Speaker 1: From our heart.
Speaker 2: We're Innovation, Money and Power Collie in Silicon Valley, NBN.
Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.
Speaker 3: Live from sunny San Francisco and Caroline Hyde.
Speaker 4: And our Ed Ludlow.
Speaker 5: This is a special edition of Bloomberg Technology. Coming up
Speaker 5: will bring you live coverage from our technology event as
Speaker 5: we speak with the CEOs and visionaries that are driving
Speaker 5: change in Silicon Valley and beyond.
Speaker 3: Now at this hour, we're speaking with the CEOs of Arm,
Speaker 3: of Hugging, Face, of Writer, AI and more as part
Speaker 3: of our live special.
Speaker 4: And a lot more to come.
Speaker 5: We'll push your head to our keynote speakers later today.
Speaker 5: That includes Adam Newman, Whitney Wolf Heard, Evan Spiegel and more.
Speaker 4: And while it.
Speaker 5: May not be a surprise to anyone too, did it's
Speaker 5: certainly not a surprised to us. Artificial intelligence is probably
Speaker 5: the overriding theme of the event. It's AI everything, even
Speaker 5: in some cases if you're not an AI company.
Speaker 3: Yeah, I mean I think it has to be. Even
Speaker 3: if you're not the AI company at heart, you're thinking
Speaker 3: about how you adapt to it, push it forward and
Speaker 3: bring out the productivity. But Ultimately, how do we live
Speaker 3: up to the hype? The valuations are so extraordinary in
Speaker 3: the private markets, they've been pretty heavy in the public
Speaker 3: markets as well. Are we really seeing the level of
Speaker 3: producted divity and growth and real use cases?
Speaker 5: Do mindication that these events are always very interesting, very engaging.
Speaker 5: Everyone's very positive, But I would say in the background,
Speaker 5: there's a talent war, frankly, and people are running out
Speaker 5: of cash.
Speaker 4: So we've got to ask those difficult questions too.
Speaker 3: And geopolitics, how are you navigating the issue of China
Speaker 3: as well? So so much to talk about in here
Speaker 3: and the now. We're talking about one key infrastructure playing
Speaker 3: When it comes to artificial intelligence, we're of course going
Speaker 3: to be talking about the chip design firm ARM, which
Speaker 3: has really bounced offlows in terms of its share price
Speaker 3: throughout the trading of today. We're currently over the last
Speaker 3: two days down by one point few percent. Coming out
Speaker 3: after the bell with its earnings, tapid forecast head was
Speaker 3: what the market seemed to be focusing in on, even
Speaker 3: though they absolutely smashed it in terms of their fiscal
Speaker 3: fourth quarter numbers and their fourth first quarter. To look ahead,
Speaker 3: let's stick in to some of that caution with Renee
Speaker 3: has is the arm CEO. Renee wonderful to have time
Speaker 3: with you. And look, there does seem to be a
Speaker 3: worry about your full year forecasts? Are you being cautious?
Speaker 2: Well, thanks both for having me Ed and Caroline. We
Speaker 2: just came off a record year in terms of revenue.
Speaker 2: We were up twenty percent a little bit over twenty
Speaker 2: percent our fiscal twenty three from twenty twenty two, and
Speaker 2: we're actually forecasting even higher growth this year, north of
Speaker 2: twenty percent. And we also signaled to the markets yesterday
Speaker 2: that in twenty five, twenty six, twenty seven, we see
Speaker 2: that growth continuing. So we have incredible visibility to our
Speaker 2: business and we're very, very confident of growth rate going forward.
Speaker 5: We're just seeing your shares actually ticking to positive territory
Speaker 5: rene up now six tenths of one percent. The underlying
Speaker 5: story is the build out in AI infrastructure. Right, we're
Speaker 5: talking about data center powered GP by GPUs. Your numbers
Speaker 5: were good. Tell me about the underlying demand then about
Speaker 5: the long term and the addressable market you think is
Speaker 5: either intact or is not.
Speaker 3: Well.
Speaker 2: I think this AI buildout, as you describe, or maybe
Speaker 2: said another way, just expanding capacity to run these foundation models,
Speaker 2: to do more and more training, to do more and
Speaker 2: more inference.
Speaker 3: We really are only.
Speaker 2: At the very beginning because when you start to think
Speaker 2: about the capabilities that this could unleash, whether it's around healthcare,
Speaker 2: farmer research, productivity, gains, call centers, we're still in the
Speaker 2: very very early days. That all starts with having to
Speaker 2: do this level of training and inprints in the cloud,
Speaker 2: but it ultimately will find itself in every single edge device,
Speaker 2: whether that's a PC, your smartphone, your car, and whether
Speaker 2: it's all those devices I've mentioned from the data center
Speaker 2: to the edge devices. They all run on ARM. So
Speaker 2: we have incredible visibility to where this is all going,
Speaker 2: which is why we're very confident in the growth rates.
Speaker 2: They're also one of the big problems you've got with
Speaker 2: all of these AI data centers is around energy and power.
Speaker 2: So power efficiency being so key, it's what ARM is
Speaker 2: really good at. Increasingly we're seeing the most complex applications
Speaker 2: moving to ARM and most sophisticated training ship on the
Speaker 2: planet that was just announced Grace Blackwell, Well that's based
Speaker 2: on ARM.
Speaker 3: Okay, so you're managing to really think that you're going
Speaker 3: to be the server play as well as the PC play,
Speaker 3: the cell phone play, and I want to focus in
Speaker 3: on the cell phone play, Renee, because that's been where
Speaker 3: your bread and butter has been in history. How are
Speaker 3: we looking from a smartphone perspective? Is the market looking
Speaker 3: strong to you? We've had many a mixed message coming
Speaker 3: from China to MOD for example.
Speaker 2: Overall, what we've seen the smartphone market briftly for ARM
Speaker 2: has been quite a good growth rate in terms of royalties.
Speaker 2: Our version nine which is now being used in many
Speaker 2: of the premium mobile phones, that drives a higher royalty
Speaker 2: rate for ARM. There's also more complex CPUs that go
Speaker 2: into that that's also better for ARM and going forward carrolling.
Speaker 2: One of the things that we're seeing, and it's not
Speaker 2: just in smartphones, is that as these AI models are
Speaker 2: moving so fast, the hardware can't keep up with the software.
Speaker 2: The software innovation is happening so quickly that by the
Speaker 2: time the hardware is ready to run those models, everyone
Speaker 2: wishes they had more performance, they had more efficiency.
Speaker 4: So what does that mean for ARM?
Speaker 2: It's driving growth in our licensing activity. People are looking
Speaker 2: to do more and more design ships faster and faster,
Speaker 2: and that's all good for us going forward. So I
Speaker 2: think going forward you're going to see more and more
Speaker 2: innovation happening, not only in the smartphones, across all these
Speaker 2: edge devices.
Speaker 3: What's interesting in AY is it's hard to keep up
Speaker 3: with the pace of geopolitical change as well. The latest
Speaker 3: news coming that Huawei, of course is not going to
Speaker 3: have access to poll Kong to Intel chips. You were,
Speaker 3: of course a UK based company, but are affected by
Speaker 3: US policies. Has this impacted your business? The limitations of
Speaker 3: Huawei's access to chip designed to chip technology to licenses.
Speaker 2: Yeah, So that issue they referred to specifically was when
Speaker 2: Huawei was placed on the entity list I think twenty nineteen,
Speaker 2: twenty twenty, companies had to apply for a license to
Speaker 2: exempt them to ship to Huawei. So a number of
Speaker 2: companies asked for those licenses, they got those licenses. Now
Speaker 2: those licenses are being revoked. We don't follow in that
Speaker 2: category in any way, shape or form. We didn't apply
Speaker 2: for any licenses at the time to share. We complied
Speaker 2: with the export controls as they were laid out. So
Speaker 2: there's really a non event for us in terms of
Speaker 2: what you're seeing with Qualcoman or Intel.
Speaker 5: We are speaking live to the ARMS CEO, Renee has
Speaker 5: We're on the ground here at Bloomberg Tech in San Francisco.
Speaker 5: Last week, Renee Christiano mom was on the show telling
Speaker 5: Caroline and I, this is the year of the AIPC.
Speaker 5: You were asked about that on your earning school last
Speaker 5: night and you gave a slightly different answer. And maybe
Speaker 5: it's not the year of the AIPC more the twelve
Speaker 5: to thirty six month window. And you don't want to
Speaker 5: see just one PC supplier, you said you'd like to
Speaker 5: see two or three. What's your beef with Qualcom?
Speaker 1: Now?
Speaker 2: When I look at the PC ecosystem, one large ecosystem
Speaker 2: has already moved to ARM in a very big way.
Speaker 2: Apple is now one based on ARM. All the Apple
Speaker 2: silicon is based on ARM. And you see amazingly good
Speaker 2: products relative to what they've delivered, fantastic battery life, performance,
Speaker 2: thin and light, no fans. When you think about the
Speaker 2: Windows market, it's a very different market. It's highly fragmented.
Speaker 2: You have lots of different players. The ecosystem matters, the
Speaker 2: channel matters, price points matter, high end gaming machines versus
Speaker 2: low end devices that are like cloud enabled. So what
Speaker 2: does all that mean. It generally has meant that breath
Speaker 2: vendor choice, multiple options to provide a full scope is
Speaker 2: what matters. And what I'm hearing is over the next
Speaker 2: couple of years, the Windows ecosystem is going to be
Speaker 2: able to afford that. And I think over the next
Speaker 2: two three years, I do believe Windows Unarmed will be real.
Speaker 2: I think you'll see multiple players, multiple price points, multiple units,
Speaker 2: and I think you'll see meaningful market share that we
Speaker 2: start to gain the kind of performance you see in
Speaker 2: the other ecosystem. I think we'll find its way into
Speaker 2: the Windows ecosystem.
Speaker 4: Rennie, I wanted to talk about geography really quick.
Speaker 5: We're here in San Francisco, right there's a lot about
Speaker 5: Americas are in d focus on AI related chips.
Speaker 4: Are you seeing this sort of equivalent activity in.
Speaker 5: Europe, for example, any of your customers outside of those markets.
Speaker 2: Yeah, well I'm in San Francisco today too, so I
Speaker 2: will see you a little bit later. But in general,
Speaker 2: I think the geopolitics are something that all tech CEOs
Speaker 2: are now having to figure out and work with AI models,
Speaker 2: foundation models, sovereign clouds, thinking about what level of training
Speaker 2: takes place in a country, versus outside the country where
Speaker 2: the weights sit, et cetera. That these are all the
Speaker 2: kind of things that politicians have never really had to
Speaker 2: think about in the past. So we're involved in a
Speaker 2: lot of those conversations, whether that's in the United States,
Speaker 2: whether that's in Europe, and really just trying to understand
Speaker 2: it because any lawmakers in all these jurisdictions are just
Speaker 2: trying to figure it all out. And as I mentioned before,
Speaker 2: as the software and models are moving so fast, it's
Speaker 2: difficult for everyone to keep up. But we are central
Speaker 2: to all those discussions.
Speaker 3: Renee, what's been keeping up is your valuation?
Speaker 4: Boy?
Speaker 3: I mean, do you think there's too much exuberance around
Speaker 3: AI valuations out there? Are you going to make the
Speaker 3: most of it? By well, we talked to one point
Speaker 3: of listing in the UK too.
Speaker 2: Yeah, you know, I don't think about the valuations as
Speaker 2: much as I just think about the AI opportunity, which
Speaker 2: I frankly believe is undercalled in terms of just what
Speaker 2: it's going to mean relative to society and what it
Speaker 2: can do for our planet. I think again we are
Speaker 2: in very very early days in terms of the capabilities
Speaker 2: of what this can unleash for our society incredibly excited
Speaker 2: to be part of it. But I don't think we're
Speaker 2: part of a hype cycle at all. I think there's
Speaker 2: a lot of innovation taking place, and you know, frankly,
Speaker 2: the innovation that's taking place, any inventions that we're seeing,
Speaker 2: it's just breathtaking. So no, I don't personally view it
Speaker 2: as a hype cycle at all.
Speaker 5: They has I'm CEO really grateful you actually be here
Speaker 5: with us later today on site at Bloomberg Tech. Your
Speaker 5: stock open pretty low, and I think it's just a
Speaker 5: little bit higher now during the conversation we've had.
Speaker 4: Thank you so much.
Speaker 5: All Right, coming up on the program, we're going to
Speaker 5: be joined by Clem DeLong, CEO of Hugging Face. That's
Speaker 5: coming up next. Stay tuned, we'll be right back. Is
Speaker 5: Bloomberg Technology. Welcome back to this special edition of Bloomberg
Speaker 5: Technology live in San Francisco at the Bloomberg Tech event
Speaker 5: and artificial intelligence Surprise.
Speaker 4: Surprise is sort of the overarching theme.
Speaker 5: We've got a pretty good guest to talk about that
Speaker 5: with and discuss all things large language model with Clemed Along,
Speaker 5: CEO of Hugging Face. You made this prediction which we're
Speaker 5: going to hold you to account on that by the
Speaker 5: end of this calendar year, and I appreciate we're not
Speaker 5: even halfway. Source models would be equivalent to the best
Speaker 5: closed source models. Give us a status check of that
Speaker 5: prediction place.
Speaker 4: I think it's already happened.
Speaker 6: Open source now is better than closed source for most
Speaker 6: use cases. We've specialized customized models on the companies like
Speaker 6: data sets. I have my meta reband glasses here that
Speaker 6: are powered by Lammatri.
Speaker 4: Right.
Speaker 6: We've seen so many now use cases being powered by
Speaker 6: open source models, and most of the big tech companies
Speaker 6: are now publishing open models. Just last month, we've seen
Speaker 6: Apple releasing open models on hogging Face. We've seen Nvidia,
Speaker 6: we've seen Snowflakes, We've seen Data Bricks, we've seen Microsoft.
Speaker 6: All of them now are publishing open models.
Speaker 5: There maybe some people in attendance who don't agree with him,
Speaker 5: which is why I asked the question.
Speaker 3: Well, also Microsoft published one and then quickly with DURI
Speaker 3: some of the reporting because they hadn't stress tested the
Speaker 3: large language model enough. I hadn't whittled out some of
Speaker 3: the toxicity checks. In particular, how are you feeling about
Speaker 3: the way in which large language models are growing and
Speaker 3: the way in which governance is developing around it.
Speaker 6: Well, we're starting to see that the most important question
Speaker 6: is concentration of power. Right for such an important technology,
Speaker 6: you don't want a world where just a few companies
Speaker 6: are controlling.
Speaker 3: It, but that is the world we live in.
Speaker 4: I don't think so, I think more and more.
Speaker 6: What we're seeing is that with open source you can
Speaker 6: actually distribute power more and you want to reduce the
Speaker 6: gap between the most powerful companies and the rest of
Speaker 6: the world, not only other companies but policy makers, non profits,
Speaker 6: academia and all of that.
Speaker 4: And that's the purpose of open source.
Speaker 6: It reduces the gap between the most powerful companies and
Speaker 6: the rest of the world, and that's what creates kind
Speaker 6: of like a sustainable, balanced future for AI and technology.
Speaker 5: It's a conversation where you're going to have all day
Speaker 5: long and you point out that basically open source allows
Speaker 5: more groups to go.
Speaker 4: To work on it.
Speaker 5: The problem is, as we're learning the tens of billions
Speaker 5: of dollars it takes to train models with yes, tens
Speaker 5: or hundreds of billions of parameters, and then you go
Speaker 5: lower down and now what we're hearing is that actually
Speaker 5: there are the folks doing this running out of cash?
Speaker 5: Are you seeing that as well?
Speaker 6: So it's more less true because for example, now you
Speaker 6: can use Lamastri that really has been closely but that
Speaker 6: meta has released and finds units for a very small
Speaker 6: amount of money. That's why I'm hugging face. There's over
Speaker 6: one million models that have been trained by companies, and
Speaker 6: a lot of these companies are very small and don't
Speaker 6: have like really really big big budget. I feel like
Speaker 6: today every single company has to build their own AI
Speaker 6: otherwise they run the risk of being left behind. And
Speaker 6: that's what we're seeing, and it doesn't require any more
Speaker 6: really really big budget. An interesting point though, that we're
Speaker 6: going to see this year though, is that we'll need
Speaker 6: to find for AI companies better business models. That's what
Speaker 6: kind of like you hinted at, something we really focused
Speaker 6: on at Talking Face. We are looking grateful to be
Speaker 6: close to profitable, which is very unusual for AI companies.
Speaker 6: But we're starting to see that there are some ways
Speaker 6: to generate revenue and not burn insane amounts of compute
Speaker 6: for AI startups today.
Speaker 3: I mean, how on that profitability perspective of yours, how
Speaker 3: many paying customers do you now have Can you give
Speaker 3: us an update. You've got a million models. What about
Speaker 3: paying customers?
Speaker 6: We have more than ten thousand paying customers out of
Speaker 6: the over one hundred thousand organizations, more than four million
Speaker 6: AI builders that are using our platform, and I think
Speaker 6: we found the right balance between monetizing, especially with like
Speaker 6: big companies that are using the platform in.
Speaker 4: Private enterprise companies exactly in.
Speaker 6: Order to fund all the free community, open source work
Speaker 6: that we're doing, and that is always going to stay
Speaker 6: open source and free.
Speaker 3: Of course, I want to go back to what I
Speaker 3: was saying though about people running out of cash. You
Speaker 3: actually put out a really interesting call on x basically saying, look,
Speaker 3: I'm here if you need me. Hugging face is here.
Speaker 3: If there are good people out there building interesting businesses
Speaker 3: but you're running out of money, we could be a
Speaker 3: home for you. Are you making acquisitions? Is it acquihiring
Speaker 3: that goes on them?
Speaker 6: We make some acquisitions. We're going to have interesting announcements
Speaker 6: in the next few weeks.
Speaker 3: I oh, don't taaser, but that's interesting.
Speaker 6: But I think in geneoin AI you're going to see
Speaker 6: more and more MNA because, as you said, I think
Speaker 6: a lot of companies took very risky bets. A lot
Speaker 6: of them are running out of money. And at the
Speaker 6: same time you have other companies like Hugging Face and
Speaker 6: others that are successful enough to be homes. Some of
Speaker 6: these M and A is going to weird, right, We've
Speaker 6: seen that happening in Lidit with Deck with some.
Speaker 5: Usual marriage with necessity rather than choice.
Speaker 4: May's.
Speaker 6: Yes.
Speaker 5: One thing that's good about summits like these Bloomberg Tech
Speaker 5: by the way, we can go around the room and
Speaker 5: ask who you're going to be shopping for. That's going
Speaker 5: to be interesting. But you get all these people in
Speaker 5: one place. You've also used the time that you've been
Speaker 5: in San Francisco because you're up in Seattle, right, Miami
Speaker 5: or Miami Apologies, you've been hiring, you've been interviewing candidates.
Speaker 5: Is that just a function of the best candidates being
Speaker 5: here in this city? How wide are you casting your net?
Speaker 4: Yeah?
Speaker 6: I think I think San Francisco is still the heart
Speaker 6: of technology and the I right, there's so much talent,
Speaker 6: so much so many interesting companies, so many interesting big
Speaker 6: technology companies being here that it's important for us to
Speaker 6: kind of like you have a foot on the ground here.
Speaker 6: We have a team already here, but we're also hiring
Speaker 6: community for hugging face here.
Speaker 3: Applications being taken.
Speaker 6: Yes, there's a really massive fight and struggle for AI
Speaker 6: talents right now with inflation of packages everywhere. But what
Speaker 6: we're seeing is that when when you have a mission
Speaker 6: that's like interesting two candidates like we open source, then
Speaker 6: you can attract really good talents. That's one of the
Speaker 6: reasons why. Also we're seeing big tech doing more and
Speaker 6: more open source. Right if you look at Meta with
Speaker 6: all the great work.
Speaker 3: That favorites, you keep on. I mean you've only really
Speaker 3: mentioned number three. You're trying to cajole Google into coming
Speaker 3: even more open source.
Speaker 6: I think as long as companies contribute to the world
Speaker 6: and to the field, if we've open source, we open research,
Speaker 6: I think it benefits everyone. I think we've we've lost
Speaker 6: a little bit this way in the US for the
Speaker 6: past few years. If you look at AI five years ago,
Speaker 6: most of it was open source and open science. It
Speaker 6: changed a little bit when some companies started to make
Speaker 6: money and and changing their approach to things. But I
Speaker 6: think it would be positive for the world to get
Speaker 6: back to an AI domain that is more open, more transparent,
Speaker 6: more inclusive.
Speaker 5: And you asked a calendar date now, by the way,
Speaker 5: because you told us you're going to announce.
Speaker 4: The news when you're ready four weeks. Yeah, we're holding you.
Speaker 3: Thanks clems on, our joy to have you with us
Speaker 3: and let you get to your breakfast where he's holding
Speaker 3: court here seeo hugging face. What a great conversation. Welcome
Speaker 3: back to this very special edition of Blue Meg Technology,
Speaker 3: Live in the Heart in San Francisco. All the grain
Speaker 3: and the good of industry movers shakers when it comes
Speaker 3: to artificial intelligence, in particular the academics, but the companies
Speaker 3: behind it, the CEOs, and notably also the investors. And
Speaker 3: this is an interesting one for the investor base. Right,
Speaker 3: we potentially have a new large language model getting at
Speaker 3: a decent evaluation.
Speaker 4: Yeah.
Speaker 5: So, I think what we reported last night is that
Speaker 5: xa I, the AI company started by Elon Musk and
Speaker 5: which he built out pretty quickly, is closing this kind
Speaker 5: of mega funding round eighteen billion dollar valuation. The thing
Speaker 5: is that we've learned right over the last year or
Speaker 5: more that is not actually that eyewatering. A number the
Speaker 5: numbers involved are not that iwak it wasn't he.
Speaker 3: Actually raising an awful lot considering an eighteen billion valuation.
Speaker 5: Yes, I think we've reported sort of up to six
Speaker 5: billion dollars. The thing is that the compute costs a
Speaker 5: mega and I took a phone call this morning saying,
Speaker 5: look past the cash and start asking whether the XAI
Speaker 5: has got access to the GPUs. Now Elon Musk has
Speaker 5: an existing relationship with Nvidio Jensen hung in the Tesla context,
Speaker 5: but it's a good gossip for the Bloomberg Tec event.
Speaker 4: It's a good thing to discuss well.
Speaker 3: And ultimately who are the investors? What we've seen I
Speaker 3: think really the rise in twenty twenty three and twenty
Speaker 3: twenty four, it's been corporate VC.
Speaker 4: Yes, of course, a strategic investor.
Speaker 3: Yeah, you've got Sequoia Capitals being incredibly active, who were
Speaker 3: going to have to co capital on a little bit later.
Speaker 3: But then more at the seed of the funding the
Speaker 3: series A series people. Amount of money necessary for these
Speaker 3: large language les means and video has to be a
Speaker 3: player or a Google has.
Speaker 5: And what I heard is that Jared Birchall, whose head
Speaker 5: of Musk's family office, has been in the Middle East
Speaker 5: tolling the sovereigns a lot of that.
Speaker 4: Stuff going on.
Speaker 3: Welcome back to a special edition of Bloomberg Technology right
Speaker 3: here in San Francisco. An event is upon our hands
Speaker 3: that has all to do with artificial intelligence and what
Speaker 3: to continue that conversation? Right here, right now at the
Speaker 3: Bloomberg Tech Summit is writer CEO Mayhabim, who joins us now,
Speaker 3: who has been doing Janata AI for the enterprise before
Speaker 3: everyone else got with the program. You both rate in
Speaker 3: twenty twenty, you've got an enormous chunk of change from
Speaker 3: Iconic Capital and other key investors. And how does it
Speaker 3: feel with everyone trying to surge in on the enterprise
Speaker 3: opportunity here? How are you standing out? I'm making sure
Speaker 3: that you keep the keys like ubers and clients that
Speaker 3: you already have.
Speaker 7: Yeah, it's actually really exciting to see all of the investment.
Speaker 7: Right We've been working on this, my Covaner and I
Speaker 7: for ten years previously in a machine translation startup, and
Speaker 7: so to see all of this attention is actually amazing.
Speaker 7: But the way we stand out, I think, is with
Speaker 7: a really differentiated platform that helps enterprises with the last mile,
Speaker 7: which is ninety percent of the work in AI.
Speaker 5: May You've been on the show a number of times
Speaker 5: over the last two years or so, and each time
Speaker 5: I always reflect on sort of the rate of change
Speaker 5: for the industry, but also grow for your company. Clem
Speaker 5: DeLong of Hugging Face just gave us some numbers about
Speaker 5: the sort of size and scope of how they're doing
Speaker 5: if you say close to profit or near profit or
Speaker 5: something like that, but just tell us about your company
Speaker 5: and how it's doing.
Speaker 7: Yeah, I mean, it's been an incredible rate of change.
Speaker 7: When we started the company, we knew AI was going
Speaker 7: to be better at people at reading and writing, and
Speaker 7: that has certainly happened. We now say, if you can
Speaker 7: write it, you can build it, because AI is not
Speaker 7: just the technology, it's the way to build new technology.
Speaker 7: But building AI apps is actually still quite difficult, and
Speaker 7: so the rate of change of just what we've been
Speaker 7: able to do, I mean, it's hundreds of enterprise customers,
Speaker 7: hundreds of thousands of users, thousands of applications that are
Speaker 7: in production. So a lot of this kind of question around,
Speaker 7: like how you get applications from POC to scale. You know,
Speaker 7: we've been doing that for years now and it's just
Speaker 7: had a tremendous impact on the growth.
Speaker 3: Of the business.
Speaker 5: You have some relatively new work on models, right, so
Speaker 5: tell us about the kind of the latest and greatest
Speaker 5: on the tech side of your offerings.
Speaker 8: Yeah.
Speaker 7: So, over the past few months, we've introduced vision as
Speaker 7: a capability into a platform. We've launched Palmyra in thirty
Speaker 7: two languages that really really high quality, beating human benchmarks
Speaker 7: our customers tell us. And next up for us our
Speaker 7: large reasoning models, so software that write software, which we're
Speaker 7: really excited about being able to go from you know,
Speaker 7: work substitution to real work reinvention and orchestration using AI.
Speaker 3: At the very start, you said basically ninety percent of
Speaker 3: the work isn't just getting the right language, large language
Speaker 3: model in the door, but it's implementing it. It's all
Speaker 3: the other bells and whistles that go to ensure that
Speaker 3: you get operational efficiencies that you put it to your
Speaker 3: own workflows. What are some of the best ways you're
Speaker 3: seeing and being harnessed. What are some of the worst ways,
Speaker 3: Because everyone's still waiting for this Eureka moment where all
Speaker 3: of our exuberants around AI actually makes a real difference.
Speaker 7: Around one hundred percent, there are fifteen hundred lms, right,
Speaker 7: if large languine hundred Yeah, I mean, and.
Speaker 3: They can pass the MCAT and the LSAT.
Speaker 7: So if lllms were the answer, everyone would have the
Speaker 7: generative AI program of their dreams, right, But that's not
Speaker 7: the case. There's so much work to get the data
Speaker 7: and the context and the workflow from the business user
Speaker 7: into the application, right, And that's what our platform does.
Speaker 7: It's this collaborative inner that combines the LLM with all
Speaker 7: of those building blocks, and that's where the magic is
Speaker 7: because the llms themselves need so much more context about
Speaker 7: the business to be able to do what customers need
Speaker 7: them to know.
Speaker 3: You said before that basically large language models are going
Speaker 3: to be commoditized. The foundational models are going to be commoditized,
Speaker 3: particularly from a consumer perspective. Where then does the value
Speaker 3: ultimately end up lying? Because there are so many people
Speaker 3: trying to fix problems using generative AI, A lot of
Speaker 3: them are coming to you to try and be bought
Speaker 3: or helped at the moment, I assume because they're running
Speaker 3: out of money themselves. Yeah, there's certainly a lot of air.
Speaker 7: Being sucked out of a room by big tech, right,
Speaker 7: but there's still a ton of opportunity for startups. Microsoft
Speaker 7: has to build for the lowest common denominator, right, so
Speaker 7: individual productivity is very different than team productivity and team workflows.
Speaker 7: So even though it feels like we're going to go
Speaker 7: through sort of a big consolidation phase, I do think
Speaker 7: there's still a ton of opportunity for for stars. We
Speaker 7: have made a small acquisition that will announce soon, and
Speaker 7: I think we'll make others. So there certainly is a
Speaker 7: real high barrier for entry to come in and serve
Speaker 7: the enterprise. But it's still there's so much blank white
Speaker 7: open space for startups to help enterprises compete.
Speaker 5: It's interesting maybe that you use the c word consolidation.
Speaker 5: I don't think glem DeLong went as far as using
Speaker 5: the word consolidation, but I think you know, you said
Speaker 5: something a moment ago about big tech sucking the oxygen
Speaker 5: out of the room. It goes to the open source
Speaker 5: closed debate. I assume you sit on the open source side,
Speaker 5: but just wigh in.
Speaker 3: So we're kind of in the middle.
Speaker 7: So our models are proprietary, A bunch are on hugging
Speaker 7: face so later generations of models, but our latest models
Speaker 7: are are closed source.
Speaker 3: But by being in the middle.
Speaker 7: What enterprises really need is the ability to audit right
Speaker 7: and have the transparency around training data and all sorts
Speaker 7: of things related to the models they don't really want,
Speaker 7: like the last mile cumbersomeness of necessarily like fine tuning
Speaker 7: or running the models themselves is what we're finding. And
Speaker 7: so like in the in the kind of sucking the
Speaker 7: air out of the room, the confusion around what vendors
Speaker 7: to turn to and how to actually get great applications shift.
Speaker 7: That's where That's where I think there's still a lot
Speaker 7: of confusion in the enterprise, and I think there's still
Speaker 7: all that work to be done to minimize hallucinations.
Speaker 3: To ensure that we're seeing a clarity of where the
Speaker 3: underlying data is coming from and you're not having copyright issues.
Speaker 3: Give us clarity on your business. Now, have you been
Speaker 3: approached to be bought? Are you remaining independent? Are you
Speaker 3: raising more money?
Speaker 7: So there's there's a really long, i think, product journey
Speaker 7: for us to really realize our vision. So I'm really
Speaker 7: excited about remaining independent. It used to be a year
Speaker 7: ago that I would say, you know, lms are for
Speaker 7: the rudgery, the work you don't want.
Speaker 3: To do today.
Speaker 7: The capabilities are so incredible, they're as good as us.
Speaker 7: But the future is work where you get to do
Speaker 7: the work you want to do and lllms do the rest,
Speaker 7: right because one person's drudgery is another person's creative passion,
Speaker 7: and that's kind of compelling.
Speaker 3: Vision for the future of work.
Speaker 7: We're not seeing enterprises come up with. Yes, we talk
Speaker 7: to hundreds of companies a week, and that really feels
Speaker 7: missing right now. Kind of executives painting a vision for
Speaker 7: what AI looks like inside their companies in a way
Speaker 7: that brings people along. So there's a lot to do
Speaker 7: both in you know, kind of bringing our vision into
Speaker 7: the world and helping companies achieve theirs.
Speaker 8: Right.
Speaker 5: A CEO may have be great to catch up here
Speaker 5: at Blue veg Tech in San Francisco.
Speaker 3: She slies every week from some Franciscot and on and
Speaker 3: I'm back.
Speaker 5: That's what we're hearing, the world of the CEO in
Speaker 5: the world of AI on a plane coming out here.
Speaker 4: We're going to be joined by Stephanie Jang.
Speaker 5: Partner at Sequoia, for her take on investing in AI startups.
Speaker 5: Stay with us, we'll be right back. This is Bloomberg Technology.
Speaker 5: Welcome back to this special edition of Bloomberg Technology. We're
Speaker 5: back together live in San Francisco a Bloomberg Tech, our
Speaker 5: annual conference, and here at the Tech Summit, we've got
Speaker 5: to talk about investing the first checks into those new
Speaker 5: and early AI startups. We have a fantastic guest for
Speaker 5: today's Visa Spotlight, Stephanie Jan, partner at Sequoia. You guys
Speaker 5: are so busy, you are writing lots of checks, but
Speaker 5: the new companies being founded in AI are not the
Speaker 5: same as they were one year ago, and certainly not
Speaker 5: eighteen months or.
Speaker 4: Two years ago.
Speaker 5: Just give us the sort of timeline of where we
Speaker 5: are now in this industry way.
Speaker 1: First of all, thank you so much for having me
Speaker 1: at Caroline. It's an absolute joy to be here. We're
Speaker 1: at a really interesting time in AI today, seven years
Speaker 1: from the advent of the transformer, four years.
Speaker 3: Since the advent of the GPT three moment.
Speaker 1: I think twenty twenty four is going to be a
Speaker 1: monumental year for AI.
Speaker 3: And here's why. I think this year is.
Speaker 1: Going to be a step function leap in digital intelligence,
Speaker 1: everything from video to AI agents to robotics. I also
Speaker 1: think that this year is going to be the year
Speaker 1: we see a shift in the ecosystem to a thriving
Speaker 1: ecosystem with many winners in the models area across closed source,
Speaker 1: open source, large models, small models, and third, I also
Speaker 1: think this is the year we start to see AI
Speaker 1: commercialization at scale.
Speaker 3: And at Sequoia, we've been really busy.
Speaker 1: As you noted, we're highly selective about the companies that
Speaker 1: we partner with, but this year, in just the first
Speaker 1: four months alone, we've invested in ten new AI companies,
Speaker 1: everything from new foundation models to new AI native applications.
Speaker 3: I love being went through the history like seven years
Speaker 3: ago since the transmission model. I mean it was twenty
Speaker 3: years ago just over that Sequoia wrote the first check
Speaker 3: into in video, and now we think there's still that
Speaker 3: company really owning really the oxygen in the room.
Speaker 5: And the value vest right they writing checks of their
Speaker 5: own is a strategic investment.
Speaker 3: And I'm interested therefore exactly to AT's point, how competitive
Speaker 3: is it out there to get those first checks in
Speaker 3: ho Who are you seeing coming? Is it the corporates
Speaker 3: that are wanting to write checks? Is it VC's wanted
Speaker 3: to write checks.
Speaker 1: It's an incredible ecosystem right now, with everyone pouring money
Speaker 1: into the AI ecosystem. I think it's very much reflective
Speaker 1: of the opportunity that we see in AI, the large
Speaker 1: market opportunity that is to come. I actually think that
Speaker 1: we're still in the very early innings.
Speaker 3: Of all of this.
Speaker 1: Well, you know, it's the classic saying of we overestimate
Speaker 1: in the short run, but we really underestimate in.
Speaker 3: The long run. And video has done a wonderful.
Speaker 1: Job of being such a critical hold in the ecosystem
Speaker 1: with hard we're driving compute, but also now with so
Speaker 1: many software tools and the entire developer ecosystem they've built
Speaker 1: around them. So I think that we're just in the
Speaker 1: early innings and there's a lot more to come.
Speaker 3: We were just speaking with Clem from Hugging Face Anadeine Mayhembib,
Speaker 3: who highlight the fact that it's really expensive to do
Speaker 3: this and video chips are a putty penny. How are
Speaker 3: you seeing the companies that you back able to sustain
Speaker 3: the investment they need to make. How do you make
Speaker 3: sure the checks you write you're going in the right
Speaker 3: direction and not just sort of going into the pool
Speaker 3: of training money.
Speaker 1: Yeah, well, I think that the classic conventional wisdom is
Speaker 1: that incumbents with scale, data, capital and distribution have a
Speaker 1: natural advantage, and that's absolutely correct. It also costs a
Speaker 1: lot to build these models because of compute and for
Speaker 1: AI talent, but I also think that there are so
Speaker 1: many nimble ways for a startup to compete. Specifically, I
Speaker 1: think the next leap is really around one high quality data,
Speaker 1: specifically high quality labels of data and targeted domain specific data.
Speaker 3: Second, it's really about what you do with that data.
Speaker 1: Reinforcement learning with human feedback I think will really shine
Speaker 1: in this next era.
Speaker 3: It's an idea.
Speaker 1: Derived from reinforcement learning, but here an agent actually also
Speaker 1: learns on the fly with human feedback, and that's what's
Speaker 1: so brilliant about chat topt for example. And finally, I
Speaker 1: think that you really differentiate not just on model performance,
Speaker 1: which is where all the capital goes into, but it's
Speaker 1: also around product distribution and the entire product experience that
Speaker 1: you offer.
Speaker 3: To the end customer.
Speaker 5: You use the word incumbent, I think we should probably
Speaker 5: talk about who those incumbents are because the point that
Speaker 5: may have even right made to a certain extent claim
Speaker 5: from Hogeyface is that big tech and where I think
Speaker 5: we're talking about alphabet Microsoft in the first instance, are
Speaker 5: sucking the oxygen out of the room. From a capital perspective,
Speaker 5: a talent perspective, you invest in the preceed and seed sage.
Speaker 4: Do you find that be true?
Speaker 1: Well, I think that incumbents absolutely have an advantage, as
Speaker 1: we just outlined, but I also think that new startups
Speaker 1: have a shop scales. At AI actually recently released the
Speaker 1: survey last week where they interviewed thousands of developers on
Speaker 1: their most popular models, and the ones that actually came
Speaker 1: into light were GPT four, GPT three point five, and
Speaker 1: Gemini as the most popular models used. But we're also
Speaker 1: starting to see new players come into play with models
Speaker 1: that are just as competitive in performance. I'm really excited
Speaker 1: about the open source model ecosystem enabling many more new
Speaker 1: players to come into play. LAMA three, for instance, is
Speaker 1: so powerful. The new eight billion PARAMETERAR model is a
Speaker 1: longer trained, small model that I think will become a
Speaker 1: really powerful building block for new developers to build new
Speaker 1: applications on top of and to build new models around it.
Speaker 1: It's going to drastically reduce the cost of what it
Speaker 1: takes to build new experiences.
Speaker 5: We are increasingly talking about Beta and its competence in
Speaker 5: building large language models. You speak highly of them. Where
Speaker 5: do you see them they? I think, Zuckerberg said on
Speaker 5: the Cool last week, we want to be the world's
Speaker 5: leading AI company.
Speaker 4: Where are they in that journey?
Speaker 1: I think that they have an incredible advantage, and not
Speaker 1: just because of the capital that they're willing to pour
Speaker 1: into play, but also because of the entire treasure trove
Speaker 1: of data that they hold, all this proprietary UGC content
Speaker 1: that they can really use to train their models. One
Speaker 1: of the things I'm really excited to see them enter
Speaker 1: the scene with this year is a new generative video
Speaker 1: foundation model, similar.
Speaker 3: To what we saw with Sora and open Ai.
Speaker 1: To me, the most powerful thing that unlocked was that
Speaker 1: the methodology we take for building large language models and
Speaker 1: digital intelligence works for video as well. You take a
Speaker 1: diffusion transformer model and you just scale it with enough
Speaker 1: video dat and compute and meta has a wonderful advantage
Speaker 1: given the entire treasure trow of content they have.
Speaker 3: To compete in the bosom.
Speaker 1: And then what they're doing with Lama three I think
Speaker 1: is game changing entirely. It opens the playing field for
Speaker 1: everyone themselves new startups, lowering the cost for a thriving
Speaker 1: ecosystem with many winners.
Speaker 3: Come back when you've got more checks you can announce
Speaker 3: in that thriving ecosystem. Such a joy to be here
Speaker 3: with you. Thank you so much for having it, Caroline,
Speaker 3: and having by Sequoia partner Stephanie Chan. Welcome back to
Speaker 3: this special edition of Bloomberg Technology, the heart of San Francisco,
Speaker 3: big event upon our hands and every year in fact,
Speaker 3: Rumbag Business Week releases in tandem. It's a list of
Speaker 3: tech wants to watch. But these are the startup founders,
Speaker 3: the big tech managers, the mom he investors as well,
Speaker 3: who of playing a big role in shaping text future
Speaker 3: and joining us now is one of these ones. To
Speaker 3: words please to welcome you did madame Amazon vice president
Speaker 3: for of course the worldwide operations side of the business,
Speaker 3: your first interviews. It's taking on an enormous role of
Speaker 3: more than a million people that you manage the focus
Speaker 3: of getting my package to me in the swiftest way,
Speaker 3: most cost efficient manner as possible. Can I just ask
Speaker 3: what your day looks like? What is a day in like?
Speaker 8: Well, first, Caroline and thank you for having me it's
Speaker 8: supposed to be here.
Speaker 5: Yeah.
Speaker 8: For me, really, my day starts, you know, fairly early
Speaker 8: in the morning. But you know, it starts with thinking about,
Speaker 8: you know, the team I've got.
Speaker 4: You know, we've got a very very broad team all
Speaker 4: around the world.
Speaker 8: We've got four thousand different locations that we operate around
Speaker 8: the world, and really it's focused on how do we
Speaker 8: continue to innovate on behalf of customers that do it
Speaker 8: in a way that puts safety.
Speaker 4: And people at the forefront.
Speaker 8: And so my day is really focused on innovation across
Speaker 8: four different spectrums.
Speaker 4: Safety, really the.
Speaker 8: Customer experience with delivery speeds innovating, especially with what's happening
Speaker 8: with technology finding new ways, you know, whether that's through
Speaker 8: robotics our operations to make things more efficient and driving
Speaker 8: you when you're.
Speaker 5: Talking about the technology, we're talking about everything from the fleets,
Speaker 5: right so there's a transition to sustainable energy in the
Speaker 5: fleet context, talking about robotics in the fulfillment centers, and
Speaker 5: dare I say AI in tracking the data? What's the
Speaker 5: biggest investment focused for you right now? And technology roll out?
Speaker 8: You know, we've got technology all across our operations and
Speaker 8: there's really two things that I would maybe thematically talk about.
Speaker 8: One is, we do have a lot of investments in
Speaker 8: automation and robotics that are going on, especially with how
Speaker 8: quickly things are accelerating with General VII. We have investments
Speaker 8: on really novel foundational models that look and use the
Speaker 8: high quality data that we've gathered in source as we
Speaker 8: ship tens of millions of products every day, and those
Speaker 8: going to help make some of those robotic solutions more
Speaker 8: generalizable as well as make them more efficient.
Speaker 4: And the second is we've.
Speaker 8: Been working on a set of really inventive robotic solutions
Speaker 8: over the last few years that are finally reaching maturity
Speaker 8: and scale and we'll start to roll out starting this year.
Speaker 8: Both those are really exciting and it will be transformative
Speaker 8: for operation.
Speaker 3: I mean, you've got to be inventive because Annie Jase
Speaker 3: is asking you to focus on costs, but I'm sure
Speaker 3: the innovation in a way does longer term once you
Speaker 3: made the investment strip out some of the costs, but
Speaker 3: ultimately does that come at a sacrifice of labor. How
Speaker 3: do you talk to those people that you are so
Speaker 3: key when you focused on to ensure that they feel
Speaker 3: that are being augmented not replaced.
Speaker 8: You know, the best thing I can talk about is
Speaker 8: our history. You've deployed seven hundred and fifty thousand robots
Speaker 8: over the last decade across our operations. We've done that
Speaker 8: while creating hundreds of thousands of jobs. And you know
Speaker 8: what's really interesting and not a lot of people know,
Speaker 8: is we've created dozens of new classic jobs, your skilled jobs,
Speaker 8: technical jobs. And what we've learned in that process is
Speaker 8: that one of the most important things that you can
Speaker 8: do you as a company in this world of generatively
Speaker 8: I and robotics, is to really focus on investing employees.
Speaker 8: So we've launched two different programs. One is a twenty
Speaker 8: twenty five off skilling pledge that really helps train people
Speaker 8: for this new workplace in the future, and a Yeah
Speaker 8: Ready program that's generally available to everybody that's really focused
Speaker 8: on investing in helping provide a skill training.
Speaker 4: Over two million people.
Speaker 8: So really focusing on people alongside the investments who are
Speaker 8: making in general.
Speaker 4: VI in Revidy, we just have thirty seconds.
Speaker 5: What's your one personal goal for the year, something you
Speaker 5: want to achieve.
Speaker 8: You know, for me, there's more than one, but I'll
Speaker 8: quickly I'll try to answer it quickly. The first and
Speaker 8: the highest priority for us is safety, and we want
Speaker 8: to be the safest workplace across the industries we operate
Speaker 8: in making measurable and really remarkable progress in that area.
Speaker 8: I want to company to invest in that. And the
Speaker 8: second is to compete to improve the convenience for customers
Speaker 8: and delivery speeds is an area of focus.
Speaker 3: Congratulations on being one of the key ones to watch.
Speaker 3: Phenomenal the amount of people who manage young age that
Speaker 3: you are, madame. We thank you, Amazon vice President of
Speaker 3: Worldwide Operations. Meanwhile, I mean from ones to watch of
Speaker 3: individuals to everything you've got to watch coming up, because
Speaker 3: this is going to be an amazing set of conversations.
Speaker 3: I'm going to be speaking with a key chip leader.
Speaker 3: Of course, you're going to be speaking about the future
Speaker 3: and technology. Who have you got lined up?
Speaker 5: Yeah, I'm going to talk to Tom Oxley of synchron
Speaker 5: I'm going to talk about brain implants and what the
Speaker 5: right method of putting a electrode into one's brain is.
Speaker 3: I love asual casuals perspective. Renee James is joining me
Speaker 3: and Perco. Look, this is the question that having just
Speaker 3: spoken with Renee the other Renee and chips of arm.
Speaker 3: Where is the market share being taken by these newer players,
Speaker 3: taking from AMD, from Intel, even potentially in video.
Speaker 5: Thank you so much for joining us on this special
Speaker 5: edition of Bloomberg Technology. It's great to be back together
Speaker 5: in the field, but we actually have a full day ahead,
Speaker 5: so many great guests stay with us. Thank you for
Speaker 5: tuning in from San Francisco at Bloomberg Tech for this
Speaker 5: is Bloomberg