Meta(META) 2023 年第四季度财报电话会议记录

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$Meta Platforms, Inc.(META)$


Meta Platforms, Inc. (NASDAQ:META) Q4 2023 Earnings Conference Call February 1, 2024 4:30 PM ET

Company Participants

Ken Dorell - Director, IR

Mark Zuckerberg - Founder, Chairman & CEO

Susan Li - CFO

Conference Call Participants

Brian Nowak - Morgan Stanley

Eric Sheridan - Goldman Sachs Group

Mark Shmulik - Sanford C. Bernstein & Co.

Justin Post - Bank of America Merrill Lynch

Ross Sandler - Barclays Bank

Doug Anmuth - JPMorgan Chase & Co.

Ronald Josey - Citigroup


Good afternoon. My name is Krista and I'll be your conference operator today. At this time, I would like to welcome everyone to the Meta Fourth Quarter and Full Year 2023 Earnings Conference Call. [Operator Instructions].

Ken Dorell, Meta's Director of Investor Relations, you may begin.

Ken Dorell

Thank you. Good afternoon and welcome to Meta Platform's Fourth Quarter and Full Year 2023 Earnings Conference Call. Joining me today to discuss our results are Mark Zuckerberg, CEO; and Susan Li, CFO.

Before we get started, I would like to take this opportunity to remind you that our remarks today will include forward-looking statements. Actual results may differ materially from those contemplated by these forward-looking statements. Factors that could cause these results to differ materially are set forth in today's earnings press release and in our quarterly report on Form 10-Q filed with the SEC. Any forward-looking statements that we make on this call are based on assumptions as of today, and we undertake no obligation to update these statements as a result of new information or future events.

During this call, we will present both GAAP and certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in today's earnings press release. The earnings press release and an accompanying investor presentation are available on our website at

And now I'd like to turn the call over to Mark.

Mark Zuckerberg

All right. Hi, everyone. Thanks for joining us. This was a good quarter, and it wrapped up an important year for our community and our company. We estimate that there are more than 3.1 billion people who use at least one of our apps each day. 2023 was our year of efficiency, which focused on making Meta a stronger technology company and improving our business to give us the stability to deliver our ambitious long-term vision for AI and the metaverse.

And last year, not only did we achieve our efficiency goals, but we returned to strong revenue growth, saw strong engagement across our apps; shipped a number of exciting new products like Threads, Ray-Ban Meta smart glasses and mixed reality in Quest 3; and of course, established a world-class AI effort that's going to be the foundation for many of our future products. I think that being a leaner company is helping us execute better and faster, and we will continue to carry these values forward as a permanent part of how we operate.

Now moving forward, a major goal, we'll be building the most popular and most advanced AI products and services. And if we succeed, everyone who uses our services will have a world-class AI assistant to help get things done, every creator will have an AI that their community can engage with, every business will have an AI that their customers can interact with to buy goods and get support, and every developer will have a state-of-the-art open-source model to build with.

I also think that everyone will want a new category of computing devices that let you frictionlessly interact with AIs that can see what you see and hear what you hear, like smart glasses. And one thing that became clear to me in the last year is that this next generation of services requires building full general intelligence. Previously, I thought that because many of the tools were social-, commerce- or maybe media-oriented that it might be possible to deliver these products by solving only a subset of AI's challenges.

But now it's clear that we're going to need our models to be able to reason, plan, code, remember and many other cognitive abilities in order to provide the best versions of the services that we envision. We've been working on general intelligence research and FAIR for more than a decade. But now general intelligence will be the theme of our product work as well. Meta has a long history of building new technologies into our services, and we have a clear long-term playbook for becoming leaders.

And there are a few key aspects of this that I want to take some time to go through today. The first is world-class compute infrastructure. I recently shared that, by the end of this year, we'll have about 350,000 H100s, and including other GPUs, that will be around 600,000 H100 equivalents of compute. We're well positioned now because of the lessons that we learned from Reels. We initially underbuilt our GPU clusters for Reels. And when we were going through that, I decided that we should build enough capacity to support both Reels and another Reels-sized AI service that we expected to emerge so we wouldn't be in that situation again.

And at the time, the decision was somewhat controversial, and we faced a lot of questions about CapEx spending, but I'm really glad that we did this. Now going forward, we think that training and operating future models will be even more compute-intensive. We don't have a clear expectation for exactly how much this will be yet, but the trend has been that state-of-the-art large language models have been trained on roughly 10x the amount of compute each year.

And our training clusters are only part of our overall infrastructure, and the rest, obviously, isn't growing as quickly. But overall, we're playing to win here, and I expect us to continue investing aggressively in this area. In order to build the most advanced clusters, we're also designing novel data centers and designing our own custom silicons specialized for our workloads.

The second part of our playbook is open-source software infrastructure. Our long-standing strategy has been to build an open-source general infrastructure while keeping our specific product implementations proprietary. In the case of AI, the general infrastructure includes our Llama models, including Llama 3, which is training now, and it's looking great so far, as well as industry standard tools like PyTorch that we've developed.

And this approach to open source has unlocked a lot of innovation across the industry, and it's something that we believe in deeply. And I know that some people have questions about how we benefit from open sourcing, the results of our research and large amounts of compute. So I thought it might be useful to lay out the strategic benefits here.

The short version is that open sourcing improves our models. And because there's still significant work to turn our models into products because there will be other open-source models available anyway, we find that there are mostly advantages to being the open-source leader, and it doesn't remove differentiation for our products much anyway. And more specifically, there are several strategic benefits.

Meta Platforms, Inc. (NASDAQ:META) Q4 2023 Earnings Conference Call February 1, 2024 4:30 PM ET

Company Participants

Ken Dorell - 董事,IR

马克·扎克伯格 - 创始人,董事长兼首席执行官

李苏珊 - 首席财务官

Conference Call Participants

Brian Nowak - Morgan Stanley 布赖恩·诺瓦克 - 摩根士丹利

埃里克·谢里丹 - 高盛集团

Mark Shmulik - Sanford C. Bernstein & Co. 马克·舒姆利克 - 桑福德·C·伯恩斯坦公司

贾斯汀·波斯特 - 美国银行美林证券

Ross Sandler - 巴克莱银行

道格·安姆斯 - 摩根大通公司

Ronald Josey - 花旗集团


下午好。我是 Krista,今天将担任您的会议操作员。现在,我想欢迎大家参加 Meta 2023 年第四季度和全年收益电话会议。【操作员指示】。

Ken Dorell, Meta's Director of Investor Relations, 你可以开始了。

Ken Dorell

谢谢你。 下午好,欢迎参加Meta平台2023年第四季度和全年收益电话会议。 今天与我一起讨论我们的业绩的有首席执行官马克·扎克伯格和首席财务官苏珊·李。




Mark Zuckerberg

好的。 大家好。 感谢大家的加入。 这是一个不错的季度,也为我们的社区和公司画上了一个重要的句号。我们估计每天使用我们至少一款应用的人数超过了31亿。2023年是我们提高效率的一年,我们致力于让Meta成为一家更强大的科技公司,并改善我们的业务,以便为我们提供稳定性,以实现我们对人工智能和元宇宙的雄心勃勃的长期愿景。

去年不仅我们实现了效率目标,而且我们还实现了强劲的收入增长,在我们的应用程序中获得了强劲的参与度;推出了一些令人兴奋的新产品,如Threads、Ray-Ban Meta智能眼镜和Quest 3中的混合现实;当然,我们建立了一个世界一流的人工智能项目,将成为我们未来许多产品的基础。我认为,作为一家精简公司有助于我们更好更快地执行,我们将继续将这些价值观作为我们运营的永久部分。



但现在很明显,我们需要我们的模型能够推理、规划、编码、记忆以及许多其他认知能力,以便提供我们设想中的最佳服务版本。我们在通用智能研究和 FAIR 上已经工作了十多年。但现在通用智能也将是我们产品工作的主题。Meta 在为我们的服务构建新技术方面有着悠久的历史,我们有一个明确的长期战略,成为领导者。


当时,这个决定在一定程度上颇具争议,我们面临了很多有关资本支出的问题,但我真的很高兴我们这样做了。未来,我们认为培训和运营未来的模型将需要更多的计算资源。至今,我们对这一需求的具体量尚不清楚,但现在的趋势是,最先进的大型语言模型每年的训练计算资源约为去年的 10 倍。