NVIDIA GTC 2025 Quantum Day Panel 1

Summary

The NVIDIA GTC 2025 Quantum Day panel was an intriguing showcase of the potential and challenges within the quantum computing industry. Led by NVIDIA CEO Jensen Wong, the panel gathered leaders from various quantum computing companies to discuss the current state and future of quantum technology. The discussion highlighted different approaches to quantum computing, the complexities involved, and NVIDIA's role in supporting this growing field with research initiatives like the Quantum Research Lab in Boston. The session also explored the ongoing debate about the usefulness and application of quantum computers, suggesting they might be better positioned as precision tools for scientific discovery rather than general-purpose computing equivalents.

Highlights

• NVIDIA aims to bolster the quantum computing field with its technologies without manufacturing quantum computers. 🚀
• Jensen Wong humorously reflects on the confusion caused when he commented on quantum computing timelines. 😂
• Quantum computing technologies are varied, with different methods like trapped ions and superconducting qubits being explored. 🔄
• NVIDIA announces a new Quantum Research Lab to push the boundaries of hybrid quantum computing in Boston.🏙️
• The panel debated whether quantum computers should be seen as instruments for special scientific tasks or universal computers. 🤔
• Talks suggest that quantum computing is still evolving with much potential for breakthroughs in numerous sectors. 📈

Key Takeaways

• NVIDIA doesn't build quantum computers but supports the industry through accelerated computing technologies. 💡
• Quantum computing is a complex field with multiple technological approaches like trapped ions, neutral atoms, and superconducting qubits. 🛠️
• NVIDIA is opening a Quantum Research Lab in Boston to collaborate with leading institutions. 🏢
• The discussion raised questions about framing quantum computers as precision instruments versus typical computers. 🔍
• There is optimism about quantum computing's future impact on scientific discovery and problem-solving. 🌟

Overview

At NVIDIA's GTC 2025 Quantum Day, the stage was set for a dynamic and cerebral exchange on the current and future states of quantum computing. Jensen Wong, founder and CEO of NVIDIA, facilitated the discussion, which included several prominent figures in the quantum computing space. Despite NVIDIA's lack of involvement in manufacturing quantum computers, Wong emphasized the company's crucial supportive role in providing accelerated computing stacks to the industry. This event was marked with humor and candid conversations about the challenges and complexities within the quantum computing landscape.

A significant highlight of the event was Jensen Wong's recounting of past misinterpretations about the quantum computing timeline, which led to stock market reactions. This was a segway into the more serious panel discussions covering the diverse technological approaches explored by companies like D-Wave, IonQ, and others, who presented their unique methods such as using trapped ions and superconducting qubits. It was also announced that NVIDIA is establishing a Quantum Research Lab in Boston, further cementing its commitment to advancing quantum research.

Participants at the event discussed whether quantum computers should be considered specialized scientific instruments rather than general-purpose computers, stirring an insightful dialogue about the future role of quantum technology. The consensus was that while full-scale adoption is years away, the future holds immense promise. There seemed to be a shared sentiment of optimism about quantum computing's potential impact on fields like material science, chemistry, and beyond, where it could drive significant advancements.

Chapters

• 00:00 - 03:00: Introduction by Jensen Huang Nvidia founder and CEO Jensen Huang opens the GTC event with an introductory address, marking the start of Quantum Day, the first of its kind. He highlights the significance of the event and welcomes attendees sharing that it's going to be an extraordinary gathering.
• 03:00 - 06:00: Quantum Computing Complexity The chapter titled 'Quantum Computing Complexity' seems to delve into the experiences and insights of a public company CEO, who shares anecdotes and responses to inquiries he receives. Despite the introduction of the chapter suggesting a focus on quantum computing, the transcript provided primarily reflects the speaker's reflections on engaging in public speaking and occasionally delivering responses that he perceives as apt. The complexity of quantum computing or specific technological insights are not detailed in the given transcript.
• 06:00 - 10:00: NVIDIA's Role in Quantum Computing The chapter discusses NVIDIA's involvement in the evolution and future of quantum computing. It begins with an anecdote about a question posed regarding the timeline for the utility of quantum computers. This context is provided through the perspective of someone with a deep background in building computing platforms, specifically NVIDIA and CUDA. The narrative suggests an exploration of technological advancements and the role of industry leaders in accelerating quantum computing's usability and practical applications.
• 10:00 - 15:00: Opening of Quantum Research Lab The chapter titled 'Opening of Quantum Research Lab' discusses the development of a quantum computing platform which has been a progression over more than 20 years. The speaker emphasizes that the time horizon of 5 to 20 years is not significant when considering the breakthroughs in quantum computing. Quantum computing is seen as a field with the potential to deliver extraordinary impacts, reflecting the hopes invested in its advancement.
• 15:00 - 18:00: Introduction of Panelists The chapter discusses the complexity of technology and how achieving advancements in this field can take years due to its intricate nature. It highlights the significant impact technological breakthroughs can have, which warrants prolonged development times. The speaker reflects on a personal experience where a prediction about the tech industry led to a notable reaction in company stocks, emphasizing the interconnectedness of technological advancements and economic sectors.
• 18:00 - 27:00: Quantum Computing Approaches The chapter discusses the speaker's surprise at learning about public quantum computing companies. The speaker mentions a specific instance where a company's stock decreased by 60%, which led them to start learning more about the industry. The speaker expresses surprise that a quantum computing company is publicly traded and shows happiness for the company's presence in the public market.
• 27:00 - 36:00: Potential of Quantum Computers The chapter discusses the potential of quantum computers and the current state of the quantum computing industry. The speaker invites companies from the industry to share their insights and knowledge. The aim is to understand the advancements in quantum computing without any preconceived negative notions or disruptions, metaphorically referring to these disruptions as throwing 'cabbages and apples.' The speaker emphasizes the significance of this moment to learn and appreciate the extraordinary aspects of quantum computing.
• 36:00 - 44:00: Positioning of Quantum Computers The chapter explores various approaches to the positioning of quantum computers, including trapped ions, neutral atoms, superconducting qubits, and topological qubits. It also mentions quantum annealing and photonics as methods in the field. The chapter suggests a discussion among CEOs and technology leaders from pioneering companies to explore these technologies further.
• 44:00 - 53:00: Applications and Challenges The chapter titled "Applications and Challenges" covers a unique event in history where a company CEO invites guests to explain why he was wrong. This intriguing premise sets the stage for a discussion on the importance of open dialogue and learning from different perspectives, which is highlighted as a key theme of the event.
• 53:00 - 62:00: Classical and Quantum Collaboration The chapter titled 'Classical and Quantum Collaboration' highlights Nvidia's role in advancing technology through creating accelerated computing stacks. While Nvidia does not produce quantum computers, it facilitates the development and integration of these technologies. Similarly, Nvidia is deeply involved in the automotive industry, particularly with autonomous vehicles, by collaborating with various car manufacturers, despite not producing cars themselves.
• 62:00 - 64:00: Future Expectations and Conclusion This chapter discusses Nvidia's diverse technology and product range, emphasizing its 'three computer solution' aimed at advancing robotics across various domains. The focus is on the integration of complex computing systems, libraries, algorithms, and models to facilitate sophisticated robotics, from factory to facility-level automation.

NVIDIA GTC 2025 Quantum Day Panel 1 Transcription

• 00:00 - 00:30 welcome to the stage Nvidia founder and CEO Jensen [Music] Wong good morning welcome welcome to Quantum day at GTC the first of its kind yeah this is this is going to be a very very special event uh as you know
• 00:30 - 01:00 this Al well you might not know so so um you know I'm a public company CEO and and every so often someone asks me a question and most of the time most of the time well some of the time I'm I'm trying to lower the bar here some of the time time I I say something right and
• 01:00 - 01:30 and sometimes sometimes it comes out wrong and and so what happened was somebody asked me uh how long before a quantum computer uh will be will be useful and um and remember this is from somebody who's built a Computing platform and to me building Nvidia and building Cuda
• 01:30 - 02:00 and turning it into the Computing platform that is it is today it has taken us almost well it's taken us over 20 years so the idea that time Horizons of 5 10 15 20 years is really nothing to me and of course of course Quantum Computing has the potential has the potential and and the hope all of our hopes that has it will deliver extraordinary impact um but the
• 02:00 - 02:30 technology is insanely complicated and so the idea that it would take years to achieve uh was something that that uh one uh I would expect two uh because of the complexity of it and the gr Grand impact it would have um something that we should expect and so when I said the the answer uh uh next day I discovered that several Company stock apparently the whole industry
• 02:30 - 03:00 stock went down 60% and and then and then I'm starting to learn about this and my first reaction was I didn't know they were public How could a quantum computer company be public and anyhow I discovered that we're public companies I'm very happy for them and uh uh
• 03:00 - 03:30 yes I'm very happy for them so I said listen listen the world's got this wrong let's invite all of those companies and more the quantum Computing industry and uh to the extent that they don't bring cabbages and apples and you know stuff that they can throw at me uh to the extent they that that this would be an extraordinary moment that we can learn about the state-of-the-art of quantum computing there are so many
• 03:30 - 04:00 different approaches trap ion neutral atoms super super conducting cubits topological cubits you have uh Quantum analing photonics I mean there's so many different different ways of addressing this that I thought wouldn't it be amazing if the CEOs the technology leaders the compan the companies that are leading this pioneering technology were coming together for the very first time to talk about it and um and of course in the process they could they
• 04:00 - 04:30 could explain why I was wrong you know this is going to be the this is the first event in history where where a company where a Company CEO invites all of the guests to explain why he was wrong but I don't know so that's what makes this movie so great that's what makes this this event
• 04:30 - 05:00 so great anyhow we don't make quantum computers Nvidia doesn't make quantum computers but we dedicate ourselves to creating accelerated Computing Stacks to enable quantum computers we do the same with self-driving cars as you know Nvidia is probably more integrated into the world of automobiles and autonomous vehicles and we work with just about everybody in some way to advance autonomous vehicles and yet we don't build cars
• 05:00 - 05:30 uh Nvidia has a broad R broad range of of Technologies and product offerings and libraries and computers we call the three computer solution to help Advance robotics in all forms facility robotics Factory robotics factories that are going to be robotics to build uh orchestrate robots that are going to build products that are robotic incredibly complicated set of computing and libraries and algorithms and models and and we approach it in a
• 05:30 - 06:00 way as if we are deeply integrated into the ecosystem and Industry and we care deeply about them and yet we don't build robots we don't build quantum computers but we are deeply integrated into the quantum Computing industry and we create libraries CA Q is a programming model for hybrid classical accelerated Quantum we have C Quantum libraries that help you uh simulate Quantum circuits and uh
• 06:00 - 06:30 dgx Quantum to do error correction uh of quantum computers we partner with them we support them we help them in any possible way and uh you know but but try to try try not to uh say anything that trips them up every now and then and so anyways anyways uh we care deeply about this ecosystem and I'm really really happy to bring uh our partners uh many of our friends there are many that are that are not here and the reason for that is because you know we had to do
• 06:30 - 07:00 this in three panels there were so many people the quantum Computing industry um as you know a new Computing platform is not easy to create and we didn't create Cuda Computing ourselves we created the architecture of course we created the computers we dedicated ourselves to a very very long uh road map of compatibility and dedication to helping developers and creating libraries and tools and evangelizing and so on so forth but in the analysis the Cuda accelerated
• 07:00 - 07:30 Computing ecosystem was built by all of us that's what GTC is about in a lot of ways this is just the beginning of the quantum Computing ecosystem and uh it's really terrific to be able to celebrate it with uh all of our friends and partners and so I'm going to invite uh many of them on stage I just want to let you know that there were many that we couldn't and I want to thank all of you for your partnership and your friendship and and we'll try to invite you next time uh but before I do that
• 07:30 - 08:00 we're making announcement I'm making an announcement today that Nvidia is starting now I'm saying this as if this announcement is coming as a result of I just want to let you know that that we were going to make this announcement before this okay so you don't make it it this the cause and effect physics matter here okay the the the cause and effect is in this case is completely unrated we're announcing that Nvidia is we we're going to open a Quant research lab in
• 08:00 - 08:30 Boston it's going to have a yep it will likely be the most advanced accelerated Computing um hybrid Quantum Computing uh research lab in the world and it's going to be located in Boston so that we could partner with Harvard and MIT and and uh uh some of our partners are going to be in there initially but many others will be working in this Quantum research lab in the long term uh quantum continum Quantum machines and Q are going to be
• 08:30 - 09:00 uh the inaugural partners with us to build this Quantum research lab and so I'm very happy about that and and uh we're going to get that going as soon as possible and so uh now what I'm going to do is I'm going to introduce uh some of my CEO colleagues and um uh and please please uh join me to welcome them uh Alan baratz d-wave [Applause]
• 09:00 - 09:30 alen Peter Chapman ion Q Peter thank you uh let's see I think the next one is L henriet I think right isn't ly okay welcome and rajib Raj hazra quanum [Applause]
• 09:30 - 10:00 rich and subad subad come on stage we're [Applause] getting nice to see you so I think the I guess the first thing is sorry about that that was funny that was you know for everybody we do hang on a second come on Mikel goodness
• 10:00 - 10:30 gracious I left cuera behind sorry about that so so I it reminds me of a joke it reminds me of a a short story this this is nothing like you so anyways I was left behind this was in 19 1995 and uh we had just started Nvidia the 3D Graphics uh ecosystem whole bunch of 3D Graphics companies it was like a
• 10:30 - 11:00 new 3D Graphics Company per week and and we were the first one to start uh but after a couple years there were like 50 60 competitors and uh we started uh we created an architecture which we chose a technology which was exactly wrong okay and and um uh and so even though we were the first company to start because our technology was exactly wrong uh we were about to go out of business and and uh this this fin fincial analyst no IND
• 11:00 - 11:30 industry analyst that follows the industry he he kept a list of all the companies that were building 3D graphic and so anyways we were and it was being published every single week and then one week it came out and we were left off that list and so I was left behind and and I said why'd you leave us off the list he said well I thought you guys went out of business but you you guys are doing great sorry about that great story great story all right
• 11:30 - 12:00 so so uh so listen so uh each one of you have some of you have chosen different approaches I mean there there quite a few different approaches to Quantum Computing and and uh maybe maybe what we could do is we start uh by having each one of you us and just remember there were a whole bunch of us so so each one of you take a moment and talk about your approach and why you did it and since Mel since I almost I almost left you behind why did you start thank you so first off thank you for hosting us it's amazing uh to be
• 12:00 - 12:30 here thank you um and um you know also thank you for your contribution to this emerging Quantum ecosystem so we are building quantum computers literally from single atoms and uh we assemble them and control them using um arrays of laser beams using basically techniques like holography uh techniques similar to those used to project for example to beam their you know computer uh kind of images to the big
• 12:30 - 13:00 screens um and uh the key advantages uh is that um the items are basically god-given cubits they're all identical they um have uh they're extremely well isolated you know we can preserve Quantum States for a very long time um but also we can use light we can use lasers to control these atoms uh basically position them at will and move
• 13:00 - 13:30 them around uh including both during the computation process itself and in particular it allows one to build allows us to build the uh a processor where connectivity is basically a living organism it evolves during computation itself and uh this is very special so this allows us to build systems now which have thousands of cubits um it uh
• 13:30 - 14:00 allows us to deploy for the first time these techniques of error correction which you mentioned and execute um algorithms with the so-called protected logical cubits great and this is um yeah it's a very special approach and we're in a very special time using this approach yeah thank you Mel go ahead let's take turns go ahead uh so thank you for the opportunity so at RTI Computing uh we develop superc conducting gate based quantum computers uh we are based in Berkeley here and we
• 14:00 - 14:30 also have a Fab in Fremont so why superc conducting gate based Quantum Computing gate based because that's how we know how to do the broad world of computing that's how classical computers run um why super conducting that's an area where along with us there are many other companies including some big companies like IBM Google Amazon as well as the government of China is investing heavily in superc conducting gate based Computing uh the reason we like superc conducting is primarily because of its advantages in scalability and gate
• 14:30 - 15:00 speeds we are using fundamentally a silicon chip so we know how to scale up once we because of the leverage of semiconductor industry and five Decades of experience there and because we are dealing with electrons our gate speeds are intense of Nano seconds uh and that makes it very easily compatible with the CPU GPU ecosystem which is the way we think Quantum Computing is going to come along so we feel very good about scalability and gate Speed The Challenge and Achilles heel if you will of super conducting Quantum Computing has always been
• 15:00 - 15:30 Fidelity we get noise because of this intrinsically engineered devices in the chips just like seos technology and historically that was in the low 90s and mid90s when the cubits entangle with each other the two Cubit get frity is what we call it what's been exciting is in the last few months arals along with some other companies in super conducting like IBM and Google have made some very important strides and now we are in the 99 to 99.5% 2 Cubit gate Fidelity which is commen through comparable with the
• 15:30 - 16:00 best over here in with pure atoms and other areas so we maintain the advantages of scalability and gate speed but now we feel very good about where we are with Fidelity so that makes it a lot more attractive within the space reting um we differentiate ourselves by hand open modular approach so we have designed our stack so if we find a more creative solution out there whether it's an error correction from a company like riverlane or Cuda Q from Nvidia or Quantum machines for Control Systems we can easily in that into our stack as opposed to some other companies
• 16:00 - 16:30 like IBM or Google who have designed it in a Mainframe approach We Believe an open modular approach is the right way to build a build an ecosystem while we are in R&D MH so in the overall Journey we um our Flagship system is an 84 Cubit system um with 79 second gate speed it's available to anyone on AWS and Azure right now we believe it's one of the best but frankly it's not good enough yet for any practical use as we talked about earlier and um we think we are roughly well don't give up yet don't
• 16:30 - 17:00 give up yet let here R why don't you start thanks Jensen for hosting us so at quanum we build uh quantum computers using the trapped ion modality as it's called Uh and a particular architectural approach called qcc or Quantum charge couble device uh the beauty of this approach is it produces the industry's highest fidelities uh triple n9s and Beyond uh and there are a lot of challenges in
• 17:00 - 17:30 Quantum Computing as you know however coherence time scalability Fidelity these are some of the the the most challenging properties and and as you're thinking about and listening to to these different Quantum Computing approaches you just listen for those words I think they're they're consistently being used anyhow and and uh it helps you helps you uh uh understand the the the the pros and cons or the challenges and and the opportunities associated with each one of the Technologies okay go ahead regie
• 17:30 - 18:00 so thank you for filling it in uh basically we have the industry's highest fidelities you asked about what approach to it our approach is to extend the qcd architecture into higher levels of scale so we will have um 50 logical cubits so highly reliable cubits this year 100 logical cubits in about 18 months and we see a clear path to millions of cubits early in 2031 32 time frame um another part of
• 18:00 - 18:30 our approach is not just building the science of it our approach is we work on really really challenging problems so it's like living on the edge we work on them with hardware and software we build and with customers so we aren't trying to look create a solution looking for a problem but start with the notion of what big hairy problem are we going to lunatic go attack and then build our capability across hardware and software to be able to do that and I hope we get
• 18:30 - 19:00 a chance to talk a little bit about what else is out in the industry today that is a beautiful comp well welcome to GTC we have a lot of hairy problems here all right so thank you Roi yeah L go ahead yeah thank thanks a lot for hosting us um at Pascal we build Quantum processors uh that leverage the neutral atom technology so quite close to what mukin and quera is doing um this technology has several key advantages like
• 19:00 - 19:30 scalability we can we can trap and control many of those cubits right now thousands of them um and also it's easy to control them with laser light and it's a relatively recent technology compared to tra ions and super super conducting cubits to develop quantum computers actually it's it's it's more recent but there is a lot of progress and a lot of momentum in terms of uh uh uh gate fidelities and scaling of of this
• 19:30 - 20:00 approach um at Pascal what we are also committed to doing is uh working very strongly on engineering of those devices to turn them uh from lab experiments to real Industrial Products I think we all agree here that usage and adoption is is very key for the entire Quantum Community right now and Pascal we really want to to to to deliver on that promise so over the past 18 months we've uh We've delivered uh we we deliver we'll
• 20:00 - 20:30 have delivered uh uh four machines worldwide uh including one in France in CA jeny and another one in Germany uh Udi super Computing Center so that's that's about it for Pascal we we work with neutral atoms and focusing very strongly on on engineering that's terrific thank you go ahead Peter please tell us about company so I umum I'm the chairman uh for I IQ we're a trapped ion company like Continuum um trapped ions actually were
• 20:30 - 21:00 used back in 1995 uh when they were looking at atomic clocks atomic clocks and and our technology have a huge overlap and back in 1995 a team at nist and one of the co-founders of IQ did the first ever Quantum logic gates and all of this craziness that you see coming all started in 1995 from that experiment so we're now 30 years into this investment um in trapped ions so very similar to
• 21:00 - 21:30 other modalities we use individual atoms and we use lasers to do computation we're down at 02 nanometers so when you look at the Silicon industry they're way way up there compared to where we play we play with individual atoms um so these uh the advantages to our technology is one is you can have a room temperature quantum computer so it can fit in a rack and to be honest
• 21:30 - 22:00 it looks kind of boring compared to to um what you probably imagine because it'll be rack based room temperature the other Advantage because where we use Optics and lasers is that you can Network them together to do distributed Quantum Computing to get to larger numbers of cubits and you can reuse the existing infrastructure of the internet using fiber optics and then as as um uh has been mentioned trapped ions have the
• 22:00 - 22:30 best average two cubic gate fidelities and so um in that sense they lead and and that's a fairly large Advantage because uh it means that the amount of error correction that you need to do is will be less than maybe some other Mo modalities but each one of and I I just say since 1995 it's amazing how many different modalities have showed up for cubits and the amount of progress that's been made uh so it's really quite exciting from that that point of view um
• 22:30 - 23:00 and it's great to see the leading companies on stage here today with us so yeah thank you Peter alen go ahead thanks Jensen so uh we are a superconducting company similar to retti uh we believe that superconducting provides the best balance between Cubit Fidelity or the quality of the cubits and gate speeds time to compute but we're actually quite unique from everybody else on this panel and pretty much everybody else in the industry
• 23:00 - 23:30 because we use analing technology as opposed to gate model technology um without going into the details analing is a much easier technology to work with it's easier to scale it's much less sensitive to noise and errors and probably the best uh proof point for that was in a paper that we published in science last week where uh we performed a useful computation properties of magnetic materials that would take nearly a million years to compute classically uh and then this
• 23:30 - 24:00 week we actually uh put a paper on the archive where we showed how to use that computation to create Quantum proof of work in a blockchain so the idea would be that you would use the quantum computer to create the hashing function and you would use the quantum computer to validate the hashing function and we now have this running on four of our quantum computers as the first distributed Quantum application um where in fact we're generating hashes we're
• 24:00 - 24:30 validating hashes and we think this could be a very interesting much lower energy consumption approach to blockchain you know every time that that somebody in the quantum Computing industry achieves a milestone it stirs up a fair amount of of um controversy among the others did you stir up any controversy in your achievement um because at at the moment I think it's I think the the the achievement to controversy
• 24:30 - 25:00 ratio is is literally one to one so so the answer to the question is that I've received a lot of um positive feedback from my colleagues in the industry just it was exactly like me when I did that having that that that having been said and only since you asked and I don't like to name names but I will um there there uh was a paper that came out of some
• 25:00 - 25:30 researchers at the flat iron Institute in New York um this is a really solid research team uh and what they were able to do was Advance a state-of-the-art on a classical computation in tensor networks and what they've been able to do is to show that for the smallest instances that we computed which we also computed classically on GPU clusters they could do it a little bit faster now they made some claims about how that undermines the results but uh not at all
• 25:30 - 26:00 I mean we computed multiple lates multiple size lates multiple Evolution time frames multiple properties on the lattice and so uh this is a very strong result it's actually been in the public domain for over a year now yeah that's terrific so so um I guess I guess the you know the question that that that uh stirred up stirred up a fair amount of of excitement uh is is really about you know what is the definition of
• 26:00 - 26:30 usefulness uh of quantum Computing and and when do we when do we when do we expect that before we answer to when do we expect that maybe we'll build up to it um you know what are some of the early applications you think uh and and we'll start back in Mel again what are some of the early applications you think that'd be worthy of uh the Endeavor of a quantum computer number one and number two you know how do you define usefulness so maybe I will start kind of at a high
• 26:30 - 27:00 level um so quantum computer is really a fundamentally new scientific and Engineering tool and if you look at a history um you know of Science and Technology whenever you come up with the new tool the first thing that you use it is to really kind of uh Advance the science and actually make scientific discoveries and in fact quantum computers literally allows us to go into corners of universe where we have never
• 27:00 - 27:30 been um and you know if you go to these Corners responsibly you always find something interesting so and um uh what um uh kind of I mean by that is that I believe there is a huge potential to use the machines which are either existing already now or kind of which are being developed in a near term to really kind of Advance this kind of scientific Frontier and actually make new discoveries there has been already
• 27:30 - 28:00 discoveries made using quantum computers but to be maximally honest there were very few and the way how many of us kind of are thinking about is that now we are in the era of this kind of quantum Discovery where we can use these machines to actually really you know mostly kind of exploring physics of complex systems maybe of you know related to things like also chemistry Material Science and um the field is now really ripe for
• 28:00 - 28:30 using these machines to kind of really make to to Really push into this kind of science directions and really start making discoveries often they are things which maybe are not necessarily directly commercially relevant you know for example understanding properties of systems away from equilibrium uh I mean a lot of world around us is not an equilibrium and
• 28:30 - 29:00 these are the kinds of things where you know I expect a lot of progress will be made within next few years and often these are the things which actually then translate to applications and often they start new Industries in a way which is not possible to predict you know and that's where I think that's why this field is in a special point right now yeah and then so that that's that's a trap iion perspective what about a super conductive it's a neutral atom proect neutal at small
• 29:00 - 29:30 differentiation so I I you know following on what you were saying I mean we I agreed with every area that you you know the fundamental premise that scientific discovery is going to be taken to a new frontier but we're seeing applications today as I said we kind of focus on what is the big problem for a customer or a partner we want to solve we seeing applications in the area of chemistry on you know how do you get to new refri meur right that have certain
• 29:30 - 30:00 sustainable properties how do you generate hydrogen from water more efficiently without needing platinum as a catalyst for the reaction uh in far in biology we looking at how peptides bind right so these are very specific instances and and doing that gives us a good way to understand two things what algorithms do you need to attack it with and then what capability you need in the machines at at a certain point in time and you
• 30:00 - 30:30 asked the question of what what is the performance standard like you know I come from a classical background you had performance per watt then you had performance per watt per dollar we're getting to a point where if you look at it through the lens of big problems you want to fundamentally solve with the figure of Merit of either solving it more accurately or solving it more accurately and with less energy and cost then we are getting to the point of what is your scale of comp computation that's usually cubits number of cubits but also
• 30:30 - 31:00 what fidelities and error rates you can sustain to make those cubits useful right I'm not saying there's a perfect ratio of those things but they're generally leading us to say how useful is your powerful quantum computer and that can only be done through the lens of looking at big problems and saying how do you solve them with the help of a quantum computer not necessarily replacing a classical computer with a quantum computer yeah Rie one of one of
• 31:00 - 31:30 the the one of the areas that I do wonder is whether Quantum Computing um is just simply poorly positioned and let me take a swing at it you know there there's a there are so many things in an industry which is built on fundamental sciences and and quantum computers in this broadest sense can be the ultimate instrument for
• 31:30 - 32:00 understanding the basic sciences that affects that industry however because it was described as an as a quantum computer instead of a Quantum instrument people have a mo a notion about what a computer is you know you should be able to run Excel super fast and and you know that you know that every every respect respectable computer should be able to run crisis the game and and so there's a there's a there's a
• 32:00 - 32:30 common sense about what a computer is and has attached to memory it's actually Network it's got storage it should be able to read and write and there's a programming model associated with the computer that I wonder I wonder if it's just a wrong wrong mental model and as a scientific instrument is extraordinary Mel as as you say and that the opportunity to understand science deeper along the way is is extraordinary but the position it as a Quantum as a
• 32:30 - 33:00 computer per se um and to hold it to the standards of a computer per se that we all understand you know what is you know I wonder if that that could be a reframing and allows allows this entire industry to be uh much further along frankly in that reframing as a as an as a scientific instrument for very important industries and go ahead yeah um I totally agree with what you said um it's some sense the word quantum computer is misleading because people
• 33:00 - 33:30 expect that you you can replace a computer classical computer with a Quantum one it's not like that it's more like very complementary we like to call our our machines like Quantum processors like very specialized machines that you can that you can use in a complex workflow alongside CPUs and gpus but really uh for specialized task and once everyone I think everyone agrees on on on on that particular uh way of using quantum computers Quantum processors um
• 33:30 - 34:00 it would be easier to work alongside classical and not not working towards replacing uh uh any all all the computer capacities that that are in place right now so so I'm actually struggling with the concept um I I don't know how to think of a quantum computer as an instrument when it's being used for materials Discovery when it's being used for blockchain when it's being used ntid do to improve cell tower resource utilization I mean it's true that there
• 34:00 - 34:30 are many applications I would never try to run on a quantum computer but for applications that require extensive processing power these machines are very powerful and I think go well beyond just instrumentation or measurement sorry I'll jump in on it's it's okay yeah I'll jump in on that I was I was actually just trying to help we we we we saw your help you you know
• 34:30 - 35:00 you know let me tell you let me tell you the M you know this this whole session is going to be like a therapy session for me it and and uh so a long time ago a long time ago um I somebody asked me so what's accelerated Computing good for and I said I said um uh a long time ago because I was wrong uh that that this is this is going to replace computers this is going to be the way computing's done
• 35:00 - 35:30 and and uh everything everything's going to be better and it turned out I was I was number one wrong and unnecessarily wrong um you know it's better to be narrowly focused on something and be extraordinarily good at it but the moment you cross that line and start talking about the traveling sales person problem then it became unnecessary because that problem is obviously being Sol solved as we know it today and Uber cars are you know taxis are
• 35:30 - 36:00 showing up you know maybe they're three 3 seconds late or 30 seconds late or whatever it is but they show up and and I I do think that that I wonder if we hold ourselves to a bar to solve a problem that is unne that's unnecessary for quantum computers to solve quite frankly to change the world and it takes it takes Focus away from something that you uniquely do and quite frankly sooner than later anyways that was just my swing at it go ahead Peter um well here at the show we actually uh have several
• 36:00 - 36:30 applications which are showing Quantum is now one of them is with Anis uh and you might know one of their products which is LS Dino and runs obviously with gpus today uh we announced that uh We've integrated our quantum computers with LSA and a 12% increase in performance in modeling a uh a blood pump and so this is the first I think the first time actually Quantum with production software we also
• 36:30 - 37:00 announced with Nvidia AWS and Asen a 20x Improvement in a chemistry application what's amazing about it is that we did that on 36 cubits our existing system today by the end of the year we will have 64 cubits every time you add a cubit you double the computational power so that's 2 to the 28 increase in a single generation of Chip which is
• 37:00 - 37:30 roughly 260 million times more powerful so by the end of the year one would expect for things like LSD and for chemistry applications to suddenly have huge performance increases and so we're working right now on these applications which to be honest probably all of you use to now be able to have significant impact using a quantum computer um I do think that your statement about 10 years
• 37:30 - 38:00 is um we think of ourselves as like 10 years where you were 10 years ago we hope that obviously 10 years from now we'll be up there with uh Nvidia as well in a rare flly uh Club so but it it does take a long time to go from um you know kind of a startup to where you are today and it's it's completely fine to sit down and say for the computer industry for the quantum industry it's going to be another 10 to 15 years to get to
• 38:00 - 38:30 where Nvidia and all the other Giants are it's just not going to start then it's going to start it's starting today you're going to be much much larger than Nvidia there's no we're we're we're going to be a relic of the past all right so so if if um it seems like there one of the things that's really interesting is that that um there are so many different approaches to Quantum computing and and it's it is uh uh so diverse in
• 38:30 - 39:00 its approaches uh why is it that this industry doesn't doesn't quickly discover a more promising approach uh as you see each other's work and naturally you know through Evolution uh people select the best approach and then everybody started to advance the old the whole industry in a unified way uh much more quickly you know as I observe this industry it's It's s surprisingly diverse and and there's thousands of
• 39:00 - 39:30 flowers blooming uh you know when does it become a garden I'll just I'll just say on actually if you look across us today there's a number of people you heard are using individual atoms lasers and all the rest and so we actually have more commonality than most people expect often and so I would think that um uh I would hope that in the future that there is more sharing and maybe even the
• 39:30 - 40:00 ability to work together because the promise of quantum Computing and what it can do for mankind is so significant it's actually larger than any one of the companies that are here sitting on stage today and so um you know I think that that mankind has a whole range of significant problems to be worked out and we need Quantum Computing to be able to solve it so um it is we're still obviously new ways to be able to build
• 40:00 - 40:30 cubits are being found every day but I think that over the next couple of years we will start to coals to probably two maybe three different approaches um and some of us will probably come together because we do share basically the the underlying technology and so it makes and many of the problems that you you've described I I the the uh the precise answer is not exactly known because as you know is fluids are quite chaotic and and um hard
• 40:30 - 41:00 to know exactly what the right answer is and in those kind of examples uh using AI for emulation can give you you know tens of thousands of X speed up orders of magnitude speed up from where we are today with principal solvers how do you guys think through that how what is the what is the point of solving that problem when when um classical still has orders of magnitude of progress in the next couple years ahead of it well there's always a magnitude of progress but at the same time there are
• 41:00 - 41:30 problems that are just you know impossible to solve classically today um you know there are problems in the area of drug Discovery there are problems in the area of global weather modeling but even just the application that I shared um which is the basis of our paper a week ago which is Computing properties of materials you know we use Frontier which is basically one of your systems massively parallel supercomputer at
• 41:30 - 42:00 Oakridge National Lab and would take millions of years to perform the computation so the point is there are still hard computational problems that are out of the reach of classical and AI isn't going to address those problems either they're just out of the reach of classical right exactly go ahead reie so I'd like to make yeah go ahead go ahead actually it's interesting that it took us 30 minutes to get to AI but from our point of view where we see it um quite interestingly is and it's an extension
• 42:00 - 42:30 to your question on whether we should call it a computer or not is you these Quantum devices or tools or instruments as you call them are expanding the ability for us to access data to train these AI engines that previously was not possible so if you're going to solve a chemistry problem today humankind's Max ability is defined by things like density function Theory or other approximations to the quantum
• 42:30 - 43:00 space the world of that information that we haven't had that's like to me trying to train autonomous vehicles by giving them City grids of you know 500 ft squared and not having the detail of lens or other things so what we see is this concept of you know computer brings in I have a computer a versus a computer B so a must run the thing faster than b for it to be better at least technically till you tell them what the price of the
• 43:00 - 43:30 a is we don't see it that way we see it as What Can A and B do if a is established classical you know wellon Frontier models how are we training those models and are we enabling those models with the data so it can now continue to be agentic and continue to reason and continue to do things that otherwise we'd be pulled in back to do right and we call that gen not AI gen Q Ai and that's kind of breaks the Paradigm of a computer compute competing
• 43:30 - 44:00 with another computer it's two computers now working together two completely different ways but they are input output for each other you're the output of the quantum computer is the input into these llms and the training methodologies so you can have llms that actually understand things like ground state energy and ground state configurations of of molecules so you can then use them to start doing perturbation theory on well is this molecule going to last
• 44:00 - 44:30 inside my body and deliver the drug at the right kinetic you know Paradigm or not so that is how we see Quantum as an addition of a tool or an instrument into what is already a developing and rapidly maturing and improving compute parad in the few minutes we have we have here uh what are the things that we could do in in the world of Accel classical uh to be helpful to all of you
• 44:30 - 45:00 so that we could Advance your work much more rapidly can we U yeah so maybe I will start or yeah can can we how about we start with in the Middle come on Mr French man let's go yeah thank you um yeah I guess um it's it's very important as as as was as was said earlier to um to to couple uh as best as possible uh the the various uh compute modalities like classical and
• 45:00 - 45:30 and Quantum for the moment it's not really a matter of bandwidth or really being able to collocate to be able to do things fast because we're not there yet uh it's not the the pressing paradig at at some point it will be a problem but not now now it's really about uh ident identifying the key uh problems the key uh domains on which we we we can uh collaborate and Leverage The Best of Both words um and I I fully agree with what you said about uh actually um using a quantum computer a Quantum processor
• 45:30 - 46:00 to uh process and to create data on a problem which is in itself Quantum that classical uh struggles with naturally and then use that Advantage natural Advantage uh in a workflow that is larger with the with the CPUs and gpus and couple that um uh quite well at the software level MH mhm I I was just going to say we use use um your gpus to design our chips to
• 46:00 - 46:30 often do co- simulation to make sure that the quantum computers are working it's a um when we look to the Future for uh Quantum Computing it's going to be a set of classical systems sitting right next to a quantum computer and the two of them are going back and forth and so it isn't something where one is replacing the other they're working together and then if you look at this the same things that are doing today you know we're applying machine learning to
• 46:30 - 47:00 be able to figure out how to build optimization not only for the quantum computers itself and how they run so it is already a synergistic relationship between classical Computing and and the strange thing is our quantum computers are almost entirely classical right the only Quantum part happens to be a little chip and a couple of atoms at the center the rest of it is entirely classical so um it isn't going to replace um I
• 47:00 - 47:30 wouldn't short any Nvidia stock at the end of this so um so I think you have a a strong strong physici going forward um but I would expect that in the future it will be a qpu a GPU and a CPU all working together to be able to Sol in fact if I I just if I could just add add a little something there I think the um so so first of all you probably observe that that that Nvidia accelerated Computing is uh the largest volume
• 47:30 - 48:00 parallel computer the world's ever seen and yet we don't call it a parallel computer um for that very reason a long time ago there was an industry called parallel computers parallel Computing and it was opposed to sequential Computing and and the mistake of that approach the mistake of that positioning is in fact you know amd's law doesn't work that way and and there's no reason to replace something that does an incredibly good job you should add to it and ride the wave ride
• 48:00 - 48:30 ride the wave of the in the the momentum that's been created for it and and so that's why we decided to call it an accelerated Computing um but it's still a computer and and uh uh and that really revolutionized how people thought about us and how we thought about ourselves and how we thought about our work and and I think the idea that this is a Quantum Computing industry or a quantum computer is less good than a Quantum processor that's going to make every computer better and and so I um anyhow
• 48:30 - 49:00 go ahead go ahead reie uh excuse me I was going to say that some of the paradigms have to change in the way we are thinking about Quantum processing or Quantum Computing some people have observed that think of a human brain and how it works and that's closer to a quantum computer than our conventional thinking of HPC and how HPC should be integrating with quantum computers we are dealing with analog inputs we are dealing with analog outputs we are dealing with simultaneous multiple
• 49:00 - 49:30 variables at the same time exactly like the way human brain and our neurons work so fundamentally we may be limiting ourselves by thinking of quantum Computing in the context of classical Computing and may have to start thinking broader and say what are the kinds of things we could potentially Envision when a quantum computer is brought in conjunction with HPC and and to your question how can we accelerate Quantum Computing development with HP SE at the same time how can Quantum Computing help
• 49:30 - 50:00 gen get to AGI those are the some of the trickier things that we could use quantum computer for yeah well this is this is going to be the beginning of a of a great conversation for the industry and and uh it's a great pleasure for for me to host all of you and this is just the first of many many in our series and and I'm looking forward to to uh Mikel wants to finish you yes yeah go ahead finish yeah so I think it's um these are all great examples and um I want to go
• 50:00 - 50:30 back to kind of the point I made before and so basically quantum computer in a sense of like computation is not a hammer it's like a scalpel and what it's a Precision instrument and what you basically want to do with that and it is it's kind of our vision if you really want to realize you know large scale useful applications you have to think about this um entire problem as a kind of code design where
• 50:30 - 51:00 if you have a problem you want to solve you want to basically solve as much as possible with the classical computers and identify hard Quantum part and then you know find an algorithm find a good error correcting code find the right compiler find the right decoder and it all has to be optimized with the specific architecture you know Quantum architecture in mind and and in all of this process what you want to do you want to basically Outsource as much as
• 51:00 - 51:30 possible at least at this time to a classical uh part and this could be CPUs gpus depending on what you want to do and of course at the end you want to use an output of the quantum data indeed to train your models and and and improve them that's how we how we see the real value of quantum computers emerging in the next you know couple productive use case yeah thank you
• 51:30 - 52:00 guys okay how about how about we just have we just have to be very quick next year this time what are we going to be talking about and so so let's just quickly go through go ahead Alan next year this time what what do you hope that we're talking about so I remember it h how how Quantum is helping you to do met better model training and inference with lower power consumption okay go ahead Peter um first uh Quantum applications in production helping
• 52:00 - 52:30 customers taking workloads and I hope that we'll see kind of along the same lines the first prototypes of a new kind of AGI based on Quantum L uh talking about the learnings um uh that we got from all the usage uh all the computers the processors that are being deployed uh today in the field mhm yeah Rim I I agree with with uh the previous speakers theme on we will see in the
• 52:30 - 53:00 next year first real tangible use cases of an AI agent working with in conjunction with a quantum computer doing things it couldn't have otherwise done before are are done with tremendous amount of trial and error MH okay sub I hope a year from now we are at a point where there's a little less skepticism about Quantum Computing and we start talking about how exactly will it be valuable in a Data Center and we can
• 53:00 - 53:30 show some real life cases mhm MH go it'll be different so I what I want to see is 10 new scientific discoveries in physics chemistry and biology and maybe other uh areas which would be delivered by the quantum well guys let's go make it happen all right guys thank you thank you thank you all right our second panel our second
• 53:30 - 54:00 panel thank you thank you guys either way either way don't worry yep no worry don't worry okay our second our second thank you thank you very much Rie