WEBVTT
00:00:05.839 --> 00:00:07.599
Welcome to Unleashing Genius.
00:00:07.679 --> 00:00:10.560
I'm Gaby Boko, the Chief Marketing Officer at NetUp.
00:00:10.720 --> 00:00:19.039
If you've been here before, then you know that this series explores the ideas, trends, and technology shifts that are shaping how organizations innovate and grow.
00:00:19.280 --> 00:00:27.760
Throughout history, discovery has often been dependent on access, access to information and expertise, access to tools.
00:00:28.079 --> 00:00:38.159
Today, some of the most important discoveries depend on access to something else: computing power, data and the ability to work with both at scale.
00:00:38.479 --> 00:00:48.799
Universities are playing a fascinating role in that shift, acting not only as places of learning, but also as engines of research, experimentation, and also innovation.
00:00:49.039 --> 00:00:59.520
The Technical University of Coshita is one of the institutions helping shape that future through its investment in high-performance computing, AI research, and advanced data infrastructure.
00:00:59.759 --> 00:01:09.359
Joining me today is Martin Hevria, head of the Department of Computer Networks and Operating Systems at the University and one of the leaders behind the Perun supercomputing environment.
00:01:09.680 --> 00:01:11.359
Welcome to Unleashing Genius.
00:01:11.840 --> 00:01:13.120
Thank you, and thanks for having me.
00:01:13.519 --> 00:01:14.560
I am so glad you're here.
00:01:14.719 --> 00:01:22.319
Listen, I want to start with something that might feel like a softball, but let's get it out there so that it becomes making what you do more accessible.
00:01:22.480 --> 00:01:33.680
For a lot of people, when you say supercomputing or a supercomputer, it sounds completely like something that's reverse used for a national laboratory or like a super expensive technology company.
00:01:34.000 --> 00:01:40.079
So what is Perune and what role does it play for a university?
00:01:40.560 --> 00:01:42.400
Yeah, this is this is a very good question.
00:01:42.560 --> 00:01:50.319
So just from the beginning, from the design, the Perune was uh designed as a national betascale uh supercomputer.
00:01:50.640 --> 00:02:06.000
And these supercomputer uh was designed to carry most intensive workloads, uh HPC workloads, AR workloads, as well as the data analysis, data visualization, and standard like numerical calculations.
00:02:06.400 --> 00:02:24.319
Um speaking about the power, uh we have more than 12,000 of the CPU cores uh inside of that supercomputer, but more impressive is that we have more than 208 uh uh graphical cards or graphic accelerators from Nvidia uh the H200.
00:02:24.639 --> 00:02:29.039
And this is basically where most of the power of that supercomputer comes from.
00:02:29.199 --> 00:02:44.800
Uh, just in a perspective of that of uh that way, uh for more than 10 months of the operation of that supercomputer, uh, we were able to calculate more than 125,000 jobs.
00:02:45.360 --> 00:02:50.479
And uh 80,000 of that job comes from the Axloid partition.
00:02:50.719 --> 00:03:01.520
So you can imagine basically how immersive load and how big demand on the such an AI calculation are right now in our country.
00:03:01.759 --> 00:03:11.039
So uh we think that we are starting to move up the research far beyond using that technology in Slovakia.
00:03:11.439 --> 00:03:13.120
That's that's just incredible.
00:03:13.280 --> 00:03:18.159
I think what's most incredible is that it's it's accelerating university.
00:03:18.319 --> 00:03:26.719
I I don't think people really realize how embedded universities have been in the development of research and supercomputing.
00:03:27.039 --> 00:03:29.439
Used to take rooms and now it clearly doesn't take rooms.
00:03:29.599 --> 00:03:41.280
So one of the more interesting aspects that I I know that we've uh talked about, but I wanted you to talk about is the Perune and tell me if I'm saying it right.
00:03:43.360 --> 00:03:45.520
Perfect extends beyond the university.
00:03:45.599 --> 00:03:58.319
So it's not just what you guys are doing with the immense amount of workloads, but it's designed to support researchers, students, public institutions, and industry, which is about access.
00:03:58.400 --> 00:04:03.680
So why is that why is access for this project so important to innovation?
00:04:04.080 --> 00:04:14.800
Yeah, the the truth is that having access as a researcher to such uh infrastructure uh give you uh the breakthrough in your research.
00:04:14.960 --> 00:04:19.839
So if you have like an ideas, you can prove it, you can test it.
00:04:20.000 --> 00:04:24.560
So this is a breakthrough, uh I think um in that.
00:04:24.879 --> 00:04:46.879
And uh truly uh the access is not only open for our university, but the project is for all universities around Slovakia, uh, all academic institutions, all scientific institutions, including students, government institutions, and this access is completely for free for them.
00:04:47.680 --> 00:04:58.800
But so we are trying to uh step up in that research and give the platform for our users for free so they can make research far beyond.
00:04:59.120 --> 00:05:07.439
But uh on the other hand, uh the truth is that we are not forgetting of our industry partners, the commercial partners as well.
00:05:07.680 --> 00:05:13.360
And we are not getting them just uh the computational time or computational power.
00:05:13.519 --> 00:05:28.000
We are getting them our expertise, our excellence and courage, and uh we are able to help them with their uh problems and solve uh the issues around the data, AI, and the HPG workload.
00:05:28.399 --> 00:05:41.920
So that's I think it's really interesting that we just talked about data as part of that process because we were just talking about the supercomputing, what access to innovation looks like, how you're trying to extend that because it makes the model, it makes the process work much better.
00:05:42.160 --> 00:05:49.120
But when we we hear a lot about that when we talk about compute and AI together, but we don't ever really talk about the data, right?
00:05:49.199 --> 00:05:54.000
So what what role does data play in how you're doing that scientific discovery?
00:05:54.399 --> 00:06:01.519
Yeah, the truth is basically that the computational power just isn't enough.
00:06:01.839 --> 00:06:05.759
Uh imagine the HPC as a huge skyscraper.
00:06:06.079 --> 00:06:14.639
Uh the skyscraper is the computational power, but if everything might work correctly, you need a very strong foundation underneath.
00:06:14.800 --> 00:06:19.519
And this is basically where the uh NetApp comes into the game.
00:06:19.839 --> 00:06:38.240
So um uh from that part, from that part, uh the uh immersive AI and HPC workload need fast, efficient, cost-efficient uh storages, but also on the top of that, you need to uh have secure storage for your data.
00:06:38.399 --> 00:06:42.720
So usually the research data are very crucial to safety.
00:06:42.959 --> 00:06:51.519
So uh this is basically uh our job to to handle these problems and not put them into the other researchers.
00:06:51.680 --> 00:06:55.600
So we we are thinking that researchers are not here for managing the data.
00:06:55.759 --> 00:06:57.839
This is our job alongside with the NetApp.
00:06:58.240 --> 00:07:07.120
And this is not uh the journey, this the this journey doesn't start um uh until the the parent is active.
00:07:07.279 --> 00:07:16.800
But our journey started far more uh 15 years ago as a university first storage and then uh right now uh to the parent storage device.
00:07:17.199 --> 00:07:18.000
I I love that.
00:07:18.160 --> 00:07:19.120
Thank you for that.
00:07:19.439 --> 00:07:25.920
So let's talk about an example because we've been talking slightly theoretical, but it's it's also quite fascinating.
00:07:26.000 --> 00:07:27.040
But let's give an example.
00:07:27.199 --> 00:07:35.120
So um one of the one of the things that the university is working on is voice analysis for ALS, right?
00:07:35.279 --> 00:07:36.079
ALS detection.
00:07:36.319 --> 00:07:36.560
Yeah, yeah.
00:07:36.800 --> 00:07:38.000
Can you tell us a little bit about that?
00:07:38.319 --> 00:07:42.639
Yeah, just before I answer that question, I would like to top up one thing.
00:07:42.959 --> 00:07:53.439
Um uh from the beginning of the supercomputer parent, so it's 10 months of the operation, we passed more than 250 research projects.
00:07:53.600 --> 00:07:53.680
Wow.
00:07:53.839 --> 00:07:56.399
And more than 100 are still ongoing.
00:07:56.639 --> 00:07:56.879
Okay.
00:07:57.120 --> 00:08:02.399
And these hundreds of projects are spread around hundreds of researchers around Slovakia.
00:08:02.560 --> 00:08:12.160
But as you mentioned, we have a couple pro couple projects that are very successful, and they are not successful only in a national way, but globally.
00:08:12.399 --> 00:08:17.759
Uh, we have one particular project which is led by Professor Peter Drotar.
00:08:18.160 --> 00:08:24.639
And this project tries to find out the eyeless disease uh from the human speech.
00:08:24.800 --> 00:08:33.679
And they do it uh with the AI modeling of the human voice and finding some special buttons inside of that voice.
00:08:33.919 --> 00:08:44.639
And they are able to find out just from your voice if you have that horrible disease, and and if you saw how it's spreading over the time.
00:08:45.360 --> 00:08:55.440
And uh speaking about the success, uh, this uh project win 2026 SAND uh challenge and at IEEE ICAPS.
00:08:55.600 --> 00:08:59.279
So it's a very successful uh project in this in this world.
00:08:59.679 --> 00:09:01.679
See, this is what people want to hear, right?
00:09:01.759 --> 00:09:07.120
They want they want technology and research to improve human life.
00:09:07.200 --> 00:09:09.679
And this is this is a really great example of that.
00:09:09.840 --> 00:09:17.200
I mean, who who doesn't want to improve and get the markers for ALS and how to how to potentially then solve that in the future?
00:09:17.360 --> 00:09:18.559
That's that's amazing.
00:09:18.720 --> 00:09:19.759
That is truly amazing.
00:09:19.919 --> 00:09:24.240
So I love the conversation we just had, especially on how we're solving ALS.
00:09:24.320 --> 00:09:26.799
I mean, that's just that's what you want to see from research.
00:09:26.960 --> 00:09:42.399
But as you look ahead and you're thinking about what comes next, how do you think universities can start to really not just do the projects but start to teach business, government, society, maybe over time about how to innovate and think to solve problems?
00:09:42.960 --> 00:09:45.600
This is this is very like a futuristic question.
00:09:45.679 --> 00:09:52.720
And to truly, uh, we think that uh the the top research uh doesn't come from a single breakthrough.
00:09:52.879 --> 00:09:58.399
So uh you see that inside of this EI era, everything is somehow interconnected.
00:09:58.639 --> 00:10:09.759
So, for example, just uh as as I as we mentioned, the ILS or or health research is uh is connected to uh high performance research as well.
00:10:10.080 --> 00:10:27.519
So uh so we think that the universities or or entire like the education sector uh are here for learning the students to solve the complex and immersive problems, but uh we need to give them the right tools to do it.
00:10:27.679 --> 00:10:35.840
So the technology is one part, but we need to show them how to use it and how to move research far beyond.
00:10:36.320 --> 00:10:42.159
This is not something that we talked about, but I'm super passionate about now that I've listened to you and we've had this conversation.
00:10:42.399 --> 00:10:48.879
I think a lot of our young people are worried that AI is coming for their jobs and that they have no future.
00:10:49.440 --> 00:10:52.320
I think that the future is so very bright.
00:10:52.559 --> 00:10:54.480
What what would you tell them?
00:10:54.960 --> 00:11:03.120
Um I'm truly on your side, to be honest, because maybe yeah, the the the some job position will be somehow shifted.
00:11:03.279 --> 00:11:08.960
But I think the AR brings up more new positions that we doesn't even hear it from right now.
00:11:09.200 --> 00:11:18.000
So I don't think they don't need to be uh scare of that and just decide to be prepared of that and use the tools right now.
00:11:18.320 --> 00:11:18.799
I love that.
00:11:18.960 --> 00:11:19.279
I love that.
00:11:19.440 --> 00:11:21.200
Is there any place we can go and learn more about this?
00:11:21.360 --> 00:11:24.159
Do you have a website or a something that we can go look at?
00:11:24.480 --> 00:11:29.200
Yeah, we we for sure have the uh website uh of our uh supercomputing center.
00:11:29.360 --> 00:11:32.879
It's the ace uh sc.2k.sk.
00:11:33.360 --> 00:11:35.440
And we'll go ahead and put that in the story as well.
00:11:35.600 --> 00:11:37.120
Martin, this has been amazing.
00:11:37.440 --> 00:11:39.519
Thank you so much for having me, it was perfect.
00:11:40.399 --> 00:11:46.399
I mean, wow, today's conversation was a reminder that discovery does not happen in isolation.
00:11:46.639 --> 00:11:54.480
Behind every breakthrough are people, ideas, data, and increasingly the infrastructure that makes new forms of research possible.
00:11:54.720 --> 00:12:06.720
What makes the 2K story especially interesting is not simply the scale of the technology, but how that technology is being made available to researchers, students, institutions, and innovators.
00:12:07.039 --> 00:12:19.519
Whether it's advancing healthcare, improving scientific understanding, or helping prepare the next generation of researchers, Access continues to be one of the most powerful accelerators of innovation.
00:12:19.759 --> 00:12:25.919
Martin, thank you so much for joining me, joining us, and sharing the university's perspective.
00:12:26.080 --> 00:12:29.919
And for everybody else, thanks again for tuning in to Unleashing Genius.
00:12:30.000 --> 00:12:31.440
We'll see you next time.
00:00:05.839 --> 00:00:07.599
Welcome to Unleashing Genius.
00:00:07.679 --> 00:00:10.560
I'm Gaby Boko, the Chief Marketing Officer at NetUp.
00:00:10.720 --> 00:00:19.039
If you've been here before, then you know that this series explores the ideas, trends, and technology shifts that are shaping how organizations innovate and grow.
00:00:19.280 --> 00:00:27.760
Throughout history, discovery has often been dependent on access, access to information and expertise, access to tools.
00:00:28.079 --> 00:00:38.159
Today, some of the most important discoveries depend on access to something else: computing power, data and the ability to work with both at scale.
00:00:38.479 --> 00:00:48.799
Universities are playing a fascinating role in that shift, acting not only as places of learning, but also as engines of research, experimentation, and also innovation.
00:00:49.039 --> 00:00:59.520
The Technical University of Coshita is one of the institutions helping shape that future through its investment in high-performance computing, AI research, and advanced data infrastructure.
00:00:59.759 --> 00:01:09.359
Joining me today is Martin Hevria, head of the Department of Computer Networks and Operating Systems at the University and one of the leaders behind the Perun supercomputing environment.
00:01:09.680 --> 00:01:11.359
Welcome to Unleashing Genius.
00:01:11.840 --> 00:01:13.120
Thank you, and thanks for having me.
00:01:13.519 --> 00:01:14.560
I am so glad you're here.
00:01:14.719 --> 00:01:22.319
Listen, I want to start with something that might feel like a softball, but let's get it out there so that it becomes making what you do more accessible.
00:01:22.480 --> 00:01:33.680
For a lot of people, when you say supercomputing or a supercomputer, it sounds completely like something that's reverse used for a national laboratory or like a super expensive technology company.
00:01:34.000 --> 00:01:40.079
So what is Perune and what role does it play for a university?
00:01:40.560 --> 00:01:42.400
Yeah, this is this is a very good question.
00:01:42.560 --> 00:01:50.319
So just from the beginning, from the design, the Perune was uh designed as a national betascale uh supercomputer.
00:01:50.640 --> 00:02:06.000
And these supercomputer uh was designed to carry most intensive workloads, uh HPC workloads, AR workloads, as well as the data analysis, data visualization, and standard like numerical calculations.
00:02:06.400 --> 00:02:24.319
Um speaking about the power, uh we have more than 12,000 of the CPU cores uh inside of that supercomputer, but more impressive is that we have more than 208 uh uh graphical cards or graphic accelerators from Nvidia uh the H200.
00:02:24.639 --> 00:02:29.039
And this is basically where most of the power of that supercomputer comes from.
00:02:29.199 --> 00:02:44.800
Uh, just in a perspective of that of uh that way, uh for more than 10 months of the operation of that supercomputer, uh, we were able to calculate more than 125,000 jobs.
00:02:45.360 --> 00:02:50.479
And uh 80,000 of that job comes from the Axloid partition.
00:02:50.719 --> 00:03:01.520
So you can imagine basically how immersive load and how big demand on the such an AI calculation are right now in our country.
00:03:01.759 --> 00:03:11.039
So uh we think that we are starting to move up the research far beyond using that technology in Slovakia.
00:03:11.439 --> 00:03:13.120
That's that's just incredible.
00:03:13.280 --> 00:03:18.159
I think what's most incredible is that it's it's accelerating university.
00:03:18.319 --> 00:03:26.719
I I don't think people really realize how embedded universities have been in the development of research and supercomputing.
00:03:27.039 --> 00:03:29.439
Used to take rooms and now it clearly doesn't take rooms.
00:03:29.599 --> 00:03:41.280
So one of the more interesting aspects that I I know that we've uh talked about, but I wanted you to talk about is the Perune and tell me if I'm saying it right.
00:03:43.360 --> 00:03:45.520
Perfect extends beyond the university.
00:03:45.599 --> 00:03:58.319
So it's not just what you guys are doing with the immense amount of workloads, but it's designed to support researchers, students, public institutions, and industry, which is about access.
00:03:58.400 --> 00:04:03.680
So why is that why is access for this project so important to innovation?
00:04:04.080 --> 00:04:14.800
Yeah, the the truth is that having access as a researcher to such uh infrastructure uh give you uh the breakthrough in your research.
00:04:14.960 --> 00:04:19.839
So if you have like an ideas, you can prove it, you can test it.
00:04:20.000 --> 00:04:24.560
So this is a breakthrough, uh I think um in that.
00:04:24.879 --> 00:04:46.879
And uh truly uh the access is not only open for our university, but the project is for all universities around Slovakia, uh, all academic institutions, all scientific institutions, including students, government institutions, and this access is completely for free for them.
00:04:47.680 --> 00:04:58.800
But so we are trying to uh step up in that research and give the platform for our users for free so they can make research far beyond.
00:04:59.120 --> 00:05:07.439
But uh on the other hand, uh the truth is that we are not forgetting of our industry partners, the commercial partners as well.
00:05:07.680 --> 00:05:13.360
And we are not getting them just uh the computational time or computational power.
00:05:13.519 --> 00:05:28.000
We are getting them our expertise, our excellence and courage, and uh we are able to help them with their uh problems and solve uh the issues around the data, AI, and the HPG workload.
00:05:28.399 --> 00:05:41.920
So that's I think it's really interesting that we just talked about data as part of that process because we were just talking about the supercomputing, what access to innovation looks like, how you're trying to extend that because it makes the model, it makes the process work much better.
00:05:42.160 --> 00:05:49.120
But when we we hear a lot about that when we talk about compute and AI together, but we don't ever really talk about the data, right?
00:05:49.199 --> 00:05:54.000
So what what role does data play in how you're doing that scientific discovery?
00:05:54.399 --> 00:06:01.519
Yeah, the truth is basically that the computational power just isn't enough.
00:06:01.839 --> 00:06:05.759
Uh imagine the HPC as a huge skyscraper.
00:06:06.079 --> 00:06:14.639
Uh the skyscraper is the computational power, but if everything might work correctly, you need a very strong foundation underneath.
00:06:14.800 --> 00:06:19.519
And this is basically where the uh NetApp comes into the game.
00:06:19.839 --> 00:06:38.240
So um uh from that part, from that part, uh the uh immersive AI and HPC workload need fast, efficient, cost-efficient uh storages, but also on the top of that, you need to uh have secure storage for your data.
00:06:38.399 --> 00:06:42.720
So usually the research data are very crucial to safety.
00:06:42.959 --> 00:06:51.519
So uh this is basically uh our job to to handle these problems and not put them into the other researchers.
00:06:51.680 --> 00:06:55.600
So we we are thinking that researchers are not here for managing the data.
00:06:55.759 --> 00:06:57.839
This is our job alongside with the NetApp.
00:06:58.240 --> 00:07:07.120
And this is not uh the journey, this the this journey doesn't start um uh until the the parent is active.
00:07:07.279 --> 00:07:16.800
But our journey started far more uh 15 years ago as a university first storage and then uh right now uh to the parent storage device.
00:07:17.199 --> 00:07:18.000
I I love that.
00:07:18.160 --> 00:07:19.120
Thank you for that.
00:07:19.439 --> 00:07:25.920
So let's talk about an example because we've been talking slightly theoretical, but it's it's also quite fascinating.
00:07:26.000 --> 00:07:27.040
But let's give an example.
00:07:27.199 --> 00:07:35.120
So um one of the one of the things that the university is working on is voice analysis for ALS, right?
00:07:35.279 --> 00:07:36.079
ALS detection.
00:07:36.319 --> 00:07:36.560
Yeah, yeah.
00:07:36.800 --> 00:07:38.000
Can you tell us a little bit about that?
00:07:38.319 --> 00:07:42.639
Yeah, just before I answer that question, I would like to top up one thing.
00:07:42.959 --> 00:07:53.439
Um uh from the beginning of the supercomputer parent, so it's 10 months of the operation, we passed more than 250 research projects.
00:07:53.600 --> 00:07:53.680
Wow.
00:07:53.839 --> 00:07:56.399
And more than 100 are still ongoing.
00:07:56.639 --> 00:07:56.879
Okay.
00:07:57.120 --> 00:08:02.399
And these hundreds of projects are spread around hundreds of researchers around Slovakia.
00:08:02.560 --> 00:08:12.160
But as you mentioned, we have a couple pro couple projects that are very successful, and they are not successful only in a national way, but globally.
00:08:12.399 --> 00:08:17.759
Uh, we have one particular project which is led by Professor Peter Drotar.
00:08:18.160 --> 00:08:24.639
And this project tries to find out the eyeless disease uh from the human speech.
00:08:24.800 --> 00:08:33.679
And they do it uh with the AI modeling of the human voice and finding some special buttons inside of that voice.
00:08:33.919 --> 00:08:44.639
And they are able to find out just from your voice if you have that horrible disease, and and if you saw how it's spreading over the time.
00:08:45.360 --> 00:08:55.440
And uh speaking about the success, uh, this uh project win 2026 SAND uh challenge and at IEEE ICAPS.
00:08:55.600 --> 00:08:59.279
So it's a very successful uh project in this in this world.
00:08:59.679 --> 00:09:01.679
See, this is what people want to hear, right?
00:09:01.759 --> 00:09:07.120
They want they want technology and research to improve human life.
00:09:07.200 --> 00:09:09.679
And this is this is a really great example of that.
00:09:09.840 --> 00:09:17.200
I mean, who who doesn't want to improve and get the markers for ALS and how to how to potentially then solve that in the future?
00:09:17.360 --> 00:09:18.559
That's that's amazing.
00:09:18.720 --> 00:09:19.759
That is truly amazing.
00:09:19.919 --> 00:09:24.240
So I love the conversation we just had, especially on how we're solving ALS.
00:09:24.320 --> 00:09:26.799
I mean, that's just that's what you want to see from research.
00:09:26.960 --> 00:09:42.399
But as you look ahead and you're thinking about what comes next, how do you think universities can start to really not just do the projects but start to teach business, government, society, maybe over time about how to innovate and think to solve problems?
00:09:42.960 --> 00:09:45.600
This is this is very like a futuristic question.
00:09:45.679 --> 00:09:52.720
And to truly, uh, we think that uh the the top research uh doesn't come from a single breakthrough.
00:09:52.879 --> 00:09:58.399
So uh you see that inside of this EI era, everything is somehow interconnected.
00:09:58.639 --> 00:10:09.759
So, for example, just uh as as I as we mentioned, the ILS or or health research is uh is connected to uh high performance research as well.
00:10:10.080 --> 00:10:27.519
So uh so we think that the universities or or entire like the education sector uh are here for learning the students to solve the complex and immersive problems, but uh we need to give them the right tools to do it.
00:10:27.679 --> 00:10:35.840
So the technology is one part, but we need to show them how to use it and how to move research far beyond.
00:10:36.320 --> 00:10:42.159
This is not something that we talked about, but I'm super passionate about now that I've listened to you and we've had this conversation.
00:10:42.399 --> 00:10:48.879
I think a lot of our young people are worried that AI is coming for their jobs and that they have no future.
00:10:49.440 --> 00:10:52.320
I think that the future is so very bright.
00:10:52.559 --> 00:10:54.480
What what would you tell them?
00:10:54.960 --> 00:11:03.120
Um I'm truly on your side, to be honest, because maybe yeah, the the the some job position will be somehow shifted.
00:11:03.279 --> 00:11:08.960
But I think the AR brings up more new positions that we doesn't even hear it from right now.
00:11:09.200 --> 00:11:18.000
So I don't think they don't need to be uh scare of that and just decide to be prepared of that and use the tools right now.
00:11:18.320 --> 00:11:18.799
I love that.
00:11:18.960 --> 00:11:19.279
I love that.
00:11:19.440 --> 00:11:21.200
Is there any place we can go and learn more about this?
00:11:21.360 --> 00:11:24.159
Do you have a website or a something that we can go look at?
00:11:24.480 --> 00:11:29.200
Yeah, we we for sure have the uh website uh of our uh supercomputing center.
00:11:29.360 --> 00:11:32.879
It's the ace uh sc.2k.sk.
00:11:33.360 --> 00:11:35.440
And we'll go ahead and put that in the story as well.
00:11:35.600 --> 00:11:37.120
Martin, this has been amazing.
00:11:37.440 --> 00:11:39.519
Thank you so much for having me, it was perfect.
00:11:40.399 --> 00:11:46.399
I mean, wow, today's conversation was a reminder that discovery does not happen in isolation.
00:11:46.639 --> 00:11:54.480
Behind every breakthrough are people, ideas, data, and increasingly the infrastructure that makes new forms of research possible.
00:11:54.720 --> 00:12:06.720
What makes the 2K story especially interesting is not simply the scale of the technology, but how that technology is being made available to researchers, students, institutions, and innovators.
00:12:07.039 --> 00:12:19.519
Whether it's advancing healthcare, improving scientific understanding, or helping prepare the next generation of researchers, Access continues to be one of the most powerful accelerators of innovation.
00:12:19.759 --> 00:12:25.919
Martin, thank you so much for joining me, joining us, and sharing the university's perspective.
00:12:26.080 --> 00:12:29.919
And for everybody else, thanks again for tuning in to Unleashing Genius.
00:12:30.000 --> 00:12:31.440
We'll see you next time.
