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Speaker 2: Well back to Tesla shares down two percent in the
Speaker 2: after hours. The company posted third quarter profit that fell
Speaker 2: short of Wall Street's expectations despite record ev sales. I
Speaker 2: want to bring back Ed Ludlow. He's the co host
Speaker 2: of Bloomberg Tech, and also bring in Ross Gerber. He's
Speaker 2: president and CEO of Gerber Kawasaki Wealth and Investment Management
Speaker 2: got more than three billion dollars in assets under management.
Speaker 2: He joins us from Santa Monica, California. Ross, you now
Speaker 2: have about eighty million dollars of Tesla shares, down from
Speaker 2: one hundred million earlier this year. At it, at your peak,
Speaker 2: how much Tesla stock did you own?
Speaker 3: I think we had about one and a half times
Speaker 3: more than we have today.
Speaker 4: So that's not that much more.
Speaker 5: No, we've got our.
Speaker 3: Positioned by sixty percent, So that's that's fairly large.
Speaker 2: Are you Are you buying or selling today or buying
Speaker 2: or selling right now?
Speaker 5: Neither neither.
Speaker 3: You know, you know Tesla as a hold for us.
Speaker 3: You know, the people who are holding the stock at
Speaker 3: our firm, our clients very much believe in Tesla and
Speaker 3: don't want to let go of their shares at all.
Speaker 3: And then you know, the clients that don't want to
Speaker 3: own Tesla don't own Tesla anymore. But we're not recommending
Speaker 3: to buy Tesla or per Se more likely recommending to
Speaker 3: sell Tesla for investors up at these prices because you're
Speaker 3: getting such a premium valuation. But in general, we've just
Speaker 3: been holding the stock because you know, we're kind of
Speaker 3: stuck with our position right now.
Speaker 2: What about you, because we check in with you quarterly
Speaker 2: and you've really changed your position on the company in
Speaker 2: recent years in recent quarters and your position on Elon
Speaker 2: Musk too.
Speaker 4: Are you a believer in the company right now?
Speaker 5: Yes, and no.
Speaker 3: I still own Tesla's stock as well personally, not a lot,
Speaker 3: but you know I like to have some because I
Speaker 3: bought it at a dollar a share or a dollar fifty,
Speaker 3: So it's like fun to have in my portfolio still.
Speaker 3: But that said, you know, I don't know what's going
Speaker 3: to happen with full self driving. I just don't think
Speaker 3: it works, and I think vision only systems don't work.
Speaker 3: And I'm very sure of this now. Even though I'm
Speaker 3: not an engineer, I can explain to you how humans drive.
Speaker 3: And I don't think Elon gets how humans work. I
Speaker 3: think he gets how machines work. And so I think
Speaker 3: that Tesla's in a pickle. If they can solve full
Speaker 3: full self driving, like I could get in my car
Speaker 3: right now and push a button and it drives me home,
Speaker 3: Like I can get in a Weymo right now and
Speaker 3: it'll drive me home no problem, then I think Tesla
Speaker 3: has a reason to buy the stock because now they've
Speaker 3: got their products working and they can grow from there.
Speaker 3: But as far as waiting for robots and cabs to
Speaker 3: pay off, it doesn't matter if full self driving doesn't work.
Speaker 3: And full self driving doesn't work, so nothing's going to
Speaker 3: get me excited about Tesla until it drives me home.
Speaker 6: All right, good stuff, we're talking with Ross, Gerber and Ludlow.
Speaker 6: I know you're reading over stuff. Come on into the
Speaker 6: conversation with Roth.
Speaker 7: Yeah, I mean, you know, just going through the deck.
Speaker 7: The way that Tesla explains it is that they had
Speaker 7: lower FSD revenue recognition in this quarter because of the
Speaker 7: timing of previous generation releases of FSD in the same
Speaker 7: period a year ago.
Speaker 5: You know, I'm not a.
Speaker 7: Tesla shareholder, as you guys know, but I do drive
Speaker 7: a Model Y in fact, and I use FSD every
Speaker 7: day for about sixty miles thirty miles to work, thirty
Speaker 7: miles back. I'm not on version fourteen yet. But Ross
Speaker 7: is speaking to the question, which is always there. Explain
Speaker 7: the jump or the steps to the end result, the
Speaker 7: end state. The end state is robotaxi, right if Tesla
Speaker 7: is to be believed, And right now, you know, the
Speaker 7: street seems kind of split on whether we understand how
Speaker 7: we go from a software platform that consumers pay for
Speaker 7: as a one offer a subscription package to a world
Speaker 7: where the vehicles built on a common software platform or
Speaker 7: iterations of that platform power a rope proprietary ride hailing
Speaker 7: robotaxi service. You know, it's difficult to see the jump,
Speaker 7: and Ross can speak for himself, but just in the reporting,
Speaker 7: that's what we hear all the time.
Speaker 3: Yeah, I mean you're one hundred percent right in that
Speaker 3: these are completely different businesses, right, Like selling cars that
Speaker 3: drive themselves is an Apple business model, And that's why
Speaker 3: I always love Tesla. When I first found Tesla, I
Speaker 3: was like, this is the Apple of cars, right, Like
Speaker 3: you build hardware and with great software, and then you
Speaker 3: make money on services, right And that's really where Tesla's
Speaker 3: making a ton of money right now is on services
Speaker 3: and energy storage, which are still great businesses for Tesla.
Speaker 3: But when you talk about building an Uber like platform,
Speaker 3: this is an extremely difficult thing that it took Uber
Speaker 3: almost a decade or more to make money doing, and
Speaker 3: Uber is very very good at this now and the
Speaker 3: only way they've been able to make money is by
Speaker 3: charging substantially more for the rides because Uber is not
Speaker 3: cheap anymore and they had to subsidize rides for a
Speaker 3: decade just to build that business. So when you actually
Speaker 3: think about Tesla scaling, if there was no competition, that'd
Speaker 3: be one thing. But there's already several cab services I
Speaker 3: can take right now, whether it be Uber, Lyft or
Speaker 3: waimap that are all very good at what they do.
Speaker 3: So you know, even if Tesla gets this to work,
Speaker 3: it's still a tough business. And the second thing I
Speaker 3: would just say, ed you use full self driving a lot?
Speaker 3: Obviously you probably if I asked, do you feel comfortable
Speaker 3: turning it on and going into the backseat of your
Speaker 3: car and letting you drive that full thirty miles home?
Speaker 7: I've never done that or attempted it, and I think
Speaker 7: you know, I post quite a lot on X my experiences,
Speaker 7: like I say today, this is what happened. You know,
Speaker 7: I would never get in the back of the car
Speaker 7: and turn it on. I also would not put my
Speaker 7: little baby boy in it either. But the way that
Speaker 7: I've tried to track it is generation by generation. How
Speaker 7: has it improved on the route that I take every day.
Speaker 7: The one area that is really struggled is with the
Speaker 7: toll boobs on the Golden Gate Bridge. You know that
Speaker 7: can be precarious, and you can see my posts on
Speaker 7: that on your point.
Speaker 5: In the AI graph of the shareholder deck.
Speaker 7: The way that Tester explains it is that the latest
Speaker 7: version of FSD, they say, has a substantial amount of
Speaker 7: the source code in the Robotaxi version, and by putting
Speaker 7: it out into the real world. It gives them valuable
Speaker 7: real world data to help them improve a future robo
Speaker 7: taxi service.
Speaker 5: I don't weigh in on that one way or the other.
Speaker 7: I'm just saying that's Tesla's explanation on the link between
Speaker 7: the two, the consumer facing FSD and the same codebase
Speaker 7: that will be used to power a future rover taxi service.
Speaker 2: He ed Ross made the point that he doesn't believe
Speaker 2: vision only FSD or vision only self driving works. Can
Speaker 2: you talk a little bit about that technology that that
Speaker 2: Tesla uses versus the other companies, namely Weima and Amazons,
Speaker 2: Amazon subsidiary as well.
Speaker 5: Yeah, so very simple.
Speaker 7: When we say vision based system, the inputs for the
Speaker 7: vehicle are only cameras on a Tesla. The cameras capture
Speaker 7: capture optical data from around the vehicle and use the
Speaker 7: underlying algorithm to make an onboard decision interpreting the world
Speaker 7: around them.
Speaker 8: Uh.
Speaker 7: The opposite academic view is that you need to paint
Speaker 7: a richer digital picture of the world using other forms
Speaker 7: of data gathered by lidar, radar, and in some cases
Speaker 7: even going beyond that. You know, like there are very
Speaker 7: degrees of lightar spinning or stationary or static. Sorry, The
Speaker 7: economic argument that Tesla and Elon must have always made
Speaker 7: is that having a vehicle that has multiple sensors on
Speaker 7: it is not scalable. You know, there is no end
Speaker 7: result whether the vehicle could be affordable for a consumer
Speaker 7: or profitable for an operator of that system to run.
Speaker 7: The other robotaxi companies like Weymo or zooks, who do
Speaker 7: have multiple sensors and custom versions of them, say that
Speaker 7: you have to have them for redundancy. So if one
Speaker 7: of those digital pictures fails, i e. The vision one,
Speaker 7: the cameras fail, or the ID or radar fails, you
Speaker 7: can still be safe because you have a rich enough
Speaker 7: digital picture of the world around you for the vehicle
Speaker 7: to make a decision based on the circumstances presented in
Speaker 7: front of it.
Speaker 6: So I put this question to both of you, and
Speaker 6: let me just start with you, Rass. I mean, I've
Speaker 6: gotten in a weymore I love it, and I've sat
Speaker 6: in the back seat, I've closed my eyes for like
Speaker 6: a thirty forty minute trip to an airport. I have
Speaker 6: loved it. So FSD full self driving?
Speaker 7: Is it?
Speaker 6: Are we crazy to think that that's going to be
Speaker 6: our world going forward, or do we have to change
Speaker 6: our infrastructure dramatically to make it possible going forward? Like
Speaker 6: trying to understand because if the model is so to.
Speaker 2: Ultrastructure is the hardest part would be the hardest part.
Speaker 6: I'm just thinking, if it's such a torture model, like,
Speaker 6: are we crazy to even be talking about it?
Speaker 3: You're getting into one of my favorite discussion debate issues
Speaker 3: out there right now, which is the future of what
Speaker 3: mobility actually looks like. And my basic premise is that
Speaker 3: humans love to drive and are not giving it up.
Speaker 3: And I'm now raising my children. I thought when I
Speaker 3: had children that we would have had this master that
Speaker 3: my kids would never learn to drive. But my kids
Speaker 3: learning how to drive now, you know what I'm saying.
Speaker 3: And people love to drive. Now, Younger people don't love
Speaker 3: to drive as much as older people. That's one thing
Speaker 3: in our surveys we've noticed. Okay, but I'm not giving
Speaker 3: up driving, And if I live another thirty years, I'm
Speaker 3: still gonna love driving. And I love cars, and I
Speaker 3: love driving fast, and I love like, you know, driving
Speaker 3: the one freeway, you know, whatever you want to call it.
Speaker 3: But you know, humans love the independence and the functionality
Speaker 3: of having their own vehicle.
Speaker 5: We've had.
Speaker 3: It started with the horse. We all had our own horse.
Speaker 3: You fought to the death to protect your horse. And
Speaker 3: I just don't see people giving up cars anytime soon
Speaker 3: for a lot of practical reasons, like when you're doing
Speaker 3: errands and you have to store stuff in your car
Speaker 3: or pick up your kids and then go to soccer.
Speaker 3: It's like you're not going to be taking cabs everywhere.
Speaker 3: That's just not a realistic view of the world. So
Speaker 3: unless we rejig our cities and start from scratch, where
Speaker 3: I think the biggest use case would be in very
Speaker 3: dense urban environments that are very difficult for people to drive.
Speaker 3: Just saying no more cars, it has to be cabs.
Speaker 3: That makes sense in New York City or downtown LA,
Speaker 3: let's say. But I just don't see how you implement that,
Speaker 3: because it's like millions of people already have their commuter
Speaker 3: lifestyle and I just don't see how that changes.
Speaker 6: All right, So EDLA. That brings us back then to Tesla.
Speaker 6: If they keep talking about FSD, I mean, they're an
Speaker 6: ev company and a lot more we know that, but
Speaker 6: I don't know is it enough. I don't know momentum
Speaker 6: I look at the valuation, like, what is this company
Speaker 6: going forward?
Speaker 7: Well, I repeat the same thing I've said every quarter
Speaker 7: for eight years. Elon Musk is often late on his predictions,
Speaker 7: but gets there in the end, and Tesla is clearly
Speaker 7: committed to this.
Speaker 5: That's part one.
Speaker 7: You know that largely Tesla has made economic benefit arguments
Speaker 7: and the industry has as well. There are people that
Speaker 7: disagree with Ross in that car ownership as a model
Speaker 7: is in doubt. You know, there are multiple reasons from
Speaker 7: the cost of owning and operating a vehicle through to
Speaker 7: generational attitude and appetite to go out and get a
Speaker 7: driving license that people feel will make the technology more
Speaker 7: pervasive and be adopted. Where people agree with Ross is
Speaker 7: the environment, the infrastructure, And I go back to the
Speaker 7: reporting always. I have to go back to what we've
Speaker 7: actually reported, which is there is a piece of legislation
Speaker 7: currently dormant and is not moved beyond the proposal stage
Speaker 7: that we reported. Elon Musk and other Tesla staff lobbied
Speaker 7: very hard on, which is to have some federal level
Speaker 7: framework where purpose built robotaxis that don't have steering wheels
Speaker 7: or pedals can be deployed unfettered in the real world,
Speaker 7: but it doesn't address that what happens with the rest
Speaker 7: of road users, and that's where academics believe we're heading
Speaker 7: for a real issue.
Speaker 6: All Right, and Lola, we know you've got some stuff
Speaker 6: to do off of these earnings, so appreciate your input
Speaker 6: throughout the day today and certainly off of Tesla's earnings. Right,
Speaker 6: we got to run. Always enjoy talking with you, Ross,
Speaker 6: Thank you so much. Ross Gerbert, President, chief executive officer
Speaker 6: of Gerbert Kawasaki Wealth and Investment Management. More than three
Speaker 6: billion in assets under management, and they own about eighty
Speaker 6: million dollars worth of Tesla shares.
Speaker 2: Stay with us more from Bloomberg Business Week Daily coming
Speaker 2: up after this.
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Speaker 6: Bloomberg's Thomas Black He recently wrote an opinion piece and
Speaker 6: he talked about the hype around humanoid robots being pretty
Speaker 6: i with forecasts of nearly one billion humanoids in service
Speaker 6: by twenty fifty, but the reality is that most people
Speaker 6: overestimate what robots can do at this point in their development.
Speaker 6: Got to say, though, one company that's been using robots
Speaker 6: a lot and for a long time and has deployed
Speaker 6: its one millionth robot happens to be one of the
Speaker 6: world's largest market at companies out there. It's also a
Speaker 6: household name. So we wanted to check in once again
Speaker 6: with Ty Brady. He's chief technologist at Amazon Robotics. He
Speaker 6: joins us from Amazon's Delivering the Future twenty twenty five
Speaker 6: event from Amazon's d u R three. It's a delivery
Speaker 6: station in Millipedes, California, and so we kind of want
Speaker 6: to find out where they are in terms of the
Speaker 6: world of robotics. Ty, I got to tell you, Tim,
Speaker 6: and I love talking to you last time, so so
Speaker 6: glad to check in with you again. First of all,
Speaker 6: this event, where you are, I mean right now, I
Speaker 6: just see a curtain, but I'm assuming there's lots of
Speaker 6: stuff happening at the event. Who's there, what's going on?
Speaker 6: Tell us a little bit about it?
Speaker 5: Yep.
Speaker 9: Well, first of all, thank you so much for having me,
Speaker 9: and I really appreciate it and I enjoyed our conversation
Speaker 9: as well.
Speaker 5: It's just really great to be here.
Speaker 9: We are are fourth delivering the Future event here and
Speaker 9: there's a bunch of press that we have here, and
Speaker 9: we made a couple of big announcements in robotics today.
Speaker 6: Can you tell us about them if you have.
Speaker 9: But the first is in our manipulation robot that we
Speaker 9: call blue Jay. And what blue Jay the way that
Speaker 9: you can think of that as we can you can
Speaker 9: take three assembly lines and put it in the same
Speaker 9: footprint of one. What it does is help eliminate the menial,
Speaker 9: the mundane, and the repetitive, and it could pick more
Speaker 9: than seventy five percent of the inventory that we actually
Speaker 9: sell in our sortable network, which is a really big deal.
Speaker 9: I'm really proud of that. And I also say there's
Speaker 9: something interesting about blue Jay as well as compared to
Speaker 9: our other bird manipulation systems Cardinal, Sparrow and Robin, it
Speaker 9: took us about three years to kind of design, deploy
Speaker 9: and get out to our frontline employees. We have actually
Speaker 9: done blue Jay with the power of AI in just
Speaker 9: over a year, so it's really the pace of innovation.
Speaker 2: I think a lot of people think about Amazon and
Speaker 2: robots I just want to jump in because we don't
Speaker 2: have a ton of time, but I I want we'll
Speaker 2: get to some of the other announcements. They think about
Speaker 2: the Kiva Systems robots the big acquisition at the time,
Speaker 2: you know, twenty twelve. That was a big position for Amazon,
Speaker 2: and they've seen pictures of the way that those can
Speaker 2: move large loads of things across warehouses. But if you
Speaker 2: were to go into a state of the art Amazon
Speaker 2: warehouse today, what would you see That's in addition to
Speaker 2: those Kiva robots.
Speaker 9: Yeah, in addition to the world's first goods to person
Speaker 9: fulfillment strategy, which was a really good idea where we
Speaker 9: have more than a million robots that we manufacture action
Speaker 9: in Massachusetts doing that job every day. You're going to
Speaker 9: see more of the unstructured fields, right, So, you're going
Speaker 9: to see green robot that we call Proteus that can
Speaker 9: move big cargoes of packages to the right dock at
Speaker 9: the right time. You're going to see many more manipulation
Speaker 9: systems that we have in there, eliminating kind of the
Speaker 9: repetitive motions that they we have. No one wants to
Speaker 9: lift a fifty pound box box all day. Robin does
Speaker 9: that cardinal does that. Moving into some of these proteus
Speaker 9: bound karts that we have, you're going to see much
Speaker 9: more collaborative robotics, right. So that's where we build our
Speaker 9: robotics systems to enable people to augment what people are
Speaker 9: capable of. And we really believe in the philosophy of
Speaker 9: people and machines working together. How can we build a
Speaker 9: tool set that enables our employees to do their job
Speaker 9: not only more efficiently, but also with better safety in mind?
Speaker 6: All right, So there's this robot arm called blue Jay.
Speaker 6: You just talked about it. You know, you guys are
Speaker 6: using this AI agent called the Iluna, and then you're
Speaker 6: also working with augmented reality glasses to be worn by
Speaker 6: drivers and delivery trucks in the field. There's like so
Speaker 6: much going on. Step back for a moment, because you
Speaker 6: guys have a lot of data. You look at what
Speaker 6: you're doing. I'm just curious investors who are thinking about
Speaker 6: Amazon and what you are doing, how do they think
Speaker 6: about the long term, like ROI return on investment When
Speaker 6: it comes to the investment you guys make in robots.
Speaker 6: Is the goal about labor efficiency through put speed or
Speaker 6: is it margin expansion? Kind of tie across your full
Speaker 6: filment operations. What is it?
Speaker 5: Yeah, well, definitely efficiency.
Speaker 9: We think about efficiencies and how can we gain efficiency
Speaker 9: through all the chain of our fulfillment processes for sure,
Speaker 9: And you mentioned data and data is the fuel for
Speaker 9: AI systems. Data has allowed us to bring think of
Speaker 9: the body of being our robotics, but bring the mind
Speaker 9: to robotics, allowing it to be more adaptable, more fluid.
Speaker 9: You can almost think of this as the ability to
Speaker 9: pour our robotics systems into any size building, any scale
Speaker 9: of building, to amplify what our employees are already doing.
Speaker 9: We want to give them an amazing tool set and
Speaker 9: we see that when we do that, we're more productive.
Speaker 9: Right when you do robotics, right when you do collab
Speaker 9: of robotics where you need both people and machines doing
Speaker 9: what they do best and they do different things better,
Speaker 9: that it allows you to be more productive. And when
Speaker 9: you're more productive, that allows you to invest more in people.
Speaker 9: We've skilled more than seven hundred thousand of our employees,
Speaker 9: which is a great stat And also in our robotics
Speaker 9: we've expanded from the Kiba days. We've expanded from just
Speaker 9: a movement solution to now movement and mobility and sortation
Speaker 9: and storage and perception systems, packing systems that have really
Speaker 9: changed the game for our customers. That's a big deal
Speaker 9: to us.
Speaker 6: But Ty, you know, well you need less workers, and
Speaker 6: I got to bring it up. You know, The Times
Speaker 6: had a story out They talked about interviews and a
Speaker 6: cash of internal strategy documents that they saw that it
Speaker 6: reveals that your execs think that the company's on the
Speaker 6: cusp of its next big workplace shift. I'm reading from
Speaker 6: the Times and replacing more than half a million jobs
Speaker 6: with robots, so you know, we know things change. I'm
Speaker 6: not in a horse and buggy anymore. I don't make
Speaker 6: things piecemeal. I get it. I don't get tons of
Speaker 6: faxes and I don't get tons of pieces of physical mail.
Speaker 6: Thank God, things change. Having said that, is Amazon, do
Speaker 6: you guys believe that you're on the cusp of a
Speaker 6: workplace shift and that you won't need as many workers
Speaker 6: because the advancements in robotics.
Speaker 9: Well, there's no doubt that things change. I mean, and
Speaker 9: we're actually really proud of that. And Amazon is that
Speaker 9: we avoid stasis at all costs. We change and we
Speaker 9: adapt and the nature of tasks definitely changed, There's no
Speaker 9: doubt about that. We are laser focused on efficiencies inside
Speaker 9: of our buildings. But when it comes to that article,
Speaker 9: that article was speculating ten years out right, that's a
Speaker 9: ten year speculation, and it's hard to say what's going
Speaker 9: to happen in the next ten years. But I can
Speaker 9: tell you what happened in the last ten years, the
Speaker 9: last ten years, which is when we seriously invested in robotics,
Speaker 9: that we created hundreds of thousands of new jobs and
Speaker 9: new job types. And there's been no employer in the
Speaker 9: United States that has employed more people than Amazon ten years.
Speaker 9: I mean, that's and that's the power of efficiencies and
Speaker 9: building your robots in way that's applied and real that
Speaker 9: actually augments the human potent.
Speaker 6: All Right, my brother Sam, I like a dog with
Speaker 6: a bone. So does that mean ten years out it
Speaker 6: could be less jobs or we just don't know, or
Speaker 6: you don't think that's the case, Well you have.
Speaker 5: To think about it.
Speaker 9: I mean there's jobs and there's tasks, right, so we
Speaker 9: of course we're changing the nature of tasks. Like I'm
Speaker 9: very bullish on eliminating every menial, mundane and repetitive job
Speaker 9: out there. Nobody wants to do that, so we were
Speaker 9: going to change those tasks one hundred percent, but we
Speaker 9: can again, as history has shown, we continue to create
Speaker 9: jobs right with the goal of two things. Can you
Speaker 9: have it all? Can you be more productive which means
Speaker 9: more efficiency, and can you also create a safer environment
Speaker 9: for employees? And we're actually doing both. That's what history
Speaker 9: has shown. In the last ten years. We have create
Speaker 9: better than thirty percent reduction in our overall recordable injury
Speaker 9: rate over the last five years because of our robotics
Speaker 9: and also much more efficient. For example, our latest generation
Speaker 9: film at Center and shreport is twenty five percent more
Speaker 9: phishing the order.
Speaker 5: So you can't have it all, but you have to
Speaker 5: build your robotics in the right way that empowers people.
Speaker 2: We're speaking with Ty Brady, chief technologist at Amazon Robotics.
Speaker 2: When we think about hiring for these one off or
Speaker 2: seasonal events like the holiday season or Amazon Prime Day,
Speaker 2: I'm wondering how you're putting pencil to paper right now
Speaker 2: and thinking about those numbers and to what extent automation
Speaker 2: has reduced Amazon's dependency on seasonal or hourly labor for
Speaker 2: holidays for Prime Day. What does that look like or
Speaker 2: what will that look like this year next year.
Speaker 9: Well, it's the same philosophy of empowering employees, whether they're
Speaker 9: temporary or the full time employees with the world's best
Speaker 9: machines that help them do their job.
Speaker 5: It's the same philosophy. I'm really proud of the.
Speaker 9: Fact that this year we're going to from more than
Speaker 9: two hundred and fifty thousand temporary jobs for our employees
Speaker 9: to come in during the holiday season. Those are good
Speaker 9: paying jobs. I'm really happy about that, really pleased with that.
Speaker 9: And I'm really pleased with the work that are women
Speaker 9: than men have done in the robotics field, designing the
Speaker 9: pioneering these new physical AI systems that help them do
Speaker 9: their jobs better.
Speaker 6: I got to say, one thing that I've been thinking
Speaker 6: a lot about is what's going on overseas, whether it's China,
Speaker 6: whether it's Japan. Bloomberg has done some reporting about service
Speaker 6: industries in Japan because they have a labor shortage that
Speaker 6: they are leading increasingly on robotics. Have you been over
Speaker 6: there and looking at what they're doing, And I'm just
Speaker 6: curious if you're seeing some things that are pretty impressive,
Speaker 6: and that the US, as a creator of things or
Speaker 6: its role in the robotics industry, has to keep a
Speaker 6: watching what's going on in other countries.
Speaker 4: Yeah.
Speaker 9: I think it's easy, especially in robotics, to get distracted
Speaker 9: about what other people are doing. I think anybody can
Speaker 9: make a YouTube video. I think anybody can kind of
Speaker 9: pop in and overflate something. But if you come into
Speaker 9: our world, our world is a lot about application. Our
Speaker 9: world is the re reality.
Speaker 3: All right.
Speaker 6: We're talking with Ty Brady, chief technologist Robotics at Amazon,
Speaker 6: of course are our shot for that's the world of technology.
Speaker 6: We're talking a lot about technology. Stuff happens, and we're
Speaker 6: hoping we can get tie back. Just to finish up
Speaker 6: this conversation.
Speaker 4: Maybe the robots are using all the Wi Fi.
Speaker 6: Robots, Like, I don't like what it is.
Speaker 4: That is a connectivity thing though.
Speaker 6: Well it fees into the path right like you.
Speaker 4: It's all question about resources.
Speaker 6: Get charge These puppies can't just plug them in right
Speaker 6: if there?
Speaker 4: I don't know we need recharging too.
Speaker 6: Okay, Yeah, it's called food and sleep. Yeah, for Tim,
Speaker 6: it's called robot food, food and sleep. You know what
Speaker 6: I will say, do we have tie back, could we
Speaker 6: grab them for twenty seconds? Tie twenty seconds forgive us
Speaker 6: your final thoughts here.
Speaker 5: Sorry about that, No, it's okay, let it go. I'm
Speaker 5: ready for you.
Speaker 6: Okay, twenty seconds. Just final thoughts for our audience because
Speaker 6: we got to run.
Speaker 5: So final thoughts.
Speaker 9: Are is that robotics when done the right way, when
Speaker 9: you reframe your relationship with machines, you can enable more productivity,
Speaker 9: create greater efficiencies, and create a more safer environment for employees.
Speaker 9: And this collaborative mindset that we've had that we've done
Speaker 9: for the last ten years really does make the day.
Speaker 6: Ty Brady over at Amazon, so appreciate it.
Speaker 4: Stay with us.
Speaker 2: More from Bloomberg Business Week Daily coming up after this.
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Speaker 6: We love talking to mayers.
Speaker 4: We do, we do.
Speaker 2: We also love talking quantum computing, and there is some
Speaker 2: news in quantum computing today. Google running an algorithm modents
Speaker 2: Willow quantum computing chip that can be repeated on a
Speaker 2: similar platform and outperformed classical computers. We spoke a little
Speaker 2: bit about this with that love though earlier. The folks
Speaker 2: in Chattanoa, ten I see, I've been thinking a lot
Speaker 2: about quantum computing for years. The first commercially available quantum
Speaker 2: network in the US was established there back in twenty
Speaker 2: twenty two. Back with us is Mayor Tim Kelly. He's
Speaker 2: an independent. He's the Mayor of Chattanooga, Tennessee. Also with
Speaker 2: us as Janet Rayberg. She's the president and CEO elect
Speaker 2: of EPB, formerly known as the Electric Power Board of Chattooga,
Speaker 2: provides energy, internet, phone, and more in and around the
Speaker 2: Chattanooga area. They both join us here in the Bloomberg
Speaker 2: Interactive Brokers Studio. We should note that last year Bloomberg
Speaker 2: Philanthropy's named Chatanooga one of twenty five cities selected for
Speaker 2: its American Sustainable Cities Program. Bloomberg Philanthropies is founded and
Speaker 2: supported by Michael R. Bloomberg, the founder and majority owner
Speaker 2: of Bloomberg LP, and Chattanooga Sustainable Cities program is still ongoing.
Speaker 2: Chattanooga also part of the Bloomberg Harvard Leading City Procurement
Speaker 2: Reform program.
Speaker 6: We're big Wilievers in full disclosure. Great to have both
Speaker 6: of you here in studio with Tim and me. Mayor Kelly,
Speaker 6: I just have to first ask you a broad question,
Speaker 6: because we do want to talk a lot about quantum
Speaker 6: computing and energy in general, because there's just so much
Speaker 6: going on the environment today. How is it in terms
Speaker 6: of running your city being a mayor in a political
Speaker 6: environment that's a tough one, an economic environment that may
Speaker 6: be tough.
Speaker 10: Yeah, it's tough, but you know, running cities is an
Speaker 10: eminently practical exercise. And I will say, you know, our
Speaker 10: mayor's races are nonpartisan. They always have been, and I stayed.
Speaker 11: In that lane. Again.
Speaker 10: I mean, I'm not here to catalog my political beliefs.
Speaker 10: They're pretty confusing to most people anyway. I'd say, you know,
Speaker 10: Republicans think I'm a Democrat, and Democrats think I'm a Republican.
Speaker 10: I'm probably doing a pretty good job. So you know,
Speaker 10: I look, that has served me well in this environment,
Speaker 10: because again I believe, as does a lot of folks
Speaker 10: of Bloomberg, as do rather, but that cities are really
Speaker 10: the foundation of our economy. I swear ninety percent of
Speaker 10: the GDP's generateds we're all innovations generated. So I'm focused
Speaker 10: on whatever is best for Chattanooga, so I can work
Speaker 10: and have managed to work with people on both sides
Speaker 10: of the aisle, and you know, in the best interest
Speaker 10: of my city.
Speaker 2: Do you find yourself getting pulled into the social issues
Speaker 2: that seem to define our era right now, the stuff
Speaker 2: that does dominate cable news, whether you're talking about the
Speaker 2: right or the left.
Speaker 10: Yeah, I mean I find myself, you know, I find
Speaker 10: people attempting to pull me into those But I think
Speaker 10: I've gotten pretty good at wrestling my way out of
Speaker 10: them and trying to just translate back into simple terms.
Speaker 10: You know, is this what's best for the city? You know,
Speaker 10: does it work or does it not work? I mean,
Speaker 10: sometimes you can't avoid those political issues. It's not as though,
Speaker 10: you know, I don't have my own beliefs. But again,
Speaker 10: I think you, just as a mayor, have to take
Speaker 10: a thoroughly practical approach to what's going to work best
Speaker 10: for the city.
Speaker 6: All right, So when you think about what's best for
Speaker 6: the city, let's talk about that. Because you are on
Speaker 6: the ground talking to people what they need, what you
Speaker 6: need to make sure you have a good economy, strong economy,
Speaker 6: not just today but in the future. That quantum computing
Speaker 6: that you made it back in twenty twenty two, tell
Speaker 6: us about kind of give us an update or for
Speaker 6: someone who didn't hear the conversation when you were last
Speaker 6: on with this kind of where you guys are with this.
Speaker 10: So I'll give you the cliff notes version, which is
Speaker 10: that you know, we took advantage of a large federal
Speaker 10: low interest loan way back when during Clinton and Gore
Speaker 10: to put in a giant municipal fibre network, and that
Speaker 10: gave us the first and fastest municipal fiber network in
Speaker 10: the country. We had a lot of folks move in
Speaker 10: during COVID because you know, you can get one gig
Speaker 10: of symmetrical speed for sixty seven.
Speaker 11: Bucks a month. Yeah, pretty great.
Speaker 10: You can get twenty five gigs of speed at your
Speaker 10: house in Chattanooga. But it turns out that you can
Speaker 10: also do quantum computing on large loops of dark fiber,
Speaker 10: one particular type that uses photons and trapped ions, which
Speaker 10: is where ion Q began to become interested in Chattanooga.
Speaker 11: So we opened and Janet can talk more about it.
Speaker 10: The first commercially available quantum network, and it is starting
Speaker 10: to attract a lot of investment and attention.
Speaker 2: So Janet, come on in here, because one thing that
Speaker 2: we're trying to understand is what the practical applications of
Speaker 2: quantum technology are. We spoke with ed Loo the cost
Speaker 2: of our Bloomberg Tech program a little earlier, and Carol agreed,
Speaker 2: I mean you thought healthcare first, he said, healthcare Also,
Speaker 2: this is one area of application, but it's still kind
Speaker 2: of the world where we're thinking about what this tech
Speaker 2: can do, not necessarily seeing what it can do. Have
Speaker 2: we seen any material things be developed as a result
Speaker 2: of this technology and what you're doing in Chattanooga.
Speaker 8: Yeah, So ian Q has been working on a lot
Speaker 8: of different type of application with different industry, and so
Speaker 8: we were interested because we're in an electric company and
Speaker 8: so we have all the data for them to help
Speaker 8: us optimize our grid. So we're doing a partnership actually
Speaker 8: with Ionq, Nvidia, and Oakridge National Lab as a full
Speaker 8: way partnership to help do use hybrid computing until quantum
Speaker 8: computing can you get to where it needs to be
Speaker 8: to help us with some great optimization problem that we
Speaker 8: can't solve today.
Speaker 6: In terms of energy demands tell us about that. That
Speaker 6: is like what you are seeing front and center. We
Speaker 6: know the AI conversation narrative has moved from the spend
Speaker 6: and chips and so on and so forth, like to basically,
Speaker 6: all right, do we have enough power to do all
Speaker 6: of this? And there is certainly a power scramble among
Speaker 6: the big hyper scalers. What are you seeing on that front?
Speaker 8: Yeah, and I think that's a nationwide you know, issue
Speaker 8: with the energy problem.
Speaker 6: And as AI gets.
Speaker 8: Better as an energy problem, right, Yeah, I mean, as
Speaker 8: AI gets better and better, the more energy that it's
Speaker 8: going to need.
Speaker 6: And so that's where quantum comes in.
Speaker 8: Very important to the part of that solution is that
Speaker 8: quantum computer, once it gets to the phase that it
Speaker 8: needs to be, is it can solve things at a
Speaker 8: much faster rate, which uses less energy than a classical
Speaker 8: computer because it can do things in parallel versus sequential
Speaker 8: as a classical computer.
Speaker 2: Today, Where do you get the energy that you sell
Speaker 2: to people in and Aroundchattanoga.
Speaker 8: Yeah, so we buy it from TVA Tennessee Valley Authority,
Speaker 8: and so they generate the power and we distribute it
Speaker 8: to our customers.
Speaker 4: How do they generate it?
Speaker 8: They have a diverse mix of portfolio, from hydro, different
Speaker 8: types of renewables to natural gas, and so you know
Speaker 8: they're continuing to look at other options.
Speaker 4: Do you see that mixed?
Speaker 10: Go ahead, now, I'm just going to say they're also
Speaker 10: very much on the front foot in terms of advanced
Speaker 10: new Do you.
Speaker 4: See that mix? This is either of you.
Speaker 2: Do you see that mixed changing and focusing less unrenewables
Speaker 2: more on nuclear as a result of the changes out
Speaker 2: of Washington.
Speaker 10: I think you're going to see that, you know, and again,
Speaker 10: regardless of your political affiliation, if you just kind of
Speaker 10: look at.
Speaker 11: The math, there's no way around nuclear, right.
Speaker 10: I do think they are giving us or EPB more
Speaker 10: latitude to generate some of our own power because of
Speaker 10: the anticipated demands. And I think we still have a
Speaker 10: lot of headway on solar, So I mean, I think
Speaker 10: we'll contain, and we've got a lot of things we
Speaker 10: can do with hydro. We're going to actually start using
Speaker 10: biogas in our wastewater treatment plant to generate electricity. So
Speaker 10: we're looking at any in all ways that we can generate.
Speaker 6: Because my understanding when we talk about SMR as the
Speaker 6: small modular reactors it's ten fifteen.
Speaker 2: Will Wade reminds us who covers this here at Bloomberg News,
Speaker 2: that we are not there right now, it's.
Speaker 10: A while, we're not, but we have a pretty significant
Speaker 10: nuclear footprint with TVA already in the times.
Speaker 6: So what would you tell people who are still nervous
Speaker 6: when it comes to the nuclear footprint that you guys have.
Speaker 6: You know what, you know, fine, people do it, okay,
Speaker 6: do it across the country or do it in another country.
Speaker 6: But you know the feeling here.
Speaker 4: I mean, I grew up in the next to a
Speaker 4: nuclear power planet. I'm fine, right, I'm a little weird.
Speaker 6: But what would you say about that?
Speaker 11: I mean, the technology has come a long long way. Yeah,
Speaker 11: that's what I would say. Man, I'd say, go do
Speaker 11: your research, do your homework. They're not.
Speaker 10: I mean, that's why we have these discussions, That's why
Speaker 10: we have the fears. But but there's just not absolute fusion.
Speaker 10: I will say the state in the University of Tennessee
Speaker 10: is also working very very hard on fusion technology.
Speaker 11: Absent that breakthrough, there's really not.
Speaker 6: That's what I'm waiting for.
Speaker 2: When we're talking about quantum today and we're talking about Google,
Speaker 2: we're talking about Silicon Valley. How do you get people
Speaker 2: to think about Chattanooga, Tennessee and not Silicon Valley, not
Speaker 2: New York City, not Austin, Texas when they're thinking about
Speaker 2: where they want to live to have a job in technology.
Speaker 11: Coming on Bloomberg is it's a great first step.
Speaker 8: No.
Speaker 11: I mean, look, we talked about this all the time.
Speaker 10: It's a it's a mid size southern city with kind
Speaker 10: of a funny name, and there's a bit of cognitive
Speaker 10: dissonance there. So you know, look, we are out telling
Speaker 10: the story. I mean, I was just in Detroit last
Speaker 10: week at a sustainable mobility conference. We were at the
Speaker 10: Quantum World Congress. I mean, at some point it's you know,
Speaker 10: the evidence is mounting.
Speaker 11: We are it's not just smoke. We are doing the
Speaker 11: work and it's working. Is it?
Speaker 5: Is it?
Speaker 2: If you build it, they will come mentality. I think,
Speaker 2: so have they come?
Speaker 11: Yes, they have come.
Speaker 10: I mean again, we had you know, we now have
Speaker 10: independent verification that you know, ten twelve thousand people moved
Speaker 10: to Chattanooga during the pandemic very you know, degree talented
Speaker 10: people that could work remotely. And I think again, our job,
Speaker 10: my job is mayor, is to help break that glass
Speaker 10: ceiling so that we have the level of business investment
Speaker 10: and again can build up our academic horsepower to be
Speaker 10: able to sustain those knowledge economy jobs.
Speaker 6: Jenna, you know, when we think about quantum computing, we
Speaker 6: spend so much time to talking about you know, large
Speaker 6: language models and generative AI and kind of where that's
Speaker 6: going agentic AI. You just talked about the power or
Speaker 6: aspect are the use of less power when it comes
Speaker 6: to quantum computing. But I mean, should our conversation be
Speaker 6: shifting in terms of what we are having for an
Speaker 6: investing audience when we talk just so much about AI
Speaker 6: generally versus quantum.
Speaker 8: Well, I think that with quantum computer, when it gets
Speaker 8: to you know, the level it needs to be, you
Speaker 8: can team it up with AI and get even more
Speaker 8: powerful algorithm that comes out of it to be able
Speaker 8: to solve more complex problems. So I don't think it's
Speaker 8: one or the other. I think it's going to be
Speaker 8: a combined of you know, how do you combine that
Speaker 8: and use less energy and be able to build algorithm
Speaker 8: more efficiently.
Speaker 6: So help me, because when we talk about the data
Speaker 6: center build out, so does that go hand in hand
Speaker 6: with the build out of quantum computing is that part
Speaker 6: of it?
Speaker 8: So right now, it's you know, the we're building a
Speaker 8: quantum computer to kind of learn more and be able
Speaker 8: to help accelerate and advance that technology with companies like
Speaker 8: ion Q, and I think once it gets to where
Speaker 8: it needs to be, then well we can team it
Speaker 8: up with AI.
Speaker 10: Okay, yeah, yeah, and many of the implications with quantum
Speaker 10: asking basic quest because I feel like we spend so
Speaker 10: much time talking about the AI, but this is something that.
Speaker 6: Increasingly is coming into the dialogue.
Speaker 4: Yeah.
Speaker 10: Now, I'm just going to say the logistics is a
Speaker 10: huge vertical and chatt near go as well. And I
Speaker 10: think the implications for quantum for logistics have huge implications
Speaker 10: for lower power demand and a lower carbon footprint, right
Speaker 10: because you're going to waste a lot less time getting
Speaker 10: stuff from A to B.
Speaker 6: Right with root optimization we're going to have to do
Speaker 6: because we talk about like the power drag or the
Speaker 6: power demand and the cost. Mayor Kelly, I'd be remiss
Speaker 6: not to ask you you are trying to build a
Speaker 6: city where everyone has an opportunity to thrive and prosper
Speaker 6: We talk so much about the case shaped economy. There's
Speaker 6: a lot of people who aren't thriving and prospering in
Speaker 6: this environment. Thirty five seconds. What's a message to send
Speaker 6: to everybody.
Speaker 10: Well, we are working very hard to reform our workforce
Speaker 10: fillment system so that we so we don't leave folks behind.
Speaker 10: And I think we have some significant opportunities to do that,
Speaker 10: and we are in the mist to doing that. Again,
Speaker 10: it's tough out there, yeah, and I think it's going
Speaker 10: to fall more to the state government into philanthropy frankly,
Speaker 10: to kind of take up the slack in the meantime.
Speaker 11: But I mean, we have to play the long game.
Speaker 10: And the long game is we need some significant change
Speaker 10: to the way that we do education workforce development in
Speaker 10: this country so that we don't leave people behind.
Speaker 4: Yeah.
Speaker 6: I just feel like in terms of education, we're starting
Speaker 6: to think about that. Yeah, come back soon. I'd love
Speaker 6: to kind of continue this conversation if we may. Mayor
Speaker 6: Tim Kelly of Chattanooga, Tennessee, and Janet Raeberg, she's the
Speaker 6: President's CEO Elective EP be joining us right here in
Speaker 6: our Bloomberg Interactive Broker studio.
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