ASL: Keynote by Antonio Neri – Architecting AI starts with your network

[00:00:00] what does it mean to be an architect an artist a scientist an engineer [00:00:16] a visionary who designs with intelligence creativity and precision in every angle [00:00:26] from the first inspiration to the first lines from blueprints to breakthroughs [00:00:38] today we're in a new ai era where you can be an architect [00:00:45] we're here to make everything you can imagine possible with a foundation designed for what's [00:00:51] next it starts with your network intelligent secure and self-driving then cloud hybrid by design [00:01:06] with flexibility and control across your entire estate and ai transforming your business faster than [00:01:16] ever so whether you're architecting ai for a data center an agentic enterprise or a vision of tomorrow [00:01:26] you can build what's next and change the way we live work and dream [00:01:38] opportunity is all around us and you hold the key to what's possible we're here to give you the [00:01:46] intelligent secure foundation to build upon so you can unlock your boldest ambitions let us show you how [00:02:08] what's next now are you ready to discover what's next [00:02:19] please welcome to the stage hpe president and ceo antonio niri [00:02:35] good morning wow that's a big crew it is great to be here with you [00:02:42] hp discover is where we showcase showcase what is next and shine a light [00:02:48] on the ambition and innovation shaping our industry and our lives today we are witnessing one of the [00:02:56] largest technology platform shifts in history workloads and applications are moving from being [00:03:03] one of the largest technology that are driven by we are driven by end users but now being driven by both [00:03:07] end users and ai agents agents agents that will fundamentally transform how we design and build how [00:03:14] we serve our customers and how we operate our businesses i have always been drawn to how things work [00:03:21] how systems are built and how they evolve over time in fact if i have not become an engineer and a ceo [00:03:30] how we have become an architect architecture like engineering teaches you to think in systems [00:03:38] to build for today and for the needs of tomorrow you don't design a building around a single room [00:03:46] you design a structure that allows the whole system to flow and adapt over time architecting for ai demands [00:03:54] the same focus and discipline fundamentally ai is only as strong as the data foundation beneath it [00:04:03] if the foundation is not robust nothing else holds across networking cloud and ai hp is the is [00:04:11] delivering the essential building blocks that make your ai ready foundation possible networking to connect your [00:04:20] infrastructure infrastructure and workloads at scale cloud to enable you with a hybrid operating model to run [00:04:27] new workloads and application where they belong an ai to turn your data into intelligence and put it to work [00:04:35] architecting for ai starts with your network for years hp aruba networking has helped you deliver secure [00:04:43] connectivity across campus branch and the edge creating the digital on-route that connects your users devices [00:04:51] and data with the addition of juniper networks we have extended that leadership into the data center and [00:04:59] across the critical networks connecting the ai era scale up scale out and scale across with our combined hp [00:05:09] networking organization our goal is to deliver the best user and operating operate operator experience possible [00:05:18] we will do this through our next generation of secure self-driving networks across every domain they fix [00:05:26] problems securely before they impact the experience we make new rollouts faster and easier and fundamentally [00:05:36] transform how you how you manage your network whether you are on the hp aruba central or hp mests you get the [00:05:45] full benefit of our accelerated innovation of both nobody is left behind on the road to self-driving [00:05:55] but the phrase self-driving may have caused some confusion with the mercedes formula one drivers let's take a look [00:06:05] through seeing pink performance and just wait until we move to self-driving wait what do you say self [00:06:10] what not to self-drive self-optimizing self-protecting self-healing this is the real deal and everyone's cool with this [00:06:18] yeah [00:06:24] gimme we all good i don't know are we [00:06:31] gimme we're good we're good we're good good because it doesn't just assist it runs itself so you [00:06:49] two can do everything else even faster yeah of course self-driving network i wasn't worried not for a second [00:06:59] but i wish we were self-appealing i'm only 19 i still am [00:07:11] i had the opportunity to talk to both drivers this past weekend and they told me they have fun doing [00:07:17] that video but the reality is that they really are very very keen and interested to understand technology [00:07:23] so congratulations to the mercedes team for a fast fantastic year so far [00:07:29] every ai architecture needs more compute in the ai era your servers need to operate more efficiently [00:07:36] than ever with hp proline gen 12 you gain the performance to run everything from enterprise world [00:07:42] load to ai inference in a much smaller more efficient solution as ai you know moves from generating content to [00:07:50] taking action the demands on the compute are increasing agentic ai requires fast orchestration continuous [00:07:58] evaluation and real-time access to data which shifts more pressure to the host cpu [00:08:05] that is why we are expanding our proline portfolio with the new hpe proline compute dl 394 394 gen 12 [00:08:14] powered by nvidia beta cpus [00:08:18] beta provides the low latency memory access bandwidth and coherence required for agentic ai [00:08:25] reinforcement learning and other cpu intensive workloads it does so with the security needs of management you [00:08:33] you expect from proline as ai moves beyond the data center compute needs to move with it we recently [00:08:41] expanded our proline age portfolio bringing secure ai ready compute to racked and distributed environments [00:08:49] so that inference can happen closer to where decisions are made ai also needs to reach the always-on systems at the core of digital business [00:08:59] that is the most advanced services with hp non-stop we are bringing ai power fraud detection [00:09:04] and autonomous operations into high volume payment processing this helps financial institutions detect [00:09:12] fraud faster automate compliance monitoring and keep transactions moving safely the most advanced [00:09:19] servers in the world are only as valuable as the data they can access which makes storage a critical part of your ai [00:09:28] foundation the hp eletra storage mp x10 000 makes your data accessible context rich and ready to continuously feed your ai data pipelines [00:09:41] across the full life cycle from ingestion training inferencing continuous learning [00:09:47] the x10 000 now supports native file and object storage on a single architectural [00:09:53] value of your data failure it is also the first object storage platform validated through nvidia certified storage [00:09:59] for enterprise ai and for the mission critical applications around your business the aletra storage [00:10:07] mp b10 000 continues to deliver the b10 000 is the fastest growing all flash block storage array in the market [00:10:18] Sitting across the top of the stack, of course, is software. As AI advances, enterprise environments are becoming more distributed and complex. [00:10:30] They spend virtual machines, containers, AI infrastructure, and, of course, public and private clouds. [00:10:36] At the same time, rising virtualization costs are pushing many of you to look for more flexibility and choice. [00:10:45] With HPE Cloud's Ops software, we have brought together HPE Morpheus, OpsRAMP, Zerto, and our broader cloud portfolio capabilities into one unified operating experience. [00:10:58] This enables you to modernize on your own terms while simplifying how you provision, observe, and protect your hybrid multi-vendor environments. [00:11:10] Security and resilience must be built into every layer of the stack of your architecture. [00:11:19] As AI changes the speed and the scale of cyber threats, new risks continue to emerge. [00:11:26] Resilience is no longer just a set of isolated tools. [00:11:32] It is a converged strategy across your systems, your data, and your network. [00:11:38] With HPE ILO Silicon Router Trust, we provide secure attestation from the silicon to cloud, helping verify that your infrastructure is trusted before your workloads run. [00:11:52] And with Zerto and Cyber Resilience Vault, we help protect your critical data, so you can recover faster and minimize disruption. [00:12:03] Networking and security are also converging. [00:12:07] As AI becomes more distributed, the network often is the first place to see what is happening across your enterprise. [00:12:16] With zero-trust architectures and integrated SASE, the network becomes an active security layer, enforcing policy, detecting threats, and reducing risk from edge to cloud. [00:12:30] We bring all the elements of your AI foundation together with our GreenLake cloud. [00:12:38] GreenLake gives you a unified cloud-native experience across your entire hybrid state. [00:12:45] With the flexibility to run workloads across public and private clouds, colors, and, of course, at the edge. [00:12:53] With GreenLake Intelligence, we bring agentic AI to hybrid IT operations, helping you see across environments, act faster, and continuously optimize performance. [00:13:07] From simplifying network operations to streamlining virtual machine migrations, GreenLake Intelligence makes your infrastructure more adaptive, more autonomous, and easier to manage. [00:13:20] So you can spend less time managing tech and more time managing and advancing your business. [00:13:27] So let's take a look. [00:13:31] GreenLake Intelligence is already inside HPE Aruba Central. [00:13:37] So when a major internal announcement is added to the calendar, you can ensure video call performance in advance. [00:13:45] It runs on historical telemetry data and analysis. [00:13:47] So when you ask for recommendations, it highlights likely points of strain and prioritizes video call traffic to keep your team online and on camera. [00:14:00] It's already in operations, so you aren't just getting alerts. [00:14:04] Agents evaluate and correlate them in real-time across infrastructure, cloud, applications, and operations. [00:14:12] Because what's causing an issue isn't always where you see the symptom. [00:14:17] GreenLake Intelligence combines frontier AI models with operational contexts to reason across domains. [00:14:24] Correlating telemetry, dependencies, and signals across the stack. [00:14:29] Delivering clear, concise information. [00:14:32] Turning observation into understanding. [00:14:35] Identifying probable root cause, even when it exists elsewhere in the environment. [00:14:39] And recommending or executing remediation. [00:14:43] And GreenLake Intelligence is already in the mesh of agents accelerating VM migration. [00:14:49] Pre-validating your plans. [00:14:51] Testing compatibility and capacity. [00:14:53] Network configuration. [00:14:55] And storage access. [00:14:57] Weeks of work. [00:14:58] Completed in minutes. [00:15:00] GreenLighting moves that reduce expenses without costing you performance. [00:15:05] This is GreenLake Intelligence. [00:15:13] It's an amazing advancement we brought with HP GreenLake. [00:15:19] But by the way, what you saw here is just the beginning. [00:15:23] In the Discover showcase, you can see how GreenLake Intelligence brings agentic AI operations to life. [00:15:29] So I will encourage you to go and experience yourself. [00:15:34] Architecting for AI takes more than technology. [00:15:36] It also requires the right people, processes, and partnerships. [00:15:40] Our services team is here to help you through your AI transformation. [00:15:46] With the HP Financial Services, we help you modernize with confidence and better economics. [00:15:51] Including lower upfront capital investment. [00:15:55] And with our IT lifecycle management program, you can retire legacy multi-vendor technology. [00:16:00] And turn that value into funding what is next. [00:16:05] This week is an opportunity to explore our full-stack AI foundation firsthand. [00:16:10] With demos, sessions, and in conversations with your peers. [00:16:15] Discover is one of the few moments where we have the full power of the HP community together in one place. [00:16:24] During the rest of our time this morning, I want to elaborate on two core tenets of our strategy. [00:16:30] First, the networks that are at the heart of today's AI data center build-outs. [00:16:37] And second, how we are enabling your transformation into an agentic enterprise. [00:16:42] In the AI era, the network is both the essential enabler and the main bottleneck for performance. [00:16:50] Nobody understands what is at stake more than our customers who are at the leading edge of AI. [00:16:57] Customers like Vulture, the world's largest privately held hyperscaler. [00:17:02] Let's take a look at what HPE and Vulture are building together. [00:17:19] Right now, everything is changing all at once. [00:17:23] AI is reshaping our lives and the way we do business. [00:17:27] People ask me if infrastructure is overbuilt for what's coming. [00:17:31] The reality is, we're not even close. [00:17:34] At Vulture, we saw this opportunity early. [00:17:37] So we got ahead of it. [00:17:39] Today, we're a global cloud infrastructure company engineered for enterprise rigor and massive-scale AI. [00:17:45] Opened by design, from architecture to stack to community. [00:17:51] Powering some of the most used real-time platforms in the world. [00:17:55] From model training, to inference, to production at scale. [00:18:01] But to lead in AI, technology alone isn't enough. [00:18:05] You need people. [00:18:07] You need trust. [00:18:08] You need the right partners. [00:18:10] This is why HPE is essential and trusted by enterprises. [00:18:16] Success depends on how fast data moves. [00:18:18] With HPE networking, Vulture can scale AI infrastructure globally, in real time, without bottlenecks. [00:18:26] It's open, automated, and built to adapt. [00:18:30] Not just for tomorrow's applications. [00:18:33] For the ones we haven't imagined yet. [00:18:37] This is the new industrial revolution. [00:18:40] Together, let's make it extraordinary. [00:18:48] Thank you to the entire Vulture team for being such a great partner. [00:18:59] I'm excited to share that this partnership continues to expand as we work together with NVIDIA to support Vulture's next phase of growth. [00:19:08] What Vulture is building at hyperscale points to a truth that every architect knows. [00:19:14] That there is always one core element of your infrastructure that touches everything. [00:19:19] With AI, the core element is the network. [00:19:22] The performance of your entire architecture depends on it. [00:19:26] Every byte, every token, every decision, all of it crosses the network. [00:19:32] Which is why, today, we are bringing the HPE Juniper network into our AI data solutions, enabling more efficient, high-performance AI environment. [00:19:43] Whether you are a hyperscaler service provider or a neocloud, or a large enterprise, you have more choice in how you connect and secure your largest AI investments. [00:19:54] Let me show you how it all comes together, starting with a model training use case. [00:20:01] An AI data center design has one purpose, turning data into intelligence as quickly and as efficiently as possible. [00:20:10] At this scale, performance depends on how tightly computer networking work together. [00:20:16] For customers building AMD-based systems with Helios, we are introducing the industry-first HPE Juniper networking scale-up switch, purpose-built for the AMD Helios architecture. [00:20:31] The QFX 520, the QFX 520, brings scale-up performance into an open Ethernet fabric designed for AI at scale. [00:20:39] It connects 72 GPUs into a single rack, delivering 260 terabytes per second of aggregate scale-up bandwidth. [00:20:51] You get the low latency performance required for large-scale AI workloads, with the openness of standard-based Ethernet Sonic OS support and Juniper AI automation. [00:21:06] But one rack is just the beginning, the largest models trained across hundreds, even thousands of racks operating as a one cohesive cluster. [00:21:16] Multiply a small delay across hundreds of thousands of GPUs over weeks of training, and your network can mean the difference between training a new model in 90 days or 30 days. [00:21:30] Think about that. [00:21:30] Think about that. [00:21:31] It is the difference between chasing a breakthrough or making one. [00:21:36] That is why the scale-out network is so important. [00:21:40] The Juniper QFX 520 is built for this next generation of AI scale-out connectivity. [00:21:48] Our newest addition to the portfolio is shipping today. [00:21:52] The QFX 5250 is the world's highest-performance, 100% direct, liquid-cooled, ultra-Ethernet transport-ready switch. [00:22:02] Powered by Junos OS, it moves data across massive AI clusters. [00:22:08] It achieves this through low latency congestion control and operational simplicity required to keep hundreds of thousands of GPUs working together. [00:22:19] Increasingly, AI data centers are expanded beyond single sites. [00:22:24] Let's find multiple data centers and regions, sometimes hundreds or even thousands of miles apart. [00:22:31] That puts new pressure on the network between these environments. [00:22:36] That is where the HP Juniper PTX routing family excels. [00:22:42] PTX is built to carry massive volume of traffic across the data center interconnect core and edge networks that connect today's distributed AI infrastructure. [00:22:55] Our PTX 12000 series is an ultra-dense routing platform designed specifically for AI fabrics. [00:23:02] It enables 800 gig routing, 1.6 terabit radio scale, and ZR, ZR Plus coherent optics to connect data centers across sites without compromising performance. [00:23:16] And to protect that connection, we have our HP networking SRX family, including our most popular firewall, the SRX 4700. [00:23:25] It is one of the fastest quantum-safe firewalls on earth, delivering up to 1.4 terabits per second of security performance in a single rack unit. [00:23:39] It helps you secure modern data centers without slowing down the application, and AI workloads you depend on it. [00:23:48] But when we talk about a complete portfolio for AI training, we support every layer of a modern networking architecture, from scale-up and scale-out, to scale-across, and secure data access. [00:24:03] All in a single coherent architecture that is secure and fully automated. [00:24:09] With the introduction of the HP AI grid with NVIDIA at GTC in March, we extended this integrated network even further. [00:24:19] Built for service providers, the AI grid combines NVIDIA accelerated computing and AI networking, including Spectrum X, Connect X, and Bluefield, [00:24:30] with ProLiant Compute and Juniper Routing, security, and unified orchestration across the full stack. [00:24:39] Together with NVIDIA, we are enabling a wide range of new real-time AI services, from conversational agents and interactive media to hyper-personalized experiences across hospitality, healthcare, and retail. [00:24:56] But the real value of AI increasingly comes from inference. [00:25:02] When intelligence moves closer to your users, applications, and data, that requires a network built to extend AI to the edge locations like regional data centers and service providers sites, [00:25:15] where the Juniper MX family of edge on-run routers is top of the class. [00:25:23] Our MX 301 brings the proven performance and flexibility of the MX family into a small form factor, a one, RU, power-optimized platform. [00:25:35] It is purpose-built to move AI inference out of the cloud and closer to where the data is processed for inferencing, so we can accelerate decision-making. [00:25:44] Powered by Juniper's sixth-generation Trio Silicon, it has near-infinite flexibility to meet your networking needs today and into the future. [00:25:54] To build your inference environment, you also need a high performance switching. [00:26:01] That is why today we are introducing the new HPE Juniper Networking QFX 5140 Inference Switch, purpose-built for distributed AI deployments. [00:26:12] Also, in one, RU, the QFX 5140 delivers up to 16 terabytes per second of switching capacity, connecting GPUs and inference infrastructure with the AI-optimized load balancing and end-to-end congestion control to maximize performance. [00:26:30] The 5140 gives every edge location the local intelligence to host AI workloads closer to where inference is needed for faster AI responses and better experiences. [00:26:42] But look, the bottom line is to win in the AI era, you need a network built for the full AI lifecycle, from training at the core to inferencing at the edge. [00:26:55] AI is also transforming the demands of the campus and branch networks. [00:27:01] They still need to securely connect people and devices. [00:27:06] But now, they also need to support AI power workflows that depend on real-time access to data without compromising speed, security and reliability. [00:27:18] That level of complexity cannot be managed through reactive troubleshooting alone. [00:27:23] Your network has to see more, understand more, and do more. [00:27:29] Self-driving networks move IT from reactive troubleshooting to proactive assurance, understanding experiences, identifying root causes, and resolving issues faster. [00:27:41] In the race to self-driving, HPE continues to lead. [00:27:45] In fact, we were recently recognized as a leader in the Gartner Magic Quadrant for both wire and wireless LAN for the 20th consecutive year. [00:27:56] Position, highest in the execution and furthest in vision. [00:28:05] What matters most is what this capability means for customers like the Milano Cortina Winter Olympics, where HPE helped deliver flawless network performance across a very complex environment spanning 15 venues hundreds of miles apart. [00:28:23] HPE mist adapted the network in real-time, helping ensure seamless, secure connectivity for everything, from broadcast, live streams, to event operations, and fun engagements. [00:28:36] Every moment, every moment could be viewed by millions. [00:28:40] I hope you watched the Olympics, while organizers operated with confidence, knowing the self-driving network was working behind the scenes to maintain a rock-solid performance. [00:28:53] Today, we are extending this self-driving experience across our Aruba networking portfolio with two new announcements. [00:29:02] First, Aruba CX switching is coming to HPE mist. [00:29:09] You gain AI-native assurance, faster troubleshooting, and automated operations across your campus and branch environments. [00:29:20] And second, which is where we talk about cross-polymenting, right, with Rami, Marvis' actions is coming to HPE Aruba Central. [00:29:32] Marvis is the first network assistant in the industry to bring conversational AI to networking, so your network can move from reactive to self-driving, with AI-native operations that are continuously improving. [00:29:48] So you can see how much progress we have made with Juniper in such a short period of time. [00:29:55] We are really proud of the progress we are making for you, our customers, and our partners. [00:30:01] But across industries, customers are making the switch to HPE networking and discovering that the self-driving network is a quiet network because it just works. [00:30:12] That is the experience we want every one of you to have. [00:30:16] If you are considering a change from your current networking provider, you know who those are, I encourage you to start with a single site or even a single floor. [00:30:27] Experience what a self-driving network can do in your environment. [00:30:32] You will be amazed at how simple the experience is. [00:30:36] And I will ask you to not miss Rami's Rami's generalization later today, plus our four networking spotlights throughout the week to see how our self-driving capabilities are coming to life across every single domain. [00:30:53] We have talked about the networks that make AI possible and how HP is delivering the next generation of self-driving networks that are self-healing, self-protecting, and self-optimizing. [00:31:05] Now, let's turn to the next major shift in the AI era, the rise of the agentic enterprise. [00:31:14] AI is no longer just a tool for finding answers. [00:31:18] It is a critical part of how work gets done. [00:31:23] Agents now reason across data applications, models, and workflows. [00:31:29] They help you make decisions, automate processes, and are increasingly taking action on your behalf. [00:31:37] Soon, IT will be responsible for thousands of agents that are part of your enterprise workforce, operating across every function. [00:31:47] But today, much of that innovation is still happening on local clients, in the hands of developers, and small teams, often outside formal IT oversight. [00:31:59] That speed of adoption is exciting, but also creates a real challenge, the shallow cost of an agentic workforce that now must be managed at scale we have never seen before. [00:32:14] Agentic AI demands a new set of enterprise requirements. [00:32:18] Agents need to be secure and governed. [00:32:21] We clear guardrails for what they can do, what systems they can act on, and most importantly, what data they can access. [00:32:30] They need to be trained with trusted enterprise data, because the agents are only as good as the data and context behind them. [00:32:39] And they need also infrastructure that can scale as demand grows without runaway costs. [00:32:47] When we introduced our HP Private Cloud AI two years ago, we gave enterprise a turnkey AI factory that simplified AI adoption and provided more control. [00:33:00] It brings AI to your data, not the other way around. [00:33:04] So today, we are enhancing Private Cloud AI for the next generation of agentic workloads, helping you govern agents, ground them in trusted data, and scale your inference initiatives. [00:33:16] Let's unpack what is new, starting with agentic governance. [00:33:20] You can now register agents built in any framework and wrap them with security controls that protect API calls, identity, and encryption with zero code changes required. [00:33:34] A new three-tier identity model verifies the user, governs the agent, and enables human approval for sensitive action. [00:33:43] Today, we're also announcing a new capabilities for secure agentic operations with NVIDIA, OpenShell, and Nemo Cloud. [00:33:51] OpenShell provides a model and active runtime for advanced private AI agents with policy enforcement built into how agents run. [00:34:02] Each agent operates in its own isolated environment with guardrails for what data it can access, what systems it can interact, [00:34:11] and what actions it can take, and with Nemo Cloud, you get an open-source reference stack and blueprints for governed agentic workflows, [00:34:21] helping you move faster while maintaining the control and accountability enterprise AI requires. [00:34:29] As agents operate across production environments, they also need a new class of operational risks, introduce a new class of operational risks. [00:34:38] And that's why we are bringing Zerto to your agentic enterprise. [00:34:45] If an agent makes a mistake, Zerto helps you quickly roll back to a clean state, reducing downtime, and helping you protect your business. [00:34:57] Governance in your agentic enterprise is paramount, but governance alone is not enough. [00:35:04] Your AI agents are only as smart as the data you used to train them. [00:35:10] Traditionally, that data requires custom preparation for every use case, a month of building the right AI data pipelines, but not anymore. [00:35:21] Private Cloud AI helps make that data you already have, ready for agentic enterprise, or for agentic AI. [00:35:29] With a governed data layer and integration with the NVIDIA AI data platform, you get a unified way to access, repair, and manage enterprise data across your existing environments. [00:35:43] Now with Alletra Storage MPX 10,000 as the storage layer for Private Cloud AI, you can build on a high-performance data foundation designed for modern AI. [00:35:56] The X10,000 adds real-time metadata enrichment and native MCP support, so your agents and applications can retrieve the right data and context faster across structured and unstructured data. [00:36:13] That means less custom integration work, and 7 to 12 times a month faster time to value compared to what you normally do, which is yourself builds the whole environment. [00:36:27] Once you have governed agents and trained them with the right data, it is time to scale across both agentic AI and your broader enterprise inference workloads. [00:36:41] Private Cloud AI can now serve larger models across multiple systems with multi-node inference, so capacity grows with a mat. [00:36:51] A new unified gateway, simplified access to frontier and open source models. [00:36:57] This gives your team one unified API for model access with centralized credentials, budgets, and policies. [00:37:06] We're also expanding private cloud AI with new configurations that scale up to 256 GPUs, including the new ProLiant DL394 with NVIDIA Beta CPUs, designed specifically for influencing. [00:37:25] And for long context workloads, we're also introducing shared KB cache capabilities that reduce the need to recompute context over and over. [00:37:35] This delivers significant cost benefits to first token and massive performance gain in compute capacity. [00:37:45] With Private Cloud AI, you have now the foundation to build your agentic enterprise with confidence. [00:37:53] And what makes us stronger is the ecosystem we have built around it. [00:37:59] We continue to expand the HPE Unleash AI program, our curated ecosystem of validated partners, blueprints, and orchestration frameworks for private cloud AI. [00:38:11] With more than 60 partners and hundreds of use cases, Unleash AI helps you find trusted solutions for scaling AI across your enterprise. [00:38:21] From securing agents and models with partners like CrowdStrike and Fortinex, to expanding where you can deploy AI with digital reality and equinex, Private Cloud AI and the Unleash AI ecosystem help you move from AI ambition to real-world impact faster. [00:38:41] Let's take examples of that, for St. Jude's Children Research Hospital, that means bringing AI closer to doctors and researchers. [00:38:50] Accelerating life-saving discoveries while protecting highly sensitive medical data. [00:38:56] For Blue Star Operations, the business behind the Dallas Cowboys, it means reducing lower-value work streams and advancing strategic decision-making across football and business operations. [00:39:10] For the Ryder Cup, it means being able to power real-time event intelligence from crowd management and concessions to volunteer assistance and operational planning. [00:39:21] In fact, the Ryder Cup organization are now leveraging the private cloud AI to turn the next event in a massive success by really using a digital twin approach, [00:39:36] so they will help them architect the 2027 tournament experience. [00:39:42] But look, these are just a few examples of how we are giving you a faster, more structured path to AI adoption, [00:39:50] that will transform how you run your business. [00:39:54] And there is more to come. [00:39:56] Tomorrow, Fidel Marrusso will share additional news in her CTO General Session, [00:40:04] and go deeper in how our latest cloud and AI innovations help you build a new operating model for your agentic enterprise. [00:40:14] AI today is about moving faster from ambition to outcome, accelerating time to token, [00:40:20] reducing execution risk, and ensuring your environments are ready to perform from day one. [00:40:27] Our AI factory solutions are designed to do exactly that, with validated architectures, agentic operations, and enterprise-grade support. [00:40:36] They also meet you where you are, designed for your unique operating models, governance needs, and scale. [00:40:43] For enterprises, I share how private cloud AI is a secure and governed, prepackaged AI factory for your agentic enterprise. [00:40:55] For model builders, service providers, and neoclouds, our AI factory at scale is built for large, multi-tenant AI environments. [00:41:04] And for governments, regulated industries, and sovereign entities, our AI factory for sovereigns enables you to deploy AI aligned to your local data, security, and compliance requirements. [00:41:16] Across our AI factory portfolio, our deep collaboration with NVIDIA helps you build the latest accelerated computing platform like NVIDIA beta and beta-rubin. [00:41:28] NVIDIA beta-rubin architectures are advancing our great portfolio for both HPC and AI. [00:41:46] And in AI factories at scale, NVIDIA beta-rubin MVL72 is driving the next frontier of rack-scale solutions. [00:41:55] Compared to NVIDIA Blackwell, beta-rubin MVL72 delivers AI training with one-fourth of the GPUs and AI inference at the one-tenth of the cost per million tokens. [00:42:11] So think about that, the massive gains you can get to get to get to that token faster. [00:42:18] So whether you are building for the enterprise or training frontier models, HPE gives you a path to build and scale on the latest NVIDIA accelerators. [00:42:32] As AI scales, scales across more users, more data, and of course critical operations, trust must be built into that foundation. [00:42:44] That is why we are making confidential computing standard across the full HPE AI portfolio, helping protect sensitive data, models, and workloads while they are in use. [00:42:59] With NVIDIA confidential computing, AI workloads run in trusted execution environments that add a hardware-protected layer of security across the stack. [00:43:09] And for organizations operating in a most sensitive environment, we are taking that trust foundation even further. [00:43:17] Our sovereign AI factories now include defense-grade security hardening, federal compliance readiness, validated encryption standards, and global data protection requirements, all built in. [00:43:33] So if you are in defense, government, or financial services, this is the sovereign AI architecture you have been waiting for. [00:43:43] Architecting for AI requires looking ahead, anticipating and designing for the constraints that will shape the future. [00:43:51] But there is one challenge we all need to overcome, not just for our industry, but for our society and our planet, and that is power. [00:44:01] Every model, every workload, every agent depends on power. [00:44:07] Because at its core, an AI factory is doing one thing, turning electrons into tokens. [00:44:15] The U.S. is on track to have a 19-gigawatt power gap by 2028. [00:44:20] That's roughly enough electricity to power 16 million homes. [00:44:25] And data centers are expected to account for nearly half of the U.S. electricity demand through 2030. [00:44:35] One customer, Siemens Energy, is tackling this challenge head-on, helping build the energy infrastructure the AI era requires. [00:44:44] They are doing it by applying AI to their own business, with HP helping deliver the AI foundation across networking, storage, and compute. [00:44:54] Let's take a look. [00:45:10] We are at an extraordinary moment. [00:45:12] AI is driving a scale of growth we simply haven't seen before. [00:45:20] And it all depends on energy. [00:45:23] It's a level of demand that's reshaping not just infrastructure, but how we engineer. [00:45:30] We are now designing systems that are more complex in less time. [00:45:35] Data is a very important asset. [00:45:38] That's why HPE is such an essential partner for us. [00:45:42] We generate enormous amounts of data across our equipment, plans, and operations. [00:45:49] What matters is how quickly we can act on it. [00:45:52] HPE is helping us become an agentic enterprise in important areas. [00:45:58] We now have enormous compute power so we can use AI in ways we couldn't in the past. [00:46:04] This speeds up innovation across our business. [00:46:08] In our turbine development, we use AI to simulate and test more models faster to identify the best designs sooner. [00:46:16] This digital twin technology and predictive maintenance we can detect failure before it happens. [00:46:26] And in the future, our engineers and AI agents will be working together, sharing knowledge to be more effective. [00:46:34] We are attracting a new generation of engineers while helping our teams build skills for what's next. [00:46:40] For me, it's about going beyond what has been possible in the past and how we use it to power the future. [00:46:48] I want to thank the Siemens Energy team for working on such an important challenge. [00:47:07] We are proud to support your ambitions. [00:47:10] Initiatives like this underscores a bigger point. [00:47:14] As AI is scaled, the future will not be defined by computer law. [00:47:18] It will be defined by how efficiently we can power it, cool it, and connect it. [00:47:24] That is why research becomes so critical. [00:47:28] For six decades, HPE Labs has helped shape the future of enterprise computing. [00:47:34] Your next generation infrastructure will need to operate with much greater intelligence, efficiency, and transparency. [00:47:42] Today, our researchers are applying AI to improve AI systems themselves, making them more scalable and more sustainable. [00:47:51] This is where HPE has a unique advantage. [00:47:54] We engineer the compute, the complete architecture from compute, servers, obviously networking, storage, software, and security. [00:48:04] And we apply that system expertise across the full stack. [00:48:09] With innovations like GreenLake Intelligence, we are developing predictive self-driving intelligence that can learn workload patterns [00:48:17] and place data where it needs to be before an application asked for it. [00:48:21] Across your broader data center environments, we are using AI to improve resource management, identifying idle patterns, [00:48:29] and reduce energy and water consumption without compromising performance. [00:48:33] We are also advancing the next frontier of computing through our work in quantum. [00:48:39] With initiatives like the Quantum Scaling Alliance and our work in distributed quantum simulation, HPE is helping bring quantum out of the lab into the real world. [00:48:50] You can see that future taking shape right here at Discover where a quantum chandelier sits along an original HPE Cray 1. [00:49:00] It is a great reminder that how far high-performance computing has come and whether it is heading next. [00:49:09] As networking HPC and AI and quantum converge, progress will depend on how effectively we bring these technologies together at scale. [00:49:21] Yesterday, we took another major step forward with the announcement of an expanded industry collaboration to advance hybrid quantum. [00:49:29] Together with these leading companies, we are building a full-stack hybrid quantum platform that extends our world-class HPC and AI infrastructure and moves quantum closer to real-time and real-world deployment. [00:49:45] Quantum advancements like this are accelerating the path to faster, more efficient solutions for most of the world's complex scientific and industrial challenges. [00:49:57] These are the challenges that inspire our HP Labs. [00:50:03] Ultimately, it all comes back to one simple mission – to advance the way people live and work. [00:50:09] It is a guiding force behind our innovation, our people, and our long-term strategy. [00:50:15] Today, we have covered how architecting for AI starts with your network and how we can help you transform into an agentic enterprise. [00:50:25] You have seen the powerful outcomes that result from people with bold ambitions that match with the right technology and the right partners. [00:50:35] Because none of this happens alone. [00:50:39] Our partners help HP bring these ideas to life. [00:50:43] With expertise, reach, and execution, customers depend every single day. [00:50:49] They help us extend our impact, bringing innovation closer to the customers and communities we serve. [00:50:56] Many of our partners have generously sponsored this week. [00:51:02] Discover is only made possible because of you, like us, believe in the vision and the power of pursuing it together. [00:51:10] So I want to thank all our sponsors and all our partners. [00:51:13] We appreciate you very, very much. [00:51:19] We take tremendous pride in knowing that our innovations are a catalyst for your success, driving outcomes that propel new opportunities for you and your customers. [00:51:35] As you experience all Discovery has to offer this week, keep these things top of mind. [00:51:42] First, architect deliberately. [00:51:46] The choices you make today will define your success tomorrow. [00:51:52] Second, start with the network. [00:51:55] Make your network the core foundation of your AI and cloud solutions. [00:52:02] And finally, choose HPE as your partner to bring the full stack to help you build your AI future with compliance. [00:52:12] This week is an invitation to think bigger, to move faster, to architect the future you want to lead and for the world. [00:52:22] And remember, you don't have to build this future alone. [00:52:27] We are here to provide the intelligence foundation so you can move boldly, live with purpose, and unlock your ambition. [00:52:36] Thank you very much. [00:52:38] I hope to see you on the floor. [00:52:39] Enjoy the rest of the week. [00:52:40] Thank you very much. [00:52:41] I hope to see you on the floor. [00:52:42] Enjoy the rest of the week. [00:52:43] Thank you very much. [00:52:44] I hope to see you on the floor. [00:52:45] Enjoy the rest of the week.