WEBVTT - OpenAI CFO Sarah Friar Talks AI in Banking and Politics

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<v Speaker 1>Welcome to our Bloomberg television and radio audiences around the world.

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<v Speaker 1>We're live in Las Vegas. This is Money twenty twenty

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<v Speaker 1>and we're joined by open AI's CFO Sarah Fryer. And

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<v Speaker 1>this is interesting.

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<v Speaker 2>You have some history with.

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<v Speaker 1>Money twenty twenty, history with fintech, but that's kind of

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<v Speaker 1>the point. And so much of the focus to date

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<v Speaker 1>on open ai has been I guess, a personal use

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<v Speaker 1>of chat GPT, but let's start with the banks and finances.

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<v Speaker 1>How much of that is made up in your business?

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<v Speaker 2>Yeah, it's like you.

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<v Speaker 3>Ad, it's so great to be here, and you're right,

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<v Speaker 3>Money twenty twenty. I've seen it progress through the years

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<v Speaker 3>and what an incredible event it is today. And we're

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<v Speaker 3>here because our customers are here. AI is happening right now.

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<v Speaker 3>It's not experimental. It's not something that people are just

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<v Speaker 3>playing around with, banks, financial institutions, FinTechs. People are using

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<v Speaker 3>it today in their business.

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<v Speaker 1>There's the Morgan Stanley case study. Yeah, you know, this

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<v Speaker 1>week alone or past week, Bank of America's talks about

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<v Speaker 1>how many patents it's got in machine learning and artificial intelligence.

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<v Speaker 1>But do you actually have a tangible sense of what

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<v Speaker 1>is is those financial institutions are doing with your large

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<v Speaker 1>language models.

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<v Speaker 2>Yes, absolutely so.

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<v Speaker 3>Morgan Stanley is a great example in their wealth management business.

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<v Speaker 3>They're using our models both to help wealth advisors be

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<v Speaker 3>more productive. They're using it as a way to create

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<v Speaker 3>better financial advice and outcomes for customers. We're seeing folks

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<v Speaker 3>like Klarna use it in a customer service. CEO of

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<v Speaker 3>Clarina has been very loud and proud on this front.

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<v Speaker 3>That's another great case study in terms of productivity improvements.

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<v Speaker 3>And then we have banks like VBVA that are using

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<v Speaker 3>it all across their business. And that's really our message here.

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<v Speaker 3>It's just get started. Get enterprise chat, GPT, roll out

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<v Speaker 3>to your organization, see what your people do with it.

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<v Speaker 2>Help them just get started.

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<v Speaker 3>Whether they're in marketing, in finance and product everyone can

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<v Speaker 3>have really interesting even.

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<v Speaker 1>If we are just getting started. Can you help our

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<v Speaker 1>audience understand how meaningful contribution the financial services sector fintech

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<v Speaker 1>makes to open AIS revenue? Yes?

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<v Speaker 3>So today if you look at our largest verticals areas

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<v Speaker 3>like EEDU, education, healthcare.

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<v Speaker 2>But financials is probably third.

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<v Speaker 3>And again I think that's because they are typically early adopters.

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<v Speaker 3>They're often willing to take that risk because they see

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<v Speaker 3>the upside in terms of driving more revenue. But they

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<v Speaker 3>also are very good at managing their cost and efficiency.

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<v Speaker 3>And it's great when you get an early adopter like

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<v Speaker 3>Morgan Stanley because it tends to lead the way.

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<v Speaker 2>I can think of a wealth.

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<v Speaker 3>Management client today that it's not coming to us to

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<v Speaker 3>say what do we need to do?

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<v Speaker 2>How do we get started?

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<v Speaker 1>Banks in particular can be sensitive to pricing. There's a

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<v Speaker 1>lot of curiosity not just in as a consumer how

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<v Speaker 1>much I'm paying on a monthly basis for chat GPT access,

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<v Speaker 1>but at the enterprise level as well. Reports are for example,

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<v Speaker 1>at the corporate per user level, you're thinking it about

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<v Speaker 1>two thousand dollars per head? How are you managing us

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<v Speaker 1>give us insight into the pricing strategy.

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<v Speaker 3>Sure, so pricing is super interesting because we're really trying

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<v Speaker 3>to think about value and what is this person getting

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<v Speaker 3>from this tool? And I think I actually don't think

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<v Speaker 3>we've done a great job of that yet ourselves. Despite

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<v Speaker 3>that we have two hundred and fifty million weekly active

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<v Speaker 3>users and all of that's a you know, five six

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<v Speaker 3>percent actually converted to be plus customers, so they're paying

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<v Speaker 3>but if you look at the value. When we were

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<v Speaker 3>rolling out oh one, our reasoning model, and this is

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<v Speaker 3>a model that stops and thinks for you. It actually

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<v Speaker 3>does hard problems. I was watching a lawyer in action

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<v Speaker 3>using it to create a brief and at the end

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<v Speaker 3>we said to him, what would you have paid for that,

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<v Speaker 3>like if you had a paralegal doing that? He was like,

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<v Speaker 3>easily one thousand to two thousand dollars per hour. And

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<v Speaker 3>this is someone who's using it. If it's an enterprise

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<v Speaker 3>per seeds, probably sixty bucks per month. And this is

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<v Speaker 3>someone who would have paid one thousand to two thousand

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<v Speaker 3>dollars per hour. So I think that there's a lot

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<v Speaker 3>of value that is in the product today, but we

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<v Speaker 3>are just trying to make sure people can get started,

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<v Speaker 3>can actually see the outcomes, and over time we believe

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<v Speaker 3>that value to price will come into alignment.

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<v Speaker 1>Is a balance right between what's of value to your customer,

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<v Speaker 1>but also you know you have to account for open

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<v Speaker 1>AIS spending. So we talked about endlessly, particularly on the

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<v Speaker 1>compute side, what is that balance in what works best

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<v Speaker 1>for you and your customer base.

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<v Speaker 3>Yeah, so our first and foremost, what's most important to

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<v Speaker 3>us is to stay on the frontier, building the frontier models,

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<v Speaker 3>making sure that we are bringing ultimately agi to the

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<v Speaker 3>benefit of humanity. To do that, it's expensive. We have

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<v Speaker 3>to invest in large scale compute and so to me,

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<v Speaker 3>there's really two ways to finance that.

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<v Speaker 2>It's either through the free cash flows of.

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<v Speaker 3>The business spoken like a good CFO, or it's through

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<v Speaker 3>raising equity and debt financing because investors can see the

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<v Speaker 3>long term potential of this business.

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<v Speaker 2>So on the former, on the cash.

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<v Speaker 3>Flows of the business, we want to make sure we

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<v Speaker 3>keep growing that business. I think we have been wowed

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<v Speaker 3>at just the pace of growth, particularly on the consumer side.

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<v Speaker 3>It's about seventy five percent of our business today. But

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<v Speaker 3>even our enterprise businesses, they are young, but they are

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<v Speaker 3>ready doing an incredible amount of annualized revenue and a

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<v Speaker 3>real excited by the potential there.

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<v Speaker 1>For a bluebig television and radio audience worldwide. We're in

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<v Speaker 1>Las Vegas at Money twenty twenty and we're speaking to

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<v Speaker 1>the Open AI CFO Sarah Fryar, and you talk there

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<v Speaker 1>about the consumer business. Something very interesting is the future

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<v Speaker 1>business model ADS supported tiers, for example, very specifically segmented pricing.

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<v Speaker 1>How do you think about that.

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<v Speaker 3>Sarah, Yeah, so I think you always want to stay

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<v Speaker 3>open to alternate business models or ways that you can

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<v Speaker 3>layer a new business model on top. Now, the key

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<v Speaker 3>for us is always access. How do we make sure

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<v Speaker 3>as many people as possible get access to this tool?

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<v Speaker 3>And that's on a global stage, by the way, And

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<v Speaker 3>so to do that sometimes you do pivot away from

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<v Speaker 3>just pure subscription models to models like ads. My last

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<v Speaker 3>company was all ads, so I've definitely experienced this. I

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<v Speaker 3>think ads have their place, but you have to be

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<v Speaker 3>really mindful of were I think in areas like commerce,

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<v Speaker 3>ads are great. Right if I do a chat GPT

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<v Speaker 3>prompt for black high heels shoes, something I probably would do,

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<v Speaker 3>so I actually don't want a history of the black

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<v Speaker 3>high heeled chew. I want five stores I could buy

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<v Speaker 3>from right now, probably e commerce. So that's why companies

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<v Speaker 3>like Shopify are great customers of ours as well. But

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<v Speaker 3>there are other places where actually the AD model doesn't

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<v Speaker 3>make as much sense. You want to get the consumer

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<v Speaker 3>to the answer they need as fast as possible, and

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<v Speaker 3>I think that's where chat Gibt is a really very

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<v Speaker 3>different platform from say something like Google Search.

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<v Speaker 1>You are still relatively early in this role, but it's

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<v Speaker 1>been two years since the original deal with Microsoft was negotiated,

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<v Speaker 1>and that compute relationship is critically important. Yes, all those

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<v Speaker 1>terms change, are they fluid or are you just sticking

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<v Speaker 1>to the contract that was on your desk when you arrived.

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<v Speaker 3>Now, and it's actually longer than two years. Microsoft and

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<v Speaker 3>OpenAI have been partners, I think for actually almost five years,

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<v Speaker 3>so they really came to us when we were a

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<v Speaker 3>research lab, and the deal that we've worked with them

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<v Speaker 3>is they do provide compute exclusively and we give them

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<v Speaker 3>the IP around artificial intelligence.

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<v Speaker 2>So it's incredible.

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<v Speaker 3>The products they're rolling out today are really built a

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<v Speaker 3>top of open AI's AI. As we go forward and

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<v Speaker 3>as we get bigger, we absolutely see a maturing in

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<v Speaker 3>that relationship, and so for consumer benefit, we want to

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<v Speaker 3>make sure consumers always get access to what they need.

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<v Speaker 3>That will probably mean compute for more parties over time.

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<v Speaker 2>Where we did.

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<v Speaker 3>Discuss the Oracle deal, or Oracle discussed it a few

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<v Speaker 3>quarters back, and I think that's a good starting point

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<v Speaker 3>for just how do we maximize compute so we maximize

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<v Speaker 3>the impact for consumers.

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<v Speaker 1>The catchphrase or buzz word of this year, I think

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<v Speaker 1>has been ship products. You're the CFO, and so there's

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<v Speaker 1>a tension between the cost of doing so and the

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<v Speaker 1>need to move quickly. I think Sam has denied recently

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<v Speaker 1>reports that the next model will be out by year end.

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<v Speaker 1>What can you tell us about the path forward their

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<v Speaker 1>the cadence of new models to come.

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<v Speaker 3>Yeah, I mean I think you hit the nail on

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<v Speaker 3>the head ship product product velocity. That is the mantra

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<v Speaker 3>internally to open an eye. And it's something I've just

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<v Speaker 3>been so wowed by since I started as just.

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<v Speaker 2>How fast we do ship products right.

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<v Speaker 3>Even in my short tenure, I've seen one come out

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<v Speaker 3>our Reasoning model, that huge step forward from kind of

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<v Speaker 3>what has been more the Chat ChiPT model series. We've

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<v Speaker 3>launched things like advanced speech talk to the model itself.

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<v Speaker 2>The O series four.

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<v Speaker 3>O enough four Mini for example, four O Mini, which

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<v Speaker 3>is our distilled model, is one hundredth the cost of

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<v Speaker 3>what the original Chat Ept four model was. That is

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<v Speaker 3>incredible for developers, and that's why you see the API

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<v Speaker 3>products be so successful. And again it goes back to

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<v Speaker 3>how do we get this into the hands of many

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<v Speaker 3>developers are a force multiplier and today I'm super proud.

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<v Speaker 3>I think every single Ai unicorn is built atop of

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<v Speaker 3>open AI's API, and that will tell you how we

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<v Speaker 3>are the frontier model.

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<v Speaker 1>I think when I started covering open Ai, there was

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<v Speaker 1>around five hundred people at the company. It's probably near

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<v Speaker 1>two thousand now.

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<v Speaker 2>Yeah.

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<v Speaker 1>That as the CFOs to keep talent long serving talent happy.

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<v Speaker 1>My understanding is that tenders will be a big part

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<v Speaker 1>of that, giving employees liquidity. What will be the cadence

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<v Speaker 1>and sort of increments of that going forward, Sarah, Yeah.

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<v Speaker 3>So we are a company that has done tenders to date,

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<v Speaker 3>and part of that is because we are in a

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<v Speaker 3>competitive market, particularly for research talent. When I think about

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<v Speaker 3>what keeps you on that front edge of the best

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<v Speaker 3>models out there, it is compute, but more importantly, it's people.

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<v Speaker 2>It's great researchers.

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<v Speaker 3>And so in order to compete with companies that have

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<v Speaker 3>liquidity already in their stock public companies, we have taken

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<v Speaker 3>this approach to tenders a little bit like others in

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<v Speaker 3>the space.

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<v Speaker 1>SpaceX is a great bax one we've covered closer, yes.

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<v Speaker 3>And so we want to be able to keep doing that.

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<v Speaker 3>We want to do it thoughtfully and mindfully, knowing that.

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<v Speaker 3>The other rule one is to keep it on the field,

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<v Speaker 3>make sure we have money for computees. It's always a balance,

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<v Speaker 3>but we do think it's important to give our researchers

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<v Speaker 3>that access for.

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<v Speaker 1>Rob Bloomberg television and radio audience all around the globe.

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<v Speaker 1>We're in Las Vegas and we're speaking to the open

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<v Speaker 1>Ai CFO, Sarah. Open Ai is a software company, or

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<v Speaker 1>it was. Now A lot of the focus is on

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<v Speaker 1>Sam and the team's ambitions with safeguarding infrastructure. How involved

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<v Speaker 1>are you in that talking about the sort of construction

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<v Speaker 1>of five gig what data centers and the financing of

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<v Speaker 1>such things. Yeah, was that a surprise to come in

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<v Speaker 1>and sort of think, Okay, I need to get a

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<v Speaker 1>handle on that project.

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<v Speaker 2>Not a surprise, but definitely a stretch.

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<v Speaker 1>It's a new territory, stretch from a capital perspective, stretch.

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<v Speaker 3>From a capital and also just my own learning. Frankly,

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<v Speaker 3>I think we're all learning in this space. Infrastructure is destiny.

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<v Speaker 3>It's this wonderful phrase that Chris Lane has managed to

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<v Speaker 3>get up there in the world, and we do think

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<v Speaker 3>that this build is important. It's important for us competitiveness,

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<v Speaker 3>it's important for world productivity. It's important even with a

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<v Speaker 3>national security lens. And so you are right. One of

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<v Speaker 3>the key jobs I need to do is to figure

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<v Speaker 3>out that capital allocation story. It's going to be both

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<v Speaker 3>a working with part. It's going to be raising financing,

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<v Speaker 3>but it's always making sure that we are staying ahead

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<v Speaker 3>of what will be required. Call it two three years out,

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<v Speaker 3>because you can't just turn on compute today if you

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<v Speaker 3>need it. You actually have to have thought about it,

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<v Speaker 3>probably about three years ahead.

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<v Speaker 2>On that, if I may.

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<v Speaker 1>One of the things I heard from some of your

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<v Speaker 1>investors is you did a very good job early in

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<v Speaker 1>explaining the basics of the plan, but the ultimate goal

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<v Speaker 1>is AGI.

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<v Speaker 2>That's correct.

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<v Speaker 1>How confident do you feel you have that sort of

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<v Speaker 1>into infrastructure in place or a plan to have it

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<v Speaker 1>for AGI?

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<v Speaker 3>I think we have the plan in place. I think

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<v Speaker 3>if Sam we're sitting on the seat, he would tell

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<v Speaker 3>you AGI is closer.

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<v Speaker 2>Than most think.

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<v Speaker 1>But I what would you say?

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<v Speaker 3>I would agree based on what I'm seeing. Like one

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<v Speaker 3>of the best meetings I get to go to once

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<v Speaker 3>in a while is the research meeting, and it would

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<v Speaker 3>blow your mind to see what's already coming and what

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<v Speaker 3>as we have learned how to take reasoning models like

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<v Speaker 3>oh one preview yes on top of GPT models and

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<v Speaker 3>the interplay between those. You're now really starting to see

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<v Speaker 3>some incredible outcomes. PhD level outcomes where you have in

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<v Speaker 3>your pocket human intelligence that is PhD level and physics

0:12:13.760 --> 0:12:17.839
<v Speaker 3>and biology and chemistry in English literature, like whatever the

0:12:17.960 --> 0:12:20.439
<v Speaker 3>job is you need to do if you're a healthcare researcher,

0:12:20.520 --> 0:12:24.360
<v Speaker 3>if you're a banker, if you're in education. The tool

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<v Speaker 3>that you are now caring the power there blows my mind.

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<v Speaker 1>Sarah, you touched on it a moment ago, financing the

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<v Speaker 1>needs to raise capital. You've just done a pretty astonishing

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<v Speaker 1>large round. But a follow on, I mean you must

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<v Speaker 1>have a good sense of the cadence of needing to

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<v Speaker 1>raise funds on an annual basis. I don't know how

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<v Speaker 1>you plan it.

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<v Speaker 2>Yeah, so it goes back.

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<v Speaker 3>To what you said, which is really understanding in your plan,

0:12:45.400 --> 0:12:47.840
<v Speaker 3>what are your big expenses? Compute is the biggest, but

0:12:47.880 --> 0:12:49.520
<v Speaker 3>we also need to run a company, so we have

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<v Speaker 3>real operating expenses. We're right in the guts right now

0:12:52.480 --> 0:12:55.040
<v Speaker 3>of FY twenty five planning that is usually a three

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<v Speaker 3>year outlook in most companies and for us, it needs

0:12:57.480 --> 0:12:59.719
<v Speaker 3>to be because we have to make those compute decisions.

0:13:00.120 --> 0:13:02.559
<v Speaker 3>And with that comes then Okay, what is our balance

0:13:02.559 --> 0:13:04.920
<v Speaker 3>sheet going to look like? What's our cash burn rate?

0:13:05.679 --> 0:13:08.040
<v Speaker 3>At what point can we generate enough free cash flow

0:13:08.120 --> 0:13:10.760
<v Speaker 3>to actually help the business? Not ready to tell you

0:13:10.800 --> 0:13:13.600
<v Speaker 3>that today, that's for the next time we talk. And

0:13:13.640 --> 0:13:15.600
<v Speaker 3>then on top of that, how do I help keep

0:13:15.640 --> 0:13:17.720
<v Speaker 3>bringing our syndicative investors along?

0:13:17.800 --> 0:13:22.079
<v Speaker 2>I called them with us.

0:13:22.600 --> 0:13:25.160
<v Speaker 1>We are less than a week from the election, and

0:13:25.240 --> 0:13:27.120
<v Speaker 1>I think about my own use of four to Oh,

0:13:28.160 --> 0:13:31.280
<v Speaker 1>I've not used it related to the elections searching for information,

0:13:31.440 --> 0:13:34.680
<v Speaker 1>but are you preparing for that election and what impact

0:13:34.800 --> 0:13:35.960
<v Speaker 1>might it have on open AI?

0:13:36.120 --> 0:13:37.360
<v Speaker 2>Yeah, we absolutely are.

0:13:37.720 --> 0:13:41.160
<v Speaker 3>We have to be very mindful from a safety perspective today.

0:13:41.160 --> 0:13:41.600
<v Speaker 2>If you do.

0:13:41.600 --> 0:13:44.760
<v Speaker 3>Searching around the election, you'll actually see that often we

0:13:44.880 --> 0:13:47.960
<v Speaker 3>will not return a response or will return with a caveat.

0:13:48.000 --> 0:13:50.480
<v Speaker 3>That says to be mindful of your sources, and I

0:13:50.480 --> 0:13:53.040
<v Speaker 3>think I learned a lot of that. Frankly, Yet nextdoor, right,

0:13:53.320 --> 0:13:56.720
<v Speaker 3>you cannot need to be careful of not being paternalistic

0:13:56.800 --> 0:13:59.320
<v Speaker 3>or paternalistic around people. People need to be able to

0:13:59.320 --> 0:14:03.600
<v Speaker 3>find information make their own educated decisions. But at the

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<v Speaker 3>same time, you also need to be very aware when

0:14:05.920 --> 0:14:08.640
<v Speaker 3>you have a platform that today services two hundred and

0:14:08.679 --> 0:14:12.199
<v Speaker 3>fifty million people every single week, we have to recognize

0:14:12.200 --> 0:14:13.960
<v Speaker 3>that they're going to want to do things, and we

0:14:14.040 --> 0:14:17.000
<v Speaker 3>need to provide avenues, but in a safe and secure way.

0:14:17.480 --> 0:14:20.640
<v Speaker 1>Open AI CFO Sarah Friar here live in Las Vegas.

0:14:20.640 --> 0:14:22.720
<v Speaker 1>Thank you very much, exactly to catch up