“But realistically, even with shifting many of our existing resources to focus on AI, we'll still grow our investment envelope meaningfully before we make much revenue from some of these new products.”

In context

“rameter models that we released are best-in-class for their scale. The 400-plus billion parameter model that we're still training seems on track to be industry leading on several benchmarks. And I expect that our models are just going to improve further from open source contributions. Overall, I view the results our teams have achieved here as another key milestone in showing that we have the talent, data and ability to scale infrastructure to build the world's leading AI models and services. And this leads me to believe that we should invest significantly more over the coming years to build even more advanced models and the largest scale AI services in the world. As we're scaling CapEx and energy expenses for AI, we'll continue focusing on operating the rest of our company efficiently. But realistically, even with shifting many of our existing resources to focus on AI, we'll still grow our investment envelope meaningfully before we make much revenue from some of these new products. I think it's worth calling that out that we've historically seen a lot of volatility in our stock during this phase of our product playbook, where we're investing in scaling a new product but aren't yet monetizing it. We saw this with Reels, Stories as newsfeed transition to mobile and more. And I also expect to see a multiyear investment cycle before we fully scale Meta AI, business AIs and more into the profitable services I expect as well. Historically, investing to build these new scaled experiences in our apps has been a very good long-term investment for us and for investors who have stuck with us. And the initial signs are quite positive here, too. But building the leading AI will also be a larger undertaking than the other experiences we've added to our apps, and this is likely g”