Yes. Maybe I'll start with the second question, and then I'll answer your question on AI, and I'll try to give a robust answer on AI because I'm anticipating some questions on that. I always want to kind of underpromise and overdeliver. So we're going to be cautious on how we want to test the milestones. But on service experiences, what I've essentially told the team is I want to approach service experiences kind of like the way we approached our core business in 2009. It's going to be a little different. But what we tried to do is get to essentially what I think is Silicon Valley called product market fit, right? Product market fit is essentially this indication that we think the business is essentially working and we have a playbook and we're now ready to scale. And so with service experiences, what I've really tried to do is say, hey, let's pick a couple of cities. We decided to pick the top 2 cities in the world on Airbnb, which are Paris and L.A. And they are different cities. They one in Europe, one in L.A., one in the United States. They are different enough that you can test a lot of different hypothesis in these 2 cities. And we said we really want to try to figure out how to get these businesses to product market fit. And then we're going to pick another about a dozen cities and go really, really deep and build out our library of supply. We learned a lot. One of the milestones -- one of the lessons we learned in Paris for experiences, for example, is that there are really 3 types of travel people. There's people where it's their first time to a city like Paris. There are people who've been to Paris repeatedly and then there's local. And that each of them want totally different types of supply. So for people for whom it's the first time to a city, they really want to go to landmark. They want see Eifel Tower. They want to see the loop, they may see [indiscernible], they want to go to [indiscernible]. And this is really what you see when you see other platforms where they're really focused on traditional tourist experiences. So we've been adding a lot of landmark experiences. We think we provide some of the very best high-quality experiences. They're very local in nature, but they're very much appealing to first-time visitors to a city. And this has been very, very popular. Then you've got people who've been to the city already. This is nearly as big and in many cities, it's a bigger market. A lot of people that go to Paris, they have been there before. If it's your second or third time to Paris, you're not going to see Eifel Tower. You want to see something different. So now you want more local experiences. You might want to do a cooking class. Now you might do some other type of activity. And then locals want to do something really unique, really off to the impact. They want to book originals. And so we see these 3 audiences, and that's been really interesting. And the year-over-year growth in Paris has been very encouraging. So by focusing on these cities, we've been able to like rapidly iterate software. We've been able to rapidly like figure out in Paris, for example, there's different supply types for different types of guests based on how many time they've been there, and we can bring these lessons to other cities. In Los Angeles, we've been really focused on building a library of supply for our 10 major categories. So when we launched, we were really deep in photography because photography or traditional travel services. We've gotten very deep now on personal trainers and masseuses and chefs. And we're starting to see that not only travelers booking but people book in their own city. So again, the milestones are going to be us determining that we have efficiently reached product market fit and we can roll out the deep playbook city by city. Now with regards to -- and I'll let Ellie expand if she would like to elaborate on other milestones over the next few years. But with regards to AI, maybe I'll just answer more broadly. Okay. So our AI strategy is pretty unique. I think that Airbnb probably more than most other companies, especially companies in travel can benefit from AI. Probably the reason why is because primarily, we don't have SKUs. Most of our homes, most of our service experiences, they're not SKUs, they're one of a kind. And therefore, the issue types, customer service is really challenging, right? Oftentimes, customer service agent will hear an issue that they've never heard before because it's from a host that might be a first-time host. And the guest and host might be speaking different languages. The might be simply locked out in a small town in a foreign country. You can imagine how complicated some of this stuff is. So we decided with AI to start with the hardest single problem we could think of, which was customer service. Customer service, we think, is a lot harder than, say, travel search. And the reason why is because the stakes are highest. You can't hallucinate. You have to handle sensitive customer data. You've got to be fast in real time. You've got to escalate to the agent if there's a trust and safety incident. And we are finding that it's working really well. And in fact, we can go from solving a problem in hours to solving a problem in seconds. We wanted to then go to the top of the funnel, and that's with AI search. What we're testing now is if you go to the search box in Airbnb, there's where, location, when, date, who guest, we're testing a what box and what is a free text natural language input, which is similar to ChatGPT or Gemini. You'll be able to type it in. And based on that, we're going to essentially -- you're going to see like natural language results. So the search cards, not just will be structured data, but will be essentially natural language generated copy and search results. That's Phase 1. Phase 2, it's going to become what I guess you'd call an AI multi-turn. Multi-turn, I think, is just a fancy way of saying conversational. So you'll be able to have a conversation. So you'll be able to like -- the information on the cards, my vision is instead of saying like 2-bedroom, 2 bath, $60, 5 reviews, a pool hot tub that no 2 people see the same copy, just like 2 people typing in ChatGPT see different outputs based on the memory and the type of question they have. So we want Airbnb to be the same way where the output is also natural language. It's unique. And you're going to start to see this iterably happen over the course of next year. Eventually, it will become more conversational. And then finally, what we want to do take AI search, which is conversational, AI customer service and the messaging platform, which is conversational and integrate them to one AI assistant or concierge. And eventually, the entire app will act like an AI agent from the top of the funnel through your trip on reservation and leaving review and then bringing you back through the app end to end. And we think that we're going to be very successful at this because, number one, we have access to all the same frontier models as the leading AI companies. We have access to the same models as Google, OpenAI and the other companies because they're all available by API. So really, you're not going to win or lose on the model because they're all available. You're going to win or lose on what you do with them. And our thesis of AI is that specialization will win in travel. That's our theory, that specialization will win. We have a lot of unique capabilities. We understand travel, we have one of the best design teams in the world, so we can design custom interfaces. We do not think the way AI search will work in the world of travel is just text. It's going to have to have rich user interface experiences. We're adding a lot more verticals. So we do think Airbnb could be a one-stop shop for travel. And then we have a lot of capabilities that no one else has built, and we don't think AI companies will want to develop like a messaging platform in the vast majority of people who book an Airbnb use the messaging platform. Verified identity to book or host, you must verify your identity. We have more verified identities, 200 million, there are U.S. passports in circulation. We have a payments platform where one in every $1,100, $1,200 spent $1 goes to our payments platform in the world. So this is essentially how we're thinking about AI. I think it's extremely exciting. And I think it's going to benefit Airbnb probably more than other travel platforms just because we don't have SKUs. And I think AI can kind of level the playing field.