Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: From Mahard were Innovation, Money and Power Collie in Silicon Valley, Nbon.
Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.
Speaker 3: I'm Caroline had a Bloomberg's World headquarters in New York.
Speaker 4: I'm Ed Dudlow in San Francisco. This is BlueBag Technology.
Speaker 1: Coming up.
Speaker 3: Full market coverage ahead. Stocks Crypto pushed a record highs.
Speaker 3: We'll discuss Bitcoin at seventy thousand, and the outlook for
Speaker 3: the AI rally as a video adds a trillion dollars
Speaker 3: to its market cap this year alone.
Speaker 4: Plus, we'll bring you exclusive reporting on Huawei's chip breakthrough,
Speaker 4: which used technology from two US suppliers.
Speaker 5: Details ahead.
Speaker 3: Microsoft says it's seeing signs hacker group Midnight Blizzard it's
Speaker 3: been attempting to gain access to its systems.
Speaker 5: Bloomberg Exclusive.
Speaker 4: Huawei and its partner Smick relied on US technology to
Speaker 4: produce an advanced chip in China last year, according to sources.
Speaker 4: The previously unreported information suggests that China still cannot rely
Speaker 4: entirely on its domestic supply chain and needs foreign components
Speaker 4: and equipment that's required for cutting edge products like semiconductor.
Speaker 4: The reporter that broke that news Bloomberg's Mackenzie Hawkins. We
Speaker 4: just showed the teardown video that Bloomberg did of the
Speaker 4: Huawei Mate sixty. It has this seven animeter processor from Smick.
Speaker 4: Smick used LAMB and applied Materials chip making equipment to
Speaker 4: do it.
Speaker 5: Tell me the rest. That's right.
Speaker 6: So this seventh animeter chip was lauded as a massive
Speaker 6: breakthrough in China. The US was trying to keep Bijing
Speaker 6: from getting seven animeter technology on the fear that it
Speaker 6: could give the country advanced AI capabilities that could lend
Speaker 6: it a military edge. And so we've seen the US
Speaker 6: implement this sweeping set of controls on the types of
Speaker 6: chips and semiconductor manufacturing equipment that can be shipped to
Speaker 6: China starting in October twenty twenty two, and the machines
Speaker 6: that were reporting were used to create this Huawei chip
Speaker 6: were shipped prior to that ban.
Speaker 1: But the through line on.
Speaker 6: This story is that despite Beijing's efforts to indigenize the
Speaker 6: full semiconductor supply chain and catch up to the United States,
Speaker 6: to the Netherlands, to Japan, these countries that are really
Speaker 6: dominant in the global chip industry to get to their
Speaker 6: most advanced ship, yet they still relied on foreign technology McKenzie.
Speaker 3: We know that the US is still applying pressure too well.
Speaker 3: Ultimately those other countries that they want to ensure that
Speaker 3: these sort of ways of ma navigating through the blocks
Speaker 3: don't still happen. They are turning to the Netherlands to
Speaker 3: Japan to squeeze even tighter. What then, of these indigenous
Speaker 3: make is over in China, won't of advanced microfabrication equipment
Speaker 3: then of Nara, Are they actually getting to a place
Speaker 3: where they could do it alone.
Speaker 5: It's an excellent question I had.
Speaker 6: Certainly the hope from the the Netherlands and Japan, which
Speaker 6: are part of this tripartite agreement to squeeze China on
Speaker 6: semicdector technology. They hope that the controls that they've already
Speaker 6: imposed will keep China from ever catching up. But the
Speaker 6: reality is there are significant differences between the controls imposed
Speaker 6: by those three countries. US firms are not allowed to
Speaker 6: send their employees to service equipment that's already in China,
Speaker 6: so these tools from LAM and Applied Materials, those employees
Speaker 6: can't go do repairs but their Dutch companies peers are
Speaker 6: able to in many cases, so there are still sort
Speaker 6: of big gaps that the US seeks to close between
Speaker 6: those three countries regimes. And then you have the US
Speaker 6: reaching out to South Korea and Germany, which are major
Speaker 6: or home to major producers of spare parts that go
Speaker 6: in chip making tools, to get them to join in
Speaker 6: on this accord and try to squeeze China further.
Speaker 5: So just really quick.
Speaker 4: At a point of clarification, that seven nanometers two generation
Speaker 4: removes from the cutting edge right three nanometer. But as
Speaker 4: you point out in your story, Mackenzie Smick obtained the
Speaker 4: lithography machines prior to that October twenty twenty two ban
Speaker 4: So I think there's more to go on this story,
Speaker 4: which I'm sure you'll look into, on how they get
Speaker 4: that domestic industry up to speed.
Speaker 5: Bluebogs. Mackenzie Hawkins terrific reporting. Thank you. Let's keep the
Speaker 5: conversation going.
Speaker 4: China is in the process of raising more than twenty
Speaker 4: seven billion dollars for its largest chip fund to date,
Speaker 4: accelerating the development of cutting edge technologies as it faces
Speaker 4: those restrictions on US tech known as the Big Fund
Speaker 4: the state back firm is expanding as the US prepares
Speaker 4: to sharply escalate technology curves designed to curtail Chinese chip
Speaker 4: and artificial intelligence progress. A tit for tat going on here.
Speaker 3: Caroline, and that investors have to navigate around. Are we
Speaker 3: still looking to put more money to work in companies
Speaker 3: that have significant exposure to China? Vida being one of them,
Speaker 3: has talked to someone at the cutting edge. Nacy Tanglin,
Speaker 3: piece of a joins our CEO CIO of Laffatanglo Investments
Speaker 3: for more. Also the author, of course, The Women's Guide
Speaker 3: to Successful Investing, You dive into where women must invest
Speaker 3: for their future. But most notably today you're joining from
Speaker 3: the CBOE a day after ringing the bell to celebrate
Speaker 3: not only International Women's Day but also the launch of
Speaker 3: your new ETF TGLR. We want to dig into the
Speaker 3: ETF in a moment, Nancy, but first your take on
Speaker 3: China US and how it factors into your investing thesis.
Speaker 7: Yeah, so it's a tricky one to navigate, clearly, Caroline.
Speaker 7: Our portfolios have about three to five percent exposure in
Speaker 7: terms of revenues to China, so we've been very careful
Speaker 7: about it, and of course the companies that have tended
Speaker 7: to underperform in the last year have been the companies
Speaker 7: that do actually have exposure to China, not just in
Speaker 7: technology but across the board. So I'm not as concerned
Speaker 7: about the twenty seven billion dollar chip fund that China's starting.
Speaker 7: I mean, I think that's pretty much what Intel spent
Speaker 7: in terms of R and D and cap X last
Speaker 7: year alone. So it's it's it's a drop in the bucket.
Speaker 7: But you do have to be aware and conscious of
Speaker 7: the fact that there are going to be continued hostilities,
Speaker 7: if you will, trade hostilities, which.
Speaker 3: Might factor into whether or not we pull back from
Speaker 3: these record highs. Nancy, we are talking to you in
Speaker 3: the nasdacs at are record high. The S and P
Speaker 3: five hundreds that a record high. Global World Index set
Speaker 3: a record high thanks to the likes of Nvidia.
Speaker 1: It's interesting that we have.
Speaker 3: Bruelcom for example. I know you've sort of called it
Speaker 3: the pullman's version of an Nvidia, but there is some
Speaker 3: weakness in that name. After its earnings, how are you
Speaker 3: ranking the AI Frenzy and the chip names to be owning?
Speaker 7: So if I think I've shared with your investing theme
Speaker 7: is old economy companies that are embracing AI and then
Speaker 7: the suppliers of the pix and shovels. So we have
Speaker 7: been expanding our exposure. We trimmed back on many of
Speaker 7: the names, including Broadcom and palowout to Networks a number
Speaker 7: of weeks ago and then again yesterday, and so I
Speaker 7: think you have to be disciplined in this environment. We
Speaker 7: still own plenty, but we've been adding to names like AXP.
Speaker 7: I have a triple A or a cube stock pick
Speaker 7: for you, and it's American Express, which is using AI
Speaker 7: to improve fraud detection, and then Amazon and Adobe the
Speaker 7: unsung hero we think of AI. So you have to
Speaker 7: pick and choose and navigate around and really focus on
Speaker 7: domestic revenues if you can.
Speaker 4: The thing about Broadcom is it's not a maker of
Speaker 4: AI accelerators, right Nancy. It kind of It has a
Speaker 4: custom silicon business, makes TPUs, but it's really in the
Speaker 4: serve a design build out. You know, it provides networking tech.
Speaker 4: But they had this specific forecast that AI will be
Speaker 4: thirty five percent contribution revenue previously from twenty five percent.
Speaker 4: Does that signal anything bigger to you? About how how
Speaker 4: continued or sustained the AI buildout is going to be.
Speaker 7: I think, I mean, you have to piece together from
Speaker 7: a lot of different companies. But I think the security
Speaker 7: I have in owning a name like Broadcom is that
Speaker 7: it is hoktan is consistently underestimated. We were buying the
Speaker 7: stock at two hundred dollars a share when he did
Speaker 7: the Computer Associates deal, and everyone hated it. It was
Speaker 7: a creative in a year. So there's more to Broadcom
Speaker 7: than just AI. But if you look at the use
Speaker 7: cases almost you know, we're sitting on earning season, everybody's
Speaker 7: talking about it across sectors, but they're really using AI.
Speaker 7: And I think that's why I think this market is
Speaker 7: analogous to the nineties, because we are going to continue
Speaker 7: to see productivity improvements and that's going to drive stock
Speaker 7: prices higher. I would just point out I didn't answer
Speaker 7: Caroline's question. I mean, if you look at the all
Speaker 7: times highs, yes, that's true, Caroline, But over the last
Speaker 7: two years, if you went twenty two to twenty three,
Speaker 7: the Nasdaq was actually down something like three percent, So
Speaker 7: we're not in nosebleed territory yet.
Speaker 4: Well, the difference is the contribution from Nvidia and Videos
Speaker 4: at nine hundred and twenty seven dollars a share stock split,
Speaker 4: stock split in video, please.
Speaker 5: So you would favor that, you think you'll go for it.
Speaker 7: I mean, they've done it before, so I think it's likely.
Speaker 7: I think it would be great if Broadcom split as well,
Speaker 7: and some of these other stocks that traded these, you know,
Speaker 7: really high levels. It makes it harder to manage portfolios
Speaker 7: with them in the portfolio, harder for the retail investor.
Speaker 7: But you know, we'll take what we get. We'll take
Speaker 7: dividend increases, we'll take share buybacks, whatever it takes to
Speaker 7: drive the stock price higher.
Speaker 3: And let's talk about the retail investor. You clearly care
Speaker 3: about them. You've been writing books for them, and you've
Speaker 3: also been looking at well, now we've got an actively
Speaker 3: managed ETF coming from you at the moment, Lafeateangla equity
Speaker 3: income ETF quality large cap stocks have strong earnings and
Speaker 3: dividend growth potential. What is your edge here, Nancy? Where
Speaker 3: do you want to be showing an offering to this clientele?
Speaker 7: Yeah, so this strategy is very different from what you
Speaker 7: would normally think of as an equity income portfolio. There's
Speaker 7: no electric utilities. We own one rate in the portfolio,
Speaker 7: but we buy what I call fallen angel growth stocks,
Speaker 7: and we do a lot of research because everybody knows
Speaker 7: the problems when the stocks are out of favor. So
Speaker 7: we have our own proprietary research model and our own
Speaker 7: proprietary valuation metrics, and that is the one we use
Speaker 7: in that portfolio. Is relative dividend yield. In these companies,
Speaker 7: management sets the dividend based on what they think long
Speaker 7: term sustainable earnings power is. So it's a total return
Speaker 7: strategy with dividend growth as the focus, and it's a
Speaker 7: great workhorse strategy. I have you the majority of my
Speaker 7: assets in this strategy, so you don't get to own
Speaker 7: some of the sexier names, but you do get really
Speaker 7: consistent risk adjusted returns that have been able to generate
Speaker 7: excess return above the benchmarks over time.
Speaker 4: Nancy Tegler, CEO CEO of Lapputengler Investments. Great to have
Speaker 4: you on the show on this Friday. In creats on
Speaker 4: the ETF All right, coming up, Microsoft says Russian hacking
Speaker 4: group Midnight Blizzard is making attempts to access its systems.
Speaker 4: We're gonna bring you all the updates on that story. Next,
Speaker 4: this is Bloomberg Technology.
Speaker 5: Time for talking tech.
Speaker 4: First up, Microsoft says there's evidence that information from an
Speaker 4: account compromised by a Russia linked hacker known as Midnight
Speaker 4: Blizzard was used in recent weeks to try and gain
Speaker 4: access to corporate data. In a blog post, Microsoft revealed
Speaker 4: that the hackers made attempts for some of the company's
Speaker 4: source code, repositories, and internal systems, but found no evidence
Speaker 4: that any customer facing systems were compromised. Plus semiconductor connectivity
Speaker 4: company Astera Labs is said to be planning to raise
Speaker 4: as much as five hundred and thirty four million dollars
Speaker 4: in an IPO. The Intel backed company hopes to tap
Speaker 4: into investor demand four artificial intelligence with a stock offering
Speaker 4: of twenty seven dollars to thirty dollars a share. That's
Speaker 4: according to a filing. The stock will trade on the
Speaker 4: Nasdaq and will debut under the ticker ALAB and Rivian
Speaker 4: hits the brakes, halting plans to build out a new
Speaker 4: multi billion dollar factory in Georgia.
Speaker 5: In a company.
Speaker 4: Filing, Rivian said the move will save the automaker as
Speaker 4: much as two point twenty five billion in capital expenditures
Speaker 4: this coming is Evmaker debuted its first mass market.
Speaker 5: R two model, which will now be.
Speaker 4: Made at first in its existing plant in Illinois. This
Speaker 4: was the Rivian CEO Carros sort of channeling his inner
Speaker 4: Steve Jobs. But the news was a change of plans.
Speaker 3: Who is charming the inner Steve Jobs with a surprise?
Speaker 1: Right the R two?
Speaker 3: Yes, we kind of had the leak on about the
Speaker 3: R three.
Speaker 1: What do you make of it?
Speaker 4: Yes, the R three is a crossover.
Speaker 5: They did keep it a secret.
Speaker 4: I'm so surprised it wasn't leaked frankly ahead of time.
Speaker 4: So it was kind of like the one more thing
Speaker 4: Steve Jobs moment. It's a prototype. It's a prototype right
Speaker 4: far in the future. But it did boost the stock.
Speaker 3: We'll see what the price point is. But what forty
Speaker 3: five thousand for an R two. We're starting to get
Speaker 3: a little bit more economical.
Speaker 5: So AI is.
Speaker 3: Helping drive stocks to new highs today, but there remains
Speaker 3: the ongoing concerns about its limitations, particularly when it comes
Speaker 3: to generator of AI and ethical standards safety.
Speaker 1: This is something I.
Speaker 3: Discussed with the CEO of Salesforce AI it's Clara Shee.
Speaker 1: Take a listen.
Speaker 8: There are so many ways of thinking about trust. It
Speaker 8: is something that I think about all the time. It's
Speaker 8: the number one company value at Salesforce.
Speaker 1: But when it comes to AI, I think we've all.
Speaker 8: Heard the stories of chat GPT and the various equivalent
Speaker 8: out there just making things up or spewing out toxic
Speaker 8: outputs or biased outputs, right because consumer chatbots are trained
Speaker 8: on the corpus of data on the Internet and so honestly,
Speaker 8: unfortunately in humanity, and there's a lot of incorrect, biased
Speaker 8: information out there, and so I think that's really the
Speaker 8: difference between consumer AI and business AI.
Speaker 1: Business AI is.
Speaker 8: Just unacceptable to make up an answer to what your
Speaker 8: sales forecast is or responding to a customer service request.
Speaker 1: And that's why our.
Speaker 8: Team, my team has spent so much time building out
Speaker 8: what we call our Einstein trust layer, So everything from
Speaker 8: data masking to citations, to zero retention prompt so that
Speaker 8: there's no data leakage, to keeping an audit trail, just
Speaker 8: to make it really trusted for companies.
Speaker 3: What about therefore, the developers you're then going out and
Speaker 3: talking to on a daylight today, why are they seeing
Speaker 3: worries about what they look like, the bias within what
Speaker 3: they're producing, or are you seeing a more diverse castic
Speaker 3: characters coming in building, particularly as you make AI easier
Speaker 3: with co pilots. The fact is that ultimately maybe we're
Speaker 3: not all going to have to be well code as
Speaker 3: let alone prompt engine is.
Speaker 8: I do think this is an amazing democratization moment for
Speaker 8: app developers.
Speaker 1: And I mean even.
Speaker 8: For years before AI Salesforce, one of the secret sources
Speaker 8: of Salesforce was it's no code and low code platform,
Speaker 8: which means that business analysts can build apps without knowing
Speaker 8: how to code, and even pro code developers who are
Speaker 8: really good at coding, they're able to use our tools
Speaker 8: to code faster. And AI is just an incredible accelerant
Speaker 8: and amplifier of both of these. And so today we
Speaker 8: had a series of really exciting announcements called our Einstein
Speaker 8: one studio that really makes it turnkey for any no
Speaker 8: code developer as well as pro code developer to use
Speaker 8: AI to build faster.
Speaker 3: Do you think that the AI systems that we're building
Speaker 3: right now are as diverse as the use cases that
Speaker 3: we're having and or are you worried about the bias
Speaker 3: that's in there, inevitably because of what it's ingesting.
Speaker 8: I think more broadly, we should all be very concerned
Speaker 8: about the AI model development and the regulation of AI
Speaker 8: not being diverse enough.
Speaker 1: And that's why I think it's so important for.
Speaker 8: Us to have rooms like this and dialogues like this
Speaker 8: to really ensure that a diverse set of perspectives are
Speaker 8: going into creating the AI itself, as well as creating
Speaker 8: the governance and the policies and the regulation around responsible AI.
Speaker 8: And then finally, AI is going to create tremendous wealth
Speaker 8: and value for shareholders, for stakeholders, for employees of these companies,
Speaker 8: for the people and the businesses that utilize AI. And
Speaker 8: we can't leave behind women in minorities in this value
Speaker 8: creation moment.
Speaker 3: My conversation a couple of days ago with the Salesforce
Speaker 3: AI CEO Claras, and we're going to dig in more.
Speaker 4: Yeah, let's stick with AI biased concerns and turn to
Speaker 4: today's Bloomberg Big Take. Our reporters have been working on
Speaker 4: an experiment to see if chat GPT has any discriminatory biases,
Speaker 4: finding in their conclusion that AI software can produce discriminatory
Speaker 4: results when prompted to rank resumes that are equally qualified.
Speaker 5: Let's bring in.
Speaker 4: One of those reporters, Bloomberg's Davy Alba. This is a
Speaker 4: must read, but it is complicated. Let's start with the methodology.
Speaker 5: First. Explain to the audience what you did.
Speaker 9: Yeah, thanks for having me. So we carried out this
Speaker 9: experiment where we used GPT's API, and so we prompted
Speaker 9: GPT three point five and GPT four with eight equally
Speaker 9: qualified resumes, keeping all of the qualifications of the resume's
Speaker 9: equal equivalent essentially, And the only thing that we changed
Speaker 9: was the name.
Speaker 5: That was on top of the resume.
Speaker 9: So that name we derived it using mutational methods and
Speaker 9: made it representative of particular demographic groups. So we had,
Speaker 9: you know, either male or female, white, Black, Hispanic or
Speaker 9: Asian demographically distinct names, and we said it loose, and
Speaker 9: we basically had GPT rank these resumes thousands of times
Speaker 9: for four different jobs. And what we found was actually
Speaker 9: some pretty stark evidence of racial bias and disparities depending
Speaker 9: on the job that we asked GPT to rank it for,
Speaker 9: and you.
Speaker 1: Know, sort of the.
Speaker 9: Candidates that it was evaluating.
Speaker 3: Okay, so you're looking for a financial analyst for example.
Speaker 3: As one of the examples, Yes, who ends up in
Speaker 3: probability coming out on top, who ends up coming off worst?
Speaker 9: Yeah, so that was one of our really good examples.
Speaker 9: You know, we found that black men and women were
Speaker 9: disproportionately ranked U sort of at the bottom. They were
Speaker 9: chosen as a top candidate the least frequently. And it
Speaker 9: was so stark that we actually measured adverse impact, which
Speaker 9: is sort of what the US federal agencies use as
Speaker 9: a benchmark to see whether a group is you know,
Speaker 9: badly impacted by a particular hiring process. And I wanted
Speaker 9: to add, this is not just theoretical that people are
Speaker 9: using GPT to use these to to use to sort
Speaker 9: of sort and rank resumes. We actually in our reporting
Speaker 9: found that a lot of businesses are indeed using it
Speaker 9: for this particular use case.
Speaker 1: And you know, it's it's.
Speaker 9: Important to consider these things.
Speaker 3: Open AI and response saying you're not meant to use
Speaker 3: chut GPT or GPT in our underlying technology, just straight
Speaker 3: out the box in this way, but still stark reporting
Speaker 3: from Davy Alba. We thank her and the team so
Speaker 3: much for it.
Speaker 4: Welcome back to Bloomberg Technology Ed love Loow here in
Speaker 4: San Francisco.
Speaker 3: I'm Caroline heard in New York.
Speaker 4: Let's keep today's jobs report in mind, but dive deeper
Speaker 4: into the tech sector angle to all of this and
Speaker 4: bring in Jacqueline Rice Nelson, CEO of the upskilling platform
Speaker 4: Tribe AI. Basically, unemployment two year high, but hiring continues.
Speaker 4: I'm going to try and make the jump to what's
Speaker 4: happening in AI in the context of that by saying
Speaker 4: there is a scarcity of roles or a scarcity of
Speaker 4: the skilled workers we need to meet that hiring demand
Speaker 4: in the AI context. Do you think that that's right?
Speaker 10: First of all, I'm thrilled to be here, and especially
Speaker 10: on a day that shows some of the potential of
Speaker 10: AI and value creation that I believe we will continue
Speaker 10: to see in the market. I think when you talk
Speaker 10: about AI and talent and opportunity, we can't really underscore
Speaker 10: that we're just at the beginning of this massive wave.
Speaker 10: And today we absolutely have steep specialists who have been living, breathing,
Speaker 10: sleeping AI for years. But what really matters right now
Speaker 10: is who has been doing on the ground generative AI
Speaker 10: applications built on top of these large language models. These
Speaker 10: models have only really been accessible to a broader population
Speaker 10: for a year, and so that population.
Speaker 5: Of people who really.
Speaker 10: Has the experience that companies actually need to do this
Speaker 10: well to do this right is limited.
Speaker 4: Okay, what is tribe seeing in the jobs market? We
Speaker 4: know jobs are being added added in this context or industry,
Speaker 4: but what are the roles?
Speaker 5: Right?
Speaker 4: All these companies are saying we're using AI, but who
Speaker 4: are they hiring as a result of that?
Speaker 10: Yeah, this is an incredibly interesting moment because I believe
Speaker 10: we are kind of at a real inflection point where
Speaker 10: the conversation around AI has been around efficiency, around cost cutting,
Speaker 10: and potentially the fears have been around job reductions. And
Speaker 10: I believe where we're headed is that there will absolutely
Speaker 10: be efficiency gains, but that's going to become table sticks.
Speaker 10: Where we're going is AI used for innovation for product growth?
Speaker 10: Examples like Service now using AI and already being able
Speaker 10: to cite quantitative value that it has contributed contributed already
Speaker 10: millions of dollars to net new ACV. And this is
Speaker 10: where I think we have the potential to look at
Speaker 10: value creation from AI, not just on the bottom line
Speaker 10: and the top line, but also on jobs and opportunities
Speaker 10: for people that extend far beyond just the builders themselves,
Speaker 10: but also the people who are thinking about the commercial
Speaker 10: implications of these technologies, the legal and compliance implications, the
Speaker 10: operational challenges, the data and back end engineering needs. There's
Speaker 10: so many pieces that we're really looking at AI as
Speaker 10: a new wave to how do you develop products and
Speaker 10: how do you commercialize those products? And that's the interesting conversation.
Speaker 3: It's also therefore interesting that basically you've gone in with
Speaker 3: a consultancy model because it feels as though you have
Speaker 3: to be integrated into every single part of a business loan.
Speaker 3: I mean this is going up from the CEO and
Speaker 3: the CTO to basically people are going to be practically
Speaker 3: using this. How do you get that buy in from
Speaker 3: a company in every pot?
Speaker 10: You're exactly right, and I would actually say it starts even.
Speaker 5: Higher, which is at the board level.
Speaker 10: So right now, all the boards are yelling at their
Speaker 10: CEOs and saying, what's your AI strategy? All the CEOs
Speaker 10: are yelling at their team and saying what's your AI strategy?
Speaker 1: And everyone's saying I don't know, yes anything, less yelling.
Speaker 10: Yes, less yelling across the board. Maybe they're nicely asking,
Speaker 10: but the point is that every company today wants or
Speaker 10: needs to become an AI company, and they don't know how.
Speaker 10: And that's really where Tribe comes in. We can help
Speaker 10: meet and work with companies at every stage of that
Speaker 10: kind of adoption journey, and then work with them to
Speaker 10: build products that actually matter for their business, that really
Speaker 10: add real value to their companies, can showcase the success
Speaker 10: and make it really tangible rather than this you know,
Speaker 10: buzzword soup, and then get them on this sort of
Speaker 10: train or journey to continuing to invest in AI in
Speaker 10: ways that really makes sense and do real things.
Speaker 3: The demand is clear, and I'm sure your business is
Speaker 3: thriving on the back of it, but talk to us
Speaker 3: about the supply side issue. You've got to bring in
Speaker 3: the right engineers, who I am sure are being offered
Speaker 3: plenty of permanent jobs at extraordinary offerings in terms of
Speaker 3: their salary.
Speaker 1: Why work with a Tribe AI? Why be a consultant?
Speaker 3: Why be a freedom set?
Speaker 10: Yeah, this is a trend that I spotted years ago,
Speaker 10: which is that the people who really have the expertise,
Speaker 10: particularly in AI, have worked at just a handful of companies,
Speaker 10: Google Amazon, Netflix, take your pick, and not everyone wants
Speaker 10: to stay at those companies despite the cushy jobs and
Speaker 10: the large salaries, and especially right now in this moment
Speaker 10: of intense AI demand that you just described, the demand
Speaker 10: for these talented folks is off the charts, and so
Speaker 10: they have their choice of these very massive floated salaries
Speaker 10: right now at these big companies. But that comes with
Speaker 10: a lot of bureaucracy that comes with being tied up
Speaker 10: at that company and potentially some it IP constraints. You
Speaker 10: know that they can't really innovate outside of their jobs,
Speaker 10: and if they are independent, what they come to Tribe
Speaker 10: for is the opportunity to really plug in on work
Speaker 10: their best at to not do any of the like
Speaker 10: boring meetings and bureaucracy stuff, but do the hard engineering
Speaker 10: that they know how to do better than anyone else.
Speaker 10: Add a ton of value, and there's a lot of
Speaker 10: mutual value where companies are getting outsize value from working
Speaker 10: with the right AI engineers who have the on the
Speaker 10: ground experience to deliver value, and the AI engineers are
Speaker 10: getting tremendous learnings from working at the cutting edge and
Speaker 10: bringing these models to life in production at scale.
Speaker 1: Jacqueline Wie Nelson.
Speaker 3: So great to have you Onis talking about, well, the
Speaker 3: fixes that are coming and actually how you can try
Speaker 3: real productivity with all this AI hype. Just called CEO
Speaker 3: of Tribe AI. Let's stick with, of course, all things
Speaker 3: artificial intelligence, because it got brought up last night State
Speaker 3: of the Union, President Biden calling for a ban on
Speaker 3: AI voice impersonations, pass by partners.
Speaker 2: And privacilizenys to protect our children.
Speaker 5: Online partners.
Speaker 2: Primus to promise with AI to protect.
Speaker 5: Us from peril.
Speaker 2: Ben AI voice impersonations and more and keep our truly
Speaker 2: sacred obligation to trade and equip those we send in
Speaker 2: the harm's way and care for them and their families
Speaker 2: when they come home and when they don't.
Speaker 3: The President did not elaborate on the types of guardrails
Speaker 3: or indeed the penalties that he would planned institute around
Speaker 3: the rise in technology or look if it would extend
Speaker 3: to the entertainment industry.
Speaker 4: Ed right coming up on the program, it's been almost
Speaker 4: a year since Silicon Valley banks collapse. We're going to
Speaker 4: speak with ORAM CEO Stephanie Kirkpatrick about the lessons learned,
Speaker 4: what individuals and businesses have done in reaction over the
Speaker 4: last twelve months.
Speaker 5: Let's go back to Nvidia.
Speaker 4: Really quick, and the session high it was up five percent.
Speaker 4: At the session low it was down five percent. We're
Speaker 4: now off session lows, down two point eight percent. I
Speaker 4: think this is a pool back RSI at seventy seven.
Speaker 4: That means the stock is pretty over bought in Layman's terms.
Speaker 4: We talked about it being at a fresh record and
Speaker 4: now the idea that a stock split might be on
Speaker 4: the table to make it more accessible to the retail
Speaker 4: investor and more manageable for the institutional investor either way.
Speaker 4: In video euphoria continues. The stock is currently down two
Speaker 4: and a half percent. This is Bloonboo Technology.
Speaker 11: We're profitable in the US. We have, you know, very
Speaker 11: meaningful presence in the US. We have thirty million customers there.
Speaker 11: But at the same point of time, we are still
Speaker 11: zero point five percent of the total payments market. Yeah,
Speaker 11: you know, there's Visa, there's master Card, it's Ames, it's tremendous.
Speaker 5: Big companies plan a CEO.
Speaker 3: They're talking earlier today to our colleague Tom McKenzie, and
Speaker 3: we want to stick with a fintech theme. We want
Speaker 3: to look at what's been happening around the space, the
Speaker 3: recovery also since, of course, remember Silicon Valley Bank collapsed
Speaker 3: almost exactly a year ago. Joining us now CEO of
Speaker 3: fintech company or Stephanie Kirkpatrick more on what the businesses
Speaker 3: individuals have learned from this event. More broadly, how you're
Speaker 3: bringing faster transactions more deeply embedded into APIs that help
Speaker 3: businesses and consumers access their money that much faster. The
Speaker 3: joy of FED now not just crypto. I'm interested as
Speaker 3: we think about we're about to get a ton of
Speaker 3: media coverage on it being the anniversary, so lead the
Speaker 3: charge is an anniversary since SVB really showed and poked
Speaker 3: holes in some of the bank's ultimate business models. Here
Speaker 3: have we fully recovered of startups, fully recovered of people
Speaker 3: like learning from this.
Speaker 12: I do think that startups are recovering. I do think
Speaker 12: the banking system is looking a bit healthier than it
Speaker 12: was a year ago. And I think what we've learned
Speaker 12: from it is that for payments, for banking, the things
Speaker 12: that are systemically important to running this economy, whether it's
Speaker 12: the American while it's small businesses commerce, we get to
Speaker 12: a point where relying on a single financial institution is
Speaker 12: no longer sufficient. I think spb's collapse highlighted that even
Speaker 12: banks of a certain size carry risk, and so what
Speaker 12: we're seeing with our customers and the way we operate
Speaker 12: at ORUM is this opportunity to work with Tier one
Speaker 12: financial institutions, systemically important banks, and at ORM we now
Speaker 12: have recently reached a milestone where we connect directly to
Speaker 12: the Federal Reserve Bank as a service provider, which means
Speaker 12: that we're delivering on the complete promise of instant payments
Speaker 12: and for us, that means our customers who work with
Speaker 12: us for payments and in the lat of cases, faster payments,
Speaker 12: are in a position to have all of the benefits
Speaker 12: of lower cost, no downtime, smart efficient routing, and access
Speaker 12: to all Federal Reserve Bank transfer rails, in addition to
Speaker 12: a portfolio of notable banks that we work with in
Speaker 12: the Tier one category, thus providing that resiliency and redundancy
Speaker 12: that needs to kick in in the event that there
Speaker 12: is something unexpected in the financial institution space.
Speaker 3: It does seem though that we've ended up was leave
Speaker 3: leaning ever more on the too big to fail institutions.
Speaker 3: I mean, we think about it being the ghost of
Speaker 3: the past talking about Silicon Valley bank collapse.
Speaker 1: But we're still confronted.
Speaker 3: By commercial list say being an issue. I think a
Speaker 3: New York community bank called that just gotten one billion
Speaker 3: dollar injection. Have you felt that people are resistant to
Speaker 3: work with the smaller banks. Have you had to say, look,
Speaker 3: we are with just the tier ones now, you know?
Speaker 1: It's interesting.
Speaker 12: I actually think that community banks, local banks, they do
Speaker 12: play a very big role and an important role in
Speaker 12: how we think about what's going on in financial services.
Speaker 12: At AURUM is the simplest API for fast, reliable payments
Speaker 12: and instant bank account verification. It's important that we work
Speaker 12: with and offer services to all size and scale of banks.
Speaker 12: How we provide those services is diversified, and I do
Speaker 12: think that there is something to be said for working
Speaker 12: with smaller banks who can provide certain types of you know,
Speaker 12: independent variables. Some of them have very discrete protections under
Speaker 12: durban regulation and other areas that provide higher interchange rates,
Speaker 12: things that are very good for FinTechs. For example, we're
Speaker 12: building in the innovative sort of economy. But to have
Speaker 12: a single point of failure in any system setting aside
Speaker 12: that is financial services is generally a risk, and companies,
Speaker 12: I think are more eyes wide open to the fact
Speaker 12: that having that risk is something that isn't as worth
Speaker 12: taking as it once was.
Speaker 4: Concentration risk, I think was the lesson from Silicon Valley's
Speaker 4: collapse right, and changes were made. People were open minded,
Speaker 4: as you say, to using multiple service providers. Has that
Speaker 4: made the market you operate in more competitive?
Speaker 5: Absolutely?
Speaker 12: I mean, I think what we hear from our customers
Speaker 12: and where we are often brought in to work with
Speaker 12: somebody in the payment's ecosystem for our products is at
Speaker 12: a scale in which a company says it's no longer
Speaker 12: a good idea to work with one bank or just
Speaker 12: with a single payment processor. And so we're hearing from
Speaker 12: every part of the market, emerging companies all the way
Speaker 12: to scaled financial services, software and technology companies that it's
Speaker 12: important to be able to diversify payments and banking traffic.
Speaker 12: And so yes, we do see more and more financial
Speaker 12: companies that work with us have multiple bank accounts, which
Speaker 12: we absolutely think is a great idea, and two that
Speaker 12: they're working with a company like Orum who can automate
Speaker 12: the process of how payments operate on the back end,
Speaker 12: it is two weeks or less to integrate to RAPI
Speaker 12: for fast reliable payments, which gets you RTP FED now
Speaker 12: ACHDMDSH wires all orchestrated, and it's usually two years to
Speaker 12: go directly to a bank, and so diversification is very
Speaker 12: a hard problem. Multi rail multi bank orchestration is also
Speaker 12: a very hard problem, and it's very high cost. So
Speaker 12: we want to do a sit in the middle of
Speaker 12: this ecosystem so that software companies, technology and financial services
Speaker 12: companies have the benefit of diversification. They don't get stuck
Speaker 12: with concentration, but they don't also have to spend two
Speaker 12: years and two million dollars achieving that when they can
Speaker 12: work with us in essentially a sprint or less of
Speaker 12: technology work.
Speaker 4: Stephanie, what data do you have about the financial health
Speaker 4: of those customers that you onboarded in the wake of
Speaker 4: Silicon Valley banks collapse.
Speaker 5: Well, what we see one you're own later.
Speaker 12: What I'm saying is just a big comeback right in
Speaker 12: a lot of ways, the venture capital market, the stock market,
Speaker 12: you know, lots of things are showing signs of optimism,
Speaker 12: and for us that is also a very optimistic part
Speaker 12: of beginning twenty twenty four with this new deliver product
Speaker 12: that we can offer to folks who are in growth mode.
Speaker 12: Connecting directly to ORM and directly to the Federal Reserve
Speaker 12: Bank means delivering on the instant payment promise and furthering
Speaker 12: our vision and helping our customers with delivering on time
Speaker 12: to value right time to money. Is a very hard
Speaker 12: problem to solve for small businesses. And you think about
Speaker 12: wage payout, insurance claims payouts, you think about logistics and
Speaker 12: factoring and trucking what runs our economy, and you think
Speaker 12: that most settlement has historically been five days on ACCH
Speaker 12: and now it can be twenty four, seven, three sixty five,
Speaker 12: literally round the clock on fed now and OURTP systems.
Speaker 12: We're a fundamentally different place, and our customers I think
Speaker 12: are really growing as a result of the capabilities that
Speaker 12: are available. And I think we feel great optimism as
Speaker 12: we had into the year.
Speaker 4: Yeah, I remember the fight calls and anxiety about moving
Speaker 4: money from A to B exactly a year ago or
Speaker 4: I'm CEO and President Stephanie Kirkpatrick.
Speaker 3: So green Bag just hosted its International Women's Day celebration
Speaker 3: in San Francisco that was on Wednesday, and indeed highlighted
Speaker 3: the philanthropic work the network does to train diverse business
Speaker 3: voices to be TV media ready. It's our new voices program. There,
Speaker 3: I had the chance to sit down with HubSpot CEO
Speaker 3: you how any Rangan to chat all about her thoughts
Speaker 3: about how she approaches running her business AI integration and
Speaker 3: diverse leadership and within her teams.
Speaker 1: Take a listen.
Speaker 13: Our leadership team is fifty percent women, and our board
Speaker 13: is sixty percent women and people of color. And our
Speaker 13: entire leadership team is forty nine percent VP and of
Speaker 13: OS forty nine percent women.
Speaker 3: Do you think that's accidental or you've been purposeful on
Speaker 3: finding those people?
Speaker 13: It is absolutely intentional. You know, I started in the
Speaker 13: tech industry in mid nineties and it did not look
Speaker 13: like this. And I think what we've thought about. You know,
Speaker 13: diversity is not an initiative, it's not an annual program.
Speaker 13: It just needs to be built into the DNA of
Speaker 13: the company. Why, because we build products to serve communities,
Speaker 13: and if we cannot represent how the communities represent themselves,
Speaker 13: then bias actually enters and we don't represent the views
Speaker 13: of our customers.
Speaker 1: And so for us, we've never.
Speaker 13: Treated, you know, diversity and inclusion and belonging as one initiative.
Speaker 1: It's just built into the DNA of the company. And
Speaker 1: it's been intentional.
Speaker 13: You know, twenty seventeen, the percent of women leaders was
Speaker 13: in the thirties.
Speaker 1: We've intentionally moved up.
Speaker 13: In twenty seventeen, the percent of BYPOC employees within HubSpot
Speaker 13: was seventeen.
Speaker 1: We've moved it up to over thirty five percent.
Speaker 13: And so it's been in intentional journey, but it's been
Speaker 13: just part of building it into the entire DNA of
Speaker 13: the company, from recruiting to hiring, to promoting, to coaching
Speaker 13: all of that.
Speaker 3: I mean, you look at your latest starnings, they've done
Speaker 3: pretty well. Can you prove do you have to show
Speaker 3: to your other stakeholders, not just your employee base, but
Speaker 3: the investor base and those that have analyzed your company
Speaker 3: that this is bang for the buck? Yeah, this isn't
Speaker 3: just intention for intention's sake.
Speaker 13: I'm done trying to prove, you know, diversity with data.
Speaker 1: We just need to be diverse. That's it.
Speaker 13: Like there is no you know, there's as an engineer
Speaker 13: and as a person.
Speaker 1: That's you know, really focused on data. This is one
Speaker 1: area that I'm not willing to go.
Speaker 13: There because there's enough proof if you look, there is
Speaker 13: enough proof. If you want, you know, the communities to
Speaker 13: be reflected in your.
Speaker 1: Companies, you just need to do it.
Speaker 13: If your product needs to be unbiased, you just need
Speaker 13: to do it. I don't think you need to tie
Speaker 13: performance to this.
Speaker 1: That's just you know, we're past that. I hope we're
Speaker 1: past that, but I am past that. I'm done.
Speaker 3: Hubspots CEO.
Speaker 2: Yeah.
Speaker 3: Amanirangan unwavering in her focus on DEI throughout the DNA
Speaker 3: of the company, but on this International Women's Day, that
Speaker 3: does it for this edition of Bloomberg Technology. What a
Speaker 3: ride for the markets.
Speaker 4: Yeah, what a ride, but really important in conversations throughout
Speaker 4: the hour, which you can recap on the podcast. We
Speaker 4: love that so many of you are going to the
Speaker 4: podcast for the show. Wherever you get their Apple, Spotify,
Speaker 4: this is Bloomberg Technology.