CMCM 猎豹移动 2024年第1季度财报电话会议文字稿中英文

Operator

各位好，欢迎参加猎豹移动2024年第一季度财报电话会议。所有与会者将处于只听模式。[接线员指示] 今天的演示结束后，将有机会提问。[接线员指示] 请注意本次活动正在录音。现在我将会议转交给猎豹移动投资者关系部Helen。

Helen Zhu

谢谢接线员。欢迎参加猎豹移动2024年第四季度财报电话会议。今天与我们一同参会的有公司董事长兼首席执行官傅盛先生，以及董事兼首席财务官任先生。管理层准备发言后，我们将进行问答环节。在开始之前，请参阅我们财报新闻稿中的安全港声明，该声明同样适用于我们今天的电话会议，因为我们将做出前瞻性陈述。现在，我将电话会议转交给董事长兼首席执行官傅盛先生。傅盛先生，请开始。

Sheng Fu

大家好。感谢各位今天参加我们的电话会议。这是我们自2021年11月以来的首次财报电话会议。我们很高兴能分享我们的进展，因为我们恢复了季度更新。猎豹移动正在做出改变。我们正从专注于2C转向2B。第一季度，我们来自人工智能及其他企业相关业务的收入同比增长62%，环比增长36%。目前这些收入占我们总收入的43%。我们预计到今年年底这一比例将增长至约50%，这标志着我们转型的重要进展。我们最近收购了人工智能服务提供商北京猎户星空，这是一个重要举措。它为我们带来了熟练的销售团队、稳固的企业客户关系，以及大语言模型（LLM）的端到端能力，包括模型训练、微调训练、开发基于LLM的应用程序，以及增强服务机器人——这是AI时代与终端用户和客户互动的新触点。借助猎户星空，我们现在专注于为企业客户开发基于LLM的应用程序，并推出针对特定业务需求的LLM驱动机器人。我们聚焦于此主要有两个原因。第一，市场机遇。与竞争激烈的2C市场不同，出于数据安全考虑，企业越来越多地选择在私有云上部署基于LLM的应用程序。然而，他们在开发定制化应用方面面临挑战，这在中国企业市场带来了巨大的机会。第二，[技术故障] 将猎豹和猎户星空结合起来，使我们能够将我们的应用企业经验与AI技术相结合，更好地把握市场机遇。通过向企业销售机器人，我们甚至能找到利用LLM提高效率的新方法。我们采用产品驱动的方法来增强我们的LLM能力。这就是为什么我们专注于100亿参数级别的LLM细分市场，并避免在GPU上进行大规模前期投资。我们认为万亿参数的LLM是必要的。而企业可以在私有云上以较低成本部署和使用100亿参数的LLM。过去几个月，我们从零开始改变了[14D]（语音）参数的基础模型，该模型已获得监管机构批准进行大规模推广，并在各类榜单中名列前茅。此外，我们正在整合几乎所有领先的开源基础模型，为客户提供更多选择，且不会显著增加成本。再者，通过将基于LLM的应用程序集成到我们的服务机器人中，我们已经看到了积极的发展。特别是，我们的配送机器人现在能够更好地与用户互动，从而带来了需求增长，尤其是在日本和韩国。目前，我们的海外收入已超过国内收入，并持续稳步增长。借助LLM，我们相信服务机器人的功能将进一步扩展。我还想强调我们如何帮助客户高效使用基于LLM的应用程序。例如，我们帮助成都大学为其应用程序开发了基于LLM的问答功能，改善了用户体验。我们还为另一家客户的产品开发了LLM驱动的客服功能，包括微信小程序、应用程序和我们的服务机器人。这项服务现已在[听不清]提供，帮助当地居民申请住房公积金。我们还在与中国特许经营行业的企业合作，利用基于LLM的应用程序提高管理效率。在基于LLM的应用程序开发的早期阶段，我们与客户紧密合作，了解他们的需求，并找出35个——利用LLM改进的领域。找到最合适的LLM [听不清] 开发客户应用程序。这一过程帮助我们标准化了一些基于LLM的应用程序和能力，特别是在客户服务、企业管理和培训方面，我们可以将其复制给更多客户。因此，我们正在监控客户反馈和认证情况。此外，所有这些应用程序都可以集成到我们的服务机器人中。我们在LLM时代的长期商业模式将涉及销售机器人和提供增值服务。随着我们专注于为企业构建基于LLM的应用程序，我们将把资源从我们的代理互联网业务转移到AI业务。这将提高我们互联网业务的运营利润率，这是我们使用的财务绩效指标。总之，LLM是千载难逢的机遇。凭借猎户星空和清晰的战略，我们现在对我们的方向充满信心。我们想强调，我们不想设定短期的收入增长目标。但我们正在积极优先考虑客户满意度并打造灯塔项目。通过这样做，我们相信我们将建立新的增长引擎，以推动收入和利润率长期可持续增长。我们需要的只是一点耐心。我们感谢所有辛勤工作的敬业员工，是他们让这一切成为可能。谢谢。托马斯？

Sheng Fu

Hello, everyone. Thank you for joining us today. This is our first earnings call since November 2021. And we are excited to share our progress as we resume our quarterly updates. Cheetah Mobile is making changes. We are moving from focus on 2C to 2B. In Q1, our revenue from AI and others or enterprise focused increased by 62% compared to last year and 36% from the previous quarter. Now these revenues make up 43% of our total revenue. We expect this to grow to about 50% by the end of the year, making significant steps in our transformation. Our recent acquisition of Beijing OrionStar, an AI service provider, was an important move. It gave us a skilled sales team, strong tie-ups with business customers, and end-to-end capabilities for LLMs, including model training, fire training, developing LLS-based apps, and enhancing service robots, a new attachment for interacting with end users and customers in the AI era. With OrionStar, we are now focusing on making customer enterprise apps with LLMs and introducing LLM powered robot for specific business needs. We see two main reasons for this focus. First, market opportunity. Unlike competitive 2C market, enterprises are increasingly choosing LLM-based apps on private cloud due to data security concerns. However, they face challenges in developing paired apps and presenting a substantial opportunities in China's enterprise sector. Second, [Technical Difficulty] bring together Cheetah and OrionStar allow us to combine our app enterprise with AI skills, better converting the market opportunities by selling robots to business, we can even find new ways to use LLMs to improve efficiency. We are using product driving approach to enhance our LLM capabilities. This is why we focus on the 10B parameters LMS segments and avoid large upfront investment in GPUs. We believe that a trillion parameters LLMs is necessary. And the enterprise can deploy and use 10B LLMs on private clouds at lower cost. Over the past few months we changed [14D] (ph) parameters foundation models from scratch, which has been approved by authorities for large-scale rollout and ranks among the top of various lists. Additionally, we are fighting nearly all leading open source foundation models to offer more options for our customers, all without significantly increasing costs. Furthermore, we have seen positive developments by integrating LLM based apps into our service robot. In particular, our delivery robot can now interact better with users leading to increased demand, especially in Japan and South Korea. Currently, our overseas revenue has surpassed domestic revenues and continues to grow steadily. With LLMs, we believe the features of our service robot will expand even further. I would also like to highlight how we assist our customers in using LLM-based apps efficiently. For example, we helped Chengdu University develop an LLM-based QA feature for its apps, improving user experience. We also developed LLM powered customer service features for another customer product including WeChat mini programs, apps and our service robot. This service is now available in [indiscernible] helping local residents apply for housing funds. We are also working with enterprises in China's franchise industry to improve management efficiently with LLM-based apps. In the early stages of LLM-based apps development, we closely work with our customers to understand their needs. And 35 years -- areas for improvement with LLMs. Find the most appropriate LMS [indiscernible] develop customer apps. This process help us standardize some LLM based apps and capabilities, particularly in customer service, enterprise management and training, which we can replicate to more customers. As a result, we are monitoring customer feedback and certification. Additionally, all the applications can be incorporated into our service robots. Our long-term business model in LMLs era will involve selling robots and offering valued added service. As we focus on building LLM-based apps for enterprise, we will shift our resource from our agency Internet business to AI business. This will improve the operating margin of our Internet business, which we use as a financial performance metric. In summary, LLM is once in a generation opportunities. With OrionStar and our clear strategy, we are now confident in our direction. We would like to emphasize that we don't want to set short-time revenue growth targets. But we are aggressively prioritizing our customer satisfaction and building light house projects. By doing so, we believe we will establish a new growth engine to drive sustainable long-term growth in both revenue and margins over time. All we need is a bit of patience. We thank you all dedicated employees for their hard work in making this happen. Thank you. And Thomas?

Thomas Ren

谢谢，[Fuzong] (ph)。各位电话会议参与者，大家好。请注意，除非另有说明，所有金额均以人民币计。今天我将讨论两个主题。首先，我们持续投资于大语言模型（LLMs），导致本季度运营亏损扩大，但总收入已恢复增长。其次，我们健康的资产负债表。首先，我们正在投资LLMs。我们的目标是帮助企业快速开发基于LLM的新应用。正如Fuzong在演讲中提到的，我们收购OrionStar使得服务机器人成为AI及其他业务板块的重要收入贡献者。2024年第一季度，AI及其他业务收入同比增长62%，环比增长36%，达到8100万元人民币，占同期总收入的43%。受北京OrionStar贡献的推动，我们的总收入同比增长12%，环比增长14%，达到1.9亿元人民币。此次收购还使得猎豹和OrionStar的两个团队能够更高效地合作，更好地把握LLMs领域的机遇，因为我们帮助中国企业开发基于LLM的应用以提高生产力。我们预计这将随着时间的推移带来收入的实质性增长。此外，LLMs使我们能够改进服务机器人提供的产品体验，现在它们更能回答用户的各种询问。这一增强加强了我们的竞争力，并应随着时间的推移推动服务机器人的销售。2024年第一季度，我们的非GAAP总成本和费用同比增长21%，环比增长19%。本季度非GAAP运营亏损为6600万元人民币，高于去年同期的4200万元人民币和上一季度的4900万元人民币。这主要是由于前述对LLM的投资。通过北京橙星，我们获得了许多研发人才和2B销售人员，这对于我们把握该领域的机遇非常重要。截至2024年3月31日，我们拥有约860名员工，高于一年前的约720名。我们还在为模型训练和[听不清]采购GPU。排除前述LLM投资的影响，我们的成本和费用以及利润率保持稳定。例如，排除股权激励费用，我们互联网业务的运营利润率为7.9%，高于去年同期的3.1%。随着我们继续优化产品组合并淘汰未能解决用户痛点的产品，我们将继续采用这种方法。同时，我们将继续投资于人才，包括专门从事LLMs的研发人员以及销售人员，以帮助我们抓住LLM机遇，为猎豹打造新的增长引擎。我们的投资将得到我们强劲现金储备的支持。同时，我们将继续提高互联网业务的运营利润。其次，猎豹移动拥有健康的资产负债表。截至2024年3月31日，我们拥有约2.5亿美元的现金及现金等价物和短期投资。此外，我们拥有约1.3亿美元的长期投资，其中包括对几家知名实体的持股，例如[听不清]。最后，[听不清]是可比中国公司在美国资本市场的惯例。我们决定不再提供未来的收入指引。谢谢。

Thomas Ren

Thank you, [Fuzong] (ph). Hello, everyone on the call. Please note that unless stated otherwise, all money amounts are in RMB terms. Today, I am going to talk about two topics. First, our continued investment in large language models, or LLMs, resulting in a widened operating loss for the quarter, while total revenue has resumed its increase. Second, our healthy balance sheet. First, we are investing in LLMs. We aim to help enterprises quickly develop LLM-based new apps. As Fuzong mentioned in his speech, our acquisition of OrionStar has allowed service robots to become a key revenue contributor to the segment of AI and others. In Q1 of 2024, revenues from AI and others increased by 62% year-over-year and 36% quarter-over-quarter to RMB81 million, accounting for 43% of total revenue in the same period. Driven by contributions from Beijing OrionStar, our total revenue increased by 12% year-over-year and 14% quarter-over-quarter to RMB190 million. This acquisition also allows the two teams from Cheetah and OrionStar to work more efficiently together to better capture the opportunity in LLMs, as we help Chinese enterprises develop apps on LLMs to boost productivity. We expect this will lead to a substantial growth in revenue over time. In addition, LLMs are enabling us to improve the product experience provided by our service robots, which are now more capable of answering users' different inquiries. This enhancement has strengthened our competitiveness and should drive the sale of our service robots over time. In Q1 of 2024, our total non-GAAP cost and expenses increased 21% year-over-year and 19% quarter-over-quarter. And non-GAAP operating loss was RMB66 million in the quarter, up from RMB42 million in the same period last year and RMB49 million in the previous quarter. This is primarily due to the investments in LLM as mentioned earlier. Through Beijing Orange Star, we acquired many R&D talents and 2B sales personnel, which are very important for us to capitalize on the opportunity in this sector. As of March 31, 2024, we had about 860 employees, up from about 720 a year ago. We are also ranking GPUs for model training and [indiscernible]. Excluding the impact of the aforementioned investment in LLMs, our cost and expenses as well as our margins remain stable. For example, excluding SBC, our operating profit for the internet business was 7.9% in the quarter, up from 3.1% in the same quarter last year. As we continue to reveal our product portfolio and remove products that did not address user pain points, we will continue this approach moving forward. At the same time, we will continue to invest in talent, both in R&D, specialize in LLMs, and to be sales personnel to help us seize the LLM opportunity to build a new growth engine for Cheetah. Our investments will be backed by our strong cash reserves. At the same time, we will continue to increase our operating profit for the internet business. Secondly, Cheetah Mobile has a healthy balance sheet. As of March 31, 2024 we had cash and cash equivalents and short-term investments of about US$250 million. In addition, we had about US$130 million of long-term investments, which include several holdings in well-known entities, such as [indiscernible]. Lastly, [indiscernible] is the practice of comparable China-based companies listed in the US capital market. We have decided not to provide revenue guidance going forward. Thank you.

Helen Zhu

各位，在今天的电话会议中，管理层将用中文回答问题。AI助手将在单独一行将管理层评论翻译成英文。请注意，翻译仅为方便起见。如有任何差异，以管理层的中文陈述为准。如果您无法听到中文——英文翻译，我们将在七个工作日内于投资者关系网站上提供英文文字记录。非常感谢。接线员，现在请开始提问。谢谢。

Operator

我们现在开始问答环节。[接线员指示] 今天的第一个问题来自摩根大通的Nancy Lu。请提问。

Nancy Lu

[外语]

Sheng Fu

[外语]

Helen Zhu

接线员，请转到第二个问题。谢谢。

Operator

下一个问题来自Jefferies的Thomas Chong。请提问。

Thomas Chong

[外语]

Sheng Fu

[外语]

Helen Zhu

接线员，请转到下一个问题。谢谢。

Operator

下一个问题来自花旗银行的[听不清]。请提问。

Unidentified Analyst

[外语]

Sheng Fu

[外语]

Helen Zhu

接线员，请转到下一个问题。

Operator

下一个问题来自美国银行的Miranda Zhuang。请开始提问。Miranda，您的线路已接通，您可以提问了。目前我们似乎无法与Miranda取得联系。那么下一个问题来自TS Securities的[Karen Kong]（音译）。请开始提问。

Unidentified Analyst

[外语]

Sheng Fu

[外语]

Helen Zhu

好的。接线员，请转到下一个问题。

Operator

下一个问题来自美国银行的Miranda Zhuang。请开始提问。

Miranda Zhuang

[外语]

Sheng Fu

[外语]

Helen Zhu

请继续下一个问题。谢谢。

Operator

下一个问题来自[indiscernible]的[Zhai Lulu]。请提问。

Unidentified Analyst

[外语]

Sheng Fu

[外语]

Helen Zhu

请继续下一个问题，接线员。

Operator

下一个问题来自Bernstein的[indiscernible]。请提问。

Unidentified Analyst

[外语]

Sheng Fu

[外语]

Helen Zhu

接线员，请继续下一个问题。谢谢。

Operator

下一个问题来自汇丰银行的Richie Sun。请提问。

Ritchie Sun

[外语]

Sheng Fu

[外语]

Helen Zhu

谢谢。接线员，请转到下一个问题。

Operator

下一个问题来自瑞穗证券的Wei Fang。请提问。

Wei Fang

[外语]

Sheng Fu

[外语]

Wei Fang

好的。谢谢。

Helen Zhu

接线员，我们没有更多问题了。现在我们将结束本次电话会议。

Operator

目前没有更多问题。现在我将把电话交回给主持人进行结束发言。

Helen Zhu

谢谢接线员，也感谢大家参加我们的电话会议。

Sheng Fu

谢谢。

Thomas Ren

谢谢大家。

Operator

会议现在结束。感谢您参加今天的演示。您现在可以断开连接了。