Speaker 1: Welcome to our Bloomberg television and radio audiences around the world.
Speaker 1: We're live in Las Vegas. This is Money twenty twenty
Speaker 1: and we're joined by open AI's CFO Sarah Fryer. And
Speaker 1: this is interesting.
Speaker 2: You have some history with.
Speaker 1: Money twenty twenty, history with fintech, but that's kind of
Speaker 1: the point. And so much of the focus to date
Speaker 1: on open ai has been I guess, a personal use
Speaker 1: of chat GPT, but let's start with the banks and finances.
Speaker 1: How much of that is made up in your business?
Speaker 2: Yeah, it's like you.
Speaker 3: Ad, it's so great to be here, and you're right,
Speaker 3: Money twenty twenty. I've seen it progress through the years
Speaker 3: and what an incredible event it is today. And we're
Speaker 3: here because our customers are here. AI is happening right now.
Speaker 3: It's not experimental. It's not something that people are just
Speaker 3: playing around with, banks, financial institutions, FinTechs. People are using
Speaker 3: it today in their business.
Speaker 1: There's the Morgan Stanley case study. Yeah, you know, this
Speaker 1: week alone or past week, Bank of America's talks about
Speaker 1: how many patents it's got in machine learning and artificial intelligence.
Speaker 1: But do you actually have a tangible sense of what
Speaker 1: is is those financial institutions are doing with your large
Speaker 1: language models.
Speaker 2: Yes, absolutely so.
Speaker 3: Morgan Stanley is a great example in their wealth management business.
Speaker 3: They're using our models both to help wealth advisors be
Speaker 3: more productive. They're using it as a way to create
Speaker 3: better financial advice and outcomes for customers. We're seeing folks
Speaker 3: like Klarna use it in a customer service. CEO of
Speaker 3: Clarina has been very loud and proud on this front.
Speaker 3: That's another great case study in terms of productivity improvements.
Speaker 3: And then we have banks like VBVA that are using
Speaker 3: it all across their business. And that's really our message here.
Speaker 3: It's just get started. Get enterprise chat, GPT, roll out
Speaker 3: to your organization, see what your people do with it.
Speaker 2: Help them just get started.
Speaker 3: Whether they're in marketing, in finance and product everyone can
Speaker 3: have really interesting even.
Speaker 1: If we are just getting started. Can you help our
Speaker 1: audience understand how meaningful contribution the financial services sector fintech
Speaker 1: makes to open AIS revenue? Yes?
Speaker 3: So today if you look at our largest verticals areas
Speaker 3: like EEDU, education, healthcare.
Speaker 2: But financials is probably third.
Speaker 3: And again I think that's because they are typically early adopters.
Speaker 3: They're often willing to take that risk because they see
Speaker 3: the upside in terms of driving more revenue. But they
Speaker 3: also are very good at managing their cost and efficiency.
Speaker 3: And it's great when you get an early adopter like
Speaker 3: Morgan Stanley because it tends to lead the way.
Speaker 2: I can think of a wealth.
Speaker 3: Management client today that it's not coming to us to
Speaker 3: say what do we need to do?
Speaker 2: How do we get started?
Speaker 1: Banks in particular can be sensitive to pricing. There's a
Speaker 1: lot of curiosity not just in as a consumer how
Speaker 1: much I'm paying on a monthly basis for chat GPT access,
Speaker 1: but at the enterprise level as well. Reports are for example,
Speaker 1: at the corporate per user level, you're thinking it about
Speaker 1: two thousand dollars per head? How are you managing us
Speaker 1: give us insight into the pricing strategy.
Speaker 3: Sure, so pricing is super interesting because we're really trying
Speaker 3: to think about value and what is this person getting
Speaker 3: from this tool? And I think I actually don't think
Speaker 3: we've done a great job of that yet ourselves. Despite
Speaker 3: that we have two hundred and fifty million weekly active
Speaker 3: users and all of that's a you know, five six
Speaker 3: percent actually converted to be plus customers, so they're paying
Speaker 3: but if you look at the value. When we were
Speaker 3: rolling out oh one, our reasoning model, and this is
Speaker 3: a model that stops and thinks for you. It actually
Speaker 3: does hard problems. I was watching a lawyer in action
Speaker 3: using it to create a brief and at the end
Speaker 3: we said to him, what would you have paid for that,
Speaker 3: like if you had a paralegal doing that? He was like,
Speaker 3: easily one thousand to two thousand dollars per hour. And
Speaker 3: this is someone who's using it. If it's an enterprise
Speaker 3: per seeds, probably sixty bucks per month. And this is
Speaker 3: someone who would have paid one thousand to two thousand
Speaker 3: dollars per hour. So I think that there's a lot
Speaker 3: of value that is in the product today, but we
Speaker 3: are just trying to make sure people can get started,
Speaker 3: can actually see the outcomes, and over time we believe
Speaker 3: that value to price will come into alignment.
Speaker 1: Is a balance right between what's of value to your customer,
Speaker 1: but also you know you have to account for open
Speaker 1: AIS spending. So we talked about endlessly, particularly on the
Speaker 1: compute side, what is that balance in what works best
Speaker 1: for you and your customer base.
Speaker 3: Yeah, so our first and foremost, what's most important to
Speaker 3: us is to stay on the frontier, building the frontier models,
Speaker 3: making sure that we are bringing ultimately agi to the
Speaker 3: benefit of humanity. To do that, it's expensive. We have
Speaker 3: to invest in large scale compute and so to me,
Speaker 3: there's really two ways to finance that.
Speaker 2: It's either through the free cash flows of.
Speaker 3: The business spoken like a good CFO, or it's through
Speaker 3: raising equity and debt financing because investors can see the
Speaker 3: long term potential of this business.
Speaker 2: So on the former, on the cash.
Speaker 3: Flows of the business, we want to make sure we
Speaker 3: keep growing that business. I think we have been wowed
Speaker 3: at just the pace of growth, particularly on the consumer side.
Speaker 3: It's about seventy five percent of our business today. But
Speaker 3: even our enterprise businesses, they are young, but they are
Speaker 3: ready doing an incredible amount of annualized revenue and a
Speaker 3: real excited by the potential there.
Speaker 1: For a bluebig television and radio audience worldwide. We're in
Speaker 1: Las Vegas at Money twenty twenty and we're speaking to
Speaker 1: the Open AI CFO Sarah Fryar, and you talk there
Speaker 1: about the consumer business. Something very interesting is the future
Speaker 1: business model ADS supported tiers, for example, very specifically segmented pricing.
Speaker 1: How do you think about that.
Speaker 3: Sarah, Yeah, so I think you always want to stay
Speaker 3: open to alternate business models or ways that you can
Speaker 3: layer a new business model on top. Now, the key
Speaker 3: for us is always access. How do we make sure
Speaker 3: as many people as possible get access to this tool?
Speaker 3: And that's on a global stage, by the way, And
Speaker 3: so to do that sometimes you do pivot away from
Speaker 3: just pure subscription models to models like ads. My last
Speaker 3: company was all ads, so I've definitely experienced this. I
Speaker 3: think ads have their place, but you have to be
Speaker 3: really mindful of were I think in areas like commerce,
Speaker 3: ads are great. Right if I do a chat GPT
Speaker 3: prompt for black high heels shoes, something I probably would do,
Speaker 3: so I actually don't want a history of the black
Speaker 3: high heeled chew. I want five stores I could buy
Speaker 3: from right now, probably e commerce. So that's why companies
Speaker 3: like Shopify are great customers of ours as well. But
Speaker 3: there are other places where actually the AD model doesn't
Speaker 3: make as much sense. You want to get the consumer
Speaker 3: to the answer they need as fast as possible, and
Speaker 3: I think that's where chat Gibt is a really very
Speaker 3: different platform from say something like Google Search.
Speaker 1: You are still relatively early in this role, but it's
Speaker 1: been two years since the original deal with Microsoft was negotiated,
Speaker 1: and that compute relationship is critically important. Yes, all those
Speaker 1: terms change, are they fluid or are you just sticking
Speaker 1: to the contract that was on your desk when you arrived.
Speaker 3: Now, and it's actually longer than two years. Microsoft and
Speaker 3: OpenAI have been partners, I think for actually almost five years,
Speaker 3: so they really came to us when we were a
Speaker 3: research lab, and the deal that we've worked with them
Speaker 3: is they do provide compute exclusively and we give them
Speaker 3: the IP around artificial intelligence.
Speaker 2: So it's incredible.
Speaker 3: The products they're rolling out today are really built a
Speaker 3: top of open AI's AI. As we go forward and
Speaker 3: as we get bigger, we absolutely see a maturing in
Speaker 3: that relationship, and so for consumer benefit, we want to
Speaker 3: make sure consumers always get access to what they need.
Speaker 3: That will probably mean compute for more parties over time.
Speaker 2: Where we did.
Speaker 3: Discuss the Oracle deal, or Oracle discussed it a few
Speaker 3: quarters back, and I think that's a good starting point
Speaker 3: for just how do we maximize compute so we maximize
Speaker 3: the impact for consumers.
Speaker 1: The catchphrase or buzz word of this year, I think
Speaker 1: has been ship products. You're the CFO, and so there's
Speaker 1: a tension between the cost of doing so and the
Speaker 1: need to move quickly. I think Sam has denied recently
Speaker 1: reports that the next model will be out by year end.
Speaker 1: What can you tell us about the path forward their
Speaker 1: the cadence of new models to come.
Speaker 3: Yeah, I mean I think you hit the nail on
Speaker 3: the head ship product product velocity. That is the mantra
Speaker 3: internally to open an eye. And it's something I've just
Speaker 3: been so wowed by since I started as just.
Speaker 2: How fast we do ship products right.
Speaker 3: Even in my short tenure, I've seen one come out
Speaker 3: our Reasoning model, that huge step forward from kind of
Speaker 3: what has been more the Chat ChiPT model series. We've
Speaker 3: launched things like advanced speech talk to the model itself.
Speaker 2: The O series four.
Speaker 3: O enough four Mini for example, four O Mini, which
Speaker 3: is our distilled model, is one hundredth the cost of
Speaker 3: what the original Chat Ept four model was. That is
Speaker 3: incredible for developers, and that's why you see the API
Speaker 3: products be so successful. And again it goes back to
Speaker 3: how do we get this into the hands of many
Speaker 3: developers are a force multiplier and today I'm super proud.
Speaker 3: I think every single Ai unicorn is built atop of
Speaker 3: open AI's API, and that will tell you how we
Speaker 3: are the frontier model.
Speaker 1: I think when I started covering open Ai, there was
Speaker 1: around five hundred people at the company. It's probably near
Speaker 1: two thousand now.
Speaker 2: Yeah.
Speaker 1: That as the CFOs to keep talent long serving talent happy.
Speaker 1: My understanding is that tenders will be a big part
Speaker 1: of that, giving employees liquidity. What will be the cadence
Speaker 1: and sort of increments of that going forward, Sarah, Yeah.
Speaker 3: So we are a company that has done tenders to date,
Speaker 3: and part of that is because we are in a
Speaker 3: competitive market, particularly for research talent. When I think about
Speaker 3: what keeps you on that front edge of the best
Speaker 3: models out there, it is compute, but more importantly, it's people.
Speaker 2: It's great researchers.
Speaker 3: And so in order to compete with companies that have
Speaker 3: liquidity already in their stock public companies, we have taken
Speaker 3: this approach to tenders a little bit like others in
Speaker 3: the space.
Speaker 1: SpaceX is a great bax one we've covered closer, yes.
Speaker 3: And so we want to be able to keep doing that.
Speaker 3: We want to do it thoughtfully and mindfully, knowing that.
Speaker 3: The other rule one is to keep it on the field,
Speaker 3: make sure we have money for computees. It's always a balance,
Speaker 3: but we do think it's important to give our researchers
Speaker 3: that access for.
Speaker 1: Rob Bloomberg television and radio audience all around the globe.
Speaker 1: We're in Las Vegas and we're speaking to the open
Speaker 1: Ai CFO, Sarah. Open Ai is a software company, or
Speaker 1: it was. Now A lot of the focus is on
Speaker 1: Sam and the team's ambitions with safeguarding infrastructure. How involved
Speaker 1: are you in that talking about the sort of construction
Speaker 1: of five gig what data centers and the financing of
Speaker 1: such things. Yeah, was that a surprise to come in
Speaker 1: and sort of think, Okay, I need to get a
Speaker 1: handle on that project.
Speaker 2: Not a surprise, but definitely a stretch.
Speaker 1: It's a new territory, stretch from a capital perspective, stretch.
Speaker 3: From a capital and also just my own learning. Frankly,
Speaker 3: I think we're all learning in this space. Infrastructure is destiny.
Speaker 3: It's this wonderful phrase that Chris Lane has managed to
Speaker 3: get up there in the world, and we do think
Speaker 3: that this build is important. It's important for us competitiveness,
Speaker 3: it's important for world productivity. It's important even with a
Speaker 3: national security lens. And so you are right. One of
Speaker 3: the key jobs I need to do is to figure
Speaker 3: out that capital allocation story. It's going to be both
Speaker 3: a working with part. It's going to be raising financing,
Speaker 3: but it's always making sure that we are staying ahead
Speaker 3: of what will be required. Call it two three years out,
Speaker 3: because you can't just turn on compute today if you
Speaker 3: need it. You actually have to have thought about it,
Speaker 3: probably about three years ahead.
Speaker 2: On that, if I may.
Speaker 1: One of the things I heard from some of your
Speaker 1: investors is you did a very good job early in
Speaker 1: explaining the basics of the plan, but the ultimate goal
Speaker 1: is AGI.
Speaker 2: That's correct.
Speaker 1: How confident do you feel you have that sort of
Speaker 1: into infrastructure in place or a plan to have it
Speaker 1: for AGI?
Speaker 3: I think we have the plan in place. I think
Speaker 3: if Sam we're sitting on the seat, he would tell
Speaker 3: you AGI is closer.
Speaker 2: Than most think.
Speaker 1: But I what would you say?
Speaker 3: I would agree based on what I'm seeing. Like one
Speaker 3: of the best meetings I get to go to once
Speaker 3: in a while is the research meeting, and it would
Speaker 3: blow your mind to see what's already coming and what
Speaker 3: as we have learned how to take reasoning models like
Speaker 3: oh one preview yes on top of GPT models and
Speaker 3: the interplay between those. You're now really starting to see
Speaker 3: some incredible outcomes. PhD level outcomes where you have in
Speaker 3: your pocket human intelligence that is PhD level and physics
Speaker 3: and biology and chemistry in English literature, like whatever the
Speaker 3: job is you need to do if you're a healthcare researcher,
Speaker 3: if you're a banker, if you're in education. The tool
Speaker 3: that you are now caring the power there blows my mind.
Speaker 1: Sarah, you touched on it a moment ago, financing the
Speaker 1: needs to raise capital. You've just done a pretty astonishing
Speaker 1: large round. But a follow on, I mean you must
Speaker 1: have a good sense of the cadence of needing to
Speaker 1: raise funds on an annual basis. I don't know how
Speaker 1: you plan it.
Speaker 2: Yeah, so it goes back.
Speaker 3: To what you said, which is really understanding in your plan,
Speaker 3: what are your big expenses? Compute is the biggest, but
Speaker 3: we also need to run a company, so we have
Speaker 3: real operating expenses. We're right in the guts right now
Speaker 3: of FY twenty five planning that is usually a three
Speaker 3: year outlook in most companies and for us, it needs
Speaker 3: to be because we have to make those compute decisions.
Speaker 3: And with that comes then Okay, what is our balance
Speaker 3: sheet going to look like? What's our cash burn rate?
Speaker 3: At what point can we generate enough free cash flow
Speaker 3: to actually help the business? Not ready to tell you
Speaker 3: that today, that's for the next time we talk. And
Speaker 3: then on top of that, how do I help keep
Speaker 3: bringing our syndicative investors along?
Speaker 2: I called them with us.
Speaker 1: We are less than a week from the election, and
Speaker 1: I think about my own use of four to Oh,
Speaker 1: I've not used it related to the elections searching for information,
Speaker 1: but are you preparing for that election and what impact
Speaker 1: might it have on open AI?
Speaker 2: Yeah, we absolutely are.
Speaker 3: We have to be very mindful from a safety perspective today.
Speaker 2: If you do.
Speaker 3: Searching around the election, you'll actually see that often we
Speaker 3: will not return a response or will return with a caveat.
Speaker 3: That says to be mindful of your sources, and I
Speaker 3: think I learned a lot of that. Frankly, Yet nextdoor, right,
Speaker 3: you cannot need to be careful of not being paternalistic
Speaker 3: or paternalistic around people. People need to be able to
Speaker 3: find information make their own educated decisions. But at the
Speaker 3: same time, you also need to be very aware when
Speaker 3: you have a platform that today services two hundred and
Speaker 3: fifty million people every single week, we have to recognize
Speaker 3: that they're going to want to do things, and we
Speaker 3: need to provide avenues, but in a safe and secure way.
Speaker 1: Open AI CFO Sarah Friar here live in Las Vegas.
Speaker 1: Thank you very much, exactly to catch up