
building something, and therefore
business developers who
are C-suite management.
Often it starts with
the CEO that's defined
that they wanna make a transformation
of how they build their business from
being not so very sustainable,
to being sustainable.
Or, in our case, planet
positive in a direction.
So that's one side of it
and how do we build things.
And then the other side of it is
really investors, investors at large.
How do we invest in what is to be
sustainable now and in the future.
And often I think both of those
find themselves in the same conundrum,
which is filled with good intention
and a knowing that we need
to do things differently.
We need to listen to like a bigger
Earth system of how we extract resources,
how we build things, how we look at
whatever is the byproduct,
and so on and so forth.
But there's still a lot of guessing.
There's multiple ways of assessing
what's sustainable in terms of investment.
There's, for the most part, a unique
processes of work, ya know,
sustainability challenges
in almost every company.
There's really no united front,
and very little of it is really sort of
based on the knowing of our planet,
what we've actually known so far.
So in the case of Planethon,
we try to make it substantially easier
to understand what are
the things we actually
need to address, what are
the technologies out there
that you can utilize to address them,
and how do you build innovation
processes to make it happen.
So that's sorta us and our
departments and end users.
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- Fundamentally when
we go about something,
we say that we are planet R&D companies,
so the research part
is enormously important
with heavily anchored in
massive sort of data sets.
Enormous amounts of
knowledge about our planet,
and all the complexities of our planet.
How does an ecosystem work,
locally or on a broader scale,
how does the atmosphere work, where are we
currently standing on
global warming, yada yada.
It's a lot.
All of that data is data on a
massive relationship, right?
It's like the Earth system
and all the social systems
on top of it are social graphs,
there are knowledge graphs,
there are enhancing graphs,
alright, regenerative graphs
you could even call it.
And so for us to use something like Neo
is fundamentally very very important,
because it's at least trying to apply
a real system to how
the real system looks.
In stark contrast to almost all
other storage of data up until now.
And it simply makes it easy for us
to see relationships that are relevant,
extract and synthesize key insights,
and, simply, see things
no one's seen before.
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- So for Planethon next
we're in an exciting stage
of both having to preform
for real with a lot of
clients and partners like
big industrial players
in the world that are committed to...
well basically building
new versions of themselves
that are sustainable and are in alignment
with how Earth's system functions.
So for us right now, we're in a stage of
R&D with many of these
companies as partners.
That's one big part of it.
The other part of it is
really just amping up
the capacity of our technology.
So right now, we're in a stage of
getting ready for funding on board
in a reasonable staff
size, but now we need to
amp up developer teams and just
build, and build, and build.
(chuckles)
(gentle music)
- We're actually, we've
done two innovation sprints,
or lab weeks, with Neo.
One very early and one once we've
dug in a little bit
deeper, and the very first
was really, we had some
graph understanding,
but it was really just how do you apply
graph to siloed Earth science,
and trying to make sort of understanding
of like how is this, how are we capable,
is it going to be tricky or not?
And that was really good; it
was fundamentally really...
What it did for us, I think, it clarified,
maybe something we already knew,
but it was without a doubt very clear
that we're a graph company first.
That is, sort of, the actual
outcome of that sprint.
Second sprint: we had data
sets, we had a direction,
so what we could do now was
to go a lot more towards
the data science part and simply
work with graph algo on
a more complex level.
And really focus on something that I think
partially is quite new to
the graph world as well
and we could be more guinea pigs for it.
And that really helped us hammer out
sort of our process rush now
in how we build technology,
and what we want to achieve.
And it actually validated our idea.
It went from idea to reality.
We can actually use
graph algo on graphs to
get the answers we're hoping to get,
which is sort of what are the companies of
the world to invest in, to support,
that should lead the way
to a sustainable future.
(gentle music)
- When approaching graph,
or stepping into a lab,
at least I am very hungry
to jump to conclusions.
At least I, who come less from
the technological background
and more from sort of the research and
business development
background, it's easier
to sort of start jumping to conclusions
and feeling borderline fragile
and frustrated along the process.
But just sort of hold on
to and trust the process
I think is one of the key factors.
And also get in there with real cases.
Like it's so much more
valuable if it's real data,
if it's a real hypothesis,
even if you just come out
having crushed your
hypothesis, it's better than
sort of fictive, ya know, mess.
Yeah, it's tough to just
learn how to swim on land
if someone just said "get in the water".
(chuckles)
- And in use it's like:
what you will most
certainly get out of a lab
is that you've learned a whole ton.
That's the fundament.
(gentle music)
