Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: Yeah, welcome to this special edition of Bloomberg Technology. I
Speaker 2: am Ed Ludlow. We're live in San Jose and in
Speaker 2: videos GtC conference, where the major focus today has been
Speaker 2: quantum computing. Over the next thirty minutes or so, we're
Speaker 2: going to speak to Nvidia's senior director of Quantum, Tim Costa,
Speaker 2: as well as the leaders of quantum computing companies ion
Speaker 2: Q and d Wave. And actually I want to look
Speaker 2: at the shares of those companies. There was some downward
Speaker 2: pressure on a number of quantum computing stocks today. I
Speaker 2: flagged that only because that pressure continued as they were
Speaker 2: speaking on stage alongside Nvidia's CEO, Jensen Jog. Now, remember
Speaker 2: quantum stocks went into free fall on January eighth, after
Speaker 2: in Vidia's CEO said we were more than a decade
Speaker 2: away from quantum computers being able to do anything useful. Now,
Speaker 2: fast forward to today, and Juang had this to say
Speaker 2: about those earlier comments. Listen, I'm a.
Speaker 1: Public company CEO, and every so often someone asked me
Speaker 1: a question, and most of the time, most of the time,
Speaker 1: well some of the time, I'm trying to lower the
Speaker 1: bar here. Some of the time I say something right
Speaker 1: and sometimes sometimes it comes out wrong.
Speaker 2: Now here's the thing in the world of technology. Historically,
Speaker 2: at least, these have been two distinct fields, quantum computing
Speaker 2: and accelerated computing or supercomputers for AI, but increasingly those
Speaker 2: worlds are coming together. Joining me now is Tim Costa,
Speaker 2: who's the senior director for quantum Computing Adam Vidia, and
Speaker 2: I think a really important place to start is what
Speaker 2: Nvidia does and what Nvidia does not do. Sure, Nvidia
Speaker 2: does not make quantum computers, nor does it sell quantum computers,
Speaker 2: but it does provide architecture software, and so this is
Speaker 2: to that industry. Just explain your role, please. Yeah.
Speaker 3: So you nailed it on the head with the easy part,
Speaker 3: which is what we don't do. We do not build
Speaker 3: a quantum quantum computer, but we have a vision about
Speaker 3: how quantum computing will be useful. And it's really a
Speaker 3: point at which we have the integration of larger scale
Speaker 3: quantum technologies quantum processors as part of data centers and
Speaker 3: large scale computing. It looks very similar to what we
Speaker 3: have today right these If you look at today's large
Speaker 3: scale computing infrastructure, it's CPUs and GPUs and storage and
Speaker 3: memory and interconnects, and it's very complex, but better heterogeneous,
Speaker 3: and each part plays the role that it's best suited for,
Speaker 3: including the CPU and including the GPU. Quantum technology offers
Speaker 3: promise to be very good at certain kinds of computation,
Speaker 3: and so that will be an additional element of that
Speaker 3: system and come in. And so what we're focused on
Speaker 3: is really helping a helping the quantum tech companies who
Speaker 3: are building those technologies to better develop those technologies because
Speaker 3: we're interested in solving the problems that it will be
Speaker 3: able to solve, but also be setting up that infrastructure
Speaker 3: to be the best partner to that quantum device right
Speaker 3: to be able to do things like error correction, calibration
Speaker 3: of the devices. These are in some ways things you
Speaker 3: can think about as physics experiments upon which we try
Speaker 3: to compute as much as a computer, and so managing
Speaker 3: that physics experiment and getting the right results out of
Speaker 3: it is actually a complex computational task that we look
Speaker 3: to our accelerated supercomputers to actually perform.
Speaker 2: What we are literally talking about here is a computer
Speaker 2: scientist or engineer at a quantum computing company with access
Speaker 2: to some of your GPUs in whatever form. Fact, it
Speaker 2: could just be the single GPU could be scaled up
Speaker 2: to that server design, which we know as DGX. What's
Speaker 2: the market there? You know? How widely is your technology
Speaker 2: being used in parallel with many of the quantum names
Speaker 2: that we saw today.
Speaker 3: Yeah, So what who we saw on stage today was
Speaker 3: a great selection of our partners who are all engaged
Speaker 3: with and who all are using GPU technology as well
Speaker 3: as accelerated computing technology including the force acts and other
Speaker 3: components that we develop in their research program to simulate
Speaker 3: their devices and build better versions of their QPUs, to
Speaker 3: work with their clients and work on algorithm design by
Speaker 3: simulating a quantum computer, and also doing the fundamental research
Speaker 3: to drive towards that vision that I just discussed a
Speaker 3: minute ago, where we actually have this tight integration of
Speaker 3: these devices together. That involves work on the interconnect between
Speaker 3: the QPU and the GPU, that involves developing new methods
Speaker 3: for error correction that can be deployed at scale on
Speaker 3: a large supercomputer using novel AI methods, among many other areas.
Speaker 3: But those are not our only partners in this ecosystem.
Speaker 3: We're working with over one hundred and sixty groups in
Speaker 3: quantum computing, and the range of application areas is quite wide.
Speaker 3: But they're all using in video technology to accelerate their
Speaker 3: work because that's what we're ultimately here to do.
Speaker 2: So we started the day with the idea that in
Speaker 2: vidious technology can help quantum computers accelerate their own timeline
Speaker 2: reach that useful metric. But the idea raised and put
Speaker 2: Jensen Wong by those partners was actually the output of
Speaker 2: a quantum computer. In other words, the computation can work
Speaker 2: both ways. It could be submitted for use in the
Speaker 2: training of a foundation model. What do you make of that?
Speaker 3: Yeah, So I think that there's two sides of AI
Speaker 3: and quantum and they're both really important and really fascinating.
Speaker 3: And what I touched on a few minutes ago was
Speaker 3: the AI four quantum right, using AI models to actually
Speaker 3: control an error correct larger and larger and more capable
Speaker 3: quantum devices. It's incredibly important and it pulls in the
Speaker 3: timeline useful quantum computing.
Speaker 2: Yes.
Speaker 3: Now, the other side that was brought up today, and
Speaker 3: it's a fascinating topic, is you know, what is a
Speaker 3: quantum computer? If you start to boil it down and
Speaker 3: I won't try to go too far down, but it's
Speaker 3: they're really physics experiments. As I said, you're modeling quantum
Speaker 3: physics in the device, and so they're able to potentially
Speaker 3: provide data to train and fine tune models for understanding
Speaker 3: the very phenomena which are inside of a quantum computer
Speaker 3: in a way which will answer questions that humanity is
Speaker 3: and they've unable to answer. So we think that that's
Speaker 3: a really interesting and exciting area to pursue, and we're
Speaker 3: engaged with our partners across all these different areas.
Speaker 2: I don't think that in the context of all the
Speaker 2: attendees I've spoken to you today and Jensen and the panelist,
Speaker 2: that we've kind of reached definitive agreement and what useful is.
Speaker 2: But I think we've definitely reached agreement. But within your industry,
Speaker 2: that this accelerates what's happening pardon the pun, accelerated quantum computing.
Speaker 2: What happens next for Nvidia and their footprinting quantum. There
Speaker 2: is going to be a research center in Boston. That
Speaker 2: those can often be abstract things, But why is that
Speaker 2: an important step?
Speaker 3: It's an important step because we're going one of the
Speaker 3: things that we have to do if we're going to
Speaker 3: build a new kind of computer, and if we add
Speaker 3: a quantum accelerator to a computer like what we build today,
Speaker 3: that is a new kind of computer. You're adding a
Speaker 3: new computer ELEMENTUS. That is a physical endeavor. It has
Speaker 3: a footprint, needs a place to do it.
Speaker 1: Now.
Speaker 3: The center in Boston won't be the only place that
Speaker 3: that happens in the world, but it's a place for
Speaker 3: some of our partners and and US can work on
Speaker 3: developing the interconnect, developing the air correction technologies literally string
Speaker 3: up their quantum devices to our GPUs and build the
Speaker 3: first versions of these quantum accelerated supercomputers that we're all
Speaker 3: working towards.
Speaker 2: You'll view on what is useful. What do you think
Speaker 2: that a quantum computer will be able to achieve, whether
Speaker 2: it's assisted by nvideo or not sure.
Speaker 3: I think that one of the most important things that
Speaker 3: Jensen talked about today on stage was really narrowing the
Speaker 3: focus and deciding what the one the problem is so
Speaker 3: that you can define success and chase after it. I
Speaker 3: do think that there's fairly wide agreement in the community
Speaker 3: that one of the first areas is to be to
Speaker 3: be accelerated and to have new kinds of problems solved
Speaker 3: that weren't before. Is in chemistry, biochemistry related areas. I mean,
Speaker 3: there's some kind of sniff test. This passes.
Speaker 4: Right.
Speaker 3: You've got basically quantum physics in the quantum device, and
Speaker 3: the ability for that to model quantum physics in terms
Speaker 3: of what's required for very accurate chemistry just kind of
Speaker 3: makes sense. So we think that that's going to be
Speaker 3: the first area that's a disrupted early side you. I'm
Speaker 3: sure there's people on my team in discree me as
Speaker 3: we start today from the panelist. There are a wide
Speaker 3: variety of opinions on everything in quantum, but we think
Speaker 3: that's promise them.
Speaker 2: Well, we're grateful for yours. Tim Coster, Senior director of
Speaker 2: Quantum Computing at Nvidia, thank you very much. A lot
Speaker 2: more coming up. We speak with ion Q executive chairman
Speaker 2: Peter Chapman. That's next. We'll be right back. This is
Speaker 2: Bloomberg Technology. Welcome back to a special Bloomberg Technology at
Speaker 2: nvidia's GtC Quantum Day. Ion Q was one of the
Speaker 2: quantum computing companies invited on stage today alongside Jensen Wang
Speaker 2: here at gtc's Quantum Day. The company's stock was one
Speaker 2: of those hardest hit January eighth, after Invidias Jensen Wong
Speaker 2: made those comments about quantum computing and its usefulness being
Speaker 2: quote a decade or more away. Since then, ARMQ has
Speaker 2: gone through some changes, appointing Nicolo Demasi as its new CEO.
Speaker 2: The former CEO Peter Chapman continues as executive chair and
Speaker 2: I'm delighted to say joins us now on set. And
Speaker 2: what was interesting in the conversation with Jensen Wang is
Speaker 2: that you were balanced in saying I'm not I don't
Speaker 2: think we necessarily agree on everything here. Still, let's start
Speaker 2: with the main point, which is did we define usefulness
Speaker 2: and do you have a sense that Jensen Wang has
Speaker 2: changed his timeline of when he thinks usefulness of your
Speaker 2: industry will be achieved?
Speaker 5: Well, I think today was kind of the purpose of
Speaker 5: today was to bring that timeline in to kind of
Speaker 5: take back what it is that he had said before.
Speaker 5: He said on stage I think twice it was his
Speaker 5: mea copper yes, right, So that was the purpose of
Speaker 5: today's kind of.
Speaker 2: He said that he would be the first CEO probably
Speaker 2: in history to invite a panel of people to te
Speaker 2: them that he was wrong.
Speaker 5: It was wrong, is exactly so, and it was funny today.
Speaker 5: Just in general, we've been working with Nvidia on a
Speaker 5: demonstration for today that was with Nvidia AWS and Astrozeneca,
Speaker 5: where we'd gotten a twenty x improvement on what we
Speaker 5: had done previously. Also, we had taken with answers with
Speaker 5: a product that they do which is normally run on GPUs,
Speaker 5: and managed to get a twelve percent increase in using
Speaker 5: our quantum computers. So while those numbers are not really
Speaker 5: enough to take over the market, because usually you need
Speaker 5: one or two orders of magnitude to be disruptive to
Speaker 5: a market, the fact that we managed to do it
Speaker 5: on the kind of our thirty six cubit system is
Speaker 5: really quite remarkable.
Speaker 2: Nvidia has a quantum computing business in so far as
Speaker 2: we got into it during the panel. That you have
Speaker 2: access to architecture, DGX, the hype performance, GPUs, also some
Speaker 2: software and open source solutions, and what they would say
Speaker 2: is that that will help your engineers and computer scientists calibrate,
Speaker 2: reduce err accounts, design better. Is that how it actually
Speaker 2: plays out for you some aspects.
Speaker 5: We have a DGX cluster that we use for a
Speaker 5: design for designing other quantum computers, not so much in
Speaker 5: the error correction aspect. That's something we do ourselves, but
Speaker 5: certainly we use a number of GPUs for designing the
Speaker 5: quantum computer itself. We also for small cube accounts, because
Speaker 5: soon as you get into me on about thirty five cubits,
Speaker 5: you can no longer simulate one of these on a GPU,
Speaker 5: So for those we actually run the simulation on a
Speaker 5: GPU just to make sure our hardware is working correctly.
Speaker 5: The problem is, when you get to sixty four cubits,
Speaker 5: you need two and a half billion GPUs.
Speaker 2: Because for each cubit you add to perform its essentially
Speaker 2: double bubbles.
Speaker 5: Right, and it means that the matrix math that you
Speaker 5: have to do suddenly is doubling as well. So basically
Speaker 5: is it about thirty five cubas To fully simulate it,
Speaker 5: you can only get it on a single dgx one hundred.
Speaker 2: I got to hold you to this, and I wonder
Speaker 2: if it ties into the new CEO and you know,
Speaker 2: sort of reset a little bit. There's a difference between
Speaker 2: lab experiment and commercial use, you know, making money, revenue generation.
Speaker 2: That's the question I get for you most.
Speaker 5: Yes, so what Jensen said, we actually one area we
Speaker 5: definitely agree on, which is you need to find a
Speaker 5: set of applications early on that you can start to
Speaker 5: make money on and to build that firewheel to be
Speaker 5: able to power your R and D. And so the
Speaker 5: examples we're talking today, for instance in the chemistry application
Speaker 5: and also with answers is exactly those kinds of things.
Speaker 5: So that's exactly what our plan is.
Speaker 2: PCU or the executive chairman. Now you were CEO one
Speaker 2: week ago, Kerisdale issued a short report on your stock
Speaker 2: on your company. I just want to give you a
Speaker 2: chance to respond, as we've not had a chance to
Speaker 2: speak since then.
Speaker 5: Sure, it's a short report, so their goal is obviously
Speaker 5: to try to cast out about the company and make
Speaker 5: money that way. Unfortunately, it's just a if you're a
Speaker 5: public company, these are the kinds of things you have
Speaker 5: to endure. You know, we don't put much credence to
Speaker 5: those things.
Speaker 2: The last thing I want to ask you is about
Speaker 2: how big today was in the change of trajectory or
Speaker 2: momentum for your industry. Jensen Wang is a character and
Speaker 2: he was honest on stage. But GtC is an incredible event.
Speaker 2: It has scale, it has eyeballs. Do you think you'll
Speaker 2: see something of substance come out of this for your company,
Speaker 2: for your sector?
Speaker 5: You know, it's an interesting it's certainly Jensen's goal was
Speaker 5: to give us the microphone today to be able to
Speaker 5: get out our story, and that's certainly important. But I say,
Speaker 5: if you were Sam Altman five years ago trying to
Speaker 5: convince the world that AI is coming, probably he wouldn't
Speaker 5: have been successful. And the question is is how much
Speaker 5: time should Sam Altman try to convince the world AI
Speaker 5: is coming? Instead just go back and actually make it happen.
Speaker 5: So in that sense, actually it's probably not that significant.
Speaker 5: What really matters is actually going and doing it, not
Speaker 5: actually getting the message out.
Speaker 2: I'm Q Executive Chairman Peter Chapman. Thank you for your
Speaker 2: time here in San Jose at GtC. Okay, much more
Speaker 2: to come. Alan Barrat's CEO d Wave, another one of
Speaker 2: the quantum computing CEOs on stage, joins us, and they
Speaker 2: have an example of success or something useful blockchain architecture progress.
Speaker 2: That's next. This is Bloomberg Technology. Welcome back to a
Speaker 2: special edition of Bloomberg Technology Live in Videos. GtC Quantum
Speaker 2: Day so shares of some quantum computing companies sank today
Speaker 2: after leaders spoke at an event with in video CEO
Speaker 2: Jensen Huang. The plunge follows a similar move back in
Speaker 2: January after Huang said it would be more than a
Speaker 2: decade before the technology quantum computing could do something that's useful.
Speaker 2: One of those quickest to say in the month of
Speaker 2: January that Wang was wrong was d Wave CEO Alan Barrats.
Speaker 2: D Wave shares under pressure today for whatever reason. But Alan,
Speaker 2: I'm grateful for your time, and I think it's fair
Speaker 2: to say that among the panelists you maintained those areas
Speaker 2: that you don't agree with Jensen Hwang on. How in
Speaker 2: any way is your mind changed on those differences through
Speaker 2: the course of today.
Speaker 4: Well, my mind has not changed. The fact of the
Speaker 4: matter is that we at d Wave have taken a
Speaker 4: very different approach to quantum computing from everybody else in
Speaker 4: the industry, and as a result of that, we are
Speaker 4: actually able to support useful, important applications today.
Speaker 2: And I think the best.
Speaker 4: Example of that is the paper that we published in
Speaker 4: Science last week, where we have demonstrated that we can
Speaker 4: compute properties of magnetic materials that just cannot be computed classically,
Speaker 4: and this gives us the opportunity to create new materials
Speaker 4: discovery platforms which will dramatically reduce the time and cost
Speaker 4: to create new materials.
Speaker 2: And that seems pretty useful to me. Yeah, there's also
Speaker 2: some applications that the audience might find harder to understand.
Speaker 2: For example, blockchain architecture. Why is a quantum computer able
Speaker 2: to improve that process where a supercomputer classically coded in
Speaker 2: ones and zeros cannot.
Speaker 4: So basically, what we did was we were able to
Speaker 4: show that that same computation that we use to compute
Speaker 4: properties of magnetic materials could be used to basicly we
Speaker 4: compute the hashing functions that are used in blockchain and cryptocurrency.
Speaker 4: What this means is that we can now create a
Speaker 4: blockchain that uses a quantum computer to do the proof
Speaker 4: of work. What's so important about that is that quantum
Speaker 4: computers consume far less energy than classical computers, So this
Speaker 4: means cryptocurrency mining could be at a fraction of the
Speaker 4: energy cost of what we're seeing today.
Speaker 2: One of those two case studies revenue generates this VIE.
Speaker 4: Well, the first prototype of this blockchain is running right now.
Speaker 4: We have it running on four of our quantum computers.
Speaker 4: It's the first distributed quantum application where each of the
Speaker 4: quantum computers can create hashes or validate hashes, basically run
Speaker 4: the proof of work algorithm. And we're now in the
Speaker 4: process of building that out so we can get to
Speaker 4: the point where we can support a full commercial blockchain.
Speaker 4: How long do I think that'll take? Yeah, I think
Speaker 4: we're looking at a year or two.
Speaker 2: Not the ten or fifteen. The ten or fifteen or
Speaker 2: twenty two. So there is work than a video.
Speaker 4: But by this, I mean that's just one application, right,
Speaker 4: I mean the materials discovery that's running today. We have
Speaker 4: customers like Entity DoCoMo. They're using us today for cell
Speaker 4: tower resource optimization. So we are useful today. Blockchain is
Speaker 4: one of our newest application areas, and yes, we're just
Speaker 4: starting to roll there.
Speaker 2: The point of difference I think, I still think is
Speaker 2: Jensen's definition of usefulness. Perhaps, But you know, Nvidia does
Speaker 2: do work with your industry. To summarize, it's basically offering
Speaker 2: GPU access on the architecture side, as well as some
Speaker 2: research and open source facilities on the other side. And
Speaker 2: their argument is you can take that and use it
Speaker 2: to make your quantum computers better calibration, air account reduction,
Speaker 2: and I think other your colleagues mentioned design, how do
Speaker 2: you work with video?
Speaker 4: Okay, so annealing quantum computers do not have the same
Speaker 4: error correction requirements as gate model quantum computers. So we
Speaker 4: are solving useful problems today without error correction, and as
Speaker 4: a result, that component of what Nvidia brings to the
Speaker 4: table is not all that important to us today. When
Speaker 4: it comes to calibration. We have the largest quantum computers
Speaker 4: in the world. Our current systems are at five thousand
Speaker 4: cubits and growing. We calibrate them ourselves. We don't need
Speaker 4: GPU paler to calibrate those systems, so currently we do
Speaker 4: not I mean, I know Jensen says he works with
Speaker 4: all the quantum computing companies, but d Wave is quite different.
Speaker 4: We are a different We've taken a different approach. We
Speaker 4: are at a different level of maturity, much more mature
Speaker 4: than the other quantum computing companies. We are delivering useful
Speaker 4: applications and useful value today. Now that having been said,
Speaker 4: we are also developing a gate model quantum computer. The
Speaker 4: approach that everybody else has taken for that effort, we
Speaker 4: will be looking to leverage some of the same sorts
Speaker 4: of things that the other quantum computing companies are leveraging.
Speaker 4: But we view a kneeling and gate as very complementary.
Speaker 4: They solve different classes of problems.
Speaker 2: We only have thirty seconds. It was a pretty public disagreement,
Speaker 2: argument debate. Will it help you in the long run?
Speaker 2: What happened today here in San Jose.
Speaker 4: I don't think this event was all that helpful to
Speaker 4: the industry or to d WAVE.
Speaker 2: I think.
Speaker 4: I thank Jensen for the opportunity to participate. I think
Speaker 4: that it was great to have the opportunity to try
Speaker 4: to get the message out. But I think we're still
Speaker 4: at the beginning of a learning curve with respect to
Speaker 4: how Nvidia and Jensen interact with quantum computing companies.
Speaker 2: D Wave CEO Alan Barratz, thank you for your time
Speaker 2: here in San Jose. Whether you agree with your host
Speaker 2: or not, Well, that does it for this special edition
Speaker 2: of Bloomberg Technology a lot to re cap, particularly when
Speaker 2: it comes to quantum computing, So don't forget our podcast.
Speaker 2: You can find it on the Bloomberg terminal as well
Speaker 2: as online on platforms like Apple Spotify, and iHeart Live
Speaker 2: from San Jose, California, at GtC and Video's Quantum Day.
Speaker 2: This is Bloomberg Technology