Tech Barometer – From The Forecast by Nutanix

In this Tech Barometer podcast segment, Debojyoti “Debo” Dutta, vice president of engineering, AI at Nutanix shares his passion for computational biology and how AI will dramatically change enterprises.

Find more enterprise cloud news, features stories and profiles at The Forecast.

Transcript:

Debo Dutta: If you look at what’s happening today, it’s not just because of AI, but in general because of high throughput data that can be generated out of a biological system. And the amount of data that you can generate was unimaginable even a few years ago.

Jason Lopez: In our series on MedPerf we wanted to introduce you to a computer scientist at the forefront of AI and machine learning development. Debojyoti Dutta, who goes by the nickname Debo. His work is bringing AI to IT leaders across many industries, including healthcare. This is the Tech Barometer podcast, I’m Jason Lopez.

[Related: Exploring Uses for AI in Healthcare]

Jason Lopez: When you hear about AI and how great it will be for healthcare, you might wonder, well who are the people making it happen? Debo is one of those technologists who’s working to connect the dots of computer science and medicine.

Debo Dutta: When coupled with AI, it’s going to completely change the way we design drugs, how we design antibodies, new therapeutics, I can’t even imagine all the things that we will be able to do using this iteration of AI coupled with the amount of data that we can generate out of living beings.

Jason Lopez: One area Debo thinks AI will have a profound effect is in examining medical images. For example, people with diabetes are at risk for loss of eyesight. With AI assistance, images of the inside of the eye could give doctors far earlier detection of diabetic retinopathy. Other imaging examples include detection of tumors and cancers. But another area where AI could bring a transformation...immunotherapy.

Debo Dutta: Immunotherapy in a nutshell is to program your immune system to fight bad actors in your body. The bad actors could be viruses, it could be cancer cells.

[Related: Building Infrastructure to Unlock AI’s Next Big Leap]

Jason Lopez: Our immune system can detect viruses, but sometimes cancer cells are invisible. Cancer cells can appear normal and the immune system allows them to go about wreaking havoc. In immunotherapy, the DNA of the immune system’s T-cells are changed to recognize the genetic strands of the tumor cell and destroy them.

Debo Dutta: Let’s see how AI gets into this space. So the programming, the existing T-cell can be done with gene therapy, but how do you know what to program? That’s where AI comes in. Using AI, you can rapidly design sequences. People are today looking at a lot of sequence data as well as literature, feeding them into large language models. And they are actually trying to generate candidate sequences for lab experiments.

Jason Lopez: Advances in large language models as well as computer infrastructure are cutting development times dramatically. Debo says what would have taken years might take a 10th or even a hundredth of the time.

Debo Dutta: I’m not an oncologist. I’m not a gene therapy researcher or an immunotherapy researcher, but I do believe that as a systems person, if I can help the lifecycle of the machine learning go faster, I can help them to make immunotherapy get better and better. We can cure more types of cancers and more diseases.

Jason Lopez: Debo was born in India. His mother is a retired doctor and his father a retired engineer. Those two professions are some of the most sought-after in the country and getting into a good university to pursue those professions is very competitive, and he was able to enroll in one of the top colleges in engineering where he opted to study computer science.

Debo Dutta: But I kept thinking about biology, but I didn’t do much about it.

Jason Lopez: After graduating, he came to the US to study for a PhD at the University of Southern California, and that’s when he saw another dimension to computer science.

Debo Dutta: It looks like pure science in many ways because it’s a lot of math, applied math and discrete math, and a lot of engineering too. But it can be applied to biology.

Jason Lopez: At USC he encountered a large team doing computational biology. And after his PhD, he had this thought:...

In this Tech Barometer podcast segment, Greg Diamos tells how an early passion for computing led him to a pioneering role Baidu’s Silicon Valley AI lab, where he discovered ways to scale deep learning systems, and went on to co-found MLCommons and AI company Lamini.

Find more enterprise cloud news, features stories and profiles at The Forecast.

Transcript:

Greg Diamos: I think computing is a way to give people magical abilities, like superpowers. I like to live in a world where you can give it to everyone. Like, what if every single person had superpowers? I had basically ten years with nothing to do and just a pile of computers in my garage.

Jason Johnson: Just getting the ball rolling, I was wondering, Greg, could you tell me a little bit about what it is you do?

Greg Diamos: I’m one of the people who builds the software infrastructure that’s needed to run applications like ChatGPT or Copilot. Let’s see, I think it’s helpful to start from the beginning. My last name is Diamos. It’s a Greek name. It’s kind of cut in half. About a hundred years ago, my family immigrated to the U.S. They mostly settled in the West.

Before I was born, my father, he moved to Arizona. And his goal in life was to retire and find someplace relaxing and to go and play golf most of the time. And so he moved to Carefree, Arizona. Most people, when they think of Arizona, they think of Tucson or Sedona or places that normal people would go. You go to the Grand Canyon or something. Carefree is a place where no one ever goes. It’s right in the middle of the desert. There are not a lot of people, but it has a lot of golf courses and it’s very relaxing. It’s like a spa. So it’s a good place for that, but it was a very boring and brutally hot place to be as a 10-year-old boy.

[Related: AI Reorients IT Operations]

So I was bored, bored out of my mind. My mom worked as a database administrator for IBM. IBM at the time, they had a mainframe business. And so they would basically throw away the last generation of stuff. She would just take all the machines that were headed to the dumpster, put them up in the car, drive them out and throw them in our garage because it would be such a waste if such a thing was thrown away. I had basically 10 years with nothing to do and just a pile of computers in my garage. So it took me from when I was 10 years old until when I was about 25 to kind of figure out how the machines worked. It seems, like, magical to me that you could build such a thing. You could do that as a little boy stuck in the desert. I did a PhD in computer engineering. After that, I went to Georgia Tech.

Okay, let me tell the story of this one. I really love telling the story. I actually worked at the Baidu search engine. You could think of it as the Google of China. If you go to the search bar, there’s a little microphone on it. You press the microphone, you can talk to it. It was based on the last generation of machine learning technology. It still used machine learning, but it didn’t use deep learning. This exists right now in all major search engines. Around 2014, 2015, Baidu was in the process of deploying their first deep learning system.

[Related: Alex Karargyris’s Path to Becoming a Pioneer of Medical AI]

One of the projects that we had in the Baidu Silicon Valley AI lab was to apply deep learning, which had just been invented and was just starting to work to improve that particular product. Along the way, we had a number of researchers. One of the researchers was Jesse Engel. He was a material scientist, but he was not a deep learning researcher. Actually, none of us were deep learning researchers because deep learning didn’t exist. One of the things that he did is he performed sweeps over all the parameters in the system.

One of the sweeps produced this plot that seemed to show that there was a relationship between the accuracy of the system or the quality of the system with the amount of data that went into the model and the size of the model. If you think of a neural network as just being a collection of a ton of simulated neurons, not real neurons, but simulated neurons in that system, trained on thousands and thousands of hours of recordings of people talking. It seemed like as you added more neurons or simulated neurons, and you added more recordings of people talking, the system got smarter. It didn’t just happen in an arbitrary way. It happened in a very clear relationship you could fit with a physics equation, E equals mc squared kind of equation, a one parameter equation. It was a very simp...

In this Tech Barometer podcast segment, explore how a partnership between data networking giant Cisco and hybrid multicloud software company Nutanix is changing perspectives and opening opportunities for people who build and manage IT operations.

Find more enterprise cloud news, features stories and profiles at The Forecast.

Transcript:

Lee Caswell: 750 million new applications in the next three years, more than the past 40 years of computing. How do you assimilate that quickly without overrunning your staff?

Jason Burns: You’re able to roll out these applications and not have to worry about how much time it might take to stand up new servers, stand up the network. All of that piece just can be more seamlessly provisioned so that you have more time to deploy applications.

Lee Caswell: Let’s say it a different way. Infrastructure doesn’t get in the way of supporting new applications. The best partnerships are customer-driven.

Jason Lopez: Those are the voices of Lee Caswell, vice president of Product and Solutions Marketing and Jason Burns, Director of Technical Marketing, both of Nutanix. This is the Tech Barometer Podcast Here, they’re in conversation about the evolving nature of network infrastructure and application deployment in the context of Nutanix’s partnership with Cisco. They chat about different perspectives and understandings that network, storage, and compute teams bring to the table, unified communications and Cisco UCS, rapid application deployment and many other facets of the partnership

[Related:Focus Shifts to Migration in Wake of Broadcom’s VMware Acquisition]

Lee Caswell: Today, for example, I was talking to a customer who’s the first Cisco customer we have in the Americas, not the first we have worldwide. And one of the things that really stuck out for them was the relationship that they have with Cisco, you know, expanding from networking into compute, has really meant that they have a level of trust there and confidence. And now that Cisco’s reselling the Nutanix offer, it’s really bringing together the networking and the, call it the infrastructure teams, in a way that we brought in the past, the storage and the compute teams together. So I’m curious on your perspective on that, Jason.

Jason Burns: From my perspective, I’ve seen the same thing. When customers are deploying a solution from Cisco, it is exactly that. Oftentimes you’ll see something with the unified communications on top of Cisco UCS and the Cisco networking piece as well. And so the combination there of being able to bring in the entire application on top of the computing system and then the storage as well is really appealing to the customers. And then having that delivered as a solution rather than something that they’re piecing together part by part.

Lee Caswell: You know, as I’m watching and talking to some of the Cisco folks, there’s some really interesting things that Nutanix does that they didn’t have access to before and now make it just easier to sell anHCI-based solution. One is, you know, the ability to have mixed nodes, for example, to be able to have nodes with different capabilities, whether it’s disk and flash or different CPU capabilities. That level of flexibility actually makes it a lot easier to sell this. And now integration, you know, support for ACI, for example, really helps from an integrated management solution. So I’m seeing those two things really set the bar as to how we’re now we’re bridging the network stack along with compute and storage.

Jason Burns: Yeah, the integration ofNutanix AHV and Cisco ACI is something that I’m personally excited about. As a former network engineer, I love to see the automation point where we can make networks inside of the network fabric and have that pushed into the compute fabric. What you get from that action is a system where you’re able to really easily deploy applications because the network substrate is already there for them. That’s part of what Cisco has done to integrate with Nutanix AHV. That’s really complemented by what Nutanix is doing on the virtualization side, both with our flow virtual networking and flow network security for virtual networks and micro-segmentation inside the hypervisor itself. So you have this physical network layer that Cisco is providing, and then you have the virtual network layer that Nutanix provides there, and that’s all being tied together.

Lee Caswell: Yeah, it’s kind of fun. I ...

In this Tech Barometer podcast segment, IT industry analyst Steve McDowell and Lee Caswell from Nutanix discuss the challenges and risks IT operations leaders face in the wake of Broadcom’s acquisition of VMware.

Find more enterprise cloud news, features stories and profiles at The Forecast.

Transcript:

Steve McDowell: Broadcom announced quite a while ago that they’re acquiring VMware.

Lee Caswell: It’s not a light switch moment.

Steve McDowell: Because of regulatory hurdles and all sorts of other things, it stretched out for multiple quarters. That is where I think the initial wave of concern came in, because now not only do I have to wait and see, I have to wait multiple quarters to see.

Lee Caswell: Very rarely in IT do you just decommission something now instead, what you’re thinking is, all right, how do I make sure that I’m containing the risk, and then taking all the new things and putting that on the new modern infrastructure.

Jason Lopez: In the ever-evolving landscape of IT infrastructure, companies are increasingly finding themselves at a crossroads, particularly in the wake of significant industry acquisitions such as Broadcom’s purchase of VMware. This shift has ushered in concerns for VMWare’s customers.

[Related: Hedging Into Expected Broadcom Acquisition of VMware]

Lee Caswell: What happens if they’re not one of the top 2,000 customers?

Jason Lopez: Lee Caswell, Senior VP of Product and Solutions Marketing at Nutanix, says VMWare customers are worried about three major things: pricing going forward, and we’ll dive deeper into that in a few minutes, as well as support for products and the risk to personal careers.

Lee Caswell: Those customers are worried from a support standpoint. I think those customers are legitimately worried that they’re not going to get a call. Partners are worried, too, because Broadcom doesn’t have a great relationship with partners. So I think that support piece will come to be the thing that really actually unhinges them. And the third one is about personal career risk. If you can’t get support and you’re running something and you didn’t make a change, then all of a sudden it’s going to be back on you.

Steve McDowell: There’s a lot of uncertainty among the IT community about what Broadcom is going to do with VMware.

Jason Lopez: Steve McDowell is principal analyst at NAND Research.

Steve McDowell: Broadcom historically, they’ve largely acquired companies that have largely commoditized and they maintain them forward, but you don’t see a lot of continuing innovation. Are they just going to take the core VMware business and maintain that moving forward? Because the reality is a technology like VMware, or VM in particular, is very sticky, right? It’s hard to kind of rip and replace.

[Related: Broadcom’s Acquisition of VMware Stirs Uncertainty]

Lee Caswell: The way that customers are talking to me about this right now is that what they had with VMware for the past, you know, almost 20 years, right, was a very safe offering with known risks. And now what’s happened is what was the safe bet is now the risky bet. And it’s got unpredictable risks.

Steve McDowell: You know, if you have a VMware license, you’re probably not going anywhere for the life of that infrastructure, right? But where the uncertainty lives is on, you know, when I do come up to a replacement cycle or I have a greenfield project, you know, is VMware going to continue to deliver the level of innovation?

Jason Lopez: This has left many customers contemplating a strategic approach where they maintain their existing VMware infrastructure but refrain from expanding. Instead, they’re considering investing in new applications and technologies on alternative platforms based on newer architectures.

Steve McDowell: From Broadcom’s perspective, I think everything they’re doing makes a lot of sense for their investors and for maybe existing VMware customers. But where there’s, I think, going to continue to be a concern: how does the VMware technology continue to evolve, right? Am I still going to get the level of support I had? And am I still going to be paying the same amount of money? There’s also...

In this Tech Barometer podcast, Tobi Knaup, general manager for Cloud Native at Nutanix, explains what’s accelerating cloud native application development and how enterprises run these apps across hybrid multicloud IT environments.

Find more enterprise cloud news, features stories and profiles at The Forecast.

Transcript (AI generated):

Tobi Knaup: Cloud Native really is a concept that describes how to build and run modern applications. Those applications are typically microservice-oriented, they run in containers, and they’re dynamically managed. On top of a container platform, typically that’s Kubernetes, that’s really become the industry standard. Kubernetes runs anywhere. You can run it on the public cloud. You can run it on a private cloud. You can run it on the edge. So if you’re building applications on top of Kubernetes in containers, that makes them truly portable so you can run them anywhere, hybrid multicloud.

Jason Lopez: That’s the voice of Tobi Knaup, the general manager for Cloud Native at Nutanix. In this short podcast, the editor of The Forecast, Ken Kaplan, chats with Tobi about the integration of cloud-native applications and hybrid multi-cloud environments. In this discussion they touch on cloud-native applications across various cloud environments; the synergy between AI and Kubernetes; and the shift to Kubernetes for consistency and portability.

[Related: Flattening the Cloud Native Learning Curve]

Ken Kaplan: What was the limitation that’s been unlocked with Kubernetes?

Tobi Knaup: The limitation that was there before is there wasn’t a consistent sort of packaging format for applications that made them really easily portable. And containers kind of provide that abstraction. In computer science, we sometimes call it a layer of indirection. So it abstracts applications away from the underlying infrastructure. And containers are a very lightweight way to package an application, so it’s very easy to ship them all around, all over the place.

Ken Kaplan: And their connection to managing data in different ways, is that something that you have to think about?

Tobi Knaup: Yeah, absolutely. So containers, or Kubernetes when it was first launched, actually did not have support for data. It purely ran stateless applications. So only a few years later, the community, it was actually our engineers at Data2IQ together with Google, created what’s called the container storage interface. And so that became the industry standard for attaching storage to containers. But that was still very bare bones, just simple volumes attached to containers. And so what we did here at Nutanix recently with NDK (application-level services for Kubernetes), really takes that to the next level. Really adds capabilities for disaster recovery and resilience. So makes it really, really easy to run these kind of sensitive stateful applications on Kubernetes.

Ken Kaplan: Awesome, and we’ve been hearing the word resilience and it sounds like the hybrid multicloud, building your apps in containers, these kinds of things are bringing some more control and flexibility for things that you need to keep your business running. Talk about hybrid multicloud in the sense that it’s a choice or it’s where people are today. How did we get here?

Tobi Knaup: Yeah, so I think there are many reasons for why people choose hybrid or multicloud. It’s typically not what a lot of people think at first. I think when hybrid cloud or multicloud first became a concept, people thought, people are going to look for the cheapest compute all over the world and that’s where things are running. I talked to some customers that are doing that actually, but they’re kind of rare and they’re typically hedge funds. So of course they look at market prices. But for most people, the constraints are different. It could be regulatory constraints, right? Data needs to reside in a certain geography or frankly just what an organization is comfortable with, where they’re comfortable putting their most sensitive data. Some don’t want to put it on the public cloud, right? But they appreciate the flexibility and the dynamicism of a public cloud for new developments. So they’re sort of running their steady state production workloads on prem, but they’re giving cloud environments to the development teams for building the next generation of apps, which then may move on prem later when they go to production. So I think a lot of organizations ...