Speaker 1: From Mahart.
Speaker 2: We're Innovation, Money and Power Collie in Silicon Vallet NBN.
Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.
Speaker 3: I'm Carolin Hyde at Bloomberg's world headquarters in New York.
Speaker 4: And I met Lovelow in San Francisco. This is Bloomberg
Speaker 4: Technology coming up.
Speaker 3: The race to regulate artificial intelligence. It's underway in Washington
Speaker 3: as his Open AI CEO Sam Altman lays out the
Speaker 3: benefits and the risks to senators, and.
Speaker 4: The CEO of Andresen backed Hippocratic AI joins us in
Speaker 4: studio to discuss their generative AI healthcare tech.
Speaker 3: An X, the parent company of Twitter, has made as
Speaker 3: first acquisition a tech talent recruiting service called Laski. We
Speaker 3: discussed why verse four almostlet's get to these markets because
Speaker 3: once again we're actually seeing big tech on top lackluster
Speaker 3: trading day muted as we worry about the debt ceiling.
Speaker 3: The arguments still abound between left and right. We're seeing
Speaker 3: that's that one hundred and five tens percent big tech
Speaker 3: scene as some sort of haven at the moment. We'll
Speaker 3: talk about the individual names with Ed, but all country
Speaker 3: world indext as I show the world is more downpat
Speaker 3: on markets at the moment. Bank of America really showing
Speaker 3: how much risk a version there is coming from traders
Speaker 3: at the moment, and we're seeing down by three tenths
Speaker 3: of a percent, people not wanting to add to the
Speaker 3: stock market.
Speaker 5: Right now.
Speaker 3: Across the world, we're seeing tenure yield actually up six
Speaker 3: bass points, even as we see in the individual retail
Speaker 3: data coming out showing you and I are still willing
Speaker 3: to spend in this inflationary data.
Speaker 5: It seems as though.
Speaker 3: Some of that federal reserves speak coming from Loretta Mesta
Speaker 3: from Barkin seem to be hinting the look that they're
Speaker 3: still all.
Speaker 5: Eyes on inflation.
Speaker 3: Let's someone look at what's happening in terms of bitcoin
Speaker 3: as well. Because the dollar is out performing, that means
Speaker 3: bitcoin's on the downside. We're off by about a percentage
Speaker 3: point in the day, still languishing around twenty seven thousand.
Speaker 3: ED dig into some of the big movers because there
Speaker 3: are points in the up side from big tech today.
Speaker 4: It's like a market that's treading water when you think
Speaker 4: about the macro, but when you think about the micro,
Speaker 4: there are some stories out there Tesla up one point
Speaker 4: six percent the AGM after the bell today, but Bloomberg
Speaker 4: reporting overnight, according to sources, Shanghai is moving towards trial
Speaker 4: production of an updated Model three that's supporting the stock. Baidu,
Speaker 4: speaking of China, also up three point three percent. Strong earnings,
Speaker 4: a beat on the top and bottom line. It's like
Speaker 4: a post Chinese New Year rebound, a reopening of that economy,
Speaker 4: and it is boosting China tech. We get Ali Barber
Speaker 4: later in the week, so we're going to continue to
Speaker 4: watch China tech, especially the US listed shares of those names.
Speaker 4: Ai Ai is Everything. I just put a Twitter out
Speaker 4: there on video. All it said was Ai is everything.
Speaker 4: And then if you look at equity markets, we've discussed
Speaker 4: and we looked at all the column inches dedicated to
Speaker 4: how a lot of the momentum in the start of
Speaker 4: twenty twenty three originates for investor enthusiasm for Ai. Amazon
Speaker 4: and Alphabet pair and of Google, both big movers to
Speaker 4: the upside, both big points gainers on the Nasdaq one hundred.
Speaker 4: We'll give you the detail and why later in the show.
Speaker 4: But Bloomberg reporting that if you look at the signs
Speaker 4: Amazon might be bringing a trat GPT style bot to
Speaker 4: Amazon dot Com, which is something we've been waiting for.
Speaker 4: But that's what the talk is about this Tuesday morning.
Speaker 4: Artificial intelligence it is.
Speaker 5: And how to regulate it.
Speaker 3: And right now Sam Altman, the CEO of Open ai,
Speaker 3: really telling law makers on Capitol Hill about perhaps steps
Speaker 3: necessary to put in place rules around AI technology. He
Speaker 3: says is so powerful that he's worried it could have
Speaker 3: repercussions quote an a level far beyond anything we're prepared for.
Speaker 3: He also said, look, it's going to choose the labor market.
Speaker 6: Take a listen, GBT four A will I think entirely
Speaker 6: ontomate away some jobs and it will create new ones
Speaker 6: that we believe will be much better.
Speaker 3: Pleased to say, we've just pulled out of that hearing
Speaker 3: ed Anna Edgerton, who's been really listening into not just
Speaker 3: Sam Altman, but we've also heard from representatives from IBM who,
Speaker 3: well we know that IBM is already saying they're cutting
Speaker 3: their back office staff most likely calls of AI and
Speaker 3: scientists represent in too.
Speaker 5: What's the key takeaway thus far?
Speaker 7: It really has been all focused on regulation. You have
Speaker 7: Sam Altman of open AI and Christina Montgomery, the chief
Speaker 7: Privacy and Trust Officer for IBM, almost pleading with lawmakers
Speaker 7: to regulate this space. They want guardrails and they want
Speaker 7: certainty to protect against the most dangerous abuses of this
Speaker 7: powerful technology. And we hear it from the senators themselves.
Speaker 7: They say, we know this is a space that needs
Speaker 7: new rules, but they are the first to recognize that
Speaker 7: Congress has not been able to regulate the technology we
Speaker 7: already have. Social media has been a big failure for
Speaker 7: the US Congress, and they are looking to do a
Speaker 7: better job as they learn more about artificial intelligence.
Speaker 4: While you join us from the hill and some outman
Speaker 4: continues to speak, and he's saying that the US should
Speaker 4: form an agency to license some AI efforts. A lot
Speaker 4: of bench capitalists and founders I know do not agree
Speaker 4: with the idea of licensing. They think it's basically a
Speaker 4: block to innovation. When you have hearings like this, also
Speaker 4: depends on the questions that get asked. Sometimes these lawmakers
Speaker 4: go way off topic. How much have they asked about
Speaker 4: US leadership in the field of artificial intelligence Outside of
Speaker 4: the regulatory debate.
Speaker 7: There have been some thoughtful questions on this and He's
Speaker 7: had some thoughtful answers as well. He made a really
Speaker 7: interesting point when he said, you know, the US can
Speaker 7: leverage its leadership in the development of microelectronics and ships
Speaker 7: that are needed to run.
Speaker 5: These powerful AI systems.
Speaker 7: The US can leverage that leadership to encourage global governance
Speaker 7: so that not only are we setting rules here in
Speaker 7: the United States, but he made the point that we're
Speaker 7: not the only ones developing this technology. This is something
Speaker 7: that has a potential to impact the whole world, and
Speaker 7: for when it comes to governance of this new technology,
Speaker 7: it really needs to happen on a global level.
Speaker 3: To that end, many will be unsurprised to know that
Speaker 3: the EU has kind of been leading the regulatory charge.
Speaker 3: They're already proposing potential laws in the next month that'll
Speaker 3: be eyed by.
Speaker 5: The entire parity of the European Commission.
Speaker 3: I'm interested in how much you think we'll make is
Speaker 3: all seeing what Europe is looking at all thinking about
Speaker 3: the global ability to regulate.
Speaker 7: Well, certainly US lawmakers are casting and their counterparts over
Speaker 7: in Europe. And Christina Montgomery of IBM had an interesting
Speaker 7: little comment in her opening statement. She said, there's been
Speaker 7: a lot of hype around generative AI, but that doesn't
Speaker 7: mean we should move away from the risk based approach
Speaker 7: that they started taking in Europe. And that was kind
Speaker 7: of a reference to what we see happening around Europe's
Speaker 7: AI Act, where they had this really well thought out
Speaker 7: regulation based on the risk of the use of AI
Speaker 7: rather than the actual development of this technology. And now
Speaker 7: you have chat GP exploding onto the scene and regulators
Speaker 7: thinking well, maybe we need include this kind of general
Speaker 7: use tool in this regulation as well. And she's trying
Speaker 7: to argue, that's what we shouldn't do. We shouldn't look
Speaker 7: at the hype around chat GPT, these other generative AI
Speaker 7: products and kind of project that onto the rest of
Speaker 7: the artificial intelligence ecosystem, which includes the kind of enterprise
Speaker 7: AI that is offered by companies like IBM.
Speaker 3: Yeah, it really is about application for many at the moment,
Speaker 3: and Juton, we thank you so much to get her
Speaker 3: back onto that hearing at the moment and fantastic analysis
Speaker 3: coming from Capitol Hill. What about those that used to
Speaker 3: advise governments, what about those that are thinking about the
Speaker 3: application thus far of regulation. Lindsay Gorman's one of them,
Speaker 3: Senior fellow for emerging technologies of the German Marshall Funds,
Speaker 3: Alliance for Securing Democracy and Lizzie.
Speaker 5: Thus far are.
Speaker 3: The right guardrails being thought about here from a global perspective.
Speaker 1: So I do think that the right issues and problems
Speaker 1: are being fought about. But I will caveat that by
Speaker 1: saying that the problems that we can anticipate today might
Speaker 1: not be the problems that end up causing us the
Speaker 1: most consternation once these technologies become more widespread. But I
Speaker 1: do think the level of literacy when it comes to
Speaker 1: what the real concerns are and also what the possibilities
Speaker 1: are being thought about, concerns around elections and disinformation and
Speaker 1: disruption of the democratic process, concerns about workforce and job displacement,
Speaker 1: and concerns about how we interact with systems and what
Speaker 1: morals and values get put into these systems on the forefront.
Speaker 1: So I do think the right questions are being asked.
Speaker 1: Of course, we can only know what we know now,
Speaker 1: and ten years from now we might say that we
Speaker 1: were completely looking at the problems from a different era Linzee.
Speaker 3: When we look at what the EU, for example, is
Speaker 3: thinking of putting in place, they want to produce risk assessments.
Speaker 3: They want to see a summarize of copyrighted material that
Speaker 3: models have been trained on. They also want it to
Speaker 3: be flagged when you're looking at AI in general, but
Speaker 3: most notably if you're looking at deep fakes.
Speaker 5: Does that, to your point of view, go far enough?
Speaker 3: And ultimately, are we just in a game of whack
Speaker 3: a mole all over again?
Speaker 1: I certainly hope not. I think the EU has obviously
Speaker 1: taken one of the most aggressive approaches to thoughtful regulation
Speaker 1: of AI with the EUAI Act and the risk based
Speaker 1: approach now and the USNST has also put out a
Speaker 1: risk based framework on AI that's the National Institute of
Speaker 1: Standards and Technology, but it's completely voluntary. One thing that
Speaker 1: I think the EU has kind of in its pocket
Speaker 1: as perhaps an advantage in coming up with thoughtful regulation
Speaker 1: is that it already has existing frameworks around data privacy.
Speaker 1: Today at the hearing, you've heard multiple senators talk about
Speaker 1: the need for protecting data that's training these AI models,
Speaker 1: because ultimately, if you're training the data on certain models,
Speaker 1: that those biases and the biases and the data are
Speaker 1: going to be propagate and the values in the data
Speaker 1: are going to be propagated through.
Speaker 5: For the models.
Speaker 1: Now, the EU has the General Data Privacy Framework, the
Speaker 1: US doesn't have that, and it's a little bit concerning that.
Speaker 1: Despite the enthusiasm with which lawmakers are tackling the AI issue,
Speaker 1: which is a positive, that we're still not able to
Speaker 1: pass federal data privacy legislation. So I do think the
Speaker 1: has a leg up in applying their existing frameworks, and
Speaker 1: that's why we've seen countries such as Italy apply the
Speaker 1: General Data Protection Regulation to chat GPT and have that basis,
Speaker 1: what are the things that need to be demanded, the
Speaker 1: common uses, the justifiability of that which Maltman alluded to today.
Speaker 5: It is notable, isn't it.
Speaker 3: Every conversation we have tends to involve regulation. Everyone seems
Speaker 3: to agree it's needed and not just self regulation, but
Speaker 3: the applications of so doing is still sort of a
Speaker 3: black box here.
Speaker 8: Yeah.
Speaker 4: The difference our guests notifires off on this show f Lindsey,
Speaker 4: is that if you regulate the deep learning part, the
Speaker 4: training of the models, you might kill innovation. There is
Speaker 4: a difference between regulating inference or in other words, the
Speaker 4: use of artificial and technology the tool and the development
Speaker 4: of it. Where do you think we should focus our
Speaker 4: regulatory efforts.
Speaker 1: Yeah, this is really the debate that you think you
Speaker 1: heard in the hearing, which is do we take an
Speaker 1: approach of only regulating at the point where technology meets society,
Speaker 1: ie the applications, or do we need to regulate in
Speaker 1: the model development? And I think both have some merits. Clearly,
Speaker 1: we need to regulate in the former case and focus
Speaker 1: on the actual harms that are being caused in society
Speaker 1: or that could be caused.
Speaker 8: But that said, those.
Speaker 1: Harms are not technology neutral. They are not applicable regardless
Speaker 1: of how you train the model. So I think that's
Speaker 1: where it gets a little bit complicated, where actually the
Speaker 1: inputs to the training do make a difference on how
Speaker 1: the harms could get propagated once technology meets society. And
Speaker 1: this idea, though that lawmakers have said today that we
Speaker 1: had the Section two thirty where we said companies just
Speaker 1: go develop and we'll give you the space and not regulate.
Speaker 1: I don't think that's going to fly now in the
Speaker 1: AI era.
Speaker 4: Do you agree with Sam Autman that the US should
Speaker 4: establish an agency to license AI development.
Speaker 1: I would like to hear more arguments on both sides.
Speaker 1: To be honest, I think we've just gotten to the
Speaker 1: scratching the surface on whether we need a whole new agency.
Speaker 1: But the point that I really do agree with that
Speaker 1: Sam and others made is that we definitely need much
Speaker 1: more resources, whether that's with existing agencies or in fact
Speaker 1: a new agency. The idea that we could keep up
Speaker 1: with these developments and that regulators and policymakers could keep
Speaker 1: up with these developments without growing significantly more resources into
Speaker 1: just hiring technical experts to understand and to craft policy
Speaker 1: solutions on them, I think is completely completely crazy. So
Speaker 1: whether that's a new agency or significantly beefing up of
Speaker 1: existing agencies, we definitely need a significant resource investment.
Speaker 4: Should point out as well that it's not just Sam Outman,
Speaker 4: We've been talking a lot about him, but IBM's Chief
Speaker 4: Privacy and Trust Officer Christina Montgomery is also testifying in
Speaker 4: that Caroline and Lindsay Linda Gorman, Senior Fellow for Emerging
Speaker 4: Technologies at the German Marshal Fund, that thank You Grinder
Speaker 4: reporting first quarter earnings with revenue of fifty five point
Speaker 4: eight million dollars, up from forty three point five million
Speaker 4: dollars a year earlier around twenty eight percent gain year
Speaker 4: on year, still shares down after reporting a net loss
Speaker 4: of thirty two point nine million dollars. Let's bring in
Speaker 4: Grinder CEO George Arrison for more so kind of growth
Speaker 4: on the top line and I think actually a decline
Speaker 4: year on year on the bottom.
Speaker 8: Line or an EPs.
Speaker 4: But what is the difference in the environment at the
Speaker 4: beginning of this year versus last year for people interacting
Speaker 4: with one another?
Speaker 9: Yeah, so ook, I've only been on here for six months,
Speaker 9: so I can only speak about a beginning of last
Speaker 9: year per se.
Speaker 8: But this was and no one looks backward looking.
Speaker 9: And this year was really good and we grew really well.
Speaker 9: Our EBIDA was really strong as well, at thirty nine percent.
Speaker 9: Both growth and EBITA numbers exceeded our Follier guidance. The
Speaker 9: I think on the EPs side, there's just some stuff
Speaker 9: with warrants that makes that number look very different because
Speaker 9: of how you do work accounting. But that doesn't really
Speaker 9: impact how our business is doing, which is extremely well.
Speaker 9: Users are obviously very engaged and our overall average quarterly
Speaker 9: users also up quarter over quarter.
Speaker 4: So for what's driving the engagement, what is it that
Speaker 4: people are turning to Grinder for what is the behavior
Speaker 4: you see.
Speaker 9: Grinder has always had a lot of success in getting
Speaker 9: each new generation of people to come on the platform
Speaker 9: so on. Like a lot of other social media platforms
Speaker 9: that lose users in the new generation, we've actually not
Speaker 9: had that. We've kept users coming in and I think
Speaker 9: it frankly, the fact that all the users are there
Speaker 9: is another reason why people come back right like that,
Speaker 9: That engagement is really strong. And also Grinder's very authentic.
Speaker 9: Grinder was a company built by gay people for gay people,
Speaker 9: so it's very authentic to user base and I think
Speaker 9: that helps us as well. Obviously, we know users want
Speaker 9: more innovation the product, and that's something that we're very
Speaker 9: actively working on.
Speaker 5: Let's talk about the innovation. And in some ways it
Speaker 5: feels a bit old school. George, you've got Grinder Web.
Speaker 3: Talk to me about why you listened and heard from
Speaker 3: your user basis that's what they wanted totally.
Speaker 9: So yeah, we just launched Grinder Web. Kind of launch
Speaker 9: it this month in anticipation of Pride next month. And
Speaker 9: the thinking is that there are a bunch of features
Speaker 9: you can launch on the web that you can't really
Speaker 9: launch anywhere else because of limitations that the app store
Speaker 9: has put on you, and that's something that our uses
Speaker 9: very much want. So Grinder Web that we launch now,
Speaker 9: which is still in data and we help users try
Speaker 9: that out, is a way to set ourselves up for
Speaker 9: the future to launch additional features that are more specific
Speaker 9: to the use cases that our users want that we
Speaker 9: can't really do on the app.
Speaker 3: Monetization one are ways in which you're thinking about people
Speaker 3: using it paying for it in a different, more seamless
Speaker 3: way on the app itself and indeed on web totally.
Speaker 9: So what we've heard from users on kind of our
Speaker 9: subscription basis is they want two things. Number one, they
Speaker 9: want a slightly higher so a slightly lower cost model
Speaker 9: where we have an entry point that's not nineteen nine nine,
Speaker 9: but something lower than that with less features obviously because
Speaker 9: we do offer a very broad base of features in
Speaker 9: our nineteen nine nine tier, so we're working on that
Speaker 9: lower priced tier. And then they also want us to
Speaker 9: build more features on the higher end and are willing
Speaker 9: to pay for those. And obviously a lot of the
Speaker 9: add ons that overdating apps offer that Blender doesn't yet
Speaker 9: have aurur card we are building, and then we think
Speaker 9: there's a lot of opportunity to build functionality that supports
Speaker 9: activity that's already happening in the app, such as dating
Speaker 9: that we don't have functionally. For as far as building
Speaker 9: on grinder Web, we do have a big portion of
Speaker 9: users that are discrete, meaning they can't really be out
Speaker 9: for a variety of reasons, whether it's where they live
Speaker 9: or family situations, et cetera. And for them, grinder Web
Speaker 9: is a really great, just stinct building option that's not
Speaker 9: available yet, but it's coming because we do want to
Speaker 9: facilidate that. Based on what the users have asces used.
Speaker 4: For this past week, one Elon Musk said that Twitter
Speaker 4: or x the everything out adding some dating functionality was
Speaker 4: an interesting idea.
Speaker 8: How seriously do you take that threat?
Speaker 9: I mean, let's see what he does. I think it'll
Speaker 9: be interesting how he approaches things. And look, you never
Speaker 9: better against even musk rat. Nobody else has done what
Speaker 9: he's done in terms of how many companies is built.
Speaker 9: But we feel really good about our user base and
Speaker 9: the fact that our users very engaged with us. I
Speaker 9: think our engagement numbers are are frankly, very unusual. Nearly
Speaker 9: an hour of spending the app last year one hundred
Speaker 9: and eleven billion messages sent. So I'm not really worried
Speaker 9: about that from our user base perspective, but more broadly,
Speaker 9: certainly interesting grind.
Speaker 4: The CEO, George Harrison here in San Francisco, Thanks for
Speaker 4: your time, Carol.
Speaker 3: Yeah, let's just stick on the awning scene for a
Speaker 3: moment and look at the Chinese giant by Do shares
Speaker 3: traded here in the US.
Speaker 5: Actually, you have been performing really well.
Speaker 3: You see up three and a half percent there or thereabouts,
Speaker 3: and looks as though the company really managed to beat expectations.
Speaker 3: Stronger than expected revenue ten percent, it grew after its
Speaker 3: advertising in cloud businesses. This seemed to be benefiting from
Speaker 3: China's post pandemic reopening overall, so some strength there ed.
Speaker 5: Meanwhile, coming up that we've got to talk.
Speaker 3: About some warries post Silicon Valley bank collapse. The former
Speaker 3: CEO Greg Becker currently testifying before the US Senate committee.
Speaker 5: They're busy up on the hill today.
Speaker 3: He has to say, of course, about the focus the
Speaker 3: failure and what is next for regional banks more generally.
Speaker 5: We can dig into that in a minute. This is Bloomberg.
Speaker 3: We of course are dissecting everything that has been happening
Speaker 3: across in Washington, not only the AI focus of some outman,
Speaker 3: but Silicon Valley Bank focus Greg Becker. He's been testifying
Speaker 3: in front of the Senate Banking Committee today blaming social
Speaker 3: media in fact, for the bank's collapse. A slipe deeper
Speaker 3: into it all without one to no nationalibascond Sanni, he's
Speaker 3: gonna have a tough crowd. What ultimately do you think
Speaker 3: he's saying? Is it landing the way he hopes it too?
Speaker 5: Do you think what is.
Speaker 10: Interesting among the lawmakers here is you're hearing kind of
Speaker 10: two sides of a story. One is a set of
Speaker 10: lawmakers that are extraordinarily frustrated by the way SVB was
Speaker 10: managed and how much Greg Becker was paid. He declined
Speaker 10: to say whether he would give back some of his
Speaker 10: bonuses as a result of the bank's failure. And the
Speaker 10: ultimate you know, blamed mismanagement. There's a sense here also
Speaker 10: among the separate set of lawmakers that believe that a
Speaker 10: lot of this was brought on by the Fed's mismanagement
Speaker 10: as well as the fast rise in interest rates. You
Speaker 10: heard some lawmakers really attack the Biden administration here and
Speaker 10: the inflationary environment that had led to.
Speaker 5: These horror It is becoming bipartisan.
Speaker 10: It is becoming certainly very very very political on on
Speaker 10: tip of and we know also for its own worth here,
Speaker 10: we know that FED officials are also being grilled in
Speaker 10: Washington this week, and they have also outlined some series
Speaker 10: of their own failure of oversight for some of these
Speaker 10: firms as well, and.
Speaker 4: The FDI see of course, Sinnati, we have been listening
Speaker 4: into that, Harry. Let's take a listen to just some
Speaker 4: of what greg Becca had to say.
Speaker 11: I believe that svb's failure was brought about by a
Speaker 11: series of unprecedented events. Despite stark differences in our business models,
Speaker 11: news reports and investors wrongly lumped SVB and silver Gate together.
Speaker 11: Rumors and misconceptions quickly spread online, culminating on March ninth
Speaker 11: with the first ever social media bank run, leading to
Speaker 11: forty two billion in deposits being withdrawn from SVB in
Speaker 11: ten hours, or roughly one million dollars every second.
Speaker 4: He claims different facts as SVB Silvergate, that did we
Speaker 4: hear any sort of mission? Shinnati quickly on him taking
Speaker 4: responsibility for what happened.
Speaker 10: I don't think he took responsibility for all of it,
Speaker 10: and I think that's the important part here. Remember this
Speaker 10: idea of a social media fuel bank run. There's a
Speaker 10: lot still to be understood about how that happened, because
Speaker 10: remember every bank CEO across the country and every private
Speaker 10: equity from trying to back them is now having that
Speaker 10: same question can this happen again? That's why these hearings
Speaker 10: are still so important, because what kind of changes need
Speaker 10: to be made to the banking system coming out of this,
Speaker 10: beyond the politics that we're obviously seeing.
Speaker 4: Clay out today, all right, bloomboch Naali Bask on the
Speaker 4: Wall Street Beat, but a story that really hit here
Speaker 4: the heart of Silicon Valley.
Speaker 3: Welcome back to bloembog Technology. I'm Caroline hind and yelks
Speaker 3: Ed Lovelow.
Speaker 4: In San Francisco. All about AI. But let's get a
Speaker 4: check in on the market. I think there's still a
Speaker 4: lot of lingering concern care about the debt ceiling and
Speaker 4: the progress that we're seeing or lack ofb in Washington,
Speaker 4: DC and AWS that one hundred outperformance in tech up
Speaker 4: half a percentage point.
Speaker 8: We've been talking about do having strong earnings.
Speaker 4: That is an outperformer in terms of the US listed
Speaker 4: shares of China tech. Ali Barber reports later in the week.
Speaker 4: But there are some movers like ten Cent to the downside,
Speaker 4: the NAS that Golden Dragon China Index, that basket of
Speaker 4: US listed China shares down half percentage point, yields climbing
Speaker 4: higher six basis points three point six percent ish on
Speaker 4: the US ten year yield where we were kind of
Speaker 4: in March, Bitcoin back down towards twenty seven thousand US
Speaker 4: dollars per token.
Speaker 8: In terms of the individual.
Speaker 4: Movers, I talked a little bit about bay Do that
Speaker 4: moving to the upside, strong earnings beat top and bottom line,
Speaker 4: the story about a rebound in China after the Chinese
Speaker 4: New Year easing of restrictions, travels stargning back up. Also
Speaker 4: the ad business doing well and AI AI everything all
Speaker 4: the time AI.
Speaker 8: There's no sort of main catalyst.
Speaker 4: But you know, Alphabet, parent of Google, has seen gained
Speaker 4: since Google Io when we learn more about it's offering.
Speaker 4: Amazon Bloomberg reporting making moves bring us some of those details,
Speaker 4: because that is what the real mover is.
Speaker 3: To the upside is oh perfect segue ed into talking
Speaker 3: tech first up, Alphabet, you were just talking about making
Speaker 3: back market cap ground as its artificial intelligence gains. As
Speaker 3: you back on, remember it seemed to be lagging behind
Speaker 3: its peers, wasn't it, in the race to deploy generative
Speaker 3: AI products.
Speaker 5: Abundance of caution many would call it, But Google's parent.
Speaker 3: Company is added more than one hundred and fifteen billion
Speaker 3: dollars in market value. Some some veiling plans for its
Speaker 3: EI tools last week at the event you were at. Meanwhile,
Speaker 3: if you've been scouring the job boards for AI related jobs,
Speaker 3: Amazon I have some listed. The e commerce giant is
Speaker 3: planning to add chatchipt style search function to its online storm.
Speaker 5: It's scorning to job posts reviewed by Blue Vegnus.
Speaker 3: Of course, as part of a larger effort to rival
Speaker 3: efforts by Microsoft, by Google tweet these generative AI elements
Speaker 3: into its own search engine set.
Speaker 8: All right.
Speaker 4: Healthcare startup Hippocratic Ai staking its claim in the large
Speaker 4: language model boom with its tool, which it hopes to
Speaker 4: make medical care more accessible with The Palo Alto based
Speaker 4: company launched out of stealth today, raising fifty million dollars
Speaker 4: in a seed round from Andres and horror Itz and
Speaker 4: General Catalyst. Here in the studio with me Sinjo Munjawsha, sorry,
Speaker 4: CEO of Hippocratic AI. Fifty million dollars for a seed round.
Speaker 4: That's a lot of money. Tell me, let me just
Speaker 4: ask what is the valuation on this. You've come out
Speaker 4: with a large language model, you say is commercially ready, right,
Speaker 4: what's your valuation?
Speaker 12: You know, we're not announcing that today, but we really
Speaker 12: felt that generator of AI has really captured the imagination
Speaker 12: of really the world right, and it's captured the zeitgeist.
Speaker 12: And when you think about its application to healthcare, you realize,
Speaker 12: you know, there's three million missing healthcare workers in this country.
Speaker 12: We do not have enough people after the pandemic, so
Speaker 12: many burned out and there's really no way to close
Speaker 12: that gap except using technologies like Generative AI.
Speaker 7: To do that.
Speaker 4: But the misconception out there this morning is that you
Speaker 4: have released a chat gp T style bot that replaces
Speaker 4: the doctor the physician.
Speaker 8: That's not the case at all, though.
Speaker 12: Now now you know, we actually, I don't think the
Speaker 12: Generative AI is ready to do diagnoses. We think diagnoses
Speaker 12: needs to come much later when these models are safe.
Speaker 12: We think that there's a set of applications, you know,
Speaker 12: healthcare is way bigger than just the doctor. There are
Speaker 12: so many people.
Speaker 8: Who work out back office, and not just back office.
Speaker 12: You have registered dietitians, you have genetic counselors, you have
Speaker 12: many other roles that are supporting roles and supporting actors
Speaker 12: in the healthcare system that really could benefit from genitive AI.
Speaker 3: I'm interested in what you see as the regulatory environment
Speaker 3: with which you put this. People are going to be
Speaker 3: fearful of medical advice plus chatchipt, many already knowing that
Speaker 3: you shouldn't. You're not going to get an abundance of
Speaker 3: advice when you go into open AI's product, when you
Speaker 3: go into bard And interestingly, we're hearing from some Oltmann
Speaker 3: at the moment thinking about regulator pressure, saying that for
Speaker 3: open ai, for Google to take on board, but they
Speaker 3: don't want to slow down smaller startups. As a man
Speaker 3: who's been in AI for throughout your learning experience, when
Speaker 3: you're at university, when you went on to further your education,
Speaker 3: when you've gone on to build companies, is a regulation
Speaker 3: going to help or hinder you?
Speaker 1: You know?
Speaker 12: I think that this is an area that does need
Speaker 12: a regulatory framework and one that allows us all to
Speaker 12: create safe large language models in safe generative AI. You know,
Speaker 12: we decided as we were building Hippocratic AI that we
Speaker 12: wanted to be safety first. Like this was the foundation
Speaker 12: of how we designed the company and how we designed
Speaker 12: the product. I mean, you know, our name is hippocratic,
Speaker 12: like the hippocratic ohth Our tagline is do no harm.
Speaker 12: This is our number one focus as a company, and
Speaker 12: we focused on a set of key features to be
Speaker 12: able to do that, which I'm happy to.
Speaker 3: Share with Yeah, it's delve in because we understand your
Speaker 3: startup has the AI is possible that one hundred healthcare
Speaker 3: certifications and outperformed open AI. What is the data that
Speaker 3: you're training on and what are the safety prints you've
Speaker 3: wound into that.
Speaker 12: Yeah, so we built in four or five things to
Speaker 12: really make this safer. I mean, I think the first
Speaker 12: was we certified it. We didn't just say, hey, let's
Speaker 12: pass the us mL the medical licensing exam, where some
Speaker 12: of the language models have posted their results on. We said,
Speaker 12: let's also look at the naeclex, the nursing exam, the
Speaker 12: pharmacy exam, the naplex, and we just said, hey, let's
Speaker 12: go through all of these and we did one hundred
Speaker 12: and fourteen of these different exams, grouped them to groups
Speaker 12: like all the dental exams together, all the physician exams,
Speaker 12: and said.
Speaker 8: Hey, it's important to be certified.
Speaker 12: These are actually the exact exams you see at the
Speaker 12: end of your nurses name on her badge.
Speaker 8: She has all those little letters.
Speaker 5: We made sure we had all of those.
Speaker 12: Those same certifications used to hire healthcare workers, or the
Speaker 12: SA certifications we used and tested on our language model. Second,
Speaker 12: we actually recruited those exact same healthcare workers. So pediatric
Speaker 12: nurses came in and gave our system feedback on how
Speaker 12: it was doing on those questions. Our dietitians came in
Speaker 12: and did the same. And so we believe who's best
Speaker 12: to judge the accuracy of a healthcare of a language
Speaker 12: model than the people doing those.
Speaker 5: Exact jobs today.
Speaker 7: And so.
Speaker 12: You know, those are two of about four or five
Speaker 12: different things that we've done to really make this a
Speaker 12: safer system.
Speaker 4: Let's do a quick far around when do you make
Speaker 4: the LM open to the public.
Speaker 12: You know, we have decided on a threshold based launch
Speaker 12: strategy than a time based land strategy. We're saying when
Speaker 12: those professionals that I just told you about. When we
Speaker 12: have the dieticians using it and they say this is
Speaker 12: ready to go out, that's when.
Speaker 5: It'll go out.
Speaker 8: How do you monetize.
Speaker 12: We will figure that out after we make sure that
Speaker 12: we build a safe and ready language model. I think again,
Speaker 12: you can't say your safety first and be like I'm
Speaker 12: launching on this date. You have to say I'm launching
Speaker 12: when the language model is ready and the professionals who
Speaker 12: do that task today say it's ready.
Speaker 3: Minchelle, you said, and I'm sure you didn't. It was
Speaker 3: a sort of a comment that just comes out, you said.
Speaker 3: Nurses she and I'm in many ways when we say yeah,
Speaker 3: a lot on urs is our female. But therein lies
Speaker 3: some of the issue and the concern around bias within
Speaker 3: these sorts of AI models and the data that's run.
Speaker 5: I'm sure you're.
Speaker 3: Thinking deeply about how, particularly from a medical perspective, biases
Speaker 3: aren't built in. How do you counteract for that going forward?
Speaker 12: You know we've already begun testing the bias of the model.
Speaker 12: You can actually go on our side at hippocraticai dot
Speaker 12: com slash benchmarks and you can take a look at
Speaker 12: our first pass of assessing the bias of our model
Speaker 12: on a bunch of different dimensions, including certain ethnic biases
Speaker 12: and certain gender biases. And you know, so far, you know,
Speaker 12: we were able to show less bias than GPT four.
Speaker 8: But that's just the beginning.
Speaker 12: That's our first installment, our down payment on really just
Speaker 12: trying to say, hey, look, we just launched, but we're
Speaker 12: already testing this, we already care about this, and it's
Speaker 12: something that we're going to continue to work on each
Speaker 12: and every day.
Speaker 8: I just put out to our audience. I wrote about
Speaker 8: this this morning.
Speaker 4: Hippocratic AI they benchmarked, were tested against Chat GPT in
Speaker 4: one hundred and fourteen certifications. I went to open ai
Speaker 4: and asked for them to comment on that performance relative
Speaker 4: to Hippocratic AI. Open ai did not reply, just putting
Speaker 4: that out there to our globalance Caroline, thanks to munjow
Speaker 4: Shar of course, CEO of Hippocratic AI. On the day,
Speaker 4: they raised fifty million dollars in a seed from two
Speaker 4: big names now turning to m and a Twitter parent company,
Speaker 4: ex Corp, has acquired a tech talent recruiting service called
Speaker 4: Laski that, according to a Bloomberg source full disclosure Bloomberg
Speaker 4: Beta part of Bloomberg LP was an investor in Laski.
Speaker 4: Bloomberg's ashaccounts has US joined us with more Asia Laski.
Speaker 8: What is it and why.
Speaker 13: Laski is a early It was early stage startup that
Speaker 13: does recruiting, so it matches employers with candidates very straightforward.
Speaker 13: It's not exactly clear why ex corporate Twitter was interested
Speaker 13: in buying this company, but Musk has talked about this
Speaker 13: idea of creating an everything app, so it could be
Speaker 13: a part of that broader vision.
Speaker 3: So we're all left kind of trying to fill in
Speaker 3: the dots. Meanwhile, Lasky doesn't seem to be operating anymore
Speaker 3: online and I'm waiting for the latest tweet out of
Speaker 3: their pretty active tweeter in chief fir CEO.
Speaker 5: Does a lot online.
Speaker 3: What remind us of the overall vision of the X
Speaker 3: product because many would say that's why the new CEO
Speaker 3: of Twitter, for example, has come.
Speaker 5: On board, right.
Speaker 13: That's one thing that Musk has said when he announced
Speaker 13: that the hiring of Linda Yakarina officially on his Twitter account,
Speaker 13: he said, this is going to be part of the
Speaker 13: vision to create this everything app or this ex app,
Speaker 13: and so it must has been pretty vocal about this.
Speaker 13: He sees it as an app where you can do
Speaker 13: everything from maybe making payments like booking a ticket or
Speaker 13: sending money to a friend, and he hasn't exactly explained
Speaker 13: what it is, but he's taking ideas from things like
Speaker 13: Uber where you can order food and also order a
Speaker 13: cab or even we chat in China. So he's talked
Speaker 13: about Twitter being a place where you can do that,
Speaker 13: where you can do anything that you might be able
Speaker 13: to imagine, and adding in the payments infrastructure as well.
Speaker 5: Asia. It's great to couch ut with you. Thank you,
Speaker 5: Asha Counts.
Speaker 3: Meanwhile, we've got our VC Spotlight next Sad and it's
Speaker 3: with someone who well knows Eno Musk and is back
Speaker 3: to him and some of those other companies from New York,
Speaker 3: from San Francisco.
Speaker 5: It's a bloomberg.
Speaker 2: The last ten years of financial services has seen an
Speaker 2: extraordinary change. The advent of digital banking, mobile banking, and
Speaker 2: all of the technology enabled services that we have now
Speaker 2: come to consider to be table stakes. The next ten
Speaker 2: years is going to take that technology impact and expand
Speaker 2: it exponentially.
Speaker 5: There are enablers to that that the primary driver.
Speaker 2: Is going to be related to the deployment of artificial intelligence.
Speaker 3: Former JP Morgan Executive Live Masters. They're speaking about the
Speaker 3: big innovations that will reshape fintech space in particular, but
Speaker 3: actually every industry when it comes to AI. Let's bring
Speaker 3: in Andrea Lamari from Manhattan Ventures Partners.
Speaker 5: For more on the world of investing.
Speaker 3: The world of well in fact, your own portfolio is
Speaker 3: fascinating discord of course in many ways AI driven. But
Speaker 3: Klana one of those companies of fintech business that's already
Speaker 3: used the chat GPT plug in and open AI plug in.
Speaker 3: How are you thinking about the ethical way in which
Speaker 3: these companies do adopt and let this generative AI run
Speaker 3: loose on their own proprietary data.
Speaker 14: Thanks Carolyn, So overall we are really thinking about generative
Speaker 14: AI as a tool for good. But what it is
Speaker 14: showing to be is that companies are learning so much
Speaker 14: more about their consumer base and allowing their consumers to
Speaker 14: spend time showing trends in a much more vulnerable way,
Speaker 14: which we find fascinating. The way that Klarna is engaging
Speaker 14: with their customers on a new level, in a way
Speaker 14: that they're gathering the data to prove that there are
Speaker 14: ways to use and harness the data to really provide
Speaker 14: better products and services to consumers from a lending perspective
Speaker 14: and then from a spend perspective. And it seems as
Speaker 14: though consumers are really engaging with the AI in a
Speaker 14: way that just seems so much more real and authentic
Speaker 14: than they ever.
Speaker 4: Have if financial conditions are getting tighter, and it's hard
Speaker 4: out there for founders all bench capitals being pushed into
Speaker 4: making AI related investments that in any other economy or
Speaker 4: environment they just wouldn't normally make because of all of
Speaker 4: the hype.
Speaker 14: Overall, what's so interesting about the vcs in the space
Speaker 14: making AI bets is that so many companies we're already
Speaker 14: utilizing AI functionality as a way to harness data and
Speaker 14: then use insights of that artificial intelligence data to build
Speaker 14: better products. But what's funny is that vcs today are
Speaker 14: having a hard time determining what's actually going to make
Speaker 14: money at so some of these companies are really taking
Speaker 14: a push towards open sourcing the technology versus actually making
Speaker 14: it a repeatable, subscription based business. And I think that's
Speaker 14: the big debate within VC world, is what's going to
Speaker 14: actually make money.
Speaker 8: I'm going to jump on that.
Speaker 4: What's actually going to make money you invest in SpaceX?
Speaker 4: When is SpaceX going to make money? Is SpaceX ever
Speaker 4: going to IPO or spin off Starlink?
Speaker 14: Well, overall, SpaceX does have a lot of cash and
Speaker 14: they do make money by way of the Starlink spaceships
Speaker 14: and satellite services. Because overall, what's fascinating is a lot
Speaker 14: of people across the world now that it's in every continent,
Speaker 14: are spending money on Starlink and it's generating a ton
Speaker 14: of revenue. But what we do think is that Starlink
Speaker 14: is big enough as a business that they could spin
Speaker 14: it off eventually, right, And I do see an independent IPO.
Speaker 14: If we just see that muskwor to integrate Generative AI
Speaker 14: in to SpaceX, it might just be a done deal.
Speaker 7: Though.
Speaker 5: If that were the case, talk to us.
Speaker 3: A little bit about tomorrow's IPOs today, which is what
Speaker 3: Manhattan Ventures Partner's sort of tagline is. You're all about
Speaker 3: the secondary market in many ways, and just what is
Speaker 3: the secondary market like for an E on back company.
Speaker 5: I mean, whether it be the vision of.
Speaker 3: X, whether it's SpaceX, so whether it's any of the
Speaker 3: companies you have in your portfolio right now and people
Speaker 3: willing and able and wanting to buy the secondary market.
Speaker 14: So right now, it is absolutely fascinating because you're getting
Speaker 14: to see that the secondary market is driving the true
Speaker 14: value of every single private company. And overall, I think
Speaker 14: it's the real indicator for where investors are willing to
Speaker 14: buy and shareholders are looking to sell. So I think
Speaker 14: we've never seen a more clear opportunity to dive into
Speaker 14: the secondary market. And what's fascinating is companies themselves are
Speaker 14: coming to us and coming to many others in the
Speaker 14: secondary market space and saying, we don't really know what
Speaker 14: the value of our company is in the current market
Speaker 14: because we last raise a big round of funding in
Speaker 14: mid twenty two, twenty one. And so the top indicator,
Speaker 14: the leading indicator we're seeing is the secondary market to
Speaker 14: price companies at their true asset value. So it's fascinating
Speaker 14: to see it, and we ourselves are seeing the opportunities
Speaker 14: are growing exponentially in a way that the companies are
Speaker 14: thankful that there's a real indicator that goes beyond a
Speaker 14: new round of primary financing.
Speaker 3: I mean, isn't it ed at the moment when we're
Speaker 3: ever talking about primary round and financing.
Speaker 5: It tends to be AI related in some way shape
Speaker 5: or forward.
Speaker 8: Does Yeah.
Speaker 4: I think that's the part that we all want to
Speaker 4: understand better, Andrea, which is just forget a new cycle
Speaker 4: or a hype cycle. What are you doing to wake
Speaker 4: up each day and say, Okay, here's where we're going
Speaker 4: to deploy capital, here's our plan for twenty twenty three.
Speaker 4: You know, what I'm trying to understand is what is
Speaker 4: driving investment visis for vcs right now.
Speaker 14: What's interesting about the thesis driven approach with all vcs
Speaker 14: is that all the companies that are approaching us and
Speaker 14: we are approaching them for capital raising, is that they're
Speaker 14: really looking to preserve the valuation that they last had
Speaker 14: and it is almost a valuation at all at all,
Speaker 14: stake at all, you know, permutations of evaluation. So what's
Speaker 14: interesting is that from a thesis perspective, we're determining whether
Speaker 14: or not to invest in companies that have investor sweeteners
Speaker 14: involved in the next round of funding. Or maybe it
Speaker 14: is that the best entry price is that secondary market value.
Speaker 14: Maybe that next round of funding is cluttered with really
Speaker 14: strong investor provisions that allow for protection and upside and
Speaker 14: so I think a lot of investors in our space,
Speaker 14: especially in the growth and late stage, are determining whether
Speaker 14: or not that next round of funding is attractive enough
Speaker 14: to go into relative to secondary.
Speaker 3: Andrew, after Linda Yakarino news came on Twitter, did that
Speaker 3: bump the valuation you've been seeing for Twitter? I know
Speaker 3: it's part of your portfolio post it going private? Is
Speaker 3: that something that you think is getting a clearer destination,
Speaker 3: getting investors more interested.
Speaker 14: Having Linda involved, we think is a very strong indicator
Speaker 14: of where we believe Elon is playing the sea level
Speaker 14: shuffle what we like to call right, so bringing in
Speaker 14: the strong adults in the room to really bring in
Speaker 14: a background in advertising and media, which overall that is
Speaker 14: what Twitter really is focused on, right, advertising, media and
Speaker 14: content driven.
Speaker 5: So I think it's a strong single Linda is.
Speaker 14: A phenomenal executive with an incredible background that I think
Speaker 14: many of us in the industry are very impressed with
Speaker 14: their ability to land. So I think generally we consider
Speaker 14: that a massive positive.
Speaker 4: Manhattan Ventures partner Andrea Lamari, who's able Caroline to talk
Speaker 4: about every news item this week and has investments related
Speaker 4: to every sub sector that we discuss, so thank you
Speaker 4: so much for your time. In other news, East Ventures,
Speaker 4: south East Age's most active early stage tech investment firm,
Speaker 4: raise two hundred and fifty million for its twelveth fund,
Speaker 4: a rare sign of confidence in the global tech sector
Speaker 4: during a tumultuous year. The Indonesia Focus says it will
Speaker 4: allocate the money as follow on investments toward growth portfolio
Speaker 4: companies that demonstrate strong potential.
Speaker 3: Going viral is the unusual gift from Google co founder
Speaker 3: so I gave Brin. In a filing that we saw Monday,
Speaker 3: it shows that he gifted Alphabet shares worth six hundred
Speaker 3: million dollars last Thursday.
Speaker 5: It's actually kind of.
Speaker 3: Unclear who's got the five point two million shares. We
Speaker 3: of course know that it could be perhaps to charity
Speaker 3: or to a trust or another financial instrument. But ultimately
Speaker 3: this is on a week where Brinn and his co
Speaker 3: founder Larry Page saw their wealth are combined eighteen billion
Speaker 3: dollars and we know why.
Speaker 5: It's because of AI.
Speaker 8: Yeah.
Speaker 4: Look, it all comes out of momentum from Google Io
Speaker 4: where we finally understood how Alphabet takes its competence and
Speaker 4: puts it into its tools. But I was there right
Speaker 4: and I would say they stressed deliberate, slow roll out
Speaker 4: safety guardrails.
Speaker 8: And now we have Altman speaking on Capitol Hill.
Speaker 5: Yeah, who's again been stressing safety.
Speaker 3: We know that it's wrapped up now the Senate hearing
Speaker 3: that features some Oltman, CEO of Open AI, as well
Speaker 3: as IBM, as well as scientists, But ultimately he's really saying, look,
Speaker 3: there are no plans for chat GPT five training in
Speaker 3: the next six months.
Speaker 5: This seems to be sort of under some juriss we'd
Speaker 5: heard that from some of.
Speaker 3: His colleagues on Twitter, saying, look, whenever you might be
Speaker 3: hearing GPT five isn't currently underway. But notably, everyone wants
Speaker 3: to know what this has on the startup culture, what
Speaker 3: this has in terms of society.
Speaker 4: Too, And again he Altman says the pressure should be
Speaker 4: on the leaders open AI and Google. The name check
Speaker 4: that was Richard Blumenthal, the Connecticut Democrat who chairs that
Speaker 4: Southern Committee, and he also had questions about the US
Speaker 4: leadership in this field.
Speaker 5: Yeah, Visa v.
Speaker 3: China something that we continue to discuss. How can you
Speaker 3: regulate without offsetting innovation? And what a thoroughly deep dive
Speaker 3: show we had today that does it for this edition,
Speaker 3: though on BlueBag technology. Tomorrow, well, we've got Patrick Zong
Speaker 3: Fanning partner of thirty one from Salt Eye Connections in
Speaker 3: New York.
Speaker 5: You don't want to miss it.