https://connectedsocialmedia.com/ Connected Social Media works with the world's most innovative companies... en-us hourly 1 2026-04-06T12:03:33-04:00 no Connected Social Media Technology, Healthcare, IT Best Practices... Connected Social Media episodic syndication@connectedsocialmedia.com Connected Social Media https://connectedsocialmedia.com/21321/eci-2026-report-shows-strain-between-ai-innovation-and-it-governance/ Mon, 30 Mar 2026 13:10:49 -0700 https://connectedsocialmedia.com/?p=21321 tech leader insights to move faster and smarter. Get more stories by subscribing to The Forecast. Podcast transcript: Jason Lopez:: This is the Tech Barometer podcast. I'm Jason Lopez. Nutanix released its eighth annual enterprise cloud index this month, and two of the key findings stood out. Containers are rapidly becoming the foundation of how modern applications are built and run, and Shadow AI is spreading through organizations largely unmanaged. We talked about this issue of Shadow AI with NAND Research chief analyst, Steve McDowell. Steve McDowell::You're like, "You know what? These IT guys, they're out of their mind. I need to use this because it's going to help me and I'm just going to pull the trigger and make the decision." Yeah, sure. The employee's getting a lot of benefit from this engagement, but you have no idea it's happening. I don't know where it's happening and I don't know what data's being exposed and where that data's going to. I think we see this kind of every big technology transition. Users are going to make their own decisions. Your employees are going to make their own decisions about the technology they use. It may or may not intersect with your corporate guidelines for IT. I remember when smartphones entered the world, that caused a lot of consternation among enterprise IT teams because how do I manage these devices? And they even coined a word, right? BYOD, bring your own device. That was a hot topic for several years until Apple came out with kind of enterprise management tools and things smoothed over. And CloudWorld kind of did the same thing a half a decade later. We're doing that now with AI. I mean, AI is so beneficial. Now, scrolling through LinkedIn and reading all the AI-generated slop, it's not clear everybody knows how to use it, but they're using it. [Related: AI’s Next Wave] Jason Lopez: The Enterprise Cloud Index is a snapshot of an industry in the middle of a profound transition, and it raises a question worth asking. What exactly is driving all of this and where does it lead? Dan Seruli has watched this transformation from the inside. As the cloud native product leader at Nutanix, he spends his days talking to organizations navigating this shift firsthand. Ken Kaplan, editor-in-chief of the forecast, interviewed him and asked him to step back and survey the arc of technology he's lived with for more than a decade. And what he's hearing now from the people on the front lines. Dan Ciruli: I think it is safe to say at this point that containers in general and Kubernetes in particular are, I'm going to say it out loud, the de facto standard for developing and deploying new applications. It is no longer something that is a science experiment, which it was eight years ago. It's no longer a viable option, which it might have been three or four years ago. I would say these days, building your application to be packaged in containers and deployed on Kubernetes is the defacto standard for how applications are being developed. And I'm pretty comfortable saying that out loud. Ken Kaplan: What are you seeing the success and struggles now in this new period compared to the early days? How have things changed? Dan Ciruli: One thing that people are wrestling with is that when it was in that phase that it was more of a science experiment or just some of the new applications, you had certain developers who would lean in and certain developers who were not affected by it. And now I think we're reaching the stage that everybody needs to be comfortable with it. Everybody needs to be ready for whatever application you're working on the next time they ask you for a thing like, "Okay, it better be packaged up in a container. We better have some Kubernetes running wherever it is. We need to deploy that application." In becoming the de facto standard, that has means we're no longer, there's a pocket of the organization who's doing in Kubernetes. Now we're in the phase that everybody needs to be comfortable talking about it, using it, deploying it, running things on it, SREing on it. Ken Kaplan: You're talking to more customers probably than ever before. You would like to talk to more. What are you learning from them? Dan Ciruli: One of the things we're trying to help our customers with is as they approach that transition is how they standardize. When you have pockets of people leaning into a technology, then you have pockets of people leaning into a technology and some might lean in a slightly different direction than others. Some people might be making a certain architectural choice, a certain security choice using a certain technology, which works for that team, but might not work for the organization as a whole. And as you adopt this technology wholesale across the organization, then you have to think about, well, how do we standardize? What policies do we want to set that apply to everybody? How do we centralize this so that this can be run by a centralized team rather than by individual teams? So it's a big transition. And as I say, it's become the de facto standard. And I say that with confidence, but for many organizations, they are still figuring out how that will affect them and how they, as an organization, do that in an efficient way that gives them the benefits that developers want, that give them the ability to innovate quickly, deploy frequently and scale as needed. Ken Kaplan: And do you see a correlation or it's similar to what happened with cloud and people could go out and use a credit card and get compute services for the first time. And then there was all these projects going on and IT didn't know about it. Do you see some similarities? Dan Ciruli: I had never thought about that way, and I think that is a fantastic way to look at it. Cloud was very much the same way. I was part of a team that we got frustrated with internal IT and the length of time it was taking them to get us literally just VMs and the amount they were going to charge us back. And we said, "Somebody on your corporate card, go to Amazon and start using this stuff." Yes. So I think Kubernetes started the same way where a team was like, "Hey, I don't want to deploy in VMs. I'm just going to start using Kubernetes." And then another team is. And then another team is, at some point, someone higher up and more central in the IT organization said, "Wait, there's way too much of this going on. This is not efficient. We've got different teams. We're spending too much money on this. We're duplicating effort all over the place. And from a security posture, we're at risk." So someone centrally said, "We need to, for all of those reasons, we need to centralize this. We need to standardize this and we need to do this in a way that does give the teams what they want, but does it in a way that doesn't put us at risk financially or from a security perspective?" That's an excellent analogy. [Related: Ecosystem Scorecards Help CIOs Avoid Vendor Lock-In] Ken Kaplan: Yeah. You hear about smart cloud strategy now. It used to be cloud first, now smart, but those people who have lived through that transition and are getting smart about their use of cloud, those are probably lessons that they can be applying to Kubernetes and containers. Why would the companies benefit now from saying, "That stuff's useful. Let's do it here together on this platform that can do the old and the new." Dan Ciruli: So the interesting thing about me saying very strongly, this is the defacto standard for how applications are written. That doesn't change history and it doesn't change the fact that at essentially every enterprise, they have decades worth of applications running in virtual machines that are for the most part going to stay in virtual machines. That isn't changing. And while the new stuff is all containerized, the old stuff was virtualized and will continue to be virtualized. Very few of those apps will be rewritten to be containerized, which means as you centralize operations for all of this, now you've got one IT team that is going to be for the next decade, two decades, responsible for running tons of VMs and a growing number of containers that some point will outnumber the VMs, but those VMs will still be there. Companies have a choice. They can build up two separate groups of people, pieces of hardware, networking strategies, security technologies to manage those, in which case they're building literal silos in data centers of which hardware can run which applications, building silos in their organizations of which people can work on which organizations and actually hampering integration. You might have a new application that needs to get an old database, old piece of data that is in a virtual machine. And if you're building those things entirely separately, that's a challenge every time you do it. Whereas companies that say, "Let's combine these on one." They allow themselves to run essentially any application. It doesn't matter if it's virtualized or containerized, you can run it in the same locations. It means the same people who work on running the infrastructure can run that infrastructure, whether it is running virtualized or any combination of containerized applications. And it means you can do things like set security policies, set backup policies, set disaster recovery, networking policies. All of those can be consistent and it becomes much easier to interoperate between the new and the old. So I think it's a really strong driver for companies to invest in ways to run all of their both containerized and virtualized applications in a way that makes sense. [Related: Clouds With Borders: IT Teams Design for Geopatriation] Ken Kaplan: And when they're doing that, are the apps that are running on VMs and containers, are they able to tap into the same storage or databases or different aspects of the system? Or is it you have this ability to manage them both, but they're still kind of separate? Dan Ciruli: I mean, I talked to some organizations who they have their VMware environment and their OpenShift environment. They are literally buying separate teams, buying separate hardware, run by separate people. From a integration calling back and forth, it might as well be separate companies because you've got different networking, you've got different security, right? And what we advocate for is running a hypervisor on all of that hardware that you buy. And then within that, some of those, it's just an app running in a VM and some of those it's Kubernetes running in those, but there's the same networking underneath. And with Flow, you can write a networking policy that says, "This containerized application needs to talk to this virtualized application." That we feel is a tremendous advantage. You don't end up with hardware silos. Hardware silos are always a bad idea because inevitably one team has more hardware than they need. We bought a huge cluster and we're only using 60% of it for our, say, containerized applications. Meanwhile, we've got this other cluster that's running virtualized applications. It's 100% full, but we have another virtualized application that we need to run. In that case, the only way to do that is to go procure more hardware. Whereas when you're running things more homogeneously, one system that can handle either, you can say, "Oh, no problem. We'll run more VMs on it. " So the hardware siloing is a really big deal. And that same thing that feeds down into the networking, "I want this application to talk to this application." Well, that's complicated when you've got completely different networking solutions on the two side. Ken Kaplan: In the report, it said, "Currently, 71% are running their AI enabled applications on a mix of traditional apps and virtual machines and modern apps in containers on VMs." While 14% are running their AI enabled apps directly on bare metal servers, is that significant and is it something you see might be changing? Dan Ciruli: I think what that's pointing to is AI is, in some cases, it's an experiment. Companies are buying hardware specifically to run these AI applications. So we do see people doing that, but what most enterprises will quickly realize is that you want AI embedded in all of your applications. I'm firmly convinced that in three years we won't differentiate between applications and AI applications. We'll just call them applications. It doesn't matter if it's just a business process workflow, if it's your email, if it's your sales database, you want AI everywhere. As I said before, some of those applications aren't going to move out of a VM, which means you need to be able to figure out how to, maybe it's an API call out that is going to hit a new service, which is an agent running in a container, but you need that logic embedded in that traditional application. So there is some experimentation going on where people are just going to buy some new hardware and run AI there. In the long run, you're going to want to run your containerizer and your virtualized applications together. You will also want that to be, I'll call it AI enabled. You will want to be able to, from anywhere, embed logic that depends on maybe an agent or maybe an LLM that is independent of whether or not that original application is deployed in a VM or deployed in a container. [Related: AI Flips the Data Storage Paradigm] Ken Kaplan: Since we're on this topic, like AI agents, you just think of AI agents as another app that's probably cloud native. Dan Ciruli: Almost certainly said before, it's become the defacto ... Containerization has become the defacto standard for writing and deploying new applications. The word agentic is only about 18 months old. All of these agents are new applications. They're all being written to be deployed in containers. And so yeah, all of that. And what I think of as agents is these are AI that can do things.That's how I think of AI. In LLM, you ask it a question and answers and an agent is actually doing things. It might be validating someone else's answer. It might be going to actually interact with a system, but the agents is where AI actually does things. And yes, we have already moved from the phase of AI where I just wanted to help me answer a question too. I want it to go do a thing for me. Ken Kaplan: Yeah. I'm going to set up a playbook and have them run my playbook. And yeah, it's happened pretty quickly. All right. Here's my last question here. Does it take specialized skills to manage containers and Kubernetes and is that changing IT teams? Dan Ciruli: It still does take additional knowledge to run containerized applications, to run Kubernetes. It does mean running Kubernetes, and there are still things that you do need to learn. There's no doubt about that. In part, I think that this gets solved through education and people learning to use new tools. If you think about how the data center evolved. At some point, Linux became a pretty kind of, I won't say de facto standard, but super, super common. And people had to learn how to navigate in Linux, right? If people in infrastructure and operations. At some point, virtualization went from being a science experiment to the standard way things were networked and people had to learn the concepts of virtualization. The same thing is happening with the Kubernetes landscape and more and more people are having to learn these concepts. But the other thing I think that is happening at the same time is that as an industry, and this is someplace that we are leaning in as a company, how do we make that process easier? How do we not just say, make that easier by giving lots and lots of education, but how do we make it easier for the average operator to run a Kubernetes cluster? How do we make the tools easy to use? How do we make the tools smart so that the tools are doing more and more of the grunt work? And I think this is a case where AI already is making their lives easier. The analogy I like to use with this is when I learned to drive in the 1980s, it was very common that you knew how to change the oil in your car, certainly check the oil level. You had to know where your dipstick was. You were going to be doing that. You probably knew where your carburetor was. You definitely knew where your spark plugs were. You knew how to clean a spark plug, you knew how to replace a spark plug. [Related: Why the Future of IT Belongs to Open Systems] Not every driver did, but most did. That was just common things, right? When was the last time anyone did any of those things in their car? The car has gotten better. It is tuning itself constantly. It is so much better at operating. The car in effect has gotten mechanically smarter, and now in some cases, actually computationally smarter. Well, our systems are doing the same thing. As vendors we are trying to make just as the car is continually tuning itself, we want Kubernetes to continually be tuning itself. We don't need to teach everybody in the world to be a mechanic. We want to make this machine easier to operate. And that's a big part of where we're investing is how do we make it easier for those operations teams for all the reasons we discussed are having to run Kubernetes. How do we make it so that doesn't feel like a burden for them, but it's just another tool in their toolbox. Jason Lopez: Dan Serulli is the general manager of cloud native at Nutanix. He's also co-founder of the OpenAPI initiative, which established the universal standard for how software systems describe and communicate with each other. Ken Kaplan is the editor-in-chief of The Forecast. The forecast produced this interview. It's part of the Tech Parameter Podcast series. I'm your host, Jason Lopez. You can find articles and other podcasts at the forecast. Just go to the forecast by Nutanix. That's all one word, theforecastbynutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) ECI 2026 report shows strain between AI innovation and IT governance 17:20 no Connected Social Media https://connectedsocialmedia.com/21319/the-reality-of-todays-aging-workforce-and-the-longevity-landscape/ Mon, 30 Mar 2026 09:50:12 -0700 https://connectedsocialmedia.com/?p=21319 syndication@connectedsocialmedia.com (Connected Social Media) The Reality of Today’s Aging Workforce and the Longevity Landscape 29:26 no Connected Social Media https://connectedsocialmedia.com/21313/what-it-sovereignty-really-means-beyond-data-location-deutsche-telekom-cto/ Tue, 24 Mar 2026 09:03:44 -0700 https://connectedsocialmedia.com/?p=21313 tech leader insights to move faster and smarter. Get more stories by subscribing to The Forecast. Transcript: Andreas Eisenreich: So welcome dear architects, strategists, and decision makers. You have arrived where the rules are being rewritten. The utopia of a borderless internet where one click deployments were possible and any location in the cloud is slowly dissolving. The IT galaxy is becoming more complex, more political, and yes, a bit more uncomfortable. But on very, don't panic. We have long lived in a kind of autopia. National borders didn't matter to us. Infrastructure was global and deployments could be distributed across the globe with a single click. The location was just a variable in a conflict file. That error is coming to an end. The topic of serenities, unfortunately, not just an abstract buzzword, but a real challenge. The impact on us as the IT industry is hard to foresee. After all, we all had the same access to technology, no matter where we in the world and almost regardless of the available budget. The democratization of innovation and technology has made us significantly more agile. Personally, I'm more of one learning by doing guy. So the impact this will have on my way of learning, for example, remains to be seen. [Related: Data Sovereignty Drives Enterprise IT Decisions]  Jason Lopez: That's Andreas Eisenreich, reading from his 2025 LinkedIn article entitled IT Sovereignty: The Hitchhiker's Guide for Architects and Decision Makers. He's the CTO for cloud and infrastructure at Deutsche Telekom. This is the Tech Barometer podcast. I'm Jason Lopez. We thought having him read from his article would be a good way to start this story about how sovereignty is now a top concern. You need a way to define it before you can make a good decision about it. And firms like Gartner, IDC, and Forrester are now treating this as a primary market force, not just a footnote. We talked to Andy shortly after his team worked with Nutanix to develop a sovereign data solution for hybrid cloud. In our interview, he began with this. Data sovereignty isn't just about where your data lives. It's about whether you can actually use it without a vendor's permission. He reminds his clients that physical control means nothing if your data is locked in a proprietary format that becomes inaccessible the moment you lose a license. Andreas Eisenreich: Phase one, let's try to free up your data. And that's not super hard, but most of the time users are involved. Jason Lopez: A good example, he says, is Microsoft 365. The moment you commit to any proprietary platform is the moment your data sovereignty journey and your responsibility to protect it begins. Andreas Eisenreich: We all use it. We love it. We are partnered with Microsoft, great partners. I love the product, but that has to be an option. So if I decide I want to go with Microsoft, my responsibility from that point in time, that's the beginning of a sovereignty journey when it comes to data. [Related: AI Trends in 2026: Finding the Right Compute Platform] Jason Lopez: Andy pointed to the idea of making fully informed decisions about how data is stored and who ultimately controls it. The moment someone else holds the encryption key, regardless of what they call it, you don't own your data, you're just borrowing access to it. Andreas Eisenreich: If there's someone telling you, "Yeah, that's now your storage box, that's completely sovereign. Just place it in your office, you're able to access your data at any time, no problem." From a technical implementation perspective, the data are encrypted and the encryption key is part of their license model. That's the opposite of an informed decision, so that's a problem for sovereignty. But as long as you are able to understand the implications and take that informed decision, for me, that's sovereign. [Related: AI Sparks Rise in Shadow IT] Jason Lopez: And he goes on to say, "True sovereignty isn't even necessarily about open source or open formats. It's about how understanding exactly what you're agreeing to and making that choice with your eyes fully open." Sovereignty may feel like a new buzzword, but the underlying struggle, who controls your data and on whose terms is as old as IT itself. Andreas Eisenreich: Look at a bunch of non-functional requirements. Things like the European Sovereignty framework that they just released, they might help us to somehow have a common ground to start the discussion around that. But at the end, it's non-functional requirements. And as all architectures, I mean, they're not just built, they're maintained. If you start with something like your own infrastructure based on Nutanix down in your data center, that might be version one. It ticks all the boxes when it comes to your understanding of Serenity, but bring that then to version two, where you have to tick all the boxes as well, but maybe with another technology. And that is where it becomes interesting on a lifecycle perspective. And exactly for that point in time, we have to be ready as a service provider to take over the workload from those platforms into something more capable, I would say, to somehow stick to the promises, to the values that cloud gives us these days. [Related: Tension Mounts Between Supply Chain Challenges and AI Adoption] Jason Lopez: Sovereignty has become one of the biggest trends in tech, but Andy says too many people don't ask enough questions, and in fact, often only ask the one we began with, "Where does my data live?" Andreas Eisenreich: That's not the point. Serenity is all about being able to act according to your strategic goals, to your values. Jason Lopez: But true sovereignty encompasses far more than simply knowing which legal jurisdiction your data happens to reside in, and it's more than just a binary choice. Andreas Eisenreich: It's not a switch that you can turn on off Sovereignty. I would say it's a scale, and it depends always where you are, what is important for you. Jason Lopez: And ultimately, your definition of sovereignty has to align with everyone else at the table. Andreas Eisenreich: That makes it super complex when we are in a service provider and client discussion. When a client just mentioned to me, "Okay, I need that sovereign." So the answer, of course, is yes, no problem. But what's the meaning of sovereign? [Related: How Kubernetes Catalyzes Enterprise IT] Jason Lopez: Andy's definition extends to SLAs, operational processes, and whether you actually have a lever to influence decisions that affect your business. For example- Andreas Eisenreich: There's patch day for your more classical infrastructure, and the provider is just telling you, "Okay, next Saturday, we patch." So that has to fit somehow to your business plans on that day. And if there's no possibility to just raise your hand and say, "Yeah, that doesn't fit, sorry, that's not a sovereign solution," even if the data is stored in your backyard. Jason Lopez: Once you've clearly defined what sovereignty means for your organization and how much influence you need across each relevant area, it makes sense to put that in writing and use it as a filter when evaluating potential partners. You can take a mathematical approach, but the challenge is that even with that kind of detail, interpretations still vary. The same criteria can look very different depending on which side of the table you're on. Andreas Eisenreich: If you see your own infrastructure service provider is running your data centers, it feels for you kind of sovereign, of course. If you share the same basic values, you have to be very open about your business goals, about your capabilities. I mean, that's something where it's easy to find out how to handle those complex topics around sovereignty. [Related: AI’s Next Wave] Jason Lopez: He says a real partnership is a foundation of mutual honesty, and that honesty has to extend to the hard questions like, "How do I get out of your solution if I need to? " If a partner can answer that openly and the answer fits your requirements, you found the kind of relationship where sovereignty stops being a problem and starts being a conversation. Andy says for a decade, the IT industry gave everyone the same answer regardless of the question, and that answer was cloud. He says clients have been told they didn't understand their own problems, reshaping their business challenges until they happen to fit perfectly inside whatever cloud offered. Andreas Eisenreich: I was tired about that, and that's true for AI use cases as well. I was really tired about that, and that is why we started with the idea of hybrid IT, where we, on one hand, have the infrastructure of Nutanix as a building block that might run on client data centers as well as on telecom data centers wherever. And so the client is able to decide per workload, so per application that he wants to run, if he wants to run that on the Nutanix stack with his premises, or just put in additional resources from the cloud, and that's completely transparent to the client. What we created together with Nutanix is a perfect example of what I want people to think about. I think the time where we do those pilots, that's over. Jason Lopez: Andreas Eisenreich is the CTO for cloud and infrastructure at Deutsche Telecom. You can read his article, The Hitchhiker's Guide for Architects and Decision Makers at LinkedIn, and he says in the piece, "Don't panic." This is the Tech Barometer podcast produced by the forecast. I'm Jason Lopez. The forecast has a treasure trove of tech articles and podcasts, and you can find them at the forecast by nutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) What IT Sovereignty Really Means: Beyond Data Location | Deutsche Telekom CTO 09:34 no Connected Social Media https://connectedsocialmedia.com/21310/do-no-harm-how-ai-helps-to-prevent-patient-harm/ Sun, 15 Mar 2026 22:01:53 -0700 https://connectedsocialmedia.com/?p=21310 syndication@connectedsocialmedia.com (Connected Social Media) Do No Harm: How AI Helps to Prevent Patient Harm 40:45 no Connected Social Media https://connectedsocialmedia.com/21307/from-automation-to-autonomy-agentic-ai-is-transforming-intel-facilities-operations/ Thu, 05 Mar 2026 12:47:15 -0700 https://connectedsocialmedia.com/?p=21307 syndication@connectedsocialmedia.com (Connected Social Media) From Automation to Autonomy: Agentic AI is Transforming Intel Facilities Operations 0 no Connected Social Media https://connectedsocialmedia.com/21302/how-ai-transforms-storage-from-passive-repository-to-intelligent-data-platform/ Tue, 03 Mar 2026 01:51:35 -0700 https://connectedsocialmedia.com/?p=21302 tech leader insights to move faster and smarter Get more stories by subscribing to The Forecast. Video transcript: Vishal Sinha: If you look at traditionally, applications and users were creating data which used to get stored in storage. Jason Lopez: As artificial intelligence accelerates, the infrastructure we usually think of, running in the background, is undergoing its most profound transformation yet. Vishal Sinha: Now, it’s the other way around. Now applications are using the data to build intelligence out of it and power those applications. So things have completely flipped in more recent days with storage. In the era of intersection between infrastructure and intelligence. We need infrastructure to run all the AI applications and workloads, and then you need data to power the intelligence for applications.  [Related: Data Management Strategies for the AI Era] Vishal Sinha: Virtualization really transformed compute. Earlier, compute was tied to a server. You had to buy a server or a desktop or a laptop to get the compute. Now, virtualization made compute portable. You could move compute around as VMs or containers. And this change really paved the way for everything software defined. So that was one big transformation that happened around 2000 to 2005 time frame. After that, the cloud transformation, that has been a big one. It has really democratized infrastructure. Today, if you want to build a new app, you don't have to build a data center to build that app. You can directly go to the cloud and build that app. Though it has created some more work, like now you have to manage the cost, you have to manage the security, you have to manage the networking. So it has added some complexity, but definitely it has made the infrastructure more accessible to everyone. And I would say the latest one is the AI. This is a brand new one. It is going to change things significantly. Even for us, the entire software stack will change to support AI. So this is still playing out. We'll see how that evolves over time. [Related: IT Leaders Modernize Infrastructure to Run AI] Vishal Sinha: AI needs data and it needs a data-ready platform. And that's where we see that in order to make a data-ready platform, you need to provide certain capabilities. First, being able to consolidate the data from different sources and bring it all together. The second piece is around making the data clean so that it can be consumed by the AI LLMs. And then the third part is providing fine-grained permissions so that LLMs learn only from the data it is supposed to. So clearly lots of transformation from a passive data repo for files, images, audio, video, to becoming a full data platform to power AI-powered applications. So that's the big change that we are seeing. Ken Kaplan: Talking about the new trends, what was it like before? Vishal Sinha: Yeah, storage was a passive data repo like where customers put their files, their pictures, their videos, their audio. So it was truly looked at as a passive infrastructure mostly for storing data. And now it's very different because now it's an active part of an AI stack like where it needs to power all these applications with the data that it stores. Ken Kaplan: So you see it more active. Vishal Sinha: Absolutely, so it's an important part of the new tech stack for AI. Ken Kaplan: Let's talk about customers and what you're hearing from them. What are their needs? Do they have some new needs they're struggling with? Vishal Sinha: Yeah, so typically I will say two categories of customers. One who are already deep into AI. For them, the AI platform, data platform, I just talked about, that's very important for them. But then there's another big set of customers who are still not there. Their problem is how to manage data at scale. Like data is doubling every 18 months and now you have to support and manage that data. So that's their number one problem. Second one that comes often is the data is now fragmented, like it's everywhere. It's at the edge in your phone, like it is in your applications, it's on the desktop. [Related: Can IT Infrastructures Meet AI Data Demands] So how do you provide a consistent operating model to manage all this data? Then security is very important, like ransomware, probably many customers have hit ransomware. So I really want to know how the system, the storage solution itself can protect the data and not have to buy a separate solution. And also the cost, like the total cost of ownership is always a very important factor. Given the growth in data, they're always looking for a much better, most cost-efficient way of storing their data. So these are, I would say, the four things that I hear often from the customers that we talk to. Ken Kaplan: Do you ever hear them say, I wish I could do this or I can't do this, but I needed to do that? Vishal Sinha: Yeah, so that we hear a lot more around the scale part. Like so today, generally most customers have different solutions for running at the edge, in the core, in the cloud, and now they have four different solutions that they are running with. And that makes it very fragmented and they say, wish I had one console, one policy that I could apply across all of this data and that would have made their life so much simpler. Ken Kaplan: Let's talk about your career a little bit. What got you into technology? What was that feeling like? Vishal Sinha: Yes, I was always fascinated by technology. I always wanted to build products that could help customers solve their problems. And for first 20 years or so, I was primarily focused on building things. And the last seven, eight years, I found it equally rewarding to take this product or products to the market and help the customer achieve the outcome that they want from these products. So this, the whole journey, which is building the products that customers love, and taking that product to the customer market, is what has been very rewarding and something that motivates me to continue with the technology space [Related: Smart Data Management is Critical for AI Success]. Ken Kaplan: And do you remember when you first started, what were some of the big challenges or exciting things that you wanted to work on? Vishal Sinha: Oh, absolutely. So I still remember those days when if you had to make an international phone call, it used to cost two dollars for one minute. Look at today, it's almost free. You can use WhatsApp and make that call. So the first one for me was the whole telecommunications shift that happened between 1995 to 2000. And I was actually in the middle of it working for a startup, which was building multi-protocol label switching to really get the service provider infrastructure more seamless. And over time, it's really brought the cost down and made everything more accessible to the end users like me and anyone else. Ken Kaplan: And when you were working in telecom, could you imagine hybrid multi-cloud, containers, VMs living together, like all the world that we're in now? Vishal Sinha: So at that time, it was all monolithic. You had one infrastructure which ran everything. We didn't have the flexibility of a VM or a container that we could move around and solve the right problems with the right form factor. I think after the virtualization, that definitely got simplified. Now we can have a very flexible, software-defined telecom infrastructure. Ken Kaplan: What's the advice that you give people to motivate them? Vishal Sinha: Learn the first principles of systems building, like don't focus only on the API layer. Understand how systems are built so that you can appreciate and you can make better things after that. The second one would be the ability to deal with ambiguity. Things are changing very fast and we have to be able to cope with uncertain things. And look at AI, for example, things will evolve and we have to be able to make progress with what we know and be ready to adapt to newer changes. That's very important. And third one is having endless curiosity. Things will change fast and if you're not curious enough, we'll not dig in and learn new things. So if we want to stay relevant, we have to be endlessly curious.]]> syndication@connectedsocialmedia.com (Connected Social Media) How AI Transforms Storage from Passive Repository to Intelligent Data Platform 08:55 no Connected Social Media https://connectedsocialmedia.com/21297/effective-ai-governance-for-organizations/ Thu, 26 Feb 2026 16:06:34 -0700 https://connectedsocialmedia.com/?p=21297 tech leader insights to move faster and smarter Get more stories by subscribing to The Forecast. Podcast transcript: Zahra Timsah: We have crossed a threshold where AI is no longer experimental at this point, right? It's kind of like an infrastructure. AI models are embedded in credit scoring, healthcare diagnostics, legal reviews. Even if you look at national defense, you have AI. They're no longer tools. They're decision makers in digital form. This is how you can think about that. When you reach that scale, governance is not optional anymore. It's kind of existential, so to speak. Jason Lopez: Zahra Timsah, co-founder and CEO of iGentic AI, asserts that the deployment of AI in an organization requires a real-time governance layer to help see what an AI system is doing. This is the Tech Barometer podcast. I'm Jason Lopez. What you're about to hear from her is a part of our Thought Leader series on AI. And while there's the debate about AI in the news headlines, at the forecast, we're going deeper, talking to technologists who are filling us in on what they're seeing in the industry and what they're working on in artificial intelligence. [Related: Shaping the Future of Enterprise AI with Intellectual Curiosity] Zahra Timsah: Ungoverned AI, and this is from experience, can create harm, like real harm. You're talking about biased hiring systems, misinformation loops, intellectual property violations, and even opaque decision paths for decision makers. They are operating in a world where every single AI decision, whether you're talking about a model output, a data merge, automated recommendation, whatever, is getting two things, opportunity and liability. Jason Lopez: She says organizations have to ensure their AI systems are transparent, accountable, and ethical. And that's why emerging regulations are rapidly shifting the conversation from optional best practices to enforceable requirements for explainability, fairness, and traceability. Zahra Timsah: If you look at regulations that are accelerating, like look at the EU AI Act, look at the US AI executive order, look at the GCC frameworks, AI governance has really evolved. It's no longer just a compliance checkbox. It's kind of a trust infrastructure. We're seeing companies kind of form AI governance councils, I think is a very good idea. And they're including in it CEOs, CIOs, general councils, and tech leadership. [Related: Measuring the Prime Ingredient in Enterprise AI] Jason Lopez: Timsah says without coordination, organizations risk managing AI through fragmented tools and disconnected processes, which will struggle to keep pace with change. Bringing stakeholders together is a great step. Zahra Timsah: You're talking about folks that specialize in GRC, governance, risk, and compliance. You're talking about legal departments, even technical experts as well. Because not only do you have people, you also have platforms. You know what they say. It's people, process, and platform. All of these are like siloed tools to manage the GRC. Jason Lopez: This is where, she says, agentic AI can deliver. And just to highlight that agentic AI isn't so much about AI agents. Agentic AI is the operating model that sets direction, plans the work, and brings team members together to achieve a larger goal. Zahra Timsah: With agentic AI, you have systems that are learning from human decisions and improving their governance reflexes. With an agent, they can run 24-7. They can handle a humongous amount of data points that a human cannot even imagine. You're getting consistent and fast results. [Related: Role of CIO Expands with Enterprise AI] Jason Lopez: In this model, AI becomes an active oversight layer rather than just a passive reporting tool. Instead of waiting for periodic reviews, leaders can monitor performance, detect risks, and respond to governance issues. Zahra Timsah: Let's imagine a boardroom. You have executives, and they can see their entire AI landscape in front of them as a living system. This is what agentic AI can provide. Models that flag when, let's say, some sort of an AI system is drifting out of ethical or regulatory bounds. Privacy agents can mask PII, cyber agents detecting anomalies, and the list goes on and on and on. It's governance that's talking back to you. Leaders can ask it questions, and then they can give you back answers quickly, not generate reports like humans would do with the answers hidden in them. Jason Lopez: It moves governance efforts from static oversight to real-time awareness. But every organization interprets risk differently. Zahra Timsah: There is no such thing as one-size fits all. Every company has its own risk appetite, understanding, and interpretation of these regulations. Then you have a team that's going to review the regulations and try to understand what they mean for your company. Jason Lopez: Timsah says internal expertise remains essential. Even with advanced automation, meaningful oversight still depends on people. Zahra Timsah: You always have to have a human in the loop. Always. Just like you're driving a Tesla, and it can just drive itself. But you can also receive guidance so that you are the decision maker. You, as a human, is a decision maker. Agentic AI is powerful, and it can get rid of mundane tasks. But you will still generate errors, and there is nothing that can replace human experience. Jason Lopez: And here's a part of the story that underlines what she says. Zahra Timsah did not arrive at agentic AI from a computer science trajectory. She came up through healthcare, studying cancer biology and drug discovery. She did postdoc work at places like the MD Anderson Cancer Center, and she discovered that personalized medicine was becoming too complex for manual analysis. Early on, she got involved in healthcare AI technologies, and one of her goals was to design and test patient-specific therapies using neural networks. Zahra Timsah: What we're doing is creating a digital nervous system that's uniting ethics, risk, and intelligence into one living operating system. [Related: Data Protection Gets Its Uber Moment] Jason Lopez: It's about embedding governance directly into how AI systems operate, so oversight happens continuously rather than after problems arise. Zahra Timsah: Agentic is really the world's first agentic AI operating system for governance, and it didn't take us a day or two, a month or two to build Agentic. It took us 17 years of experience to fine-tune these agents to act on our experience as founders to achieve the results. It's a platform where you have autonomous agents, but these are in reality digital chief compliance officers that can monitor in real time, which a person cannot do, enforce, and even learn, you know, like you're learning compliance, whether that relates to AI, data, privacy, and cybersecurity. So it's running 24-7, and it's instant. It's proactive. It's not reactive. So these agents think of them as intelligent layers of oversight. That's what we're doing. So everyone who's touching or benefiting from AI carries responsibility. Governance cannot be delegated to a single compliance officer, or you can't bury it inside IT. Jason Lopez: Zahra Timsah is the co-founder and CEO of iGentic AI, a governance platform that uses AI agents to manage and enforce governance, risk, and compliance. Our story with her is part of The Forecast's reporting on thought leaders in the AI industry. You might check out some of our stories from other thought leaders, such as our profile of Greg Diamos. Go to theforecastbynutanix.com. That's all one word, theforecastbynutanix.com. This is the Tech Barometer Podcast. I'm Jason Lopez. Thanks for listening.]]> syndication@connectedsocialmedia.com (Connected Social Media) Effective AI Governance for Organizations 8:01 no Connected Social Media https://connectedsocialmedia.com/21294/cost-effective-and-scalable-infrastructure-for-genai-workloads/ Thu, 26 Feb 2026 01:12:23 -0700 https://connectedsocialmedia.com/?p=21294 syndication@connectedsocialmedia.com (Connected Social Media) Cost-Effective and Scalable Infrastructure for GenAI Workloads 0 no Connected Social Media https://connectedsocialmedia.com/21290/modelops-cto-on-strong-governance-is-essential-for-agentic-ai/ Wed, 25 Feb 2026 10:22:12 -0700 https://connectedsocialmedia.com/?p=21290 tech leader insights to move faster and smarter Get more stories by subscribing to The Forecast. Podcast transcript: Jason Lopez: How do companies control, govern, and deploy AI safely at scale? When Jim Olsen, the Chief Technology officer at ModelOp, talks about AI adoption, the theme of what he says rests on the idea of restraint. Jim Olsen: Try not to just build things for the heck of it. That's why you have to tie all this back to a use case to understand, what is my goal and what does success look like? If you don't have a clear process in place everybody can understand and follow, then you lose that trust, and the solutions just don't happen. That's, of course, a missed opportunity. If you have a truly resilient agentic system, it can adapt to new business needs, new things that just pop up. Given that autonomy, how do you actually control and make sure it doesn't disclose all your user passwords? Jason Lopez: This is the Tech Barometer podcast I’m Jason Lopez. This story is part of our ongoing thought leader series with people at the cusp of AI technological development, like Jim Olsen of ModelOp, a platform that helps govern, monitor, and manage AI and machine learning models to ensure they are compliant, reliable, and aligned with regulatory and ethical standards.  Agentic AI is the operating model that sets direction, plans the work, and brings team members together to achieve a larger goal. When you talk to Jim Olsen, before he gets into the AI conversation, he’s laser focused on why you need it in your organization. What’s the use case? Jim Olsen: If you can actually get agents to automatically do that stuff and do it reliably, it obviously increases the success of your business at its core. That's why it really comes down to what is your business value, what is your use case, and the success is going to look very different based on that. Ultimately, my business is successful, everyone's happier, and I've reduced my overall costs. Jason Lopez: But that promise only holds if the system performs as expected. The models need to be trusted and safe. Jim Olsen: The nature of generative AI is that it does go out and perform differently based on very minor changes or even sometimes no changes at all. If you don't have some insight into that, naturally, people are concerned and paranoid about what could happen. You need that clear, transparent process in place in order to build that trust that we can see what's going on. We do know we've put the research in behind this to make sure it's going to behave okay. Jason Lopez: Olsen says that while a clearly defined use case is the bedrock of an organization’s deployment of AI, another critical part of the strategy has to be managing AI’s behavior. Jim Olsen: When you use these tools or allow people to use these tools, what impact that could have? What kind of information could go out? What kind of information could come in? What kind of damage could be done? So you need an approval mechanism in place to actually do that. You do need some automated process in order to scale this in an appropriate manner, because what you really need to know is, okay, what are the use cases out there that need to use agentic AI? Is it appropriate for them to be using agentic AI? Then what pieces are they using? What tools? What model? How many tokens are they actually using? Are you getting your value back out of your investment in these areas? You do need to track all of this information. You do need some approvals in place to make sure you have that process to do that. You can try to do it on a spreadsheet or something like that. We see that quite often, but we find that really gets lost. Jason Lopez: One of those mechanisms is MCP, or Model Context Protocol, an open protocol designed to let AI systems securely connect to external tools, data sources, and services in a standardized and predictable way. Jim Olsen: But now you introduce these MCP tools and true agents that can act autonomously. How do you ensure that they only have access to the tools and data that they're supposed to? That's where one piece we're providing that we saw a lot lacking that ties directly into our overall automated approval process is an MCP gateway slash proxy that only allows specific use cases to use specific tools and blocks access to tools otherwise, so that way you know what they're being used. As A2A gets in there, we're going to see even more pieces that need to go in there and monitor and understand what's going on. Jason Lopez: Olsen says he’s seen cases of MCP tools that have access to a company’s proprietary information. What ModelOp does is essentially act as a control plane AI across an organization. It provides insight into what MCP tools are doing, where they’re enabled with agents, AI models, workflows, and governance. Jim Olsen: What we've done at ModelOp is we've actually created that kind of a gateway or a proxy where you can deploy approved tools and actually monitor what use cases in your organization use those, and are they approved to use those tools, and block them if they aren't, and put protections in place that can do things like detect PII and say, hey, you can't send PII out of our company, these kinds of things. You can get some control around these MCP tools and understand their usage. Jim Olsen: Reducing costs, increasing customer satisfaction, increasing accuracy of processes, et cetera, are all kind of standard business goals that a true agentic system can deliver on by being adaptable. Jason Lopez: Jim Olsen is the CTO of ModelOp, a software platform that helps organizations govern, manage, and scale AI systems responsibly. This is the Tech Barometer podcast, I’m Jason Lopez. We’ve got some other great stories in our thought leader series on AI. Check out our profile of David Kanter, co-founder of ML Commons. That’s at theforecastbynutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) ModelOps CTO On Strong Governance Is Essential for Agentic AI 6:19 no Connected Social Media https://connectedsocialmedia.com/21288/crafting-the-story-communicating-with-impact/ Tue, 24 Feb 2026 11:03:36 -0700 https://connectedsocialmedia.com/?p=21288 Second Opinion Media, to explore why the art of storytelling is a crucial skill for all companies to learn, and how it can be particularly helpful skill for health and well-being leaders to more effectively communicate – and drive impact. Employers will learn the importance of showing up with authenticity and empathy and how to use storytelling strategies to support big benefit changes and transformation in health care. Guest: Christina Farr, author of The Storyteller's Advantage: How Powerful Narratives Make Businesses Thrive and editor in Chief and CEO of Second Opinion Media]]> syndication@connectedsocialmedia.com (Connected Social Media) Crafting the Story: Communicating with Impact 37:50 no Connected Social Media https://connectedsocialmedia.com/21282/hycu-ceo-simon-taylor-podcast-interview/ Thu, 12 Feb 2026 14:16:52 -0700 https://connectedsocialmedia.com/?p=21282 HYCU CEO Simon Taylor takes listeners into the mind of a creative, disruptive entrepreneur who’s turning data protection into an AI-powered arsenal against cybercrime and ransomware attacks. Get tech leader insights to move faster and smarter Get more stories by subscribing to The Forecast. Podcast transcript: Simon Taylor: I was in a bar in Las Vegas and I happened to bump into an engineer that I'd known from Slovenia and I said, what are you doing now? And he said, I'm in the data protection space. I was trying to prove to him that data protection was this sort of old, ugly, fugly world that no one would be interested in because it was so old school, it was in the plumbing, who cares about it? He said, Simon, how did you get here today? So what do you mean? Did you take a taxi? No, I took an Uber. He said, aha, but there's no Uber in data protection. It struck me that if you want to truly disrupt the marketplace, you need three different things. Jason Lopez: Simon Taylor is the founder and CEO of HYCU. This is the Tech Barometer podcast I'm Jason Lopez. HYCU is a data protection company and its name is spelled H-Y-C-U. There are ways to construe Japanese poetry with data protection, but the truth is the pronunciation, haiku, is an unintended benefit of the acronym. Simon Taylor: Hybrid Cloud Uptime, that's where the name really comes from, H-Y-C-U, Haiku. Jason Lopez: Taylor says HYCU was launched on the idea of making it easy to back up and recover data of disparate elements in enterprise computing. Simon Taylor: We're called Hybrid Cloud Uptime, H-Y-C-U, Haiku, for a reason, because we believe in the power of on-prem and the power of public cloud. And we want to make sure there's a seamless transition, whether you're going one way or the other. Jason Lopez: But before we go forward on that, let's complete Taylor's thoughts on disrupting the marketplace... you need three different things. Simon Taylor: You need a technology that is sort of used by all and liked by none. Two, it's got to be something that is highly commoditized. And three, it's got to be something that is truly undisrupted in this space. In other words, nobody's gotten there before you. [Related: Nutanix CEO Stokes Surge in IT Ecosystem Partnerships] Simon Taylor: AI is here, it's here to stay, and it's only going to get better because that is the nature of things, the nature of technology. Jason Lopez: Taylor likes to talk about AI not so much in terms of the technologists who create it, not from the economist's point of view, or from the hype in the news, but as he describes it, as a kind of energy customers have for their vision of how it can benefit their businesses and products. Simon Taylor: I kind of break down AI into three proof points, humanity, exceptionalism, and resourcefulness. So humanity, is it good for human beings? It seems really odd, but at the end of the day, we are humans. And so the only kind of AI I care about is that which is good for human beings. The second one is exceptionalism. It's how do we leverage AI in our daily work to make sure that we're not falling behind, and in fact that we're getting ahead. And the last one is resourcefulness. How can we be resourceful in terms of driving more value to our customers? Jason Lopez: This is where he moves from a guiding philosophy of humanity, exceptionalism, and resourcefulness into technical reality. How is it possible to better support IT services that live across on-prem and public clouds? Simon Taylor: You've got your data in so many different places. You've got data that you're spinning up and spinning down. It's all containerized. And I think it takes modern platforms to be able to support that. HYCU is supporting 92 services across on-prem, public cloud, and SaaS. That's more than 12 times any other data protection vendor in the marketplace. HYCU's customers are able to stitch together the fabric of all of their data across 12 times more data silos than anyone else. You're going to see a lot more coming out of HYCU in the coming months where we talk about the AI fabric that's going to add tremendous value to HYCU and to Nutanix as well. [Related: Clouds With Borders: IT Teams Design for Geopatriation] Jason Lopez: Taylor's key message is HYCU isn’t just backing up data, it’s creating a unified view of everything.  And AI can turn that big picture into powerful insights. Simon Taylor: I've always thought of HYCU as a giant patchwork quilt. How are we going to help our customers to process and manage all that data? That's a lot of different data silos. So we went out and we said, it'd be great if you could almost click a button, discover your environment, and then visualize where all that data is. And we call that Rgraph. So today we have an observability tool called Rgraph that will allow you to visualize every element of your data estate across on-prem, public cloud, and SaaS. So that's fabulous. I think in a pre-AI world, that's done a tremendous amount. Now I want you to imagine that that data protection toolkit can extend even further. I want you to imagine you can overlay AI across all of that. What I'd love you to just imagine is what could you do if all of the data across on-prem, public cloud, and SaaS was linked together with AI? When you combine what we do with SaaS, what we do with cloud, what we do with Nutanix, all of a sudden you can build a far more sophisticated picture of what your world actually looks like. And from that, you can leverage AI to do a whole lot of very, very interesting things. [Related: Turnkey IT Platforms Unlock Enterprise AI Success] Jason Lopez: Simon Taylor describes himself as a serial entrepreneur. Simon Taylor: I would have started a fleet of ice cream trucks if the mood took me. Jason Lopez: In his 20s he liked to write business plans in his spare time. And he says these plans weren't tied to a technology but were about almost anything. Simon Taylor: Ultimately, I came up with an idea for an e-sourcing and e-discovery tool that would allow you to cut the time, money, and resources involved in recruiting outsourced engineers. I decided that to do that, I needed two things. I need to build an algorithm matching engine that would allow me to do that matching. And two, I had to build a database of great engineers. I felt that there was an untapped resource in Eastern Europe for incredible engineering talent. I'd read a lot about it. I'd never been there. I don't have any familial links, didn't speak the language. But I knew two things. I knew that there was a lot of engineering talent there, and that it was a heck of a lot cheaper than the United States. So I raised a little bit of cash, sold what little I had. I moved to Prague in the Czech Republic, hired an engineering team, and I got to work. Then I started traveling. I went to Estonia, Latvia, Lithuania, Romania, Bulgaria, Serbia, Slovenia. Everywhere I went, I was building out this database of engineers that then went into the product. [Related: How Ivy League Dartmouth College Moved to a Future-Ready IT Platform] Jason Lopez: The experience was so profound, Taylor says when his son talks about the future -- where to go to college, what to major in -- the advice was: Simon Taylor: Just go overseas. Go international. Try different things. The more diversity you can bring into your life, the more you can open your eyes to different experiences, I think the better off you're going to be. Simon Taylor: How expensive is it from a time, money, and resources perspective to execute an attack on an innocent victim? Jason Lopez: He says we've moved past the era of human hackers typing commands into a terminal. We are now in the era of agentic AI, where a hacker sets a goal, such as to find a CEO's personal emails and the AI does it autonomously. In the past, you could spot a phishing email by its bad grammar or slightly off tone. AI eliminates those red flags. And the cost to hack has plummeted. Simon Taylor: It used to be $100 to execute a white glove ransomware attack on the dark web. Today, it's $1.50. When we first started this, people said that 90% of their ransomware attacks and all of their cyber threats were occurring through on-prem data. Today, 50%, according to our study of state of SaaS survey, 50% of those who responded said that their most recent ransomware attack or cyber attack occurred through SaaS and cloud. So all of a sudden, we're seeing this massive shift, and that is happening because of AI. We're seeing better phishing attempts. We're seeing social engineering that we couldn't have imagined years ago. Right here in my office the other day, somebody got a voicemail from me that sounded like me asking for gift cards. [Related: Mastering a Myriad of Databases in the AI Era] Jason Lopez: But it goes both ways. AI gives security teams an advantage they’ve never had before with the ability to triage millions of data points across cloud, on-prem, and SaaS apps in seconds. Simon Taylor: What we're starting to see now is that it's becoming cheaper for us to innovate on the side of the defenders, where we can leverage prompt engineering, we can leverage tools like Cursor and IntelliJ, we can build products faster, more swiftly, more adeptly, and we can go after these guys. We can do it aggressively, and we can do it at a fraction of the cost. When I looked at the history of data protection, you have companies like Veritas backing up Unix years ago, and then you had Commvault for Windows, you had Veeam doing VMware. But when we really thought about the fragmentation of data protection across on-prem, public cloud, and SaaS, nobody had really looked at it from a holistic perspective.  We set out to look at how you could bring together all these different elements of the modern data estate and make it incredibly easy to backup and recover the data almost as simply as you would on an iPhone with iCloud backup. Jason Lopez: Simon Taylor is the founder and CEO of data protection company HYCU, a data protection company based in Boston. This is the Tech Barometer Podcast produced by The Forecast, I'm Jason Lopez, thanks for listening. If you want to take a deeper dive into this story, check out David Rand's piece for The Forecast, entitled "HYCU CEO Simon Taylor Brings Order to Data Protection Chaos." You can find that and more stories on technology at theforecastbynutanux.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) HYCU CEO Simon Taylor Podcast Interview 10:29 no Connected Social Media https://connectedsocialmedia.com/21279/business-benefits-of-running-dbaas-in-an-open-source-virtualized-environment/ Thu, 12 Feb 2026 13:57:31 -0700 https://connectedsocialmedia.com/?p=21279 syndication@connectedsocialmedia.com (Connected Social Media) Business Benefits of Running DBaaS in an Open-Source Virtualized Environment 0 no Connected Social Media https://connectedsocialmedia.com/21276/how-agentic-ai-reconfigures-customer-service/ Tue, 10 Feb 2026 17:36:00 -0700 https://connectedsocialmedia.com/?p=21276 tech leader insights to move faster and smarter Get more stories by subscribing to The Forecast. Podcast transcript: Henry Iversen: With agentic AI now, you can see much more use cases around actually executing, not only understand a question and react to that, but also look at the sequence of things and help the customers or employees to make sure that they get an amazing experience. AI technology can open up opportunity to actually have one-to-one relationship with the customers at scale. Jason Lopez: Henry Iverson is a co-founder of Boost.ai. The company builds conversational and agentic AI platforms that let organizations automate customer services through human-like dialogue. This is the Tech Barometer podcast produced by The Forecast. I'm Jason Lopez. As artificial intelligence continues to evolve, agentic AI is on the road to genuinely reason and do complex tasks. Iverson, who The Forecast reached out to for his AI thought leadership, says this shift could redefine how companies implementing AI get the right balance of people leadership and technology. But it's not that simple. It requires coordination between executives, technologists, and business teams to align on what AI should actually do. And one thing it should do, he says, is bring different apps and tech together. Henry Iversen: How can we consolidate them? How can we maybe remove some of them? But I think with the new AI technology, it represents the opportunity to have a new interface. And you should get the same experience. I think the multimodality is also extremely important. I want to have an opportunity to talk to my organization, my local bank, my local insurance company, and then continue the conversation on phone, on chat, or whatever, where I need to. [Related: How Kubernetes Catalyzes Enterprise IT] Jason Lopez: The picture that comes to mind is the anecdote of changing a tire while the car is still moving. Iversen says the biggest challenge is things are moving very quickly. Henry Iversen: Even on a weekly basis, there's new models coming out, new large language models performing better and stuff like that. So there's obviously a lot of things going on in this space, which again also have kind of implication in terms of like, when do we get access to the model? What is the privacy around that? How do we need to think about like actually implementing this in my own kind of call center? So there's a lot of things which is also outside the bigger ecosystems. Jason Lopez: With new language models emerging almost every week, the technology is evolving faster than most organizations can adapt. And that constant change doesn't affect just the tools themselves. It reshapes how companies think about scale, privacy, and the entire structure of their customer operations. Henry Iversen: AI can handle thousands or millions of interactions. One of the challenges now is just how do you put together kind of the future of your contact center or customer engagement at scale with all the moving parts? [Related: Game Hosting Companies Unsheathe AI and Cloud Native Tools to Combat Cheaters and Cyberattacks] Jason Lopez: Perhaps a deeper question is how the organization works with AI. It's a given. No one is under the illusion that AI just magically works. It takes effort. And that begins with getting executives, IT, and business teams on the same page to implement and use it. Henry Iversen: Being able to really align the organization in terms of what is the needs of the future is pretty hard, I think. What I've seen so far is just make sure you can have those alignment early on with the executive leadership, but also the tech and the CIO also involved. Because everyone has different perspectives, but you really need to have that alignment. I think another key consideration you need to make is also, okay, are we going to operate and manage these systems over time? Some of these systems already out there is built for technical people. And then how do you scale up with that internally where you maybe want to have a bit more kind of a no-code interface? The business is definitely extremely important, that the business is a key part of this. Jason Lopez: On the technology side of the equation, the company's cloud infrastructure is vital. Iversen says cloud-based systems are essential to enable AI models to function effectively. Henry Iversen: For everything we do, it needs to be available in a cloud because a lot of these kind of generative systems obviously needs to have access to information quickly to make sure that everything works between the clouds so you can make sure that you reduce the latency. Then also you need to manage the costs. So having a vendor which can actually manage and make sure that the cost is not taking off is also extremely important for the overall business case for it. [Related: Shaping the Future of Enterprise AI with Intellectual Curiosity] Jason Lopez: But as critical as the IT side is, he says the business vision should drive AI partnerships and architecture. The starting point isn't speeds and feeds, but rather the organization's business goals. Henry Iversen: How do we envision the future of customer service should look like? You can also then start reverse engineering what you need to do to get there. And we also need to realize that some things are going to change along the way, but that's okay. But it's super important to have this kind of North Star where we know where you're all headed. And that also brings a lot of kind of clarity but also alignment into the organization. Jason Lopez: It's one thing to imagine the future, says Iversen, to map out that North Star and picture customer service. But at some point, vision meets reality. And that's where an important question comes in. Does it make sense from a financial point of view? Henry Iversen: There's a lot of cool stuff we could do, but again, there's also a cost element to it. But I also think it's just extremely important to make sure that, okay, what level of support and experience are we going to bring out to the market? One overlooked possibility and opportunity with agentic AI is also that you can do something you haven't done before. I have one example actually from a bank where they offer new services because now they can use, say, agentic AI to handle a lot of the workload of offering that service. Some service could be made available from customers, but it's just too time-consuming. Another example could be, I could potentially, if I have one million customers, I could potentially call all of them. But again, that would probably not be very scalable if I'm the CEO of a bank to call every customer. But with AI technology, you can open up an opportunity to actually have that one-to-one relationship with the customers at scale. We can obviously automate existing processes with agentic AI, but for me, it's more like, okay, how can we open new opportunities with agentic AI? [Related: Bridging the Gap Between AI’s Promise and Fulfillment] Jason Lopez: And that question of how AI can unlock new opportunities rather than automate the old ones leads to a deeper point. Because innovation isn't only about efficiency, it's also about elevating the experience. As Iverson explains, the real challenge is to use these new tools not just to do things faster, but to do them better for customers and for the people who serve them. Once AI agents start acting with a degree of autonomy, the question becomes, how do you guide them responsibly without holding them back? Henry Iversen: Yeah, that's a good question. And I think one element which is extremely important as you start scaling these systems is that you're going to have a lot of these AI agents. You want to make sure that you have the level of control, but you also need to make sure that there is a level of autonomy into it. Because you can imagine if you have hundreds of AI agents in the same way as you have humans, you're not going to be able to have control on every action they do. So you need to make sure that they can do that within a controlled space, but also being open that, okay, if there's a thing I'm unsure about, then I should maybe ask you for approval. So make sure that you have the human in loop for some of the questions coming in. Jason Lopez: Finding that balance between control and autonomy brings the human into focus. As AI takes on mundane tasks, the role of people becomes less about managing volume and more about creating meaning. It's a shift Iversen says will be essential to how organizations design the future of their customer experience. Henry Iversen: There's always going to be customers needing to get help from a human. But I also think that back in the days when we started kind of doing all the simple inquiries to chatbots and we gave all the complex stuff to humans, we thought that that was a good thing because all the simple stuff, humans don't want to go answering those things. But what we learned is there was some burnout in some of the people on the customer service because all the complex stuff was obviously, you need to use your brain extensively to kind of solve those. So I think just finding the right balance of things you need to kind of route through to humans is going to be pretty essential to make sure that they also support customers. Jason Lopez: Henry Iversen is co-founder of Boost AI, a company that was founded in Norway. It builds conversational and agentic AI platforms. This is the Tech Barometer podcast produced by The Forecast. I'm Jason Lopez. You can check out more technology stories. We have them at theforecastbynutanix.com. That's The Forecast webpage. Again, that's theforceastbynutanix, all one word, dot com.]]> syndication@connectedsocialmedia.com (Connected Social Media) How Agentic AI Reconfigures Customer Service 6:43 no Connected Social Media https://connectedsocialmedia.com/21274/from-climate-crisis-to-the-cradle-safeguarding-pregnancy-and-birth/ Mon, 09 Feb 2026 00:01:20 -0700 https://connectedsocialmedia.com/?p=21274 syndication@connectedsocialmedia.com (Connected Social Media) From Climate Crisis to the Cradle: Safeguarding Pregnancy and Birth 26:53 no Connected Social Media https://connectedsocialmedia.com/21270/how-ai-is-supercharging-software-development/ Thu, 05 Feb 2026 13:24:04 -0700 https://connectedsocialmedia.com/?p=21270 Pendo CEO Todd Olson explains how AI is reshaping how teams work and how it helps tackle time-consuming, complex tasks. Pendo’s Software Experience Management platform has helped companies like United Airlines, Morgan Stanley and iRobot optimize software performance by identifying issues, streamlining workflows and enhancing usability. To keep it running smoothly, Olson said his engineers now spend more time reviewing AI-generated code than writing it from scratch. With AI changing not just development techniques, but also the dynamics of software teams, Olson is adjusting to a new paradigm and encouraging others to do the same. “Everyone needs to rethink their role and how they can do it differently,” Olson said. Find more enterprise cloud news, features stories and profiles at The Forecast. Podcast interview transcript: Todd Olson: How do you know… There are certain tasks we’re hardwired not to even try because they’re long and painful. That’s where AI can do things really, really easily. AI’s not eliminating all thinking that would be a scary and dangerous place for a lot of folks. It’s just shifting how we work. Jason Lopez: These days we can see that shift with developers who spend less time writing code and more time reviewing what AI generates, while designers and product teams are using new tools to prototype and test ideas faster than ever. This is the Tech Barometer podcast produced by The Forecast, I'm Jason Lopez. Todd Olson is the co-founder and CEO of Pendo, a company based in Raleigh, North Carolina, which helps developers and product managers make their software more effective and intuitive to use. They do this by integrating into software solutions and AI has become a growing component of that. Olson spoke with us about how AI is reshaping how teams work, especially tackling time-consuming complex tasks. [Related: HYCU CEO Simon Taylor Brings Order to Data Protection Chaos] Todd Olson: I was talking about this with a few developers recently, is simulating user behavior. Testing can be very, very difficult, but creating real and simulated environments can be just prohibitively expensive and very, very difficult. But it could be very easy with AI. AI can just generate fake users, fake data, whatever. You give it some level of parameters and boom, it's going to go off and go do it. Jason Lopez: Olson says that hand coding systems for that kind of task would be much more painful. But with AI, a full simulation is far more efficient than manual testing, and opens up new ways to approach development. It expands what’s possible in the work itself and sparks new ways to collaborate for hybrid teams. Todd Olson: We're seeing team members share very openly, wow, look what I did with this. And then another team member saying, wow, I can apply that to my own work and get all this sort of productivity benefits out of it.  I mean, a ton of our folks are recording Loom videos and posting it places and saying, here's a video of me using AI to solve and experiment with this problem. Have a look. And people are commenting and experimenting. And I just think this is a really exciting time for a lot of folks. [Related: Is Your AI Data and Infrastructure Audit Ready?] Jason Lopez: That spirit of experimentation isn’t just cultural — it’s changing the work itself. Developers are finding that AI doesn’t replace their jobs, but rewrites the way they do them. Olson says it’s less about writing code from scratch, and more about refining what the machine produces. Todd Olson: I was talking with our CTO and we were talking about thinking in terms of, yeah, if I had done this without AI, I could have written this code in say four hours versus AI is going to spit out the code. And then I'm going to edit, review and adjust it for maybe one hour. So that's a, well, it's a two hour savings if I'm looking at it that way, but it's also a difference in skills, right? And you still need to have critical thinking skills because you need to understand if, if what the AI generated is correct, whether it actually meets the, the intent of what you're trying to do. Jason Lopez: AI isn’t taking human thinking out of the equation, it’s changing what we think about. Developers spend less time writing raw code and more time improving what AI creates. And, Olson says, people are rethinking their roles. Todd Olson: We have designers, we have product managers, we have sometimes QA, sometimes not, but someone more focused in sort of the quality testing side. We have obviously developers themselves. I think we're seeing AI sort of break down a lot of these walls and redefine what these roles actually mean. Like, like a really good example is actually in terms of designers, you know, designers historically, you know, obviously they, they would create everything from prototypes to they want to validate with customers. Now they're using it via prompt. They can essentially generate an entire working application, you know, with, with, without having to, to lean on a developer or anything to that degree, much, much, much faster. And then get that prototyped application in front of customers much faster and get sort of much better feedback and much faster than they've ever been able to do before. And then when they're collaborating with, with engineers, they can actually pass them a prototype and say, you know, Hey, this is kind of what I built. It kind of looks like this. Let's tweak this. Let's do this. Let's make sure it's scaled. Like it's a different style of working. [Related: Get Tech Insights to Move Faster and Smarter] Jason Lopez: He also points out that to make real progress, companies need to give teams time and space to experiment, learn, and discover where AI can truly make a difference. Todd Olson: We're working on a project now to internationalize our products. That's taking our products and making it available in different, different languages. That's historically a very painful project. You know, you have to look for all the hard coded, essentially word string texts throughout your application, replace that with sort of an API call based on like, you know, geography.  That's actually a really good task for AI. And we've, you know, it, one thing from a change man perspective is, but if I went to my team and said, I need you to use AI for it. How long is it going to take? They've never done it before. They don't know Adam. So what we needed to do is say, okay, we'll give you a month to play around with AI and test it and prototype it for this, all this problem. Then tell us what it's going to take now. So we gave them, we carved out time, we let them experiment. And then they came back and told us they can cut the estimate in half. Well, that's a pretty good ROI, but if I hadn't given them that time to experiment, they wouldn't have actually known. So I think every company from a change, like they need to give their team space to try things out. It's not just saying you must use AI. It's give them space to like really play with the technology to learn from it. [Related: Nutanix CEO Stokes Surge in IT Ecosystem Partnerships] Jason Lopez: That kind of space can also depend on where the work gets done. And that’s increasingly in the cloud, where the newest AI models live and evolve. Todd Olson: The cloud's hugely important. Most of the foundational models are delivered via cloud infrastructure. So whether, I think the interesting thing to consider is that different models need to be better at different tasks. For example, most of my engineering team, when they're doing any level of like code assistance or using anthropics models, cloud, especially a lot of the more modern, newer models. And what we're seeing is the pace of innovation and change, like you want to be using the latest models. And like the models today, in some cases are significantly better than models six months ago. So like making sure you're constantly trying to like use the same thing is sort of like top of mind. But yet for other roles, like non-engineering roles, non-code generating roles, we're seeing OpenAI or ChattVT be the dominant decision. Again, both of these are delivered via cloud solutions. So I think cloud's going to be important. Now, look, we have some customers that are very concerned around sharing their data with the cloud. So when I'm building products and I'm using these, I think one, you have to be very transparent about what models and infrastructure you're using. Two, you certainly think about building in flexibility of potentially calling self-hosted models, which would be potentially open source models, think Metaslama or even things like DeepSeek. I think we're seeing more people like think about leverage of those, which would be, again, you're using a third party, but it's open source and it's hosted by yourself versus a third party hosted model. But I also think there's gonna be opportunities to like, at least for us, use our customers' models. [Related: Turnkey IT Platforms Unlock Enterprise AI Success] Jason Lopez: Many of Pendo's customers have invested heavily in developing their own AI models, trained with their own data and context. The question Olson raises now is how they can design applications that tap into those customer built models instead of hosting everything themselves. But if there's a guiding principle that emerged in our conversation with Olson, it goes back to his strong belief that we're still in a wide open learning phase, especially human learning. [Related: How Kubernetes Catalyzes Enterprise IT] Todd Olson: We're in the middle of our hackathon for our engineering team. Hackathon's a week where they can basically work on whatever they want. But to stimulate AI activity, we altered how we do prizes. So we're doing $1,000 cash prizes to teams who either build AI capabilities in some unique or interesting way or use AI on their projects in some unique or interesting way. And guess what? People are experimenting. People are doing things. We're seeing interesting work being done. And yeah, look, money's a nice little carrot, nice little motivator. But to me, it's all about getting people to be uncomfortable and try something new. And I think you've got to find a way to be a catalyst for change at your company. And you've got to prioritize it. You've got to give people space to experiment. So give people space. Let them experiment. Even if the first few things they do may not quite yield the efficiency gains you were hoping for or may not be as high quality as you wanted, they are learning every step of the way. Encourage that learning and sharing. But yeah, I think that's what you need to do. [Related: Solving the Public Sector’s AI Agent Safety Puzzle] Jason Lopez: Todd Olson is co-founder and CEO of Pendo, a company which provides software helping companies understand how their software is being used to help improve the product experience. This is The Tech Barometer podcast produced by The Forecast, I’m Jason Lopez. The Forecast published tech news and features both in text, audio and video. Check out more stories at theforecastbynutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) How AI is Supercharging Software Development 9:15 no Connected Social Media https://connectedsocialmedia.com/21268/decrease-commercial-database-licensing-costs/ Wed, 28 Jan 2026 11:24:20 -0700 https://connectedsocialmedia.com/?p=21268 syndication@connectedsocialmedia.com (Connected Social Media) Decrease Commercial Database Licensing Costs 0 no Connected Social Media https://connectedsocialmedia.com/21265/hidden-threats-to-womens-hearts-preventable-outcomes/ Mon, 26 Jan 2026 11:35:54 -0700 https://connectedsocialmedia.com/?p=21265 WomenHeart CEO Celina Gorre. Together, they share powerful personal stories, highlight the urgent need to improve women’s heart health, and offer a message of hope grounded in community, advocacy and prevention. Tune in for ways employers can better assess the impact of their health and well-being programs to understand if they are meeting women’s needs today and in the future. Guests: Delya Sommerville, WomenHeart Champion and Celina Gorre, Chief Executive Offer of WomenHeart ]]> syndication@connectedsocialmedia.com (Connected Social Media) Hidden Threats to Women’s Hearts, Preventable Outcomes 30:44 no Connected Social Media https://connectedsocialmedia.com/21259/a-turning-point-for-alzheimers-study-shows-new-future-for-brain-health/ Mon, 05 Jan 2026 00:01:10 -0700 https://connectedsocialmedia.com/?p=21259 syndication@connectedsocialmedia.com (Connected Social Media) A Turning Point for Alzheimer’s: Study Shows New Future for Brain Health 21:01 no Connected Social Media https://connectedsocialmedia.com/21257/keeping-hearts-in-motion-in-a-glp-1-era/ Mon, 15 Dec 2025 12:44:10 -0700 https://connectedsocialmedia.com/?p=21257 syndication@connectedsocialmedia.com (Connected Social Media) Keeping Hearts in Motion in a GLP-1 Era 36:23 no Connected Social Media https://connectedsocialmedia.com/21250/finding-clarity-during-euc-industry-disruption/ Tue, 02 Dec 2025 19:18:50 -0700 https://connectedsocialmedia.com/?p=21250 The Forecast. Transcript: Ruben Sprujit: It's like a massive plate of spaghetti. Where do I start? What's the challenge? What's the idea you have? Jason Lopez: Ruben Spruit is the field CTO and VP of product at Dizion, a company that provides desktop as a service and cloud computing solutions to enable remote and hybrid workforces. He helps companies understand how to deploy end-user computing technologies, but not only companies. He's passionate, hands-on, and ready to help anyone in the EUC community. Ruben Sprujit: First, you listen to peers, to customers, to prospects and understand, hey, what is their idea or challenge? And many of us listen for a couple of seconds and then, okay, this is the problem, this is the solution, this is the vendor. But it's good to step back and listen a little bit more. Jason Lopez: Here at The Forecast, we've interviewed Ruben numerous times for articles and Tech Barometer podcasts to learn about end-user computing, virtual desktop infrastructure, and desktop as a service. In this interview at .NEXT 2025 in Washington, DC, he talked with The Forecast editor-in-chief, Ken Kaplan, about changes around EUC, such as new vendors and partnerships in the wake of Broadcom VMware's spinoff of its EUC offering, which became Omnissa. And he talked about AI and methodologies for helping IT teams build and evolve their EUC strategy, and offers tips for building a career around the EUC ecosystem. But he starts with the question, why are people using desktop as a service? [Related: How End-User Computing Leaders Make IT Work for People] Ruben Sprujit: It could be students with their own Chromebook want to access SPSS, nuclear power plant designer and builder using high-secure, sensitive data with design apps to design a nuclear power plant. It could be a retailer or using a handful of Windows apps in their retail office. It could be government agencies using office productivity. So it's different reasons to use virtual apps and desktops. But it all starts with, OK, I want to have a simple access to apps and desktops. I want to be workplace independent, need to be secure. And simple is the key. How can I keep it simple so the operational complexity is sort of gone? And that's important these days because knowledge and people with skills is challenging nowadays. Keep them is challenging. Find them is challenging as well. So building a platform that's easy to run as an admin and easy to consume as a user, like both we are also end users, consumers of solutions, these are the main ingredients of a good platform. Ken Kaplan: I met you seven years ago at Nutanix. It was explained as it's streaming your desktop experience from a server, from the data center, from the cloud. That idea, just how we would watch a Netflix video, it's streamed to you. So your apps aren't necessarily on your device. And there are lots of reasons for doing that. And it seems to be almost the status quo now. So what has changed in those seven years and what are you excited about today? [Related: From Skunkworks to Leading Hypervisor Alternative] Ruben Sprujit: A lot of things changed. Like seven years is a long time. So if we go back maybe seven years, Nutanix acquired our company, Frame. We saw Corona and a surge of workplace independent work. That's one of the reasons why we grow like crazy also within Nutanix. So that changed. That's new normal nowadays, right? Hybrid cloud is new normal. So supporting on-prem, supporting NT2, supporting public cloud natively. Unified communications is normal as well, supporting that. High-end graphic apps, all kinds of apps supporting that. But still with a clear strategy, keep it simple. Like how can we make sure that admin experience and user experience is as simple as it can? Everyone is using today a browser. 70% of the work we do as end users is browser. And then the other 25% often is like Windows apps. So how can we deliver both web and Windows apps in a seamless way to users? What is happening as well, we spin out of Nutanix, a little bit more than two years ago. So Nutanix can focus on infrastructure, hybrid cloud, and we can focus on end-user computing. So Dijon acquired Frame technology. Look at Frame as the car engine, while Dijon is more like a sort of managed services company. Coincidentally, both companies, so Dijon and Frame started roughly in the same time, 2012. Dijon with focus on Horizon, nowadays called Onisa, build their own control plane to orchestrate and automate Horizon deployments. In the same time frame was built as, okay, how can we build in cloud native solutions to stream apps and desktops to end users? So fast forward today, 2025, Dijon is using the engine, the Frame engine, to stream desktops and apps, Windows and Linux, personal and pooled, that's technology, but also add a managed service on top of that to help customers when needed, not required, but when needed to add admin services to local admins with service we offer. It's a services company with a very strong engine called Frame. Ken Kaplan: The ecosystem, you touched on it, can you talk a little bit more about the constellation that you're seeing out there, companies and changes that are happening? Ruben Sprujit: It's a very exciting space, end-user computing. So end-user computing, I always explain as a massive umbrella, and end-user computing, in essence, is the solutions we, you, listener, are using to get work done. That could be a virtual app, virtual desktop, that could be unified communication, that could be an AI agent, it could be a web or SaaS app, it could be a mobile device, it could be cloud storage, all the things I just explained equals end-user computing. And virtual desktops and applications, my expertise, or one of the expertise I have, is a fundamental element in end-user computing, but end-user computing, as I mentioned earlier, is much broader than that. So if you look at the bigger picture of what is happening in end-user computing, AI is part of that, AI agents, SaaS tools, old tools but then sort of AI-infused is happening, unified communications, but still Windows apps, SaaS, software as a service, desktop as a service, application streaming, all these items combined is what is real today. People think, well, Windows apps are dead. That's not the case. They are kicking alive. Yes, it's slowly degrading from 100% usage, 15 years ago, 20 years ago, to maybe 70% or 60% nowadays. Yes, SaaS and web did pick up the other like the bucket, but it's a combination of SaaS, Windows, mobile applications which gets work done for us. So that's happening. The whole industry is evolving to as a service. If I zoom in a little bit into like the VDI, the virtual desktop infrastructure, and DAS, the desktop as a service space, that's evolving as well with private equity taking over like the Citrix part, same for Omnissa, spin out of Broadcom, VMware, refocusing, finding new alliances, including with Nutanix. That's good for the industry, gives more choice. If you look at from a vision perspective, all these developments are helping us big time because a lot of customers, I would say 60% of the conversation I had in the show for past days, are customers, partners, scratching their head, price increase, 2x, 3x. Some vendors are refocusing on like only top segment of customers, and they are not in that segment of their customers. So they are scratching their head, hey, what is next for us? And next could be a physical PC. Next could be alternative for Citrix or Omnissa. That's happening big time. It's a very interesting space right now. Combination of like hybrid cloud, on-prem, public cloud, workplace independent, building a secure workplace, security is super critical for many. So if there's no data on the endpoint, which is the case with virtual apps and desktops, that makes life much easier, not easy, but easier to build a secure workplace. That's happening in our space. [Related: How AI is Shaping the Future of Data Storage Strategies] Ken Kaplan: There's not even a perfect storm, but it's certainly a storm of changes out there, from the vendor changes, the price hikes, to just the innovation that's coming across, the options that are out there. You add to that AI and people are thinking differently. How do you characterize this time in your career and what you're seeing? It seems like there's a lot of partnerships going on, a lot of working together. There's some urgency. Ruben Sprujit: Yeah. On one side, it's super energizing, but it's also complex. It's like a massive plate of spaghetti. Where do I start? And to help customer with that conversation, and there's nothing to do with vision or product. My background is consulting, and I always try to explain the bigger picture and understand the why. What's the challenge? What's the idea you have and you want to sort of solve? Okay, then what kind of concepts fit with that, and then which vendors can help to fill in that concept to help with the idea or challenge. So what we did last year, we built an EUC Hexagrid. The EUC Hexagrid is a physical representation of our end-user computing space. It has main pillars, six of them, and 22 sort of sub-pillars. And the goal is you start, okay, what is EUC? What is end-user computing? What's the purpose of these six main pillars? What's the purpose of the 22 sub-pillars? First, you listen to peers, to customers, to prospects and understand, hey, what is their idea or challenge? And then you use the Hexagrid to plot maybe two of the main pillars and three of the sub-pillars to what their idea or challenge is. Before you talk about how the vendor landscape looks like, and many of us listen for a couple of seconds and then, okay, this is the problem, this is the solution, this is the vendor. But it's good to step back and listen a little bit more and then plot six pillars, 22 sub-pillars, and then talk about the vendors, what they can do. That's what the EUC Hexagrid is all about. So it's an infographic, a graphical representation, 220 vendors are in that picture. It took us three months to build, and there's a white paper as well. So EUC Hexagrid, if you go to edition.com, you will find the resources EUC Hexagrid. Just fill in the email address, you'll get the Hexagrid white paper. And that helps in understanding what's happening in this space from a higher or medium level and paints a picture what vendors are in this space and what are the relevant vendors in this in this space. [Related: Performance Engineering in the Age of AI] Ken Kaplan: So how do you describe where we are today versus when we met seven years ago, for people who might be interested in focusing their career in this area of IT? Ruben Sprujit: Opportunity, I would say. Like, look at AI. But people are also scratching their head, hey, what does it mean for me? What does it mean for my business? What does it mean for products? I'm responsible for products. How can we leverage AI to make life simpler as an admin? How can we solve issues before the end user sees them? Would be great if that is possible, and it is possible, that's something we're building. So that's one angle to understand, hey, what the possibilities are. The beauty of cloud is that you don't need to spend a crazy amount of money to get started. And that applies to, well, Gemini, JetDVT, that whole theme of AI, that's where I would spend, if not spend already, time in understanding what the value is in your personal life, but also like with agents, communicating with agents, what it might look like in two, three, five years from now. No one knows. It's tough to predict. Also with this whole, like, global thing that's happening, tough to predict, but nevertheless, don't be shy, don't be sort of confused by that. It's not something you can control, and if it's not something you can control, just set it aside, focus on the things you can control. That's what I would do. And one of the things is understanding what's new. AI is newer, but still like the as-a-service cloud, hybrid cloud, I see customers moving from public cloud back to on-prem for different reasons, understand why, understand what kind of tools and vendors are key in that space. It's really exciting, exciting time. [Related: FinOps Flicks on AI to Optimize IT Resources] Ken Kaplan: You're also so well known in the community because you're very involved. You're on webinars. I remember you'd be at your desk and talking with your hands in the air, or you had your home desk set up just perfectly for these kinds of interactions that you have with people. Where can people go to join the community or learn more about the community? How do they get in to follow what you do? Ruben Sprujit: Well, the beauty is there are many different communities. So I would say my community is all around end-user computing, about GPUs, about remoting protocols, about VDI and that. So that's my community. One of the communities is World of EUC. So World of EUC is a massive community. There is a European community called E2EVC, not connected to any vendor. It's crazy guys like myself organizing it. And there are also online communities as well, like on BlueSky, on X it’s relatively easy to find the right folks and connect with them. So if you're new or newer to this space and want to learn, my experience in the past 20 years in that community is that I would say everyone, 99% is here to help. So if you're new and maybe new to writing or new to presenting or new to technology, just reach out. I'm still Ruben with two feet on the ground. I'm smiling, right? You can see. Ken Kaplan: Even just to get you to sit down and sit with me, I waited in line because people just want to come and talk to you. Jason Lopez: Ken Kaplan is editor-in-chief of The Forecast. He interviewed Ruben Spruid, field CTO and VP of product at Dizzion, a company that provides desktop as a service and cloud computing solutions. Learn more about end-user computing at Nutanix.com. Go to Nutanix.com slash solutions slash end-user-computing. I'm Jason Lopez. This is Tech Barometer produced by The Forecast. You can find many other technology stories at theforecastbynutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) Finding Clarity During EUC Industry Disruption 14:31 no Connected Social Media https://connectedsocialmedia.com/21247/itintel-data-center-strategy-leading-intels-business-transformation/ Thu, 20 Nov 2025 15:31:04 -0700 https://connectedsocialmedia.com/?p=21247 syndication@connectedsocialmedia.com (Connected Social Media) IT@Intel Data Center Strategy Leading Intel’s Business Transformation 0 no Connected Social Media https://connectedsocialmedia.com/21245/innovations-in-confidential-manufacturing-improve-security-and-scalability/ Thu, 20 Nov 2025 15:24:05 -0700 https://connectedsocialmedia.com/?p=21245 syndication@connectedsocialmedia.com (Connected Social Media) Innovations in Confidential Manufacturing Improve Security and Scalability 0 no Connected Social Media https://connectedsocialmedia.com/21239/finops-and-ai-optimizes-it-resources/ Tue, 18 Nov 2025 11:22:36 -0700 https://connectedsocialmedia.com/?p=21239 The Forecast. Transcript: Mayank Gupta: How can we make FinOps itself a lot more intelligent, now that we have Gen AI, can intelligence be built into the system where it automatically understands usage patterns and takes action to bring it down? Jason Lopez: Generative AI is transforming how organizations manage cloud and IT spending. Although it brings new costs and it also affords new opportunities for automation. This is the Tech Barometer podcast, I’m Jason Lopez. On today’s edition: FinOps, bringing together finance, engineering, and business teams to manage cloud computing costs. This is increasingly important for optimizing IT resources in the age of AI. Mayank Gupta: A lot of companies are getting into a hybrid multicloud environment as they're using GenAI. Jason Lopez: Mayank Gupta, Director of Product Marketing at Nutanix, tells The Forecast editor-in-chief Ken Kaplan how FinOps is evolving with better observability and automated cost controls. Mayank Gupta: They are realizing that they have to actively track these dollars they cannot just use and run this forever without having some sense of accountability. [Related: AI is Hungry for Data, But Can IT Infrastructures Keep Up?] You used to just track your CPU storage. Now you're tracking one more resource, which is your GPU. Similarly, when it comes to training and inference, whether you're running on prem or whether you're running on the public cloud, a lot of these FinOps tools have to have insights into your training cost and inferencing cost. Training models can be a very expensive proposition. So we are building that in the tool, and we're building these new features into our cost governance models, where we are seeing something which has come into the industry, going to be there for the very long haul. Let's bring in those models and have that. The other very interesting side of this business is, how can we make FinOps itself a lot more intelligent now that we have Gen AI? Can intelligence be built into the system where the system automatically, through agents or through intuition, through learning, understands, hey, this is the usage pattern. And if it's deviating from them, let me take some action automatically and bring it down. How can we make the job of an IT admin or a FinOps admin easier, getting all these signals from different places? And now we have AI to help. We can distill these signals in something which is easily digestible. Even on the actions that need to be taken off, the user can say, hey, take these actions based on a set of best practices, and now Gen AI can help with them. So we are looking at, how can GenAI make it more effective? [Related: Performance Engineering in the Age of AI] Ken Kaplan: Let's talk about maybe the biggest challenges of your customers, the biggest challenges that come to mind and you hear all the time. Mayank Gupta: Certainly I think what's happening a lot is customers have their on-prem infrastructure, which is their data centers. They might have stuff on the edge. They definitely have stuff on the public cloud. How do I have visibility across public cloud, edge core data center visibility is the first step in you controlling your cost. The second big step is having an accountability and doing the due diligence of let's put this set of dollars to this account. Let's set this dollars to this account. Who's using what and where? That's the second important step. Once you have the visibility, once you have the accountability, how do you make sure you're optimizing those dollars? How do you set constraints and limits on those dollars? There has to be a sense of checks and balances that, and this is the industry term for this is a showback. We'll show back to you how many dollars that you'd use. Right? You might not pay me for that, but at least these are the resources that you're consuming. And then we optimize this, right? If you are wasting dollars, let's bring those resources down. If something is not needed, let's turn it down. That's the third very important step where we make sure that nothing is being wasted. [Related: How Ivy League Dartmouth College Moved to a Future-Ready IT Platform] Ken Kaplan: You do a lot of webinars, and you talk with professionals and also customers. (3:12) Are there some stories that come to mind about how they've applied FinOps? Mayank Gupta: I was talking to a Philadelphia utility and the cloud bill just from one vendor had 160,000 line items of different services each costing something else, and they were getting overwhelmed because they could not A understand, and then B, how do I optimize this? So having a solution, having a product, having a tool that can ingest all this information, tag it appropriately, and then automatically give you suggestions on, Hey, you know what? These are the resources that can be reduced or eliminated or optimized. That is something which everybody needs, and I think that's just one use case. And across the board, every single time they started using our product and they realized that it was a lot easier when we tagged things under services and we said, Hey, this is your storage. This is your load balances. These are your VMs. These are your containers in a graph format, and this is where you can optimize. And they were able to click and right-size things. So that's one example. The other case where I've talked to customers, 80%, in fact, I think it's 83% of Nutanix customers have not just their on-prem system, but they also have multiple hyperscalers. So these are multiple public clouds because all of these vendors have different clouds. The ability to see all of this in one single place is a great benefit for these vendors, and that's what finops tools provide them. You have the ability to see every single thing in one single place. That's a fun conversation for me to have. If you had this visibility, what would you do? And they say, oh, you know what? That would make me so much more empowered. That's what I see every single time. [Related: Search for VMware Alternatives That Meet Existing and Future Needs] Ken Kaplan: Do you see FinOps, does it help with other parts of budget control, like sustainability issues, energy consumption? And do you see FinOps maybe evolving to other places such as that? Mayank Gupta: Yeah, a lot of our customers are seeing that, hey, we are a little mindful of their dollars. People are being mindful of their carbon footprint. And this is all coming together. So you bring a great point, Ken, that yeah, people are bringing it together and people want to see, hey, this is another evolution in me seeing off my costs, my carbon footprint, and all of those things. Yeah, absolutely. Ken Kaplan: Yeah, it feels like maybe it starts to move into this regulatory area where you have to report out certain performance of your business and maybe FinOps helps contribute to those pure reporting that needs to be done. Mayank Gupta: Yeah, no, absolutely. (5:50) There are regulations with some time-bound periods where these reportings are going to be as a part of your regulatory planning. (5:57) Just as you file your quarterly Q1 reports and 10K reports, this will come in there, right. (6:01) So a lot of our customers are getting ahead of the curve and they are asking these things, not just for FinOps, but also for their carbon footprint. (6:09) And that's why a lot of vendors are actively working to build that into their dashboards and their metrics that they track, yeah. [Related: Composable Data Centers That Power Enterprise AI] Ken Kaplan: Yeah, I mean, anything you want to say to people who are just getting into FinOps? (6:21) How do you see this evolving. Mayank Gupta: A lot of people think that, Hey, you know what? This is a rum part of business, I kind say is that this is the kind of business which your CIO, the CFO, and don't be surprised, even the CEO would actively track. So it's a great line of business to be in because this does touch the bottom of the company, the dollars that you save, other dollars that can be applied in other parts of the department. So it's a great field to be in. A lot of companies are getting into a hybrid, multi-cloud environment. As they're using genai, they are realizing that they have to actively track these dollars. They cannot just use and run this forever without having some sense of accountability as the regulations for carbon, as the regulations for cost come even more mandatory than in that regards. It'll be a more exciting field to run. There'll be always more to be done, and there's always be an opportunity to be in the limelight because you'll be saving your company dollars and saving your line of businesses dollars, and you could be the hero. Jason Lopez: Mayank Gupta is Director of Product Marketing at Nutanix. He spoke with The Forecast’s Ken Kaplan.  Learn more about managing FinOps with Nutanix Cloud Manager software. Search Nutanix NCM Cost Governance. This is the tech Barometer podcastI'm Jason Lopez, Check out our other stories at the forecast website which you can find: nutanix.com/theforecastbynutanix]]> syndication@connectedsocialmedia.com (Connected Social Media) FinOps and AI Optimizes IT Resources 9:30 no Connected Social Media https://connectedsocialmedia.com/21237/when-offering-supportive-cancer-care-employers-do-good-and-do-well/ Mon, 17 Nov 2025 13:03:14 -0700 https://connectedsocialmedia.com/?p=21237 The Sheri and Les Biller Family Foundation ]]> syndication@connectedsocialmedia.com (Connected Social Media) When Offering Supportive Cancer Care, Employers Do Good and Do Well 30:41 no Connected Social Media https://connectedsocialmedia.com/21235/standardizing-application-portfolio-management-with-gated-resource-provisioning/ Fri, 07 Nov 2025 01:22:08 -0700 https://connectedsocialmedia.com/?p=21235 syndication@connectedsocialmedia.com (Connected Social Media) Standardizing Application Portfolio Management with Gated Resource Provisioning 0 no Connected Social Media https://connectedsocialmedia.com/21233/agentic-ai-in-the-enterprise/ Mon, 03 Nov 2025 02:03:44 -0700 https://connectedsocialmedia.com/?p=21233 syndication@connectedsocialmedia.com (Connected Social Media) Agentic AI in the Enterprise 0 no Connected Social Media https://connectedsocialmedia.com/21227/dartmouth-college-it-director-builds-modern-it-platform-for-ai/ Fri, 31 Oct 2025 00:54:33 -0700 https://connectedsocialmedia.com/?p=21227 The Forecast. Transcript: Ty Peavey: Some people have the thought process that AI may replace what they do every day, and then there's others that look at it to elevate what we do every day. And I kind of am in that camp. I really believe in treating AI as a tool. It's a way to do things easier, faster, better, but at the end of the day, the human really matters. Jason Lopez: The 2025 Enterprise Cloud Index Report found that AI applications are driving productivity, automation, and efficiency across industries. At Dartmouth College, an Ivy League Research University in Hanover, New Hampshire, that trend is playing out in real time. Ty Peavey Dartmouth's, director of Infrastructure Services, explains how his team uses Nutanix software to modernize IT operations and support researchers who increasingly rely on AI in fields such as medicine, neuroscience, and environmental science. [Related: Orthogonal Advantages of Cloud Native Technologies] Ty Peavey: We have some of the best faculty in the world that really have some challenging needs. They all want access to some sort of ai. Some of 'em have small budgets, some of 'em have large budgets, and it's really been a challenge to try to help them adopt LLMs into their research these days. And so as we look at tools like Nutanix and what we're seeing there, we're hoping to see that simplified somewhat and maybe commoditize and get access to LLMs on-prem early. It does take a lot of effort to help translate what they're looking for and really appreciating the kind of resources both from people and hardware of how to deliver that. There's also a lot of need to access AI with our vendors like Azure and with AWS. And so we try to facilitate those conversations as best as possible. We have a research group that also does infrastructure, and they're kind of the pioneers. They're the early adopters. They really paved the way for more of the generalists, like my team, to learn about AI. [Related: Public Sector Adopting AI, But Serious Gaps Remain] One of the things that we've done recently as more of a team building is we've worked with them to use some of the hardware that they've gotten under research to build our own infrastructure LLM. Really the goal is to try to understand the vocabulary, understand the platform and the architecture. What are the layers that go in to bringing in your own LLM? And really training it is the other thing. We have this fun approach that we want to take all of the documentation, all of the tickets we've processed over the years and train our LLM so that we can ask it all kinds of questions that we do every day. So it's a lot of fun. We'll do it for a while and we'll take it down and then we'll move on to the next thing. [Related: Legacy Health Turns from Broadcom VMware to Nutanix] We've traditionally had really siloed roles dedicated to storage, Linux, windows, all of these job descriptions that were very unique. And so when we got away from three-tier technology and moved into hyperconverge, we were able to break those walls down. I'm very proud of that, and I think my team has adopted it quite well. We no longer have a Windows sys(tem) admin. You may be on my team and work on Kubernetes in the morning and Nutanix in the afternoon. We brought in Kubernetes about a decade ago, really kind of some niche places that we could roll out containers. Today we have over 400 containers, over four Kubernetes clusters. Two being in Nutanix with NKP and two being in EKS. We find the adoption is great. I think we'll always have a fair amount of full VMs, but we anticipate as our application location start supporting more and more containers. We'll see that number grow as well. And I think what we've found in that is really good job satisfaction. People like what they're doing. It is challenging at times a good challenge. And Nutanix has really helped facilitate that for us. I mean, we've dodged the Broadcom bullet a bit and we're in a really good place and we're really happy about that decision. [Related: Search for VMware Alternatives That Meet Existing and Future Needs] A number of things have shaken up the market and shaken up the technology. Definitely the acquisition of VMware from Broadcom is a first for me in my 30 years. Supporting infrastructure, adapting to that and trying to come out from the other side with an equal or better technology stack for our users has been really important. At the time, Nutanix and I think still does, you can buy it with AHV or you can buy it with VMware. And we literally took a vote in my staff like, okay, you've, you've seen VxRail, you've seen Cisco's product, you've seen HP's product, now you see Nutanix. What are we going to do? And we unanimously said, yeah, let's go Nutanix and let's go AHV. Let's go all in. And it was a bit of a shock. I didn't expect it, but it was unanimous. And the transformation had, I don't want to say easy, but it wasn't bad. There was a lot of similarity to concepts that we already knew. A lot of the fears were just in our head. So I would say it was an easy adoption, if you would. My team will probably hate that I said that, but it is. I think we were better for it, and I think Dartmouth is better for it.]]> syndication@connectedsocialmedia.com (Connected Social Media) Dartmouth College IT Director builds modern IT platform for AI 6:56 no Connected Social Media https://connectedsocialmedia.com/21223/the-real-face-and-cost-of-mens-poor-health-in-the-u-s/ Mon, 27 Oct 2025 01:55:26 -0700 https://connectedsocialmedia.com/?p=21223 Movember and co-author of Movember’s new report, “The Real Face of Men’s Health” Dr. Derek Griffith | Professor and co-author of Movember’s new report, “The Real Face of Men’s Health” ]]> syndication@connectedsocialmedia.com (Connected Social Media) The Real Face – and Cost – of Men’s Poor Health in the U.S 30:41 no Connected Social Media https://connectedsocialmedia.com/21221/no-more-tossing-and-turning-improve-your-sleep-improve-your-health/ Mon, 13 Oct 2025 00:34:27 -0700 https://connectedsocialmedia.com/?p=21221 syndication@connectedsocialmedia.com (Connected Social Media) No More Tossing and Turning: Improve Your Sleep; Improve Your Health 39:33 no Connected Social Media https://connectedsocialmedia.com/21215/spark-systems-coo-built-powerful-it-system-for-fx-trading/ Fri, 10 Oct 2025 00:53:03 -0700 https://connectedsocialmedia.com/?p=21215 Spark Systems Chief Operating Officer Chaitanya Peddada describes how migrating to a modern IT platform powered by Nutanix’s hyperconverged infrastructure technology boosts the FinTech firm’s high-speed foreign exchange trading capabilities. Find more enterprise cloud news, features stories and profiles at The Forecast. Transcript: Chaitanya Peddada: It's an extremely competitive space, and the FX markets aren't like the stock exchanges which start at a particular time and end at a particular time. It starts up Monday morning and goes throughout the week right up to Saturday. So maintaining that is extremely important. Customers expect to see the best prices exactly in real time, no matter where they're sitting in the world. It's sub-milliseconds, which means it's microseconds. [Related: AI Ambitions in Financial Services Tempered by IT Infrastructure Challenges] Jason Lopez: The largest financial market in the world, the FX market, is a global decentralized network where banks, financial institutions, hedge funds, corporations, and traders exchange the world's nearly 180 currencies at negotiated prices. Singapore-based Spark Systems is a financial technology company that creates and runs high-speed, ultra-low-latency FX trading platforms. Chaitanya Padada of Spark talked to The Forkast about its goal to double average daily trader volume. [Related: The State of IT is Moving to Trusted Vendors] Chaitanya Peddada: In order to do that, we have to ensure that we have all of our basics right, which means the software services on our side, the customer support on our side, and most importantly the infrastructure, because that's where it takes a lot of lead time in order to set up the infrastructure, which we maintain. And this year we made the transition to move our entire Singapore data center onto the Nutanix stack, which allowed us to not spend money on our SAN storage devices, which would have to be renewed this year. So we used Nutanix Move to move from the legacy system to the new stack, and we also were able to add in a couple of extra servers to have a much larger stack, and we are ready to service clients or add customer servers up till the end of the year. We are in a very tightly regulated space, so there are not just regulatory requirements but also requirements imposed by our clients, especially the banking clients, right? They have tight requirements, and these are not just security requirements but even data storage requirements. And that's the reason why we host our own hardware. We don't host customer data in the cloud. And because we have to maintain our own hardware stack, it's very important that we, apart from our own software, which is Java-based technology, we partner with the right partners right from the OS level to the VM level, as well as the entire infrastructure stack. [Related: How Ivy League Dartmouth College Moved to a Future-Ready IT Platform] We host our own software in data centers, which are maintained by us for the customer, which means as soon as the client signs up, within days, if not weeks, they want to start up and start trading right away, right? So, having the right platforms in place, being at the right locations, which are the FX hubs around the world, is extremely important. Apart from that, latency plays a very key factor. We need to be in the sub-millisecond space, right? And those are the sort of benchmarks we use while testing any third-party product. So, whether it's the OS or whether it's the VM solution that Nutanix provides, these are some of the basic test cases that we run through, apart from load testing and other FX parameters. [Related: AI’s Rising Tide Confounds IT Decision Makers] We also consume a lot of data, and per day, there's an immense amount of market data that's going through our systems, as well as the client's proprietary trading data, orders and trade data. All of this data has huge potential in order to leverage for building TCA systems or AI-enabled TCA systems, right? What we are looking at doing at the moment is to use this data in order to give our customers trading signals before time. We also have a library of algorithms which have predictive capabilities. Now, when we get into the predictive space, it's very important for vendors like us to be able to assist our clients in order to provide new strategies for them, because in terms of predictive AI or algos, we need to really partner with the right customers. The traders are the people who come up with the ideas, but we need to be ready to implement those ideas as soon as possible. So this also allows us to leverage on the cloud technology, which we haven't done so far, but even over there, I think Nutanix is probably the right partner for us to have on-prem services as well as cloud services using the same technology stack. [Related: Legacy Health Turns from Broadcom VMware to Nutanix] This was the year we transitioned onto Nutanix in a big way, right? We had initially started off in 2022, experimenting in our London data center, which is a smaller footprint compared to Singapore and Tokyo for us. And this year, we took the decision to transform the entire Singapore data center onto a Nutanix HCI stack. The most interesting thing about this transformation was, as I told you, we have only a small window to do a migration per week. So it's one and a half days per week. And over a period of six weekends, our team managed to transform the entire stack onto a Nutanix HCI stack. We've gone issue-free so far, which is a first, probably in my career. We haven't had any migration issues because there was also a lot of support from not just from Nutanix, but also from Nutanix partners to practice and prep for this migration process. ]]> syndication@connectedsocialmedia.com (Connected Social Media) Spark Systems COO Built Powerful IT System for FX Trading 6:29 no Connected Social Media https://connectedsocialmedia.com/21210/global-cancer-rates-are-rising-address-regional-risk-factors-to-reverse-the-trend/ Mon, 22 Sep 2025 11:45:59 -0700 https://connectedsocialmedia.com/?p=21210 American Cancer Society discusses the soaring incidence of cancer globally, particularly in low and middle-income countries and shares how cultural factors, stigma, and financial burdens can complicate the treatment journey. Tune-in to hear why education and navigation are crucial to global cancer care, along with ideas on how employers can support employees during treatment. Guest: Anu Agrawal | Vice President, Global Cancer Support at American Cancer Society ]]> syndication@connectedsocialmedia.com (Connected Social Media) Global Cancer Rates Are Rising: Address Regional Risk Factors to Reverse the Trend 23:58 no Connected Social Media https://connectedsocialmedia.com/21201/making-of-nutanix-ahv-hypervisor-a-top-alternative/ Tue, 02 Sep 2025 07:43:48 -0700 https://connectedsocialmedia.com/?p=21201 The Forecast. Transcript: Mike Cui: Well, this is where we have to go into the story. Greg Smith: Maybe Mike, since you were there before me, you can provide some of the context and the lead up for what happened. Mike Cui: I came up with an idea and I convinced a whole bunch of people we should do this. Not that we should do this, but we could actually do this. It's possible. Greg Smith: As I remember it, when I joined, I thought I was joining the Stargate team to work on storage and performance tuning, and Mike pulled me aside and said, well, we need this one change in Stargate, but then you should really go and work on making KVM a product. Jason Lopez: Even in IT, life happens. Innovations often emerge when you don't plan them, and that's what happened to Mike Cui and Greg Smith. Today, Mike is a principle engineer at Annapurna Labs and Greg works at Foxglove Technologies. In 2013, they were at Nutanix and back then the market wasn't expecting another hypervisor. Kanchan Mirani: It was very much VMware who created that category. Jason Lopez: Kanchan Murani is senior director of strategic marketing at Nutanix. She said VMware was a pioneer of the hypervisor and grew into an industry leader. Kanchan Mirani: At some point, VMware was so far ahead. It was really the only hypervisor out there that any enterprise would seriously consider. Jason Lopez: Until AHV. [Related: IT Resiliency: Running Two Different Hypervisors] Mike Cui: I had an idea for something like AHV. Greg Smith: I guess we were the creators of AHV. Yeah. Mike Cui: This is where it's not like we had a grand plan. It is tied with the story of how we accidentally got our first customer and what we had to do to solve the problem for this customer, and then eventually evolving into a full-blown product. Jason Lopez: Before delving into the story of how AHV came to be, let's look at what it is. Nutanix AHV, or the Acropolis Hypervisor, is virtualization software that enables it to run VMs. It's a core component of the Nutanix Cloud platform which is ever evolving. With the latest update, as of mid 2025, AHV is at version 10.0. Here's how Kanchan describes it. Kanchan Mirani: It's a pretty core infrastructure software piece, which helps IT teams manage all their resources, essentially. Think of an IT team that’s getting requests from all different departments and lines of business who want to run their specific applications and they're trying to manage all their resources. Now, imagine if they had to put in actual boxes for each request that each line of business came to them with, versus having a sort of bank of resources, which they're able to allocate really easily without actually doing physical connections and so on and so forth. So virtualization helps you do that because it makes it software based. You can give somebody a machine, which is a fractional part of a server and say, here, go develop on this, and you can do that all with software through the hypervisor. [Related: Legacy Health Turns from Broadcom VMware to Nutanix] Jason Lopez: Back in 2011, AHV didn't exist, but at the time, Mike was on a team pushing to get the company's first version of its Power App out. Power App was designed to provide a simple and efficient way for users to create, deploy and manage virtual machines. Mike Cui: We shipped it and then throughout 2012 things were mostly chill. Like people can finally relax. Jason Lopez: A year later, Nutanix decided to expand support beyond VMware to other hypervisors such as Microsoft's, HyperV and kernel based virtual machines or KVMs, the open source virtualization technology for Linux operating systems. Mike Cui: We installed it. It was our first attempt at making something work in Japan. The customers were asking us, how does this KVM thing work? Where's your user interface? I'm like, we don't have any. Jason Lopez: Mike thought the customer wanted KVMs because they knew how to use them, but they didn't know anything about them. Mike Cui: We'll go back and work on it, and I tried to build something during the same trip. The night before I was flying back, we had a Friday all-hands meeting. We just did a deal with a three-letter government agency, and this deal was going to be all KVM and this is me still sitting here in Japan, asking: like what? I just had to explain to our first customer that we have nothing. [Related: Search for VMware Alternatives That Meet Existing and Future Needs] Jason Lopez: Mike saw another customer was eager to run Nutanix on KVM and knew it was high time to create that GUI. Mike Cui: Right about when we closed the deal, they realized they didn't have any money left to buy ESX licenses. Jason Lopez: The customer in Japan could no longer pay for the VMware hypervisor because they had spent their budget on buying new Nutanix software and new flash memory powered hardware. As Mike recalls, they held Nutanix in such high regard. They believed it was possible to move from ESX to the KVM. They were all in on Mike and his team to get them up and running on the new high hypervisor. Greg Smith: There's no way that any customer in the modern era would've accepted this as a solution, right? But because they had no experience with virtualization, we got away with a lot, and so this really scrappy, scripted, hacked up solution. How much time do we spend on that? A couple of weeks, right?  Mike Cui: It was all you. I don’t know (chuckles) Greg Smith: Yeah, it wasn't more than a couple of weeks. The first week I spent on doing the Stargate code, a snapshot from NFS to SCSI, and then I think it was two or three weeks working on the scripts and then you went on vacation for two weeks. Mike Cui: Oh, yeah. I went to try that. Greg Smith: So I'm brand new at the company. Like here I'm defending this…thing that did not feel like a product at all. [Related: The State of IT is Moving to Trusted Vendors] Kanchan Mirani: When Nutanix came along, we essentially created AHV from an open source base to begin. At that point, we were trying to optimize what's possible in the field of software-defined computing. We had the storage piece. We wanted to extend it to computing, which is where the hypervisor came in, and over time we developed it into a pretty world-class hypervisor that was very competitive with what was out there. Jason Lopez: AHV became a real alternative to VMware. Over time, this evolved with steady but slow adoption, but the latest chapter in the AHV story started when Broadcom acquired VMware. Kanchan Mirani: We've always supported freedom of choice. So in our platform, we support ESXi, which is VMware's hypervisor as well as our own AHV. And we've seen a steady growth in the percentage of our customers who are using AHV. We've seen a steady growth since the beginning, but it definitely got a bump and continues to grow after the acquisition, so that's an indicator of where the customers are putting their choices now. Jason Lopez: Between August, 2023 and April, 2025, the adoption of AHV as a percentage of cores grew significantly, which means customers run more of their Nutanix powered IT operations on the AHV hypervisor. Greg said simplicity and optionality are built into the core of AHV. Greg Smith: Part of what made VMware such a great product to use as an engineer was like all of these nerd knobs that you could just tweak out to the nth degree, but it led to a very complicated experience, especially when you had to consider things like upgrades. So we decided very deliberately to try and sidestep all of that by presenting a very simple interface that we expected never to change. That was a huge part of our philosophy. For a long time, we thought that the surefire win for AHV as a solution was like test and dev. We had made it work for test and dev internally, and we said: Look, we know that this works. Jason Lopez: Greg and Mike say there was some luck, too. You can have the right philosophy but the wrong timing, and in their story, they didn't think they were building a full-blown marketable product, but a solution for a single customer. Mike Cui: I did not expect AHV to have that level of success. I just feel like we were building something and we got it to work. That was already a huge accomplishment. Greg Smith: It just had a knack of being in the right place at the right time with the right things going on all around it, various things from the open source world that we were able to take advantage of. [Related: How Ivy League Dartmouth College Moved to a Future-Ready IT Platform] Mike Cui: Oh yeah. Greg Smith: Like VMware trying to stop us from shipping ESX, if that hadn't happened, we wouldn't be shipping AHV as broadly as we are today. It wouldn't have had as much exposure. Mike Cui: I think things just happened to align when I went to Japan to set up the first customer. At that time, there was sort of no concept of vSwitch on Linux. Greg Smith: Oh, yeah. Mike Cui: You use Linux bonding if you want to bond two interfaces, and then you would apply a VLAN-tag on top of the bond. Then the issue is, well, if you use both bonding and VLAN tagging at the same time, now all your performance is crap for some reason, right? Like that year is when (Nutanix) AOS went mainstream and all of a sudden it worked. We did everything we needed to do. It worked. Greg Smith: Really well. Jason Lopez: Greg Smith works for a robotics company, Foxglove Technologies. Greg Cui is a principal engineer at Annapurna Labs, provider of custom chip software and accelerators. This is the Tech Barometer podcast. I'm Jason Lopez. Tech Barometer is a production of The Forecast. Check out The Forecast on Nutanix.com for a more detailed print version of this story, "Birth of a Hypervisor that Unleashed a Hybrid Multicloud Era." Again, at The Forecast by Nutanix.com. And once you're there, check out some other technology stories at The Forecast. Thanks for listening. ]]> syndication@connectedsocialmedia.com (Connected Social Media) Making of Nutanix AHV Hypervisor a Top Alternative 09:55 no Connected Social Media https://connectedsocialmedia.com/21194/nutanix-ceo-on-2025-it-trends/ Tue, 26 Aug 2025 00:34:38 -0700 https://connectedsocialmedia.com/?p=21194 The Forecast. Transcript: Rajiv Ramaswami: Now it's time for us to look at the most modern or modern applications, AI. As the year progressed, we saw AI, generative AI evolving at a rapid clip. Here we've expanded from just doing simple inferencing to providing you a full set of age agent frameworks and models. Jason Lopez: At the .Next 2025 conference in Washington DC, The Forecast caught up with CEO Rajiv Ramaswami after his keynote to briefly chat about technology and market trends. Rajiv Ramaswami: If you're a customer, I think everybody wants to know about what's going on now? What are the trends? What's Nutanix doing? How can we help these days? Of course, top of mind topics for everybody is what's their future end state when it comes to a vendor that they can partner with for the long haul as they migrate away from their current solutions. So that's a very top of mind topic for everybody. And then we quickly get into a discussion of trends and where things are going for the future and how we can help them. For the longest time, VMware was the established infrastructure vendor for many of these companies. They've had 20-year-plus relationships with them, and I was in Japan, and I think there was a growing awareness two years ago. They weren't particularly concerned. Last year, they started getting concerned. [Related: Nutanix CEO Stokes Surge in IT Ecosystem Partnerships] This year they're actually moving. For example, here at the show, we had Toshiba talk about how they're planning the migration away from Vme Nutanix. And you're seeing that, right? I mean, some of this is also from certain cultures. There's a lot of faith and trust built up over the years, and they want to work with somebody they can trust. So we are seeing a lot of that certainly happen over the last year. We've gone even in terms of what we've been able to bring to market and made tremendous progress. And it's still not mature. There's a lot going on every day, and I don't know what it's going to be. It was regular AI, generative AI, then agentic AI, I don't know what's coming next. Reasoning models came in recently. So this is rapidly evolving. I think hybrid cloud is pretty much established at this point. [Related: Growing a Multibillion Dollar Data Security Company in the AI Era] Everybody realizes they're going to be operating in a multicloud environment with some workloads running in the data center, some at edges, some in the public cloud. So that model is very well established. And almost every customer I talk to has made these comparisons. They've looked at the cost of running in a public cloud, whether on-prem, they've looked at the security issues, all of those things, and they've decided that they'll figure out some things that were done in the public cloud, some and on-prem. So that's well established at this point. Now it's a matter of more executing on that at scale. ]]> syndication@connectedsocialmedia.com (Connected Social Media) Nutanix CEO on 2025 IT Trends 3:00 no Connected Social Media https://connectedsocialmedia.com/21192/finding-strength-in-the-middle-place-between-acute-sickness-and-full-eating-disorder-recovery/ Sun, 24 Aug 2025 23:40:53 -0700 https://connectedsocialmedia.com/?p=21192 Slip: Life in the Middle of Eating Disorder Recovery, Professor, University of Texas, Austin ]]> syndication@connectedsocialmedia.com (Connected Social Media) Finding Strength in the Middle Place: Between Acute Sickness and Full Eating Disorder Recovery 42:06 no Connected Social Media https://connectedsocialmedia.com/21184/it-intel-preparing-our-pc-fleet-future-ai/ Tue, 12 Aug 2025 00:40:43 -0700 https://connectedsocialmedia.com/?p=21184 syndication@connectedsocialmedia.com (Connected Social Media) IT@Intel: Preparing Our PC Fleet for the Future of AI 0 no Connected Social Media https://connectedsocialmedia.com/21178/what-you-say-and-how-you-say-it-how-a-positive-narrative-identity-elevates-mental-health-and-well-being/ Mon, 11 Aug 2025 10:07:01 -0700 https://connectedsocialmedia.com/?p=21178 Olin College of Engineering ]]> syndication@connectedsocialmedia.com (Connected Social Media) What You Say and How You Say It: How A Positive Narrative Identity Elevates Mental Health and Well-being 37:32 no Connected Social Media https://connectedsocialmedia.com/21172/cohesity-ceo-sanjay-poonan-ai-powered-data-security/ Mon, 11 Aug 2025 00:30:38 -0700 https://connectedsocialmedia.com/?p=21172 The Forecast. Video transcript: Transcript: Jason Lopez: Cohesity is a cybersecurity company led by Sanjay Poonan. He told The Forecast how he came to Cohesity on advice from Nvidia, CEO, Jensen Huang. Sanjay Poonan: He said something that really rang with me, which is, you've done the big company stuff, 20 billion, 10 to 20 billion at SAP, six to 12 billion at VMware. You haven't taken a small company and made it big, so you should try that. And for me it was a little bit of like, can we take something that was small and make it an iconic company? SAP and VMware were already iconic when I got there, and we of course made it even better. That's what I saw as the opportunity of Cohesity. It was a world-class company. It was about a $300-million company when I joined, with fantastic technology and an incredible founder. In fact, many of the customers told me it was the best tech they'd seen since VMware, so there was no tech risk there. We needed to scale the go-to market to get it to be a multi-billion and the leader in the space. We were number seven. So I saw a tremendous opportunity at the center of this notion of data security because of ransomware attacks and all the pressure on data to create a leader, and that's what we're off doing today. [Related: Composable Data Centers That Power Enterprise AI] The entire product is based on notions of machine learning and AI. Before generative AI, the founders were Google folks who built a lot of key capabilities of ML and AI into the product. A lot of these cybersecurity data detection of entropy and anomaly detection are AI algorithms. So that was from the get go, built to be a key part to the proposition of the product driven by Generative AI. We started working with Nvidia. Nvidia made one investment in this space. They looked at all the tech companies and picked us to do an equity investment because we cracked an important problem of how you could use retrieval augmented generation, also known as RAG, directly on secondary and backup data. We invented that. We in fact patented the idea. Nvidia loved it, and we were featured at GTC in both 2024 and 2025. Jenssen's words were Cohesity backs up the world's data and they're building their RAG application called Cohesity Gaia on top of the Nvidia platform. We're working with them and Google and Microsoft and Amazon who are also those four companies, I think pioneers in what the world of AI is going to look like. You can imagine a problem like this where hundreds of millions of PDF documents sit in our backup. You can easily query that, summarize it, get insights into sort of flying a flashing of torch light right into your data. That is going to be a tremendous advantage to not just keeping the data secure, but also getting insights into it. [Related: Raising Ransomware Resistance] Today, the number one problem is data resilience. People's data is under attack from nation state actors, cyber criminals, and we work with 13,000 customers. The largest of the largest 85% of the Fortune 100, 70% of Global 500, and it's the name brand and financial services, tech, telco, healthcare, you name it. The public sector are our customers. So their number one priority is keeping their data safe from ransomware attacks. And we've designed something that's got the fastest cyber recovery and enormous amount of advanced security. Now, what they want to be able to do is, let's take that a step further and using AI tools, get insight into that data, and we have a very good sort of two-pronged engine approach to how we approach our company's ambitions. Number one, we innovate to be the best product in the industry, and that's been always the pride of Cohesity, I hope, and we will continue to do that. [Related: Protecting Against Ransomware at the Data Level] Number two, we obsess about our customers. We get an anchor customer, particular vertical. We study their needs, we drive what they need. And then every customer, that vertical becomes automatically like that anchor customer. You pick the largest bank, make 'em successful, pick the public sector agency and the federal, the biggest telco, the biggest tech company, the biggest hospital. And when you do that, you can repeat that. That's the playbook I learned at SAP and at VMware and now you get to apply it at a smaller company. We've gone from 300 million now with this major acquisition we've done at Veritas. We're now on the path to being a 2 billion company and the biggest space, number one, but the enormous amount of innovation and we're pouring a lot of engineering including into our exciting new work we're doing on Nutanix, which I'm very excited about. ]]> syndication@connectedsocialmedia.com (Connected Social Media) Cohesity CEO Sanjay Poonan AI-powered Data security 4:28 no Connected Social Media https://connectedsocialmedia.com/21169/addressing-the-overlooked-epidemic-in-mens-health/ Mon, 28 Jul 2025 00:32:32 -0700 https://connectedsocialmedia.com/?p=21169 American Institute for Boys and Men ]]> syndication@connectedsocialmedia.com (Connected Social Media) Addressing the Overlooked Epidemic in Men’s Health 33:49 no Connected Social Media https://connectedsocialmedia.com/21164/it-trends-impacting-it-departments/ Mon, 28 Jul 2025 00:01:06 -0700 https://connectedsocialmedia.com/?p=21164 The Forecast. Video transcript: Jason Lopez: In between press briefings, Lee Caswell tells The Forecast about some of the biggest IT trends, challenges and innovations explored at the 2025 .NEXT event in Washington, D.C. Lee Caswell: We're really interested in that customers get value out of AI. And this is one of the things where a lot of customers today are a little bit stalled trying to figure out, well, hey, I don't want to spend too much. I don't want to spend on the wrong thing. How do I get started, right? And how do I also make sure that the AI that I bring to market has the same enterprise level resilience, the same day-to-day operations, the same security and privacy that I bring for all of my traditional apps. How do I make AI just the next enterprise app? And so we're helping customers basically with choice. So the idea is, what are the fast-changing parts? GPUs are changing pretty fast, so we're going to give you the access to the GPUs or CPUs with acceleration, for example. LLMs are changing fast. Last year, we gave you almost an app store, if you will, into LLMs from our partners Hugging Face and NVIDIA. This year, now we're supporting agentic workloads, which is an iterative cycle where it's not enough to just get an answer. Now, I want to iterate on that answer and give you more relevant results, maybe through guardrails, maybe through re-ranking, maybe through embedding. And so we're giving you all of those access points so you can get started today and have a production-ready enterprise experience. Jason Lopez: Caswell talked about how enterprises are onboarding AI and managing data privacy. Lee Caswell: Well, I think first off, we're helping customers understand the fast pace of the AI market. So most customers today realize that large language models, or they don't have to be that large, it could be SLMs as well, will be developed either in the public cloud or by some of the largest customers because of the incredible capital expense of training a model. So now customers are looking and saying, well, all right, I'm probably going to get access to a model, but how do I make sure now that my data remains private? It could be, for example, that your model becomes more sensitive than the data itself because the model now starts showing you're inferencing your ideas, your insights into the data that you have. And so that idea of saying, it's going to be important to access large language models and change them out. I want to have access to that. We provide that capability. And then I also want to have this ability to go and have more responsible results and be able to go and manage the infrastructure so that it's actually an enterprise-level experience. That's how we're helping customers basically get started with our Nutanix AI, enterprise AI products. Jason Lopez: He tells how Nutanix software helps enterprises build and run a future-ready IT operation. Lee Caswell: Yeah, it turns out, right, you know, the quality of our engineering has been really something that's just been delightful to see as we're bringing all the elements necessary to bring AI into the enterprise. And so that could be, for example, like the storage, right? You have to ingest that data. You've got to run the model. You've got to archive the data. How do you do all of that together? We provide an offer for that. In addition, by the way, many of these models are containerized. And so as you bring containers and Kubernetes, for many customers, these are relatively new concepts into the on-prem world. How do you leverage what you know already today? And here we acquired a company called D2IQ, and we have a terrific set of engineering leadership resources there who are now taking that, what was a production shipping product, and now adding Nutanix data services. It's an incredibly compelling offer and part of the complement of products you need to make AI successful.]]> syndication@connectedsocialmedia.com (Connected Social Media) IT trends impacting IT departments 3:38 no Connected Social Media https://connectedsocialmedia.com/21158/liqid-cto-sumit-puri-composable-it-infrastructure/ Wed, 23 Jul 2025 01:30:35 -0700 https://connectedsocialmedia.com/?p=21158 The Forecast. Transcript: Jason Lopez: Liquid is a software-defined infrastructure company that enables more efficient use of high-cost, high-power resources like GPUs in data centers. Instead of installing GPUs directly into each server, Liquid creates centralized GPU pools and dynamically allocates them to servers based on workload demands. This composable approach maximizes GPU utilization, reducing waste, and improving performance. Sumit Puri: We saw this vision of GPUs being important in the data center many years back, and then all of a sudden this thing called ChatGPT burst upon the scene and made this front and center in everyone's mind. And so we've been focusing on pooling and sharing these resources for a long time, and now all of a sudden AI is forcing itself into the mainstream, especially in the areas that we focus on, things like the enterprise, and now all of it's coming kind of market for us in a very, very good way. And so we ended up building the product, and the market ended up coming our way. [Related: Nutanix CEO Stokes Surge in IT Ecosystem Partnerships] Jason Lopez: Liquid addresses the growing demand for AI inference workloads, especially for enterprises that want to keep their data on-prem instead of moving to the cloud. Sumit Puri: What Liquid focuses on is very much on building power-efficient, cost-efficient solutions for inference. And it's interesting to think whether it's on-prem or it's in the cloud, a lot of the data, which is what a lot of this AI is driven on, it lives on-prem. Eighty-three percent of the data is actually on-prem. And so one of two things must happen. We either must move the data into the cloud, or we must bring the GPUs on-prem. We think there's a lot of customers who are not willing to wholesale move their data to public cloud, and so therefore we want to build efficient solutions to allow them to process their data on-prem. [Related: Swarms of AI Agents Powering Businesses and Daily Life] Jason Lopez: There are advantages of pooling and sharing GPUs instead of deploying them directly in each server. Sumit Puri: There's three primary benefits why somebody takes this journey of pooling and sharing the GPUs. One is around performance. I need that server to have a lot of GPUs because I need it to run very fast. We're not limited by two or four or eight in a box. We can compose 30 GPUs to a server and give you the fastest servers on the planet. That's one reason. The other is cost. If I have to deploy 30 GPUs, do I want to buy four servers, put eight GPUs in every server, buy a bunch of networking? Or do I want to buy a single server, deploy 30 GPUs, reduce my cost, reduce my power, and have a more efficient way of deploying these resources? And the third reason is agility. It's very hard to predict, will my workload need one? Will it need two? Will it need four? Will it need eight? Do I use an H100? Do I use an A100? Do I use an L40S? There's too many choices, and so we try to take the guesswork out of it. Let's put a centralized pool of whatever device type we need and pick the right tool for the right job at the right time. [Related: Search for VMware Alternatives That Meet Existing and Future Needs] Jason Lopez: The AI infrastructure landscape is evolving from training to inference, especially for companies that are not building foundational models. Sumit Puri: The first chapter of this entire AI journey was very much focused on training and building these foundational models. And the way that we see that going forward, there's probably only going to be 10 companies on the planet that can afford to build these massively large 100,000, 200,000 GPU clusters to build the foundational model. The other 100,000 customers that are out there, they're going to take these models, open-source models like Llama, they're going to bring them on-prem, they're going to fine-tune that model, they're going to do RAG, they're going to do inference, and that part of the journey now is just starting. We think by the end of the decade, inference actually is going to be a larger piece of the overall AI pie than is something like the training portion of it. Jason Lopez: Liquid makes AI inference more accessible and efficient for enterprises, especially with Kubernetes and model deployments. Sumit Puri: So NVIDIA has a big push for something called NIMS, NVIDIA Inference Microservices, which is basically a container. And what they've said, it's very, very difficult for people to get all the layers of the stack perfectly right to deploy these models, and so we're going to containerize these models, and that is the way that enterprises are going to go off and deploy this. We have a plugin for our solution where what we do is we suck the container in, we probe the container, we figure out what type of GPU and the quantity of GPU in the backend, and we connect that GPU resource to the specific server in the Kubernetes cluster, then we deploy that container on that machine, so you have this perfect matching of hardware to container, and we automated the entire process. We're at a point now where we have one-click deployment of inference. You say, give me Llama7b go, and we will automate the entire process on the backend, and within two minutes, give you a model that you can speak with. When you're done with it, you hit the delete button, we'll rip those GPUs off, put them back into a centralized pool so that next container, that next model that you're looking to deploy has resources to use. We think that's how you get there, is you have to make it easy for enterprises to deploy these things. They don't have the large armies of data scientists to do this on their own, so the more that we can automate this, the easier it is for those companies to consume, the more that we can make it more efficient, and the way that we think about efficiency is tokens per dollar and tokens per watt, because that's what the enterprises are limited by, they're limited by power and money. If you're a hyperscaler and you have unlimited power, unlimited money, we can't help you. But if you're an enterprise, that is the metric you need to think about. Tokens per dollar, tokens per watt, automation, ease of use, those are the things that are needed to get AI to scale. [Related: Bracing Data Centers for Wave of AI Workloads] Jason Lopez: The company supports virtualization and dynamic GPU allocation in enterprise environments. Sumit Puri: We are a platform for a variety of different applications. One of the applications we are very well suited for is virtualization. If we think about VMs for a second, it's very difficult for enterprises to predict which VM they're going to deploy at what time and what resources that VM might need. We deploy infrastructure for three to five years and making that long-term prediction is very difficult. We've partnered with Nutanix where we can put a centralized pool of GPUs inside of a Nutanix cluster and depending on the requirements of a specific VM, we can match the GPUs on the fly dynamically, hot-plugging GPUs into servers to meet the requirements of the VMs on Nutanix.]]> syndication@connectedsocialmedia.com (Connected Social Media) Liqid CTO Sumit Puri Composable IT infrastructure 7:04 no Connected Social Media https://connectedsocialmedia.com/21154/enterprise-architecture-accelerating-intels-business-transformation/ Fri, 18 Jul 2025 10:15:19 -0700 https://connectedsocialmedia.com/?p=21154 syndication@connectedsocialmedia.com (Connected Social Media) Enterprise Architecture: Accelerating Intel’s Business Transformation 0 no Connected Social Media https://connectedsocialmedia.com/21148/high-hopes-for-healing-exploring-cannabis-therapy/ Mon, 14 Jul 2025 00:56:48 -0700 https://connectedsocialmedia.com/?p=21148 UCLA Center for Cannabis and Cannabinoids, breaks down the spike in usage for both medicinal and recreational purposes, how products and consumption methods continue to evolve and the health conditions for which cannabis is FDA-approved. Tune in to learn more about the urgency for evidence-based guidance on the therapeutic effects, dosing and safety requirements for clinicians, employers and consumers alike. Guest: Ziva Cooper, Director of the UCLA Center for Cannabis and Cannabinoids ]]> syndication@connectedsocialmedia.com (Connected Social Media) High Hopes for Healing: Exploring Cannabis Therapy 44:25 no Connected Social Media https://connectedsocialmedia.com/21099/eat-gobble-and-go-unpacking-american-food-culture/ Mon, 30 Jun 2025 06:40:13 -0700 https://connectedsocialmedia.com/?p=21099 syndication@connectedsocialmedia.com (Connected Social Media) “Eat, Gobble, and Go:” Unpacking American Food Culture 37:09 no Connected Social Media https://connectedsocialmedia.com/21089/2024-25-intel-it-annual-performance-report-it-the-resilient-change-agent/ Wed, 18 Jun 2025 03:01:40 -0700 https://connectedsocialmedia.com/?p=21089

We have developed an enterprise-grade, scalable GenAI platform and a dashboard that enables us to track the lifecycle and business value of all GenAI projects across Intel. 30,000 monthly users have already created more than 7,000 personal assistants, and our 400+ GenAI use cases have generated an estimated USD 376 million in business value.

We are nearing completion of modernizing our enterprise resource planning (ERP) platform. So far, we have over 56 million master and transactional data records loaded, and during our first and second releases, we achieved 100% and 90% data load success, respectively. We are now poised to start scaling our data strategy across the enterprise.

We are transforming our data centers by using sustainable technology like advanced cooling techniques and fuel cell technology; deploying software-defined networking; and evolving our enterprise architecture (EA) processes and practices. The EA effort alone has eliminated more than 300 in-house applications, removed 1,400 commercial software products from the environment, and generated USD 13 million in cost avoidance.

Factory modernization initiatives include implementing a 5G private network and extending our industrial Internet of Things (IIoT). We have also deployed over a dozen robots equipped with multiple integrated IoT sensors; these robots can autonomously roam Intel facilities to perform facility inspections and read values from instrumentation.

We are transforming the employee experience through cloud-based client device management, improving the Wi-Fi experience using client analytics, and benchmarking the PC experience to pinpoint applications that negatively affect battery life. We have cut the number of “How do I…” support tickets by 30% by deploying a GenAI-based chatbot.

We are creating a strong workforce that can keep innovating despite disruption and rapid change. Our new People Council is staffed by leaders who focus on developing and retaining top talent, talent trends, and strategic workforce planning. Our employee training programs center on five top skills for the future: AI, SAP, cloud, business relationship management, and data.

Read the entire APR for the details of these stories and more. ]]> syndication@connectedsocialmedia.com (Connected Social Media) 2024-25 Intel IT Annual Performance Report: IT – The Resilient Change Agent 0 no Connected Social Media https://connectedsocialmedia.com/20971/working-with-cancer-helping-employers-support-employees-impacted-by-cancer/ Tue, 10 Jun 2025 00:54:53 -0700 https://connectedsocialmedia.com/?p=20971 Publicis Groupe ]]> syndication@connectedsocialmedia.com (Connected Social Media) Working with Cancer: Helping Employers Support Employees Impacted by Cancer 35:43 no Connected Social Media https://connectedsocialmedia.com/20963/seeing-swarms-of-ai-agents-powering-businesses-and-daily-life/ Tue, 03 Jun 2025 00:16:39 -0700 https://connectedsocialmedia.com/?p=20963 The Forecast. Podcast transcript: Jeremiah Owyang: The biggest industry right now in AI is the AI agent space. It's destined to grow 10 times every five years. Right now it's estimated at 5 billion, which will go to over 65 billion, and then it’s estimated to be 500 billion just within the next several years. This is the hot market growing within the AI space right now. People use the internet. You physically go out and find different websites to get information. You fill out tasks and you order flights, you order e-commerce, you get things done even inside of your enterprise. You have to fill out expense reports and timecards. All of these things are wasteful and not great experiences in the future. Your AI agents are going to go out and do those tasks for you. The information will be reassembled in the way that you want when you want in a multimodal way, whether it's text, video, ar, vr, whatever time of day that you want, and in the amount of information that you want. It's no longer up to the web designer. It's no longer up to the website or the app designer. It's up to you. [Related: 4 Trends Defining the Future of Enterprise AI] Jason Lopez: What you heard are excerpts from a keynote speech by Jeremiah All Yang, general partner at Blitzscaling Ventures. He also leads an event called the LAMA Lounge and AI community of hundreds of AI company founders. We recently interviewed Jeremiah to tell us more about agents. Jeremiah Owyang: AI agents are dependent upon large language models. Jason Lopez: In just a moment, Jeremiah explains the importance of LLMs to agents. But let's start here. An agent is software code that allows a device to understand its environment process information then acts autonomously to take actions to achieve specific goals. AI agents can do more than common AI assistance that respond to specific user prompts. An AI agent can self task, it can learn over time and even recruit other agents to help. They operate across multiple apps, often working silently in the background even while we sleep. A smart home thermostat or robot vacuum or autonomous vehicle, or just a few examples of AI agents in action. In many ways, AI agents are less like tools and more like digital organisms adapting and evolving in a world built from code. Jeremiah Owyang: As they become more advanced, they operate in sequence, in combination with each other. In concert, which is called the agent crews or fleets or groups or swarms. In many cases, they are like low level human employees. [Related: Managing Enterprise AI Sprawl] Jason Lopez: So how does an agent know what to do? Jeremiah Owyang: They get it from large language models. They're dependent, so it's not if they're a replacement of large language models, they're actually executing the tasks. So think of large language models as your brain with all that knowledge and the things to do, but the actual clicking and typing and doing the actual physical tasks like your limbs, your appendages, your body are the AI agents, and you need both in combination to be an effective quote creature. Jason Lopez: From the point of view of an enterprise, you might be wondering if IT infrastructure needs to change as companies shift from just using LLMs to deploying AI agents. The answer would be yes. An IT team needs to prepare for how agents will interact with the company's systems. This means choosing the right tools or partners and deciding on what permissions and access an agent should have for the tasks it could do. Jeremiah Owyang: It could fill out your expense report after looking at your credit card. It could create meetings or meeting summaries. It could build your monthly reporting deck and grab data from disparate places and aggregate it into one location. It could be like a virtual colleague. It could be just the two of us on a call. We could have three, four, or five assistants that are not just recording, but actually talking, collaborating, taking notes, taking actions, and generating diagrams in real time. [Related: Enterprise AI Reality Check: Implementing Practical Solutions] Jason Lopez: Many companies are already using AI assistance for customer service, handling basic questions using company data, and Jeremiah says, companies are using Gen AI in all sorts of interesting ways. He said 10% of Pfizer's marketing content is being generated by ai. This can help workers be faster and more productive. Jeremiah Owyang: Now, imagine if that worker who just wants to focus on making good decisions or the relationships with customers or relationships with internal stakeholders could allow the AI agent to do all that busy work for them. Now at your company and many companies who has an executive assistant, typically it's only provided to those at the top of the hierarchical pyramid. Now, imagine a world where every worker has one assistant wait, two assistants, wait, wait, wait, 10 assistants, 10 assistants that help with data or meetings or scheduling. Just all of those things. Imagine the level of productivity that can increase for those knowledge workers, and I think we're on the cusp of that because if you interface with just an AI agent, it means you just don't need that many enterprise apps anymore. [Related: A New Generation of Data Centers Spreads Use of Enterprise AI] Jason Lopez: This isn't to say that an AI agent is just a simple addition to a team. Some companies are exploring what it would be like to rely on AI led teams. Jeremiah Owyang: So it's really critical that you as a worker lean into AI and lead that within your company and for your career, or you might have to be updating your LinkedIn profile. So I think it's critical that we lean into this technology. Jason Lopez: We've reported before as we head into the age of ai, there's a skills gap. Companies like Nutanix have AI teams that can build AI into products or create apps that boost business productivity, but using AI as a skill that will be needed across different business units to enhance employee competency. Many companies onboard AI capabilities like Microsoft Copilot or Glean or services like writer.com. Many workers take upon themselves to acquire knowledge and certifications for AI expertise. They turn to YouTube or platforms like Coursera or continuing ed from colleges and universities. Jeremiah Owyang: Every worker is responsible for their continued growth. Now, for executives, there's a new role. There's a chief AI officer leading the charge within the organization to use these tools. Most of the innovation is happening with the young startups, many of them who spun out a big tech or spun out of big companies and they say, I'm going to move much faster. [Related: Business Steps for Using Agentic AI] Jason Lopez: Jeremiah says, small teams are capable of building a global enterprise AI software suite in one year with rapid adoption. Jeremiah Owyang: Crew AI only has 16 employees, and they're already one of the dominant enterprise agent leaders because they're using AI for everything. Jason Lopez: Crew AI is a San Francisco based firm, which makes development tools to build AI agents that do tasks in apps like CRM or ERP systems. Jeremiah Owyang: They are what is called an AI-first mentality. So let's talk about an AI first mentality. This is a common mental framework within Silicon Valley, amongst the AI leaders. If you have a problem in your life, you first see if there's an AI that exists off the shelf, whether it's an app you download or an enterprise app that's an existing enterprise software. If it doesn't exist, then you try to build it and step three, if it doesn't, you can't build it. Then you hire somebody to build it. So you follow that lineage to think about, how do I move fast? And it's always about leveraging AI first. So that's the AI-first mindset. [Related: AI and Cloud Native Skills Reshape Careers] Jason Lopez: Building on the rise of enterprise AI platforms and the growing availability of ready-made templates. The next logical step is even more transformative. As tools become more accessible in development, more streamlined, the creation of AI agents is starting to shift as well, possibly even to the agents themselves. Jeremiah Owyang: We are probably going to see AI agents create AI agents. There's already no-code AI, so developers can be even more efficient and can create even faster. I anticipate that developers and software engineers, they're still needed. We need them more so they can just produce more. I don't see them going out of a job. That's our take in this Jason Lopez: Space. Still, the development of AI agents in the enterprise lags behind the customer side. A lot of that has to do with security. Jeremiah Owyang: One rogue AI system within an enterprise, potentially from a nation that is not friendly with your nation, could upend your company. It could grab data and send it back to the home country. So I think there are appropriate concerns around ensuring that the AI is safe for the enterprise and the organization eventually, which would help with the customer relationships. So I think that's why we see that lag. [Related: CIOs Sharpen Skills for the AI Era] Jason Lopez: Jeremiah points out that while AI agents can be like coworkers, they're not human, but powerful tools, tools that aren't neutral because they mirror the intentions of people. Jeremiah Owyang: The old adage in Silicon Valley that you and I know quite well is that if the product is free, then you are the product. If you're paying a premium, whether it's enterprise or consumer for the AI agent, then it is more likely to be aligned for your benefit. If not, then it is more likely to be towards the benefit of the builder. And I think the old business models in Silicon Valley apply here. They're tools, and we have used Fire for cooking, which helped us to expand our brains with more nutrients by having clean food. We've used steel to build amazing vehicles and buildings, but we've also used fire and steel for weapons, and that choice is very much a human thing where we choose how to use these tools and technologies. The difference here with AI though is that it is a thinking machine and it's trained off what humans will do, and it starts to think or simulate thinking on its own, and that's something we haven't seen before in every possible way you look at this, it's an embodiment of the human condition, and that is a wild thing to think about, that we're creating a new species. Jason Lopez: Jeremiah Al Yang is the founder of Lama Lounge AI events, and he's a partner at Blitzscaling Ventures. You can find out more about his events at lu.ma/lama lounge. This is the Tech Barometer podcast. I'm Jason Lopez. Thanks for listening. Tech Barometer is a production of the forecast where you can find more stories about artificial intelligence as well as cloud and enterprise computing. Look for those at the forecast by nutanix.com, all one word, theforecastbynutanix.com.]]> syndication@connectedsocialmedia.com (Connected Social Media) Seeing Swarms of AI Agents Powering Businesses and Daily Life 11:25 no Connected Social Media https://connectedsocialmedia.com/20961/itintel-it-resiliency-drives-a-resilient-enterprise/ Tue, 03 Jun 2025 00:07:02 -0700 https://connectedsocialmedia.com/?p=20961 syndication@connectedsocialmedia.com (Connected Social Media) IT@Intel: IT Resiliency Drives a Resilient Enterprise 0 no Connected Social Media https://connectedsocialmedia.com/20958/itintel-transforming-siloed-manufacturing-data-into-unified-insights/ Sat, 31 May 2025 00:01:51 -0700 https://connectedsocialmedia.com/?p=20958 syndication@connectedsocialmedia.com (Connected Social Media) IT@Intel: Transforming Siloed Manufacturing Data into Unified Insights 0 no Connected Social Media https://connectedsocialmedia.com/20952/nutanix-ceo-stokes-surge-in-it-ecosystem-partnerships/ Tue, 27 May 2025 00:01:51 -0700 https://connectedsocialmedia.com/?p=20952 The Forecast. Podcast transcript: Jason Lopez: One of the key messages from the 2025 Nutanix .NEXT Conference in Washington DC: the expanding partner ecosystem. This is the Tech Barometer Podcast, I’m Jason Lopez. dot-NEXT is where enterprise IT professionals come together with an eye on building their future on the Nutanix software platform. One thing we learned this year is companies like Pure Storage, NVIDIA, and Dell will play a key role in delivering integrated solutions to customers, in areas like enterprise AI and infrastructure modernization. The Forecast’s Editor in Chief, Ken Kaplan, recorded this walk-and-talk with Nutanix CEO Rajiv Ramaswami as he headed to another session at the .NEXT conference, which continues to build in numbers of attendees and partners. Rajiv Ramaswami: Yesterday I was at the Partner Summit. I believe there were 1,600 partners in attendance. So a lot more. The partner network is expanding. Our ecosystem partners are growing. This year I think we had about 85 plus, 86 I think, sponsors for the event. A few years ago it was 25. So I think we've come a long way. [Related: Get a Grip on Data Storage in Quest for Enterprise AI] Ken Kaplan: Yeah, the theme for me is partners and Pure Storage was a big announcement. What is it like to work with NVIDIA, Dell, all these partners you've been talking about for years, but you're really close with them now. Rajiv Ramaswami: It all comes down to can we work together to create something of value that each of us brings together and create a solution for the customer. That is the core of every partnership. You look at NVIDIA, it's all about enabling enterprise AI. If you look at Pure, it's about providing customers with choice. Many of the large install base of customers out there with Pure Storage and now they all have an option to be working together with the Nutanix Cloud Platform and Pure. It's all about providing a better solution and experience for customers. Ken Kaplan: There was Cisco, Dell, NVIDIA. What's driving all this togetherness now? Is it a push for AI? Is it a push that there's really a lot of innovation and we got to get together on the same page? Why is this happening now? Rajiv Ramaswami: It's across all the themes that we talked about. Modernizing infrastructure, building cloud native applications, enabling enterprise AI, and depending on the partner specifically, it's one or all of these vectors. [Related: What’s Driving IT Decisions Around Enterprise AI and Cloud Native Technologies] Ken Kaplan: Do you anticipate more of this happening or does this thing start to close up or are we in a real open go, go, go period? Rajiv Ramaswami: We've always been a company that's focused on creating a platform and a platform always has an ecosystem around it. I do expect our ecosystem to continue to grow and flourish. Do you see the customers wanting this kind of openness? Absolutely. This is creating a huge value for customers because they know that we can't provide everything and so combining solutions together, if we can make it work well, yes, absolutely. Ken Kaplan: Have you seen some of the customers, once they have these capabilities, start going in new directions? You mentioned a customer who came on stage with you and now they're getting into AI. Rajiv Ramaswami: Their needs are evolving as well. They may have been running traditional infrastructure stuff on us. They may have been running VDI workloads on us. They're running mission critical databases on us these days. Now they're running AI on us. Their needs evolve and we as a platform continue to work hard to evolve with them. [Related: AI Lifecycle’s Impact on IT Infrastructure] Ken Kaplan: The last thing here: we're seeing a lot of people talking about VMs and having cloud native. Are they doing these things and don't know it or is it just something they have to do now going forward? Rajiv Ramaswami: They're all going to have a mix of their traditional applications at the same time be looking at building modern applications and they actually have to do both. They have to run their traditional ones and they have to at the same time be building modern ones and figuring out how to run all of these very efficiently. Jason Lopez: Rajiv Ramaswami is the the CEO of Nutanix. Ken Kaplan is the Editor in Chief of the Forecast, the producer of this Tech Barometer podcast. They spoke on the floor of the .NEXT conference in Washington DC. .NEXT will move to Chicago in April 2026.The Forecast reports on the enterprise computing industry can be found at theforecastbynutanix dot com. I’m Jason Lopez, thanks for checking in.]]> syndication@connectedsocialmedia.com (Connected Social Media) Nutanix CEO Stokes Surge in IT Ecosystem Partnerships 04:29 no Connected Social Media https://connectedsocialmedia.com/20950/tune-in-to-well-being-with-the-healing-power-of-music/ Mon, 12 May 2025 01:23:01 -0700 https://connectedsocialmedia.com/?p=20950 Stanford Medicine ]]> syndication@connectedsocialmedia.com (Connected Social Media) ‘Tune in’ to Well-being with the Healing Power of Music 32:23 no Connected Social Media