Fireside Chat with nCent Labs Founder Kapil KK Jain and Steve Jurvetson,

[Ed Roman] Welcome back
to the 2018 Hack Summit. We are privileged to be
here with Kapil KK Jain, as well as Steve Jurvetson,
and Kapil’s launching a brand-new startup
company out of Stealth Mode here at Hack Summit. It’s an exclusive opportunity for you to learn about his new initiative. And to give you some
background about Kapil, Kapil previously served on the faculty of the Stanford School of
Engineering where he ran the Mathematical and
Computational Finance program, and he taught courses, and
he led a research group there on advanced financial technologies, blockchains, and cryptocurrencies, and he’s a recognized
thought leader in the space, a quant expert, and we’re super
privileged to have him here. He’s the CEO and founder of nCent. Then Steve Jurvetson is a
world-renowned venture capitalist who will be interviewing
Kapil on camera here. They’re here together, and
Steve, in case you don’t know about him, he is the
co-founder and former partner at DFJ, Draper Fisher Jurvetson, which is a world-renowned
venture capital firm here. He has a new venture capital firm that he’s started recently as well, and he sits on the board
of SpaceX and Tesla. He’s been on the Forbes Midas list, which is a list of like the best investors in Silicon Valley and around the world. He invested early into Hotmail,
and he’s also an engineer, just like us, so he has a
double-E degree from Stanford where he graduated with honors. So, Steve, it’s a pleasure to meet you and to have you here as well, Kapil. And I’ll let you guys do your interview. Have a lot of fun with
it, and I’ll be right here in case you need me. – [Steve Jurvetson] Fantastic. Thank you so much, and
thanks for having us. – [KK Jain] Great, thanks, Ed. – [Steve] Yeah, assuming
you can hear us okay. Text us if you can’t at any point. – [Ed] You sound great. – [Steve] Oh, fantastic. Well, we’re delighted to be here today. We’re here in San
Francisco, and thematically, we thought it’d be appropriate
to sort of go to the moon, given my long fascination with this area, and so we have a few props for you today obviously the moonscape behind us. Interestingly, just for inspiration, that is the largest slice
of the moon on earth. It literally comes from our moon. Larger than any moon rock
from themeteorite. It’s beautiful. We love that as a theme. And lastly, and we love this gimmick, we have a 3D printed rocket
engine from a startup across the bay that’s hoping
this weekend coming up to put their first payload into space. And so, since we’re having
a fireside chat, we thought, we’ll, you know, we’ll actually
just have a fireside chat while we speak. So, this is gonna get pretty hot for us, I just now realized. (Kapil laughs) We’ll have a warm glow the entire time. I might move my mic back a little bit. (both laughing) So here we go. – [KK] This was not planned, by the way. [Steve] Yeah, this was untested,
let’s just put it that way. Proximity of face to the fire. But, yeah. Most modern rocket engines are 3D printed, because inside of her,
you have regenerative cooling channels and such
that are hard to cast. So that’s not what we’re
here to talk about today. Today, we’re here to talk about nCent, and this is also quite special,
because this is the first public appearance of any kind
that the company is making, so it’s the first time people like you can ask questions and hear
about the nCent story. I’m pretty excited about that myself. And there’s also an
additional thing today. They’re announcing their
first round of funding, a $10 million seed round with a pretty illustrious
group of investors. We have Naval Ravikant,
who I’m a huge fan of. We have Sequoia, SV Angel then AME Cloud, which is Jerry Yang’s fund, the Winkelvii, or the Winkelvoss Partners Floodgate, Zhen Fund
and a bunch of others, in fact, a large number
of other investors. And so this is an exciting
day for the company to have its beginning of its debut, or at least announcing what
it is doing in the world. – [KK] Sure, and I can add
one other investor as well, Steve Jurvetson, of course. And for those of you who don’t know, Steve obviously doesn’t need
any introduction in the valley and has been a great
supporter, so thank you, Steve, and there’s also a bit of a news, I know Steve’s pretty modest about it, but there’s also some
great news on Steve’s side where he’s actually
launching Future Ventures, a venture capital fund that we’re proud to be part of the blockchain family of. – [Steve] Fantastic. Thank you, KK. So, we also are gonna
spend some time describing what nCent is all about and
the problems is aims to solve and the opportunities to use
the blockchain in particular or to use cryptotechnologies to address some really huge unmet
needs in the economy, some that are dear to my heart as well. So, as we get into it, maybe I’ll start with
a very broad question. How would you describe
what nCent is all about and what you’re aiming to
do at the simple level? We’ll get into more details later of the history and problems. – [KK] Sure. – [Steve] But, you know,
just nutshell, so people have a placeholder, what is it
that nCent’s all about? – [KK] Yeah, sure. So, we like to describe nCent
as a decentralized protocol for incentive markets. And incentive markets we
think are a super exciting category of blockchain or
decentralized applications that folks, up until now,
have not been very focused on. And an incentive market is quite simple. It’s an efficient way
for people to collaborate and have the value of their
work and collaboration be rewarded, and that ends
up creating the substrates of incentives that allows markets to form. And I think, you know,
as we know from Econ 101, the two best ways to organize
people are sort of firms and markets, and, you
know, firms in many cases are all we have; oftentimes,
oftentimes they’re inefficient. The incentives of
individuals inside of a firm can be broken or misaligned,
and firms may even be misaligned with their
users or their customers. And so, what we’re trying to
do is to create a platform that’s decentralized
that allows market forces to enter into the organizational
structures or principles that typically have been
the dominion of firms. We can talk about examples of that, but there’s lots of different
ways to kind of disaggregate or really break apart the
elements of what makes incentives form for people
to collaborate together, and that’s really kind
of what we’re focused on. We have a laser-like
focus, focus on incentives, and hence the name, nCent labs. – [Steve] Exactly. In fact, that might be a good segue a bit to your background, ’cause
as I listen to this, I think thoughts around economic systems,
thoughts around obviously incentives and motivations,
but also, how do markets form? What makes for liquidity of markets? What makes for stability of markets? What makes for a thriving economy? And so maybe you can dive a
little bit more than we’ve heard just a moment ago in
terms of your background, ’cause it’s quite interesting. In fact, KK and I first met,
or the first time we met in great depth, we were
on a stage at Stanford at an AI and financial
technologies conference that he helped organize and moderate, and that was fascinating on its own right. We’ve since kept up since then, and I often, when I find
someone who combines two backgrounds that are very different, not the usual combination or pairing that you might find just
walking down the street, I pay keener attention. That’s usually where
the big ideas come from, the sort of interdisciplinary
ideas that cross boundaries. So, maybe give a little more
background on what inspired your personal path and
what inspired you in that personal path and then
transitioned into starting nCent. – [KK] Yeah, sure. You know, I would love
to kind of introduce a little bit of my background. You know, when I was a kid,
I sort of was very fortunate to see kind of personal computing be one of the formative trend
of my kind of childhood, and then to see sort of the internet, and then later on of course mobile. So these are sort of
like the formative years where I sort of had these
inspiring thoughts or dreams about sort of the promise
of personal computing and the internet to really
connect people and sort of democratize opportunity,
spread information, and, you know, make the world
a bit fairer in that regard. I was kind of a Mac geek growing up, so, like many I think young people, that was the first exposure
to a development environment, just kind of in my local public school. And I actually ended up going to Dartmouth because it was a Mac-ified campus. – [Steve] That’s why you chose Dartmouth? (both laughing) – [KK] That, and they offered
me the most financial aid, so. And, you know, I was
really inspired by Apple, and it was kind of during
my undergraduate years that they went through some tough times, and Steve Jobs came back, and
I remember actually sitting in one of my clubs with
one of my classmates who was also kind of a Mac guy, and we saw the big screen of
Bill Gates show up ominously, and then they announced that
Microsoft is bailing them out, and then, you know, our initial reaction as kind of a Mac faithful
was a little bit to be down, but then we sort of had the strange idea that we should all just
go work for Microsoft, because in order for the Mac to succeed, they needed Office to
be an awesome product, and we just didn’t trust that
Microsoft would deliver it. So, a bunch of my friends ended up, like, interning at Microsoft,
and a funny thing happened. It was a great experience
to be a kid, you know. We were the largest Mac
development team outside of Apple, and I remember actually one
of the internships, you know, I got to meet Steve Jobs. So I think a lot of people in the valley had this experience of like. – [Steve] I did too. I worked at NeXT, actually. – [KK] Oh, really, what
was your experience? – [Steve] It was amazing. The long walks, the sort of, he was possessed by Apple, I think. He was still at NeXT. He was just possessed by Apple. He had like chiseled the
icon out of his keyboard. He was just fanatical
about coming back to Apple, and I didn’t think it was
possible, when we were at NeXT, an enterprise
software company at the time. It turned out to play out exactly the way he thought it would. – [KK] Hmm, hmm. He was just sort of silently
attending a sort of review, but his, even in silence,
his presence was basically felt in the room. But anyway, you know, long
story short, one of the things that I ended up doing
while I was at Microsoft as an intern is, it was kind
of the first time in my life that I had a little bit
of money to play with, and like every dot-com
1.0 kid who was clueless, I ended up day trading internet stocks, (KK laughs) which in retrospect was just some kind of weak form of gambling. But, you know, I ended up sort of. – [Steve] Topical, topical
for some in the audience. – [KK] Topical for some,
right, in crypto now. But, you know, that was
sort of an experience where I actually didn’t
know that you could do this for a living, and I was
just sort of screwing around and made a little bit of
money, which, at the time, was all the money in the world to me and sort of have this
circuitous path to Wall Street. I ended up getting recruited
by a company called D.E. Shaw, which was a quant hedge
fund, and, you know, I didn’t really know anything
about finance before that. You know, they sort of paid
me more money than Microsoft, and I was sort of like, on my way in terms of a Wall Street career. But I almost sort of felt that, kind of like Wall Street picked me. I didn’t necessarily, like,
affirmatively pick Wall Street. But having said that, you
know, I learned a ton, and I’m super grateful
for my experience there. And, you know, I really learned a lot about statistical arbitrage,
what makes market works, how to model markets, and how to develop, you know, safe and secure code at scale to be able to engage in
financial transactions. And so, it was a very fertile kind of learning environment
for me and my career. I, so I had a 10-year
career on Wall Street. I actually had a brief cameo
where I was at Stanford in a grad program, which
I thought was a good hedge to actually creating a hedge
fund, ’cause if the fund worked out as a startup, you know,
I was hedging my hedge fund by enrolling in a, you know,
stats program at Stanford. So I was in my dorm room at
Rains being a stat arbitrator and then pretend to take, you know, the PhD first year curriculum, and then ended up kind of
just going back to Wall Street and worked at Perry Capital,
which was a large hedge fund, and ran a multiple-billion
dollar quant portfolio there, and then I was thankful to
have the opportunity to run the Citi Principal Strategies prop desk in the quant business there, which was a, which was a huge business. And you know what, after sort
of 10 years of doing that, you know, I just sort of took a step back and kind of just went through
this internal thought process of including that sort of,
you know, I think a lot of people, especially young
people coming out of college, they sort of end up
being good at something, and they just kind of go into that track, and then eventually, you kind of realize or you analyze from first
principles your life, and you sort of think, like, well,
why did I actually do that? What was the kind of rationale behind it? And I sort of ended up having
this analogy in my mind of the kind of mouse olympics. And so it was the first time in my life I kind of like looked
at myself in the mirror and was like, well, you
know, I was very successful and very thankful for the
opportunities that I got, but I think kind of a
career on Wall Street is some kind of form of like
playing the mouse olympics. And, you know, every year, you
get a bonus, you do better, you get a bigger team, you
get more capital to manage, and these are all kind of like gold medals along the way of the mouse olympics, but, you know, as the line
sort of goes, you know, even if you win all the gold medals at the mouse olympics,
at the end of the day, you’re still an effing mouse. (KK laughs) So it sort of like took
me 10 years to realize I was kind of playing the mouse olympics. And then, so I sort of stepped back. I really wanted to give back by teaching, and I actually was
inspired to try and teach in sort of disadvantaged
high school situations. It turns out, it’s actually very difficult from a licensure standpoint. For those of who know Michelle Pfeiffer, my goal was to be like Michelle
Pfeiffer in Dangerous Minds. – [Steve] Yes, I’m familiar with that. (both laughing) – [KK] And it turns out,
I mean, I the movie, she just walked into the
school and started teaching, but yeah, it doesn’t
really happen like that. – [Steve] Gotta go with Teach for America. – [KK] Yeah, Teach for America
would have been another one. But anyway, long story
short, I ended up talking to my old advisor at Stanford,
and he was like, well, why don’t you just come teach here? We’ll let anyone teach here. (both laughing) So, I ended up, you know,
having a faculty appointment in the engineering school. I ran the computational
finance program there, and it really gave me, number one, a front-row seat to the
kind of innovative fervor that I experienced in
the first dot-com boom when I was out here kind
of in this, like the spirit of like this Mac, Mac
community, where it was sort of like being part of a movement that was larger than yourself,
that was technology-based. You as a developer can actually,
like, make a difference. It’s literally like
your fingers typing code into a computer can like, make an impact. – [Steve] Right. – [KK] And, you know, so
like, on Wall Street, right, all your wins are private. Essentially, you’re monetizing
all the gifts you’ve been given, gifts of, you know,
intellect and grit and whatever, just to sort of like monetize your brain, and so I really missed this idea of like, you can actually contribute
to something, you know, bigger, bigger than yourself. And so, you know, being
able to have the opportunity to come back here and being
involved was really great, and then it also gave me
a lot of freedom to run a kind of blockchain research group. – [Steve] At Stanford? – [KK] At Stanford, which, you know, was so one another great opportunity to help me develop my ideas
and my thinking about, about blockchain. – [Steve] Also helps kinda
tap into an initial pool of talent potentially to recruit. – [KK] Yeah, I mean, look,
I think that the space is really changing super, super fast. I mean, it’s often stated
that, you know, a week in blockchain feels like a few
months in some other sector. I think that’s certainly true, and there’s a lotta really
good research and creativity at Stanford that we’re
certainly tapping into. We’re really blessed to have, you know, wonderful
advisors and contributors. David Mazieres is the
chief scientist at Stellar, and may get on the list,
but, we’re really blessed to be plugged into that cutting
edge research community. In the Bay area, I think
there’s really, you know, a really fertile environment
for people to develop products, and there’s a lot of institutional
knowledge about scaling and how you develop
technology to be impactful on an internet and worldwide scale. So we’re very blessed
to be a part of that. – [Steve] ‘Cause I noticed
you formed a Telegram group that went from zero to
9,000 people in a week, before you had said a word
much about what you’re doing other than come join us, you know. We’re doing something interesting, and maybe word of mouth
among your interns. How did you pull that off? Do you have some sort of
amazing community manager? – [KK] It’s actually like
not as, not as sophisticated as one would think for
an incentive community. We just sort of created this Telegram site and just asked people that we knew. We didn’t even email all
of our investors yet, or we didn’t really tell
anyone about it yet, and it just sort of grew organically. Actually, we wanted to design a new logo, so the t-shirt that I
have now is our old logo that an nTern created for us, so thanks. We wanted to just refresh the logo, and we thought it’d be fun
to sort of crowd source it, and it’s just sort of one
thing’s becoming to another. But I do think our key secret
weapon in building out our Telegram community, I would
encourage everyone to join, ncnt is our Telegram name, has
been our community manager. So we did appoint a
worldwide community manager about three days ago, and I think we actually
have him right here. – [Steve] Oh, yeah. – [KK] So, this is the world famous, this is the world famous Popcorn. His name is Porter Cornelius,
but he goes by Popcorn. And he’s our office golden doodle. And so he has been, really
gotten kind of internet famous on, on our Telegram, and so
kind of by popular fan demand, you know, he’s making a cameo here. – [Steve] Still a puppy? – [KK] He’s still a puppy. – [Steve] Crypto puppy. – [KK] He’s definitely
one of our crypto puppies. (both laughing) – [Steve] He’s soft, he’s quite nice. Yeah, so he’s a golden
doodle, and we kind of. – [Steve] It’s gonna
eventually be a big-ass dog. – [KK] He’s gonna be a pretty big dog. It’s like a 50-pound dog,
but we kind of saved him from a bad situation, and
now he’s kind of surrounded by love, not only in the office, but with the tens of thousands
of adoring fans online. (KK laughs) – [Steve] Probably ’cause,
you know, fire, and being on stage, you know, stage fright. – [KK] Yeah, we didn’t
practice this with the fire, so that’s kind of a new
variable for the puppy to grok. – [Steve] It’s like the old tradition. You know, gather around
the fire. Fantastic. Well, I’m glad he’s here
for our fireside chat. – [KK] Yeah, so he’s
definitely a key team member, and, you know, kind of adding value. It’s a little bit clickbait-y, but it’s a bit of our,
it’s a bit of our homage to our colleague Sebastian
Thrun, who famously went on TechCrunch with
his puppy. (KK laughs) – [Steve] I remember that. – [KK] So Sebastian, if you’re
watching, say hi to Charlie. – [Steve] There we go. Well, fantastic. Well maybe I can segue to some of the timeline of development. There was, I know, an
inspirational moment for you, ’cause I read your blog post about it, and I spoke with you about
it since we’re investing about the DARPA red balloon challenge. – [KK] Yeah. – [Steve] And I had not
heard of this prior to you introducing it to me, and maybe you can introduce it to the audience as well as to what this is all about
and what it managed to achieve. – [KK] Yeah, so, I think
that this DARPA red balloon challenge was kind of one of
the core pieces of the founding kernels of idea for me anyway, and it was just sort of this quirky story that ended up inspiring
me, really, for the last, you know, almost decade now. And the story begins in 2009, when DARPA, you know, for those of you who
aren’t familiar with DARPA, it’s the US Department of
Defense’s Advanced Research Projects group, and they
often do research challenges. And they challenge academics
or other community folks to come up with innovative solutions. They very famously had a
self-driving car contest in the desert, which
was a really inspiring kind of watershed moment
for that community. And there was one kind of
a little bit lesser known. In 2009, they had the so-called
red balloon challenge, and it was a pretty modest contest. What the formulation of it
was, they offered $40,000 as a reward for people
to find 10 red balloons that they had placed all over
the map, all over the country. – [Steve] Anywhere in the US. – [KK] Anywhere in the US. So they didn’t tell you
anything about where they were. You got a photo of the red balloon, so it was like a moored weather balloon. – [Steve] Actually I just
thought of something. This might be a fun pause. Once you’ve described the challenge, have people think, how long do they think it takes to solve this challenge, after you describe it. – [KK] Yeah, yeah. – [Steve] And then reveal. – [KK] Yeah, so just imagine
the entire, it could be anywhere in America, and then,
remember, in 2009, this is before you had like, quasi
real-time satellite imaging or the ability to do some
kind of computer revision. This is like a hard physical search, like needle in the haystack-type problem. In fact, many of the people
that were the critics of the problem, there
was actually an article where people were famously
talking about how this is actually like a needle
in the haystack problem. It’s like not even worth doing. – [Steve] Maybe impossible. – [KK] Another line of, kind
of like an impossible task. Or another criticism was that
$40,000 actually wasn’t enough of an incentive, ’cause you
might consider, for example, having a whole team kind
of screening or careening the whole, like, the fields of Nebraska, trying to find these red balloons. And it really was, even though it was kind of a fun game or a formulation, it was really mimicking
like, real problems. So one of the kind of
stylized canonical use cases of something like this or
analogies is, you know, like, if there’s a missing
child or missing person. – [Steve] Collective mobilization. – [KK] Collective
mobilization, and sort of it’s like an ad hoc social network. And there’s sort of
elements of virality in it. So studying how this kind of information propagates is important. You know, there’s so much noise and, well, information out there that’s
competing for our attention, so being able to get through
and craft the incentives around a campaign such that it breaks through that attention
barrier so that people are focusing on it so the
information can truly propagate. Another use case is sort of,
you know, finding the bad guys, finding the most wanted person. But anyway, why don’t
I tell you a little bit about the sort of solution. So. – [Steve] I read there were
like 4,000 sort of attempts, and then a few hundred that
really made a go of it, if I recall, and then, what, MIT? – [KK] Yeah, so the MIT team
eventually ended up solving it, and actually, Ed, if we
could throw up a poll, maybe some of you guys know
about the red balloon challenge, but maybe we can do a poll
to guess how long it took the MIT team. – [Steve] So, we would have to get buckets so people could vote in the binary. Do you wanna do like less
than a day, a week, a month? – [KK] Yeah, how about less
than a day, a week, or a month. I think those would be a couple buckets. – [Steve] You can vote
if you know the answer, but that would just be biasing Only vote if you haven’t
heard this before. So, before, we’ll give you a little, ’cause the poll may take a
second to actually pull together. Let’s see, I don’t see poll yet. So, let’s, before we reveal the results, maybe mention, ’cause I think you can say how they approached it, right? – [KK] Yeah. – [Steve] You wanna describe
how the MIT team approached it? Because it’s relevant. The reason we’re giving this example is it’s directly relevant
to what motivated the founding of nCent in the first place. – [KK] Yeah, for sure. So, you know, and actually, the solution was something that I was fascinated about when they
postulated the solution, and I think part of the reason
why I got so obsessed with it is because I was sort of
like, recruited into this, and so I was really focused on it, and I was planning to help out the team, except for like I was at work or whatever, and like,
(KK laughs) but they solved it, and
it sort of was something where it was, you know, my personal involvement
ended up kind of making me like, more obsessed with it
than the average bear, I think. And their approach was
to crowdsource support off of the internet, which in
and of itself wasn’t novel. There were a couple of
others teams that did that in different formulations. But what they did is they were
really hacking incentives. So they really thought
about, hey, how can we take this $40,000 pool that’s
gonna be the prize and sort of create the
right incentive structure that not only rewards the
people that find the balloons, sort of the naive solution
is okay, let’s reward the people that find the balloons. – [Steve] Open this, get
a little cold air, yeah. We gotta cool down the rocket engine. It’s sort of radiating heat
continues long after it’s done. – [KK] It’s a cool down sequence. (both laughing) – [Steve] Thank you. – [KK] And, so, you know, what
was really inspiring to me is they actually kind of gave a
thoughtful incentive structure for people to propagate
information about the network and about the formulation. And so, you know, what ended up happening, I can just describe the
algorithm a little bit, they sort of had $40,000
was the total reward that the MIT team was gonna get from DARPA if they were able to solve the problem, and what they did was they
divided that into 10 buckets, because there were 10 balloons,
and they basically said, each balloon will be worth $4,000. And so, let’s just
algorithmically call 4,000=n, and then their advertising
campaign or their pitch was sort of come all, kind of
join our red balloon hunting team, and if you find the
solution, you get n over two. So that’s your reward, so $2,000. And there’s also gonna be incentive for you to propagate
information about this campaign, and so if you tell your friends about it, and one of your friends ends
up finding the solution, that person gets n over four, and if you find the finder,
you get n over eight, n over 16, so they used this
so-called recursive limit. – [Steve] And the limit, It
won’t add up to more than 40,000, no matter how
deep this goes, right? – [KK] Yep, yep, yep. – [Steve] Recursive. – [KK] It’s a recursive
structure that converges, and this convergence property
ends up being super important, because you wanna design something where the network can
generate enough value to pay off all of the participants, and so people intuitively
trusted the MIT team to make good on their promises. There was no sort of
community default risk associated with MIT, so MIT
was a trusted central actor sponsoring this contest. But, you know, it sort of
was a very elegant solution to this problem that had some pretty interesting
mathematical properties. So there was a whole bunch
of papers written after that event or after that result. – [Steve] And I’ll just
mention, if people online don’t know how to do the poll, there’s a little button
or word poll at the bottom that showed up, and if
you click on that once, you’ll be able to vote, if
you wanna have your vote, ’cause in a moment here,
he’ll reveal the answer. So if you just wanna through
the exercise yourself of, you know, trying to
think, how long do I think this would take to propagate
and find a solution across the entire United States? But go ahead. – [KK] Mmhmm, mmhmm. So it was really remarkable. So basically like, you got a
reward to find the solution, and then essentially, you got a reward if the solution appeared in your sub-tree. So you can think of it as
sort of creating a tree. – [Steve] Infinitely deep in theory. – [KK] It could be infinitely deep. And the cool thing is with
this type of structure, and there was a post-mortem
paper afterwards, is that, you know,
everyone found a balloon that was sort of like
in Chicago or, you know, one of the areas where it was
easier to find the balloons. It really outperforms, search-wise, as these sort of deep tails,
where maybe you require multiple hops to try and find them, or it’s a more idiosyncratic, and there’s all kinds of interesting ideas that came out to me or what
I became inspired by it, and so, you know, one of
the ideas from my youth is really that like, you
know, I used to read a lot about like Doug Engelbart. – [Steve] Before we get
there, ’cause it’s killing me, we gotta do the reveal. – [KK] Okay. – [Steve] ‘Cause we could go
on and on, and people are like. So just a, we’ll wrap up the
poll and release the summary. It looks like the majority of people, the modal answer is
about less than a week. So more than a day, less that an week, with the single most popular at about 43%. About a third of you, less than a third, thought that it actually could
be done in less than a day. Some, maybe almost, almost equal amount though it was more like month
to year kind of timeframe. So, do you wanna reveal? – [KK] Yeah, it was less than nine hours. – [Steve] Within nine hours. – Yeah. And so, in fact, I actually
was not able to add any value, ’cause it was solved faster
than I could do anything. (KK laughs) So I don’t wanna claim
credit for any of it. I wasn’t part of the core team. It was out of Sandy
Pentland MIT Manuel Cebrian and the media lab there and their research group that ran it. I was just sort of a fan or spectator that kind of got obsessed with this result and tried to figure out,
what is the, and there’s a lot of subtlety and
complexity involved in this. So, you know, one of the kind
of like dreams of the internet I think for me, as I was
saying, is sort of like, the internet’s kind of connected people, but unlocking our common
potential is something that’s a little bit of a,
of an unfulfilled promise. We’ve only begun to scratch the surface. – [Steve] Yeah, you’re starting
to say this when the early founding vision of what
the internet should enable. – [KK] Yeah. – [Steve] I remember when I was
working at NeXT and you were at Microsoft that .net’s and
some other big, whatever was being discussed, and I really
came increasingly to believe that a large part of the
value of these infrastructure layers, whether it’s
blockchain, whether it’s other protocols people are trying to promulgate, are largely directory and search. How do I find what I’m
looking for, and also, how do I get paid, directory,
search, and payments. And when you’re developing nested code, like an object-oriented framework
like NeXT was working on, you would ideally wanna be
able to pay an infinitely deep tree, if you will, or perhaps
a cyclic graph, either one, of contributors, and how could one do that in a very efficient manner? That’s intriguing me now,
so I wrote some papers on blockchain back, actually
not blockchain, on digital cache back in ’94, but
this is what fascinated me. It fascinated me when Hotmail
came around and Skype, which we invested in, and the
whole term viral marketing that I actually coined
with my partner Tim, and so I’ve been
fascinated at the power of, basically, what’s endemic
to the internet itself, what Kevin Kelly would say
is the inevitable trajectory of this technology is
towards distributed systems, towards nested and
recursive incentive systems, and unlocking the power and potential. You’ll see that in the gig economy. You’ll see that in some areas
where there’s no payment, it’s just reputational capital.But if you could layer on
an infrastructure layer to address that in some
sense, you could unlock sort of the main untapped
potential of the internet, at least, in my opinion. – [KK] Yeah, for sure. I mean one of the things
that we like to say is sort of like, if aliens
came down from Mars, and they sort of saw Bill Gates, and they saw Linus Torvalds, and they were sort of saying that like, okay, like, Bill Gates
is like the richest guy or maybe one of the
richest guys in the world, and Linus is sort of like a
modest, open-source like mega hacker, but the value
attribution’s a little bit strange, because like you could
probably argue that Linux was at least as impactful as Windows was as an operating system. But the world’s value attribution, particularly in open source, is something that’s always been a little
bit of a head scratcher. We haven’t actually solved
incentives for open-source development, and I think
that a lot of people that do open-source
development aren’t really doing it necessarily for like, the payday, but the point is, if you can
somehow have some incentive market, some incentive
market forces enter something as simple as, for example,
open-source development, you might be able to broaden
the pie of people for whom it’s worthwhile to contribute
to open-source development. So, open-source is something
that one may not consider it to be a broken market,
but it’s an opportunity to expand that market to
be able to touch people that don’t have the luxury
of just kind of contributing to open-source development
for like, you know, hacker karma points. And so, one of the things
that really struck me about the red balloon
challenge was it’s exploiting private information that
people knew about each other. Like, I may have, my friend
may have a hunch that like, KK is really into something
like this red balloon stuff. I don’t know why, but he
just likes kind of puzzles or games of this nature, so this would be right up his alley. So you don’t even necessarily
need to even know the model. Your brain doesn’t actually
even have to grok the model of why, but there’s
this huge treasure trove of data, the information in our brains, that we know about each other. I mean, human beings are social creatures, and we have a hunch of
each other’s potential, their capabilities, their skills, what their, you know, ideals are, and so, all of that is essentially going untapped. Only a small fraction of
that even appears online. So, even Facebook, if it had
a super targeted ad campaign where it literally just took
everyone’s profile, sucked it all in, put it into some
machine learning algorithm, I don’t think it would
have been able to solve the red balloon challenge
in less than nine hours. It was exploiting private
information that people had, and there was this awesome
aspect of geographic diversity. You wanted to recruit friends
from different regions in America, because
that’s how the problem, it would maximize the problem. So all of the things who were. – [Steve] It’s like the
ultimate capitalistic or like economic
distribution of value add, that someone on the edge can figure out where on the edge to explore
this under-exploited. Everyone could be making a
local optimization decision of where they could find
the most untapped potential. – [KK] Mmhmm. – [Steve] Literally in this case. And they don’t even need
to, it’s sort of like, the hardest crypto is the
crypto that’s sort of like, information that’s
encrypted in your brain, and like, you actually can’t
even explain the model. Like, I don’t, you know,
if I saw some like, cool space object, I might have a hunch that Steve might be interested in it. – [Steve] I think
there’s a big window open and things are flying over. We have some airflow issues that are knocking things
over in the distance. Sorry about that. – [KK] It’s probably a get
engine vortex, you know, the shutdown procedure of the engine. – [Steve] So this is one area
that we’ve explored a bit. But are there others, like,
in certain areas of markets. There’s advertising. I’m thinking recruiting,
match making in general. – [KK] Yeah. – [Steve] This is where
like, my fiancee works in a recruiting business
using AI to help, you know, companies to build up
their teams, and the idea of who best can find a match
for a given opportunity, we all know this in our hearts, that the easiest time building a company is with someone you know. – [KK] Yeah. – [Steve]There’s a few people, and then a few people they know, and so forth, because of that. – [KK] Yeah, totally. It’s sort of like, so,
what is the status quo? We have this dream of the internet. It’s connected us for sure, but it has not unlocked
our common potential, and like, the biggest
companies or the biggest central actors that have
the deep enough pockets or enough eyeballs and enough users and enough user data to
organize people are just simply kind of like not really
incentivized to do this. Sort of like, first of
all, I think, you know, one of the things that people
misunderstand about blockchain is yeah, there’s sort
of a distributed systems component to this and
decentralization as a trend, but it’s also a new way
to set up an organization, and you can set up the initial conditions of the organization so everyone’s
in line and incentivized on tokens, on a tokenized network. You know, you look at something
like Facebook or Google, where you sort of have the
shareholders as the benevolent caretaker, so to speak,
of the user network, but they’re not quite benevolent, because they’re for-profit shareholders. They have a duty and a
fiduciary to maximize profits, which is naturally gonna fall out of alignment with its users. And so, at scale, this
alignment’s just gonna naturally fall farther and farther apart. So, you know, I think a
lot of these controversies that we’re seeing about
Facebook and so forth, you know, maybe it’s just an initial
condition design flaw of how they’re set up from
an incentive structure vis a vis their user network. And Facebook’s an interesting example, but so like, you know, like, Steve and I have a
natural social connection. We have natural social, like, you know, like, what is more fundamental
for like, human ownership than like, owning your social graph, owning your social network? It actually exists in real life. It’s just that like,
we all can’t figure out how to create the data
representation of that online, so we like, defer to Facebook to figure out the protocol
of how to do that. And then in exchange,
they’re able to like, extract all this economic rent off of us. – [Steve] Generally familiar
with a plot like this. I can tell you, he’s been
ranting about this for a while. – [KK] Yeah, so. – [Steve] Reimburse the people
for their contributions. – [KK] Yeah, so, the upshot
of all of this is, these centralized actors are rapidly
kind of like losing trust, and they’re not motivated
to solve this problem of unlocking our common
potential, necessarily, and what you’re left with is just like
broken markets everywhere. So, you know, like you were
just talking about ads. I mean, ads is like,
literally, the market’s like been the same way on the
internet for like 20 years. It’s just been like
the engine that’s been, and they’re all like,
super spammy, they’re super inefficient from an
information content standpoint. It’s like a super expensive
way to acquire customers. And yet, like, you know,
this powers, you know, most of the, you know,
P&L off of the internet. You know, recruiting’s another one. I mean, I think that, you
know, I think myself, Steve, of course, a lot of people
that are probably tuning in, we’re really, really
blessed to have our careers and our chosen profession
be fulfilling to our kind of intrinsic potential,
and like, the reality is, for 99% of the people in the world, that’s just not the case. They kinda just check in, get paid, and like, you know, check out. And so, we’re starting
to see kind of the rise of the gig economy, and, you know, even the early green
shoots of the gig economy are kind of like a little bit centralized, and, you know, it would be
interesting to see how that goes, but the idea is, you know,
these are kind of like broken markets that, you know,
if we can kind of create an incentive market
around and set up those initial conditions of incentives properly, you know, maybe that
composes into something where we can unlock
some of this potential, and address things like a
smarter way to acquire customers or a smarter way to recruit people, and it’s really just quite simple. I mean, we know a lot
of valuable information about each other, and that
potential is not really unlocked. And so, if you can just
create the right incentives around it, you can let a market form, and when markets form, I
mean, this is another one of the rallying cries of
the internet, of technology. It just allows market
forces to enter into places that have just been ossified by firms. You know, if you look
at, for example, Uber or, you know, deconstructing
taxis or Airbnb, you know, deconstructing hotels, you know, good things seem to happen when you allow market forces to enter. Technology can enable. – [Steve] On the second floor,
a big slider, a glass slider. You have to go towards the back yard. Sorry. There’s a huge noise that
we’re trying to address. I’ll come do it if you can’t. – [KK] Again, I think it’s
another sign from God. – [Steve] Yeah, that’s really
not where we are right now. Sorry about that. Let’s shift gears, ’cause
I’m noticing the time. – [KK] Yeah. – [Steve] Let’s talk about blockchain. – [KK] Yeah. – [Steve] And obviously
how that applies here. We’ve set it up. Just one a second. I’m
gonna ask the question and let you answer it. – [KK] Yeah, sure. – [Steve] The question is,
how does this map to the blockchain, everything from
the ledger to, you know, elements of distributed trust,
and why might the elements of what we learned from the
crypto, you know, world, apply to everything we’ve
just been talking about? – [KK] Yeah, sure, and so, I
think one of the analogies, actually I was tuning
into the CryptoKitties presentation, and they
actually had a very clear slide where it sort of said, the
internet has connected us, but blockchain is really the substrate for us to collaborate. So, if you go back to this MIT example, people just sort of took the
centralized trust of MIT, but, you know, what if
you actually had this on a decentralized or trustless way, do you didn’t actually
have to trust anyone? We could guarantee convergence. We could guarantee that the
value will be attributed to you as a matter of
mathematical protocol. So you could just sort of like
download, it’s open source. You can download the code
and convince yourself that it’s convergent, that you can audit, there’s this high transparency
and high auditability in the chain that you can
sort of see the transactions are sort of being routed or
being allocated properly, and even more fundamental than that, it’s sort of like, if you
look at the gatekeepers now, the large companies, right, you as a user might get value from a market
across, across many of them; however, they have no
incentive to actually do that. And so, imagine a way that I can do sort of like distributed exchange of incentives from party A to party B, and I
can extract the value of them without part A and party B being in a trusting
relationship with each other. Facebook and Google are
never gonna trust each other, but, you know, maybe there’s
a way to compose these on a blockchain so that,
you know, you can create this ecosystem where it can
operate, operate trustlessly. And so that’s, that’s,
that’s part of the vision. – [Steve] So tell us how
you’re gonna build this? What’s the, what’s the plan of how you get from here to there? I’m just really curious about that. – [KK] Yeah, yeah, yeah. So this is, this is a lot
of fun, and by the way, just as a little bit of a plug, you know, we are hiring,
so please, you know, feel free to email me at [email protected], you know, if you’re interested
in any one of these topics. Yep, ncnt.,, and
also, you know, follow us on Telegram and Twitter
and whatnot as well. But, really, there’s really
kind of three big steps here. One is sort of, we’re
launching a new chain, and the difference between
our chain and other chains is that our chain is
designed from the ground up. Every design decision
is optimized to be able to facilitate incentive markets. So, unlike the Turing Complete
Smart Contract chains, we are sort of able to be more specialized around this incentive market use case. So it’s a matter of sort
of just focus, and we think these incentive markets
can be widely applicable to lots of different categories, and so, we think by focusing, and
the reality is on some level, it’s a bit of like a, you know, like a bit of a mundane task from an
implementation standpoint. It’s sort of like accounting. Value attribution is just
sort of like accounting, but if you get that right, you can unlock all this
other stuff on top of it. So, so that’s, you know, the first kind of like substrate
of what we’re doing. The second is we’re, you
know, sort of, you know, I think anyone who’s building
a protocol has to be really, really driven by building
great tools for developers. You know, that’s why we’re here, and we really want to kind of
project sort of an API-first, having very thoughtful
SDKs of our products, and having great libraries that compose into launch applications. Some of the initial launch
applications that we’re going to market with are around
customer acquisition, sort of how can you incentivize a
community to find a customer. Typically, these, a good
place to start for these ends up being domains
that are hugely tribal, so professional sports, for example. You know, we have a couple of
professional sports partners in our investor group,
really tribal brands. We were talking about like
LaCroix water earlier, or, you know, like Lululemon
yoga pants or Subaru cars, just anything that has the property where there’s high brand loyalty. – [Steve] Fanatical user base, is that? – [KK] Fanatic user base,
fanatical user base, where there’s sort of, sort
of like the viral network is already, the social
network, the viral network has already been sort of established. – [Steve] Mmhmm. – [KK] So you can kind
of like grok off of it. And there’s many, many
other use cases there. A second thing that we’ve
been doing internally, and Steve alluded to this earlier, is recruiting, so, other than one person, every single person from
nCent has been recruited using the same dynamics
of what we call JobCent, which is sort of a
recursively incentivizing a large community of
developers to help talent come to your company. So, if you think about headhunting, it’s kind of a strange market. You have a natural social
graph of developers, and then you kind of have
these like headhunters who kind of like ingratiate
themselves with everyone and try and insert themselves
into the graph to be able to like, extract all this
economic rent off of it, but actually, if you sort of like spirited the community of developers themselves, and oftentimes, just a
matching problem, right? You just need to find the right position that matches the interests,
capabilities, and skills of the right person, and if
you can kind of like spirit a community of developers, even ones that maybe don’t even
necessarily wanna work here but they know other people,
you know, you could just sort of like have all those
incentives kind of be like passed back into the community to make the community stronger,
to augment the community rather than kind of
like, have this strange like principal/agent problem
with like headhunters. And this works really
with any agent market. And so, the recruiting
use case is something that we’re really grokking
for our own internal use, and another internal use is, you know, this sort of what we
call BuildCent, which is sort of our way to incentivize
open-source development. You know, the reality is,
I think we as a blockchain can be more about customer
acquisition and how we build a user community. I mean, right now, the state
of the art in blockchain is like Airdrops, and this
is something that like, you know, my young daughters
could come up with, just like, you know, dropping blocks. – [Steve] I mean, it is a bit
disturbing how many tweets, I think it’s maybe a
quarter of all the tweets aimed at me these days,
are get this great Airdrop. It’s, you know, good team, high quality. Same message every day. – [KK] Yeah, and if you have like, you just get like spam of
all kinds of like random. So, it’s a little bit,
like, strained, and so, I think we have to do better. I think part of what we
wanna do for our community is have more thoughtful incentives. I mean, yeah, we’ll do something
that looks like Airdrop, but we wanna kind of have kind
of an incentives substrate to be able to like sort
of encourage the right, the right things and speaking
to sort of developers, incentivizing kind of like
useful and creative work. Build Challenge is another
great example of sort of like, a version two. Stellar, for example, does
amazing build challenges, you know, so we’re kind of
more kind of in that direction, and then, you know,
sometimes people ask me, like, every week, I do calls
on Tuesday at six o’clock, just open calls with the community, whoever wants to join, and one of the questions
I always get asked is sort of like, well,
KK, like, what are your most favorite applications? And obviously, the Jobs one speaks really, hits close to home, ’cause
that’s like our people, so we’re sort of like
really like that one, but I mean, it sounds kind
of corny, but like, you know, we’re building a protocol. So we’re building tools for
developers to create things. And so, like, our favorite
application is sort of like the one that hasn’t been developed yet, the one that someone’s
gonna pick up with their API and figure out that this dynamic
works really, really great for x, y, z market, and
then the challenge is, how can we build a community
to exchange this information and sort of like syndicate it,
you know, on a global scale. So, we obviously had our
community manager Popcorn here a little bit earlier, you know, but up until now, we’ve
kind of been a little bit in hacker mode, and, you
know, really starting today, we wanna start having a
more sophisticated message and start opening up to
the community a little bit, you know, on Telegram and
some of the other channels. You know, we hope to have
a more vibrant GitHub with some interesting
kind of side projects. You know, we had this like, logo contest, which is just sort of like a way to kind of spirit our community
a little bit to help us out with design tasks, but it’s
really, at the end of the way, gonna come down to, we
call it nCent Nation. – [Steve] Mmhmm. – [KK] And kind of empowering
developers to wanna join nCent Nation and try out your own markets, figure out what works
and what doesn’t work, and I think, you know, one of
the themes that we said before is that, you know, it
feels like the early days of the internet, and we know
that there’s something really, really powerful here, but on some level, we’re all kind of joined at
the hip in this colossal, worldwide hunt for like,
product market fit. – [Steve] Yeah. – [KK] And so, we just are
like kind of like setting the substrate and setting the
primitives up so we can like, cycle, really, really quickly, and globally exchange all the information to just get smarter
faster and faster, and so that’s a little bit of the,
the hope of the community. – [Steve] In the time that remains, like, I wanna make sure that we’re addressing questions and things that have come up. I noticed in the comments,
people pieced together finally that nCent relates
phonetically to incentivize. – [KK] Yeah. – [Steve] Right, incentive, so just, see if that’ll help you remember. – [KK] And yes, just to
address all the rumors, that was a real torch,
that was a real fire. (both laughing) – [Steve] And what this thing
was, it’s a rocket engine, for those who miss the
beginning, and we wanted to have a fireside chat, so, you
know, when you wanna go to the moon, you should
bring a rocket engine. It’s from a local Silicon Valley startup that’s helping me get to
space this weekend coming up. Not one I’m invested in,
but one that I’m supporting and cheering for. Yes, it is a real fire. We will also, I love my Model Three. It’s obviously off-topic. (both laughing) But I would encourage everyone to try one. And maybe, yeah, you actually,
actually happen to hit a lot of the questions about
about product market fit. So perhaps, I’m gonna try to think. Are there any of those
that you wanted to grab that we didn’t cover
yet, ’cause otherwise, I wanted to ask you something
completely different. – [KK] Yeah, I think we
pretty much talked about many of these. I think that one area that, you know, we sort of wanted to talk about is again, on this theme of community building. One thing that we do
internally in our culture is sort of have this
teacher-learner model. You know, so we have our
kind of world-famous nTerns, and we spend a lot of time
talking about blockchaining. Every Tuesday we have a reading circle where we just talk
about blockchain papers, and we try and get smarter on blockchains. So, in some ways, you know, we’re trying to be a little bit, like,
humble with our approach, and we really wanna kind of
engage, engage the community, and we’re not necessarily
trying to say that, you know, we’re the smartest
people in the world here, but blockchain is an incredible and phenomenal substrate for incentives. I would argue that Bitcoin works. I mean, I sometimes
call myself a little bit of like a Bitcoin maximalist, and I know it’s a bit
of a controversial term, but that’s only because, you
know, sort of like, like many people, my first experience
in blockchaining was Bitcoin. And so there’s a certain kind of like, you know, romance to the design of that, and the second you kind of
like grok what the aims were and how it actually worked
in practice, you know, some strange, like, neutral
pathways end up forming and firing, and so it’s less
to be like kind of political or wary wading into this whole
Ethereum, altcoin type thing, but, you know, it truly is,
you know, a beautiful piece of technology, and it truly
is a beautiful system, but let’s be honest, even the
strongest Bitcoin maximalist among us would probably concede that it’s not a particularly
elegant distributed system. Proof of work is like a, I
would say it’s like a big, dirty hammer, and, you know,
it’s not particularly elegant in terms of mathematical properties. It has like, probabilistic finality. It’s not even guaranteed
to come to consensus. I mean, you just go down the list. It’s terrible for environment
with the way it’s set up anyway, but then there’s ASICs involved and centralization, but that’s all fine, but the reality is, it
works because of incentives. Incentives is the piece that people miss, and, you know, a lot of
times, academics come up with like, great new consensus protocols or great new technology
of scalability and whatnot or infrastructure, but,
sort of, incentives is the thing that makes all of them go. And so we just think
that like, more people should be working on
the incentive problem. And so, that’s kind of why we
named the company nCent, too. – [Steve] Actually something,
this does remind me of maybe one last question that I think’s special given your background. Again, this unusual
combination of experience, having worked at a
statistical arbitrage firm like D.E. Shaw and working
on quantitative, you know, day trading, if you will
in high-frequency modeling. What can you make of
that in the crypto space? There’s been a number of funds forming. – [KK] Yeah. – [Steve} Which to me,
just my first reaction is, where is there enough liquidity to pull something like this off, and what are your thoughts on that? – [KK] Yeah, you know, obviously, this speaks close to my heart, being kind of an
ex-statistical arbitrage trader and kind of seeing every trick
in the book on Wall Street. It’s sort of like sometimes,
it’s sort of like, the more things change, the more things kind of stay the same. And, you know, I would actually say, just in my judgment,
being a stat arb trader, that there actually is no
alpha or outperformance systematically to be gained in investing in stat arb funds in crypto. You know, that might be a bit
of a controversial statement, but you definitely hit one
nail on the head is liquidity. You know, if you look
at volumes in the space, just from a technical standpoint, you know, oftentimes, those
volumes are misleading. You know, as the old expression goes, volume is what you see, but
liquidity is what you get. And what you really care
about is your exit liquidity. And all of volume and liquidity, it goes into one statistical
model, and that is your essential transaction cost
when you need to liquidate. And so, a better model is, what do I think the probability of having
to liquidate the trade is, times the transaction cost
that I’m going to incur on the day that I need to liquidate, and that’s kind of an
unbounded thing in crypto. I would also say that, you
know, a lot of the fees out there are kind of
absurd, almost usurious, especially given the bid/offer spreads. Most investors are probably better off just holding Bitcoin with zero fees. And there are custody solutions
for institutions as well that are getting better, to the extent that that needs to be something
that’s a custodied process. But there’s many, many reasons
why statistical arbitrage just isn’t there right now in crypto. There’s been a lot made about exchanges, and I know that there’s a
decentralized exchange panel. It’s obviously very topical with Bancor. It has its own, you know,
issues with decentralized exchanges and how centralized
really are these things if you offer sort of certain
types of functionality, but, I mean, the exchange
market is designed to essentially exploit
insider information. And so, the reality
is, insider information is rampant in this space. And so, you know, I think we all need to grow up as a market. I mean, either this is gonna
become an institutionalized market that’s credible
for capital formation, or it’s gonna be a den of
asymmetric insider information. It can’t be both. So, I think anyone with a vested interest and a long-term interest
of institutionalizing and building this out into a real market should be very, very
cognizant of the issue, and again, I would be, be
very, very wary of anyone trying to traffic a
stat arb fund in crypto. I’ve been pitched them before,
and these sort of black boxes in this space, for many, many reasons that are even more
technical to get into here, and the thing about stat
arb, right, it’s sort of like you’re trying to make a
weighted roulette wheel. And the reality is, there
aren’t enough independent bets that you can make in crypto to make that wheel spin enough times. If you have a casino that
has a roulette wheel, and you only get to spin once a day, that’s not a very good business model. Stat arb requires lots and
lots of independent bets, and the reality is,
there’s not enough liquid independent bets that you
can make out there in crypto on an institutional basis. – [Steve] I’m noticing our
host has popped back on, which I think is our signal. – [KK] All right. – [Steve] That our time is done. Is that a safe assumption? – [Ed] Yeah, I just wanna thank
both of you for being here. You know, the audience and
I learned a lot about what you’re up to here, and I
think it’s super inspiring. In fact, one of our audience members said that he thought this was
his favorite session so far at Hack Summit, and that these guys really get the why of the blockchain, and they’re able to help
us understand it as well. And so, I think you guys
are really onto something, and, you know, we really hope
that the market networks, the incentive networks that
you build out in the future will really help people to solve problems and help humanity in ways that
we can’t even imagine today. And so Steve and KK, we really wanna acknowledge you for being here. We know how busy both of you are, and for choosing Hack Summit
as the venue to launch this. Thanks so much for being here. We really appreciate your time. – [Steve] Sure, thank you. – [KK] Thank you. We appreciate the opportunity, and thanks to everyone at nCent Nation. To the moon. – [Ed] To the moon! And we’ll be right back, guys, with the team from Kadena, who’s building a scalable high-end
blockchain for businesses with the first human readable
Smart Contract language. We’ll be right back, guys. Stay in here. You’re not gonna wanna miss it. Three of their leadership team members are here with us together. So thanks, again, guys,
and we’ll see you soon. – [Steve] Thank you.
– [KK] Thank you.

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