>> From Sand Hill Road,
in the heart of Silicon Valley, it's theCUBE!
Presenting the People First Network,
insights from entrepreneurs and tech leaders.
>> Hello everyone, I'm John Furrier with theCUBE.
We are here on Sand Hill Road
at Mayfield's Venture Capital Headquarters
for the People First Network.
I'm here with Pradeep Sindhu,
who's the co-founder of Juniper Networks
and now the co-founder and CEO of Fungible.
Thanks for joining me on this special conversation
for the People First Program.
>> Thank you, John.
>> So I want to talk to you about entrepreneurship.
You're doing a new startup,
you've been so successful as an entrepreneur over the years,
uh you keep building a great company at Juniper Networks,
everyone kind of knows the success there, great success.
We've interviewed you before on that,
but now you got a new startup!
>> I do.
>> You're building a company
I thought startups were for young people.
(Pradeep laughs) Come on!
We're nine years into our startup, we're still a startup.
>> Well, I'm not quite over the hill yet.
(John Laughs)
One of the reasons I jumped back in to the startup world
was I saw an opportunity to solve
a very important industry problem
and to do it rapidly and so, I took the step.
>> Well, we're super excited
that you shared your vision with us
and folks can check that video out on theCUBE
and deep dive on the future of that startup.
So, it's exciting, check it out.
Entrepreneurship has changed and one of the things
that we're talking about here is how things
have changed just since the last time you've done a round.
I mean, you're now a couple years in,
you've been stealth for a while building out
this amazing chip, the the Data Processing Unit, the DPU.
What's different about building companies now?
I mean, are you a unicorn?
You have a billion-dollar evaluation yet?
I mean, that's the new bar, it's different.
What are some of the differences now in building a company?
>> You know, one thing, John, that I saw
is a clear difference between when I started Juniper
and started Fungible,
is that the amount of bureaucracy and paperwork
that one has to go through is tremendously larger.
And this was disappointing because one of the things
that the US does very well is to keep it light
and keep it fast so that it's easy for people
to create new companies.
That was one difference.
The other difference that I saw was
actually reluctance on the part of Venture
to take big bets.
Because people had gotten used to the idea
of a quick turn around
with maybe a social media company or something.
Now, you know, my tendency to work on problems
is I tend to work on fundamental problems
that take time to do,
but the outcome is potentially large.
So, I'm attracted to that kind of problem.
And so, the number of VCs that were willing
to look at those kinds of problems
were far fewer this time around than last time.
>> So you got some no's then?
>> Of course, I got no's.
Even from people that-- >> You're the Founder of
Juniper Networks, you've done amazing things,
like you created billions of dollars of value,
you should be gold-plated.
>> What you did 20 years ago only goes so far.
I think what what people were reluctant,
and remember, I started Fungible in 2015.
At that time, silicon was still a dirty word.
I think now there are several people who said,
no, we're regretting because they see that it's
kind of the second coming of silicon
and it's for reasons that we have talked about
in the other discussion that, you know,
Moore's Law is coming to a close.
And that the largest that it was distributing
over the last 30, 40 years
is going away so what we have to do
is we have to innovate on silicon.
You know, as we discussed, the world has only seen
a few architectures for computing engines on silicon.
One of the things that makes me very happy
is that now people are going to apply their creativity
to painting on this canvas.
>> So, silicon's got some new life blood.
What's your angle with your silicon strategy?
>> So, our silicon strategy is really to focus
on one aspect of computations in the data center
and this aspect we call Data Centric Computing.
Data Centric Computing is really computing
where there's a lot more movement of data
and lot less arithmetic on data.
And today, giving scaled out architectures,
data has to move and be stored and retrieved and so on
as much as it has to be computed on.
So, existing engines are not very good
at doing these Data Centric Computations,
so we are building a programmable DPU
to actually do those computations
much, much better than any engine can today.
>> And that's great.
And just a reminder, we got a deep dive on that topic,
so check out the video on that.
So, I got to ask you the question,
why are people resistant at the silicon trend?
Was it trendy?
Was it the lack of information?
You almost see people almost less informed
on computer architecture these days
as people Blitzscale for SASPA businesses.
Cloud certainly is great for that ,
but there's now this renaissance.
Why was it, what was the problem?
>> I think the problem is very easy to identify.
Building silicon is expensive.
It takes very specialized set of skills.
It takes a lot of money, and it takes time.
Well, anything that takes a long time is risky.
And Venture, while it likes risk, it tries to minimize it.
So, it's completely understandable to me that, you know,
people don't want to take, they don't want to put money
in ventures that might take two, three years.
Actually, you know, going back to the Juniper era,
there are Venture folks, I won't name them, but who said,
well, if you could do this thing in six months,
we're in, but otherwise no.
>> How long did it take?
>> 2 1/2 years.
>> And then the rest is history.
>> Yeah. >> So, there's a lot
of naysayers, it's just categorical kind of like, you know,
courses for horses for courses,
as they say, that expression.
All right, so now with with your experience, okay,
you got some no's, how did that, how did that make you feel?
You're like, damn, I got to get out and do the rounds?
>> Actually-- >> You just
kind of moved on or?
>> I just moved on because, you know,
the fact that I did Juniper
should not give me any special treatment.
It should be the quality of the idea that I've come up with.
And so, what I tried to do,
my response was to make the idea more compelling,
sharpen it further, and and try to convince people
that, hey there was value here.
I think that I've not been often wrong
about predicting things maybe two, three years out,
so on the basis of that people were willing
to give me that credibility,
and so, there were enough people
who were interested in investing.
>> What did you learn in the process?
What was the one thing that you sharpened pretty quickly?
Was it the story, was it the architecture message?
What was the main thing
that you just had to sharpen really fast?
>> The thing I had to sharpen really fast
was while the technology we were developing is disruptive,
customers really, really care,
they don't want to be disrupted.
They actually want the insertion to be smooth.
And so, this is the piece that we had to sharpen.
Anytime you have a new technology,
you have to think about, well,
how can I make it easy for people to use?
This is very, very important.
>> So the impact to the architecture itself,
if it was deployed in the use case,
and then look at the impact of ripple effect.
>> For example, you cannot require people
to change their applications.
That's a no-no.
Nobody's going to rewrite their software.
You also probably don't want to ask people
to change their network architecture.
You don't want to ask people
to change their deployment model.
So, there are certain things that need to be held constant.
So, that was a very quick learning.
>> So, one of the other things that we've been talking about
with other entrepreneurs is okay,
the durability of the company.
You're going down, playing the long game,
but also innovation and and attracting people
and so you've done, built companies before,
as with Juniper, and you've worked
with a great team of people in your network.
How did you attract people for this?
Obviously, they probably were attracted
on the merit of the idea, but how do you pick people?
What's the algorithm?
What's the method that you use
to choose team members or partners?
Because that's also super important.
If you got a gestation period where you're building out.
You got to have high quality DNA.
How do you make that choice?
What's the thought process?
>> So John, the the only algorithm that I know works
is to look for people that are either known to you directly
or known to somebody that you trust
because in an interview, it's a hit or miss.
At least, I'm not so good at interviewing
that I can have a 70, 80% success rate.
Because people can fake it in an interview,
but you cannot fake it once you've worked with somebody,
so that's one very important test.
The other one was, it was very important
for me to have people who were collaborative.
It is possible to find lots of people who are very smart
but they are not collaborative.
And in an endeavor like the one we're doing,
collaboration is very important,
and of course the base skill set
is very important so, you know,
almost half of our team is software because we are--
>> It's a programmable chip.
We're writing our own operating system, very lightweight.
So, you need that combination
of hardware and software skills
which is getting more and more scarce regrettably.
>> I had a chat with Andy Bechtolsheim at VMworld
and he and I had a great conversation similar to this,
he said, you know, hardware is hard, software is easier,
(laughs) and that was his point,
and he also was saying that with merchant silicon,
it's the software that's key.
>> It is absolutely the key.
Software, you know, software is always important.
But software doesn't run on air.
We should also remember that.
And there are certain problems, for example,
switching packets inside a data center where the problem
is reasonably well-solved by merchant silicon.
But there are other problems
for which there is no merchant silicon solution,
like the DPU that we're talking about.
Eventually, there might be.
But today there isn't.
So, I think Apple is a great example for me
of a company that understands the value
of software hardware integration.
Everybody thinks of Apple as a software only company.
They have thousands of silicon engineers, thousands.
If you look at your Apple Watch,
there are probably some 20 chips inside it.
You look at the iPhone.
It won't do the magic that it does
without the silicon team that they have.
They don't talk about it a lot on purpose because--
>> 'Cause they don't want a China chip in there.
>> Well, they don't want a China chip,
but not only that, they don't know to advertise.
It's part of their core value.
>> Yeah.
>> And so, as long as people keep believing that everything
can be done in software, that's good for Apple.
>> So, this is the trend,
and this is why, Larry also brought this up years ago
when he was talking about Oracle.
He tried to make the play that Oracle
would be the iPhone of the data center.
>> Mm-hmm. >> Which people poo-pooed
and they're still struggling with that idea,
but he was pointing out the benefit of the iPhone,
how they are integrating into the hardware
and managing what Steve Jobs always wanted
which was security number one
>> Absolutely. >> for the customer.
>> And seamlessness of use.
And the reason the iPhone actually works as well as it does
is because the hardware and the software are co-designed.
And the reason it delivers
the value that it does to the company
is because of those things.
>> So you see, this as a big trend,
now you see that hardware and software will work together.
You see cloud native heterogeneous
almost server-less environments
abstracted away with software and other components,
fabric and specialized processors?
>> Yes.
>> And just application developers just programming at will?
>> Correct, and edge data centers,
so computing, I would say that maybe in a decade
we will see roughly half of the computing and storage
being done closer to the edge and the remaining half
being done in these massively skilled data centers.
>> I want to get geeky with you for a second,
I want to ask you a question,
I want to get your take on something.
I've been thinking about
and haven't really talked publicly about,
kind of said on theCUBE a few times in a couple interviews,
but I want to get your thoughts.
There's been a big discussion about hybrid cloud,
private cloud, multi-cloud, all that stuff going on,
and I was talking with Andy Jassy, the CEO of Amazon,
and Diane Greene at Google and I'm like okay,
I can buy all these definitions, I don't believe any of 'em,
but, you know, what the hell does that mean, what I know.
I said to Diane Greene, I said,
well, if everyone's going cloud operations,
if cloud operations and edge is the new paradigm,
isn't the data center just a big fat edge?
And she looked at me and said, hmm, interesting.
So, is the data center
ultimately just a device on this network?
If the operating model is horizontally scalable,
isn't it just a a big fat edge?
>> So you can, so here's the thing, right,
if we talk about, you know, what is cloud?
It's essentially a particular architecture,
which is scaled out architecture uh to build a data center
and then having this data center be connected
by a very fast network.
Two consumers anytime, anywhere.
So, let's take that as the definition of cloud.
Well, if that's the definition of cloud,
now you're talking about what kind of data centers
will be present over time,
and I think what we observed was it's really important
for many applications to come, and with the advent of 5G,
with the advent of things like augmented reality,
now, with the advent of self-driving cars,
a lot of computing needs to be done close to the edge
because it cannot be done,
because of laws of physics reasons,
it cannot be done far away.
So, once you have this idea
that you also have small scale out data centers
close to the edge,
all these arguments about whether it's a hybrid cloud
or this cloud or that cloud, they kind of vanish because--
>> So, you agree then, it's kind of like an edge?
>> It is.
>> Because it's an operational philosophy
if you're running it that way, then it's just what it is,
it's a scale out entity.
>> Correct.
>> It could be a small sensor network
or it could be a data center.
>> Correct.
So, the key is actually the operational model
and the idea of using scaled out design principles,
which is don't try to build
50,000 different types of widgets
which are then hard to manage.
Try to build a small set of things, tinker toys
that you can connect together in different ways.
Make it easy to manage, manage it using software,
which is then centralized by itself.
>> That's a great point.
You you jumped the gun on me on this one.
I was going to ask you that next question.
As an entrepreneur who's looking
at this new architecture you just mentioned,
what advice would you give them?
How should they attack this market?
'Cause the old way was you get a PowerPoint,
you show a presentations of the VCs,
they give you some money, you provision some hardware,
you go on next generation, get a prototype,
it's up and running, you got some users.
Built it then you get some cash, you scale it (laughs).
Now with this new architecture,
what's the strategy of the eager entrepreneur
who wants to create a valuable opportunity
with this new architecture.
What would you advise them?
>> So I, you know, I think it really depends
on what is the underlying technology
that you have for your startup.
There's going to be lots and lots of opportunities.
>> Oh don't fight the trend, which is,
the headwind would be, don't compete against the scale out.
Ride that wave, right?
>> Yeah, people who are competing against scale out
by building large scale monolithic machines,
I think they're going to have difficulty,
there's fundamental difficulties there.
So, don't fight the trend.
There's plenty of opportunities for software.
Plenty of opportunities for software.
But it's not the vertical software stack
that you have to go through five or six different levels
before you get to doing the real work.
It's more a horizontal stack, it's a more agile stack.
So, if it's a software company,
you can actually build prototypes very quickly today.
Maybe on AWS, maybe on Google Cloud, maybe on Microsoft.
>> So, maybe the marketing campaign for your company,
or maybe the trend might that's emerging
is data first companies.
We heard cloud mobile first, cloud first, data first.
>> Correct.
We think that the world really, the world of infrastructure
is going from compute centric to data centric.
This is absolutely the case.
So, data first companies, yes.
>> All right, so final question for you,
as someone who's had a lot of experience
in building public company,
multi-billions of dollars of value,
embarking on a big idea that that we like, I love the idea.
A lot of people struggle with the entrepreneurial equation
of how to leverage their board,
how to leverage their investors and advisors
and service providers.
What would you share to the folks watching
that are out there that have struggled?
Some think, oh the VCs, they don't add value.
Some do, some don't.
There's always missed reactions.
There's different, different types out there.
Some do, some don't.
But in general, it's about leveraging the resources
and the people involved.
How should entrepreneurs leverage their advisors,
their board, their investors?
>> I think it's very important for an entrepreneur
to look for complementarity.
It's very easy to want to find people
that think like you do.
If you just find people that think like you do,
you're not, they're not going to find weaknesses
in your arguments.
It's more difficult, but if you look to entrepreneurs
to provide complementarity,
you look to advisors to provide the complementarity,
look to customers to give you feedback,
that's how you build value.
>> Pradeep, thanks so much for sharing the insight,
a lot of opportunities.
Thanks for sharing here on--
>> Thank you, John.
>> The People Network.
I'm John Furrier at Mayfield on Sand Hill Road
for theCUBE's coverage of the People First Network series,
part of Mayfield's 50th Anniversary.
Thanks for watching.
(upbeat music)