>> Narrator: Live from Austin, Texas
it's theCUBE covering South by Southwest 2017
brought to you by Intel.
Now here's John Furrier.
Welcome back everyone,
we are here live inside theCUBE SiliconANGLE Media's
flagship program.
We go out to events, and extract the signal from the noise,
I'm John Furrier, we're here in the Intel AI Lounge
for South by Southwest special,
three days of coverage,
interviews all day, some interviews tomorrow
and some super demos and panels
with Intel's top AI staff and thought leaders
and experts and management.
My next guest is Suresh Acharya
with JDA Software,
I've got it right? Welcome to theCUBE.
>> Thank you.
>> We were chatting before we were coming on
about the IOT in your world,
but you had made a comment about you were walking around
the convention center-- >> Suresh: Yeah.
>> What's it like outside?
What's the scene look like out there?
>> Well, I mean first of all, it's really fun
to be here for South to Southwest, of course,
and just walking from the convention center here,
there are a lot of places,
but you guys have something going on here,
long lines, it's just a very, you know, a ...
There's a huge buzz if you will. Very exciting.
>> People are partying here,
they got free beer, free booze--
>> Suresh: It's great!
>> If you're watching and you're here at South pie,
you definitely want to be at the Intel AI Lounge,
one it's cooler, all the cool kids are here--
>> Suresh: That's right.
Talking AI which is onstage, it's an AI VR show.
You've seen a lot of virtual reality,
you've seen a lot of AI. >> Suresh: Uh, huh.
>> This speaks to a new interface,
a new interface from a virtual augmented reality,
but also AI from a data centric world--
>> Suresh: Of course. Yes.
>> Your thoughts, cuz this is what you're involved in.
>> Sure, let me tell you a little bit more about what I do,
just to set the context.
JDA we work in the supply chain and those are
manufacturing plants into transportation
into warehouse into stores.
Things that are--
>> Known businesses, known processes.
>> Known exactly. But what is now changing dramatically
is the fact that a lot of this is being digitized.
And not only is data being generated, the smarts,
that's where the AI comes in has really helped
or will continue to help improve efficiencies.
So in your question around what the role of hollow ends
or whatever the VR capabilities could be
and where the smarts come in, if you will,
is what we're trying to do is how do these technologies,
how do you use them in the store,
how do you use them in the warehouse,
so that dynamically you can use the smarts
for better efficiency.
So that's where the machine learning as well
as the VR technology comes together.
>> So Suresh talk about the dynamics
between data science and math and software,
because what's happening is it's a real intersection now
of confluence of maths, math and science, data,
that's really available, and software.
>> Suresh: Yeah.
>> This is the power trend.
This is the big tailwinds to the marketplace.
>> Sure, so I'm a data scientist by training, you know
I've always done algorithmic work and I've always worked
in an industry where my mathematical models make
it into the software.
It's just music to my ears that a lot of this
is now really, really becoming very, very important.
Data science is just a word,
there's two pieces.
There's a data piece. There's a science piece.
We all get trained in school on the science,
and what we're finding early on was
that data sometimes simply wasn't there.
>> John: Yeah.
>> But now, there's a lot more data,
there's a lot more clean data
and you can do a lot more with it.
So it's a great time to be in AI, machine learning,
and just the broader space of the data side.
>> Well databases are changing,
you're making more unstructured data available--
>> Suresh: Yes.
>> Addressable, okay let's get back to your example
of manufacturing in supply chain
because I was going to say, boring, but it's never boring,
it's business. >> Suresh: Yeah.
>> We have a world we live in, an analog world,
but you mentioned digitizing.
This is not trivial. So I want you to take me through
in your opinion and working in the labs of JDA Software,
what are the key things for digitizing businesses,
because you've got to bolt on senors,
you got to have actuators,
you got to have all kinds of new potentially hardware--
>> Suresh: Yeah.
>> You need more processors.
But now you got to connect it to the network,
that's the Internet of Things.
How hard is it to digitize a business?
>> Sure, so it is hard and so this is more of a journey
than something that's going to happen over night.
Let me walk you through a couple of use cases
both upstream to the end, and then the other way around,
just so that you see the value
and how complex, but yet how much value one can add.
As you know, there are production plants all over the world,
so it's quite possible then that there's a vessel
that's carrying your product
from China to Long Beach, California.
A lot of times currently there's no visibility
around when that ship will ever make it to Long Beach.
But with sensors, with real-time tracking
of all these vessels, we're now able to say
that rather than it arriving in Long Beach on the 22nd
because of weather reasons,
it's now going to arrive on the 25th instead.
And how that then drives the downstream supply chain
around when should the product make it
to the distribution center,
when will it make it to the store,
and oh, by the way, I might need to make alternate plans now
because I don't have the luxury to wait
for the three day delay that I am incurring,
what are my alternate sources.
So that's upstream down to the store.
We don't really see it
when we go buy something at the store,
the fact that this has had such a long journey upstream,
is typically shielded from us.
>> So it's a ripple effect. >> Ripple effect.
>> So the old days was, hey where's my product?
Oh, it's on a boat from China,
so you didn't know where it's coming from
and the guild expression-- >> Suresh: Exactly.
>> Maybe it was China or not. >> Suresh: Right.
>> But the point was that you had a delay in impact,
a disruption-- >> That's right.
>> Here you can say, okay contingency policy, software,
trigger, hey it's here, get some supply from somewhere else,
it could be produce or other goods.
>> Suresh: Exactly. >> Am I getting it right?
>> You're absolutely right.
So that's the kind of upstream down to the consumer,
but how about the consumer or the store upstream, right,
so sometimes what happens is folks go to the store
and then they start to get on social media
to say these are awesome products,
everyone's got to buy em,
these things start to sell off the shelf,
if you will, very, very rapidly.
And now can you start to detect that social sentiment trend
to start to realign your supply chain so
that you avoid out of stock.
Alternatively, you could have the rewards--
>> Or you could game it like they're doing now.
Create scarcity, then make the retail market move.
>> There's that as well.
>> Supreme is doing it.
My kids are buying these things, Supreme,
these jackets and backpacks.
>> Correct. You can gamify as well.
On the other hand, what you can also do is
what if you introduce a new product,
which you're now finding out is not selling
as well as you thought it would.
You're not going to continue to push inventory there,
you're going to be smart about where you now send those
and potentially also manage the manufacturing upstream.
>> So it's the classic effect of efficiency
opportunities are every. >> Suresh: Exactly.
>> Talk how about Intel,
what do you think Intel's doing right?
Because if you think about about what's powering all this,
it's the chips. >> Suresh: Yep.
>> It's not just the processor and the PC,
it's software end-to-end solutions.
>> Suresh: Yeah.
>> I was just covering Mobile World Congress two weeks ago,
and 5G is bringing potentially a gigabit,
I mean not that you need a sensor on a boat or a machine
to use a gigabit-- >> Suresh: Sure.
>> But still it does create more bandwidth--
>> Suresh: Yeah.
>> Cuz you got to connect to the network. (laughs)
>> Suresh: Sure. Exactly. (laughs)
>> Your data's got to go somewhere.
>> So one of the pieces of work that we're doing with Intel
is really at the store level
to have sensors detect where an object is.
You'd be surprised. People sometimes, not sometimes
a lot of times what happens is retailers will
say that they're out of stock,
when it's still in the store,
it's just that they don't know where it is.
>> John: Yeah.
>> To now have sensors to precisely detect
whether it's in the back office,
whether it's in a fitting room,
whether it's somewhere else and really track
that inventory real-time to then provide the visibility
around inventory is huge.
This is the holy grail. You and I may not realize it,
but this is the holy grail for a lot of retailers.
Because they simply do not know where their inventory is
and the work that we're doing around sensors,
you know connecting the devices and
of course adding the smarts with AI, that's the value.
>> I love to hear the word holy grail, great stuff.
I want to ask you a question on a personal note.
>> Suresh: Yeah.
>> Someone who's in labs and you've been in the industry
of data science with a math background in retail,
in supply chain, you kind of see the big picture.
What are the coolest things out there right now,
for the folks watching, whether it's a young kid
or someone in college or an executive or a developer.
Can you highlight some things of the coolest things
that people should pay attention to,
and what is cool that people aren't paying attention to.
>> Yeah, well I think I'm going to be biased when I say
just the space of machine learning is actually exploding,
but it is. So that's my own heritage as well.
To me it's just fascinating to see how things
that were very rudimentary have now really caught on.
So the area of AI and machine learning
has endless potential in my mind.
Around a lot of the devices then
that actually generate the data
that then feeds into it, that space is exploding as well.
One of the pieces of work-- >> John: You mean IoT data?
>> IoT data. I'd like to give you a specific example
of things that are now possible.
We are doing research in the space of cognitive robotics.
These are not robots that will help automate things
or make things faster,
these are robots in the stores that will actually
interact with you, so they will actually talk to you.
You can go up it and say, "Hey, I'm trying to find
"these shoes and I can't find them."
What it's going to tell you is it's going to bring
that immense power of AI to tell you where the products are,
it could be in that store and it's going
to have someone go fetch it for you,
or it's going to tell you, oh it's in another store
five miles down the road,
would you rather go there to pick it up
or it can say I can have it be mailed to your house.
So that's in terms of the cognitive robot
understanding your emotions that you're angry trying
to find something or you're a happy customer
and being able to respond that way,
but it's also continuously collecting data about you.
That it's a male of a certain age group coming
into the store at this time, coming out of aisle number 19
looking for this kind of product.
This is all pieces of info ...
So our goal is even when you're 10 feet away from the robot,
it's going to know what questions you're going to ask.
>> So robotics is really hot right now,
>> Suresh: Right.
>> Because this is the interactivity potential,
not just a static machine. >> Suresh: Correct.
This is more ...
>> It's the whole experience.
>> We had Dr. Naveen, on earlier, Rao,
he said it's like the Jetsons, go clean my room,
I mean we're getting there.
>> Suresh: We are getting there.
>> Almost there.
>> We're almost getting there and so ...
So the notion that users will use software
in a two-dimensional screen manner that we're doing now,
that's already changing.
So to your point earlier on VR being submersing yourself
into your supply chain,
which we never have done-- >> John: Yeah.
>> Is really where this is going.
>> John: Got it.
>> So--
>> Suresh, so final question,
shoot the arrow forward five years,
what does our future look like,
what's going to change, what's it going to look like?
>> Well, there's a lot of buzz
around the autonomous self driving car.
In my world it's really the autonomous
self-learning supply chain.
Think about it, it's going to detect things,
it's going to know things,
it's going to predict things so much better
and also be able to prescribe things dynamically.
There's a lot of inefficiencies built into the supply chain
that will gradually over time get better and better.
So a lot of folks that could be scary,
just like driverless car to a lot of folks is scary,
but if you really grasp the value of it,
where we're going is tremendous
in terms of operational efficiencies,
in terms of smart,
just making our everyday lives so much better.
>> Alright Suresh Acharya inside theCUBE,
we're here in the Intel AI Lounge,
I'm John Furrier with SiliconANGLE Media.
We're breaking it down here at South by Southwest
where all the buzz is happening
virtual reality, artificial intelligence,
machine learning is the hottest reality trend right now.
Software developers are booming,
it's Suresh great, it's the holy grail!
This is theCUBE here at the Intel AI Lounge.
Back with more coverage after this short break.
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