Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: Perhaps no company embodies the promise of AI more than
Speaker 2: in Vidia.
Speaker 1: Very quick story of in Nvidia is that it used
Speaker 1: to make video game chips that gamers really liked. It
Speaker 1: turned out those things we're good for AI, and now
Speaker 1: it's one of the biggest companies in the world.
Speaker 2: Joshua Breustein is a technology editor at Bloomberg BusinessWeek. He's
Speaker 2: covered in Videa's stunning rise and says the company is
Speaker 2: now on the cusp of its next chapter.
Speaker 1: And video doesn't a funny place because, on the one hand,
Speaker 1: it is in a great position. It's very good at
Speaker 1: making these chips that everyone wants.
Speaker 2: Microsoft, Meta, Amazon, pretty much all the big tech companies
Speaker 2: have collectively announced hundreds of billions of dollars of investment
Speaker 2: in AI, and much of that investment will go straight
Speaker 2: to buying in Vidia's product. In some ways, it's a
Speaker 2: dream position for a company, but being at the top
Speaker 2: also means there's a law way to fall. In Vidia
Speaker 2: got a glimpse of what that could look like in
Speaker 2: late January, when the Chinese AI startup deep Sea released
Speaker 2: its R one chatbot. Deep Seek's developers say their model
Speaker 2: uses a fraction of the resources of American competitors. That
Speaker 2: news rattled assumptions about how much computing power and how
Speaker 2: many in Nvidia chips the AI revolution will actually need.
Speaker 3: The main event yesterday one single name in video in
Speaker 3: video getting absolutely hammered yesterday session down by seventeen percent,
Speaker 3: a record five hundred and ninety three billion dollars taken
Speaker 3: off the market cap.
Speaker 2: It was the largest route in market history, and Joshua
Speaker 2: says the risk of something like that happening again is
Speaker 2: something in Vidia's founder, Jensen Huang takes seriously.
Speaker 1: Huang looks at the history of semiconductors and knows that
Speaker 1: when you see a big transition in tech, the infrastructure
Speaker 1: companies do really well at the beginning of it, and
Speaker 1: then their products become commoditized and they crash.
Speaker 2: I'm David Gera, and this is the big take from
Speaker 2: Bloomberg News today. On the show, in Vidia's scrambled to
Speaker 2: future proof it's technology and hold on to its top spot. Today,
Speaker 2: the semiconductor manufacturer in Vidia is one of the largest
Speaker 2: companies in the world by market cap. Bloomberg's Joshua Brustein
Speaker 2: says its story starts more than thirty years ago with
Speaker 2: its CEO, Jensen Huang.
Speaker 1: He just really is known within Nvidia in the wider
Speaker 1: industry as kind of a force of nature. He's a
Speaker 1: very hard charging boss. He is very enthusiastic about the
Speaker 1: technical aspects of running a semiconductor company.
Speaker 2: To put it simply, he's a nerd.
Speaker 1: But not in the way that I think a lot
Speaker 1: of people think of tech nerds, where it's like a
Speaker 1: lot of talk about our computer is gonna become sentient,
Speaker 1: and you know, will they lead to the end of
Speaker 1: human existence. It's more kind of like how many transistors
Speaker 1: can we fit on this chip? And is there a
Speaker 1: new architecture we can use to do it even better?
Speaker 1: So he's not doing the science fiction thing. He's doing
Speaker 1: the engineering thing.
Speaker 2: Joshua says. Doing the engineering thing has been at the
Speaker 2: core of Nvidia's business since the beginning.
Speaker 1: So the founders thought that they saw a niche for
Speaker 1: making a specific kind of chip that would be really
Speaker 1: good at rendering graphics, primarily for video games. The idea
Speaker 1: was that there's general use chips, but if we focus
Speaker 1: on this one use, we can find a good niche
Speaker 1: and maybe we can you know, make a couple of
Speaker 1: tens of millions of dollars.
Speaker 2: And it was in pursuit of that goal that in
Speaker 2: Vidia develop was a key breakthrough in chip technology.
Speaker 1: The basic way to put this is that Intel makes
Speaker 1: chips that are general use chips that are very powerful
Speaker 1: and that do things sequentially. They do a task by
Speaker 1: doing one part of the task, then the next part
Speaker 1: of the task. In Vidia's chips take a task, they
Speaker 1: break it up into a bunch of little parts, and
Speaker 1: they do it all at once. There's a forthcoming book
Speaker 1: about in Vidia where they describe it as instead of
Speaker 1: having a truck that drives around the city making deliveries,
Speaker 1: they buy a bunch of motorcycles. Each motorcycle carries one package,
Speaker 1: and they go to everyone's house all at once. So
Speaker 1: that turns out to be a very good way to
Speaker 1: do modern AI, which is based on these things called
Speaker 1: neural networks, which pass information through a whole bunch of
Speaker 1: nodes in parallel.
Speaker 2: But the wider use and mass market appeal of Nvidia
Speaker 2: was still years away, and Joshua says the company went
Speaker 2: through some rocky times, like.
Speaker 1: A lot of companies in the semiconductor industry. It went
Speaker 1: through a series of existential crises. It would release a chip,
Speaker 1: there'll be something wrong with it. It almost went out of
Speaker 1: business several times early in its existence. This is part
Speaker 1: of company lore. Jensen likes to say that over always
Speaker 1: thirty days from going out of business.
Speaker 2: In Video sought to widen its customer base. The goal,
Speaker 2: Joshua says, was to take its video game graphics cards,
Speaker 2: which were getting faster and faster, and sell them to
Speaker 2: non video game clients.
Speaker 1: The problem was doing this required making the chips more expensive,
Speaker 1: so it started doing things that made its core product
Speaker 1: worse in the hopes that someone would find some use
Speaker 1: for it.
Speaker 2: And eventually someone did. In Nvidia built its own computer
Speaker 2: language called Pudha, which allowed developers to maximize the potential
Speaker 2: of their GPU chips, and in Vidia's coding language and
Speaker 2: in Vidia's chips became the standard hardware for early pioneers
Speaker 2: of what's called deep learning. That's a branch of computer
Speaker 2: science that relies on those neural networks modeled after the
Speaker 2: neurons in the human brain. Early on, Joshua says, the
Speaker 2: commercial applications of deep learning weren't yet clear, but Nvidia
Speaker 2: saw an opportunity.
Speaker 1: It just happened that in Vidia saw the seeds of
Speaker 1: its product being good for this use and really pursued
Speaker 1: it from a very early point and was very effective
Speaker 1: at building this technology.
Speaker 2: Then OpenAI's chat GPT took the world by storm, and
Speaker 2: so suddenly every player looking to invest in AI was
Speaker 2: in need of Nvidia's chips.
Speaker 1: In Nvidia now finds itself having the thing, maybe not
Speaker 1: that customers want the most, but it has a thing
Speaker 1: that Meta wants the most, Google wants the most, Microsoft
Speaker 1: wants the most, and that puts it in an incredibly
Speaker 1: powerful position.
Speaker 2: For the last few years, the tech Titan seems certain
Speaker 2: that the AI future would be powered by massive data
Speaker 2: centers filled with Nvidia chips, and the Frenzy showed just
Speaker 2: how quickly the fortunes of semiconductor manufacturers can change. At
Speaker 2: the start of twenty twenty, Intel's market cap was roughly
Speaker 2: twice the size of Nvidia. Today, in Vidia is around
Speaker 2: thirty times more valuable, and Joshua says the precariousness of
Speaker 2: being on the cutting edge of tech is something that
Speaker 2: weighs heavily on Nvidia's CEO, especially after the deep Seek
Speaker 2: route in late January.
Speaker 1: There's some jitteriness now, not only within video but throughout
Speaker 1: the economy that like, are we reaching the end of
Speaker 1: this stage of the AI boom? I mean, people who
Speaker 1: are pessimized it will tell you we're reaching the point
Speaker 1: where the bubble pops. Other people will say it's time
Speaker 1: to move on from building the foundation to actually creating
Speaker 1: something more than that. And because expectations are so high,
Speaker 1: if this isn't a really really big success, even if
Speaker 1: it's just like a pretty good success, then in Vidia
Speaker 1: could be in kind of a tricky spot. And that's
Speaker 1: sort of the water that it's navigating right now.
Speaker 2: Joshua Sayshuog is now scrambling to find new customers and
Speaker 2: markets for Nvidia's technology.
Speaker 1: His plan for doing that is to do more than
Speaker 1: just make the hardware that everyone builds their tech on
Speaker 1: top of, but to actually be involved in building a
Speaker 1: little bit more of that tech, both which brings that
Speaker 1: tech along faster, increasing the demand for the company, and
Speaker 1: which makes it harder to get rid of Nvidia and
Speaker 1: go with something else.
Speaker 2: So what is the company planning for its future? That is,
Speaker 2: after the rate, Even though in Vidia is the world's
Speaker 2: most valuable chip maker. It's CEO Jensen Huang is always
Speaker 2: selling as he was back in January Welcome to CUS
Speaker 2: at the industry's biggest trade show in his trademark leather jacket.
Speaker 2: Do you like my jacket? Blimber's Joshua Brustein says one
Speaker 2: of the markets Swang is trying to develop is what
Speaker 2: he refers to as physical AI, and.
Speaker 1: That's basically just instead of chatbots that operate on the Internet,
Speaker 1: it's stuff that operates in the real world.
Speaker 3: With this physical AI, there are many downstream things that
Speaker 3: we could do as a result.
Speaker 1: We could do synthetic so you have robotics factories that
Speaker 1: would be automated self driving cars. Obviously, that's been a
Speaker 1: big thing for Nvidia for about a decade, and if
Speaker 1: they can get all of those things to happen sooner,
Speaker 1: then those are enormous markets that they can.
Speaker 2: Unlock, Joshua says. Another big strategy is developing new software
Speaker 2: technology in Vidia could sell not only to their existing customers,
Speaker 2: but tech that also could be used to unlock AI
Speaker 2: applications in some of the world's biggest industries, like healthcare.
Speaker 1: That would be not only hospital systems but also pharmaceutical
Speaker 1: companies doing drug discovery, maybe robotic surgery, but also just
Speaker 1: kind of the administration of hospitals.
Speaker 2: Joshua Siswang is pursuing this with a lot of urgency.
Speaker 1: So what he's doing now is really trying to almost
Speaker 1: will into existence all these AI applications that you'll hear
Speaker 1: people say are coming soon, are coming down the road.
Speaker 1: He wants those things to come in six months, not
Speaker 1: in seven years.
Speaker 2: It's not just will, it's also money, Joshua says. In
Speaker 2: Vidia is investing in all kinds of companies that are
Speaker 2: trying to realize new commercial applications for AI.
Speaker 1: Not so much in the hopes that they'll invest in
Speaker 1: a startup that's now worth a million dollars that will
Speaker 1: be worth a billion dollars, although they wouldn't mind that great,
Speaker 1: but that they want to make sure that they are
Speaker 1: having as many irons in the fire of future in
Speaker 1: Vidia customers, Like they just want a startup that is
Speaker 1: now small to be an enormous in video customer, and
Speaker 1: so they invest in and work with lots of startups
Speaker 1: in many different fields to try to form those relationships
Speaker 1: and to have them like working on in video hardware
Speaker 1: from the very beginning.
Speaker 2: You mentioned that in Vidia makes its own software. It's
Speaker 2: not just making chips, but it's serving dips.
Speaker 1: There are kind of other.
Speaker 2: Things augmenting the kind of core of its business model.
Speaker 2: What is the appetite so much as we know it
Speaker 2: for that other stuff. Are we at a point at
Speaker 2: which tech companies AI companies really just want the chips
Speaker 2: they don't really care about that stuff. Or is the
Speaker 2: other stuff that in video makes appealing to them? Do
Speaker 2: they need it? Do they want it? Is that catching on?
Speaker 1: I think that that question is like a core dynamic
Speaker 1: to watch within video right now. There's a metaphor that
Speaker 1: computer scientists use a lot, which is like a stack
Speaker 1: of technologies. You start at the bottom, that's the chips,
Speaker 1: all the way at the top is like whatever software
Speaker 1: the user's using, and in videos, building upwards on the
Speaker 1: stack and talking to a lot of startups who are
Speaker 1: in video customers, the enthusiasm starts very high at the
Speaker 1: bottom and diminishes as they go up. So they really
Speaker 1: want the chips, and like the software that makes the
Speaker 1: chips do the basic functions they're really into. When it
Speaker 1: gets to like the NVIDIAI models, they'll kind of politely
Speaker 1: acknowledge that in video makes those but like they kind
Speaker 1: of wouldn't build that stuff, So it's hard to tell
Speaker 1: where that line is. And in video will say, well,
Speaker 1: we're happy as long as they're you know, like we
Speaker 1: want them to use whatever is useful to them. But
Speaker 1: they're also aggressively trying to sell you the whole computer.
Speaker 1: So it's interesting to watch how that plays out.
Speaker 2: I think in VideA is a proxy for a lot
Speaker 2: of people for AI generally. I think for investors, it's
Speaker 2: a way to get into this this sector, this part
Speaker 2: of the tech sector. What is its success or failure
Speaker 2: navigating say these next twelve months going to say about
Speaker 2: the industry more broadly, it's in other words, how good
Speaker 2: is it as a proxy for where AI is and
Speaker 2: where it's heading.
Speaker 1: So I think that on the one end, if you
Speaker 1: saw like a real retrenchment in the construction of data centers,
Speaker 1: a real lack of demand in video chips, then that
Speaker 1: would be really bad for in video. It'd be bad
Speaker 1: for video share price and all those investors who are
Speaker 1: hoping to get in AI, and it would indicate that
Speaker 1: maybe AI has been overhyped over the last couple of years.
Speaker 1: On the other end, you could see full speed ahead,
Speaker 1: all of these things are getting built. In video is
Speaker 1: still doing really well, and there would still be the
Speaker 1: question of when we get past the building out phase,
Speaker 1: what happens next? And I think even in video will
Speaker 1: tell you like, that's not going to We're not going
Speaker 1: to know that in twelve months. It will tell you
Speaker 1: that it will be everywhere, but the world will change
Speaker 1: more slowly than maybe the next year, and so you'll
Speaker 1: have to just continually watch, like is AI progressing, and
Speaker 1: if it is in video will likely be in a
Speaker 1: central role, and if it's not, then you know, we
Speaker 1: may have to reassess some things.
Speaker 2: Is there a moment? Are there going to be moments
Speaker 2: in the near future when we're likely to learn more
Speaker 2: about what he has planned?
Speaker 1: Yeah? One is coming up actually next week and Vidia
Speaker 1: has an annual conference in which it sort of takes
Speaker 1: over downtown San Jose. Almost a thousand other tech companies
Speaker 1: come and present how they interact with Nvidia. Jensen will
Speaker 1: give a big keynote in which he will lay out
Speaker 1: the vision. I'm sure we'll hear a lot about his
Speaker 1: pet projects at that point, and given the potential moment
Speaker 1: of inflection. We're in for AI. Generally, it will be
Speaker 1: an interesting time to kind of take in video's temperature
Speaker 1: and see how the company responds to what could be
Speaker 1: a tricky moment.
Speaker 2: He'll don the leather jacket and yes, always done to
Speaker 2: the leather jacket.
Speaker 1: If he has on a different jacket, then we'll know
Speaker 1: something is big and changed.
Speaker 2: This is the Big Take from Bloomberg News. I'm David Gera.
Speaker 2: This episode is produced by Alex Tye and David Fox.
Speaker 2: It was edited by Tracy Samuelson, Mark Million, and our
Speaker 2: senior editor, Elizabeth Ponso. It was fact checked by our
Speaker 2: editorial team and mixed and sound designed by Alex Sigura.
Speaker 2: Our senior producer is Naomi Shaven. Our executive producer is
Speaker 2: Nicole Beamster. Board Sage Bauman is Bloomberg's head of Podcasts.
Speaker 2: If you liked this episode, make sure to subscribe and
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