Cheetah Mobile Inc. (CMCM) Earnings Call Transcript & Summary

Good day, and welcome to the Cheetah Mobile First Quarter 2024 Earnings Conference Call. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Helen, Investor Relations for Cheetah Mobile.

Thank you, operator. Welcome to Cheetah Mobile Fourth Quarter (sic) [ First Quarter ] 2024 Earnings Conference Call. With us today our company's Chairman and CEO, Mr. Fu Sheng; and Director and CFO, Mr. Thomas Ren. Following management's prepared remarks, we will come back to Q&A section. Before we begin, I refer you to the safe harbor statement in our earnings release, which also applies to our conference call today as we will make forward-looking statements. At this time, I would now like to turn the conference call over to Chairman and CEO, Mr. Fu Sheng. Please go ahead, Fu Sheng.

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 quality 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, our AI service provider was an important move. It gave us a skilled sales team, strong hired with business customers and end-to-end capabilities for LLM, including model training by turning, developing LLM-based apps and enhancing service robots, a new attachment for interacting with end users and the customers in the AI era. With OrionStar, we are now focusing on making customer enterprise apps with LLM and introducing LLM-powered robot for specific business needs with the two main reasons for this focus. First, market opportunity. Unlike competitive 2C market, enterprise are increasingly choosing LLM-based apps on private cloud due to data security consents. However, they face challenges in developing apps and presenting us substantial opportunities in China's enterprise sector. Second, synergies, bringing together Cheetah and OrionStar allow us to combine our app -- our app enterprise with AI skills after capturing the market opportunities by saving robots to business, we can even find new ways to use LLMs to improve efficiency. We are using product driving approach, approach to enhance our LLM capabilities. This is why we focus on the 10b parameters, LLM segments and avoid large upfront investment in GPUs. We believe that the changing parameters LLM is unnecessary and the enterprise can deploy and use 10B LLMs on private cloud at lower cost. Over the past few months, we changed our 14B parameters foundation models from scratch, which has been approved by authorities for our large-scale rollout and ranks among the top of various lists. Additionally, we are fighting nearly all leading open resource -- open source foundation models to offer more options for our customers or without significantly increasing costs. Furthermore, we have seen positive developments by integrating LLM-based apps into our service robots. 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 continue to grow steadily. With LLMs, we believe the features of our robot -- 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 have [ Hunan ] University, developed an LLM-based QA feature for its app, improving user experience. We also developed LLM-powered customer service features for another customer products, including WeChat mini programs, apps and our service robots. This service is now available in [indiscernible], helping local residents apply for housing funds. We are also working with enterprise in China's branches the industry to improve management especially with LLM-based apps. In the early stage of LLM-based app development, we closely work with our customers to understand their needs, identify areas for improvement with LLMs, find the most appropriate edge LLM, fine tune and develop customer apps. This process help us standardize some LLM-based apps and capabilities, particularly in customer service, enterprise management and change, which we can replicate to more customers. As a result, we are monitoring customer feedback and certification. Additionally, the other applications can be incorporated into our service robots. Our long-term business model in LLM [indiscernible] will involve selling robots and offering value-added service as we focus on building LLM-based app for enterprise. We will shift our resource from our efficiency in 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 one in a generation opportunities with OrionStar, and our clear strategy, we are now confident in our direction. We would like to emphasize that we do want to set short-time revenue growth targets, but we are aggressively prioritizing our customer satisfaction and building lighthouse 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?

Thank you, Fu Sheng. Hello, everyone, on the call. Please note that unless stated otherwise, all money amounts are in RMB terms. Today, I'm going to talk about two topics: First, our continued investment in large language models or LLMs, resulting in a widen 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 our LLM-based new apps, as Fu Sheng 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 CNY 81 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 CNY 190 million. This acquisition also allows the two teams from Cheetah and OrionStar to work more efficiently together to better capture the opportunity in our LLMs as we help Chinese enterprises develop apps on our 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. Non-GAAP operating loss was CNY 66 million in the quarter, up from CNY 42 million in the same period last year and CNY 49 million in the previous quarter. This is primarily due to the investment in OrionStar as mentioned earlier. Through Beijing OrionStar, we acquired 90 R&D talents and to be 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 ramping GPUs for model training and fine-tuning. 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 review our product portfolio and remove products that did not address user pinpoints. We will continue this approach moving forward. At the same time, we will continue to invest in talent, both in R&D, stabilizing LLMs and to the sales personnel to help us size the 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 USD 250 million. In addition, we had about USD 130 million of long-term investments, which include several holdings in well-known entities such as [indiscernible] . Lastly, in line with the practice of comparable China-based companies listed in the U.S. capital market, we have decided not to provide revenue guidance going forward. Thank you.

Everyone, for today's call, management will answer questions in Chinese and an AI agent will translate management comments into English in a separate line. Please note the translation is for convenience of [indiscernible] in the case of any discrepancy management saying in Chinese as well. If you are able to see the trends in new translation, a transcript in English will be available on our IR website within 7 working days. Thank you so much. And operator, please now take questions. Thank you.

[Operator Instructions] The first question today comes from Nancy Lu with JPMorgan.

[Foreign Language]

[Foreign Language]

The next question comes from Thomas Chong with Jefferies.

[Foreign Language]

[Foreign Language]

The next question comes from Vicky Wei with Citi.

[Foreign Language]

[Foreign Language]

The next question comes from Miranda Wyn with Bank of America. It appears we are unable to connect with Miranda at this time. So the next question comes from Karen Kong with TF Securities.

[Foreign Language]

[Foreign Language]

The next question comes from [ Miranda Rein ] with Bank of America.

[Foreign Language]

[Foreign Language]

The next question comes from Jay Lulu with Vopak.

[Foreign Language]

[Foreign Language]

The next question comes from [ Dori Fan ] with Bernstein.

[Foreign Language]

[Foreign Language]

The next question comes from Richie San with HSBC.

[Foreign Language]

[Foreign Language]

The next question comes from Wei Feng with Mizuho.

[Foreign Language]

[Foreign Language]

Operator, we have no further questions, then we end the call.

There are no further questions at this time. I'd now like to hand the call back over for closing remarks.

Thank you, operator, and thank you so much for joining our conference call.

Thank you.

Thank you, everybody.

The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.