Susan Li: Sure. So the first part of your question was early sort of signals with Quest 3. We are not sharing any explicit expectations for Quest 3, either Q4 Reality Labs revenue, unit sales, et cetera. But we are very excited to have Quest 3 in market, in particular, during the holiday shopping period. We think early reviews have been great. And we’re very excited to have a product out there that are going to introduce a lot of people to mixed reality experiences for the first time. So it’s very early. I think we don’t have very many more specifics. But again, we’re quite excited to have it in the market and to have it in particular during the holiday marketing season. Your second question was about political spend. And so this is a place where I would say we saw acceleration of positive year-over-year growth in all verticals this quarter really except politics, which is lapping the lead-up to the 2022 US midterms last year.
So I will say though that this is also just a very small vertical for us so there’s not too much more to add there.
Ken Dorell: Dave, we have time for one last question.
Operator: Certainly. Thank you. That will come from the line of Ross Sandler with Barclays.
Ross Sandler: Great. Hey, Mark, just going back to the AI agent theme. I know it’s early but how would you rank the overall strategy here around these AI agents and AI Studio compared to other big initiatives that Meta has made in FoA over the years? Is this bigger than or as big as the Stories transition or the Reels transition? And any thoughts just kind of high level on that? And then the cost of serving up responses, especially stickers and images is a little bit more expensive than your core business of aggregating the News Feed. So how much more expensive, I guess, is the question? And are there things you can do to bring that cost down? Thanks a lot.
Mark Zuckerberg: Yeah, sure. In terms of how big this is going to be, it’s hard to predict because I don’t think that anyone has built what we’re building here. I mean, there’s some analogy is like what OpenAI is doing with ChatGPT, but that’s pretty different from what we’re trying to do. Maybe the Meta AI part of what we’re doing overlaps with the type of work that they’re doing, but the AI characters piece, there’s a consumer part of that, there’s a business part, there’s a creators part. I’m just not sure that anyone else is doing this. And when we’re working on things like Stories and Reels, there were some market precedents before that. Here, there’s technology which is extremely exciting. But I think part of what leading in an area and developing a new thing means is you don’t quite know how big it’s going to be.
But what I predict is that I do think that the fundamental technology around Generative AI is going to transform meaningfully how people use each of the different apps that we build. I think for the Feed apps, I think that over time, more of the content that people consume is going to be either generated or edited by AI. Some of it will be creators will now have all these tools to make content more easily and more fun. And I think over time, maybe we’ll even get to the point where we can just generate content directly for people based on what they might be interested in. I think that, that could be really compelling. On the messaging side, I think that the way that we’re looking at these AIs kind of ties into that directly where you’ll be able to message with Meta AI or any of these different AIs for whether it’s for fun, you have a question about something, you want to help doing something, you want to play a game or you want to message with a business for commerce or you want to engage with your favorite creator and they wouldn’t normally otherwise have time to message you back, but now they have an AI representing them that can.
I think that will accrue to kind of to messaging behavior. It’s going to change advertising in a big way. It’s going to make it so much easier to run ads. Businesses that basically before would have had to create their own creative or images now won’t have to do that. They’ll be able to test more versions of creative, whether it’s images or eventually video or text. That’s really exciting, especially when paired with the recommendation AI. On the hardware side, I mean, obviously, the smart glasses that we just rolled out, we sort of thought were a precursor to eventually getting to displays and holograms for augmented reality, and I think we will eventually get there still. It’s not that far off. But I think that now the ability to deliver AI through smart glasses may end up being a killer use case for that even before you get to the kind of augmented reality type of use cases.
So I think you’re basically seeing that there are going to be — this is a very broad and exciting technology. And frankly, I think that this is partially why working in the technology industry is so awesome, right, is that every once in a while, something comes along like this, that like changes everything and just makes everything a lot better and your ability to just be creative and kind of rethink the things that you’re doing to be better for all the people you serve. I mean, I just think that’s a lot of what is energizing and fun around building companies like this. But yes, it’s hard sitting here now to be able to predict like the metrics are going to be around, like what’s the balance of messaging between AIs and people or what the balance and Feeds between AI content and people content or anything like that.
But I mean, I’m highly confident that this is going to be a thing and I think it’s worth investing in. To the question about efficiency and costs, I think initially, it’s most important to focus on getting to product market fit. And we obviously care a lot about efficiency, right? I mean, the CapEx costs for our company are very significant, and it’s one of the main things that weighs on the economic model of the company. So on the one hand, as we can improve the efficiency, we’re able to do things like train bigger models and serve more people, which currently, right now, we’re going to be bottlenecked on based on the amount of infrastructure that we have as this gets to the scales that we aspire to get to. So in the near term, the efficiency wins will primarily just be to deliver better products to more people.
But over time, we’re going to continue working on that. And I think we’ve been able to do pretty good work on efficiency on our hardware and compute. And over the long term, once we kind of have more of an understanding about what these products want to be, then we’ll be able to drive the economic model based on that. But we’ll work on that all throughout, but I think we’re still in the pretty early part of that curve.
Ken Dorell: Great. Thank you for joining us today. We appreciate your time, and we look forward to speaking with you again soon.
Operator: This concludes today’s conference call. Thank you for joining us. You may now disconnect your lines.
