WEBVTT - On Site at the Earthshot Conference

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<v Speaker 1>Bloomberg Audio Studios, Podcasts, radio news.

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<v Speaker 2>This is the Bloomberg Surveillance Podcast. I'm Tom Keene along

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<v Speaker 2>with Paul Sweeney. Join us each day for insight from

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<v Speaker 2>mornings from seven to ten am Eastern from our global

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<v Speaker 2>headquarters in New York City. Subscribe to the podcast on Apple, Spotify,

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<v Speaker 2>or anywhere else you listen, and always I'm Bloomberg Radio,

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<v Speaker 2>the Bloomberg Terminal, and the Bloomberg Business app. Joining us

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<v Speaker 2>right now, she's with Airbus Adventures. She's not with the Airbus,

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<v Speaker 2>although she likes the Beluga, but she's with Airbus Ventures.

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<v Speaker 2>No Cole Connor joins us here on investment in all

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<v Speaker 2>of this, is there too much money chasing too few

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<v Speaker 2>ideas or the other way around?

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<v Speaker 3>It thinks the other way around. There's so many opportunities

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<v Speaker 3>right now, and I think this is a really special

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<v Speaker 3>time for venture capital and for these startups who are

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<v Speaker 3>working on taking these important emerging technologies out of the

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<v Speaker 3>lab and into the real world. At our fund, we're

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<v Speaker 3>investing in everything from autonomy to electrification, the low carbon economy,

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<v Speaker 3>news space, advanced materials, quantum computing, networking and sensing. And

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<v Speaker 3>as we've seen a climate week, there's no end to

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<v Speaker 3>the number of startups who are trying to solve these

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<v Speaker 3>important challenges.

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<v Speaker 2>You have a wonderful transatlantic view at Airbus Ventures. What

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<v Speaker 2>I see when I'm in London or Paris is a

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<v Speaker 2>huge success or belief in the future of climate versus

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<v Speaker 2>a hugely fractious United States debate on climate. Describe that

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<v Speaker 2>debate and how it affects investment.

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<v Speaker 3>What we see is that we're you know, we're investing

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<v Speaker 3>in CEEDD, siri B companies who are working on bricks

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<v Speaker 3>of technology that are hoping to solve this challenge. We

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<v Speaker 3>are uniquely positioned as one of the few global VC funds.

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<v Speaker 3>We're investing all over the world, and what we see

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<v Speaker 3>as an optimism on seeing how these technologies can help

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<v Speaker 3>shape the future of tomorrow. Some of these technologies that

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<v Speaker 3>will be changing products, you know, in decades time, So

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<v Speaker 3>we have a very optimimistic view on the current environment.

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<v Speaker 4>Help me with the term deep technology, So you invest

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<v Speaker 4>in deep technology entrepreneurship, what does it mean and how

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<v Speaker 4>does that set you apart from other VC shops.

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<v Speaker 3>We're investing in the hardest engineering problems to solve, and

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<v Speaker 3>the deep tech investment practice is extremely important in unlocking

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<v Speaker 3>these opportunities down the chain. So when you think about

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<v Speaker 3>I think about one of our portfolio companies who's sitting

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<v Speaker 3>in the Brooklyn Navy Yard called que Net. They're working

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<v Speaker 3>on quantum networking hardware. This is a product suite that

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<v Speaker 3>will sit on existing telecom infrastructure to allow for quantum communications.

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<v Speaker 3>Why that matters is that's ultra secure communication. So the

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<v Speaker 3>national security sector is very interested in seeing even how

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<v Speaker 3>if you can use their product suite to see if

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<v Speaker 3>someone is tapping the line, and ultra secure communication matters

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<v Speaker 3>for so many industries, finance, defense, national security, of course.

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<v Speaker 3>So that's where we're focused on. How can we work

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<v Speaker 3>on using these bricks of technology to unlock other problems.

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<v Speaker 4>Nicole, We'll get Tom over to the Brooklyn Navy Yard here,

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<v Speaker 4>we'll get you to Brooklyn at some point.

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<v Speaker 3>Bagels crave that that's incredible community over there.

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<v Speaker 4>Tell me about your background. I mean you are somebody's

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<v Speaker 4>a lawyer. You're based in DC. I remember talking with

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<v Speaker 4>Steve case a while back about sort of broadening the

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<v Speaker 4>reach of VC beyond Boston, beyond the Bay Area. What

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<v Speaker 4>added value perspective does that give you being based in

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<v Speaker 4>Washington versus those other places.

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<v Speaker 3>Well, certainly in the areas that we're investing. These are

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<v Speaker 3>all on the Critical and Emerging Technologies list for the US.

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<v Speaker 3>So many of our folio companies, they are in and

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<v Speaker 3>out of DC, meeting with their customers, the agencies, the

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<v Speaker 3>aerospace primes in Northern Virginia, their headmans on the hill.

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<v Speaker 3>I think there is a strong appetite to better understand

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<v Speaker 3>how these technologies can be plugged into other areas and

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<v Speaker 3>challenges that we have. I would say, with my background,

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<v Speaker 3>what we'd like to say within our fund is that

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<v Speaker 3>we have a Swiss Army knife of a team. Founders

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<v Speaker 3>have no end to the challenges that they need to navigate,

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<v Speaker 3>and so yes, I bring my financial and operational background.

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<v Speaker 3>We have aerospace engineers and mechanical engineers, physicists, all of whom

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<v Speaker 3>are working with our founders to get their technologies out

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<v Speaker 3>into the market.

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<v Speaker 2>You are living the skepticism of America over climate change

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<v Speaker 2>in this election of David's expert on the election. I'm not,

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<v Speaker 2>but you go state to state, it's almost an unmentionable

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<v Speaker 2>rather too candidates, how does America become more like Europe

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<v Speaker 2>in climate change? Or do you suggest we stay distant

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<v Speaker 2>from the enthusiasm.

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<v Speaker 3>I think it's important to focus on the technologies themselves

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<v Speaker 3>because in the debate it's getting lost, Like for example,

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<v Speaker 3>we could look at hydrogen aircraft. These are exciting opportunities.

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<v Speaker 3>This is what the market wants, is they want to

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<v Speaker 3>have novel ways of flying that has less climate impact.

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<v Speaker 3>And so we like to stay out of the noise

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<v Speaker 3>and in terms of any debate on this, because we

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<v Speaker 3>think the technologies will show themselves.

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<v Speaker 4>What do folks need to know just about the environment?

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<v Speaker 4>For venture capital? At this point, we've been through a

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<v Speaker 4>couple of years when the environment wasn't as great as

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<v Speaker 4>as it had been. Where are we in the arc

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<v Speaker 4>of sort of its energy or success or how does

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<v Speaker 4>it feel at this moment being in VC.

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<v Speaker 3>Feeling optimistic? Actually, I think that there's a lot it's

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<v Speaker 3>important right now, and we as a fund want to

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<v Speaker 3>really bring the expertise into bringing these technologies out, and

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<v Speaker 3>so I think it's important that right now we're seeing

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<v Speaker 3>VC funds who have special expertise really focused on the founders,

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<v Speaker 3>and I think the interest rate helps helps. It certainly helps,

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<v Speaker 3>and so we're feeling good and I think hopefully getting

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<v Speaker 3>through the election process itself.

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<v Speaker 5>Well, I've got my question of the day.

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<v Speaker 2>Is a shock worldwide that Microsoft is going to team

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<v Speaker 2>up for electrical generations three Mile Island with Constellation Energy.

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<v Speaker 2>How did you react when you saw that, I mean

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<v Speaker 2>talk about a jump condition for energy or energy generation,

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<v Speaker 2>I should say yeah.

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<v Speaker 3>I think it's it's just reflective of the fact that

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<v Speaker 3>companies are eager for anyone to find solutions for the

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<v Speaker 3>energy crisis that they that they have, I mean a lot.

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<v Speaker 3>I mean, if you think about AI, there's a huge

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<v Speaker 3>amount of energy consumption in order to run some of

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<v Speaker 3>these models, and so it's it's unsurprising that they're looking

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<v Speaker 3>for any particular technology that can help solve their problem.

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<v Speaker 5>Nicole, thank you for j.

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<v Speaker 2>So there must be not today getting us started here

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<v Speaker 2>at the Earth Shot A Prize awards.

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<v Speaker 6>It this is a joy.

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<v Speaker 2>He is someone at Morgan Stanley who's done the tour

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<v Speaker 2>of duty and very rarely do you see such an

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<v Speaker 2>extended commitment to one project.

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<v Speaker 5>That project.

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<v Speaker 2>Well, maybe it's not as iconic as the Dow Jones

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<v Speaker 2>Industrial Average, but within Global Wall Street, MSCI is understood

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<v Speaker 2>by all. Henry Fernandez joins us this morning with your

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<v Speaker 2>baby ms CI. What was it like the first years

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<v Speaker 2>of MSCI where you had to go into every meetia.

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<v Speaker 6>To explain what are we doing there?

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<v Speaker 2>Now you own Emerging market in Global Index Analysis.

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<v Speaker 7>So I created a company thirty years ago on top

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<v Speaker 7>of the what was then the morning Stanley Capital International

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<v Speaker 7>in this is and that was the only problem we had, right,

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<v Speaker 7>you know, market cup in this is and it was

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<v Speaker 7>a call center, so we didn't have a lot of resources,

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<v Speaker 7>and the world wanted a lot from us. So we

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<v Speaker 7>had to educate a lot of people and expand and

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<v Speaker 7>you know, eventually brought a lot of companies and spin

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<v Speaker 7>out of Morgan Stanley and it's a forty billion dollar

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<v Speaker 7>market cap company today.

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<v Speaker 2>You were focused on the innovation here of the accountability

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<v Speaker 2>of data over to the climate challenges we have. How

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<v Speaker 2>are you going to bring your data acumen over to

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<v Speaker 2>a better measurement of our climate disaster?

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<v Speaker 7>So clearly climate risk is an existential risk for all

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<v Speaker 7>of us. But in the Capital industry. You know, you

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<v Speaker 7>can decimate portfolios. There'll be winners and losers, and all

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<v Speaker 7>of them arender your portfolio today. So the question is

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<v Speaker 7>how are you going to discern who those are and

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<v Speaker 7>how you're going to start transitioning to a low carbon PORTFOLI.

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<v Speaker 7>So it's a lot of it a question of measurement.

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<v Speaker 7>So what's the nature of your problem? Whereas the carbon emissions,

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<v Speaker 7>where are the big climate risk? What do you do

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<v Speaker 7>about it? Where do you start? Do you start in

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<v Speaker 7>private assets and public acids? And very importantly, at what

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<v Speaker 7>pace do you go? If you go too fast, you

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<v Speaker 7>get underperform because.

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<v Speaker 8>You're gone too fast. Is Europe going too fast?

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<v Speaker 5>No?

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<v Speaker 7>No, I mean nothing in the world is going too

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<v Speaker 7>fast for you know, the Parents Agreement put a day

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<v Speaker 7>of twenty fifty because we needed to get two hundred

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<v Speaker 7>countries to agree. But it was so far out that

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<v Speaker 7>you know, people think that this is a long term problem.

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<v Speaker 7>Of course it is a long term problem, but it's

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<v Speaker 7>also a short to medium term problem.

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<v Speaker 5>You know, we.

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<v Speaker 7>Already see an enormous physical risk around the world.

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<v Speaker 2>I mean, you've got a risk in Brooklyn that your

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<v Speaker 2>house can float away, right, Well, I.

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<v Speaker 4>Mean thankfully out of the bottom floor. Yeah, get around

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<v Speaker 4>the great way up park slope. I remember talking to

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<v Speaker 4>Anfinuca on her last day at Bank of America about ESG,

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<v Speaker 4>something about which she is so passionate, has been for

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<v Speaker 4>so long, and we talked about the issue of standardization

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<v Speaker 4>that company is trying to keep up with this kind

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<v Speaker 4>of data, have so many ways which they're filing or

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<v Speaker 4>making filings known. Help me understand that where we are

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<v Speaker 4>in that process of winning and simplifying data when it

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<v Speaker 4>comes to ESG and climate issues and in particular, is

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<v Speaker 4>it's still too much of a wild west that it

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<v Speaker 4>should be?

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<v Speaker 5>No, really there is.

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<v Speaker 7>First of all, ESG is investment risk and opportunities. It's

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<v Speaker 7>term politicized, you know, into political philosophies, but you know

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<v Speaker 7>it's about understanding the coupit of markets and the risk

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<v Speaker 7>associated with it with additional information, right in terms of

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<v Speaker 7>non financial information as you know.

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<v Speaker 4>Well.

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<v Speaker 7>Secondly, unfortunately, we call them ratings, and we have a

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<v Speaker 7>metric system that is similar to credit ratings. So a

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<v Speaker 7>lot of people think that there has to be convergence

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<v Speaker 7>of the ratings, just like credit ratings. Of convergence where

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<v Speaker 7>credit ratings are your dimensional. It's about cash flows and

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<v Speaker 7>the stability of the cash flows. So how far can

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<v Speaker 7>you be in different people?

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<v Speaker 5>Right?

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<v Speaker 7>In terms of the rating, ESG measures a huge number

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<v Speaker 7>of various things, so it's almost like Seales side opinion.

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<v Speaker 7>So therefore it's very hard to think that you're going

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<v Speaker 7>to end up with, you know, standardization of the ratings

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<v Speaker 7>because you know, my opinion not MSCI may be different

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<v Speaker 7>than our competitor's opinion. They may think that governance is

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<v Speaker 7>more important. We may think that climate is more important.

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<v Speaker 7>The key is not on the ratings. The key is

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<v Speaker 7>to make sure the quality of the data.

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<v Speaker 2>Henry Fernandez with us with the MSCI here at the

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<v Speaker 2>Earthshot Prize a Plaza Hotel.

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<v Speaker 4>David, let's talk about sort of one area in particularly

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<v Speaker 4>through voluntary carbon credit market. I know that MSCI has

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<v Speaker 4>kind of looked at the integrity of that data, rated

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<v Speaker 4>that data. How representative is that of the work that

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<v Speaker 4>you're doing when it comes to climate in particular. What

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<v Speaker 4>did you find of looking at those data in particular?

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<v Speaker 7>So, first of all, we believe strongly that voluntary carbon

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<v Speaker 7>markets have to be part of the process of the

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<v Speaker 7>risk and the portfolios of the world, and the world itself,

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<v Speaker 7>you know, every airplace else we go markets serve a

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<v Speaker 7>function of transferring value and transferring risk and in climate

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<v Speaker 7>we're going to say they don't play any function. You know,

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<v Speaker 7>it's not it's.

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<v Speaker 5>Crazy to think that they want.

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<v Speaker 7>The issue is how do we build integrity and you

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<v Speaker 7>know and understanding that what you buy is what you

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<v Speaker 7>thought you were buying and all of that. So we

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<v Speaker 7>have come up with ratings. We have four thousand projects

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<v Speaker 7>right now that we're rating. We just announced that last week,

0:12:28.920 --> 0:12:31.880
<v Speaker 7>and we're going to bring more integrity, more data and quality.

0:12:31.920 --> 0:12:35.120
<v Speaker 2>How are you rating something in Chengdu, China? Explain to

0:12:35.200 --> 0:12:40.200
<v Speaker 2>me the dating data veracity we can bring to the

0:12:40.360 --> 0:12:46.120
<v Speaker 2>distrust around what China is doing in carbon management and

0:12:46.280 --> 0:12:49.960
<v Speaker 2>coal management. Are you optimistic that we can get a

0:12:50.000 --> 0:12:50.599
<v Speaker 2>handle on that?

0:12:51.160 --> 0:12:53.520
<v Speaker 7>Well, I was just in chang Dou, China a couple

0:12:53.640 --> 0:12:55.320
<v Speaker 7>of months ago to begin with.

0:12:55.480 --> 0:12:56.600
<v Speaker 5>But important did you.

0:12:56.600 --> 0:12:58.800
<v Speaker 8>Go see the pandas absolutely good?

0:13:00.320 --> 0:13:01.600
<v Speaker 5>A number one thing we've learned from.

0:13:03.360 --> 0:13:08.199
<v Speaker 7>And but it's not different that how we how we

0:13:08.400 --> 0:13:12.600
<v Speaker 7>classify countries, how we classify the ESGO companies, you know,

0:13:12.840 --> 0:13:15.000
<v Speaker 7>how we so how we look at carbony, so we

0:13:15.040 --> 0:13:19.560
<v Speaker 7>collect an enormous amount of data from independent sources, and

0:13:19.600 --> 0:13:23.880
<v Speaker 7>then we sort of package it into a classification system

0:13:23.920 --> 0:13:26.520
<v Speaker 7>of the various sources, and then you know, we create the.

0:13:26.559 --> 0:13:29.160
<v Speaker 8>Radio for our American audience coast to coast.

0:13:29.240 --> 0:13:32.320
<v Speaker 2>Thank you this morning for listening and tuning in on

0:13:32.360 --> 0:13:36.680
<v Speaker 2>YouTube as well. There's a belief here that China is cheating.

0:13:37.520 --> 0:13:42.360
<v Speaker 2>Does MSc I have the data amount or veracity to

0:13:42.480 --> 0:13:44.560
<v Speaker 2>say that China is or is not.

0:13:44.640 --> 0:13:46.959
<v Speaker 8>Cheating or any other countries for that matter.

0:13:47.880 --> 0:13:50.480
<v Speaker 7>Well, I mean they could be cheating in many different aspects,

0:13:50.520 --> 0:13:55.720
<v Speaker 7>you know, obviously, but in our case, we have incredible

0:13:55.800 --> 0:13:59.720
<v Speaker 7>norse sources of independent data, you know, the the global press,

0:14:00.120 --> 0:14:05.360
<v Speaker 7>the local press. Sometimes it is obviously control to find

0:14:05.400 --> 0:14:08.559
<v Speaker 7>independent sources and verify those sources, like in the newspaper

0:14:08.559 --> 0:14:12.439
<v Speaker 7>would to understand what is the nature of the climate

0:14:12.480 --> 0:14:14.760
<v Speaker 7>emissions of a company, what is the nature of ESG,

0:14:15.000 --> 0:14:16.400
<v Speaker 7>what is the nature of you know, in.

0:14:16.320 --> 0:14:17.920
<v Speaker 5>The west of China and all of that.

0:14:18.040 --> 0:14:21.920
<v Speaker 7>And it doesn't make us popular in China necessarily, but

0:14:22.120 --> 0:14:25.520
<v Speaker 7>we have an independent view and an unbiased view, and

0:14:25.560 --> 0:14:28.160
<v Speaker 7>that's how we rate everything, you know, including in China, right.

0:14:28.160 --> 0:14:32.360
<v Speaker 7>But it's not different than Indonesia sometimes no different than Nigeria,

0:14:32.560 --> 0:14:34.160
<v Speaker 7>no different than Mexico and the like.

0:14:35.080 --> 0:14:37.720
<v Speaker 4>The last question here, just given your perspective having traveled

0:14:37.720 --> 0:14:39.920
<v Speaker 4>to the bamboo for us and trained to do and elsewhere,

0:14:40.360 --> 0:14:42.840
<v Speaker 4>what don't we understand about emerging markets today? So we're

0:14:42.920 --> 0:14:46.040
<v Speaker 4>coming out of the pandemic as we see the world

0:14:46.080 --> 0:14:49.400
<v Speaker 4>reopening again, what are people misunderstanding or not understanding about

0:14:49.400 --> 0:14:49.880
<v Speaker 4>the health of.

0:14:49.920 --> 0:14:52.880
<v Speaker 7>First of all, emergent market is a catch all, yes, right,

0:14:52.960 --> 0:14:55.840
<v Speaker 7>so you have to then break it down into you know,

0:14:56.200 --> 0:15:00.080
<v Speaker 7>commodity exporting markets, consumer markets, and markets that don't have

0:15:00.120 --> 0:15:01.560
<v Speaker 7>a lot of competitive advantages.

0:15:01.640 --> 0:15:01.800
<v Speaker 5>Right.

0:15:02.640 --> 0:15:07.120
<v Speaker 7>Secondly is emerging markets are where the demographics you know,

0:15:07.160 --> 0:15:09.480
<v Speaker 7>growth is in the world. They have a lot of

0:15:09.480 --> 0:15:11.960
<v Speaker 7>problems obviously, you know the emerging markets is where the

0:15:12.000 --> 0:15:15.320
<v Speaker 7>climate problem will be the biggest because they don't have

0:15:15.320 --> 0:15:18.880
<v Speaker 7>a lot of resources, but they also present significant opportunities

0:15:18.920 --> 0:15:21.560
<v Speaker 7>you know, in the world. So there is a little

0:15:21.560 --> 0:15:25.000
<v Speaker 7>bit of too much of a glossover, you know, merging.

0:15:24.760 --> 0:15:27.160
<v Speaker 4>Market attaps needs to you need to go more.

0:15:26.920 --> 0:15:30.280
<v Speaker 7>In depth into each category and understand Brazil is different

0:15:30.280 --> 0:15:31.560
<v Speaker 7>than Turkey, different than China.

0:15:32.360 --> 0:15:35.320
<v Speaker 2>Thank you so much. I'd like to continue this conversation.

0:15:35.880 --> 0:15:37.080
<v Speaker 4>Thank you for how I make Yeah.

0:15:36.920 --> 0:15:39.600
<v Speaker 2>We'd love to see you over at Bloomberg. Henny Fernandez

0:15:39.600 --> 0:15:47.200
<v Speaker 2>with us here with the ms CI on the politics

0:15:47.200 --> 0:15:49.560
<v Speaker 2>of the moment. There's no one better than David Gerr

0:15:49.600 --> 0:15:51.240
<v Speaker 2>to be looking state by state.

0:15:51.760 --> 0:15:52.280
<v Speaker 5>So when you.

0:15:52.240 --> 0:15:55.560
<v Speaker 2>Slice in die fifty states for the selection of November fifth,

0:15:55.840 --> 0:15:59.720
<v Speaker 2>there's no question Colorado can be front and center with.

0:15:59.720 --> 0:16:02.720
<v Speaker 8>A really rich and interesting politics.

0:16:02.800 --> 0:16:05.880
<v Speaker 9>I like the ballot that the Governor of Colorado put

0:16:05.920 --> 0:16:09.400
<v Speaker 9>as a ballot initiative, which is to bring back Tullagis

0:16:09.400 --> 0:16:12.960
<v Speaker 9>in Boulder, Colorado. The shutting down of Tulagi's as a

0:16:13.000 --> 0:16:15.120
<v Speaker 9>club was a national scandal.

0:16:15.160 --> 0:16:16.800
<v Speaker 2>I hope you can bring Tulagi's back.

0:16:17.080 --> 0:16:19.440
<v Speaker 4>We'll get into that. We'll let Tom Wax nostalgic about

0:16:19.440 --> 0:16:21.480
<v Speaker 4>his time at the Sink, his time on the hill.

0:16:21.480 --> 0:16:24.360
<v Speaker 4>Maybe we'll talk about Tom's tavern on Pearl Street as well.

0:16:25.000 --> 0:16:26.960
<v Speaker 4>But we're here at the Earth Shot Summit at the

0:16:26.960 --> 0:16:30.360
<v Speaker 4>Plaza Hotel on this Tuesday morning with us now the

0:16:30.400 --> 0:16:32.840
<v Speaker 4>forty third governor of the State of Colorado, Jared Poulis,

0:16:33.160 --> 0:16:35.160
<v Speaker 4>who is of course a supporter of and a surrogate

0:16:35.160 --> 0:16:38.280
<v Speaker 4>for the Harris Walls campaign. And Governor Paul is great

0:16:38.280 --> 0:16:39.480
<v Speaker 4>to speak with you. And I got to start with

0:16:39.520 --> 0:16:41.040
<v Speaker 4>what has been in the news. We talked about it

0:16:41.080 --> 0:16:44.359
<v Speaker 4>just a moment ago. That is the degree to which Aurora, Colorado,

0:16:44.400 --> 0:16:46.600
<v Speaker 4>has been in the news. And I saw an interview

0:16:46.600 --> 0:16:50.400
<v Speaker 4>on KUSA on nine news in Colorado, your former congressional colleague,

0:16:50.440 --> 0:16:53.680
<v Speaker 4>Mike Kaufman, now the mayor of that city, evincing a

0:16:53.760 --> 0:16:56.040
<v Speaker 4>kind of unease as he was asked about whether he

0:16:56.040 --> 0:16:58.600
<v Speaker 4>would stand by former President Trump as he came to

0:16:58.680 --> 0:17:01.680
<v Speaker 4>Aurora for a row to address what he's been talking

0:17:01.720 --> 0:17:03.840
<v Speaker 4>about over and over again. That is what's really an

0:17:03.840 --> 0:17:07.320
<v Speaker 4>apparition here. The dangers, the dangers as he describes them,

0:17:07.400 --> 0:17:10.399
<v Speaker 4>Venezuelan gangs in that city, give us a sense of

0:17:10.400 --> 0:17:13.040
<v Speaker 4>what's really happening on the ground there in Aurora.

0:17:13.080 --> 0:17:15.440
<v Speaker 1>Well, I mean, the way the former president talks about

0:17:15.440 --> 0:17:18.080
<v Speaker 1>it is frankly one of the reasons he's so unpopular here.

0:17:18.160 --> 0:17:20.919
<v Speaker 1>I mean, Aurora is a thriving Auroras, a thriving city.

0:17:21.520 --> 0:17:25.800
<v Speaker 1>I was there last week. Most residents are are, you know,

0:17:25.880 --> 0:17:28.240
<v Speaker 1>enjoy living in one of our most culturally diversities in

0:17:28.280 --> 0:17:30.879
<v Speaker 1>the state. Violent crime has been down two years in

0:17:30.920 --> 0:17:33.639
<v Speaker 1>a Row car thefts are way down two years in

0:17:33.680 --> 0:17:36.080
<v Speaker 1>a row. They have a new police chief. We've been

0:17:36.119 --> 0:17:37.960
<v Speaker 1>working with them on law enforcement for a number of

0:17:37.960 --> 0:17:40.760
<v Speaker 1>different years. So I mean, that's that's the reality in Aurora.

0:17:41.240 --> 0:17:43.160
<v Speaker 1>And then you have somebody talking about it like it's

0:17:43.160 --> 0:17:46.200
<v Speaker 1>some alternate reality place in Colorado and just sort of

0:17:46.240 --> 0:17:47.760
<v Speaker 1>roll our eyes and say, that's not us.

0:17:48.119 --> 0:17:50.359
<v Speaker 4>Governor. We look at the latest polling, which has gotten

0:17:50.400 --> 0:17:52.720
<v Speaker 4>pretty granular, especially on the state by state level, looking

0:17:52.760 --> 0:17:55.600
<v Speaker 4>at the issues that matter most to voters, and chief

0:17:55.600 --> 0:17:57.280
<v Speaker 4>among them in the latest set of polls we've gotten

0:17:57.320 --> 0:18:00.280
<v Speaker 4>has been the economy has been inflation. What are you

0:18:00.280 --> 0:18:03.639
<v Speaker 4>hearing from Coloraden's about that? And what more does the

0:18:03.680 --> 0:18:06.320
<v Speaker 4>ticket you support need to do to make the case

0:18:06.400 --> 0:18:08.640
<v Speaker 4>that they're going to make life better for those who

0:18:08.680 --> 0:18:12.320
<v Speaker 4>are still struggling, still dealing with the effects of high

0:18:12.359 --> 0:18:13.680
<v Speaker 4>inflation and higher prices.

0:18:14.160 --> 0:18:16.480
<v Speaker 1>Certainly high costs of inflation are one of the big

0:18:16.560 --> 0:18:19.280
<v Speaker 1>challenges we face, and I think that the type of

0:18:19.320 --> 0:18:23.080
<v Speaker 1>thing that we saw from the Wharton School pen came

0:18:23.119 --> 0:18:26.400
<v Speaker 1>out and said that Donald Trump's big spending plan would

0:18:26.400 --> 0:18:29.600
<v Speaker 1>increase the deficit more than two times more than Kamala

0:18:29.680 --> 0:18:32.720
<v Speaker 1>Harris's plan. People understand that this kind of big spending

0:18:32.760 --> 0:18:35.879
<v Speaker 1>mentality is inflationary. That's more of what the former president

0:18:35.920 --> 0:18:38.160
<v Speaker 1>brought last time he was president. That's what he's likely

0:18:38.240 --> 0:18:41.360
<v Speaker 1>to bring again. I think Kamala Harris has a responsible

0:18:41.400 --> 0:18:46.280
<v Speaker 1>plan and encourages entrepreneurship, innovation, really leans into the opportunity

0:18:46.359 --> 0:18:48.760
<v Speaker 1>economy from the bottom up and doesn't rely on big

0:18:48.800 --> 0:18:50.240
<v Speaker 1>government spending like Donald Trump.

0:18:50.840 --> 0:18:54.080
<v Speaker 2>Governor, you are living there for decades, way back before

0:18:54.119 --> 0:18:55.560
<v Speaker 2>this fractious politics.

0:18:55.960 --> 0:18:58.200
<v Speaker 8>The Latino vote and the turnout.

0:18:58.560 --> 0:19:01.720
<v Speaker 2>What is your prediction for the size of the Latino

0:19:01.840 --> 0:19:05.960
<v Speaker 2>vote in Colorado, and particularly the youth vote that many

0:19:06.080 --> 0:19:09.040
<v Speaker 2>say finds an affection with the former president.

0:19:09.320 --> 0:19:12.800
<v Speaker 1>There's a lot more excitement now with Kamala Harris's the nominee.

0:19:12.840 --> 0:19:15.199
<v Speaker 1>I think this was a legitimate problem when Joe Biden

0:19:15.280 --> 0:19:18.760
<v Speaker 1>was talking about running again, especially among the younger vote.

0:19:19.000 --> 0:19:21.080
<v Speaker 1>I think we now have a candidate that really speaks

0:19:21.119 --> 0:19:23.880
<v Speaker 1>to a new generation, to their aspirations, to their goals.

0:19:24.359 --> 0:19:26.000
<v Speaker 1>And I'm getting a lot of assignment, whether I'm at

0:19:26.040 --> 0:19:30.480
<v Speaker 1>our campuses at CU and DU and CSU, or whether

0:19:30.520 --> 0:19:34.159
<v Speaker 1>it's at our community colleges or in stores and on restaurants.

0:19:34.359 --> 0:19:36.800
<v Speaker 1>I think people really get that she is an agenda

0:19:36.840 --> 0:19:39.359
<v Speaker 1>that works for them. Our Latino population in Colorado is

0:19:39.359 --> 0:19:41.760
<v Speaker 1>incredibly diverse, right. We have people that have been families

0:19:41.760 --> 0:19:43.640
<v Speaker 1>that have been here hundreds of years. We have families

0:19:43.640 --> 0:19:46.000
<v Speaker 1>that arrive here in a generation or two ago. Like

0:19:46.040 --> 0:19:50.560
<v Speaker 1>any group, there's a broad political diversity among them. Overwhelmingly,

0:19:50.600 --> 0:19:54.040
<v Speaker 1>of course, Latino voters, just like all Colorado's, are supporting

0:19:54.080 --> 0:19:56.400
<v Speaker 1>Kamala Harris and what she offers to bring down inflation,

0:19:56.760 --> 0:19:59.040
<v Speaker 1>secure our border, and help grow opportunity.

0:19:59.400 --> 0:20:02.480
<v Speaker 4>Gunnary, You've got to know the vice president's running made

0:20:02.480 --> 0:20:05.119
<v Speaker 4>through his service and the Democratic Governor's Association. Imagine you've

0:20:05.119 --> 0:20:06.880
<v Speaker 4>gotten know him well over the course of that. Tom

0:20:06.920 --> 0:20:09.680
<v Speaker 4>asked me yesterday on air, so what he can bring

0:20:09.720 --> 0:20:13.080
<v Speaker 4>to states like Arizona and Colorado As he makes this

0:20:13.119 --> 0:20:15.600
<v Speaker 4>way along that campaign trail, it's bound to get busier.

0:20:15.960 --> 0:20:17.479
<v Speaker 4>What if voters want to hear from him? What does

0:20:17.520 --> 0:20:19.600
<v Speaker 4>he offer that the vice president doesn't that the incomon

0:20:19.640 --> 0:20:22.720
<v Speaker 4>president didn't offer before him? What's he able to do

0:20:22.840 --> 0:20:26.000
<v Speaker 4>to kind of galvanize or energize the electorate there in Colorado.

0:20:26.200 --> 0:20:27.960
<v Speaker 1>So you know, Tim Walls was somebody I served with

0:20:28.000 --> 0:20:30.040
<v Speaker 1>in the United States Congress as well. This is somebody

0:20:30.080 --> 0:20:33.360
<v Speaker 1>who won a red district in the United States Congress.

0:20:33.359 --> 0:20:38.320
<v Speaker 1>How by really understanding and being authentic with people, I mean,

0:20:38.320 --> 0:20:41.480
<v Speaker 1>this is a guy who can get along with almost anybody.

0:20:41.560 --> 0:20:44.240
<v Speaker 1>He's comfortable in his own skin. He's able to hear

0:20:44.280 --> 0:20:46.840
<v Speaker 1>people where they're at and help them imagine a better

0:20:46.880 --> 0:20:49.840
<v Speaker 1>world for themselves and others. So that's really who Tim is.

0:20:49.920 --> 0:20:52.639
<v Speaker 1>And through his service to our country in the military

0:20:52.680 --> 0:20:55.359
<v Speaker 1>as a teacher, he's really put his work where his

0:20:55.440 --> 0:20:57.960
<v Speaker 1>mouth is, and people are really excited across the country

0:20:58.000 --> 0:20:59.520
<v Speaker 1>to get to know him as our next vice president.

0:21:00.000 --> 0:21:00.439
<v Speaker 5>Thank Governor.

0:21:01.000 --> 0:21:02.880
<v Speaker 8>How do you feel about the tradition?

0:21:03.040 --> 0:21:04.959
<v Speaker 2>And I'm going to go back to Ronald Reagan, who

0:21:05.040 --> 0:21:06.800
<v Speaker 2>maybe was on the right and.

0:21:06.800 --> 0:21:10.600
<v Speaker 8>Ran to the center in the days to November fifth.

0:21:10.280 --> 0:21:13.119
<v Speaker 2>Are we going to see the vice president run to

0:21:13.200 --> 0:21:17.920
<v Speaker 2>the middle and become verbally less progressive and more centrist?

0:21:18.280 --> 0:21:20.159
<v Speaker 8>Is maybe we see from Jared Pois?

0:21:20.720 --> 0:21:23.040
<v Speaker 1>Well, Look, I mean she is who she is. She

0:21:23.200 --> 0:21:25.960
<v Speaker 1>obviously evolves on issues and learns just like any of

0:21:26.040 --> 0:21:28.679
<v Speaker 1>us do. It's a different job to be a DA

0:21:28.760 --> 0:21:30.919
<v Speaker 1>It's a different job to be a senator from California.

0:21:30.920 --> 0:21:33.000
<v Speaker 1>It's a different job to be vice president, and it's

0:21:33.000 --> 0:21:35.320
<v Speaker 1>a different job to want to be the next president

0:21:35.359 --> 0:21:37.840
<v Speaker 1>of all America. And that's really what she's leading into.

0:21:38.080 --> 0:21:40.399
<v Speaker 1>She wants to be a uniter. She's the person we

0:21:40.440 --> 0:21:43.600
<v Speaker 1>need as America approaches our two hundred and fiftieth anniversary

0:21:43.880 --> 0:21:46.560
<v Speaker 1>in twenty twenty six. We don't need a nation divided.

0:21:46.600 --> 0:21:49.080
<v Speaker 1>We need a nation united, and that means somebody who

0:21:49.080 --> 0:21:52.840
<v Speaker 1>speaks to everybody. And that's why conservative Republicans, liberal Democrats,

0:21:52.920 --> 0:21:56.760
<v Speaker 1>moderates are all flocking to Takamala Harris, including former Vice

0:21:56.760 --> 0:21:57.679
<v Speaker 1>President Dick Cheney.

0:21:57.920 --> 0:22:00.119
<v Speaker 4>I'm the vice president. You say she is who she is?

0:22:00.240 --> 0:22:01.439
<v Speaker 4>I think there are a lot of people still in

0:22:01.440 --> 0:22:03.399
<v Speaker 4>this country who don't know who she is, and we

0:22:03.440 --> 0:22:05.240
<v Speaker 4>see that in the polling data as well. Is she

0:22:05.280 --> 0:22:08.400
<v Speaker 4>doing herself with the service by not doing more interviews,

0:22:08.480 --> 0:22:11.600
<v Speaker 4>doing more one on ones with reporters? How do you

0:22:11.640 --> 0:22:13.359
<v Speaker 4>respond to that. It's great to speak with you this morning,

0:22:13.400 --> 0:22:15.800
<v Speaker 4>to have the opportunity to do so, of course, but

0:22:16.280 --> 0:22:18.000
<v Speaker 4>is she missing an opportunity by not doing more of

0:22:18.000 --> 0:22:18.520
<v Speaker 4>that her self?

0:22:18.560 --> 0:22:21.800
<v Speaker 1>Do you think she's a thoughtful, diligent leader who studies

0:22:21.840 --> 0:22:25.160
<v Speaker 1>the issues, and she's a prosecutor, put criminals behind bars,

0:22:25.160 --> 0:22:27.160
<v Speaker 1>stared them in the face. Nothing's harder than that.

0:22:27.480 --> 0:22:27.600
<v Speaker 7>Oh.

0:22:27.640 --> 0:22:29.440
<v Speaker 1>Look, she is doing more interviews and I'm sure she'll

0:22:29.440 --> 0:22:32.560
<v Speaker 1>do even more going forward. She's working very very hard

0:22:32.600 --> 0:22:34.879
<v Speaker 1>on the campaign trail, doing far more campaign events and

0:22:34.920 --> 0:22:37.120
<v Speaker 1>outreaching her opponent. I'm going to I think that'll help

0:22:37.160 --> 0:22:38.320
<v Speaker 1>carry the day in November.

0:22:38.720 --> 0:22:41.840
<v Speaker 2>Governor, thank you so much for joining Bloomberg this morning.

0:22:42.000 --> 0:22:46.440
<v Speaker 2>The governor of Colorado, Jared Poles, greatly appreciated.

0:22:45.880 --> 0:22:58.280
<v Speaker 8>Her advantage New Haven. If you're in New Haven and.

0:22:58.240 --> 0:23:01.760
<v Speaker 2>You're double E electrical engineer, you spend a lot of

0:23:01.840 --> 0:23:03.320
<v Speaker 2>time at Sally's Pizza.

0:23:03.480 --> 0:23:06.479
<v Speaker 8>I mean, it's just no other way to put it.

0:23:06.560 --> 0:23:10.240
<v Speaker 2>You're grinding, you're cramming differential equations and the rest of it.

0:23:10.440 --> 0:23:12.960
<v Speaker 2>I assume you took the Wheatstone Bridge to Sally's.

0:23:12.960 --> 0:23:15.320
<v Speaker 6>What was it like Double E at.

0:23:15.200 --> 0:23:18.240
<v Speaker 2>Yale in a school acclaimed for liberal arts.

0:23:18.440 --> 0:23:19.440
<v Speaker 6>How lonely were you?

0:23:19.640 --> 0:23:22.000
<v Speaker 10>We spent a lot of time in a basement away

0:23:22.000 --> 0:23:23.040
<v Speaker 10>from sunlight.

0:23:23.760 --> 0:23:26.240
<v Speaker 2>Am Trepani with us? I heard this morning on what

0:23:26.320 --> 0:23:29.920
<v Speaker 2>he's doing in this innovation. Explain to me your innovation

0:23:30.119 --> 0:23:31.240
<v Speaker 2>project right now today.

0:23:31.720 --> 0:23:33.879
<v Speaker 10>Yeah, it's great to be with you. So I'm the

0:23:33.880 --> 0:23:37.600
<v Speaker 10>CEO of atlas Ai, Wh're a Palo Alto, California based

0:23:37.640 --> 0:23:42.240
<v Speaker 10>startup that is building models based on geospatial data. So

0:23:42.280 --> 0:23:46.040
<v Speaker 10>geospatial is data that has a location or a geographic

0:23:46.080 --> 0:23:50.920
<v Speaker 10>element associated with it. So our models aim to understand

0:23:50.960 --> 0:23:53.880
<v Speaker 10>and anticipate what the future of the planet is likely

0:23:53.920 --> 0:23:55.960
<v Speaker 10>to look like, where people are likely to live in

0:23:56.000 --> 0:23:59.679
<v Speaker 10>the future, how economy is likely to evolve and adapt,

0:23:59.720 --> 0:24:04.000
<v Speaker 10>and really to macro factors like conflict or climate change.

0:24:04.480 --> 0:24:06.879
<v Speaker 10>And we aim to help international organizations.

0:24:07.000 --> 0:24:09.120
<v Speaker 2>I would go to climate and flooding today, but this

0:24:09.240 --> 0:24:12.199
<v Speaker 2>morning I have to go to conflict. As you consider

0:24:12.320 --> 0:24:15.720
<v Speaker 2>three wars Ukraine, Gaza and North to Lebanon as well,

0:24:15.960 --> 0:24:19.840
<v Speaker 2>what is your value add to people assessing the conflict

0:24:19.880 --> 0:24:20.520
<v Speaker 2>in the levant?

0:24:20.720 --> 0:24:24.760
<v Speaker 10>So there's immediate elements of monitoring the impact of the

0:24:24.800 --> 0:24:29.800
<v Speaker 10>conflict on the environment itself, but also on communities. How

0:24:29.800 --> 0:24:33.640
<v Speaker 10>are people being displaced forced to move from the places

0:24:33.680 --> 0:24:36.280
<v Speaker 10>that they live because of the nature of the conflict.

0:24:36.920 --> 0:24:39.640
<v Speaker 10>But more so than that, some of the interesting factors

0:24:39.680 --> 0:24:43.119
<v Speaker 10>are how is the conflict impacting the agricultural industry in

0:24:43.240 --> 0:24:46.080
<v Speaker 10>Ukraine and what global implications does that have on supply

0:24:46.200 --> 0:24:49.960
<v Speaker 10>chains that flow from this critical area of agriculture.

0:24:50.280 --> 0:24:53.119
<v Speaker 4>Talk about your role in the broader AI sector if

0:24:53.119 --> 0:24:54.960
<v Speaker 4>we can christen that or call it that now and

0:24:55.040 --> 0:24:57.320
<v Speaker 4>we talk a lot about a handful of companies in particularly,

0:24:57.320 --> 0:24:59.720
<v Speaker 4>talk a lot about chip manufacturing as well. As you

0:25:00.000 --> 0:25:02.679
<v Speaker 4>look at the sort of ncency evolution, early evolution of it,

0:25:02.720 --> 0:25:04.160
<v Speaker 4>where are we in that process now?

0:25:05.160 --> 0:25:08.240
<v Speaker 10>So not surprising. A lot of the early focus has

0:25:08.320 --> 0:25:11.840
<v Speaker 10>been on modalities of information that we work with almost

0:25:11.880 --> 0:25:18.040
<v Speaker 10>every day, text, video, imagery, tom's phone, Tom's phone, where

0:25:18.080 --> 0:25:22.040
<v Speaker 10>to find pizza and Newhagen. Yes, some of the interesting

0:25:22.119 --> 0:25:24.679
<v Speaker 10>next set of questions that we're dealing with relate to

0:25:24.720 --> 0:25:28.199
<v Speaker 10>different types of data. How do we help organizations understand

0:25:28.560 --> 0:25:30.719
<v Speaker 10>the information that they have access to that may not

0:25:30.760 --> 0:25:34.240
<v Speaker 10>be as neatly structured in a document or in an

0:25:34.280 --> 0:25:37.920
<v Speaker 10>image file like Satellite imagery is a good example. There

0:25:37.960 --> 0:25:41.440
<v Speaker 10>is an immense amount of information about economic activity, about

0:25:41.520 --> 0:25:45.119
<v Speaker 10>the climate, about other dimensions of change that's happening on

0:25:45.119 --> 0:25:48.320
<v Speaker 10>the planet, and we have satellite images that are capturing

0:25:48.359 --> 0:25:51.080
<v Speaker 10>every square foot of the planet every single day. Now,

0:25:51.840 --> 0:25:55.000
<v Speaker 10>using AI gives us a real time lens on what

0:25:55.240 --> 0:25:57.840
<v Speaker 10>change is unfolding across the planet in a way that

0:25:58.200 --> 0:26:02.159
<v Speaker 10>some of the other other aspects of AI are not

0:26:02.520 --> 0:26:03.639
<v Speaker 10>able to capture today.

0:26:03.760 --> 0:26:05.240
<v Speaker 4>I think that so many of us glam on to

0:26:05.359 --> 0:26:08.880
<v Speaker 4>kind of the Aeschucks factor of the modality that you're

0:26:08.920 --> 0:26:11.280
<v Speaker 4>talking about, how it can affect our lives individually. Do

0:26:11.359 --> 0:26:14.159
<v Speaker 4>you think that people, as if yet comprehend kind of

0:26:14.200 --> 0:26:17.200
<v Speaker 4>the wider implications of what AI will be able to offer, deed,

0:26:17.200 --> 0:26:20.000
<v Speaker 4>what it may offer right now they're.

0:26:19.840 --> 0:26:22.080
<v Speaker 10>Starting to, in part because it's on our phone and

0:26:22.119 --> 0:26:26.280
<v Speaker 10>we have access to magical technology that allows us to

0:26:26.320 --> 0:26:29.920
<v Speaker 10>do things that we couldn't do yesterday. The reality is

0:26:29.920 --> 0:26:32.639
<v Speaker 10>is that a lot of this is just scratching the

0:26:32.680 --> 0:26:34.879
<v Speaker 10>surface of what we're seeing come out of the labs

0:26:34.920 --> 0:26:37.919
<v Speaker 10>in Stanford and Yale and other schools in terms of

0:26:38.240 --> 0:26:42.399
<v Speaker 10>not just how individual models, but how models that can reason,

0:26:42.520 --> 0:26:45.760
<v Speaker 10>that can engage with the world are able to now

0:26:46.440 --> 0:26:49.680
<v Speaker 10>start to enhance the productivity of companies and organizations.

0:26:49.760 --> 0:26:54.400
<v Speaker 2>You are hugely qualified to answer a question. It's understanding,

0:26:57.040 --> 0:27:02.760
<v Speaker 2>But Microsoft and Constellation and three Island fine the thermodynamics

0:27:02.760 --> 0:27:06.159
<v Speaker 2>of all this AI chit chat in the need for electricity.

0:27:06.600 --> 0:27:09.359
<v Speaker 2>To me, there's almost a free lunch to it. What

0:27:09.440 --> 0:27:12.040
<v Speaker 2>will be the cost of having to generate all that

0:27:12.119 --> 0:27:14.879
<v Speaker 2>electricity to power your world?

0:27:15.160 --> 0:27:17.760
<v Speaker 10>Well, I think there's probably two questions in bed there.

0:27:17.800 --> 0:27:20.320
<v Speaker 10>What's the cost and what's the sustainability of being able

0:27:20.359 --> 0:27:22.600
<v Speaker 10>to do so? And the good news is that from

0:27:22.640 --> 0:27:27.159
<v Speaker 10>a sustainability angle, we are now seeing the acceleration of

0:27:27.200 --> 0:27:31.240
<v Speaker 10>new technologies like solar and wind, but also hydrogen and

0:27:31.280 --> 0:27:36.280
<v Speaker 10>other newer energy sources that are going to be prevalent

0:27:36.400 --> 0:27:38.600
<v Speaker 10>in in the next couple of decades. So the energy

0:27:38.640 --> 0:27:42.840
<v Speaker 10>demand will be significant, but I'm also very optimistic that

0:27:43.240 --> 0:27:47.080
<v Speaker 10>this energy will be powered by renewable, sustainable sources of energy.

0:27:47.200 --> 0:27:50.080
<v Speaker 2>What do the seven big stocks? What do they get

0:27:50.200 --> 0:27:52.640
<v Speaker 2>from you? When you talk to Nvidio, when you talk

0:27:53.000 --> 0:27:56.440
<v Speaker 2>to Microsoft? How do they listen to what atlas Ai

0:27:56.600 --> 0:27:57.040
<v Speaker 2>is doing.

0:27:57.359 --> 0:27:59.680
<v Speaker 10>So I'll give you a specific example, and that where

0:27:59.760 --> 0:28:02.600
<v Speaker 10>we partner with Google Cloud extensively. Our technology is built

0:28:02.640 --> 0:28:05.800
<v Speaker 10>on Google Cloud and we're a member of a sustainability

0:28:05.800 --> 0:28:09.720
<v Speaker 10>ecosystem within Google Cloud that's focused on questions of how

0:28:09.720 --> 0:28:14.800
<v Speaker 10>do we help companies advance their sustainability priorities. Many of

0:28:15.320 --> 0:28:18.240
<v Speaker 10>Google has Gemini they have one of the leading large

0:28:18.280 --> 0:28:22.480
<v Speaker 10>language models, but many of their customers are asking a

0:28:22.520 --> 0:28:27.280
<v Speaker 10>whole array of questions related to how does air Bus

0:28:27.359 --> 0:28:32.600
<v Speaker 10>think about anticipating the demand of air travel in Indonesia

0:28:32.640 --> 0:28:35.800
<v Speaker 10>in the future, And so there are questions that language

0:28:35.800 --> 0:28:38.360
<v Speaker 10>models are not by themselves able to answer that at

0:28:38.400 --> 0:28:39.640
<v Speaker 10>let's a I can at.

0:28:39.520 --> 0:28:42.440
<v Speaker 2>Let's say, I question, how about that midtown traffic this

0:28:42.600 --> 0:28:46.960
<v Speaker 2>istout getting over to the lunch.

0:28:47.440 --> 0:28:48.720
<v Speaker 10>I wish I could have told you how to get

0:28:48.720 --> 0:28:49.880
<v Speaker 10>to the east side last night.

0:28:51.960 --> 0:28:54.040
<v Speaker 4>A Let me just stick with infrastructure a little bit here,

0:28:54.040 --> 0:28:55.640
<v Speaker 4>and we hear from Jensen Kwang about, you know, how

0:28:55.640 --> 0:28:57.680
<v Speaker 4>he deploys the chips that his company is making, and

0:28:57.720 --> 0:29:00.880
<v Speaker 4>there's such demand for them, which comes to shove. Is

0:29:00.920 --> 0:29:02.960
<v Speaker 4>that a difficulty for folks like you who are starting

0:29:03.040 --> 0:29:06.719
<v Speaker 4>these businesses in this space, just getting access to the infrastructure,

0:29:06.720 --> 0:29:08.960
<v Speaker 4>getting the chips, to put it bluntly, getting the access

0:29:09.000 --> 0:29:11.280
<v Speaker 4>to these data centers. How much of that is yet

0:29:11.360 --> 0:29:13.480
<v Speaker 4>a hurdle to the kind of development that you'd like

0:29:13.520 --> 0:29:14.120
<v Speaker 4>to see.

0:29:14.640 --> 0:29:16.840
<v Speaker 10>It's a question that we constantly have to face because

0:29:16.880 --> 0:29:19.040
<v Speaker 10>not only are we thinking about the current generation A model,

0:29:19.040 --> 0:29:21.920
<v Speaker 10>but we're also now thinking about next year's generation. The

0:29:21.960 --> 0:29:25.880
<v Speaker 10>pace of training new models is accelerating at such a

0:29:25.880 --> 0:29:27.520
<v Speaker 10>pace that you need to be thinking one or two

0:29:27.520 --> 0:29:31.040
<v Speaker 10>generations down the line. And with each generation the compute

0:29:31.120 --> 0:29:36.920
<v Speaker 10>requirements are increasingly increasing exponentially. I'll say that the last

0:29:36.920 --> 0:29:40.040
<v Speaker 10>few years are likely tougher than the next few years

0:29:40.080 --> 0:29:43.680
<v Speaker 10>will be. The supply chains are starting to work themselves out.

0:29:44.440 --> 0:29:47.160
<v Speaker 10>Nvidia and other companies have been able to now adapt.

0:29:47.400 --> 0:29:50.320
<v Speaker 10>New generations are coming out that are more efficient, so

0:29:51.040 --> 0:29:53.560
<v Speaker 10>that's not one of the elements that we worry most

0:29:53.560 --> 0:29:55.440
<v Speaker 10>about when we think about the next few years growth

0:29:55.480 --> 0:29:56.240
<v Speaker 10>of the business.

0:29:56.360 --> 0:29:58.560
<v Speaker 2>So wonderful come to our world headquarters sometime. I'd love

0:29:58.600 --> 0:30:01.440
<v Speaker 2>to talk to you from our studios. Am Terror Parne

0:30:01.440 --> 0:30:09.360
<v Speaker 2>with us with alis Ai, finally for Global Wall Street.

0:30:09.920 --> 0:30:13.320
<v Speaker 2>An important conversation you think of the Securities and Exchange

0:30:13.320 --> 0:30:18.360
<v Speaker 2>Commission in America f s A in London. How about

0:30:18.360 --> 0:30:25.160
<v Speaker 2>the International Organization of Securities Commissions is OSCO ISCO IOSCO.

0:30:25.320 --> 0:30:28.000
<v Speaker 2>Thank you joining us from my Oscar and Brussels. With

0:30:28.160 --> 0:30:32.960
<v Speaker 2>all the headaches of regulation and cryptocurrencies. Future Jean Paul

0:30:33.000 --> 0:30:35.720
<v Speaker 2>Survey joins us this morning. Wonderful to have you with us.

0:30:36.400 --> 0:30:41.360
<v Speaker 2>Different presidential candidates are saying crypto is part of a

0:30:41.440 --> 0:30:47.240
<v Speaker 2>legitimate American political and economic future. Where does that take

0:30:47.360 --> 0:30:52.200
<v Speaker 2>our understanding of crypto if we see politicians talking it up.

0:30:52.400 --> 0:30:56.120
<v Speaker 11>Yeah, by spot of the political legitimacy debate, it's about innovation.

0:30:56.600 --> 0:31:00.360
<v Speaker 11>We have Securities Markets Regulator. I'm not against imidation, but

0:31:00.480 --> 0:31:03.360
<v Speaker 11>all job is to ensure that there is stress, that

0:31:03.440 --> 0:31:06.000
<v Speaker 11>there are no accidents. And due to the fact that

0:31:06.040 --> 0:31:08.680
<v Speaker 11>we know that most of the time, in fact, we

0:31:08.840 --> 0:31:12.040
<v Speaker 11>have a business developed by cross border I would say

0:31:12.120 --> 0:31:15.640
<v Speaker 11>crypto asset provider, we need to be an iOS come

0:31:15.720 --> 0:31:19.480
<v Speaker 11>means in fact, the Global Membership Organization we have one

0:31:19.600 --> 0:31:22.600
<v Speaker 11>hundred and thirty jo addiction. It means that my coroeague

0:31:22.640 --> 0:31:25.280
<v Speaker 11>and members are involving in the supervision of ninety five

0:31:25.320 --> 0:31:28.360
<v Speaker 11>percent of the financial like the US SEC and usc FTC.

0:31:28.840 --> 0:31:30.640
<v Speaker 11>So we need to be there and that's what we did.

0:31:30.720 --> 0:31:34.440
<v Speaker 11>We endorsed last year a toolkit in order to help

0:31:34.520 --> 0:31:37.760
<v Speaker 11>all job addiction to have an appropriate supervision. It's not

0:31:37.880 --> 0:31:40.880
<v Speaker 11>about the enforcement assets does the job of the national

0:31:41.000 --> 0:31:44.160
<v Speaker 11>agency like in the US. So we try to avoid

0:31:44.320 --> 0:31:47.000
<v Speaker 11>that there are collapses, that they are accident, that there

0:31:47.000 --> 0:31:48.600
<v Speaker 11>are problem about the quality.

0:31:48.920 --> 0:31:50.840
<v Speaker 5>I would say of the of the business.

0:31:50.520 --> 0:31:52.640
<v Speaker 8>There's about there's a new legitimacy lawrence.

0:31:52.720 --> 0:31:59.240
<v Speaker 2>Think of black rockets tracking up everybody else, Airbelt Tuness, Blombergers, encyclopedic. Honest,

0:31:59.400 --> 0:32:01.400
<v Speaker 2>that's all great, but how is.

0:32:01.400 --> 0:32:03.320
<v Speaker 8>The bitcoin underlying?

0:32:04.440 --> 0:32:07.800
<v Speaker 2>The Bank of International Settlements is studied so hard? Is

0:32:07.800 --> 0:32:11.480
<v Speaker 2>there an underlying value like there is to gold or

0:32:11.840 --> 0:32:14.000
<v Speaker 2>you know, what's the latest stock I had at crater?

0:32:14.160 --> 0:32:15.040
<v Speaker 6>There's something there.

0:32:15.280 --> 0:32:18.000
<v Speaker 11>That's a very difficult question. And you are for there,

0:32:18.080 --> 0:32:21.360
<v Speaker 11>of course, because it's a never ending story. All I

0:32:21.360 --> 0:32:24.920
<v Speaker 11>would say objective is to be helpful for discovery.

0:32:24.400 --> 0:32:26.200
<v Speaker 5>Price to avoid.

0:32:26.400 --> 0:32:29.120
<v Speaker 11>Let us be clear many of the accident which took

0:32:29.120 --> 0:32:31.760
<v Speaker 11>place during the crypto meet it was about the absence

0:32:32.160 --> 0:32:36.720
<v Speaker 11>of segregation of upset, something that is quite manageable, I

0:32:36.720 --> 0:32:39.320
<v Speaker 11>would say, and something that it had to be managed

0:32:39.360 --> 0:32:43.360
<v Speaker 11>for thirty years by trading, venue, stocking, change asset manager.

0:32:43.680 --> 0:32:46.240
<v Speaker 11>What we are proposing is to copy and paste this

0:32:46.360 --> 0:32:49.640
<v Speaker 11>well known principle and then to provide that for the

0:32:49.680 --> 0:32:50.720
<v Speaker 11>sake of the supersion.

0:32:50.720 --> 0:32:51.960
<v Speaker 5>When working very.

0:32:51.800 --> 0:32:54.600
<v Speaker 11>Hard with the imas, and I was very happy to

0:32:54.640 --> 0:32:57.880
<v Speaker 11>see that now the I'm start by using old toolkit.

0:32:58.240 --> 0:33:01.160
<v Speaker 11>When they performed their well known mission article for f

0:33:01.240 --> 0:33:03.200
<v Speaker 11>s UP and so it means that we are useful

0:33:03.360 --> 0:33:05.880
<v Speaker 11>and that we are working together with other global standards.

0:33:06.040 --> 0:33:07.560
<v Speaker 4>You'll forgive the phrase, but I imagine a lot of

0:33:07.560 --> 0:33:10.120
<v Speaker 4>your job is hurting cats. You're having to deal with

0:33:10.200 --> 0:33:12.480
<v Speaker 4>all of these regulatory agencies all over the world's which

0:33:12.520 --> 0:33:15.200
<v Speaker 4>have different priorities. How much unanimity is that you can

0:33:15.200 --> 0:33:17.000
<v Speaker 4>take crypto as an example and how we've seen this.

0:33:17.400 --> 0:33:19.520
<v Speaker 4>Maybe arbitrage is a good way of putting it. But

0:33:19.960 --> 0:33:22.640
<v Speaker 4>companies moving from place to place, jurisdiction to jurisdiction because

0:33:22.640 --> 0:33:25.240
<v Speaker 4>they offer different things. Are we seeing a movement toward

0:33:25.240 --> 0:33:26.840
<v Speaker 4>a more unified regulatory lands?

0:33:26.920 --> 0:33:28.440
<v Speaker 5>Yeah, well, thanks for your question.

0:33:29.480 --> 0:33:32.960
<v Speaker 11>That's maybe mycro league thought that a Belgium guy had

0:33:33.000 --> 0:33:35.280
<v Speaker 11>to be elected because the DNA of Belgium is about

0:33:35.320 --> 0:33:38.080
<v Speaker 11>Belgium compromise because we are not sure that our countries

0:33:38.120 --> 0:33:41.240
<v Speaker 11>still exist today after so we need compromise every day.

0:33:41.400 --> 0:33:42.120
<v Speaker 5>We never vote.

0:33:42.320 --> 0:33:45.080
<v Speaker 11>It's like United Nations, except that I think that we

0:33:45.120 --> 0:33:45.800
<v Speaker 11>are able to.

0:33:45.800 --> 0:33:47.120
<v Speaker 5>Take get things do OK.

0:33:48.520 --> 0:33:52.680
<v Speaker 11>So it's consensus because it's a global membership organization, and

0:33:52.720 --> 0:33:55.560
<v Speaker 11>I think that we are able to find consensus because

0:33:55.880 --> 0:33:59.280
<v Speaker 11>whenever you have global challenges, risk and ability. We are

0:33:59.280 --> 0:34:01.920
<v Speaker 11>here because some members are involved in the supersion of

0:34:02.000 --> 0:34:03.800
<v Speaker 11>ninety five percent or much of.

0:34:03.760 --> 0:34:06.360
<v Speaker 5>It of members are in fact grow and emergent market.

0:34:06.760 --> 0:34:07.240
<v Speaker 5>So when we.

0:34:07.160 --> 0:34:10.920
<v Speaker 11>Speak about crypto assets, that's a danger also for crypto

0:34:10.960 --> 0:34:14.800
<v Speaker 11>and an opportunity also for many countries in Africa.

0:34:14.920 --> 0:34:17.000
<v Speaker 5>The same for climate fans. It's cross border.

0:34:17.640 --> 0:34:21.560
<v Speaker 2>I understand that can be banking transactions, a cross water transactions,

0:34:21.960 --> 0:34:24.160
<v Speaker 2>but I still don't see out there a lot of

0:34:24.360 --> 0:34:27.920
<v Speaker 2>use of crypto in day to day transactions. Do you

0:34:28.080 --> 0:34:31.319
<v Speaker 2>envision out there while reptore will actually be a daily

0:34:31.280 --> 0:34:32.239
<v Speaker 2>to day transaction.

0:34:33.000 --> 0:34:35.160
<v Speaker 11>I think that you are right to be product. There

0:34:35.160 --> 0:34:38.880
<v Speaker 11>are many expectations. I think the first step if you

0:34:38.960 --> 0:34:41.920
<v Speaker 11>want to have confidence in crypto is to have a

0:34:42.000 --> 0:34:44.399
<v Speaker 11>solid frame at global frame, and that's what we are

0:34:44.400 --> 0:34:46.560
<v Speaker 11>doing for the time being, and we are going the

0:34:46.640 --> 0:34:49.480
<v Speaker 11>right direction because I think that all tool kit was

0:34:49.520 --> 0:34:52.160
<v Speaker 11>able to take into account what happens last year, the

0:34:52.239 --> 0:34:55.439
<v Speaker 11>crypto winter, some accident, and that's the objective of IO

0:34:55.800 --> 0:34:56.600
<v Speaker 11>to be helpful for the.

0:34:56.600 --> 0:34:59.040
<v Speaker 5>Members, like for climate finances. That's the reason why the

0:34:59.080 --> 0:35:00.000
<v Speaker 5>pleasure to be here.

0:35:00.920 --> 0:35:02.799
<v Speaker 4>Let's pull back a bit as you look at the

0:35:02.840 --> 0:35:05.319
<v Speaker 4>broader landscape, are there pockets of risk or things that

0:35:05.760 --> 0:35:07.879
<v Speaker 4>give you pause for concern at this point in time

0:35:07.920 --> 0:35:10.680
<v Speaker 4>when it comes to sort of the regulatory risk regulatory landscape,

0:35:10.719 --> 0:35:11.400
<v Speaker 4>yeh as.

0:35:11.320 --> 0:35:15.080
<v Speaker 11>Ioscop chair, I think that there are too global issue

0:35:15.480 --> 0:35:21.080
<v Speaker 11>climate finance nbify the former shadow banking climate finance. If

0:35:21.080 --> 0:35:23.440
<v Speaker 11>you are not able to speak more or less the

0:35:23.480 --> 0:35:26.839
<v Speaker 11>same language to use the same I would say, sustainty

0:35:26.920 --> 0:35:30.520
<v Speaker 11>reporting standard together data as much as possible, and that's

0:35:30.520 --> 0:35:33.600
<v Speaker 11>the reason why the initiative taken by Mike Bloomberg and

0:35:33.680 --> 0:35:37.280
<v Speaker 11>Emmanuel McCoy is going the right diction to extract data.

0:35:37.440 --> 0:35:41.239
<v Speaker 11>We will have many questions about greenwashing because green washing

0:35:41.360 --> 0:35:44.360
<v Speaker 11>means most of the time the lack of capacity to

0:35:44.440 --> 0:35:46.360
<v Speaker 11>use the same language. And that's the reason why we

0:35:46.480 --> 0:35:49.120
<v Speaker 11>endorsed last yearsb stun. It means at the end of

0:35:49.200 --> 0:35:52.879
<v Speaker 11>the day, one hundred and thirty thousand company will use

0:35:52.880 --> 0:35:53.520
<v Speaker 11>the same stand.

0:35:53.560 --> 0:35:54.720
<v Speaker 5>It's a giant step.

0:35:54.840 --> 0:35:58.200
<v Speaker 11>Let us be clear, who could believe that some years ago,

0:35:58.480 --> 0:36:00.960
<v Speaker 11>and it's a recent and it's thanks to the devolvement

0:36:01.000 --> 0:36:03.719
<v Speaker 11>of I school. The same for shadow banking, I would say,

0:36:03.719 --> 0:36:07.120
<v Speaker 11>we know the evolution after the subprime crisis, and we

0:36:07.160 --> 0:36:10.960
<v Speaker 11>are not working I would say, very intensely with the BIS,

0:36:11.000 --> 0:36:14.160
<v Speaker 11>with the FSB, we are reporting to the G twenty

0:36:14.760 --> 0:36:16.640
<v Speaker 11>leaders in order to develop new tools.

0:36:16.680 --> 0:36:17.520
<v Speaker 5>For instance, we were.

0:36:17.440 --> 0:36:20.760
<v Speaker 11>Able to get with this SB to publish a useful

0:36:20.800 --> 0:36:23.560
<v Speaker 11>toolkit for the liquidity of manager tool. We are not

0:36:23.680 --> 0:36:26.040
<v Speaker 11>working on leverage in order to keep to account that

0:36:26.120 --> 0:36:28.480
<v Speaker 11>ons if our chare goes, the games and so on,

0:36:28.840 --> 0:36:31.040
<v Speaker 11>so there is always something to learn, I would say,

0:36:31.080 --> 0:36:33.960
<v Speaker 11>and then to make progress about new toolkits.

0:36:34.040 --> 0:36:34.799
<v Speaker 8>Thank you so much.

0:36:35.600 --> 0:36:37.080
<v Speaker 5>We thank you with I ask.

0:36:37.480 --> 0:36:40.640
<v Speaker 2>This is the Bloomberg Surveillance Podcast, bringing you the best

0:36:40.640 --> 0:36:45.440
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0:36:45.520 --> 0:36:49.560
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0:36:49.680 --> 0:36:53.680
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