3006: IBM Qiskit and the Road to Quantum Advantage

[00:00:03] [SPEAKER_01]: Have you ever wondered how quantum computing could revolutionize industries by solving complex

[00:00:10] [SPEAKER_01]: problems faster than traditional computers? Well today I'm diving into the heart of quantum

[00:00:17] [SPEAKER_01]: innovation with my guest Blake Johnson. And he's the quantum engine lead for IBM Quantum

[00:00:24] [SPEAKER_01]: and together today we're going to explore the significant expansion of Qiskit. And it's

[00:00:31] [SPEAKER_01]: now engineered to harness the full potential of quantum hardware. From its evolution over

[00:00:36] [SPEAKER_01]: seven years to the introduction of AI powered tools and new features all aimed at simplifying

[00:00:42] [SPEAKER_01]: quantum computing, I've invited Blake to join me on the podcast and share how these advancements

[00:00:48] [SPEAKER_01]: are positioning IBM to achieve that elusive quantum advantage. But the big question is

[00:00:55] [SPEAKER_01]: how close are we to truly integrating quantum solutions into everyday business applications?

[00:01:02] [SPEAKER_01]: Well let's find out.

[00:01:03] [SPEAKER_01]: Delivering daily content to 140,000 of you wonderful monthly listeners across the globe

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[00:02:01] [SPEAKER_01]: moderate authorised. Thank you for your patience today. This is the moment you've

[00:02:05] [SPEAKER_01]: been waiting for. It's time to welcome my guest onto the show.

[00:02:09] [SPEAKER_01]: So buckle up and hold on tight as I beam your ears all the way to New York where Blake Johnson

[00:02:15] [SPEAKER_01]: is waiting to talk with us today. So a massive warm welcome to the show, Blake. Can you tell

[00:02:21] [SPEAKER_01]: everyone listening a little about who you are and what you do?

[00:02:25] [SPEAKER_00]: So I'm Blake Johnson. I was trained as a physicist, but I've spent the last 20 years of my

[00:02:29] [SPEAKER_00]: career working to build con computers and make them reality. Today I'm an engineering

[00:02:34] [SPEAKER_00]: lead at IBM Quantum and our program is large, but the particular slice of that program that

[00:02:40] [SPEAKER_00]: I'm accountable for is something we call the quantum engine, which encompasses like the

[00:02:43] [SPEAKER_00]: software systems that execute queries on IBM's quantum computers.

[00:02:48] [SPEAKER_01]: Fantastic. Well, it's a pleasure to have you on here. Every day I try and take a different

[00:02:52] [SPEAKER_01]: topic and demystify it for listeners putting the language everyone can understand and

[00:02:57] [SPEAKER_01]: you're working on is it quiz kit at the moment or kids? How do you pronounce

[00:03:00] [SPEAKER_00]: that? Yeah, sure. The everlasting debate about the pronunciation. Either is fine. We actually

[00:03:05] [SPEAKER_00]: had at our team one summer to kind of celebrate the different pronunciations made t-shirts with

[00:03:11] [SPEAKER_00]: the two different common pronunciations and people got to choose their pronunciation

[00:03:15] [SPEAKER_00]: that they preferred and had it like in a dictionary like phonetic spelling of quiz

[00:03:19] [SPEAKER_01]: kit or quiz kit. And inside IBM was the preferred pronunciation there?

[00:03:24] [SPEAKER_00]: Really you find both. I say quiz kit so we can stick with that one for today.

[00:03:28] [SPEAKER_01]: Quiz kit is an open source software development kit for working quantum computers at the level

[00:03:35] [SPEAKER_01]: of circuits, pulses and algorithms. So we're going to geek out a little bit today. But

[00:03:38] [SPEAKER_01]: just to set the scene, can you give me a bit of an overview of the recent expansion you've had

[00:03:43] [SPEAKER_01]: and also exactly what it is and how you're enhancing the performance of real quantum hardware?

[00:03:49] [SPEAKER_00]: Yeah, great. So maybe a little bit of background to help set the scene, right? So the

[00:03:53] [SPEAKER_00]: fundamental unit of computation on a quantum computer is a quantum circuit, which is a sequence

[00:03:58] [SPEAKER_00]: of logical operations performed on quantum bits or qubits of a quantum computer. And the kind

[00:04:04] [SPEAKER_00]: of the core element of quiz kit, the quiz kit SDK is a Python firmware for building,

[00:04:08] [SPEAKER_00]: optimizing, executing those quantum circuits. The SDK has gotten really quite good over

[00:04:13] [SPEAKER_00]: the past seven years so much so that we were finally willing to kind of give it the label

[00:04:17] [SPEAKER_00]: of 1.0 in a quiz kit SDK release this past March. So and that represents a certain level of maturity,

[00:04:25] [SPEAKER_00]: stability, but it also represents its performance, right? It's 16 times faster transpiling in terms

[00:04:30] [SPEAKER_00]: of third of the amount of memory and produces better circuits than ever before. So a quiz kit

[00:04:34] [SPEAKER_00]: SDK has really kind of come of age. But we've also been learning over these years about

[00:04:39] [SPEAKER_00]: effective patterns for applying quantum computing to problems. And users need sort of a richer

[00:04:44] [SPEAKER_00]: collection of tools to aid them on their journey of mapping problems to quantum circuits, optimizing

[00:04:48] [SPEAKER_00]: those circuits for execution, executing them on quantum hardware and finally post processing

[00:04:53] [SPEAKER_00]: the results back into their like problem domain, the problem they're trying to solve.

[00:04:57] [SPEAKER_00]: So two years ago, we made kind of the first step of sort of enriching the kids get family

[00:05:01] [SPEAKER_00]: by introducing the kids get runtime, which introduce primitives computational primitives

[00:05:07] [SPEAKER_00]: that kind of encapsulate common queries to quantum hardware, or things like sampling

[00:05:11] [SPEAKER_00]: from quantum circuits or estimating properties of the output of circuits. And this year, we

[00:05:16] [SPEAKER_00]: move on another step further introducing new tools and services that apply artificial

[00:05:20] [SPEAKER_00]: intelligence to quantum. For instance, we now have the kids get transpiler service that brings

[00:05:25] [SPEAKER_00]: a novel set of methods for optimizing circuits. And the kids get code assistant, which brings

[00:05:29] [SPEAKER_00]: generative AI into your development environment to help you write modern a kiss get code.

[00:05:35] [SPEAKER_00]: And finally, we have the kiss get serverless tool, which allows users to combine

[00:05:39] [SPEAKER_00]: quantum and classical computing resources into kind of seamless workflows to explore even

[00:05:45] [SPEAKER_00]: richer set of possibilities of workflows. And there has been tremendous interest in

[00:05:51] [SPEAKER_01]: and progress in AI and quantum computing. But I think it's important to highlight that

[00:05:56] [SPEAKER_01]: kiss get has been around for many, many years. And over the past seven years,

[00:06:01] [SPEAKER_01]: it has evolved significantly. So I'm curious what are some of the key milestones and

[00:06:06] [SPEAKER_01]: advancements that have brought it to its current state because it's not an overnight success story,

[00:06:11] [SPEAKER_00]: is it? No, for sure. We've been working on this for a while. So I mean, back in 2017,

[00:06:16] [SPEAKER_00]: it was more or less just a circuit building tool. It wasn't until the next year in 2018

[00:06:20] [SPEAKER_00]: that we introduced a transpiler to kiss get so transpiler is a kind of compiler

[00:06:26] [SPEAKER_00]: that transforms circuits to circuits. So the input and output formats are kind of

[00:06:31] [SPEAKER_00]: in the same representation. But along the way it optimizes them,

[00:06:34] [SPEAKER_00]: optimizes those circuits and it puts them in a form which kind of conforms to the instruction set

[00:06:39] [SPEAKER_00]: of the hardware that the quantum hardware that we're trying to target. So that was a major advance

[00:06:44] [SPEAKER_00]: for the kind of the scope of kiss get. In 2021, we introduced the kiss get runtime,

[00:06:49] [SPEAKER_00]: which I just briefly introduced and as this sort of managed performance experience for the

[00:06:55] [SPEAKER_00]: execution part of the kind of workflow using quantum systems. And we used it to show a

[00:07:02] [SPEAKER_00]: significant speed up in a variational algorithm which makes sort of repeated or iterative use

[00:07:07] [SPEAKER_00]: of a quantum computer. And in 2020, we started a project to really reinvent the performance

[00:07:13] [SPEAKER_00]: of kiss get. And what we had in mind, right, kiss get started, kiss get SDK started out as a

[00:07:18] [SPEAKER_00]: Python pure Python library. But we started to kind of reinvent the kiss get SDK as a

[00:07:27] [SPEAKER_00]: Rust library, which is a Rust systems programming high performance systems programming language

[00:07:32] [SPEAKER_00]: to make kiss get SDK kind of in 100% Rust core with just a thin Python interface to it.

[00:07:38] [SPEAKER_00]: And that project was sort of well underway and some of those advances are already present

[00:07:44] [SPEAKER_00]: in the kiss get SDK 1.0. But we really intend to complete that project with the kiss get

[00:07:49] [SPEAKER_00]: SDK 2.0, which will be released early next year.

[00:07:53] [SPEAKER_01]: Incredibly exciting times for you all there. And the concept of quantum advantage is also

[00:07:58] [SPEAKER_01]: something that is crucial in quantum computing. So how does the expansion of kiss get bring us

[00:08:04] [SPEAKER_01]: closer to achieving quantum advantage? I know it's something that the tech community is

[00:08:08] [SPEAKER_01]: incredibly passionate about we have to be careful what we say here, but how close do we

[00:08:13] [SPEAKER_01]: do you think we are close to achieving this?

[00:08:15] [SPEAKER_00]: I think we've set the sort of necessary we set the stage who created some of the

[00:08:19] [SPEAKER_00]: preconditions for it to be possible within the next few years.

[00:08:23] [SPEAKER_00]: I guess just to be clear for our listeners, right? Quantum advantage is when you can do

[00:08:27] [SPEAKER_00]: some computation better faster cheaper than with a quantum computer than with any known

[00:08:31] [SPEAKER_00]: classical counterpart. There's a kind of a precursor to advantage which we think is also

[00:08:37] [SPEAKER_00]: important. It's kind of a necessary but not sufficient ingredient, which is something

[00:08:41] [SPEAKER_00]: that we've been labeling utility. Quantum utility is when your quantum computer finally

[00:08:46] [SPEAKER_00]: is better at being a quantum computer than a classical simulator, which kind of is obviously

[00:08:53] [SPEAKER_00]: a necessary thing for advantage because if you could just use a simulator or quantum simulator

[00:08:57] [SPEAKER_00]: instead, then you wouldn't need the quantum hardware. The simulation approach would

[00:09:04] [SPEAKER_00]: provide the right or best computational approach. So our quantum hardware needs to at

[00:09:10] [SPEAKER_00]: least be better than we can simulate quantum hardware. And we made the kind of the first

[00:09:14] [SPEAKER_00]: we showed the first evidence that was possible with near term quantum computers in a result that

[00:09:19] [SPEAKER_00]: we published in the magazine Nature last summer. And so we're kind of with that, we finally stepped

[00:09:26] [SPEAKER_00]: into this age of utility scale, quantum computing and the kids get SDK sort of needs to support

[00:09:32] [SPEAKER_00]: this new era of utility scale quantum. And what that means is that we need to be able to

[00:09:37] [SPEAKER_00]: it kind of has two parts. We need to be able to build and optimize circuits at utility scale

[00:09:42] [SPEAKER_00]: and sort of this the scale, which is beyond our capability to simulate the action of the

[00:09:47] [SPEAKER_00]: quantum computer. And we need a runtime environment, which we have with the kids get runtime that can

[00:09:52] [SPEAKER_00]: sort of augment the capabilities of the quantum hardware with error mitigation,

[00:09:58] [SPEAKER_00]: which are techniques that sort of take advantage of multiple executions of a quantum circuit and

[00:10:03] [SPEAKER_00]: post processing to sort of remove some of the effects of errors that can occur in

[00:10:10] [SPEAKER_00]: quantum systems. And that's important because it allows us to work at larger scales, execute

[00:10:14] [SPEAKER_00]: larger circuits and get accurate results kind of in this era before the introduction with

[00:10:20] [SPEAKER_00]: the widespread use of quantum error correction in the quantum systems.

[00:10:23] [SPEAKER_01]: And I was also reading before you came on the podcast today that Kiske now includes

[00:10:28] [SPEAKER_01]: features to easily interface with quantum systems and abstract away infrastructure. So

[00:10:34] [SPEAKER_01]: just for everyone listening here, how does this simplify the use of quantum computing,

[00:10:38] [SPEAKER_01]: especially for developers and researchers, etc. Right. So I mean, in this really comes

[00:10:45] [SPEAKER_00]: through to the user in the form of computational primitives. So like we've now with seven years

[00:10:51] [SPEAKER_00]: of experience of with Kiske, we saw many patterns emerge as people develop a use cases and

[00:10:58] [SPEAKER_00]: applications using it. And we took some of those most common patterns and wrap them up into

[00:11:03] [SPEAKER_00]: primitives that could be reused, which saves the developer a lot of time. And because it removes

[00:11:10] [SPEAKER_00]: a bunch of work that they don't have to do. But it's also important like we've sort of moved up

[00:11:16] [SPEAKER_00]: the abstraction hierarchy, it's slightly more abstract than just execute this circuit.

[00:11:20] [SPEAKER_00]: We have a task that's a bit more involved. And that sort of gives us freedom from some

[00:11:25] [SPEAKER_00]: execution perspective to introduce things like the error, error mitigation technology that I

[00:11:32] [SPEAKER_00]: just mentioned to suppress the or to remove the effects of errors in certain kinds of circuits.

[00:11:39] [SPEAKER_01]: And I think combining the strengths of classical and quantum resources seems to be a

[00:11:44] [SPEAKER_01]: key feature of the new Kiske. So can you elaborate on this and also how this hybrid

[00:11:50] [SPEAKER_01]: approach works and some of the benefits that we can expect from this?

[00:11:55] [SPEAKER_00]: Sure. So the tool that we have in this new Kiske stack that enables this is something

[00:12:00] [SPEAKER_00]: called Kiske Serverless. At IBM were big believers in the concept of hybrid cloud,

[00:12:07] [SPEAKER_00]: which is the idea of enterprises and compute users in general have sort of moved from

[00:12:14] [SPEAKER_00]: one generation of completely local or on-premises computing. They then had the advent of cloud

[00:12:20] [SPEAKER_00]: computing where they have access to even flexible infrastructure in a remote location.

[00:12:24] [SPEAKER_00]: But enterprises and researchers have often struggled with the fact that their data is maybe

[00:12:30] [SPEAKER_00]: local and their compute resources is remote. And even just getting the data to their compute

[00:12:35] [SPEAKER_00]: is a hard task. And so the general concept of hybrid cloud is to bring your data in

[00:12:41] [SPEAKER_00]: your compute and to the place where it makes sense for your workflow. And so then you see

[00:12:45] [SPEAKER_00]: things like edge computing, local clusters, and computing models which allow you to mix and

[00:12:50] [SPEAKER_00]: match or assemble the compute resource that is sort of the most appropriate for your task.

[00:12:57] [SPEAKER_00]: And so Kiske Serverless exists in this kind of conceptual framework of the hybrid cloud where

[00:13:04] [SPEAKER_00]: you can assemble the kind of the compute infrastructure that makes sense for your workload,

[00:13:11] [SPEAKER_00]: whether that's a local compute cluster that you have in your research institute or enterprise

[00:13:17] [SPEAKER_00]: with a quantum resource that we have. And so it both has sort of tooling that makes it

[00:13:22] [SPEAKER_00]: possible to assemble those things and then for the developer make it very straightforward to kind of

[00:13:27] [SPEAKER_00]: mark up the code of sort of how that resource should be consumed to splitting the problem on

[00:13:33] [SPEAKER_00]: the quantum and classical. So there's kind of one aspect of it which is about kind of the

[00:13:36] [SPEAKER_00]: infrastructure concerns about creating these hybrid quantum and classical computing resources.

[00:13:42] [SPEAKER_00]: But the kind of for us, the kind of the reason we're doing it isn't just that we believe in that as

[00:13:49] [SPEAKER_00]: sort of a useful computing model. We also see the possibility to extend the power of

[00:13:55] [SPEAKER_00]: quantum computing by making these combinations. There is a sort of a new family of techniques

[00:14:00] [SPEAKER_00]: that we generally label as circuit knitting which are ways that can kind of split up the problem

[00:14:07] [SPEAKER_00]: either in sort of the problem description layer or in the description of those quantum circuits

[00:14:11] [SPEAKER_00]: themselves and address part of the problem with the classical computing technique and part of the

[00:14:17] [SPEAKER_00]: problem with a quantum computing technique and to be able to combine that the two that you can

[00:14:21] [SPEAKER_00]: do computations that you couldn't do with those computing paradigms in isolation.

[00:14:27] [SPEAKER_01]: And I said a few moments ago, there's an incredibly passionate community out there and I was

[00:14:31] [SPEAKER_01]: reading that there's a global quantum ecosystem of more than 600,000 users. So

[00:14:37] [SPEAKER_01]: how does IBM foster collaboration and innovation within this community to

[00:14:42] [SPEAKER_01]: together help advance quantum computing? I would imagine this is something that

[00:14:46] [SPEAKER_00]: you're passionate about too, right? Oh for sure. And it happens in several different ways,

[00:14:52] [SPEAKER_00]: some of which are kind of more structured, some of which are more organic,

[00:14:56] [SPEAKER_00]: kind of more on the structured side we have our IBM quantum network which now has over

[00:15:00] [SPEAKER_00]: 300 members that include enterprises, startups, research institutions, governments,

[00:15:04] [SPEAKER_00]: universities and so forth. And we host IBM hosts kind of regional events for quantum network members

[00:15:10] [SPEAKER_00]: in the US, Europe. We had our first one in South America earlier this year.

[00:15:16] [SPEAKER_00]: And those events really their primary purpose is to bring network members together to create

[00:15:21] [SPEAKER_00]: a sort of network effect where they can collaborate and learn from each other.

[00:15:27] [SPEAKER_00]: Part of that network includes working groups that we organize to work with

[00:15:32] [SPEAKER_00]: network members on application area, on specific application domains in this

[00:15:37] [SPEAKER_00]: sort of utilities, health quantum era. So we have one on healthcare and life sciences,

[00:15:41] [SPEAKER_00]: one on optimization, quantum assimilation materials and so forth. So there's

[00:15:44] [SPEAKER_00]: that's kind of the structured side. On the more organic side we also have a growing

[00:15:49] [SPEAKER_00]: network of what we call Kisket advocates. There's over 500 Kisket advocates now in over

[00:15:54] [SPEAKER_00]: 50 countries. And the Kisket advocates often organize sort of local events in their

[00:15:59] [SPEAKER_00]: communities like camps, hackathons and so on. Other enthusiasts get them together to kind of

[00:16:05] [SPEAKER_00]: share their passion and work together in a focused way on quantum computing projects.

[00:16:10] [SPEAKER_01]: But I'm not sure how much you will be able to share with me but looking ahead what are

[00:16:14] [SPEAKER_01]: IBM's visions for the future of quantum software? And again how do you see the role of Kisket

[00:16:19] [SPEAKER_01]: and its users evolving in this pursuit of useful quantum computing where we're solving real

[00:16:25] [SPEAKER_00]: world problems? So I think actually we can say more than maybe some others because we've

[00:16:29] [SPEAKER_00]: been very public about kind of forecasting where we're going, right? So we started this practice

[00:16:34] [SPEAKER_00]: of producing a roadmap back in I think 2019. And we've updated ever since our latest version

[00:16:41] [SPEAKER_00]: of that actually has a 10 year view projecting out to 2033. So you can see where we're trying

[00:16:47] [SPEAKER_00]: to go from both a sort of systems perspective, what the computer fundamental compute

[00:16:52] [SPEAKER_00]: resource that we're trying to build and then the layers that we want to build on top of it.

[00:16:56] [SPEAKER_00]: And if you look at that roadmap, what you'll notice is that we've put the focus on

[00:17:04] [SPEAKER_00]: the size of circuits that users can, at the foundational level, the size of circuits that

[00:17:10] [SPEAKER_00]: can reliably execute on the quantum hardware. And that roadmap includes a kind of a transition

[00:17:15] [SPEAKER_00]: point from this current era of error mitigation to an era of fault tolerance or error correction

[00:17:22] [SPEAKER_00]: starting in 2029. And so one of the things that we need from kind of the base level of our

[00:17:29] [SPEAKER_00]: software stack, the kind of the engine right that I'm responsible for is to continue to evolve

[00:17:35] [SPEAKER_00]: the systems to be able to scale up to these larger and larger circuits and to manage this

[00:17:40] [SPEAKER_00]: transition from error mitigation default tolerance in a way that we desire it to be

[00:17:45] [SPEAKER_00]: actually in some sense transparent to use the user, right? Like that what you notice is

[00:17:50] [SPEAKER_00]: simply that you can run larger circuits that you're not sort of intimately fusing over the

[00:17:55] [SPEAKER_00]: details of how that capability is delivered. But then we also need to sort of grow up the kind

[00:18:00] [SPEAKER_00]: of a platform and application layers on top of that foundation together with users and ecosystem

[00:18:06] [SPEAKER_00]: partners so they can be able to explore application domains informing like how what

[00:18:11] [SPEAKER_00]: patterns actually lead to quantum advantage, and then be able to sort of deliver that

[00:18:16] [SPEAKER_00]: capability to users through application layers and application libraries that kind of work on

[00:18:21] [SPEAKER_00]: top of our platform. Sort of like the big picture of vision though, right, is that we

[00:18:26] [SPEAKER_00]: want kids get to be the fabric that sort of enables scale increasing scale and sophistication

[00:18:32] [SPEAKER_00]: and that eventually like we use together classical computing resources into

[00:18:36] [SPEAKER_01]: a new paradigm of high performance computing. Wow, so much excitement on the road ahead there

[00:18:43] [SPEAKER_01]: and before I let you go, I want to have a little bit of fun with you. We've geeked out a

[00:18:46] [SPEAKER_01]: little today but I also asked my guests if there's a book that they recommend that we can add to our

[00:18:51] [SPEAKER_01]: Amazon wish list or a song that we can add to a Spotify playlist. All I'm going to ask is which

[00:18:57] [SPEAKER_01]: would you like to leave everyone listening with and why? Oh wow, I love asking this question

[00:19:03] [SPEAKER_01]: because you can talk about quantum computing and so many complex subjects ask you a book

[00:19:08] [SPEAKER_00]: or a song but that's the tricky stuff, right? Yeah, so I just read this biography of Albert

[00:19:15] [SPEAKER_00]: Einstein by Isaacson which I found absolutely fascinating. I imagine many of your listeners

[00:19:21] [SPEAKER_00]: have encountered already but if not it's well worth reading. It's a hefty book, it's quite a

[00:19:26] [SPEAKER_00]: few pages but his story is fascinating and in many ways surprising and so particularly for me

[00:19:32] [SPEAKER_00]: as a scientist, I think he's a fascinating character and particularly one in which he's

[00:19:39] [SPEAKER_00]: obviously very celebrated but also kind of curiously flawed as well and so his story is

[00:19:45] [SPEAKER_00]: really curious and entertaining. What's the title of the book again? I'll get that added

[00:19:49] [SPEAKER_00]: straight to our Amazon wish list. Einstein, His Life in Universe by Walter Isaacson.

[00:19:54] [SPEAKER_01]: Perfect, I'll get that added straight to the Amazon wish list and for everyone listening,

[00:19:59] [SPEAKER_01]: especially if the part of that quantum computing and they want to find out more,

[00:20:02] [SPEAKER_01]: maybe contact you or your team or just dig a little bit deeper on the subject and explore it

[00:20:07] [SPEAKER_01]: some more. Where would you like to point everyone listening? Find out more.

[00:20:10] [SPEAKER_00]: IBM.com.com slash quantum. We also have our quantum computing platform is quantum.ibm.com

[00:20:16] [SPEAKER_00]: and there's in particular, listeners may find that we have a wealth of learning content,

[00:20:22] [SPEAKER_00]: courses, YouTube videos, tutorials, like there is a massive amount of content and is super

[00:20:28] [SPEAKER_00]: high quality. So you can find that at learning.quantum.ibm.com. I will get all those links added to

[00:20:35] [SPEAKER_01]: the blog post associated with this podcast and share that far and wide just to make it easier for

[00:20:40] [SPEAKER_01]: people to get their hands on that information, take a look around. And more than anything,

[00:20:44] [SPEAKER_01]: just thank you for sharing your insights with me today about quantum computing, how the expansion

[00:20:49] [SPEAKER_01]: of Kiske is bringing us that little step closer to achieving quantum advantage, a topic that

[00:20:54] [SPEAKER_01]: we could talk about entirely on another episode on its own. But just thank you for your time today,

[00:20:59] [SPEAKER_01]: really appreciate it. Yeah, my pleasure. Thank you. So a huge thank you to Blake for that enlightening

[00:21:04] [SPEAKER_01]: conversation around the transformative capabilities of quantum computing and the pivotal role

[00:21:11] [SPEAKER_01]: of Kiske in pushing the boundaries of what's possible. And it's clear that as that becomes

[00:21:16] [SPEAKER_01]: more robust, the quantum ecosystem will continue to expand bringing us closer to

[00:21:22] [SPEAKER_01]: realizing quantum advantage. And I know me saying that out loud will excite and frustrate listeners

[00:21:28] [SPEAKER_01]: in equal measure, it's a very passionate community. And for the right reasons too.

[00:21:32] [SPEAKER_01]: So over to you, this isn't about me or today's guests, what potential impacts

[00:21:36] [SPEAKER_01]: do you think quantum computing will have in your field? Have you thought about how

[00:21:42] [SPEAKER_01]: quantum advancements might alter your approach to technology and solving problems?

[00:21:47] [SPEAKER_01]: I'd love to hear your thoughts on this and maybe some of your predictions too. So please keep the

[00:21:53] [SPEAKER_01]: conversation going by messaging me at LinkedIn at neil c Hughes or email me tech blog writer outlook.com.

[00:22:01] [SPEAKER_01]: But that's it for today. So thank you for listening as always, keep your questions,

[00:22:05] [SPEAKER_01]: comments and emails coming in. And I'll be waiting to talk with you all again tomorrow

[00:22:10] [SPEAKER_01]: morning. Speak with you all then.