>> Live from San Francisco.
It's theCube covering IBM Think 2019.
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>> Welcome back to Moscone Center everybody.
The new, improved Moscone Center.
We're at Moscone North, stop by and see us.
I'm Dave Vellante, he's Stu Miniman
and Lisa Martin is here as well,
John Furrier will be up tomorrow.
You're watching theCube, the leader in live tech coverage.
This is day zero essentially, Stu, of IBM Think.
Day one, the big keynotes, start tomorrow.
Chairman's keynote in the afternoon.
Jamie Thomas is here.
She's the general manager of IBM's Systems
Strategy and Development at IBM.
Great to see you again Jamie, thanks for coming on.
>> Great to see you guys as usual and thanks
for coming back to Think this year.
>> You're very welcome.
So, I love your new role.
You get to put on the binoculars sometimes the telescope.
Look at the road map.
You have your fingers in a lot of different areas
and you get some advanced visibility
on some of the things that are coming down the road.
So we're really excited about that.
But give us the update from a year ago.
You guys have been busy.
>> We have been busy,
and it was a phenomenal year, Dave and Stu.
Last year, I guess one of the pinnacles we reached
is that we were named with our technology,
our technology received the number one and two
supercomputer ratings in the world
and this was a significant accomplishment.
Rolling out the number one supercomputer
in Oakridge National Laboratory and the number two
supercomputer in Lawrence Livermore Laboratory.
And Summit as it's called in Oakridge
is really a cool system.
Over 9000 CPUs about 27,000 GPUs.
It does 200 petaflops at peak capacity.
It has about 250 petabytes of storage attached to it
at scale and to cool this guy, Summit, I guess it's a guy.
I'm not sure of the denomination actually
it takes about 4,000 gallons of water per minute
to cool the supercomputer.
So we're really pleased with the engineering
that we worked on for so many years
and achieving these World records, if you will,
for both Summit and Sierra.
>> Well it's not just bragging rights either, right, Jamie?
I mean, it underscores the technical competency
and the challenge that you guys face
I mean, you're number one and number two, that's not easy.
Not easy to sustain of course, you got to do it again.
>> Right, right, it's not easy.
But the good thing is the design point of these systems
is that we're able to take what we created here
from a technology perspective around POWER9
and of course the patnership we did
with Invidia in this case and the software storage.
And we're able to downsize that significantly
for commercial clients.
So this is the world's largest
artificial intlligence supercomputer
and basically we are able to take that technology
that we invented in this case
'cause they ended up being one of our first clients
albeit a very large client, and use that
across industries to serve the needs
of artificial intelligence work loads.
So I think that was one of the most significant elements
of what we actually did here.
>> And IBM has maintained, despite you guys
selling off your microelectronics division years ago,
you've maintained a lot of IP
in the core processing and the design.
You've also reached out certainly with open power,
for example, to folks.
You mentioned Invidia.
But having that, sort of embracing
that alternative processor mode as opposed
to trying to jam everything in the die.
Different philosophy that IBM is taking.
>> Yeah we think that the workload specific processing
is still very much in demand.
Workloads are going to have different dimensions
and that's what we really have focused on here.
I don't think that this has really changed
over the last decades of computing
and so we're really focused on specialized computing
purpose-built computing, if you will.
Obviously using that on premise and also using that
in our hybrid cloud strategies for clients
that want to do that as well.
>> What are some of the other cool things
that you guys are working on that you can talk about.
>> Well I would say last year was quite an interesting year
in that from a mainframe perspective
we delivered our first 19 inch form factor
which allows us to fit nicely on a floor tile.
Obviously allows clients to scale more effectively
from a data center planning perspective.
Allows us to have a cloud footprint,
but with all the characteristics of security
that you would normally expect in a mainframe system.
But really tailored toward new workloads once again.
So Linux form factor and going after the new workloads
that a lot of these cloud data centers really need.
One of our first and foremost focus areas
continues to be security around that system
and tomorrow there will be some announcements
that will happen around Z security.
I can't say what they are right now
but you'll see that we are extending security
in new ways to support more of these hybrid cloud scenarios.
>> It's so funny.
We were talking in one of our earlier segments
talking about how the path of virtualization
and trying to get lots of workloads
into something and goes back to the device
that could manage all workloads which was the Mainframe.
So we've watched for many years system Z
lots of Linux on there if you want to do some cool container,
you know global Z that's an option, so it's interesting
to watch while the pendulum swings in IT have happened
the Z system has kept up with a lot of these innovations
that have been going on in the industry.
>> And you're right, one of our big focuses for the platform
for Z and power of course is a container-based strategy.
So we've created, you know last year we talked about
secure container technology and we continue to evolve
secure container technology but the idea is
we want to eliminate any kind of friction
from a developer's perspective.
So if you want to design in a container-based environment
then you're more easily able to port that technology
or your applications, if you will
to a Z mainframe environment
if that's really what your target environment is.
So that's been a huge focus.
The other of course major invention that we announced
at the Consumer Electronics show is our Quantum System One.
And this represented an evolution of our Quantum system
over the last year where we now have the world's
really first self-contained universal quantum computer
in a single form factor where we were able to combine
the Quantum processor which is living in
the dilution refrigerator.
You guys remember the beautiful chandelier from last year.
I think it's back this year.
But this is all self-contained with it's electronics
in a single form factor.
And that really represents the evolution of the electronics
in particular over the last year where we were able
to miniaturize those electronics and get them
into this differentiated form factor.
>> What should people know about Quantum?
When you see the demos, they explain
it's not a binary one or zero, it could be either,
a virtually infinite set of possibilities,
but what should the lay person know about Quantum
and try to understand?
>> Well I think really the fundamental aspect of it
is in today's world with traditional computers
they're very powerful
but they cannot solve certain problems.
So when you look at areas like material science,
areas like chemistry even some financial trading scenarios,
the problems can either not be solved at all
or they cannot be completed in the right amount of time.
Particularly in the world of financial services.
But in the area of chemistry
for instance molecular modeling.
Today we can model simple molecules
but we cannot model something even as complex as caffeine.
We simply don't have the traditional
compute capacity to do that.
A quantum computer will allow us once it comes to maturity
allow us to solve these problems that are not solvable today
and you can think about all the things that we could do
if were able to have more sophisticated molecular modeling.
All the kinds of problems we could solve probably
in the world of pharmacology, material science
which affects many, many industries right?
People that are developing automobiles,
people that are exploring for oil.
All kinds of opportunities here in this space.
The technology is a little bit spooky, I guess,
that's what Einstein said when he first solved
some of this, right?
But it really represents the state of the universe, right?
How the universe behaves today.
It really is happening around us
but that's what quantum mechanics helps us capture
and when combined with IT technology
the quantum computer can bring this to life over time.
>> So one of the things that people point to is potentially
a new security paradigm because Quantum can flip
the way in which we do security on it's head
so you got to be thinking around that as well.
I know security is something that is very important
to IBM's Systems division.
>> Right, absolutely.
So the first thing that happens when someone hears
about quantum computing is they ask about quantum security.
And as you can imagine there's a lot of clients here
that are concerned about security.
So in IBM research we're also working
on quantum-safe encryption.
So you got one team working on a quantum computer,
you got another team ensuring that the data
will be protected from the quantum computer.
So we do believe we can construct quantum-safe encryption
algorithms based on lattice-based technology
that will allow us to encrypt data today
and in the future when the quantum computer does reach
that kind of capacity the data will be protected.
So the idea is that we would start using
these new algorithms far earlier than the computer
could actually achieve this result but it would mean
that data created today would be quantum safe in the future.
>> You're kind of in your own arm's race internally.
>> But it's very important.
Both aspects are very important.
To be able to solve these problems
that we can't solve today, which is really amazing, right?
And to also be able to protect our data
should it be used in inappropriate ways, right?
>> Now we had Ed Bausch on earlier today.
Used to run the storage division.
What's going on in that world?
I know you've got your hands in that pie as well.
What can you tell us about what's going on there?
>> Well I believe that Ed and the team have made
some phenomenal innovations in the past year
around flash MVME technology and fusing that
across product lines state-of-the-art.
The other area that I think is particularly interesting
of course is their data management strategy
around things like Spectrum Discover.
So, today we all know that many of our clients
have just huge amounts of data.
I visited a client last year that interesting enough
had 1 million tapes, and of course we sell tapes
so that's a good thing but then how do you deal
and manage all the data that is on 1 million tapes.
So one of the inventions that the team has worked on
is a metadata tagging capability that they've now shipped
in a product called spectrum discover.
And that allows a client to have a better way
to have a profile of their data, data governance
and understand for different use cases like data governance
or compliance how do they pull back the right data
and what does this data really mean to them.
So have a better lexicon of their data, if you will
than what they can do in today's world.
So I think that's very important technology.
>> That's interesting.
I would imagine that metadata could sit in Flash somewhere
and then inform the serial technology
to maybe find stuff faster.
I mean, everybody thinks tape is slow
because it's sequential.
But actually if you do some interesting things
with metadata you can--
>> There's all kinds of things you can do I mean
it's one thing to have a data ocean if you will,
but then how do you really get value
out of that data over a long period of time
and I think we're just the tip of the spear in understanding
the use cases that we can use this technology for.
>> Jamie, how does IBM manage that pipeline of innovation.
I think we heard very specific examples of how
the super computers drive HPC architectures
which everybody is going to use for their AI infrastructure.
Something like quantum computing
is a little bit more out there.
So how do you balance kind of the research
through the product and what's going to be more useful
to users today.
>> Yeah, well, that's an interesting question.
So IBM is one of the few organizations in the world really
that have an applied research organization still.
And Dario Gil is here this week he manages
our research organization now under Arvind Krishna.
An organization like IBM Systems
has a great relationship with research.
Research are the folks that had people working
on Quantum for decades, right?
And they're the reason that we are in a position now
to be able to apply this in the way that we are.
The great news is that along the way we're always working
on a pipeline of this next generation set
of technologies and innovations.
Some of them succeed and some of them don't.
But without doing that we would not have things
like Quantum.
We would not have advanced encryption capability
that we pushed all the way down into our chips.
We would not have quantum-safe encryption.
Things like the metadata tagging
that I talked about came out of IBM research.
So it's working with them on problems that we see
coming down the pipe, if you will
that will affect our clients and then working with them
to make sure we get those into the product lines
at the right amount of time.
I would say that Quantum is the ultimate partnership
between IBM Systems and IBM research.
We have one team in this case
that are working jointly on this product.
Bringing the skills to bear that each of us have
on this case with them having the quantum physics experts
and us having the electronics experts and of course
the software stacks spanning both organizations
is really a great partnership.
>> Is there anything you could tell us
about what's going on at the edge.
The edge computing you hear a lot about that today.
IBM's got some activities going on there?
You haven't made huge splashes there
but anything going on in research that you can share
with us, or any directions.
>> Well I believe the edge is going to be
a practical endeavor for us and what I mean by that
is there are certain use cases that I think
we can serve very well.
So if we look at the edge as perhaps a factory environment,
we are seeing opportunities
for our storaging compute solutions
around the data management out in some of these areas.
If you look at the self-driving automobile for instance,
just design something like that can easily take
over a hundred petabytes of data.
So being able to manage the data at the edge,
being able to then to provide insight appropriately
using AI technologies is something we think
we can do and we see that.
I own factories based on what I do
and I'm starting to use AI technology.
I use Power AI technology in my factories
for visual inspection.
Think about a lot of the challenges around provenance
of parts as well as making sure that
they're finally put together in the right way.
Using these kind of technologies in factories is just
really an easy use case that we can see.
And so what we anticipate is we will work
with the other parts of IBM that are focused on edge as well
and understand which areas we think
our technology can best serve.
>> That's interesting you mention visual inspection.
That's an analog use case which now
you're transforming into digital.
>> Yeah well Power AI vision
has been very successful in the last year .
So we had this power AI package of open source software
that we pulled together but we drastically simplified
the use of this software, if you will
the ability to use it deploy it
and we've added vision capability to it in the last year.
And there's many use cases for this vision capability.
If you think about even the case where
you have a patient that is in an MRI.
If you're able to decrease the amount of time
they stay in the MRI in some cases
by less fidelity of the picture
but then you've got to be able to interpret it.
So this kind of AI and then extensions of AI
to vision is really important.
Another example for Power AI vision
is we're actually seeing use cases in advertising
so the use case of maybe you're at a sporting event
or even a busy place like this
where you're able to use visual inspection techniques
to understand the use of certain products.
In the case of a sporting event it's how many times
did my logo show up in this sporting event, right?
Particularly our favorite one is Formula One
which we usually feature the Formula One folks
here a little bit at the events.
So you can see how that kind of technology can be used
to help advertisers understand the benefits in these cases.
>> Got it.
Well Jamie we always love having you on
because you have visibility into so many different areas.
Really thank you for coming and sharing
a little taste of what's to come.
Appreciate it.
>> Well thank you.
It's always good to see you
and I know it will be an exciting week here.
>> Yeah, we're very excited.
Day zero here, day one
and we're kicking off four days of coverage with theCube.
Jamie Thomas of IBM.
I'm Dave Vellante, he's Stu Miniman.
We'll be right back right after this short break
from IBM Think in Moscone.
(upbeat music)