All right. Yes. Thanks, Ken. On hotels, I think our experience is going to be quite different than other OTAs. I think Airbnb, first of all, is we care a lot about conversion, but first and foremost, we really, really care about doing something in a differentiated way and doing it in a design-forward way. With regards to inventory being co-mingled versus tabs, I'll say two points. Number one, if you were to search right now in New York City, it is comingled, but we are testing a variety of user interface components like a carousel. So carousel is obviously left to right where it's got a title and there's a left or right swipe. So it allows a distinct type of inventory within a search result page. This works really, really well. So that's one thing we're doing. The second thing is with regards to hotel tabs, doesn't take away too much of our product strategy, but we are probably going to have more tabs in the future for people that want to find something very, very specific. But the more important and broader answer is neither of those. The more important answer is personalization. There are people that only want to book hotels, they should only see a hotel. There are people that only want to book home, they should only see home. There are people that would book homes or hotels and depends on the trip type. So if you are going to search last minute for one night on the business trip and we know all that. And we know you sometimes book hotels, we're probably going to show you hotels. If you're looking for a family vacation, you're traveling with four other guests, you're going to stay for a week in Italy, in Tuscany, a hotel is probably not right. We're probably going to show you an Airbnb, a home. And so I think the ultimate, like, paradigm is not this tab versus co-mingle inventory. I believe that's a pre-AI paradigm. I think post an AI paradigm that we're moving towards and this relates in a second to AI search is deep personalization, understanding every user, every member. And I just want to remind everyone listening that 100% of people who booked have an account, and they have to have a verified ID. You cannot book as a guest. You have to have account, you have to be a member of the community. Therefore, we know something about you. We can infer a lot, not only about what you're clicking on the site, but all of your past booking activities. So the best answer to all of this and the best answer is not necessarily tabs, although I do think we want tabs as navigation for people buying things. But I think in the age of AI, we know about you, we know your intent and we give you exactly what you're looking for. I think this is what most -- all e-commerce sites will look like in a age of AI. And that is point number one. Okay. So now let's talk about AI search. What we've learned? So I'm going to talk about Airbnb's strategy, and I'm going to also talk for a moment about where I see AI search going for travel and e-commerce more generally. So let me talk first about AI search. Okay. So our strategy with AI is actually quite different than our competitors because many of our competitors decided to start top of funnel, where should I travel? We decided to start bottom of the funnel. The reason we decided to start with this is we want to focus on the hardest problem in AI, which we thought was customer service. The reason why is the stakes are high, you have -- you cannot hallucinate, you have to answer things very, very quickly because they are calling and they have problems. You have to be multilingual, often in the same conversation because sometimes guests and hosts don't speak the same language. You have to adjudicate very difficult things. You have to escalate to human accurately, especially if it's timely or there's a trust and safety incident. And you have to deal with personally identifiable information that means that you have to be able to protect people's data, you have to be able to read and train based on nearly 100 policies, tens of thousands of evolving conversations and look at like millions of data points of how a prior case was adjudicated to be able to answer correctly. This is very, very hard. In fact, entire start-ups like I think Sierra's got like a $15 billion market cap, just to solve this problem. So it's a very, very difficult problem. Well, I'm proud to say that we've made a lot of progress. And over 40% of people connect with our AI assistant self-solve. And I believe it's, by far, the best AI self-solve in all of travel. I'm pretty confident of that. So from bottom of the funnel, then we move mid-funnel. And mid-funnel would be things like people go on the Airbnb listing page. And we have hundreds of millions of reviews on Airbnb. And one of the things our guests told us is when they get to an Airbnb, it's great when they see like 100 reviews, it's awesome, but they don't have time to read all 100 reviews. So we now have AI summaries. And AI summaries are really great. We have filters, we have AI summaries. We're now using AI for matching. AI is really helping our search ranking and our relevance. So these are -- on May 20, again, to plug one more time, we're going to see a bunch more AI features in the mid funnel. So that's mid-funnel. Finally, it's top of funnel, which you would call AI search. This is top of funnel. And this is what we're currently testing. And I think the first point I want to make is AI feels like magic, but of course, it's not magic. Nothing is really magic. It just feels like it. And when you break AI under the hood, you realize that you need -- in order to be good at AI, you need to be really good at technology, foundational. You need to be really good data and infrastructure. So what we have been doing over the last few years is really getting our data warehouse really, really clean because your AI is only as good as your data. We've done that. Of course, as I mentioned in our last earnings call, we hired Ahmad, our CTO, who was the leader of the Meta LLaMa model. So we are probably one of the only technology companies in the world certainly only in travel that has an AI-native person running as the entire technology stack. And we are essentially piloting a variety of different ways to use AI, whether it's in the search box, whether it's once you search, interrupting on the search, it's the filter panel, once you book a trip. So we're trying a lot of different things. We're really in the exploration, research development mode. And I think this goes to my final point, which is I don't think anyone figured out AI for travel or e-commerce yet. Let me use an example, ChatGPT. Last year, ChatGPT announced the creation or of third-party apps. And then this past March, they shut that project down. And one of the things we noticed is that while ChatGPT is -- traffic converts higher than Google traffic when it's sent to Airbnb, we think the design of a chatbot fundamentally as its currently constructed today does not work for travel e-commerce. There's essentially four problems. The first problem with the chatbot is there's too much text. Chatbot are LLMs, large language models. They're language. And most of e-commerce is not language forward, it's photo forward. That's the first problem. The second is there's no direct manipulation. You can't touch anything. You have to type everything. And that's great for a conversation. But if you want to like move the price slider, that's much easier than type, well show me X, Y and Z. The third problem is comparison. You go to Airbnb in Paris, there's tens of thousands of homes, I think over 100,000 homes. Imagine trying to compare 100,000 homes in a chat bot, you get lost. And so it wants to show you just three options. You want to see more than three and pretty soon you get confused in a thread. And the fourth problem is that almost all bookings of Airbnb have multiple guests, what we call multiplayer. Chat bots are primarily single player. This doesn't account for the fact that 85% of people booking Airbnb send a message, 100% have an account. And also chat bots are not map-native. So there's a whole bunch of reasons why I don't think travel or e-commerce for AI has been figured out. That's why I think, while AI is a risk to us and everyone. If it's a risk to us, it's a risk to everyone. So risk to everyone is an opportunity for us. And so I believe that over the next year, you can see a lot of innovation around AI search, AI-native interfaces. And I think not only can we solve this for home sharing, I think we can solve it for all parts of travel and maybe even parts of living.