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There's a company nearly every chipmaker
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relies on that doesn't actually make
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anything tangible. Yet, its Blockbuster
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IPO in September valued it above 54
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billion.
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It's the largest public offering in over
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2 years.
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The valuation of the company has
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tripled.
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If you have a smartphone in your pocket
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or in front of you, you have an ARM
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circuit somewhere inside of it.
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We are the CPU, the heart of everything.
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They're the winner of the CPU side. the
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foundation models, the software, it's
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moving far faster than the hardware. So,
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what we're seeing is people investing
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faster and faster into new hardware,
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which ends up being a good thing for us.
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Ladies and gentlemen, please welcome ARM
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CEO Renee Hos.
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[Applause]
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[Music]
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Thank you so much.
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How are you?
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Welcome. Welcome,
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David. Hey, good to see you. Hi.
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Hello,
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Renee. What are you banging these days?
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3 milligrams of AL pouches or you're up
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to nine.
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I know you're competing with Nvidia, so
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you probably want to go with the nine,
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right?
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I will go with the nine with Jensen. You
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have to go big.
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You have to go big with Jensen. What's
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that like to compete against Nvidia?
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Well, I will say uh Nvidia is a customer
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of ours. So, I'm not going to say Jensen
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is my competitor uh today, but you know,
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I worked for Nvidia for for many many
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years as as you know. uh and he's
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fantastic right and uh learned so much
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working there working for him working
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with him and then Nvidia you know almost
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acquired ARM in 2020 uh so I almost you
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know had a chance to work with him again
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what did you learn from Jensen
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you know one of the things about Jensen
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that is amazing I think it's also true
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for people like uh Michael Dell uh Masa
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you have these entrepreneurs who started
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their companies uh 30 years ago 40 years
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ago go and and they're still running it.
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So, you have this amazing set of
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characteristics of vision, speed,
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fearlessness, taking risk, and a an
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ability to pivot uh very very fast. And
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and I saw that a lot at NVIDIA. You
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know, when I was there, we were only
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about $4 billion in sales. And uh and at
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that time, we were looking at lots of
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different ways to grow business models
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and such. And I just remember being, you
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know, one story we were at a a strategic
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offsite and it was supposed to be a
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review of road maps where we were
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looking at each one of the general
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managers going through what they uh
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projected in their business and what was
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intended to be a roadmap review turned
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into we're changing the strategy. We're
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abolishing this product line. We're
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going to move 2,000 engineers off of
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project X onto project Y. And by the
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way, we were only about 6,000 people at
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the time.
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What was project X? What was project Y?
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So we were involved uh at that time in
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trying to do uh mobile chipsets
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connecting to an Intel processor, right?
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And back in the day uh for those who
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remember PC architecture doing these
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chipsets competing with Intel was was
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really hard business and Intel was
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making it very very hard to compete uh
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relative to the integration that they
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did. And in fact that was the genesis of
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starting to pivot to ARM in a very big
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way inside Nvidia because at that time
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Jensen looked at what was going on with
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SOC's and ARMbased architecture and
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moved everybody onto the program.
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Let's maybe take a step back and level
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set for the audience. So just to give
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some background um Masayoshi Sun and
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Soft Bank took ARM private
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took private yeah for $32 billion.
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$32 billion and then tried to sell it
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famously.
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Yes.
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Couldn't find a bidder.
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Could not find a bidder.
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Hung on to it. took it public. It's now
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a $150 billion market cap company.
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That's right.
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And you were telling us backstage he
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famously, you know, refuses to sell a
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share.
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So, it's like a slow kind of process of
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just building the the shareholder base,
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but you've done phenomenally well as a
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business.
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Just set the landscape for people that
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want to understand Nvidia, the most
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valuable company in the world, but it's
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a it's a window to understanding AI.
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Mhm.
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Why does what do they make that's so
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powerful? And why aren't there other
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competitive solutions at at that level
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of scale yet? And how do you think that
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changes over the next 5 10 years?
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Oh boy. Uh lot lot a lot there to uh to
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describe. So the the way to think about
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Nvidia uh and to some extent I I don't
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even though I'm the CEO of ARM I don't
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want to tie it necessarily back to ARM
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but in our world what really drives
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demand is compute workloads. you know at
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the end of the day is compute workloads
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and when a new workload is uh
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essentially either identified and or
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invented then it comes down to what is
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the best architecture processor-wise to
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address that workload. So let's look at
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AI. You know the lightning bolt moment
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of of Alex Net uh and the work actually
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that the Demison team were working on.
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AI particularly training uh is a very
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very complex parallel problem that is
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well suited for a GPU and in fact the
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very first work done by the engineers on
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AlexNet was not with Blackwell. It was
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not with a an AI processor but it was
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with a gaming GPU a gaming card. So
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Nvidia was in a a very very good place
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to seize that moment relative to the
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deepmind moment slalexnet
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slash the transformer/training
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and fast forward training these complex
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AI models as Dennis was just talking
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about this is a huge huge amount of work
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now what role does ARM play there every
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one of these workloads requires a CPU to
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not only run the computer but help the
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accelerator run and that's where Nvidia
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is a customer today their most advanced
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chip called Grace Blackwell is 72 ARM
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CPUs with a Blackwell architecture and
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that's that's where Nvidia plays today.
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So back to uh where does Nvidia fit?
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There is competition. You know Demis
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talked about uh prior with Google they
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do their own chip called TPUs. Uh
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obviously Nvidia is the leader with
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general purpose but right now we're in
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this interesting world where people are
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looking at is it a general purpose chip
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is it a custom chip etc etc. It's a
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fascinating time to be in this industry
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for sure.
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Where do you think companies like
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Tesla, you know, Tesla recently merged
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two pads and now they're working on AI5
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and AI6? Um, and some of the more
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emerging companies like Cerebras and
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there's a whole slew of companies now,
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Grock and others that have raised
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enormous amounts of money. Um, do you
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believe that the the role of ARM should
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be to be the lack of a better phrase,
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the arms dealer to all of those folks
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that need that capability or at some
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point do you think that you know you see
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enough of it where you're like gosh I
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could just do this better?
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Maybe a little bit of both. Uh, I mean
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today the role we play is we are now
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increasingly that microprocessor that
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connects to these accelerators whether
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it's something that's done by Cerebras
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or it's something that's done by Nvidia.
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uh something done by uh by Google,
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they're connected. Uh could we do
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something ourselves custom? It's
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possible. Could we also supply the
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intellectual property to somebody
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building a custom chip? We're doing that
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today. So to some extent um we're in a
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very unique place that not only can we
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provide the solution whether it's
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standard or custom but as AI moves from
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gigawatt data centers to running in
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these headsets or running in a wearable
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or running in something that needs to be
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energy efficient you still need to run
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the compute workload but now you need to
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run the run the AI workload and that is
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a place that I think only ARM is
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uniquely positioned to address.
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So you're going to make chips and
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compete with Nvidia. Uh, I'm not going
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to say that today, but could we do that?
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I hinted in the last conference call
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that we're looking at going a little bit
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further than we do today.
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Could we see in the, you know, next few
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years, could we see a divergence in the
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market between training and and
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inference? Because what I've noticed is
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that you've got XAI and OpenAI and, you
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know, Google's already doing it with
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TPUs. They're they're building their own
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chips for inference, which might be, I
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don't know, 99% of the workloads. They
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seem to acknowledge that Nvidia is the
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best at training and they don't seem
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they haven't at least announced an
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effort to challenge Nvidia for for
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training. So is there is there a
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possibility that you know the the market
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could sort of bifurcate into training
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chips and inference chips and inference
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gets much more competitive? Yes. I and I
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also think you have a third bucket where
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training distills down to simpler
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training chips that you don't need to
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run a trillion parameter model. You
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could have a giant model that now treats
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and teaches smaller models, mixture
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experts, 20 billion parameters that can
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be a mix of inference and training doing
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reinforcement learning where the chip is
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now helping uh learn trained areas. It's
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almost like the professor teaching a
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student who can also be a student
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teacher, right? Who can do a little bit
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of both. Uh and then there's inference
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that over time will be very dedicated
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and particularly as you get to uh end
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points that you can't have a GPU that
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you know runs at at a kilowatt of power
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you just it's impossible
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right so if you have robots in the field
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we have 500 million robots what is the
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chip market going to look like for
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robotics how what makes it different
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than what we have today on the embedded
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side versus the data center side for AI
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in
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yeah physical AI is going to be a
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gigantic market I mean today quite
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candidly bigger than data centers.
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Uh yeah, I think so. Uh and because I
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think they're going to today they
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largely use repurposed automotive chips,
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right? Things that have functional
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safety uh compliance around ADAS, but
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they're not specific for actuators or
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specific for smaller parts of the joint.
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So physical AI, particularly AI that can
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learn, uh is I think going to be a giant
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market because the robots themselves
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will have tens of chips, hundreds of
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chips. So yeah, from a unit standpoint,
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it could be huge. Uh the numbers are
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going to be well beyond what we what we
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see today.
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You started the business or ARM started
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really making reference designs and then
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working with partners. Does that give
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you a different perspective on things
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like export controls and export
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restrictions and the role that China
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plays in this ecosystem than say a
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different kind of vendor who would
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actually be you know originating trying
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to tape out themselves and trying to
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sell through
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to some extent? uh although we don't
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build anything right our business model
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is we do the design someone else has the
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chip built mostly at TSMC some at
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Samsung even Intel uh but because we are
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early in the value chain relative to the
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software ecosystem in other words we
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probably see what people are doing
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earlier than anybody else because
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ultimately we're the link between the
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hardware and the software so on export
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control yes to some extent we have a
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very big lens into it now today The
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China ecosystem actually follows the
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global ecosystem uh which which is good
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uh from the standpoint that every mobile
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phone in China it doesn't run Google
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Android but it runs a version of Android
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and it leverages this the app ecosystem
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that comes off of Android. Same thing
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with autonomous vehicles. They leverage
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the the ADAS stack that was created by
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uh by ARM and then Qualcomm and Nvidia.
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So right now the China ecosystem on
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software looks a lot like uh like the
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west which for us is obviously great. Uh
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and we have a very you know market
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opinion in terms of where we want things
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to go. It's great if the global
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ecosystem remains open.
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What's your take on um President Trump
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taking 9 10% of Intel and and how did
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that company miss this entire revolution
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so badly?
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So, you know, semiconductors, which I've
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spent my entire career at. I I started
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TI in 1984, and I've just been
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semiconductors my my whole career. There
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are long product cycles. It takes a long
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time to develop chips. It takes a long
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time to invest in fabs. It takes a long
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time to define architectures and
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ecosystems.
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If you miss a few, uh time is very very
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uh you will be punished for that. And I
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think Intel has unfortunately been
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punished on a few areas. They were
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punished on on mobile obviously they
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missed that completely. They were also p
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punished in terms of manufacturing of uh
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of going to EUV uh on uh EUV is a an
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advanced uh methodology for building the
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smallest chips on the planet. They
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decided not to invest in that probably a
00:12:31
decade ago at the rate that TSMC did and
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they fell behind. Once you fall behind
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in chips, it's very, very difficult to
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catch up because the cycle gets on top
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of you. TSMC now has the best fabs in
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the world. The leading edge companies,
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Apple, Nvidia, AMD, they all build a
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TSMC. TSMC gets better at what they're
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building.
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An Intel, a Samsung, they don't get the
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opportunities. It just compounds. And
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and and that flywheel once it compounds
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and it compounds, it compounds, it's
00:13:01
very hard to catch up.
00:13:03
series of position.
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So if you think about maybe then Intel
00:13:05
having lost its footing, you did mention
00:13:08
EUV and the leaders there like companies
00:13:10
like ASML and then even one step back
00:13:13
companies like Carl Zeiss that make
00:13:15
these lenses. Those are critical
00:13:17
infrastructure that the west needs.
00:13:20
Is there a role for the government to be
00:13:22
spending more capital to incubate those
00:13:25
kinds of things so that we have a little
00:13:26
bit more diversity in the supply chain?
00:13:29
So that you know if you contrast and
00:13:31
compare there's the Intel investment but
00:13:33
then there's these other things that are
00:13:35
still maybe we should also be doing.
00:13:37
Oh 100%. I mean if you look at um one of
00:13:40
one of the most critical components in
00:13:41
building chips are these rare earth
00:13:43
compounds and there's a belief that oh
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China has cornered the market because
00:13:46
they have all the access to these rare
00:13:48
earth minerals. The access for the
00:13:51
minerals are global. There's no issue in
00:13:53
getting access to materials. Yeah,
00:13:54
the issue is in the refinement and
00:13:56
actually building the factories that can
00:13:59
refine the materials.
00:14:00
Again, that's a decades level of
00:14:03
investment. And I'll tell you one thing
00:14:05
that I when I I lived in China for a
00:14:06
number of years and one of the things
00:14:08
that I was very impressed with when I
00:14:10
lived there and still am is the uh
00:14:13
industrial policy that sits inside the
00:14:16
central government that will last uh
00:14:19
respectfully an election cycle and it
00:14:22
will essentially be something that they
00:14:24
require a lot of the folks who are in
00:14:27
the Ministry of Technology to be
00:14:28
engineers to be thinking about a policy
00:14:30
on on building. So to your question,
00:14:33
should the US do it? Absolutely.
00:14:35
Okay. So Rene, let me put you on the
00:14:36
spot. Look, between the Korea trade
00:14:38
deal, the Japanese trade deal, the
00:14:40
European trade deal, you know, we have
00:14:41
close to now two trillion of investment
00:14:43
capital that these countries will make
00:14:46
into the United States. How do we go
00:14:48
about creating
00:14:50
an ASML type company or capability or
00:14:54
you know these lenses like how do we do
00:14:57
that? What universities do we go to or
00:14:59
what labs do we go to? What do we do?
00:15:01
I I I think there probably needs to be
00:15:03
more of some of the US companies working
00:15:06
together. And I'll say this because ARM
00:15:07
is not a US company, but we I would do
00:15:09
the same if I would working together uh
00:15:12
pool pulling capital for some of these
00:15:14
initiatives to essentially get some type
00:15:16
of grounding. You need universities uh
00:15:18
but you need corporations to get behind
00:15:20
this as well as well as uh financing
00:15:24
private equity all kinds of different
00:15:25
capital because this is a this is a huge
00:15:28
capital investment that also requires
00:15:31
investment from companies and and and
00:15:32
private equity but at the same time
00:15:34
needs to last for years.
00:15:36
Just talking about the fabs TSMC's built
00:15:39
this facility in Arizona. There was
00:15:41
reports about the inability to get labor
00:15:43
to train labor to get a workforce that I
00:15:46
don't know what the right term to use is
00:15:48
culturally the workforce would operate
00:15:50
the same way as they do back in Taiwan
00:15:52
and they were really challenged and they
00:15:54
had to bring folks over to Arizona to
00:15:56
work the facility. These were news
00:15:57
reports so I I we don't know this
00:15:59
firsthand. Do you think we have the
00:16:01
capacity to do fabs in in the United
00:16:03
States on uh on shore here? And what's
00:16:06
it going to take if you were in the
00:16:08
administration? Let's say you were the
00:16:09
AISAR for example. What would you advise
00:16:12
the president to do to ensure that that
00:16:13
happens successfully?
00:16:15
Yeah, I don't want I don't want to take
00:16:16
anything away from David. He's doing an
00:16:17
amazing job as the AISAR. You've hit a
00:16:20
very key tenant though relative to uh
00:16:22
worldclass manufacturing inside the
00:16:24
United States and what is required to uh
00:16:27
to make that happen. We had it decades
00:16:30
ago, believe it or not. There was there
00:16:32
was a time where the leading contract
00:16:34
manufacturers
00:16:36
uh in the world were US-based companies
00:16:39
uh and uh and we knew how to do that.
00:16:42
And if you go back 30 years ago when
00:16:45
Apple and Compact used to build their
00:16:47
own PCs and they had their own
00:16:49
factories, believe it or not, then all
00:16:51
of that went to companies like
00:16:53
Flextronics and SCI etc etc. So we had
00:16:56
that uh ultimately for cost reasons that
00:17:00
began to move all the way to uh to the
00:17:02
Far East into Foxcon in China etc etc.
00:17:04
There's a great book uh Apple in China
00:17:06
that documents a lot of this to your
00:17:10
point in terms of you know could we get
00:17:11
that back in some ways there's no reason
00:17:14
why we why we couldn't but it is a
00:17:16
mindset TSMC is a 24/7 operation where
00:17:20
if a line goes down or a customer's got
00:17:22
a problem not only are the technicians
00:17:25
need to be ready to go the engineers to
00:17:27
be need to be ready to go and that is
00:17:29
something that uh I think we've lost the
00:17:32
muscle memory inside the United States
00:17:34
quite frankly on how to go do that. I
00:17:35
mean, we may have had it a generation or
00:17:37
so ago. I don't know that we have it
00:17:39
now. And we certainly haven't trained a
00:17:41
generation of folks to look at
00:17:42
manufacturing jobs as being something
00:17:44
that is as lucrative and prestigious.
00:17:46
They're sort of thinking, "Oh, it's a
00:17:47
blue collar job. I don't want to go into
00:17:48
that way." It's not viewed that way uh
00:17:50
in Taiwan, right? And in Taiwan, if you
00:17:53
say you're working for TSMC or studying
00:17:54
to go off and do that, it's a highly
00:17:56
prestigious kind of thing. So, it's it's
00:17:58
not just the AISAR's uh problem. I think
00:18:02
it's uh it's deeper than that in terms
00:18:03
of us getting
00:18:04
so you've diagnosed the problem. Do you
00:18:05
have a solution or recommendation? Is
00:18:07
there a short form that you could
00:18:08
highlight?
00:18:08
I I you know I think we've seen a huge
00:18:11
amount of work already done by
00:18:12
universities. I was at Carnegie Melon uh
00:18:14
a couple weeks ago. They now have micro
00:18:16
electronics classes for chip design.
00:18:19
That was gone a number of years ago.
00:18:20
There weren't even people designing
00:18:21
chips. So I think getting manufacturing
00:18:24
operations excellence uh into the
00:18:25
universities making that a field of of
00:18:29
discipline uh that the universities get
00:18:31
behind to build up that capacity in the
00:18:33
US. I think that's required. Let me go
00:18:35
back to export controls which Jamath
00:18:37
mentioned. And I'm not sure people here
00:18:38
know exactly how these things work, but
00:18:40
basically if a product like a advanced
00:18:43
semiconductor is put on the export
00:18:44
control list, it means that the company
00:18:47
that's selling it or the buyer, they
00:18:48
have to apply for a license from the
00:18:50
commerce department to get their
00:18:51
purchase order fulfilled. And the the
00:18:55
commerce department will then, you know,
00:18:57
process that license request and it goes
00:18:59
through some inter agency committee and
00:19:01
five different departments will
00:19:02
basically have to sign off on it. And
00:19:04
best case scenario, it takes months, but
00:19:06
there are license applications that
00:19:07
literally have been in the hopper for 2
00:19:09
years, by which time the chip is
00:19:11
obsolete. And believe it or not, there
00:19:13
are a lot of people on groups in
00:19:15
Washington right now who are calling for
00:19:17
literally every sale of a advanced
00:19:19
semiconductor worldwide to be a licensed
00:19:22
sale uh because they think that GPUs are
00:19:25
like plutonium or something and they're
00:19:26
inherently scary. I mean, this is
00:19:28
seriously the the the discourse that's
00:19:30
going on right now. And in fact, there
00:19:32
was um there's a major uh rule that was
00:19:34
put forward called the Biden diffusion
00:19:36
rule in the last 5 days of the Biden
00:19:38
administration that basically did
00:19:40
require every sale of a GPU worldwide to
00:19:42
be licensed subject to some carveouts.
00:19:44
Uh we we rescended that, but there is a
00:19:47
neverending clamor and pressure in
00:19:49
Washington to bring back these sorts of
00:19:51
of rules. And the irony is that the
00:19:54
people who are advocating for these
00:19:55
things called themselves China hawks.
00:19:57
But it seems to me that the whole basis
00:20:00
of the semiconductor industry, the
00:20:01
reason why it's moved so fast, why you
00:20:03
get new chips every year is it's really
00:20:05
been left alone by the government for
00:20:07
the most part and hasn't it hasn't been
00:20:09
a highly regulated industry. And I'm
00:20:11
curious, what do you think will happen
00:20:13
to the industry and the pace of
00:20:14
innovation if the government now makes
00:20:16
it heavily regulated in the way that I'm
00:20:19
describing? You you brought up a great
00:20:21
point and I think I think we may even
00:20:23
have a couple of those in the queue that
00:20:24
hasn't been approved for for a couple of
00:20:26
years. You're right. Semiconductors have
00:20:29
not been regulated traditionally. And
00:20:31
because of that, if you look at the real
00:20:33
heart of what drives uh semiconductor
00:20:36
growth, compute, whether it's Intel,
00:20:39
whether it's ARM, whether it's Nvidia,
00:20:40
that's the West. And why is that the
00:20:43
West? Because that requires both
00:20:44
innovation at the chip level and a
00:20:46
global software ecosystem. And the world
00:20:48
works really well when it's flat and
00:20:51
there isn't constraints relative to who
00:20:54
you sell to or how ecosystems get built.
00:20:57
If you shut off supply of a computing
00:20:59
architecture into other parts of the
00:21:01
world, what what will happen? Certain
00:21:04
parts of the world that have the
00:21:05
capabilities either in terms of people,
00:21:07
technology,
00:21:09
uh innovation, they will find a way and
00:21:12
they will find a way around around the
00:21:14
problem. And once that happens, you've
00:21:16
now created two parallel universes. And
00:21:19
then the US and the West would be at
00:21:21
risk of that other ecosystem being an
00:21:24
ecosystem of choice. So if you can
00:21:27
navigate for those licenses being
00:21:28
expedited, uh the the world works really
00:21:31
well in semis when it's flat and a
00:21:33
global ecosystem. Uh may the best
00:21:36
company win. Renee, the company started
00:21:38
in Cambridge
00:21:40
and uh originally all the employees were
00:21:42
there, but now it's sort of, you know, I
00:21:44
think 50% of the employees are in the
00:21:46
UK. Um, tell us about building a company
00:21:49
there and just multiculturally and where
00:21:53
you're going based on sort of, you know,
00:21:55
where technology is going. company was
00:21:57
started in uh in the UK in Cambridge uh
00:22:00
in a barn uh part of a joint venture for
00:22:03
uh the Apple Newton uh building a
00:22:05
processor combination of a joint venture
00:22:07
of Apple and BLSI technology. They
00:22:10
needed a lowcost chip that could run off
00:22:11
a battery. They contracted a company to
00:22:14
build the chip. The chip wasn't so good,
00:22:16
but a bunch of guys said, "You know
00:22:18
what? The design's pretty good and why
00:22:20
don't we try to build a business from
00:22:21
it?" And that that's how ARM uh ARM was
00:22:23
born. I'm the fourth CEO. Um, I'm the
00:22:26
first one that is not from the UK. Uh,
00:22:29
and I'm what I've been trying to do in
00:22:31
the in the three and a half years that I
00:22:32
took over is to keep the great
00:22:35
scientists and technology innovation
00:22:37
that we have in Cambridge, but inject a
00:22:39
bit of a a Silicon Valley uh
00:22:41
aggressiveness and and twist to uh to
00:22:43
moving faster and going quicker. Uh now
00:22:46
as you said half the employees are in
00:22:47
the UK but we've got folks globally
00:22:49
2,000 people in Bangalore uh probably
00:22:52
over over a thousand in the United
00:22:53
States different parts of Europe. So
00:22:55
it's a highly global company and we go
00:22:58
where the talent is and we look for
00:22:59
great engineers.
00:23:00
Are you able to find great STEM talent
00:23:02
still here or do you need now more
00:23:04
investment in core double E and chip
00:23:06
design?
00:23:06
We need far more investment. Uh our
00:23:09
business is not one yet where I can say
00:23:11
I'm hiring less people because of AI.
00:23:14
I'm certainly hiring less finance people
00:23:16
and legal people. Sorry Jason and
00:23:18
Spencer if you're in the audience. But
00:23:19
for engineers, uh, AI for development,
00:23:22
AI for creation, AI for science, that's
00:23:26
still a hard problem to solve. Uh, which
00:23:29
is why we need more engineers to develop
00:23:30
chips, which is great. I think back to
00:23:32
is there more demand for compute? Is
00:23:34
this AI wave that we're seeing going to
00:23:37
continue in the world of generating AI
00:23:40
for science and creation? I think
00:23:42
there's a ways to go.
00:23:43
Leveling up for a second and looking at
00:23:45
our relationship with China and to get a
00:23:47
little geopolitical here, how do you
00:23:50
view China versus America? Is this going
00:23:53
to be a winner take all with AI? Or can
00:23:56
these two, you know, powers get along?
00:23:59
Are we competitors? Are we
00:24:01
collaborators? Are we destined to fight
00:24:05
uh and go to war in Taiwan like we
00:24:07
talked about last year on this stage?
00:24:09
What's your take on it? And is there a
00:24:10
path to us having a great collaboration
00:24:13
with China?
00:24:14
I'm going to be an optimist here, Jason,
00:24:15
and say I think yes. Uh I think uh that
00:24:18
that China views some of the things
00:24:21
around AI in terms of whether there are
00:24:24
these are things like guard rails or
00:24:26
policies or things to keep things in
00:24:27
such a way that we've got the right
00:24:29
level of safety checks. I think their
00:24:31
their their minds are in the right
00:24:32
space. And I say this just based upon
00:24:34
conversations I've had with folks over
00:24:36
there. I wouldn't necessarily compare it
00:24:38
to the nuclear arms race, but in some
00:24:41
ways it's not dissimilar in the sense
00:24:43
that you need the the the countries that
00:24:45
have the capabilities to be willing to
00:24:47
sit at the table to have the
00:24:48
conversations and China in my experience
00:24:50
has shown that so far.
00:24:52
Ladies and gentlemen, Renee Hos. Thank
00:24:54
you.
00:24:58
[Applause]
00:25:00
Thanks, Rene.
00:25:02
[Music]
00:25:03
Thank you so much.
