Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: You're listening to Bloomberg Business Week with Carol Masser and
Speaker 2: Tim Stenoveek on Bloomberg Radio.
Speaker 3: Well, it seems like everybody is talking about AI, but
Speaker 3: the question is is everybody using AI? We talked a
Speaker 3: little bit about this with Vinnie Catalano. Yeah, he said
Speaker 3: he's like going all in on us.
Speaker 4: He did, Yeah, which is kind of funny.
Speaker 3: It turns out my takeaway from that conversation is I'm
Speaker 3: no Einstein.
Speaker 2: But neither are you.
Speaker 3: No Exactly, Well, it turns out there are some stark
Speaker 3: differences when it comes to who is engaging with the tech,
Speaker 3: and it actually falls along gender lines. Check out this
Speaker 3: research Carol Harvard Business School Associate Professor Rembrandt Koning found
Speaker 3: that women are using new AI tools at a lower
Speaker 3: rate than men, about twenty five percent, according to the
Speaker 3: research cited in a story last month. In a post
Speaker 3: from Harvard Business School, curious what Jenny Troutman thinks about this.
Speaker 3: She's director of Training and Certification at Amazon Web Services.
Speaker 3: Of course we refer to it as AWS. She joins
Speaker 3: us from Houston, Texas. Jenny, I know you watch the
Speaker 3: way that this falls along gender lines really closely. In
Speaker 3: your position at aws Why do you think the adoption
Speaker 3: among women is so much less than men?
Speaker 2: Right?
Speaker 1: Well, yeah, so it's interesting. In technology in general, women
Speaker 1: only make up about thirty percent of the workforce, but
Speaker 1: it is more stark in AI, with I'm only comprising
Speaker 1: about twenty two percent. We did do a study though,
Speaker 1: that shows that women are interested in learning about generative AI.
Speaker 5: In fact, in the.
Speaker 1: Study, it showed three out of four women are interested
Speaker 1: in learning how to apply generative AI at work, and
Speaker 1: eighty percent actually want to apply for jobs involving generative AI.
Speaker 1: So while I think we're seeing a gap right now
Speaker 1: in the workforce, we're not seeing a gap in interest.
Speaker 1: And I think the issue is confidence in skills, and
Speaker 1: that's really why I'm here. What I'm focused on is
Speaker 1: how do we at AWLS help the global workforce and
Speaker 1: women across the globe get confidence working with AI and
Speaker 1: generative AI technologies.
Speaker 4: Well, you know, this is something I'm glad we're talking.
Speaker 4: We actually had an earlier conversation about AI and the workforce.
Speaker 4: And you know, when anybody says, you know, we're hiring
Speaker 4: a lot of AI related jobs and it's AI related skills,
Speaker 4: and like, what's an AI related skill? Because to be
Speaker 4: quite honest with you, Jenny, you know, Tim and I
Speaker 4: play around certainly with like chatchipt and things, and part
Speaker 4: of it is like our job. How do you ask
Speaker 4: the right questions right and drill down those questions. I mean,
Speaker 4: I know that's just basic level, but I mean, what
Speaker 4: what do you see as AI skills? Be it for
Speaker 4: men or for women?
Speaker 5: Yeah, so that is a very big question.
Speaker 1: Sorry, when we talk about when we talk about AI skills,
Speaker 1: there are kind of a breadth of them that we're
Speaker 1: talking about.
Speaker 5: To your point, we're.
Speaker 1: Talking about people who are just using the technology, which
Speaker 1: the foundational skills really are what we need. So things
Speaker 1: like are to the possible? What is generative AI? And
Speaker 1: what can you do with it? Because one of the
Speaker 1: one of the biggest roadblocks to getting started is really
Speaker 1: understanding how you can use it and thinking differently about
Speaker 1: what you do. So I'm you know, understanding use cases,
Speaker 1: places to get started, where to play with it. And
Speaker 1: then the second is exactly what you just said, which
Speaker 1: is what we call prompt engineering how to write good prompts,
Speaker 1: And that's relevant for anyone looking to use the technology,
Speaker 1: no matter their role technical non technical alike, if you
Speaker 1: don't write a good prompt, you don't get a good
Speaker 1: output from the from the technology, and so that is
Speaker 1: a skill in and of itself. In fact, we offer
Speaker 1: free training online on a to a skill builder. We
Speaker 1: can go in and take a course on how to
Speaker 1: do that.
Speaker 3: Isn't that funny that?
Speaker 4: Like, wait, can we take that course?
Speaker 5: Yes? You can. It's for free. You can go online
Speaker 5: and find it. Today.
Speaker 3: Carol's like so excited about learning how to do prompts
Speaker 3: so she can get away from her cohed.
Speaker 4: We want to say, no, I don't want to get
Speaker 4: away from you. But I mean everybody has said that
Speaker 4: learning how to use it is like learning how to
Speaker 4: prompt and ask correct.
Speaker 3: Well, that's why the turn, that's why engineers, that's like
Speaker 3: why it's such an important skill. I think one cool
Speaker 3: thing about this, though, Jenny, is you don't even need
Speaker 3: to be like anyone. Anyone can I've never taken a
Speaker 3: course on prompt engineering. I'm not going to pretend that
Speaker 3: I know what I'm doing. But it's such a forgiving
Speaker 3: product where if you don't get the answer you're looking for,
Speaker 3: then you change the way you ask the question or
Speaker 3: you refine it, and you ultimately get there.
Speaker 4: Now it's not like a co host who says that
Speaker 4: was a stupid question.
Speaker 3: Never yet, well, I bet I would do that by
Speaker 3: the way, it probably would.
Speaker 1: I would say yes, and yes, that is very true.
Speaker 1: And in fact, a big part of using generative AI
Speaker 1: is validating the What you got is what you were
Speaker 1: looking for. The problem comes in if you weren't exactly
Speaker 1: sure what the output should be. So, for example, if
Speaker 1: you're using the tool beyond writing a document for you,
Speaker 1: but maybe to do some data analysis and you ask comparison,
Speaker 1: if you don't actually do the right prompt, the results
Speaker 1: of the data analysis you get might not be correct,
Speaker 1: and unless you a deep.
Speaker 5: Validation, you might not know that. So that's where it
Speaker 5: becomes important.
Speaker 1: But part of learning the technology and getting good at
Speaker 1: prompt engineering is to your point, practicing it, doing it
Speaker 1: over and over seeing what kind of results you get,
Speaker 1: and constantly refining.
Speaker 4: I'm looking at your background. I didn't know you were
Speaker 4: a pilot. That's really pretty cool stuff Like no, I
Speaker 4: just you know, I think about how the world has
Speaker 4: evolved and continues to evolve. How are you thinking about
Speaker 4: and kind of all that you've done in your world,
Speaker 4: and like, as we it just feels like we're just
Speaker 4: scratching the service in terms of what generative AI and
Speaker 4: LMS can do for our world. And I know that
Speaker 4: there are a lot of concerns about it going off
Speaker 4: in the wrong direction, and that's all.
Speaker 1: You know.
Speaker 4: We could spend hours on that, but I'm just curious
Speaker 4: about from your vantage point, what you've done professionally, like
Speaker 4: how you are looking at this moment in time.
Speaker 1: So we are actually in the same place everyone else is,
Speaker 1: which is trying to figure out how we do our
Speaker 1: own jobs differently and then using that to then help
Speaker 1: educate people on how to think differently for other roles.
Speaker 1: I would agree we're at the very early stages. And
Speaker 1: that's why the lack of skills in the industry around
Speaker 1: AI are so prevalent, because, like I mentioned, it's not
Speaker 1: only the foundational skills the other areas. We need deep
Speaker 1: technical experts who can build good models, who can build
Speaker 1: good tooling on top of the models, and all of
Speaker 1: that is a work in progress right now. The tooling
Speaker 1: is getting better day by day, but as the tooling
Speaker 1: gets better, we need to get better and better at
Speaker 1: how we use it. So I would say we're still
Speaker 1: at the very beginning of figuring out how much this
Speaker 1: is going to change the way we work. And I
Speaker 1: take it back to thinking about the Internet. I am
Speaker 1: old enough to remember when the Internet became big and
Speaker 1: we had no idea how much it was going to
Speaker 1: change the way our day to day lives and worked,
Speaker 1: and how we looked for things, how we found things,
Speaker 1: how we thought about getting from place to place. We're
Speaker 1: in that same same place. It's AI and generative AI
Speaker 1: is the one thing I can guarantee you is the
Speaker 1: way we do things ten years from now will be
Speaker 1: very different from the way we.
Speaker 5: Do them now.
Speaker 1: Yeah, but it's hard to predict exactly how quickly things
Speaker 1: will change or how much they will change.
Speaker 4: I'm with you. I remember doing a premer on what
Speaker 4: is the Internet like early on in my career.
Speaker 3: What did you find out?
Speaker 2: The answer?
Speaker 4: But it wasn't around.
Speaker 5: It wasn't around.
Speaker 4: No, I want to go back to you being a
Speaker 4: commercial or having a commercial pilot license, Like when you say,
Speaker 4: in ten years from now that you know generative AI
Speaker 4: and what we were talking about today is going to
Speaker 4: dramatically change our world, Like do you see AI ultimately
Speaker 4: handling you know, systems like air traffic control? Like how
Speaker 4: far does it go? Or I know it's hard, it's
Speaker 4: like who knows where it goes? But I mean, how
Speaker 4: do you think about it? Like on what scale?
Speaker 2: Yeah?
Speaker 1: The way we think about it is anything that can
Speaker 1: be automated will be. So anything that you can write
Speaker 1: down a word for, if it's not already automated, it
Speaker 1: will be. And the beauty of that is the things
Speaker 1: that we can't automate, like our creative thinking, like taking
Speaker 1: that and making connections with other things innovating. That's the
Speaker 1: sort of thing that doesn't automate. And so where I
Speaker 1: think it will go is we will all have AI
Speaker 1: assistance that will be doing kind of that automated repetitive
Speaker 1: work for us. We will be guiding those agents or
Speaker 1: those assistants, and we will we will be innovating so
Speaker 1: much faster than we can even imagine because we've never
Speaker 1: had a machine in the back end doing all of
Speaker 1: the grunt work for us.
Speaker 5: That's a down stall.
Speaker 3: I think Jennie Diamond, I'm quoting him again, but I
Speaker 3: believe he said our kids are going to live to
Speaker 3: one hundred not have cancer as a result of these
Speaker 3: tools and be working three and a half days a week.
Speaker 2: Is that true?
Speaker 5: Your guess is as good as mine.
Speaker 3: It sounds like a pretty great world.
Speaker 1: Well, I look back before cloud and before the Internet,
Speaker 1: and we didn't work less than Yeah, so it's hard
Speaker 1: for me to imagine.
Speaker 3: I think some people would say we work more because
Speaker 3: we always have these computer things attached to our hands
Speaker 3: always on.
Speaker 1: Might say that, and it's hard for me to imagine,
Speaker 1: just because of human nature, that we will do less
Speaker 1: than we did.
Speaker 5: In the past.
Speaker 1: But but I do think that we will be able
Speaker 1: to do a whole lot more, a whole lot faster.
Speaker 1: And that's that's the part that's hard to imagine. I
Speaker 1: have a I have a daughter who's in high school
Speaker 1: and has wanted to be a doctor her whole life.
Speaker 1: And that's an area where you know, it's already using robotics,
Speaker 1: and you can imagine a lot will change it. So
Speaker 1: I question, you know, what is the what is the
Speaker 1: place to be there? But there are always going to
Speaker 1: be people needing to guide the machines.
Speaker 3: I think, and yeah, exactly, And I think, I mean,
Speaker 3: I think radiology is one profession. That's certainly right for
Speaker 3: disruption when it comes to AI, but maybe dermatology not
Speaker 3: so much.
Speaker 1: Fair Yeah, I think where you have to have kind
Speaker 1: of the human intervention, there will always be some level
Speaker 1: of human intervention needed. And the question is how much
Speaker 1: better can we be? How much less time do we
Speaker 1: need to spend in a doctor's office because they're able
Speaker 1: to solve problems automatically for us? And then how much
Speaker 1: will they be able to accelerate the time, you know,
Speaker 1: spend more time on innovating the solutions for us?
Speaker 5: Yeah, I know.
Speaker 4: And people talk about drug discovery right, being able to
Speaker 4: kind of go through a lot of information and figure
Speaker 4: out things.
Speaker 3: What hey, Jenny, before we let you go, since you
Speaker 3: are in aviation, Also, do you think we'll in our
Speaker 3: lifetimes we'll see commercial aircraft with just one pilot rather
Speaker 3: than two.
Speaker 1: You know, I can't predict the future, but I don't know.
Speaker 3: Why not, whereas like maybe on the ground they're doing
Speaker 3: some of the controlling or even.
Speaker 1: Already have so much unmanned in the military, unmanned spacecraft
Speaker 1: or sorry, aircraft spacecraft too, But I don't know why
Speaker 1: we would continue to need as much on the plane
Speaker 1: with the exception of the backup factor. Something happens to
Speaker 1: one pilot, you definitely don't want to have nobody.
Speaker 3: Yeah, yeah, that's true. Or they can control it on
Speaker 3: the ground, who knows.
Speaker 4: I guess I don't know, like a remote yeah, like
Speaker 4: a like a drone or something, right, exactly, exactly.
Speaker 1: Listen, this was what I saw my car drive for me,
Speaker 1: as though, to be fair, I'm.
Speaker 5: Not ready for that.
Speaker 2: I'm ready.
Speaker 3: Oh my gosh, you got to get in one of
Speaker 3: these waymouth things.
Speaker 2: They're amazing. It was awesome.
Speaker 1: Jenny.
Speaker 5: Thanks.
Speaker 4: Jenny Troutman, director of Training and Certification at AWS, Amazon
Speaker 4: Web Services, joining us on this Monday from Houston, Texas.
Speaker 2: Well.
Speaker 3: The Trump family is set to launch a bitcoin mining
Speaker 3: focused venture with HUT eight. It's the latest expansion of
Speaker 3: the US President's ties to the cryptocurrency sector. HUT eight
Speaker 3: is launching the American Bitcoin Corp. As a major already
Speaker 3: owned a subsidiary focus exclusively on bitcoin mining and quote
Speaker 3: strategic bitcoin reserve development this company. The company said this
Speaker 3: in a statement today. For more, let's go to Fred
Speaker 3: Tealey's chairman and CEO of the four billion dollar market
Speaker 3: cap bitcoin minor Mara holdings. He joins us from Miami today. Fred,
Speaker 3: good to have you back with us. I want to
Speaker 3: talk the market, bitcoin mining, the health of the industry
Speaker 3: as you see at big changes. But first I want
Speaker 3: to get your reaction to this news that the Trump
Speaker 3: family is teaming up with hot eight. What do you
Speaker 3: make of it?
Speaker 2: Oh, I think obviously the president and his family are
Speaker 2: very positively inclined to bitcoin. So bitcoin mining is a
Speaker 2: key part of anybody's crypto strategy if you're looking at
Speaker 2: the industry overall. So I think that the fact that
Speaker 2: they're interested is a good sign. Obviously, I think there
Speaker 2: could have been a better choice for partner for them,
Speaker 2: but that's just me being biased.
Speaker 3: I understand. But do you think that there's a concern
Speaker 3: that he's a little too close in the sense of, well,
Speaker 3: if his firm is partnering up and picking partners, then
Speaker 3: he can pick winners and losers.
Speaker 2: I'm listening. I'm a big believer in free competition and
Speaker 2: open competition in the marketplaces, and you know, my expectation
Speaker 2: is that you know, there won't be any preferences played
Speaker 2: in this marketplace. You know, the great thing about bitcoin
Speaker 2: mining is it's really a business where we all compete
Speaker 2: with our compute and our hash rate, and I think that,
Speaker 2: you know, we'll just have to see if this company
Speaker 2: has given preferential treatment. Then I think I'm sure the
Speaker 2: media industry will cover that and in its a typical
Speaker 2: way and bring that to light, and that point it'll
Speaker 2: be up to the public to kind of deal with it.
Speaker 3: And do you think the president should be in this business?
Speaker 2: Yeah, I'm not going to pine on that. I think
Speaker 2: the what you know, members of government do and don't do.
Speaker 2: I think it is up for the government to police
Speaker 2: and make determinations on that. You know, there's so many
Speaker 2: people who have been in very high offices that have
Speaker 2: had financial dealings big businesses, and even though the rules
Speaker 2: call for you to kind of step away from those businesses,
Speaker 2: are they really stepping away? I mean, I think you
Speaker 2: can go back over history and see that this wouldn't
Speaker 2: be the first time that, you know, members of high
Speaker 2: office have fingers in businesses and influenced businesses.
Speaker 3: So let's go bigger picture here and just talk a
Speaker 3: little bit about how you view the administration with regard
Speaker 3: to crypto.
Speaker 2: If we were to.
Speaker 3: Speak a few months ago, maybe we'd see the eyes
Speaker 3: in the price of bitcoin and talk about the optimism
Speaker 3: that the industry had for a Trump administration. Are you
Speaker 3: seeing that promise fulfilled at this point?
Speaker 2: Absolutely? You know, I spend a lot of time in
Speaker 2: Washington these days. I was at the White House Crypto
Speaker 2: Summit as the only bitcoin minor representing the industry. I
Speaker 2: think as we look at the things President Trump laid
Speaker 2: out in his kind of campaign promises at the Bitcoin
Speaker 2: Nashville conference, you know, obviously changes at the sec Bitcoin
Speaker 2: Strategic Reserve. You know, more bitcoin mining should be done
Speaker 2: in the US. You know, a lot of those things
Speaker 2: have come to pass. I think we're going to see
Speaker 2: market Structure Bill be introduced here shortly. We're going to
Speaker 2: start seeing further process progress on the Strategic Bitcoin Reserve.
Speaker 2: We'll see a variety of other things around stable coin
Speaker 2: legislation as well. So I think you're going to see
Speaker 2: a lot of progress to make up for the years
Speaker 2: during the Biden administration when nothing happened in the industry
Speaker 2: was attacked. So you've got to think about it. We're
Speaker 2: not even one hundred days into his administration at this point, right,
Speaker 2: So no, that's fair. A lot has already happened.
Speaker 4: Hey, Fred broad Now just remind our world. I mean,
Speaker 4: you're publicly held, you're almost a four billion dollar market
Speaker 4: cap company. Remind our world exactly what your business is.
Speaker 2: So we're in the business of transforming energy into digital gold.
Speaker 2: We consider ourselves really a digital energy company. So we
Speaker 2: take energy which otherwise isn't necessarily being used. So if
Speaker 2: you think about a lot of renewable energy assets like
Speaker 2: wind farms, a lot of the time that energy can't
Speaker 2: be sold into the marketplace because either there is too
Speaker 2: much supply and so the market is flooded, or there's
Speaker 2: not enough transmission capacity and it's called congestion. And you know,
Speaker 2: the renewable energy boom that happened in this country over
Speaker 2: the past decade has created an oversupply in certain geographies.
Speaker 2: And what happens is that supply can't get to market
Speaker 2: and so it sits idle. So we can go in
Speaker 2: and take that excess energy and move demand to where
Speaker 2: supply is. Energy consumption is not a constant flat amount
Speaker 2: all day long, so the energy companies can just plan
Speaker 2: to have a flat amount of energy. It varies all
Speaker 2: day long. From the morning it goes up and then
Speaker 2: it goes bottoms out midday, and then it peaks around
Speaker 2: nine o'clock at night and then drops again. And while
Speaker 2: you can plan for those flows, what you can't plan
Speaker 2: for is the weather because that affects solar farms, it
Speaker 2: affects wind farms, and that intermittent type of energy generation
Speaker 2: is very challenging to plan for. And so the only
Speaker 2: energy that really is consistent and constant is nuclear, coal,
Speaker 2: natural gas. But all of the renewable energy forms really
Speaker 2: are what's called intermittent, and so our industry supplies what's
Speaker 2: called flexible load. And Duke University just put out a
Speaker 2: study a few weeks ago where basically, the whole AI
Speaker 2: industry in this country needs about forty eight gigawatts of
Speaker 2: power over the next few years, and yet our grid
Speaker 2: has seventy three gigawatts, nearly double what the AI industry needs.
Speaker 2: But it's only available if the load is flexible. And
Speaker 2: we're flexible because we can shut our operations down at
Speaker 2: a moment's notice when the grid needs the energy. The
Speaker 2: AI industry has a harder time doing that. So we're
Speaker 2: a kind of a unique animal in that, but we
Speaker 2: play a very vital role in balancing the grid.
Speaker 4: So do you have a good do you feel like
Speaker 4: tell us about your vantage point when it comes to
Speaker 4: data centers and AI demand, because I do think there
Speaker 4: has been a bit of a reset this year. So
Speaker 4: what are you seeing? What can you tell us with
Speaker 4: clarity about that demand? And certainly it's you know, draw
Speaker 4: down on energy.
Speaker 2: So we've spoken number of times in our earnings calls
Speaker 2: and interviews about the fact that we believe that this
Speaker 2: first phase of the AI data center build out is
Speaker 2: very similar to the pattern that occurred at the buildout
Speaker 2: of the original Internet. Go back to ninety the period
Speaker 2: nineteen ninety five to two thousand and two. What happened
Speaker 2: we were building data centers. It was like every company
Speaker 2: has to be an Internet company and you have to
Speaker 2: have a dot com after your name, and a lot
Speaker 2: of capital flowed into these businesses, and what ended up
Speaker 2: happening was that the cost initially to build websites was
Speaker 2: millions of dollars. You had to have unique machines by
Speaker 2: Sun Microsystems, You had to write all the code yourself,
Speaker 2: and then very quickly tools came out, Things came out
Speaker 2: that lowered the cost dramatically and lowered the amount of
Speaker 2: infrastructure you had to have to do this, and so
Speaker 2: all this infrastructure that got built was superfluous for a while.
Speaker 2: It took years for that supply to get consumed. And
Speaker 2: maybe I'm just an old guy in that I lived
Speaker 2: through that industry. I was in the data communications industry
Speaker 2: at the time, and I lived through that boom bus cycle.
Speaker 2: And so as we looked at it, we said, we're
Speaker 2: only in the first generation of this technology, really, and
Speaker 2: people are going to be very focused on how do
Speaker 2: I do this cheaper? How do I do this so
Speaker 2: it uses less energy? Because in the bitcoin mining business,
Speaker 2: that's what you focus on all day long is how
Speaker 2: do I do this to consume less energy? How do
Speaker 2: I do this more efficiently and low? And behold, you
Speaker 2: had deep Seak came out, you had all of a sudden,
Speaker 2: all these things came out that essentially showed you could
Speaker 2: do more with less, which while that does drive faster adoption,
Speaker 2: it drives lower cost drives faster adoption. With what happened
Speaker 2: with cell phones, when you stop being charged for minutes,
Speaker 2: you just use it, right, So what happens now is
Speaker 2: instead people like I think Microsoft has been mentioned a
Speaker 2: few times by analysts and an analyst reports that they're
Speaker 2: slowing down on their execution of some of their private
Speaker 2: data center contracts because what they're seeing is, you know, okay,
Speaker 2: there's a certain amount of demand based on current technology.
Speaker 2: People are starting to use this next generation reasoning technology,
Speaker 2: which is much more energy efficient, and as that transition happens,
Speaker 2: the design of what you need in the data center
Speaker 2: is slightly different reasoning models. I think the easy way
Speaker 2: to think of it is open AI. Everything is in
Speaker 2: memory at all times. When you look at deep Seek,
Speaker 2: only what you're working on is in memory, so it
Speaker 2: lets you have much smaller footprint, which means less compute,
Speaker 2: less memory, etc.
Speaker 4: Yeah, this is something thing we've talked about too with
Speaker 4: our tech guys, but we're going to need to continue
Speaker 4: this conversation because it's certainly one that dominates our world
Speaker 4: and your world as well, and look forward to next time.
Speaker 4: Fred til He's chairman and chief executive officer of Mayor,
Speaker 4: joining us from Miami, Florida.