There's a company nearly every chipmaker

relies on that doesn't actually make

anything tangible. Yet, its Blockbuster

IPO in September valued it above 54

billion.

>> It's the largest public offering in over

2 years.

>> The valuation of the company has

tripled.

>> If you have a smartphone in your pocket

or in front of you, you have an ARM

circuit somewhere inside of it.

>> We are the CPU, the heart of everything.

>> They're the winner of the CPU side. the

foundation models, the software, it's

moving far faster than the hardware. So,

what we're seeing is people investing

faster and faster into new hardware,

which ends up being a good thing for us.

Ladies and gentlemen, please welcome ARM

CEO Renee Hos.

[Applause]

[Music]

>> Thank you so much.

>> How are you?

>> Welcome. Welcome,

>> David. Hey, good to see you. Hi.

>> Hello,

>> Renee. What are you banging these days?

3 milligrams of AL pouches or you're up

to nine.

>> I know you're competing with Nvidia, so

you probably want to go with the nine,

right?

>> I will go with the nine with Jensen. You

have to go big.

>> You have to go big with Jensen. What's

that like to compete against Nvidia?

>> Well, I will say uh Nvidia is a customer

of ours. So, I'm not going to say Jensen

is my competitor uh today, but you know,

I worked for Nvidia for for many many

years as as you know. uh and he's

fantastic right and uh learned so much

working there working for him working

with him and then Nvidia you know almost

acquired ARM in 2020 uh so I almost you

know had a chance to work with him again

>> what did you learn from Jensen

>> you know one of the things about Jensen

that is amazing I think it's also true

for people like uh Michael Dell uh Masa

you have these entrepreneurs who started

their companies uh 30 years ago 40 years

ago go and and they're still running it.

So, you have this amazing set of

characteristics of vision, speed,

fearlessness, taking risk, and a an

ability to pivot uh very very fast. And

and I saw that a lot at NVIDIA. You

know, when I was there, we were only

about $4 billion in sales. And uh and at

that time, we were looking at lots of

different ways to grow business models

and such. And I just remember being, you

know, one story we were at a a strategic

offsite and it was supposed to be a

review of road maps where we were

looking at each one of the general

managers going through what they uh

projected in their business and what was

intended to be a roadmap review turned

into we're changing the strategy. We're

abolishing this product line. We're

going to move 2,000 engineers off of

project X onto project Y. And by the

way, we were only about 6,000 people at

the time.

>> What was project X? What was project Y?

So we were involved uh at that time in

trying to do uh mobile chipsets

connecting to an Intel processor, right?

And back in the day uh for those who

remember PC architecture doing these

chipsets competing with Intel was was

really hard business and Intel was

making it very very hard to compete uh

relative to the integration that they

did. And in fact that was the genesis of

starting to pivot to ARM in a very big

way inside Nvidia because at that time

Jensen looked at what was going on with

SOC's and ARMbased architecture and

moved everybody onto the program.

>> Let's maybe take a step back and level

set for the audience. So just to give

some background um Masayoshi Sun and

Soft Bank took ARM private

>> took private yeah for $32 billion.

>> $32 billion and then tried to sell it

famously.

>> Yes.

>> Couldn't find a bidder.

>> Could not find a bidder.

>> Hung on to it. took it public. It's now

a $150 billion market cap company.

>> That's right.

>> And you were telling us backstage he

famously, you know, refuses to sell a

share.

>> So, it's like a slow kind of process of

just building the the shareholder base,

but you've done phenomenally well as a

business.

>> Just set the landscape for people that

want to understand Nvidia, the most

valuable company in the world, but it's

a it's a window to understanding AI.

>> Mhm.

>> Why does what do they make that's so

powerful? And why aren't there other

competitive solutions at at that level

of scale yet? And how do you think that

changes over the next 5 10 years?

>> Oh boy. Uh lot lot a lot there to uh to

describe. So the the way to think about

Nvidia uh and to some extent I I don't

even though I'm the CEO of ARM I don't

want to tie it necessarily back to ARM

but in our world what really drives

demand is compute workloads. you know at

the end of the day is compute workloads

and when a new workload is uh

essentially either identified and or

invented then it comes down to what is

the best architecture processor-wise to

address that workload. So let's look at

AI. You know the lightning bolt moment

of of Alex Net uh and the work actually

that the Demison team were working on.

AI particularly training uh is a very

very complex parallel problem that is

well suited for a GPU and in fact the

very first work done by the engineers on

AlexNet was not with Blackwell. It was

not with a an AI processor but it was

with a gaming GPU a gaming card. So

Nvidia was in a a very very good place

to seize that moment relative to the

deepmind moment slalexnet

slash the transformer/training

and fast forward training these complex

AI models as Dennis was just talking

about this is a huge huge amount of work

now what role does ARM play there every

one of these workloads requires a CPU to

not only run the computer but help the

accelerator run and that's where Nvidia

is a customer today their most advanced

chip called Grace Blackwell is 72 ARM

CPUs with a Blackwell architecture and

that's that's where Nvidia plays today.

So back to uh where does Nvidia fit?

There is competition. You know Demis

talked about uh prior with Google they

do their own chip called TPUs. Uh

obviously Nvidia is the leader with

general purpose but right now we're in

this interesting world where people are

looking at is it a general purpose chip

is it a custom chip etc etc. It's a

fascinating time to be in this industry

for sure.

>> Where do you think companies like

Tesla, you know, Tesla recently merged

two pads and now they're working on AI5

and AI6? Um, and some of the more

emerging companies like Cerebras and

there's a whole slew of companies now,

Grock and others that have raised

enormous amounts of money. Um, do you

believe that the the role of ARM should

be to be the lack of a better phrase,

the arms dealer to all of those folks

that need that capability or at some

point do you think that you know you see

enough of it where you're like gosh I

could just do this better?

>> Maybe a little bit of both. Uh, I mean

today the role we play is we are now

increasingly that microprocessor that

connects to these accelerators whether

it's something that's done by Cerebras

or it's something that's done by Nvidia.

uh something done by uh by Google,

they're connected. Uh could we do

something ourselves custom? It's

possible. Could we also supply the

intellectual property to somebody

building a custom chip? We're doing that

today. So to some extent um we're in a

very unique place that not only can we

provide the solution whether it's

standard or custom but as AI moves from

gigawatt data centers to running in

these headsets or running in a wearable

or running in something that needs to be

energy efficient you still need to run

the compute workload but now you need to

run the run the AI workload and that is

a place that I think only ARM is

uniquely positioned to address.

>> So you're going to make chips and

compete with Nvidia. Uh, I'm not going

to say that today, but could we do that?

I hinted in the last conference call

that we're looking at going a little bit

further than we do today.

>> Could we see in the, you know, next few

years, could we see a divergence in the

market between training and and

inference? Because what I've noticed is

that you've got XAI and OpenAI and, you

know, Google's already doing it with

TPUs. They're they're building their own

chips for inference, which might be, I

don't know, 99% of the workloads. They

seem to acknowledge that Nvidia is the

best at training and they don't seem

they haven't at least announced an

effort to challenge Nvidia for for

training. So is there is there a

possibility that you know the the market

could sort of bifurcate into training

chips and inference chips and inference

gets much more competitive? Yes. I and I

also think you have a third bucket where

training distills down to simpler

training chips that you don't need to

run a trillion parameter model. You

could have a giant model that now treats

and teaches smaller models, mixture

experts, 20 billion parameters that can

be a mix of inference and training doing

reinforcement learning where the chip is

now helping uh learn trained areas. It's

almost like the professor teaching a

student who can also be a student

teacher, right? Who can do a little bit

of both. Uh and then there's inference

that over time will be very dedicated

and particularly as you get to uh end

points that you can't have a GPU that

you know runs at at a kilowatt of power

you just it's impossible

>> right so if you have robots in the field

we have 500 million robots what is the

chip market going to look like for

robotics how what makes it different

than what we have today on the embedded

side versus the data center side for AI

in

>> yeah physical AI is going to be a

gigantic market I mean today quite

candidly bigger than data centers.

>> Uh yeah, I think so. Uh and because I

think they're going to today they

largely use repurposed automotive chips,

right? Things that have functional

safety uh compliance around ADAS, but

they're not specific for actuators or

specific for smaller parts of the joint.

So physical AI, particularly AI that can

learn, uh is I think going to be a giant

market because the robots themselves

will have tens of chips, hundreds of

chips. So yeah, from a unit standpoint,

it could be huge. Uh the numbers are

going to be well beyond what we what we

see today.

>> You started the business or ARM started

really making reference designs and then

working with partners. Does that give

you a different perspective on things

like export controls and export

restrictions and the role that China

plays in this ecosystem than say a

different kind of vendor who would

actually be you know originating trying

to tape out themselves and trying to

sell through

>> to some extent? uh although we don't

build anything right our business model

is we do the design someone else has the

chip built mostly at TSMC some at

Samsung even Intel uh but because we are

early in the value chain relative to the

software ecosystem in other words we

probably see what people are doing

earlier than anybody else because

ultimately we're the link between the

hardware and the software so on export

control yes to some extent we have a

very big lens into it now today The

China ecosystem actually follows the

global ecosystem uh which which is good

uh from the standpoint that every mobile

phone in China it doesn't run Google

Android but it runs a version of Android

and it leverages this the app ecosystem

that comes off of Android. Same thing

with autonomous vehicles. They leverage

the the ADAS stack that was created by

uh by ARM and then Qualcomm and Nvidia.

So right now the China ecosystem on

software looks a lot like uh like the

west which for us is obviously great. Uh

and we have a very you know market

opinion in terms of where we want things

to go. It's great if the global

ecosystem remains open.

>> What's your take on um President Trump

taking 9 10% of Intel and and how did

that company miss this entire revolution

so badly?

So, you know, semiconductors, which I've

spent my entire career at. I I started

TI in 1984, and I've just been

semiconductors my my whole career. There

are long product cycles. It takes a long

time to develop chips. It takes a long

time to invest in fabs. It takes a long

time to define architectures and

ecosystems.

If you miss a few, uh time is very very

uh you will be punished for that. And I

think Intel has unfortunately been

punished on a few areas. They were

punished on on mobile obviously they

missed that completely. They were also p

punished in terms of manufacturing of uh

of going to EUV uh on uh EUV is a an

advanced uh methodology for building the

smallest chips on the planet. They

decided not to invest in that probably a

decade ago at the rate that TSMC did and

they fell behind. Once you fall behind

in chips, it's very, very difficult to

catch up because the cycle gets on top

of you. TSMC now has the best fabs in

the world. The leading edge companies,

Apple, Nvidia, AMD, they all build a

TSMC. TSMC gets better at what they're

building.

>> An Intel, a Samsung, they don't get the

opportunities. It just compounds. And

and and that flywheel once it compounds

and it compounds, it compounds, it's

very hard to catch up.

series of position.

>> So if you think about maybe then Intel

having lost its footing, you did mention

EUV and the leaders there like companies

like ASML and then even one step back

companies like Carl Zeiss that make

these lenses. Those are critical

infrastructure that the west needs.

Is there a role for the government to be

spending more capital to incubate those

kinds of things so that we have a little

bit more diversity in the supply chain?

So that you know if you contrast and

compare there's the Intel investment but

then there's these other things that are

still maybe we should also be doing.

>> Oh 100%. I mean if you look at um one of

one of the most critical components in

building chips are these rare earth

compounds and there's a belief that oh

China has cornered the market because

they have all the access to these rare

earth minerals. The access for the

minerals are global. There's no issue in

getting access to materials. Yeah,

>> the issue is in the refinement and

actually building the factories that can

refine the materials.

>> Again, that's a decades level of

investment. And I'll tell you one thing

that I when I I lived in China for a

number of years and one of the things

that I was very impressed with when I

lived there and still am is the uh

industrial policy that sits inside the

central government that will last uh

respectfully an election cycle and it

will essentially be something that they

require a lot of the folks who are in

the Ministry of Technology to be

engineers to be thinking about a policy

on on building. So to your question,

should the US do it? Absolutely.

>> Okay. So Rene, let me put you on the

spot. Look, between the Korea trade

deal, the Japanese trade deal, the

European trade deal, you know, we have

close to now two trillion of investment

capital that these countries will make

into the United States. How do we go

about creating

an ASML type company or capability or

you know these lenses like how do we do

that? What universities do we go to or

what labs do we go to? What do we do?

>> I I I think there probably needs to be

more of some of the US companies working

together. And I'll say this because ARM

is not a US company, but we I would do

the same if I would working together uh

pool pulling capital for some of these

initiatives to essentially get some type

of grounding. You need universities uh

but you need corporations to get behind

this as well as well as uh financing

private equity all kinds of different

capital because this is a this is a huge

capital investment that also requires

investment from companies and and and

private equity but at the same time

needs to last for years.

>> Just talking about the fabs TSMC's built

this facility in Arizona. There was

reports about the inability to get labor

to train labor to get a workforce that I

don't know what the right term to use is

culturally the workforce would operate

the same way as they do back in Taiwan

and they were really challenged and they

had to bring folks over to Arizona to

work the facility. These were news

reports so I I we don't know this

firsthand. Do you think we have the

capacity to do fabs in in the United

States on uh on shore here? And what's

it going to take if you were in the

administration? Let's say you were the

AISAR for example. What would you advise

the president to do to ensure that that

happens successfully?

>> Yeah, I don't want I don't want to take

anything away from David. He's doing an

amazing job as the AISAR. You've hit a

very key tenant though relative to uh

worldclass manufacturing inside the

United States and what is required to uh

to make that happen. We had it decades

ago, believe it or not. There was there

was a time where the leading contract

manufacturers

uh in the world were US-based companies

uh and uh and we knew how to do that.

And if you go back 30 years ago when

Apple and Compact used to build their

own PCs and they had their own

factories, believe it or not, then all

of that went to companies like

Flextronics and SCI etc etc. So we had

that uh ultimately for cost reasons that

began to move all the way to uh to the

Far East into Foxcon in China etc etc.

There's a great book uh Apple in China

that documents a lot of this to your

point in terms of you know could we get

that back in some ways there's no reason

why we why we couldn't but it is a

mindset TSMC is a 24/7 operation where

if a line goes down or a customer's got

a problem not only are the technicians

need to be ready to go the engineers to

be need to be ready to go and that is

something that uh I think we've lost the

muscle memory inside the United States

quite frankly on how to go do that. I

mean, we may have had it a generation or

so ago. I don't know that we have it

now. And we certainly haven't trained a

generation of folks to look at

manufacturing jobs as being something

that is as lucrative and prestigious.

They're sort of thinking, "Oh, it's a

blue collar job. I don't want to go into

that way." It's not viewed that way uh

in Taiwan, right? And in Taiwan, if you

say you're working for TSMC or studying

to go off and do that, it's a highly

prestigious kind of thing. So, it's it's

not just the AISAR's uh problem. I think

it's uh it's deeper than that in terms

of us getting

>> so you've diagnosed the problem. Do you

have a solution or recommendation? Is

there a short form that you could

highlight?

>> I I you know I think we've seen a huge

amount of work already done by

universities. I was at Carnegie Melon uh

a couple weeks ago. They now have micro

electronics classes for chip design.

That was gone a number of years ago.

There weren't even people designing

chips. So I think getting manufacturing

operations excellence uh into the

universities making that a field of of

discipline uh that the universities get

behind to build up that capacity in the

US. I think that's required. Let me go

back to export controls which Jamath

mentioned. And I'm not sure people here

know exactly how these things work, but

basically if a product like a advanced

semiconductor is put on the export

control list, it means that the company

that's selling it or the buyer, they

have to apply for a license from the

commerce department to get their

purchase order fulfilled. And the the

commerce department will then, you know,

process that license request and it goes

through some inter agency committee and

five different departments will

basically have to sign off on it. And

best case scenario, it takes months, but

there are license applications that

literally have been in the hopper for 2

years, by which time the chip is

obsolete. And believe it or not, there

are a lot of people on groups in

Washington right now who are calling for

literally every sale of a advanced

semiconductor worldwide to be a licensed

sale uh because they think that GPUs are

like plutonium or something and they're

inherently scary. I mean, this is

seriously the the the discourse that's

going on right now. And in fact, there

was um there's a major uh rule that was

put forward called the Biden diffusion

rule in the last 5 days of the Biden

administration that basically did

require every sale of a GPU worldwide to

be licensed subject to some carveouts.

Uh we we rescended that, but there is a

neverending clamor and pressure in

Washington to bring back these sorts of

of rules. And the irony is that the

people who are advocating for these

things called themselves China hawks.

But it seems to me that the whole basis

of the semiconductor industry, the

reason why it's moved so fast, why you

get new chips every year is it's really

been left alone by the government for

the most part and hasn't it hasn't been

a highly regulated industry. And I'm

curious, what do you think will happen

to the industry and the pace of

innovation if the government now makes

it heavily regulated in the way that I'm

describing? You you brought up a great

point and I think I think we may even

have a couple of those in the queue that

hasn't been approved for for a couple of

years. You're right. Semiconductors have

not been regulated traditionally. And

because of that, if you look at the real

heart of what drives uh semiconductor

growth, compute, whether it's Intel,

whether it's ARM, whether it's Nvidia,

that's the West. And why is that the

West? Because that requires both

innovation at the chip level and a

global software ecosystem. And the world

works really well when it's flat and

there isn't constraints relative to who

you sell to or how ecosystems get built.

If you shut off supply of a computing

architecture into other parts of the

world, what what will happen? Certain

parts of the world that have the

capabilities either in terms of people,

technology,

uh innovation, they will find a way and

they will find a way around around the

problem. And once that happens, you've

now created two parallel universes. And

then the US and the West would be at

risk of that other ecosystem being an

ecosystem of choice. So if you can

navigate for those licenses being

expedited, uh the the world works really

well in semis when it's flat and a

global ecosystem. Uh may the best

company win. Renee, the company started

in Cambridge

and uh originally all the employees were

there, but now it's sort of, you know, I

think 50% of the employees are in the

UK. Um, tell us about building a company

there and just multiculturally and where

you're going based on sort of, you know,

where technology is going. company was

started in uh in the UK in Cambridge uh

in a barn uh part of a joint venture for

uh the Apple Newton uh building a

processor combination of a joint venture

of Apple and BLSI technology. They

needed a lowcost chip that could run off

a battery. They contracted a company to

build the chip. The chip wasn't so good,

but a bunch of guys said, "You know

what? The design's pretty good and why

don't we try to build a business from

it?" And that that's how ARM uh ARM was

born. I'm the fourth CEO. Um, I'm the

first one that is not from the UK. Uh,

and I'm what I've been trying to do in

the in the three and a half years that I

took over is to keep the great

scientists and technology innovation

that we have in Cambridge, but inject a

bit of a a Silicon Valley uh

aggressiveness and and twist to uh to

moving faster and going quicker. Uh now

as you said half the employees are in

the UK but we've got folks globally

2,000 people in Bangalore uh probably

over over a thousand in the United

States different parts of Europe. So

it's a highly global company and we go

where the talent is and we look for

great engineers.

>> Are you able to find great STEM talent

still here or do you need now more

investment in core double E and chip

design?

>> We need far more investment. Uh our

business is not one yet where I can say

I'm hiring less people because of AI.

I'm certainly hiring less finance people

and legal people. Sorry Jason and

Spencer if you're in the audience. But

for engineers, uh, AI for development,

AI for creation, AI for science, that's

still a hard problem to solve. Uh, which

is why we need more engineers to develop

chips, which is great. I think back to

is there more demand for compute? Is

this AI wave that we're seeing going to

continue in the world of generating AI

for science and creation? I think

there's a ways to go.

>> Leveling up for a second and looking at

our relationship with China and to get a

little geopolitical here, how do you

view China versus America? Is this going

to be a winner take all with AI? Or can

these two, you know, powers get along?

Are we competitors? Are we

collaborators? Are we destined to fight

uh and go to war in Taiwan like we

talked about last year on this stage?

What's your take on it? And is there a

path to us having a great collaboration

with China?

>> I'm going to be an optimist here, Jason,

and say I think yes. Uh I think uh that

that China views some of the things

around AI in terms of whether there are

these are things like guard rails or

policies or things to keep things in

such a way that we've got the right

level of safety checks. I think their

their their minds are in the right

space. And I say this just based upon

conversations I've had with folks over

there. I wouldn't necessarily compare it

to the nuclear arms race, but in some

ways it's not dissimilar in the sense

that you need the the the countries that

have the capabilities to be willing to

sit at the table to have the

conversations and China in my experience

has shown that so far.

>> Ladies and gentlemen, Renee Hos. Thank

you.

[Applause]

Thanks, Rene.

[Music]

Thank you so much.