This is a story about God playing dice with the
universe, something Albert Einstein told us he didn't do
back in 1926. Einstein was criticizing physicists' theory of
quantum mechanics. Yet a century after Einstein's denial,
billions of dollars are being invested today in taking that
theory and turning it into reality, with the prospect
of a revolution in computing potentially larger even than generative
AI. Quantum computing is very high potential. Investors
are increasingly asking us about the implications of quantum computing
. Quantum computing, quantum computing, political and state
level economic support to develop quantum, and we want
to be part of that. IBM is one of
the companies leading the charge in quantum computing. At
IBM we developed some of the very foundations of quantum
information science starting as early as 1970. Jamie Garcia
is the director of quantum partnerships at IBM, a
PhD chemist. She's working on quantum computers transforming healthcare
at places like the Cleveland Clinic. Quantum computers are
just a totally different paradigm to calculate. Regulate solutions
to problems and so what most, you know,
experts have done today that are studying quantum computing for
different application spaces is to really sit down with the
math and figure out like are the algorithms here that
I can use and that I can exploit using a
quantum computer going to bring me any sort of advantage
over what can be done today in classical sort of
state of the art techniques. At the core of
classical computing are bits, single pieces of information that
can have the value of 0 or 1, but
quantum technology relies on cubits, a unit that can
have multiple values simultaneously. It's like holding a coin
in your hand that is heads, tails, and
everything in between until you open your hand to check
. Physicist Jerry Chow is IBM's director of quantum hardware
system development. Really fundamentally, there's a different math
, right? It's the mathematics of quantum mechanics that
is governing how you actually manipulate these quantum bits,
which then gives rise to a whole host of different
. Um, opportunities for algorithms and types of problems
that you can actually solve using quantum computers as we're
studying things today, we're using a lot of something
called error mitigation as our approach to deal with dealing
with errors and noise in the system and in the
quantum computer. Itself. This is going to continue
to evolve. In fact, we think that next
year we're going to see examples of what we call
quantum advantage, which is where you're able to come
up with a solution to a problem that is cheaper
, faster, or more accurate than with classical alone
. A turning point in IBM's efforts to make quantum
computing a reality came when it made it available to
the world on the cloud. 2016, the IBM
Quantum Experience was really a pivotal moment for us in
terms of getting quantum computers for the first time out
onto the cloud and into the hands of. Anybody
, really, people, right? What's interesting is
that before that period, I'd say it was really
much. More in the realm of physics, right
, that we were doing experiments on small devices,
qubit devices that we were looking at understanding how they
worked, trying to make them better, um,
but we didn't have any kind of real thought about
how is this gonna be used for computation. In
the 9 years since you put quantum experience out there
, what is, what have you learned at IBM
? I think what I learned from that experience really
was that there was. A whole lot of people
out there who wanted to touch and learn about Quantum
. I think we were sitting there that first night
after we launched it watching, uh, these circuits
coming in and people were actually running things and we're
like, oh wow, this is picking up some
steam here, um, you know, and then
, you know, to this point we've had tremendous
uptake in terms of using the platform to actually generate
. New papers and research, thousands of papers have
been generated, which have been, would have been
impossible for us to do just as individual scientists or
researchers studying these devices in our own lab and working
with other scientists in collaborations. And in success,
that community could go places that classical computing, even
using the large language models of AI, could never
take us. So it's not just speed, it's
actual accuracy. When we're using classical, no matter
how infinite. We get, it's an approximation,
right? Absolutely. It's absolutely not just not,
not a, not a question about speed. The
whole point of the quantum computer and what it can
do is that it can give us the ability to
actually get potentially more accurate results, also get results
that otherwise are unattainable using a classical computer alone.
Companies like Google, Microsoft, and Intel are all
exploring the potential of quantum computing, but there's also
a new group of contenders, startups that are betting
it all on the hope that quantum tech will one
day become profitable. One of those firms is Maryland-based
INQ. Its CEO is Niccolo Dimasi, who believes
he has the best horse in the race. We
supply quantum computers to our both federal, state,
and commercial customer partners. We also provide quantum key
distribution, and we do that both on the ground
and up in the heavens. Quantum key distribution is
effectively quantum cybersecurity, and we're very focused on.
This not being just proof points in the lab,
but doing useful quantum advantage examples for our customers and
embedding ourselves into their workflows on an ongoing basis.
So what will it look like as we go beyond
showing so-called quantum advantage in the lab and embedding it
into real world workflows? One place people look to
first is in the life sciences, work like Doctor
Garcia is doing at the Cleveland Clinic. An example
of something that we've done is we've taken some of
the algorithms that we've worked on for chemistry. And
alongside Cleveland Clinic, we've started looking at different chemical
processes that they really care about. So you can
think about this in the larger context of, you
know, therapeutics design, drug discovery, that kind
of thing. And really what we're doing with Cleveland
Clinic is pushing the boundaries of algorithm development, methodology
of using quantum computers again in concert with classical computers
to. Come up with solutions to problems that they
care about. Protein folding is definitely one area.
mRNA, secondary structure understanding, how things like come
together and how they look in sort of 3D is
a very interesting area, as you can imagine as
you're trying to understand how these things fit together in
a biological system. It isn't just life sciences that
could be revolutionized by the addition of quantum computing.
Financial markets are another target of opportunity. IBM scored
an early advantage this year when HSBC said it used
the tech company's Heron Quantum Processor to make a 34%
improvement in predicting how likely a bond will trade at
a given price. I think there's a lot of
excitement in the market space as well, right?
Especially because optimization is certainly in another area which we
know is a classically difficult problem. And um from
the point of view of actually using a quantum computer
to address optimization, there are many threads there in
terms of, you know, leveraging this kind of
large exponentially uh computational space to handle problems such as
portfolio optimization, right, or uh risk management,
right? So there's, there's a lot of interesting
ideas there that are being looked at by various financial
institutions. What I can say at this stage is
, uh, portfolio theory, options, pricing.
These are very much now accessible from a quantum advantage
perspective using our new Tempo system. Quantum key distribution
and cybersecurity that is of course front and center for
financial services on a global basis and so security and
integrity of the data flow is of course vital.
I always like to jokingly say that you can spot
our quantum security customers because they are not in the
news for data breaches. Even agriculture could benefit from
quantum computing in ways we haven't yet imagined. Understanding
processes such as nitrogen fixation to make things like better
fertilizer, right, to help us grow better crops
, right? Uh, understanding things that are critical
in uh impacting climate change, right, and in
terms of how, how uh carbon is handled,
right? Um, other things including better, better
batteries, right, in terms of uh materials discovery
. The potential may be great, as are the
investments being made, but when can we expect to
see these potentially dramatic results? It turns out that
that depends on whom you ask. IBM has made
getting to quantum advantage in the real world a strategic
priority. And has a timeline of getting there in
a big way by 2029. Our roadmap really shows
the detail in terms of how we want to get
from today to 2029. In between, we have
this real important milestone also that we believe that with
the community we'll be hitting quantum advantage, right,
where there'll be some problems and claims of advantage where
we'll see quantum really. Surpassing any classical methods of
solving certain types of problems, right, and we
are looking at various ways of showing that. Academically
, scientifically, and also empirically from the ground up
in terms of compared with various kinds of uh um
classical methods today, and then we're building a lot
of the, it's, you know, it's in
the end it's like architecting a a uh a large
skyscraper we're building a lot of the foundational elements so
that when we hit Starling in 2029. All the
applications that people have been developing, all the software
stack, all the eventual software libraries, they're still
going to work, so they're gonna work on a
machine that's even more capable, something that can run
hundreds of millions of gate operations compared to several thousands
of gate operations on the on the advantage level machines
that we're building today. IBM says it's on track
to have quantum computing payoff in a big way by
2029, but IAQ's Demasi says they're already there.
So our machines we announced on September 12th at our
analyst day are 36 quadrillion times more powerful than anyone
else's machine, and that gap is increasing. Not
only do we believe we are five years ahead of
anybody else in the quantum computing business. Whether it's
government programs, adversaries, or commercial companies, but
we also have the lowest unit economics, so we're
able to build a fully fault tolerant 2 million qubit
system and keep our cost of goods sold under$30
million. Taking that together, it means that we
are a fully fledged quantum internet solution. We can
provide our customers a platform of computing, cybersecurity,
networking, communications, and sensing. And there's no
other company in the history of the world that's ever
been able to supply a complete quantum internet. Everyone
in the quantum business seems to agree that Einstein was
wrong, that it's either coming soon or is already
here, and that it will be big. But
figuring out who's ahead in this race sometimes feels like
predicting those dice. IBM says it's ahead because it
has more total cubits in its machines. INQ says
it's not the number of cubits, but the number
of algorithmic qubits putting it in front. And quantum
company continuum has yet a 3rd measure of quantum volume
. Maybe we shouldn't be surprised that there isn't a
single measurement. It's like those cubits that are both
1s and 0s at the same time until they're observed
, and it looks likely that we will all be
able to observe what quantum computing can do for us
in the very near future.