>> Announcer: Live, from Copenhagen, Denmark, it's theCUBE!
Covering Nutanix.NEXT 2019.
Brought to you by Nutanix.
>> Welcome back everyone
to theCUBE's live coverage of Nutanix.NEXT.
We are at the Bella Center in Copenhagen, Denmark.
I'm your host, Rebecca Knight,
alongside of Stu Miniman, of course.
We are joined by a good friend of theCUBE, Ray Wang,
principal analyst and CEO of Constellation Research.
Thank you so much for returning to theCUBE.
>> Hey, how you doing?
Good morning!
>> Good morning, good morning!
>> Good morning! (laughing) >> Good morning!
>> I don't know.
I get all my accents wrong out here.
>> (laughing) So, you got a shout out on the main stage
this morning, from Monica Kumar, congratulations on that.
She talked about you and your research on the
infinite role of computing.
You also do a lot with the future of work.
I know that that is really right
in your wheelhouse right now.
What are you hearing, what are you seeing,
what kinds of conversations are you having
that are interesting you?
>> Yeah, so, this infinite computing option,
it's one of the that we're talking about, the fact that
you can scale out forever, right?
And the problem that's holding us back has been
technical debt, right?
So all that legacy that everyone's got to figure out.
It's like, my connections, my server, my disk-rack recovery,
my disaster recovery, my backup, everything.
It's a pain in the butt.
And I'm still trying to get onto the cloud.
So on that end, we're like,
okay, all this stuff is holding us back,
how do we get there?
Now, the future of work is a little bit different.
We're seeing a very very different set of work.
People have talked about where we are the gig economy,
but that's just one aspect of it.
Everything is being decomposed into microservices.
Large processes are becoming smaller and smaller
microservices, they're being reusable,
well our work and tasks are following the same way.
We're getting smaller and smaller tasks,
some are more repetitive, some are going to be automated,
and it's really about where we actually find
the difference between augmentation of humanity,
and full automation,
and that's where the next battle's going to be.
>> Yeah, Ray, some of the discussions we've been having
this week, is how do we really simplify the environment?
The balance I hear from customers, on the one hand,
they're always like, I don't have enough money,
I don't have enough personnel, on the other hand,
oh my gosh, that full automation sounds like
you're going to put me out of a job.
We know we're not putting everybody out of work
in the next couple of years.
There are challenges;
we worry about the hollowing out of the center
of the economy,
but here, what Nutanix is trying to do,
of course, is, I don't want to have to
thrive in that complexity anymore, I want to be able to
drive innovation, keep up with that, take advantage of that
unlimited resources out there, so, where do you see,
you've been here at the show, what are you hearing
from the customers here?
Anything different in Europe versus back in North America
that you'd share about that journey onto the changing roles?
>> Oh it's a great point.
It's about simplifying everything where you can,
it's about areas of automation where they make sense.
Here in Europe it's slightly different
because a lot of the focus in Europe has been about
cost and efficiency, followed by of course regulatory.
Those have been the two drivers.
And they've been battling that in order to be,
even they will look at some level of innovation.
Where in the US, people are head on doing innovation,
regulatory and operational efficiency at the same time.
So that creates a very very different environment.
But what we have noticed are some patterns,
especially when we look at automation and AI;
there are four areas out of seven
where we see a lot more automation that's happening.
The first one is massively repetitive tasks,
those are things, yeah, got to get that out of the way,
we don't do this very very well.
The second one is really thinking about
massive nodes of interaction.
When you're connected to multiple places,
multiple organizations, multiple instances,
that's something where we start to get overwhelmed,
and then of course, there's lots of volume.
If you've got lots of volume or requests
that are coming through, you can't possibly handle that,
and that's a place where we see a lot of machine scale.
And the last piece is really when you have to scale,
humans don't scale very well.
However, it's actually not a hollowing out of the middle;
it's actually a hollowing out of the ends
in a very, very real end,
because really really simple tasks go away,
super complex tasks go away,
and the middle actually remains, and the middle is
things that are complex that cannot be recreated by math,
they're also areas that require a lot of creativity,
humans make the rules, we break the rules,
and then the last part is really
fine motor skills and presence,
the machines still aren't as good.
So we still have some hope.
So the middle stays, it's the hollowing out of the ends,
the high end jobs and the low end jobs are the ones
where we're going to see a lot of risk.
>> So what does that mean?
So we have, leaving the middle there, and as you said,
the high end jobs and the low end jobs go away,
but what does that mean in terms of the skills?
In terms of what employers are looking for,
in terms of what they need
in their prospective applicants and hirees.
>> That's a great point.
Soft skills are important;
it's the qualitative skills that become even more important,
it's also being able to manage
and orchestrate the hard skills;
because you don't necessarily have to know
how to do the calculation, you have to just know
which algorithm to apply.
>> Okay, and then also, these soft skills of managing people,
I'm assuming too?
Because computers are not so good at that either.
>> Yes.
Soft skills are managing people,
but also manage the human and machine equation
that's going to happen.
Because we have to train the machines,
the machines aren't going to know that level of intuition,
and there's a large amount of training
that's going to happen over time.
>> All right.
So, Ray, one of the things Nutanix is doing is,
as they've been transforming to not only subscription,
software's always been at their core,
but they're starting to do not just infrastructure software,
but application software.
I know you live in that world quite a lot,
so when you hear Nutanix talking about building databases,
delivering these services, it's something that I look at,
Amazon does some of that,
but for the most part they're infrastructure
and build on top of us.
How do you think, how is Nutanix doing,
what are some of the challenges for them,
going up against some of the bellwethers out there in tech,
and all the open source projects that are out there.
>> So the challenge is always going to be,
there is a one dominant player in every market.
And what they're providing is an alternative
to allow the orchestration of not having that,
not only that dominant player, but a choice.
So in every single market, they're focused on
giving users choice, and giving the ability to aggregate,
and bring everything into one single plane.
That is tough to do, right?
And the fact that they see that as their big hairy
audacious goal, that's impressive.
If you said they were going to do this three years ago,
I wouldn't have believed them.
>> Well yeah, I think back to,
remember almost 10 years ago,
VMware tried to get into applications,
they bought Zimbra, they bought a few others.
Cisco did like 26 adjacencies,
they were going to take over video and do all these things,
and we've seen lots of failures over the years.
They refocused on their core, was a big thing that I heard,
that the users seem to be excited about.
Are there areas that you're find especially interesting
as to where Nutanix is poking?
>> So, I would say that Nutanix three years ago
was a little bit sleepy.
They got comfortable, they did the stuff
that they did really well, and it feels like,
maybe about 12 months ago,
Dheeraj had a different vision.
Like something snapped, something hit,
he said this isn't working, we're going to change things,
and we've seen a whole bunch of new talent come into play.
We've also seen a huge expansion of what they're trying
to do, and a cleanup of all those
side projects that were all going on before.
So I think they've actually honed in on,
okay, if we can simplify this piece,
this is a money-winning business for some time,
and they're talking about 80% margins last quarter,
I mean that's huge, and that's just trying
to save customers money, and make their lives simpler.
>> Do you think that they have the messaging right?
Because, I mean, they're going
to this Thoreauvian/Emersonian idea
of simplify, simplify, simplify,
and it does resonate, of course!
What customer doesn't want a simpler computing experience?
But do you think that they are reaching the right people,
and they have obviously very passionate customers,
but are they getting into new businesses.
>> I think they're getting to the businesses
that their customers are asking them to,
those adjacencies are huge,
I think and when you think about cleaning up technical debt,
all that legacy debt that you actually have to fix,
I mean, this is where you begin.
It's so hard to make that cloud journey to begin with,
it's even harder to carry all that legacy with you.
And we're going to see a lot more of this going forward.
>> All right.
So, Ray, talk a little bit about,
I loved an event you did last year,
the people's centered digital future.
Help explain to our audience what this is about,
and where you're taking it again this year.
>> So that event was a one-time event.
We were celebrating the 70th anniversary
of the United Nations founding,
we were celebrating almost 50 years of the internet,
and 50% of the world being connected to the internet.
And part of the reason that was an important event was,
we really felt that there was a need to get back
to the roots of where the internet had begun,
and more importantly, talk about where we are today
in the world of privacy.
One of the biggest challenges we have in the a digital world
is that your personal data, your genomics,
all this information about you is being brokered for free.
And what we have to do is take that back.
And by taking that back, what I mean is,
we've got to make all these rights, property right.
If we can make that a property right,
we can leverage the existing rules and legislation
that's there, and we can actually start paying people for
that data through consent, and giving people that ability,
on consent to data, could create lots of things,
from universal basic income, to a brand new set of
data economy that equalizes the playing field,
while keeping the large tech giants.
>> There's some of those big journeys that we went on,
you talk about the internet, this year's 50th anniversary
of the first walking on the moon,
and you look at how entire countries rallied together,
so much technology was-- >> Yeah, look at India.
>> Spun off of what they've done there,
it's like we need some rallying cries in today's day and age
to solve some of these big day and age.
Is that AI?
Where are some of the big areas that you see tech
needing to drive forward in the next decade?
>> I think the big area's going to be around decentralization,
giving individuals more empowerment.
We've got large, big tech companies,
that are, I'd say, imbalanced.
We start companies right away,
building monopolies on day one,
and we don't open up those markets.
And the question is, how do we create a level playing field
for the individual to be to compete, to bring a new idea,
and to innovate, if that's continuously stifled
by big technology companies without an opportunity,
we're in trouble.
And so that starts by making data a property right,
to the personal data.
It starts by also creating marketplaces for that data,
and those marketplaces have to have regulations,
similar to capital market flows.
The way treat exchanges, we treat marketplaces,
we need to do the same thing with the way we do with data,
and then the third piece, there has to be some level
of a tax, that goes to all these data economies,
so that they can fund the infrastructure
and the watch dogs that are there.
Now this is coming from a free market,
I'm a free market capitalist, okay?
I can't stand regulation, but I also realize that
it's so important that we have a fair market.
>> But do you, we know so much about how Americans are
so much more cavalier about their privacy
than even Europeans, what will it take
to galvanize Americans to care about those little crumbs
that they're leaving on the internet, that is the data
that you say should be a property right,
that we should be paid for?
>> I think it's going to start with companies actually take,
and do the right thing, where they actually
give them that opportunity to monetize that information.
>> Will they do that? >> I think the new set
of startups are starting to do that,
because they're looking at the risk that's being posed,
at Facebook and Google and Amazon,
on the anti-trust, DOJ, FCC, they're all coming in
at the same time, the FTC, they're all wondering,
do we break these companies up or not?
The short answer is, I don't think they're going to,
because we're competing with China,
and when you're looking at that scale of data,
where Amazon's transactions are only 1/10 of Ali Baba's?
That's huge.
So the consolidation has to happen,
but we need to create a layer that actually democratizes
and creates a fair trading play.
>> And those startups, you think,
can compete with established players?
>> I think once we set the roles, and the ground rules,
I think people are going to be able to do that,
but once you free that data, what are we competing on now?
You have to pay for my consent,
you have to earn my business, you can't trade it for free,
or just say, "Hey look, you are the product."
That changes everything.
>> Rebecca: Yeah, that's a good point.
>> Ray, I know you spend a lot of time talking to,
and giving advice to some of the leaders in technology,
you're welcome to get into some specifics about Nutanix,
or some of the cloud players,
but what are some of the key themes,
what are people getting right,
and what are they still doing wrong?
>> Okay, so theme number one,
this is going to be a multicloud hybrid world for a long time.
Anybody that's bucking the multicloud trend,
they've missed the point, right?
Because we want portability in data,
there's only two or three players in every single market,
if I can't move my data, my workloads, and my IO in and out,
then you've actually created vendor lock-in from hell.
And I think customers are going to protest against that.
The second one,
and you guys are probably following this trend a lot,
is really about AI ethics and design principles for AI.
So what is ethical AI?
We've got five things that are important:
The first one is make sure it's transparent.
See the algorithms, see what they write.
Second one, make sure it's explainable.
Hey, bias is not a bad thing,
so if I'm discriminating against redheads,
with, left-handed, and that happened to like,
I don't know, Oracle, fine.
But, if that was unintended,
and you're discriminating against that,
then we have to get rid of that, right?
And so we have to figure out how to reduce
that kind of bias, if it's unwanted bias.
If you discover that you're discriminating,
and not being inclusive,
you've got to make sure that you address that.
So then the next part is, it's got to be reversible.
And once you have that reversibility,
we also make sure that we can train these systems over time.
And then the last piece is, Musk could be right!
Musk could be right, the machines might take over,
but if you insert a human at the beginning of the process,
and at the end of the process, you won't get taken over.
>> I want to hear about what the future of work
looks like for Ray Wang.
You are on the road constantly, you are (laughs)
you are moving your data from one place,
you are everywhere, all the time.
So what do you have on next,
what's exciting you about your professional life?
>> I think the challenge's that
we are living in a world where there's too much information,
too much content.
And you guys say this all the time, right?
Separating the signal from the noise.
And people are willing to pay for that signal.
But that is a very very tough job, right?
It's about the analysis, the insights,
and when you have that,
people don't want to read through your reports.
They don't want to watch through the videos.
They just want to call you up and say,
"Hey, what's going on?"
And get the short version of it.
And that's what's making it very interesting,
because you would expect this would be in a chat bot,
it'd be in a robo advisor, doesn't work that way.
People still want the human connection,
especially given all that data out there,
they want the analysis and insights that you guys provide,
that's very very important,
but even more important right now,
it's really about getting back to those relationships.
I think people are very careful
about the relationships they're keeping,
they're also curating those relationships,
and coming back to spending more time.
And so we're seeing a lot more of in-person meetings,
in-person events, very very small, curated conversations,
and I think that's coming back.
I mean that's why we do our conference every year, as well,
we try to keep 200 to 300 people intimately together.
>> Those human connections, not going away. (laughs)
>> Nope, not going away, in an automated, AI, digital world!
This is our post-digital future.
>> That's excellent.
Well Ray, thanks you so much for coming on theCUBE,
it's always so much fun to talk to you.
>> Hey, thanks a lot. >> High energy guy (laughs).
>> Low energy.
>> I'm Rebecca Knight for Stu Miniman,
we will have more from the Bella Center at Nutanix.NEXT
coming up in just a little bit.
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