We have this benefit of living in the future. Let's not waste it. Our mission is AGI for the benefit of humanity, not AGI for the benefit of humanity who can pay for it. I just find extremist conversations so frustrating. Data centers clearly can be a contentious conversation. This is where you earn trust. Most importantly, you show up and you don't tell them what they need to do. You ask them. How do we engage with the world at large as we have those conversations, and help people understand the pace at which we're moving?
Please welcome Sarah Friar and Reid Hoffman.
Okay. Since we were in a hearts conference, we get a little hug.
Yes. Exactly. Well, it's, you know, super smart and super wonderful, I think, is the right way to describe you. That would be the...
I will give you the check. Thank you.
So, let's start with: what kind of age is the age of AI?
Wow, that is a big question. Well, thank you. Yes, for letting us be here.
We are in an incredible moment to be alive. A lot of people talk about the age of AI as another industrial revolution, right? We laid the rail tracks, we put up electricity wires, we kind of gave people the first taste of what it was like to get an extra hour of light in their homes. And I think we're in that early, early zone in the age of AI, but I think it's so much more than that. Sam has used this term: a renaissance of creativity and innovation. We announced yesterday the acquisition of a company called Orchestra Bio. And what is that? It's a platform for AI agents and scientists. So this is working together to speed up drug discovery, drug delivery out into the world.
Beyond that, if you look at our platform today at OpenAI, what we're seeing is people going from asking — so the ChatGPT moment — to doing — so the agent moment — to actually really proactive. Everybody in the world can now have a virtual coworker. And what does that mean for 1.2 billion people who use ChatGPT every week? That's a fifth of the world's population. And they might be asking something fairly prosaic like, 'What do I make for dinner tonight for my picky kid?' or literally doing something that is life-changing. That's what we're talking about.
And just a couple more comments on then what it means for OpenAI. We are seeing an incredible inflection in our business too. So of those, for example, in ads, we just announced this morning 100,000 advertisers on the platform, now offering in 89 different countries. But why is that important? It's important because those 1.2 billion people, 90% of them can get AI for free because we're building a durable business model behind it. And free is important because our mission is AGI for the benefit of humanity, not AGI for the benefit of humanity who can pay for it or who live inside a corporation, right? Literally everyday people getting to benefit. And then we're going to talk about it, but it's not without risk either.
These models, you know — because I remember when you called me about DALL-E and you were talking about a panda riding a bicycle, and I was like, why is Reid so excited about a panda riding a bicycle? But we can talk about that later.
But they're very powerful in areas like cyber. The bad guys are getting access to very powerful Chinese models. We need to make sure the good guys, the defenders, have the tools. This morning the Journal just ran an article about PHP, where we've been working with them since the end of the summer, when we discovered, using actually an n-1 model 56, a set of vulnerabilities in PHP, which really means the internet. So about 70% of websites would have been impacted — would have brought down probably a lot of the internet. So we've been working in a very secret way to get those vulnerabilities fixed before the offense discovers them. And so happy to announce today that we've done that work. Is the work done? Definitely not. Is the bar going to keep getting raised? Absolutely. But yeah, the age of AI — I mean, I'm grateful to be alive.
Yeah, what a time to be alive. So last year we had Brené Brown on, and part of the thing for leadership — and leadership in these times where we're redefining the scope of how society, you know, industry operate, what it means to be human, where are we going — it's important to have these cycles, to think about the big questions, to make the space for that. So how do you do that? How does OpenAI do that, given that the questions here are like the invention of electricity, the invention of the printing press? So how do you make that space for these kind of important, very big thoughts?
Yeah, and happening — the printing press or electricity happened at a much slower pace. Although I bet if you lived then you thought it was an incredible pace, by the way. To make the space: I mean, we've used a phrase called pacing the frontier, and pacing the frontier is really about, as we think about safety and alignment, giving our researchers and our whole company and the world to some degree time to digest, like, what are the implications. So right now we have paced the frontier most recently by actually holding back our most powerful model, partially because we want to make sure the safety and alignment is at a place where our researchers have had time to really think it through. That model is the model that solved the Navier-Stokes Millennium Math problem, and also about 350 more theorems have certainly moved along from a theoretical proof perspective.
What I think a lot about internally, where I try to make the space, is: theories are great, and we need to work closely with the scientific community on that, but what does it actually mean in practice? Like, you know, I was a material scientist, so I actually remember Navier-Stokes coming up, only because I think Stokes was Irish, so I was very taken by that. I'm Northern Irish in case you wonder why I'm going down that track, hence the green shoes. But what does it really mean when you discover something in fluid dynamics from a theoretical math problem? It means now we actually can have thoughts on how to make heart valves in artificial hearts more — just more efficient, more effective. It means data center cooling actually can become more efficient. Which means that when we go into communities and talk about water use, we now can talk about less water being required. It's about two Olympic swimming pool sizes, by the way, for a data center, particularly one with a closed loop cooling system that uses about 300 households' worth of water per year. So it's not a big amount of water, but if we can make that 100 households, suddenly it's a much better conversation with the communities.
So to me, finding the time is about allowing that pacing of the frontier. It's allowing, like if you saw us at work, we really try to — we just had an offsite last week at Sam's house, Friday and Saturday. You know, you give up all your time to sit down and have these much deeper conversations. So unlike a lot of, you know, having grown up somewhat in corporate America, where you did offsites and it was to talk about like, what's our revenue going to look like next year or next quarter, and how are we going to think about headcount and so on — like, I would say that shrinks back a lot. That's still my job, to make sure we have a strong financial footing, but most of the space is for these much bigger conversations. And of course, it's how do we engage with the world at large as we have those conversations and help people understand the pace at which we're moving.
Yeah. Well, one of the key things is trust, because trust in all institutions is at an all-time low, right? I mean, it's actually disastrous for society. It's disastrous for us functioning, and obviously it makes business itself difficult. But given AI, and given the problem is that most people are like, 'Ah, what's going on?' What's the work? What's the effort to try to build some understanding and trust? Like, what are you doing? What is OpenAI doing? What could people do to kind of help understand that?
So, first of all, trust is earned. It doesn't just fall down on you like manna from heaven. It is earned. So it takes time, and it's grindy, because, you know, I always call it you're filling the bucket, because all the things will happen where you take — I always tell my kids, like, you'll take stuff out of the bucket, but you got to fill the bucket. I would start by saying something like healthcare is actually a very strong footing for us in a world where people do trust AI and healthcare together. So of those 1.2 billion people around the globe, about a third ask ChatGPT a health or wellness question every week. And if you go look in health deserts, like West Texas for example is a health desert, that number spikes. It's not a third; it can be upwards of 80, 90% of all users are using it for health or wellness. So that's kind of a starting point where consumers feel it.
Then we can create tools for physicians, which we've done. And to me that's important because if you look at AI in the world of medicine there's a lot we can talk about — better, faster drug discovery, right? In Boston Children's Hospital they gave us genetic data, diagnostic data, scientific literature, and today I think they gave us something like 300-plus not-yet-resolved diseases to try to resolve, and today we've gotten to 40. So still a lot to get, but what does that 40 mean? It means answers for families who didn't have an answer before. But for physicians — a lot of what happens, or nurses, who are the whole gamut — a lot of their work is paperwork. My brother is a doctor in the UK in the NHS. He's an HDU doctor. What that means is if you show up in the ER, his job is to right away triage you. If you're having a heart attack, you go to cardio. If you've got a gunshot wound, you go to trauma. But mostly you don't know, and you do not want to show up in front of my brother. That is not because he's not a great doctor, but it means not good things are happening for you.
Do you think that this man wants to do paperwork in that moment? 'Let me fill out a form.' He's like, 'No. What can I do?' And when I talk to him about how much time he spends on paperwork, we can shrink that. So then if you think about how we work with enterprises, we work with some of the largest hospital chains in the world. And there we just did a proof of concept that showed HCA, which is the largest in the US, that we could speed the time a patient spends in hospital, lowering it by 25%. What that means is those patients get out of hospital faster into community medicine, and they're not getting sicker, because often if you hang around in a hospital too much, you will actually just catch the next disease. So it's a way to talk about the unified platform that OpenAI is building: consumers to individual — you know, it could be a dentist office, a doctor's office — to a large enterprise. And it's important that we're touching all three, which comes back to your question of trust, because then you start earning trust because you're showing up, creating outcomes, and you're not just telling the world 'trust us, AI is great' — you're actually showing what these magical outcomes can be.
So, one of the things that kind of throws people off, and I think it's good for Sam to have said things like this, which is: you have to accept some of the bad things, some of the risks, etc., because that is what the path looks like in order to deploy to the good things. What's the way that that kind of — because, you know, one of your primary jobs is also navigation of risk. How do you get both — like from your approach and also OpenAI — think, okay, here's how we navigate risk in order to get these good things?
