>> Narrator: From theCUBE studios in Palo Alto and Boston,
it's theCUBE, covering IBM Think,
brought to you by IBM.
>> We're back.
You're watching theCUBE and our coverage of IBM Think 2020,
the digital IBM thinking.
We're here with Jamie Thomas, who's the general manager
of strategy and development for IBM Systems.
Jamie, great to see you.
>> It's great to see you as always.
>> You have been knee deep in qubits, the last couple years.
And we're going to talk quantum.
We've talked quantum a lot in the past,
but it's a really interesting field.
We spoke to you last year at IBM Think about this topic.
And a year in this industry is a long time,
but so give us the update what's new in quantum land?
>> Well, Dave first of all,
I'd like to say that in this environment
we find ourselves in,
I think we can all appreciate why innovation of this nature
is perhaps more important going forward, right?
If we look at some of the opportunities
to solve some of the unsolvable problems,
or solve problems much more quickly,
in the case of pharmaceutical research.
But for us in IBM, it's been a really busy year.
First of all, we worked to advance the technology,
which is first and foremost in terms
of this journey to quantum.
We just brought online our 53 qubit computer,
which also has a quantum volume of 32,
which we can talk about.
And we've continued to advance the software stack
that's attached to the technology
because you have to have both the software
and the hardware thing, right rate and pace.
We've advanced our new network,
which you and I have spoken about,
which are those individuals
across the commercial enterprises,
academic and startups, who are working with us
to co-create around quantum to help us understand
the use cases that really can be solved
in the future with quantum.
And we've also continued to advance our community,
which is serving as well in this new digital world
that we're finding ourselves in,
in terms of reaching out to developers.
Now, we have over 300,000 unique downloads
of the programming model that represents the developers
that we're touching out there every day with quantum.
These developers have, in the last year,
have run over 140 billion quantum circuits.
So, our machines in the cloud are quite active,
and the cloud model, of course, is serving us well.
The data's, in addition,
to all the other things that I mentioned.
>> So Jamie, what metrics are you trying to optimize on?
You mentioned 53 qubits I saw that actually came online,
I think, last fall.
So you're nearly six months in now, which is awesome.
But what are you measuring?
Are you measuring stability or coherence or error rates?
Number of qubits?
What are the things that you're trying
to optimize on to measure progress?
>> Well, that's a good question.
So we have this metric that we've defined
over the last year or two called quantum volume.
And quantum volume 32, which is the capacity
of our current machine really is a representation
of many of the things that you mentioned.
It represents the power of the quantum machine, if you will.
It includes a definition of our ability
to provide error correction, to maintain states,
to really accomplish workloads with the computer.
So there's a number of factors that go
into quantum volume, which we think are important.
Now, qubits and the number of qubits
is just one such metric.
It really depends on the coherence
and the effect of error correction,
to really get the value out of the machine,
and that's a very important metric.
>> Yeah, we love to boil things down to a single metric.
It's more complicated than that
>> Yeah, yeah. >> specifically with quantum.
So, talk a little bit more about what clients are doing
and I'm particularly interested in the ecosystem
that you're forming around quantum.
>> Well, as I said, the ecosystem is both
the network, which are those
that are really intently working with us to co-create
because we found, through our long history in IBM,
that co-creation is really important.
And also these researchers and developers
realize that some of our developers today
are really researchers, but as you as you go forward
you get many different types of developers
that are part of this mix.
But in terms of our ecosystem,
we're really fundamentally focused on key problems
around chemistry, material science, financial services.
And over the last year, there's over 200 papers
that have been written out there from our network
that really embody their work with us on this journey.
So we're looking at things like quadratic speed up
of things like Monte Carlo simulation,
which is used in the financial services arena today
to quantify risk.
There's papers out there around topics
like trade settlements, which in the world today
trade settlements is a very complex domain
with very interconnected complex rules
and trillions of dollars in the purview of trade settlement.
So, it's just an example.
Options pricing, so you see examples around options pricing
from corporations like JPMC
in the area of financial services.
And likewise in chemistry, there's a lot of research
out there focused on batteries.
As you can imagine, getting everything
to electric powered batteries is an important topic.
But today, the way we manufacture batteries
can in fact create air pollution, in terms of the process,
as well as we want batteries to have more retention in life
to be more effective in energy conservation.
So, how do we create batteries
and still protect our environment,
as we all would like to do?
And so we've had a lot of research around things
like the next generation of electric batteries,
which is a key topic.
But if you can think, you know Dave,
there's so many topics here around chemistry,
also pharmaceuticals that could be advanced
with a quantum computer.
Obviously, if you look at the COVID-19 news,
our supercomputer that we installed
at Oak Ridge National Laboratory for instance,
is being used to analyze 8000 different compounds
for specifically around COVID-19
and the possibilities of using those compounds
to solve COVID-19, or influence it in a positive manner.
You can think of the quantum computer when it comes online
as an accelerator to a supercomputer like that,
helping speed up this kind of research even faster
than what we're able to do with something
like the Summit supercomputer.
Oak Ridge is one of our prominent clients
with the quantum technology,
and they certainly see it that way, right,
as an accelerator to the capacity they already have.
So a great example that I think is very germane
in the time that we find ourselves in.
>> How 'about startups in this ecosystem?
Are you able to--
I mean there must be startups popping up
all over the place for this opportunity.
Are you working with any startups
or incubating any startups?
Can you talk about that? >> Oh yep.
Absolutely.
There's about a third of our network are in VC startups
and there's a long list of them out there.
They're focused on many different aspects
of quantum computing.
Many of 'em are focused on what I would call loosely,
the programming model, looking at improving algorithms
across different industries,
making it easier for those that are,
perhaps more skilled in domains,
whether that is chemistry or financial services
or mathematics, to use the power of the quantum computer.
Many of those startups are leveraging our Qiskit,
our quantum information science open programming model
that we put out there so it's open.
Many of the startups are using that programming model
and then adding their own secret sauce, if you will,
to understand how they can help bring on users
in different ways.
So it depends on their domain.
You see some startups that are focused
on the hardware as well, of course,
looking at different hardware technologies
that can be used to solve quantum.
I would say I feel like more of them are focused
on the software programming model.
>> Well Jamie, it was interesting hear you talk
about what some of the clients are doing.
I mean obviously in pharmaceuticals,
and battery manufacturers do a lot of advanced R and D,
but you mentioned financial services, you know JPMC.
It's almost like they're now doing advanced R and D
trying to figure out how they can apply quantum
to their business down the road.
>> Absolutely, and we have a number of financial institutions
that we've announced as part of the network.
JPMC is just one of our premiere references
who have written papers about it.
But I would tell you that in the world
of Monte Carlo simulation, options pricing, risk management,
a small change can make a big difference in dollars.
So we're talking about operations that in many cases
they could achieve, but not achieve
in the right amount of time.
The ability to use quantum as an accelerator
for these kind of operations is very important.
And I can tell you, even in the last few weeks,
we've had a number of briefings with financial companies
for five hours on this topic.
Looking at what could they do and learning from the work
that's already done out there.
I think this kind of advanced research
is going to be very important.
We also had new members that we announced
at the beginning of the year at the CES show.
Delta Airlines joined.
First Transportation Company, Amgen joined,
a pharmaceutical, an example of pharmaceuticals,
as well as a number of other research organizations.
Georgia Tech, University of New Mexico, Anthem Insurance,
just an example of the industries that are looking
to take advantage of this kind of technology as it matures.
>> Well, and it strikes me too, that as you start to bring
machine intelligence into the equation,
it's a game changer.
I mean, I've been saying that it's not Moore's Law
driving the industry anymore,
it's this combination of data, AI,
and cloud for scale, but now--
Of course there are alternative processors going on,
we're seeing that, but now as you bring in quantum
that actually adds to that innovation cocktail, doesn't it?
>> Yes, and as you recall when you and I spoke last year
about this, there are certain domains today
where you really cannot get as much effective gain
out of classical computing.
And clearly, chemistry is one of those domains
because today, with classical computers,
we're really unable to model even something
as simple as a caffeine molecule,
which we're all so very familiar with.
I have my caffeine here with me today. (laughs)
But you know, clearly, to the degree we can actually apply
molecular modeling and the advantages
that quantum brings to those fields,
we'll be able to understand so much more about materials
that affect all of us around the world,
about energy, how to explore energy,
and create energy without creating the carbon footprint
and the bad outcomes associated with energy creation,
and how to obviously deal with pharmaceutical creation
much more effectively.
There's a real promise in a lot of these different areas.
>> I wonder if you could talk a little bit about
some of the landscape
and I'm really interested in what IBM brings to the table
that's sort of different.
You're seeing a lot of companies enter this space,
some big and many small, what's the unique aspect
that IBM brings to the table?
You've mentioned co-creating before.
Are you co-creating, coopertating with some
of the other big guys?
Maybe you could address that.
>> Well, obviously this is a very hot topic,
both within the technology industry
and across government entities.
I think that some of the key values we bring to the table
is we are the only vendor right now
that has a fleet of systems available in the cloud,
and we've been out there for several years,
enabling clients to take advantage of our capacity.
We have both free access and premium access,
which is what the network is paying for
because they get access to the highest fidelity machines.
Clearly, we understand intently, classical computing
and the ability to leverage classical with quantum
for advantage across many of these different industries,
which I think is unique.
We understand the cloud experience
that we're bringing to play here with quantum since day one,
and most importantly, I think we have strong relationships.
We have, in many cases, we're still running the world.
I see it every day coming
through my clients' port vantage point.
We understand financial services.
We understand healthcare.
We understand many of these important domains,
and we're used to solving tough problems.
So, we'll bring that experience with our clients
and those industries to the table here
and help them on this journey.
>> You mentioned your experience in sort
of traditional computing,
basically if I understand it correctly,
you're still using traditional silicon microprocessors
to read and write the data that's coming out of quantum.
I don't know if they're sitting physically side by side,
but you've got this big cryogenic unit, cables coming in.
That's the sort of standard for some time.
It reminds me, can it go back to ENIAC?
And now, which is really excites me
because you look at the potential to miniaturize
this over the next several decades,
but is that right, you're sort of side by side
with traditional computing approaches?
>> Right, effectively what we do with quantum today
does not happen without classical computers.
The front end, you're coming in on classical computers.
You're storing your data on classical computers,
so that is the model that we're in today,
and that will continue to happen.
In terms of the quantum processor itself,
it is a silicon based processor,
but it's a superconducting technology, in our case,
that runs inside that cryogenics unit
at a very cold temperature.
It is powered by next-generation electronics
that we in IBM have innovated around
and created our own electronic stack
that actually sends microwave pulses into the processor
that resides in the cryogenics unit.
So when you think about the components of the system,
you have to be innovating around the processor,
the cryogenics unit, the custom electronic stack,
and the software all at the same time.
And yes, we're doing that in terms
of being surrounded by this classical backplane
that allows our Q network, as well as the developers
around the world to actually communicate with these systems.
>> The other thing that I really like about this conversation
is it's not just R and D for the sake of R and D,
you've actually, you're working with partners to,
like you said, co-create, customers, financial services,
airlines, manufacturing, et cetera.
I wonder if you could maybe kind of address
some of the things that you see happening
in the sort of near to midterm, specifically as it relates
to where people start.
If I'm interested in this, what do I do?
Do I need new skills?
Do I need--
It's in the cloud, right?
>> Yeah. >> So I can spit it up there,
but where do people get started?
>> Well they can certainly come to the Quantum Experience,
which is our cloud experience
and start to try out the system.
So, we have both easy ways to get started
with visual composition of circuits,
as well as using the programming model that I mentioned,
the Qiskit programming model.
We've provided extensive YouTube videos out there already.
So, developers who are interested in starting
to learn about quantum can go out there
and subscribe to our YouTube channel.
We've got over 40 assets already recorded out there,
and we continue to do those.
We did one last week on quantum circuits
for those that are more interested
in that particular domain,
but I think that's a part of this journey
is making sure that we have all the assets out there
digitally available for those around the world
that want to interact with us.
We have tremendous amount of education.
We're also providing education to our business partners.
One of our key network members,
who I'll be speaking with later, I think today,
is from Accenture.
Accenture's an example of an organization
that's helping their clients understand
this quantum journey, and of course they're providing
their own assets, if you will, but once again,
taking advantage of the education
that we're providing to them as a business partner.
>> People talk about quantum being a decade away,
but I think that's the wrong way to think about it,
and I'd love your thoughts on this.
It feels like,
almost like the return coming out of COVID-19,
it's going to come in waves, and there's parts
that are going to be commercialized thoroughly
and it's not binary.
It's not like all of a sudden one day we're going to wake,
"Hey, quantum is here!"
It's really going to come in layers.
Your thoughts?
>> Yeah, I definitely agree with that.
It's very important, that thought process
because if you want to be competitive in your industry,
you should think about getting started now.
And that's why you see so many financial services,
industrial firms, and others joining
to really start experimentation around some
of these domain areas to understand jointly
how we evolve these algorithms to solve these problems.
I think that the production level characteristics
will curate the rate and pace of the industry.
The industry, as we know, can drive things together faster.
So together, we can make this a reality faster,
and certainly none of us want to say
it's going to be a decade, right.
I mean, we're getting advantage today,
in terms of the experimentation
and the understanding of these problems,
and we have to expedite that, I think,
in the next few years.
And certainly, with this arms race that we see,
that's going to continue.
One of the things I didn't mention is that IBM is also
working with certain countries
and we have significant agreements now
with the countries of Germany and Japan
to put quantum computers in an IBM facility
in those countries.
It's in collaboration with Fraunhofer Institute
or miR Scientific Organization in Germany
and with the University of Tokyo in Japan.
So you can see that it's not only being pushed by industry,
but it's also being pushed from the vantage of countries
and bringing this research and technology
to their countries.
>> All right, Jamie, we're going to have to leave it there.
Thanks so much for coming on theCUBE and give us the update.
It's always great to see you.
Hopefully, next time I see you, it'll be face to face.
>> That's right, I hope so too.
It's great to see you guys, thank you.
Bye.
>> All right, you're welcome.
Keep it right there everybody.
This is Dave Vellante for theCUBE.
Be back right after this short break.
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