【完整公開】(AI即時翻譯) Intel執行長陳立武 COMPUTEX主題演講 @投資看非凡

Heat. Heat.

Heat up here.

silicon.

The foundation of modern technology.

Every transistor placed with purpose.

Every watch wrestled from physics. Where

every instruction set earns its right to execute.

This is how performance gets driven, how efficiency gets built, how intelligence acts, not just answers.

Our future is with ecosystems, shaped by architecture, capable of connecting technologies, tools, and partners. Powerful enough to

execute, efficient enough to scale, familiar enough to build with speed.

Tomorrow, it's about the progress we scale through open platforms, shared standards and partnerships, amplifying each other's strengths. A unified

architecture engineered for systems. The next chapter is being written at Silicon with our engineering at its heart. Built

different, built together, built on Intel.

And now, ladies and gentlemen, please give a warm welcome to the CEO of Intel, Li Pan.

Intel computer steps.

Uh this is the elephant mountain and so 1,00 step to 184 meter and so I survived and I came down with one piece. So I'm

here. So but if I walk a little bit slower then you know uh I'm exhausted.

But anyway it's a beautiful view. I mean

highly recommend all of you to do that.

Yep. I think first of all I think uh delighted to be here and uh this is an important event and then I'd like to get started

and about nearly six decades ago a group of brilliant and highly motivated engineers

and venture capitalists uh including Artur Rock, Don Valentine and many others. It found companies like Intel,

others. It found companies like Intel, Apple and others broadly set the motion the largest economic known to mankind

uh create what became known as Silicon Valley and uh this is a very exciting time and that is a very same ambition

and mindset with the semiconductors make across the ocean. that sparked the creation of Silicon Island right here in

Taiwan. And I have been very fortunate

Taiwan. And I have been very fortunate to associate with the creation of semiconductor industry in Taiwan 40 years ago

uh because uh 40 years ago uh Minister KT Lee Leorting Tuten uh invite me to lay the foundation of venture capital

concept in Taiwan. It's a very new concept and uh you know you people put money with you and you play the money

and then you share the profit of 20%.

But you don't share 20% of the losses.

So this is a very unique uh venture capital concept but I managed to do that and then with the help of Minister KT Lee and then development fund and I set

up my venture fund and about the same time you know uh uh Maurice Chang uh from TI came back to E3 and then uh then

set up the TSMC. So it's a very exciting time that I'm being involved in this whole science park and uh science park

and the foundation of become the silicon island and so I really see the benefit of you know uh from OEM ODM from design

to manufacturing it's all here in Taiwan.

Taiwan PC ecosystem has played a critical role uh in Intel growth and success. In fact, last year I was here

success. In fact, last year I was here uh to celebrate Intel 40th anniversary in Taiwan. I want to thank all of the

in Taiwan. I want to thank all of the suppliers, partners, and customers for 40 years of partnership with Intel. As partnership

continue to grow.

Thank you.

As partnership continue to grow and uh stronger every year.

It had been the year since I stepped in uh the role of Intel CEO to be more precise 14 months uh to being CEO of

Intel and it may be the first CEO can speak Mandarin and in fact couple of uh customer of Taiwan very important partner for us is

that Lippo also So very unusual if a CEO can drink liquor with us but anyway it's I'm part of this

community. Uh execution has always

community. Uh execution has always always at the top of my list to do so we had to bring focus back to the core. Uh

at our heart Intel is a engineering company and that's what I decided from day one I came to become CEO of Intel. I

have all the engineering report to me.

So they're understanding to really drive the engineering drives success in engineering uh performance. Our customer

and partners are always uh in already seen a shift uh in the Intel showed up.

We are just getting started and so stay tuned. We have a journey in front of us.

tuned. We have a journey in front of us.

opportunity ahead is enormous and our job is to stay focused, execute and deliver.

Every year Intel ship hundred millions of uh hundreds and millions of uh SOC orchestrating silicon across every

industry working tightly with our partners ecosystem across each layer of the stack

from silicon to SOC to system and to software.

This generates trillions of dollars in value across four core compute ecosystem.

First personal computers, second edge agentic AI and later

physical AI, third foundational data centers and finally emerging intelligent centers

that will power digital agents of the future. Each of these ecosystem

future. Each of these ecosystem represent generational opportunity and increasingly each of these will need

purpose-built CPU, GPU and A6 solutions caters for specific

workloads and application. The silicon

we are building now will be for human use and the digital agent use.

Let us begin with the ecosystem that started all to talk more about the PC ecosystem. Please join me to welcome to

ecosystem. Please join me to welcome to stage our new leaders for client compute and physical AI, Alex

Thank you. Thank you. Thank you. Thank

Thank you. Thank you. Thank you. Thank

you Lupu.

Little story about me. The first time I came to Taiwan was the year 1990.

And I was fresh out of school, first job, first international trip, first East Asia country I've ever been to. And

I came right here in Taipei.

And I quickly realized even back then that you know this the the desire to grow uh the mindset of win-win and cooperation

is all over all of our customers and our partners here in Taiwan. And so it quickly became uh one of my favorite

countries to visit and work. And now

forward the clock 36 years, I'm here in my first international trip with all the great people here at Intel. And where do I come? Right here to Taipei.

I come? Right here to Taipei.

Thank you.

I can't wait to plan and build the future with you guys. So, let's get started. We have a lot to cover.

started. We have a lot to cover.

Intel has continuously increased the pace of progress across all PC segments.

workstations desktops creators gamers, premium and mainstream laptops.

Every major segment, every major segment is driven by an Intel system solution.

With that vast coverage in mind, we're adding another dimension to scale these products even more effectively.

The Intel 18A process is now at full scale.

We have a full lineup of products with hundreds of design wins. To prove that, at CES, we launched the Core Ultra Series 3,

Intel's first product built on 18A process technology.

It's setting a new standard for premium mobile performance and battery life.

The Ultra Series 3 enables great user experiences across any tasks with a very fast response CPU,

a highly improved GPU, low power processing NPU, and the latest multimedia capabilities.

It's a perfect blend of IP performance and power for any AI and agentic experience.

It's allowing us to lead the way to transform every PC, every PC to an agentic capable platform.

Today, more than 300 designs are shipping across consumer and commercial segments, over 300.

And to scale these capabilities even further, we've taken the latest core ultra IPs and specifically tailored them

for the mainstream market.

The result, the Intel Core Series 3 introduced in April. Let me repeat, we just introduced this in April and it's

already scaled up to 70 plus designs.

That brings Thank you.

Thank you.

That brings the total series lineup to nearly 400 designs in just a few short months. Now, that is massive scale.

months. Now, that is massive scale.

Let's look at some of the capabilities of the Core Series 3. And we can start with battery life. You know, I can go over these numbers here that are printed and I can talk about how we measure them

and things like that, but I I have a question for you guys. How long is your day? 10 hours, 12 hours, 14 hours,

day? 10 hours, 12 hours, 14 hours, or more like us at Intel.

But the great user experience is if your PC lasts longer than your workday. And

that's exactly what we're delivering in all segments.

And we support ample number of ports for all of your connectivity needs, unlike some of our competitors who only have

one USBC interface. But I'll let you be the judge of that one.

The goal of this uh uh Core Series 3 is to bring premium feel and experiences to incredibly thin form factors for mainstream PCs.

And you know, you don't have to take my word for it. You can look at this wall of incredibly designed, sleek PCs that are here, and all of it is thanks to

you, our partners, and our customers. We

couldn't have done it without you. So,

please, a round of applause.

Isn't it awesome? Super light, super thin, really great.

Okay, now the next proof is scaling 18A IP into growing markets and the fastest growing portion of the PC market is the handheld gaming. Let's

take a look.

Heat. Heat.

Heat up here.

This is the Arc G3.

I think a beautiful chip. More beautiful

than what was presented yesterday at a keynote.

Okay, the G3 is derived from the Core Ultra Series 3 and the ARC G3 is a tuned high-erformance GPU specifically for

handheld gaming and it's providing great battery life.

The performance tested across multiple games is consistent and stable versus competition.

We are more than 40% faster. 40% faster

and at the same performance, we're half the power.

And on top of that, we're running all AAA games at 1080p resolution, many of them above 120 frames per second. Now,

that is giving gamers a great user experience.

All of these devices will be available late later this month, and this is just the beginning. We're going to have

the beginning. We're going to have plenty more designs coming throughout the year.

Thank you. Thank you.

Okay. It is indeed true that Intel has a leading lineup of processors and with the vers versatility of the ATNA process technology, our newest offerings, we're

bringing powerful performance and efficiency to scale across the breadth of premium mainstream and handheld gaming segments.

These same fundamentals, the same IP, the same capabilities can deliver far beyond the PC ecosystem.

The demand for our processors at the edge has been booming.

As you've seen, we've already taken existing product lines and pivoted them into adjacent markets, enabling our

customers to grow their businesses.

Now, the edge is demanding the latest products from Intel. And that's why this year we're taking our latest series 3 products into the edge business with

over 130 designs in multiple verticals.

For largecale edge business, our customers need the best technology and chipsets, easy to use reference designs,

and appropriate software stacks.

And at Intel, we've done all of that.

We have over 4,000 edge ecosystem partners deploying into such verticals such as manufacturing, robotics, retail, and many more.

For those of you here at Computex, you can see some of that at the pavilion.

Given that capability, given the IP, given the chipsets, given the scale that we have, there's a massive opportunity ahead of us across many segments of physical AI.

It's projected to be a 25 trillion market by 2050, and it will leverage all

of our scale in the PC ecosystem.

Physical AI form factors will take shape across key industries, as you see behind me.

We will continue growing these markets with the same strategy of leading IP and chipsets, complete reference platforms of enduser hardware and applicable

software stacks enabling our customers to expand into new physical AI form factors and applications.

And indeed, this will be our future.

Now, back to you, Lipu. Thank you.

Thank you. Thank you. Thank you.

Uh thanks, Alex.

AI is profoundly impacting the way we use our devices.

A major focus area for us is the use of AI on device.

Together with partners, we are at the forefront of advancing intelligence.

To tell you more about it, let me welcome on stage my close friend and founder CEO of Perplexity, Aravvin.

Well, Aravvin, welcome. You and I have been talking about hybrid compute for a while. The reason why are clear

while. The reason why are clear you know the privacy cost performance and let's talk about how to make this

work. Yeah. So in February we launched

work. Yeah. So in February we launched perplexity computer. Computer is an AI

perplexity computer. Computer is an AI operating system. It creates a team of

operating system. It creates a team of agents, uses up to 20 different AI models, and

it orchestrates across models, tools, and files in one single system.

The agent harness inside computer is model agnostic, perfectly balancing intelligence,

accuracy, privacy, and cost is the orchestration problem it solves. And so

this allows you to run smaller models locally on the Intel Core Ultra Series 3

GPU. And so for the first time ever, we

GPU. And so for the first time ever, we work together to create hybrid aenic inference. And so what we are showing

inference. And so what we are showing today is just the start. Hybrid agenic

inference is how we maximize token value per watt per user.

So should we show them how it works?

Yep.

All right. So here it is.

Let's say I'm an associate at a private equity firm and um I'm working on something that has a confidential project code name project falcon. Here's

the query.

So, think of it as me trying to understand if a certain private company is worth $1.1 billion and I'm feeding it

confidential deal materials.

The work begins on the laptop. It sees

that project falcon has private dealroom files and an NDA, a local leverage buyout financial model, a whiteboard diagram

and bilingual transcripts that are very confidential. You don't want these

confidential. You don't want these materials to be shipped to the server.

So what the local model does on the core ultra series 3 is it first decides this is all very important work and shouldn't be sent to the server. It reads the

files classifies what is sensitive and what is not and then computer decides what should leave the device and what shouldn't and each of these things is

done with local AI.

The orchestrator can spin up additional agents as necessary.

And so if you need a research agent to bring in outside file materials against local model without exposing any private

files, that's what you want in the hybrid system. And so computer arc acts

hybrid system. And so computer arc acts as one single system, brings all inputs and outputs together. And so let's actually skip and see what the actual

result would be.

All right. So, the result is a document, a research report, and sporting data.

And it's being created by agents on large cloud-based models, keeping your sensitive information only on your device. And so, all your local device

device. And so, all your local device models will take care of the private files and the server side models will take care of other things. through

hybrid inference orchestration.

This is the architecture we both believe in and the future is more compute in the data center and more compute on the local machine.

And so I think of this as a big milestone for engineering on both the agent harness AI side as well as the chip side. And so um it's been really

chip side. And so um it's been really fun to partner with you and Intel on this. So thank you so much Libu.

this. So thank you so much Libu.

Definitely. Thank you Aravvin and looking forward to continue partnership.

Thank you.

We talk a lot about the exciting new developments in the PC edge and physical AI space. I want to take a few minutes

AI space. I want to take a few minutes to talk about the foundational IP that power all these advancements.

Let us talk about x86.

When most people think of generalpurpose computing, they think x86 and that is a good reason for that. X86

is architecture that has power data center for nearly five decades and the leadership continues.

uh according to the IDC expect eight out of the 10 servers installed through 2030 to be x86based

powering modern computing from foundational to emerging intelligent use cases.

Intel pioneer most of the breakthrough architectural innovation that have enhanced 886 over the last

four decades starting with the 8086 that become the foundation of modern computing.

Uh if you can see the chart today we have two flagship CPU cores pores and ECores.

One optimized for performance, one the others is for efficiency.

These are Intel most advanced CPU cores with the accelerator building built in spec uh specifically for

foundational workloads like security.

Our x86 cores power our PC client edge portfolio and also power our data center

and AI portfolio. Under my leadership, we are committed to building the best CPU cores compute inensive workload run

best on 886 x86.

Next let us talk. Thank you.

Now let us talk about how x86 is enabling foundational data centers.

To tell you more about it, let me invite on to the stage Kavoke.

Thank you. Thank you. Thank you, Lipu.

Wow. It's so great to be here. uh

specifically in this point in our history, global history, collective history and be at Computex with the blue badge. So I'm very happy, I'm very

badge. So I'm very happy, I'm very humbled to be here to share with you some of the innovations that we have. So

uh let's talk a bit about uh see what this AI thing is about. So when we say foundational, we mean the workloads that keep the

world running. So currently we have data

world running. So currently we have data centers and there's a number of items and workloads and entities that run on these data centers. So uh for example we

have 5G networks that uh keep us connected. We have databases that keep

connected. We have databases that keep our data safe. We have cloud services that power our daily lives. So we expect

and demand for these workloads to to grow in size and capacity between uh now and 2030 from 80 gawatt to about 100

gawatt. And uh yeah most of you involved

gawatt. And uh yeah most of you involved in this uh domain understand the the the extent of this type of an expansion.

These workloads are broad. They are

mission critical. So attention special attention has to be taken uh when running them. but also they require

running them. but also they require performance, efficiency, security and resiliency. And we can't emphasize

resiliency. And we can't emphasize enough uh all these four factors.

That is why we are excited to have Intel Xeon 6 Plus introduced at the Computex this week.

It has 288 eores, a massive 576 mgabyte of L3 cache built with our Intel 18A technology. And

we can't emphasize enough the the value of uh Intel technology that brings to data center products. But most

importantly, it delivers efficiency and density, which enables our partners to save uh very precious

real estate, have more compact servers and the racks.

So this is a leadership compute for the next era of cloud and network infrastructure.

So Zeon 6 Plus launches with the strength of our ecosystem that's been built over decades and decades of data center development both from a hardware but also from a software and

infrastructure perspective.

Moreover, our ODM partners are bringing Zeon 6 plus solutions to the market today.

So 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 launch Xeon 6 based on peores.

Both of these uh category and class of uh solutions delivers new performance and choice for all the enterprises whose infrastructure backbone is built on x86

and zeon.

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 was 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 uh they are today.

So we have these two paradigms where we have the foundational data centers keep 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 and this is where Intel and Zeon 6 plus come in.

Now up to now training split the data center into two. So on one hand we have CPUled enterprise infrastructure and the other hand we have GPU heavy AI

factories and that was very clear divide for a while right and we've all been accustomed to that uh that reality but as a 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.

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

straightforward. We take a prompt. It

gets fed into an LLM where it spends most time reasoning about the prompt.

And 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 more. Now the way agentic AI works is

is more. Now the way agentic AI works is radically different. It's given goals

radically different. It's given goals rather than prompts. So we all seen the uh the different types of loop 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 aspect that were, you know, in the traditional realm of CPUs and x86.

And then for each step, the type of underlying compute needs is very different. And we'll show that in a bit.

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. And 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

Agentic AI. The CPU orchestrates the show.

Now, what we're seeing is we're also seeing the balance and the ratio of uh one CPU to 8GPU and more is uh is coming much closer to par. So, let's take a

look at the real example. John,

thanks Gaborg. You talked about how Agentic AI is changing the compute requirements. Let's take a look at a

requirements. Let's take a look at a real example. I have a traditional AI

real example. I have a traditional AI inference set up on the lefth 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 to1 GPU

screen. GPU dominates nearly 7 to1 GPU heavy.

In contrast, let's take a look at an Aentic AI system. Across the top, look at the pipeline stages. Green is GPU work. Blue is CPU work. Linting is

work. Blue is CPU work. Linting is

happening on our Xeon 6 Plus processor with effic 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

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 32 years of compute space.

Thank you, John. Wow, this is pretty amazing and some data to ponder on.

By far the the density of CPU we showed is is has the highest density per rack ever. But also looking at the number of

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

150,000 agents. So good news to all the CIOS in the audience. Now your very expensive GPUs can be can see more utilization because of uh our solutions.

Now both Zeon 6 with pores and ecores are built on 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.

So we've seen all the workloads we've run all the analysis and we are delivering these solutions uh to to all of you now.

Having said that, we are working with our customers and partners to make sure that each solution is uh tailored to to your needs. So,

your needs. So, I'd like to welcome Libu back on stage to talk about the server and rack sale solutions that our partners are working on. Thank you.

on. Thank you.

Thank you, my friend.

Thank you. Thank you.

Uh thank you Kavoke. It is great to see the momentum uh in the data center.

As we look forward to see that is for intelligence at scale. Discrete compute

alone is not enough. Our customer are asking us to think of system level to help them serve real agentic workloads

at scale. It push us to rethink how we

at scale. It push us to rethink how we deliver our compute beyond the socket and to the rack.

That is why we start the initiative called Rex scale blueprints working with ecosystem partners to

develop Rex scale blueprints built on open standards.

So customer can rapidly scale their intelligent infrastructure with confident without proprietary workarounds.

Behind me as you can see two examples of these blueprints. One is for agentic

these blueprints. One is for agentic performance based on Intel Xeon 6 with pores.

The other is agent density with the Intel Xeon 6 Plus with ECores.

We are working closely with our partners ecosystem including Foxcomanova to expand our Rex scale offering. Let me

call on stage one of our partners, chief product officer of Foxcom, Jerry Xiao to talk about how we partners on Rick scale

solution.

Thank you Libu.

Thank you, Jerry.

Um, I'm so excited to be here today.

Wonderful product and amazing event.

Jerry, Intel and Foxcom have been working together to many decades and Foxcom has been instrumental in driving

technology innovation in Taiwan and around the world.

Yeah, that's right, Abu. Um I'm proud the work we have done together from AI servers to data centers

and to age computing all together and today we're excited to announce the next step in our partnership.

Intel andcom are working together to develop Rex scale products built upon Intel Xeon processors. Together we will

focus on exploring the development integrations and commercialization of differentiated

uh rack scale AI infrastructure solution leveraging comp complementaryary architecture to address diverse AI workload requirements.

Yeah, together we will continue to deepen and expand our partnership unlocking new opportunities ahead.

Through this collaboration, we will deliver system level AI solution to our joint customers in airballing more

integrated and scalable computing environments. This makes it marks an

environments. This makes it marks an important step ahead and we look forward unveiling more in the near future. Thank

you Liu.

Today is an exciting uh milestone for our continual partnership uh with Foxcom. Jerry, thank you for joining us.

Foxcom. Jerry, thank you for joining us.

Fantastic. Thank you for having me.

Thank you to the many partners in the audience today that is helping to bring this rack scale vision to life providing

choice throughout uh through the ecosystem power. Uh we do not believe

ecosystem power. Uh we do not believe one size fit all approach for intelligent centers. Each enterprise

intelligent centers. Each enterprise will run unique workloads. So their

infrastructure needs will also need to be unique and purpose-built. As you can see from the screen here, just look at the server in front of me.

Uh this is whole series of partnership we have.

Intel is working with a lot of partners to provide service rack scale solution designed to fit your existing

infrastructure ready for AI at scale as you can tell in front in front of you.

We see token usage exploding.

Agent now consume 1,000 time more tokens than single event reasoning.

In addition to building the best CPUs, it is critical that we deliver compute solutions optimized for token

consumption and token generation.

The bottom line, AI at scale will require hetogeneous computing. To this

end, Intel recently announced a partnership with Sonova.

To talk more about this, let me call to the stage founder CEO of Sonova, Rodrigo Leong.

Rodrigo, welcome to joining me today.

Thank you, Lupu.

And over the next few months, we have announced few updates on our joint development partnership. Can we talk a

development partnership. Can we talk a little bit more about the work that Intel and Sonova are doing together?

Absolutely. We've been busy. Earlier

this year, we announced a multi-year collaboration to deliver high performance, costefficient AI inference solutions based on Xeon infrastructure.

We've been building something really special. Excited to show you today.

special. Excited to show you today.

This is the this is the SM50 sambar we announced earlier this year.

Rack scale AI infrastructure built for agentic workloads.

It uses Intel Xeon 6 processors with Sonova SM50 RDUs and shipping to customers later this year. Today, we're

also excited to demonstrate the world's first heterogeneous disagregated inference using Simonova'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.

So the one on the left is GPUs, RDUs, and CPUs. This aggregated difference and

and CPUs. This aggregated difference and this one on my right is GPUs on their own. They both get the fed the same

own. They both get the fed the same prompt in the same model just different stacks.

The disagregated inference stack is taking off. And what's happening here is

taking off. And what's happening here is you have the Xeon 6 processors doing all the tooling execution. You have

Salmonova RDUs doing the decode and generating all of the tokens. And then

you got the GPUs performing the PROM 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 engetic AI and the

other side the GPU stack is still working away.

So the initial result of our work is disagregated inference is the the GPUs, the RDUs, the CPUs that's the fastest

and artificial analysis and our test found it to be two to three times faster than just the GPUs alone. And this gives us an early look at how fast this can

be. Rorico, the most exciting part about

be. Rorico, the most exciting part about all this is that we have tremendous customer interest uh in these solutions.

Absolutely. So, let's see who comes next. So, turn it back over to you.

next. So, turn it back over to you.

Thank you so much.

Thank you. Thank you. Thank you.

To continue this conversation, I'm delighted to invite my good friends uh you know, Robert Smith uh is a Vista

Equity Partners, chairman, CEO and and uh you know of the partners and Roger Smith to tell you more about how they

plan to use this racks from Intel and Samnova. Robert.

Samnova. Robert.

Great. Thank you,

Lipu. Good to see you.

Same here. Thank you so much for joining me. Pleasure. Thank you, my friend.

me. Pleasure. Thank you, my friend.

Thank you, my friend.

Yes. So, Robert, AI is driving huge demand uh for computing and it is reshaping the silicon system software

and at all at once. What are you seeing and hearing from the enterprises that you work with? Yeah, first of all, I'm excited to be here at Computex to join

you at this wonderful event. Um, for us, it's been quite quite incredible. Uh,

there's been a huge focus right now to bring AI to enterprises around the globe. Uh, we want to make it usable. We

globe. Uh, we want to make it usable. We

want to make it impactful for the organizations that we work with. You

know, we have over 90 portfolio companies and well over half of them have now uh have converted to Agentic Solutions. And with over 750 million

Solutions. And 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 disagregated 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 are

targeted to convert existing data centers to inference data centers. This

is very exciting and as we saw from Ro a few minutes ago uh we are already starting to see strong momentum for these offerings. Can you talk a little

these offerings. Can you talk a little bit more about how Intel Victor core compute and our partners like SANOVA are bringing this aggregated uh inference to

life?

Of course uh I'm excited to share that first together AI is the first commercial customer uh 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 and this is has to be and it is more efficient than anything they pre

previously have had access to. Most

critically VC2 is built and utilizes the senova stack which is an aircooled data center. We believe it will deliver what

center. We believe it will deliver what enterprise customers and communities are asking for which is reliable, low

latency, lowcost 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.

Uh we are excited about that. Thank you

for joining me today and delighted to have you here.

Always a pleasure, Liu. Thank you.

Congratulations. 14 more months. We're

excited to see what you're doing.

Thank you.

Thank you.

As you just saw from Roro and Robert, picking the right silicon architecture for your needs is critical for enterprises today. There's a broad range

enterprises today. There's a broad range of architectures to choose from. As

large workloads increasingly become strategic asset for companies, they are increasingly looking for silicon built

around their exact needs.

Next, I would like to invite Shrini, a semiconductor design veteran and a leader of our purpose-built silicon team

to talk more about the work we are doing in this area. Swini,

hi Leu, thank you. Thank you so much. A

very good afternoon to you guys.

purpose-built silicon. It is this has been a journey that the industry 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. Liu 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

internally. How do we bring this out to the external world and do something more? With that said, we we had a

more? With that said, we we had a proposition. We've been working on it

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 or 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. I would call it Intel processing unit actually but infrastructure processing unit which is a 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 this is working on we've been Intel as a company

has been pretty active in the telco market and in this telco market another marquee customer Ericson has between uh partnering with us and Erikson chooses

us wherein we deliver or Intel delivers the next generation infrastructure silicon for 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 and 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 you some of

your aspirational goals on silicon.

Okay. Thank you Liu.

I'm super excited about all this partnership that you announced and more to come.

Yes absolutely more to come. Yes.

Thank you so much. Thank you so much.

Thank you.

Thank you.

The work Streiny and the team are doing with purpose silicon is really important. I am super excited to be

important. I am super excited to be partnering to build custom silicon with many leading edge companies as well as

some of the most dynamic startups across the industry vertical. I would like to highlight some of this partnership today.

One of the most exciting areas where we can deploy advanced silicon is biomed engineering. For years, emulating the

engineering. For years, emulating the function functionality of the human brain has been the holy grail of computing.

One company that is in the forefront of brain inspire computing is echo neuro technologies.

Let us hear more from Eddie Chan, founder CEO of Echo Neurochnology and also one of the world best

neurosurgeons.

Hi, I'm Eddie Chang. I'm a neurosurgeon at UCSF and co-founder of Echo Neurochnologies.

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

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

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.

brain. We're excited about what's ahead.

Thank you.

Thank you, Eddie. I'm amazed by the work you are doing. I'm confident that our work together will help lay the foundation of highly efficient AI

computers uh in the future.

Another company doing work at the cutting edge of biology is Greenstone Technologies.

We are partnering with Greenstone to establish scalable reference architectures applicable across the broader life

science imaging ecosystem.

Dr. Joseph Wu is a head of cardiology at Stanford and the founder CEO of Greenstone. Let's hear from him.

Greenstone. Let's hear from him.

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

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 bio bank of human induced flu potent stem cells. From just 10 ccs of your

stem cells. From just 10 ccs 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 biio medicine 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

Biosciences. Thank you very much and enjoy the event. Shaja,

thank you Joe. I'm amazed by the work you're doing and my excited about the potential of our partnership.

Another key partners is Hitachi.

They have a wide range of capabilities that help accelerating our our work our plan around foundry tools and quantum

computing system. Let us hear from

computing system. Let us hear from Hitachi CEO Toko Nagasan.

Hello Complex. I'm Toshiaki Tokunaga, CEO of Hitachi. For decades, Hitachi and Intel have worked together to solve key

challenges for society. And today, we are bringing our strength even closer.

By combining Intel's advanced computing with Hitachi's industrial strength in a physical world, we will create

intelligent solutions that will benefit both businesses and society.

Thank you, Libu. I look forward to our future together.

Thank you, Titi.

We are really looking forward to working with you.

Finally, uh if you look at, you know, we have the brains inspire computing, biomed medicine, and then energy. The last one

is industrial automation. Finally, one

partner I would like to hear like you to hear from is known for their pioneering work in industrial automation. Let us

hear from my very good friend uh Rhoden Bush at Seammens.

Hi Lipu, as a customer of Intel, we all know that global semiconductor demand has hit a high record. In 2023, Seammens

and Intel already joined forces to meet it. And now we are taking our cold

it. And now we are taking our cold liberation to the next level. We are

expanding our partnership across the entire value chain from design to manufacturing to chip applications in seammen's products.

We improve design quality through EDA automation and software solutions built with Atlantic AI. We partner on all

areas of the manufacturing process including product life cycle 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 seammen's products.

Looking forward to what's coming up.

Thank you, Roland.

We are delighted to expand our long partnership with the Seaman groups.

I'm looking forward to disclose more about this partnership in the coming months and we are working with several

other partners to keep pushing the boundary of what is possible.

I would like to close by returning to where we start our conversation.

The opportunity for Intel and for our partners is immersed. PC, Edge, Agentic,

physical AI, data center and emerging intelligence center from silicon to SOC to system and applications.

This opportunity is only made possible by all of you.

Look at the list and the largest ecosystem of partners, suppliers and customer.

Intel is a iconic company. We lay the foundation of modernday computing and we are proud of our heritage.

But we do not want to rest on our honors and goreers. A year ago, I joined as a

and goreers. A year ago, I joined as a CEO. I challenged my team to work with

CEO. I challenged my team to work with me to build a new Intel.

That is exactly what we are doing. We

are not encumbent by the past. We are

building something wonderful.

It is have been year of transformation for Intel. We ram our 18A to high volume

for Intel. We ram our 18A to high volume with multiple products. We are executing well on our advanced packaging

milestones. We make tremendous progress

milestones. We make tremendous progress on engaging customers and building our foundry business. We introduce new SOC's

foundry business. We introduce new SOC's for all major compute platforms from premium mobile to high density cloud and

5G.

We are be rebuilding and strengthening partnership across the ecosystem.

We are double down on creating new business opportunity across existing and emerging domains.

We are working at the forefront to imagine re-imagine computing and make it highly efficient for the AI era.

And this is just the beginning. I super

excited to continue executing at hypers speed.

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

Intel events. And please don't forget your personal belongings.

AP Foreign