LIVE: Intel CEO Lip-Bu Tan Delivers Major COMPUTEX 2026 Keynote in Taiwan | APT

Thank you, Lip-bu. It's so great to be here, specifically at this point in our history, global history, collective history, and be at Computex with the blue badge. I'm very happy and humbled to be here to share with you some of the innovations that we have. Let's talk a bit about what this AI thing is about. When we say foundational, we mean the workloads that keep the world running. Currently, we have data centers and there's a number of items and workloads and entities that run on these data centers. For example, we have 5G networks that keep us connected, databases that keep our data safe, and cloud services that power our daily lives. We expect demand for these workloads to grow in size and capacity between now and 2030 from 80 gigawatts to about 100 gigawatts. Most of you involved in this domain understand the extent of this type of expansion. These workloads are broad, they are mission-critical, so special attention has to be taken when running them. But also, they require performance, efficiency, security, and resiliency, and we can't emphasize enough all these four factors. That is why we are excited to have Intel Xeon 6 Plus introduced at Computex this week. It has 288 E-cores, a massive 576 megabytes of L3 cache, built with our Intel 18A technology. We can't emphasize enough the value that Intel technology brings to data center products. But most importantly, it delivers efficiency and density, which enables our partners to save very precious real estate, have more compact servers and racks. This is leadership compute for the next era of cloud and network infrastructure. Xeon 6 Plus launches with the strength of our ecosystem that's been built over decades of data center development, both from a hardware but also from a software and infrastructure perspective. Moreover, our ODM partners are bringing Xeon 6 Plus solutions to the market today. These range from full rack-scale deployments to server-level designs. Xeon 6 Plus joins our lineup of data center processors next to our already launched Xeon 6 based on P-cores. Both of these categories and classes of solutions deliver new performance and choice for all the enterprises whose infrastructure backbone is built on x86 and Xeon. This is critical for enterprises that need to increasingly balance preparing for AI workloads but at the same time running their day-to-day mission-critical applications. So let's switch gears and talk about how Intel is certifying the deployment of intelligence at scale. It's undeniable that enterprise infrastructure today will have to evolve to keep up with the AI demand. Recent research forecasts that AI inference workloads are expected to become 40% of all data center power demand and much more than they are today. We have these two paradigms where we have the foundational data centers keeping on running their traditional workloads, but at the same time they have to figure out ways of building their infrastructures to serve intelligence at scale. This is where Intel and Xeon 6 Plus come in. Up to now, training split the data center into two. On one hand, we have CPU-led enterprise infrastructure, and on the other hand, we have GPU-heavy AI factories. That was a very clear divide for a while, and we've all been accustomed to that reality. But as AI moves into real workflows, data tools, governance, the needs change. The next wave is not just about training models; it is about putting AI to work. So let's look at why Agentic AI changes the infrastructure equation. The way AI inference works is straightforward. We take a prompt, it gets fed into an LLM where it spends most time reasoning about the prompt. We've all seen this, we've done this thousands of times, and out comes an answer. In this case, a lot of time is spent computing the large language model, which is mostly GPU and compute-intensive. Now, the way agentic AI works is radically different. It's given goals rather than prompts. We've all seen the different types of loops that people are running on this agentic AI. It's also very iterative in nature but also prompted by automation, and thinking, planning, acting, and reflecting are a natural way of these agents interacting with us. As it works, it uses tools, reads and writes files, checks rules, and other aspects that were in the traditional realm of CPUs and x86. For each step, the type of underlying compute needs is very different, and we'll show that in a bit. This is particularly important as agents scale up their work, spawning new agents that work concurrently. The category and the complexity of agents are going to be very different depending on the complexity of the work. That's the main reason that there's such a rapid increase in CPU demand for agentic AI. The CPU orchestrates the show. Now, what we're seeing is the balance and the ratio of one CPU to eight GPUs and more is coming much closer to par. So let's take a look at a real example. John.

Thanks, Kavouk. You talked about how Agentic AI is changing the compute requirements. Let's take a look at a real example. I have a traditional AI inference setup on the left-hand side of the screen. Let's send a request: write a Python function that calls an OpenAI-compatible chat completions API. The model gets the response, generates code, and sends the request back. Take a look at the slider on the top of the screen. GPU dominates, nearly 7 to 1, GPU-heavy. In contrast, let's take a look at an agentic AI system. Across the top, look at the pipeline stages. Green is GPU work, blue is CPU work. Linting is happening on our Xeon 6 Plus processor with efficiency cores. Web fetch and compile is happening on our Xeon 6 performance cores, and unit testing is coming back and running on our Xeon 6 Plus efficiency cores. The right class CPU for each stage of the pipeline. Take a look at the slider across the top again. We're near par, but CPU-heavy this time. What's this look like when we multiply that by millions of queries a day? As you mentioned, each Xeon 6 Plus processor has up to 288 cores. That's 576 cores per two-socket server. When we look at that from a rack-scale perspective, that gives us over 36,000 cores per 32U of compute space.

Thank you, John. Wow, this is pretty amazing and some data to ponder on. By far, the density of CPU we showed has the highest density per rack ever. But also looking at the number of agents, and these are the new metrics that are emerging, we can safely say that that particular rack can run up to 150,000 agents. So good news to all the CIOs in the audience: now your very expensive GPUs can see more utilization because of our solutions. Now, both Xeon 6 with P-cores and E-cores are built for intelligence at scale. There are different cores, of course, but we've seen the workloads that require very high-performance cores pushing the frequencies, but also there's a need for very high-density, power-efficient cores. We've seen all the workloads, we've run all the analysis, and we are delivering these solutions to all of you now. Having said that, we are working with our customers and partners to make sure that each solution is tailored to your needs. So, I'd like to welcome Lip-bu back on stage to talk about the server and rack-scale solutions that our partners are working on. Thank you.

Thank you, Lip-bu. I'm so excited to be here today. Wonderful product and amazing event.

Yeah, that's right. I'm proud of the work we have done together, from AI servers to data centers and to edge computing. Today, we're excited to announce the next step in our partnership. Intel and Foxconn are working together to develop rack-scale products built upon Intel Xeon processors. Together, we will focus on exploring the development, integration, and commercialization of differentiated rack-scale AI infrastructure solutions, leveraging complementary architectures to address diverse AI workload requirements. Together, we will continue to deepen and expand our partnership, unlocking new opportunities ahead. Through this collaboration, we will deliver system-level AI solutions to our joint customers, enabling more integrated and scalable computing environments. This marks an important step ahead, and we look forward to unveiling more in the near future. Thank you, Lip-bu.

Fantastic. Thank you for having me.

Thank you, Lip-bu.

Absolutely. We've been busy. Earlier this year, we announced a multi-year collaboration to deliver high-performance, cost-efficient AI infrastructure solutions based on Xeon infrastructure. We've been building something really special, excited to show you today. This is the SN50 rack we announced earlier this year. Rack-scale AI infrastructure built for agentic workloads. It uses Intel Xeon 6 processors with SambaNova SN50 RDUs and is shipping to customers later this year. Today, we're also excited to demonstrate the world's first heterogeneous disaggregated inference using SambaNova's RDU with Intel's CPU and NVIDIA GPUs. What you're about to see is the same prompt, the same model, running side by side, two different stacks. The one on the left is GPUs, RDUs, and CPUs disaggregated inference. And this one on my right is GPUs on their own. They both get fed the same prompt and the same model, just different stacks. The disaggregated inference stack is taking off. What's happening here is you have the Xeon 6 processors doing all the tooling execution, you have SambaNova RDUs doing the decode and generating all of the tokens, and then you got the GPUs performing the prompt caching and the faster prefill, reducing overall time. When all three chips are working together, you dramatically reduce the end-to-end latency and the agents for the fastest need for agentic AI. On the other side, the GPU stack is still working away. So the initial result of our work in disaggregated inference is the GPUs, the RDUs, the CPUs. That's the fastest, and artificial analysis and our tests found it to be two to three times faster than just the GPUs alone. This gives us an early look at how fast this can be. The most exciting part about all this is that we have tremendous customer interest in these solutions.

Thank you so much.

Great. Thank you. Lip-bu, good to see you.

Yes.

Yeah, first of all, I'm excited to be here at Computex to join you at this wonderful event. For us, it's been quite incredible. There's been a huge focus right now to bring AI to enterprises around the globe. We want to make it usable, we want to make it impactful for the organizations that we work with. We have over 90 portfolio companies, and well over half of them have now converted to agentic solutions. With over 750 million users of our software, that really translates to over 10 billion agents. That's why we've launched Vector Core Computer VC2 with our partners at Cambium Capital to offer the world's first commercially available architecture for disaggregated inference. This novel agentic neocloud is built to deliver the fastest enterprise inference throughput of any architecture to date. The demo you just witnessed with Rodrigo was conducted live in our Los Angeles data center, and we have over 50 deployments planned in the US, which we're targeted to convert existing data centers to inference data centers.

Of course. I'm excited to share that First Together AI is the first commercial customer and is excited to use this architecture as a service to accelerate inference workloads. We expect many of our enterprise software companies and their customers to quickly follow as the demands for inference keep growing. This has to be, and it is, more efficient than anything they previously have had access to. Most critically, VC2 is built and utilizes the SambaNova stack, which is an air-cooled data center. We believe it will deliver what enterprise customers and communities are asking for, which is reliable, low-latency, low-cost inference at scale. Partnering to advance AI is one of the best ways to develop this transformational technology, making it usable and economically viable for enterprises worldwide.

Always a pleasure, Lip-bu. Thank you. Congratulations. 14 more months. We're excited to see what you're doing.

Hi, Lip-bu. Thank you so much. A very good afternoon to you guys. Purpose-built silicon, it is. This has been a journey that the industry has been using almost for the last decade or so, and especially hyperscalers have tapped into this to its full potential and shown us the benefits in every way possible. Lip-bu, last year you challenged us to see in this space, given the fantastic assets and the breadth of assets that we have at Intel, how could we be relevant to this, not just be focused on the stuff that we do internally, how do we bring this out to the external world and do something more with that. So we had a proposition, we've been working on it, and today I'm very happy to share a couple of good outcomes that we have. The first, on the hyperscaler side, we have Google and Intel have gone into a partnership wherein Intel is delivering what is called as the infrastructure processing unit. I would call it Intel processing unit actually, but infrastructure processing unit, which is a piece of silicon very vital for hyperscalers' performance, and that journey continues. And by the way, this is a deployment today, so it is not just something that we are doing, but it's already designed and being deployed. While this is working on, Intel as a company has been pretty active in the telco market, and in this telco market, another marquee customer, Ericsson, has been partnering with us. Ericsson chooses us wherein we deliver, or Intel delivers, the next-generation infrastructure silicon at a global scale for them across the board. This just gives you a very sneak preview at the highest level to see the kind of work that's happening in the purpose-built silicon space, which is a very exciting space and more importantly, a high-growth space. I was just thinking, what better place than Computex and Taipei where custom silicon really is the name of the game here to announce that Intel has officially entered this market. So looking forward to working with many of you guys and see how we can be relevant to some of your aspirational goals on silicon. Thank you, Lip-bu.

Yes, absolutely. More to come. Yes.

Hi, I'm Eddie Chang. I'm a neurosurgeon at UCSF and co-founder of Echo Neuro Technologies. For decades, AI has been brain-inspired, meaning borrowing ideas from neuroscience at a distance. Neuromorphic computing has carried that vision the furthest. It built silicon around the brain's core principles like spikes, sparse communication, memory, and compute all in the same place. That architecture is right. But what's been missing is direct evidence of how the brain actually performs the computation. That's now within our reach. For the first time, we can study how the human cortex computes language in real time at the resolution where computation actually happens. This opens a whole new possibility. Algorithms that are not just brain-inspired, but new ones that are trained on the brain activity itself, measured against the brain itself. That's the shift in our collaboration with Intel. Together, we're developing brain-trained algorithms for streaming speech that approach the efficiency of biological computation. The payoff runs both ways: AI that's faster, lighter, and closer to how we actually think, and new tools to restore speech to people who have lost it. Together with Intel, we're building AI that learns from the most powerful computer ever discovered, the human brain. We're excited about what's ahead. Thank you.

Hello, my name is Joseph Wu, and I'm a professor of medicine and director of the Stanford Cardiovascular Institute, as well as the co-founder of Greenstone Biosciences. Thank you so much for including me in Computex. Intel and Greenstone are working together to speed up the development of new medicines. Our partnership combines state-of-the-art human genetics and biology from Greenstone with advanced AI computing from Intel so that we can scale data processing, storage, and analysis. Greenstone has built the world's largest biobank of human induced pluripotent stem cells. From just 10 cc's of your blood, we can make your brain, heart, liver, kidney, gut, and any type of organoids in your body that are genetically identical to the patient. This will then allow us to test existing and new medications more quickly and at a lower cost. I believe the combination of human biology and AI computing will help shape the future of biomedicine in the next decade. And this is why we're so excited about the partnership between Intel and Greenstone Biosciences. Thank you very much and enjoy the event.

Hello, Computex. I'm Toshiaki Higashihara, CEO of Hitachi. For decades, Hitachi and Intel have worked together to solve key challenges for society. And today, we are bringing our strengths even closer. By combining Intel's advanced computing with industrial strength in the physical world, we will create intelligent solutions that will benefit both businesses and society. Thank you, Lip-bu. I look forward to our future together.

Hi, Lip-bu. As a customer of Intel, we all know that global semiconductor demand has hit a high record. In 2023, Siemens and Intel already joined forces to meet it. And now we are taking our collaboration to the next level. We are expanding our partnership across the entire value chain, from design to manufacturing to chip applications in Siemens products. We improve design quality through EDA automation and software solutions built with AI. We partner on all areas of the manufacturing process, including product lifecycle management, automation, electrification, quality, and sustainability. And what makes this even more relevant for us, the chips created in this value chain will be used in our own Siemens products. Looking forward to what's coming up.

Before the lights go out, the race begins. From simulation to strategy, performance begins with compute. With electrons that power pace and data that backs decisions, the race never ends. Engineering never stops. Intel, official compute partner of McLaren Racing. Ladies and gentlemen, this concludes the Intel Computex 2026 keynote. Thank you for joining us this afternoon to witness the future of technology. We look forward to seeing you again at future Intel events. And please don't forget your personal belongings.