Speaker 1: From Mahard where Innovation, money and power Collie in Silicon
Speaker 1: Vallet NBN. This is Bloomberg Technology with Caroline Hyde and
Speaker 1: Ed Ludlow.
Speaker 2: I'm Ed Ludlow here in San Francisco.
Speaker 3: Caroline hids off today. This is Bloomberg Technology. Coming up
Speaker 3: on the program. Apple hits a three trillion dollar valuation.
Speaker 3: Will we close above that historic market cat milestone remains
Speaker 3: to be seen? The co founder of DeepMind now the
Speaker 3: CEO of Inflection AI. He discusses the potential of his
Speaker 3: company after raising a whopping one point three billion dollars
Speaker 3: and more trouble for Adobe's purchase of Figma, with the
Speaker 3: UK joining the EU and US in multiple probes of
Speaker 3: that twenty billion dollar deal. Such a big week in
Speaker 3: the world of ten technology.
Speaker 2: But there is one.
Speaker 3: Big story this Friday, and it is Apple, the first
Speaker 3: company ever to hit a three trillion dollar market cap.
Speaker 2: And this chart tells the story.
Speaker 3: Look at the nine hundred billion dollars of marketcap we've
Speaker 3: added so far in twenty twenty three.
Speaker 2: What is the story here? We will get to it in.
Speaker 3: Just a moment, but I remind you last time we
Speaker 3: were near that level was at the beginning of twenty
Speaker 3: twenty two.
Speaker 2: It's taken us that long to get back.
Speaker 3: There is one person you want to speak to on
Speaker 3: a daylight today, and it is Bloomberg's Mark German.
Speaker 2: Mark.
Speaker 3: You cover this company as close as any journalist on
Speaker 3: the planet. I want to start by asking you, what
Speaker 3: kind of a moment is this? What kind of a
Speaker 3: milestone in technology history is registering a three trillion dollar
Speaker 3: market cap?
Speaker 4: Ed?
Speaker 5: Thank you so much for having me. Obviously, this is
Speaker 5: a incredibly big milestone for Apple or any technology company really,
Speaker 5: and for Apple to do this, to get back to
Speaker 5: where it was in early twenty twenty too. You saw
Speaker 5: what happened to the broader market over the last year
Speaker 5: or so, and to really come back up that mountain
Speaker 5: and get back here is a big moment for the company.
Speaker 5: I think that you saw a slew of departures, not
Speaker 5: only at the executive level, but maybe at the mid
Speaker 5: level or lower level of the company. And one continued
Speaker 5: theme on those departures was people felt like their RSUs
Speaker 5: or the restricted stock units would not really pay out
Speaker 5: as much money as maybe they can earn in another company. Right,
Speaker 5: and the stock coming back up right, I think that
Speaker 5: could be a key way that Apple will be able
Speaker 5: to retain people moving forward as well. It adds new
Speaker 5: excitement to the rank and file at the company. They
Speaker 5: know what they're working towards. In terms of an ultimate
Speaker 5: payout for the consumer doesn't really have an impact, but
Speaker 5: I think internally at Apple it is a something they'll
Speaker 5: never say, but I think it is a quite a
Speaker 5: positive moment.
Speaker 3: That deep reporting is such a good point as well.
Speaker 3: It has not yet been brought up in our coveragejumping
Speaker 3: big Television of the three trillion dollar milestone. The short
Speaker 3: term story for the consumer has been about Vision Pro,
Speaker 3: but you argue in Today's Tech Daily that actually, if
Speaker 3: you think about the three trillion dollar market cap, it's
Speaker 3: not got much to do with Vision Pro at all.
Speaker 2: What's your point, Yeah, I think we would hit.
Speaker 5: This three trillion dollar market cap whether or not Apple
Speaker 5: announced the vision Pro head set in June at the
Speaker 5: Developers Conference or not. I think the Vision Pro story,
Speaker 5: you know, very long term for Apple could become an
Speaker 5: Apple Watch or iPad sized opportunity, which is about twenty
Speaker 5: five billion annually to the bottom line. And that's in
Speaker 5: the real long term. In the short term, you're not
Speaker 5: likely to see this generate more than two to four
Speaker 5: billion a year annually for Apple, which is essentially very small.
Speaker 5: It's one to two percent of their overall annual revenue.
Speaker 5: It's really the ecosystem play, right. It's the idea that
Speaker 5: the ecosystem walks you in and such, where you're going
Speaker 5: to own an iPhone, an iPad, a Mac, and then
Speaker 5: every few years or so, you're going to upgrade to
Speaker 5: new models. On top of that, you're going to subscribe
Speaker 5: to services, you're going to use Apple Care, You're going
Speaker 5: to visit Apple retail stores. You're going to buy more
Speaker 5: accessories like air pods, the Apple Watch, and maybe one
Speaker 5: day the Vision Pro at a cheaper price as well.
Speaker 5: And so that's stickiness, the idea where consumers are willing
Speaker 5: to spend extra. They're really willing to shell out for
Speaker 5: a new iPhone, the priciest iPhone, the most storage you
Speaker 5: can get. That's what makes this company so lucrative and
Speaker 5: so special to the shareholder. One really important aspect that
Speaker 5: we also haven't touched upon about this three trillion dollar
Speaker 5: measure is that we're heading right into iPhone season. Believe
Speaker 5: it or not, We're only about two months away from
Speaker 5: the iPhone fifteen going on sale. The iPhone fifteen is
Speaker 5: going to be a pretty significant upgrade on both the
Speaker 5: low end models and the high end models for the
Speaker 5: first time in three years since the iPhone twelve lunch
Speaker 5: in twenty twenty.
Speaker 2: New design, big camera.
Speaker 5: Improvements, changes to the display on the cheaper models, You're
Speaker 5: going to see another big iPhone upgrade cycle, and so
Speaker 5: I think consumers are excited to only be eight weeks
Speaker 5: away from that, and shareholders see that excitement, and so
Speaker 5: you're likely to see a big influx of purchases in
Speaker 5: just a few months, which obviously is going to drive
Speaker 5: attention to purchasing the stock too mark quickly.
Speaker 3: The one phrase or word you haven't used is artificial intelligence.
Speaker 3: Why are we not talking about Apple in the context
Speaker 3: of artificial intelligence?
Speaker 5: Because Apple has really set out this recent AI boom
Speaker 5: right over the past year or so. You've seen Microsoft,
Speaker 5: Google obviously open AI with chat GPT. You've seen Amazon
Speaker 5: all throw around the buzzword and talking about their new
Speaker 5: generative AI chatbots and such. Apple has really stood on
Speaker 5: the sidelines here and I don't anticipate any significant new
Speaker 5: AI related service from Apple to launch until the tail
Speaker 5: end of twenty twenty four calendar year twenty twenty four
Speaker 5: at the earliest, so there's not much there. I know
Speaker 5: there's been some speculation for analysts and such that Apple
Speaker 5: is nearing some sort of generative AI ecosystem. There's nothing
Speaker 5: coming soon, and so I don't really think that could
Speaker 5: be priced into the stock as of yet. And I
Speaker 5: don't have necessarily think that Apple is planning very significant
Speaker 5: AI initiatives other than a new AI based health coaching
Speaker 5: service for next year. But obviously the mother of all
Speaker 5: AI projects, as Jim Cookers said, is the company's self
Speaker 5: driving car. You're unlikely to see that at least for
Speaker 5: another four years or so.
Speaker 3: Yeah, you and I have done a lot of digging
Speaker 3: on the subject of an Apple self driving car. Will
Speaker 3: stick with it. Bloombo's Mark Gum and everything Apple, Thank
Speaker 3: you so much. Happy Friday. All right, that's top story
Speaker 3: number one. Top story number two. We go to the UK,
Speaker 3: where anti trust regulators launching an in depth investigation into
Speaker 3: Adobe's twenty billion dollar purchase of Figma. Let's get the details.
Speaker 3: Bloomberg's Caffine Gemmel live for us in London. Cafriine, what
Speaker 3: do we know.
Speaker 6: Hi, thanks very much for having me.
Speaker 7: So what we know today is that the CMEs of
Speaker 7: the Competition of Markets Authority has said that as the
Speaker 7: Adobe FIGMADY will need an in depth investigation unless the
Speaker 7: companies offer any remedies up to solve these anti trust
Speaker 7: problems that they have found.
Speaker 6: In the stage of this investigation. So, I mean, the
Speaker 6: main concerns from the CME are that within the design
Speaker 6: platform and the supply of screen tools as well. I know,
Speaker 6: these are two areas where Adobe and Pegma really compete,
Speaker 6: and the main concerns are that if Adobe bis stigma,
Speaker 6: then that means that they're really going to take that
Speaker 6: competition away and that could rise that could leave to
Speaker 6: arise in prices for customers and could also stifle innovation.
Speaker 3: We're just showing the shares of Adobe at one point
Speaker 3: six percent near session highs. When you get a headline
Speaker 3: like this, sometimes the stocks react negatively because the market's thinking, wow,
Speaker 3: maybe this deal won't happen.
Speaker 2: Is that the situation we're in now?
Speaker 3: How serious is this development in the context of a
Speaker 3: deal actually getting done?
Speaker 6: We look, I mean, it's too early right now to
Speaker 6: know whether it's serious or not. I mean these deals.
Speaker 1: Will obviously always get some scrutiny. This particular deal is
Speaker 1: also getting scrutiny as Ideal and the US and as
Speaker 1: potentially pheasans go to meet in Europe. So I mean
Speaker 1: we'll need to, you know, find out what the CME
Speaker 1: finds and its potential fees to investigation, whether we know
Speaker 1: it's going to be CDs or not.
Speaker 6: These are just the stages that these sorts of deals
Speaker 6: have to go through. And of course you know that
Speaker 6: the CME that people rely on. Consumers in the UK
Speaker 6: rely on the CME to do to make sure that
Speaker 6: consumers are getting a good deal.
Speaker 3: The Moss Catherine Gemel in London. How often is this happening?
Speaker 3: The trifecta US, EU, UK regulators when we're talking about
Speaker 3: a tech deal. Great reporting this Friday, we'll stick with it.
Speaker 2: Now.
Speaker 3: Coming up, Inflection AI CEO is going to join us
Speaker 3: to discuss the company's one point three billion dollar fundraise
Speaker 3: and it came from the likes of Reid Hoffman, Bill
Speaker 3: Gates in Nvidia. Big conversation coming up this is Bloomberg Technology.
Speaker 3: Inflection AI has just announced it's raised one point three
Speaker 3: billion dollars in funding from investors like in Video and
Speaker 3: Earlier this year, Inflection Ai launched its first product, a
Speaker 3: chatbot called Pie, a personally modeled AI chat box. Inflection
Speaker 3: Ai CEO and co founder The Stuffa Sullyman joins us
Speaker 3: from London. Interestingly, Congratulations, what is frankly a monster a round?
Speaker 3: Why did you need to raise that much money?
Speaker 2: Thanks?
Speaker 8: Ed, Yeah, great to be with you and appreciate the congrats.
Speaker 8: I mean, you know, we're really building the cutting edge
Speaker 8: of machine learning models today in order to create Pie,
Speaker 8: our conversational AI, and that requires vast amounts of compute.
Speaker 8: I mean, we're actually constructing the largest supercomputer in the
Speaker 8: world today, built on in videos h one hundred chips,
Speaker 8: and that's obviously very expensive, but as a startup, it
Speaker 8: actually enables us to get the best of both worlds.
Speaker 8: Have you know, the kind of resources that you might
Speaker 8: otherwise expect in a big tech company, but also the speed,
Speaker 8: agility and super high quality talent that you get when
Speaker 8: you bring together the kinds of folks that have been
Speaker 8: involved in building all the last generation of models at
Speaker 8: deep Mind, Open Ai and at Google.
Speaker 3: All the attention goes to Nvidia because they are participating
Speaker 3: in this roundless stuffer that you are building the underlying
Speaker 3: LM or foundation model using their H.
Speaker 2: One hundred GPUs.
Speaker 8: Yeah, I mean, we have an incredible partnership with them.
Speaker 8: They've been fantastic to us. Not only they investing in
Speaker 8: this round, but they made us their key partner to
Speaker 8: get access to H one hundreds and we've built a
Speaker 8: really powerful cluster with them. Just a couple of days ago,
Speaker 8: we announced that we have the fastest performing AI cluster
Speaker 8: in the world, and in a few months time we
Speaker 8: will have increased the size of that cluster to be
Speaker 8: the second largest supercomputer on the planet, which is just
Speaker 8: an incredible opportunity. And so we're super grateful for their partnership,
Speaker 8: but also the partnership with Microsoft. You know, we use Azure.
Speaker 8: They have an incredible cluster there and their AI infrastructure
Speaker 8: is also second.
Speaker 2: To none the stuff.
Speaker 3: When I bumped into you in the corridor of Bloomberg
Speaker 3: Technology Summit last week, I reminded you of something you
Speaker 3: said on stage about AI development being a meritocracy. You
Speaker 3: mentioned that in passing, but I wondered if you could
Speaker 3: elaborate on what you meant by that.
Speaker 8: Well, it's a meritocracy in the sense that you know,
Speaker 8: the cutting edge is also being open sourced and made
Speaker 8: available to millions of developers around the world to adapt, innovate,
Speaker 8: and experiment. And it's kind of an incredibly interesting time
Speaker 8: because on the one hand, models are getting bigger and better,
Speaker 8: and on the other they're also getting more efficient, smaller,
Speaker 8: and cheaper to run. So both directions of progress are
Speaker 8: really being turbocharged in this new wave of AI, and
Speaker 8: that's incredibly meritocratic, and we're seeing huge innovation at both
Speaker 8: ends of the.
Speaker 3: Spectrum supercharged in a meritocratic way. But you guys, is
Speaker 3: kind of have a big advantage in the access to
Speaker 3: the H one hundreds and the compute that the GPUs provide.
Speaker 3: Is there a way you can kind of quantify the
Speaker 3: advantage for me? I think a lot of people will say, Okay,
Speaker 3: we have Inflection AI and PI, how is it similar
Speaker 3: and or different to open AI and GPT three point five.
Speaker 3: What is the difference technologically and the goals as well?
Speaker 8: Yeah, it's a fair question. So our most recent LLLM,
Speaker 8: which is called Inflection one, is actually better on all
Speaker 8: of the public benchmarks than googled Palm one. Deep minds
Speaker 8: Chinchilla and open AI's three point five, which is a
Speaker 8: great achievement for a small organization like ours. In terms
Speaker 8: of the total amount of compute that we have, the
Speaker 8: twenty two thousand, h one hundreds in aggregate represents three
Speaker 8: times more computation than was required to train GPT four
Speaker 8: according to the best guesses of the rumors online these days.
Speaker 8: So it is a seismic amount of compute and it
Speaker 8: gives us an enormous advantage because we're really concerned with
Speaker 8: building the absolute cutting edge, like we really want to
Speaker 8: build the absolute best experiences in the world, so that
Speaker 8: when you get access to your personal AI PI, it's
Speaker 8: going to be aligned with your interests and on your
Speaker 8: team and increasingly be able to do useful things for you.
Speaker 8: It will book, you know, appointments for you, it will
Speaker 8: plan holidays, it will buy things for you and be
Speaker 8: a scheduler. And everybody has been waiting for that moment
Speaker 8: when the real personal digital assistant arrives, and we think
Speaker 8: that PI, you know PI dot ai where where you
Speaker 8: can access it online, is really going to be that assistant.
Speaker 3: Mastafa, you use words like building and I think about
Speaker 3: your past, your career, your time, at DeepMind Google. How
Speaker 3: important is it right now that you are basically moving
Speaker 3: from research to real world introduction of a tool. You know,
Speaker 3: a lot of people are calling to hit the brakes
Speaker 3: right on development. That seems to be the point of differentiation,
Speaker 3: moving from development of future generations and models, or indeed
Speaker 3: the research arm to having a product that businesses and
Speaker 3: consumers can use.
Speaker 8: I mean, AI is now coming of age. I mean
Speaker 8: this is going to be the meta technology of our times.
Speaker 8: It is going to be the technology that enables everything else,
Speaker 8: just like electricity or steam powered the last huge industrial revolutions.
Speaker 8: And so that's very exciting for us because it's a
Speaker 8: very practical time. You know, we're doing applied research, We're
Speaker 8: getting things to work in production and at scale with
Speaker 8: millions of users. And that's really the fun of it
Speaker 8: is making these things very very useful and seeing how
Speaker 8: they save time, improve performance, increase quality, and increasingly enable
Speaker 8: us to actually create completely new experiences that technology has
Speaker 8: never enabled before. I kind of think of this as
Speaker 8: a new sort of design material. It's a new clay
Speaker 8: that we can use to mold and create emergent, entirely personalized,
Speaker 8: and completely adaptive experiences. Which are going to feel very
Speaker 8: unlike the kinds of static user interfaces that we've had
Speaker 8: of the past. I mean, today, a website is a
Speaker 8: website is a website. It's just static and two D
Speaker 8: and it stays the same. Tomorrow, your conversational AI is
Speaker 8: going to enable you to experience dynamic, real time generated
Speaker 8: personalized user interface and it will feel really magical compared
Speaker 8: to what we've had in the past and.
Speaker 2: The stuff of what scares you in all of this.
Speaker 8: I think what's amazing about this technology is that it
Speaker 8: is the ultimate force amplifier. Right wherever there is a
Speaker 8: desire to take actions in the world to generate new content,
Speaker 8: you know, people are now going to have access to
Speaker 8: a tool that makes that easier to plan and to create.
Speaker 8: And of course, you know that's going to lower the
Speaker 8: barrier to entry to create chaos, and some people, you know,
Speaker 8: with bad intentions will choose to you know, amplify the
Speaker 8: disruption unfortunately. But I'm pretty confident that the vast majority
Speaker 8: of people are going to use these tools for incredible
Speaker 8: good and that where there are downsides, like for example,
Speaker 8: the spread of misinformation or the growth of counterfeit people
Speaker 8: which imitate you know, real humans. I think we're going
Speaker 8: to get control of that pretty quickly.
Speaker 3: And the stuff that you're joining us from London, What
Speaker 3: are you doing in my old stumping ground, my hometown.
Speaker 8: Well, this week coming up, we have a hackathon with
Speaker 8: our team. We relocate to a different city, you know,
Speaker 8: every month or so we get together and we work
Speaker 8: on a project. So you should expect some exciting new
Speaker 8: product features to be coming out in the next few week.
Speaker 8: It's just a great time to be building. So it's
Speaker 8: great to be here in London in the summer too.
Speaker 3: Inflection Ai CEO Ma Stuffer Salum and I feel like
Speaker 3: I see you every week. But we're on a good trend.
Speaker 3: Thank you so much. All right, time for talking tech.
Speaker 3: First up, the Netherlands published new export controls that will
Speaker 3: restrict more ASML chip making machines from being sent to China.
Speaker 3: This new Dutch regulation will force ASML to apply for
Speaker 3: shipping licenses to export DUV systems as early as September first,
Speaker 3: and one of Apple's biggest supplies, Foxconn, will invest about
Speaker 3: two hundred and forty six million dollars in two new
Speaker 3: projects in Kwang Nin, Vietnam. The plants FECV and FMMV
Speaker 3: FOXCN were awarded investment licenses and will begin operations in
Speaker 3: twenty twenty four and twenty twenty five.
Speaker 2: Plus.
Speaker 3: Airbnb is dismissing data in a viral that suggested revenue
Speaker 3: for property owners in some US cities was down nearly
Speaker 3: fifty percent. Airbnb spokesperson Sam Rendell said the data is
Speaker 3: not consistent with airbnbs and that the demand for short
Speaker 3: term rentals is alive and well. Joining us for more
Speaker 3: to talk about this, Bloomberg's Natalie Lung.
Speaker 2: Natalie explain this one to me.
Speaker 3: There was a viral tweet we're going to show it
Speaker 3: in just a moment that said basically, people that have
Speaker 3: Airbnb homes, they're not making any money.
Speaker 5: Right.
Speaker 4: So this viral tweet that came out around two days
Speaker 4: ago that showed had data from all the rooms which
Speaker 4: aggregates Airbnb and vrbo listings data showing in cities like Sevenville, Phoenix,
Speaker 4: Austin are seeing revenue per listing drop nearly fifty percent,
Speaker 4: And what's god people talking about this data is obviously
Speaker 4: the fixed, but also people were wondering like the accuracy
Speaker 4: and veracity of the data because there was an other
Speaker 4: data source, air DNA, which is also widely cited by
Speaker 4: the hotel and short ton reto industry.
Speaker 5: Their data shows for.
Speaker 4: The same markets, the decline is more muted, so around
Speaker 4: in the single digits.
Speaker 5: The biggest one was around nine percent.
Speaker 2: Natalie very quickly Airbnb's response to.
Speaker 4: This, Yes, they are saying this data is not consistent
Speaker 4: with what they're seeing. They reported a record revenue in
Speaker 4: verset Q and they're still seeing shorng demand for short tomentos.
Speaker 3: All right, Bloomberg's Natalie Lung reporting there out of the
Speaker 3: East Coast.
Speaker 2: Thank you so much.
Speaker 3: Welcome back to Bloomberg Technology and lovel here in San Francisco.
Speaker 3: Let's turn to data intelligence platform Elation, recently named Data
Speaker 3: Governance Partner of the Year. But get this by both
Speaker 3: Snowflake and Data Bricks CEO Sachin Sanghani joins me here
Speaker 3: in San Francisco for more. Find this really interesting because
Speaker 3: Snowflake and Data Bricks, you could call them frenemies, you
Speaker 3: could call them rivals. They both pick you. That's an
Speaker 3: interesting triangle. Tells me about the relationship with both companies.
Speaker 9: And thank you for having me. It's great to be here.
Speaker 9: Both companies are quite interesting. They had their conferences this week,
Speaker 9: both at the same time, both at the same time,
Speaker 9: which may have been purposeful, may not. But both of
Speaker 9: them had twelve thousand attendees at the conference. So while
Speaker 9: they both operate in the same space, they also have
Speaker 9: quite distinct audiences that use them and leverage them and
Speaker 9: quite indicative of the growth in data. If you think
Speaker 9: about ten years ago when Elation was founded, when data
Speaker 9: Bricks was roughly founded, with Snowflake was roughly found, did
Speaker 9: these are companies that had twenty five hundred people at
Speaker 9: the biggest data conferences and now you have almost ten
Speaker 9: times that amount. So both of them are indicative of
Speaker 9: the massive growth and data and we're excited to be
Speaker 9: a part of it and excited to rationalize all of
Speaker 9: this data in the ecosystem.
Speaker 3: I reported recently that data Bricks is SQL producted passed
Speaker 3: one hundred million dollars in any lized revenue. That's an
Speaker 3: area they're trying to grow. Kind of puts them in
Speaker 3: an interesting territory with Snowflake. How do you work with
Speaker 3: both companies? What is the interplay between Elation and their
Speaker 3: both sort of that I mean everything from mL and
Speaker 3: AI through to cloud based enterprise is interesting.
Speaker 9: So we describe Elation as a data intelligence platform.
Speaker 2: What is that?
Speaker 9: What does that exactly mean? Well, if you live inside
Speaker 9: of the standard enterprise, think about companies like Pfizer and
Speaker 9: Cisco and Virsion Australia, Nasdaq, all of whom are Elation customers.
Speaker 9: These are companies that have petabytes and petabytes of data
Speaker 9: strewn across data bricks, Snowflake, Amazon, Microsoft, Oracle, all of
Speaker 9: this legacy technology that it has existed since, you know,
Speaker 9: the last twenty years. And so what Elation does is
Speaker 9: it provides a map of your data so that any
Speaker 9: person can find and understand and trust that data. And
Speaker 9: as a result of that, we have over five hundred customers,
Speaker 9: thirty five of Fortune one hundred use us. But the
Speaker 9: broad idea is that if you exist inside of one
Speaker 9: of these companies, you basically are existing. If you don't
Speaker 9: have Elation, you know, as somebody maybe who's trying to
Speaker 9: navigate the streets of Boston without a map, or you know,
Speaker 9: try to navigate the web without Google, it's just impossible
Speaker 9: to do, and we provide you with that capability.
Speaker 3: The specific use case right now is generative AI and
Speaker 3: indistinction from AI more broadly, because you have to use
Speaker 3: your own data set to make a generative AI tool
Speaker 3: relevant to whatever it is you do. Where does elation
Speaker 3: come in in that process?
Speaker 9: So you can't do trusted AI without having tru data
Speaker 9: and your own data and on your own data or
Speaker 9: even on third party data. So, if you think about
Speaker 9: all of these models, they operate on a garbage in,
Speaker 9: garbage out basis, and particularly in the realm of structured data,
Speaker 9: if you have a really highly well trained model operating
Speaker 9: off of very bad, poor data, what you're going to
Speaker 9: have is multiplicatively wrong answers. You're going to get consistently
Speaker 9: bad outputs. And so the ability to be able to
Speaker 9: locate the right data sets, the ability to understand that
Speaker 9: the data that you're feeding this model is appropriate and
Speaker 9: well is a massive problem that every one of these
Speaker 9: companies has to deal with, and frankly that Snowflake in
Speaker 9: Data Bricks has to deal with in order to get
Speaker 9: their customers to adopt at scale.
Speaker 3: The simple concept of the company elation is to help
Speaker 3: an organization it's users find manage trust the data that
Speaker 3: they're looking at. There's a lot of interest in your company,
Speaker 3: the transparency. You raised one hundred and twenty three million
Speaker 3: dollars in November. I think that's right, and Data Bricks
Speaker 3: is Drum did participate in that, so that's correct. You
Speaker 3: are their most trusted partner, but they also are one
Speaker 3: of your back is interesting. Valuation as well, one point
Speaker 3: seven billion dollars. How do you grow your business from here?
Speaker 9: We were, interestingly at that point in time in November,
Speaker 9: thirty percent up up when the rest of the market
Speaker 9: was seventy percent in.
Speaker 2: Top line growth. Valuation got it.
Speaker 9: So our prior around valuation was done in twenty twenty one,
Speaker 9: which was a close to the top of the market,
Speaker 9: not quite exactly the top of the market, but we
Speaker 9: were still fifty percent up when the rest of the
Speaker 9: market was seventy percent out, which is an indication to
Speaker 9: both the strength of the market but also the strength
Speaker 9: of the business in that last round. Snowflake was an
Speaker 9: investor in our company. And why are these companies invested
Speaker 9: Because fundamentally, you can have all of the data in
Speaker 9: the world, but if you can't use it, if you
Speaker 9: can't understand it, if people aren't enabled with it, then
Speaker 9: it's really quite valueless. And so from our perspective and
Speaker 9: I think from theirs, the real problem is enabled hundreds,
Speaker 9: if not thousands of people within the enterprise to actually
Speaker 9: leverage this stuff at scale, and the road has been
Speaker 9: up into the right in general, but there is a
Speaker 9: lot of variation in terms of the returns on these projects,
Speaker 9: and so being able to return more reliably by basically
Speaker 9: building skills within each of these companies, within many of
Speaker 9: these companies, that's real trick, and that's what we try
Speaker 9: to help.
Speaker 3: With Elation CEO Sachi and Sanghani here with us in
Speaker 3: San Francisco and Bloomberg Technology.
Speaker 2: Thank you. Sum up and actually coming up, we'll talk.
Speaker 3: To Data Breaks, investor Race Capital about AI some more,
Speaker 3: also the m and A landscape and what the VC
Speaker 3: world has to say about literally everything we've been talking
Speaker 3: about on the show, ed if Young Race Capital coming
Speaker 3: up next, Let's get a quick check on Uber shares
Speaker 3: where they're trading up one point six percent in the session.
Speaker 3: Piece of news out overnight Parents, if you're listening, Uber
Speaker 3: is giving parents and caregivers the option to request a
Speaker 3: ride on the app with a car seat as part
Speaker 3: of a part and a shit with Nuna Baby which
Speaker 3: is a baby gear brand, but it's kind of a PSA.
Speaker 2: If you're out.
Speaker 3: There and you're a new A user and you got kids, well,
Speaker 3: they've been thinking about that.
Speaker 2: This is Blomberg.
Speaker 10: AI has been a technology and development for decades. A
Speaker 10: lot of tech actually, I think originates from gaming as
Speaker 10: a use case.
Speaker 11: These large language models are very exciting and what they
Speaker 11: can do is they can act as an interface where
Speaker 11: you can finally talk to the computer in a way
Speaker 11: that you couldn't perform.
Speaker 2: With John AI.
Speaker 10: There is a new surface area, I would say in
Speaker 10: terms of both increasing productivity of workers, for example artists
Speaker 10: and gaming.
Speaker 12: AI will move into industries that were or are underserved
Speaker 12: by SaaS.
Speaker 11: AI is something where it can impact drug design, It
Speaker 11: can impact how we think about healthcare, how we allocate
Speaker 11: healthcare resources.
Speaker 13: I think San Francisco inarticular with the AI boom, is
Speaker 13: really about cerebral value.
Speaker 12: You'll walk around and literally, like how they talked about
Speaker 12: in the nineties, you'll see garage doors open and people
Speaker 12: on their computers and you'll literally see on the telephone
Speaker 12: polls flyers for AI happy hours, AI Hakathans.
Speaker 13: The smartest people in the world are sitting in those cafes,
Speaker 13: you're having discussions not just about starting their companies, but
Speaker 13: also what is the cutting edge of what these AI
Speaker 13: models can do.
Speaker 3: That was just some of our VC guests weighing in
Speaker 3: on AI and the rise of San Francisco is the
Speaker 3: epicenter of what's happening in AI. Let's move away from
Speaker 3: the Bay and stick with AI though, and check out
Speaker 3: other headlines in the world a venture capital.
Speaker 2: Just take a look at climate tech.
Speaker 3: It's been an investing bright spot since twenty twenty one
Speaker 3: reikian deals as other sectors stagnated, but the first half
Speaker 3: of twenty twenty three saw a forty percent decrease in
Speaker 3: climate venture funding that according to Climate Tech VC, growth
Speaker 3: and late stage startups saw the biggest declines. Union fifty four,
Speaker 3: an African startup backed by Tiger Global, is entering the
Speaker 3: race to developed super apps as investors look to tap
Speaker 3: the continents increasingly tech savvy market. Called Chitchat, it offers
Speaker 3: secure messaging paired with dollar based virtual cards that it
Speaker 3: developed with MasterCard. The new app could debut in September
Speaker 3: and back to AI Intel leading a Series B financing
Speaker 3: round in the German AI startup alef Alpha, whose luminous
Speaker 3: language model competes with open ais Chat GPT. That's all
Speaker 3: according to Handle's Blat, citing sources. Nvidia and SAP also
Speaker 3: participating in the more than one hundred million euro financing round.
Speaker 3: Right back here to the US as digging some more
Speaker 3: into the bench capital landscape and AI and bring in
Speaker 3: Edith Jung, partner at Race Capital.
Speaker 2: That's a lot to take in, Edith.
Speaker 3: But where's your head at right now when it comes
Speaker 3: to investing in AI?
Speaker 14: I think you know, AI literally is happening everywhere, all
Speaker 14: at once. And this week or one of our portfolio companies,
Speaker 14: Data Brick acquired Mosaic mL for one point three billions.
Speaker 14: And obviously we're also really really into any infrastructure layer
Speaker 14: that is supporting the AI ecosystem.
Speaker 2: Let's go ahead.
Speaker 3: No, I'm sorry to interrupt you if I think we
Speaker 3: should stick with it and jump on this Data Bricks
Speaker 3: acquiring Mosaic pretty significant acquisition.
Speaker 2: What did you make of it?
Speaker 3: The rationale behind it, and what it's going to do
Speaker 3: to shake things up right now here in Silicon Valley
Speaker 3: in San Francisco.
Speaker 14: Yeah, it's really exciting time to be Like, if you
Speaker 14: look at what Data Brick. Particularly in the last sixty days,
Speaker 14: they acquire three different companies a Kia which is focused
Speaker 14: on more on the data governance, and then also Rubercon
Speaker 14: which is two weeks ago that focus on data storage.
Speaker 14: So now having will say it MLO, it basically complete
Speaker 14: the story building their own l M. I think like
Speaker 14: the world the world is heading is in some sense,
Speaker 14: I think enterprise AI is having an iPhone moment. Everybody
Speaker 14: want a piece of AI, but not just because you
Speaker 14: want to do AI doesn't mean that you will do
Speaker 14: it well. And I think a lot of the enterprise
Speaker 14: it's a little weary about feeding data to open the
Speaker 14: AI is just like a black box, right. The world
Speaker 14: wants open source, the world wants to keep the propriety data. Hence,
Speaker 14: you know, data bricks comes in because it's really built
Speaker 14: on a parte Spark, which is an open source framework,
Speaker 14: and now you'll be able to basically build your own
Speaker 14: enterprise l M on your own data. So that's really
Speaker 14: what the Data break is pushing. So at the end
Speaker 14: of the day, you know, we've been always been saying,
Speaker 14: you know, data is really the key goal mine and
Speaker 14: for us, the way that we look at in terms
Speaker 14: of our investment is who actually have access to a
Speaker 14: propriety data. And it's not just about training a general
Speaker 14: personal AI because if you think about it, right, if
Speaker 14: I asked a question to CHATGBT on, you know, who
Speaker 14: is the best doctor My mom recently have a heart
Speaker 14: problem and she would rather talk to a doctor that
Speaker 14: have seen you know, thousands of similar patients with similar
Speaker 14: dcs versus just you know, I'm not quite sure where
Speaker 14: the data come from. So essentially that's what your data brains.
Speaker 2: Is trying to do. So there's also the transactional part
Speaker 2: of this.
Speaker 3: We had Ali Godzi, the CEO Data Breaks, on the
Speaker 3: show two weeks ago and he said, quote, when it
Speaker 3: comes to AI right now, you have to pay up,
Speaker 3: in other words, get your check book out valuations.
Speaker 2: This is getting a little big.
Speaker 3: You think about Inflection, we reported with the CEO and
Speaker 3: the show today one point three billion around at four
Speaker 3: billion proportionately.
Speaker 2: What do you make of that?
Speaker 14: Yeah, I really enjoyed your segment with the CEO. Inflection
Speaker 14: one point three billion dollar rates is exactly the same
Speaker 14: amount how much Ali have paid for Mosaic mL and
Speaker 14: but as you mentioned earlier in the show, that Inflection
Speaker 14: actually has access to the H one hundred and their
Speaker 14: partnership with Nvidia, which to me is super fascinating and
Speaker 14: in some sense, yes, there's a lot of hype, but
Speaker 14: yet I think there is like so much room and
Speaker 14: things going on that can be improved, not let alone.
Speaker 14: Obviously everybody is saying that we're building on LLM, but
Speaker 14: we also need to think about data privacy. We need
Speaker 14: to think about how do we correct hallucination. We don't
Speaker 14: want to just come up with some random recommendation for
Speaker 14: which doctor to go to, because there's a lot more
Speaker 14: tuning need to be done well.
Speaker 3: Edith on the point of Inflection, H one hundreds are
Speaker 3: everything in the AI story right now, the GPU compute power.
Speaker 3: Are you phoning up Ali at Data Bricks and saying
Speaker 3: what GPUs have you guys got access to you know
Speaker 3: down the road? How much of a concern is that
Speaker 3: for you as a bench capitalist.
Speaker 14: I think you know Ali have previously explained before, which
Speaker 14: is when you're training as much smaller subset of data set.
Speaker 14: What Reinflection is really focusing on is literally building a
Speaker 14: personal LM. Right so there could be an ad at
Speaker 14: a GPT or either GPT.
Speaker 2: But what data.
Speaker 14: Bricks is focusing on is training a much more success
Speaker 14: smaller data set of data, enterprise data. So in that
Speaker 14: sense you don't really need sort of the the H
Speaker 14: one hundred to train. But absolutely Nvidia is on fire,
Speaker 14: being over a trillion dollars in market now and being
Speaker 14: able to secure the chipset, especially the H one hundred
Speaker 14: Order eight one hundred is super super important for not
Speaker 14: all LOM focused companies.
Speaker 3: Edith Young, Race Capital General partner, is so good to
Speaker 3: catch up. Thank you for joining us out of New
Speaker 3: York time now for what's going viral and it's the
Speaker 3: number one trending on Google trends right now. In a
Speaker 3: six to three ruling, this US Supreme Court has stricken
Speaker 3: President Biden's plan to forgive student loans for some borrowers.
Speaker 3: To get more context about this ruling and who is
Speaker 3: the most impacted, Bloomberg's Ryan Tige beckwith in Washington, and
Speaker 3: of course I will Street reporter Narlie Bassek out in
Speaker 3: New York bear with me headlines crossing the Bloomberg terminal.
Speaker 3: President Biden saying in a tweet, the High Court ruling
Speaker 3: on student loans is quote unthinkable. The Supreme Court striking
Speaker 3: down student debt relief is wrong. The fight is not
Speaker 3: over on student loan relief. That is President Biden's response
Speaker 3: ryan based on the court decision.
Speaker 2: Where do we stand right now?
Speaker 15: This doesn't leave President Biden with a lot of options.
Speaker 15: There's a lot of smaller, sort of more targeted things
Speaker 15: that he can do for giving student loans to certain
Speaker 15: sort of groups like veterans or people who have become
Speaker 15: disabled or something like that. But he's not going to
Speaker 15: be able to do the kind of large scale program
Speaker 15: here like he was proposing. They pretty much ruled that out.
Speaker 15: So I think you're going to see a push for
Speaker 15: these smaller things, and then you're going to see a
Speaker 15: renewed push in twenty twenty four as a campaign issue
Speaker 15: for Congress to take some kind of action on its own.
Speaker 3: Shanali, we need to talk about the technology side of
Speaker 3: this story, in particular fintech. The market reaction was in
Speaker 3: SOFI volatility, and I think we had a hole at
Speaker 3: one point.
Speaker 2: What is happening that.
Speaker 16: Yeah, remember there's not a lot of lenders that are
Speaker 16: in the student loan environment here. In fact, the government
Speaker 16: itself is one of the largest banks when you think
Speaker 16: about it, because there's so much debt on the government's
Speaker 16: own balance sheet. In terms of private lenders, it's SOFI,
Speaker 16: which is really one of the biggest out there, and
Speaker 16: SOFI has initially built so much of their business model
Speaker 16: around it. Ed this end of the student loan pause
Speaker 16: is poised to help SOFI, but remember, as students start
Speaker 16: to look to refinance, interest rates are much much higher.
Speaker 16: There are a lot of unknowns about what this moratorium
Speaker 16: pose it mean, and what it means now that many
Speaker 16: others forty million people may not anymore face this idea
Speaker 16: of forgiveness. What does it also mean for SOFI at large?
Speaker 16: You've had SOFI anyways over the last couple of years
Speaker 16: really start to pivot as business model away from being
Speaker 16: so reliant on student loans and looking to other areas instead.
Speaker 16: So big question marks about the through loan business moving forward,
Speaker 16: as well as what this still large part of Sofi's
Speaker 16: business model means, but also how they continue to keep
Speaker 16: diversifying away from it and who fills the student loan
Speaker 16: gaps in between.
Speaker 3: Ryan So much of the Bloomberg technology audience might be
Speaker 3: technology sector employees founders who are trying to make their
Speaker 3: world weigh in the world with student loans, and it
Speaker 3: makes me ask you the politics of this. This was
Speaker 3: really important for Biden's presidency.
Speaker 15: Right, I mean, this is one of those things young
Speaker 15: people helped put him in the White House, and this
Speaker 15: is a top priority among a lot of young people.
Speaker 15: So he's going to be motivated to continue to push
Speaker 15: on this. His hands are tied unless he wins back
Speaker 15: the House and the Senate. It's possible that he could
Speaker 15: do something in a second term if he had both
Speaker 15: of those through budget reconciliation, which doesn't subject to the filibuster.
Speaker 15: So there's some potential there that this could be an
Speaker 15: issue that he runs on and one that would motivate
Speaker 15: young people, which I think benefits And politically, it's clearly
Speaker 15: on demographic lines. Republicans of all come out against, you know,
Speaker 15: in favor of this Supreme Court ruling who are running
Speaker 15: for president, So it'll probably be a dividing line in
Speaker 15: the twenty twenty four election.
Speaker 2: Shnali target.
Speaker 3: Also moving to the downside, the economic impact here on
Speaker 3: the consumer is a big thing.
Speaker 2: It's a huge thing.
Speaker 16: Remember, student loans on average are between two hundred to
Speaker 16: three one hundred dollars a month ed. That is concert tickets,
Speaker 16: that is food, that is travel, that is retail. So
Speaker 16: of course you are going to see an impact here.
Speaker 16: Remember we've been in a moratorium, which is why we
Speaker 16: have that huge unknown here in terms of what that
Speaker 16: impact will be for so many borrowers to have to
Speaker 16: not only start repaying again, but also have to contend
Speaker 16: with the idea that much of this won't be forgiven.
Speaker 2: Bloomberg's Ryan T.
Speaker 3: Beckwith Shnali Basseck on the story, will continue to track.
Speaker 2: That does it for this edition of Bloomberg Technology.
Speaker 3: But catch me on a Twitter spaces in an hour's time,
Speaker 3: Apple three trillion mark germ, and this is Bloomberg Technology,