Baidu Inc

NASDAQ:BIDU

Earnings Call Analysis

Baidu's AI Focus Drives Q1 Growth

In the first quarter of 2024, Baidu's core revenue grew 4% year-over-year to RMB 23.8 billion, with a non-GAAP operating margin improving to 23.5%. Revenue from Baidu AI Cloud surged by 12%, contributing significantly to overall growth. The company continues its transformation into an AI-first business, with its ERNIE model enhancing ad revenue and driving new AI applications. Although Baidu's mobile business faces short-term challenges, the firm anticipates recovery as AI adoption increases. Additionally, Baidu's Apollo Go robotaxi service is slated to break even in Wuhan soon. Despite macroeconomic headwinds, Baidu remains confident in AI's long-term revenue and profit potential.

Strong Revenue Growth Driven by AI Innovations

In the first quarter of 2024, Baidu's core total revenue rose by 4% year-over-year to RMB 23.8 billion. This performance was bolstered by the accelerating growth in Baidu AI Cloud, which increased by 12% year-over-year. The company's focus on AI, particularly its Gen AI initiatives, played a pivotal role in driving these results. Baidu's CEO, Robin Li, emphasized the company's transformation from an Internet-centric to an AI-first business, highlighting the importance of their ERNIE models in both consumer and enterprise applications.

Financial Metrics Highlight Operational Efficiency

Baidu reported a net income attributable to Baidu Core of RMB 5.2 billion. Non-GAAP net income stood at RMB 7 billion, translating to non-GAAP diluted earnings per ADS of RMB 19.91. The non-GAAP operating margin for Baidu Core improved to 23.5%. This indicates that the company has managed to enhance its operational efficiency, despite challenges in the broader macroeconomic environment.

AI Cloud and ERNIE Models at the Forefront

AI Cloud revenue reached RMB 4.7 billion, driven mainly by Gen AI and foundation models, contributing 6.9% of total AI Cloud revenue. The daily API calls handled by ERNIE increased significantly, reaching about 200 million in April from around 50 million in December last year. Baidu’s innovative 4-layer AI architecture has been crucial in improving efficiency and reducing costs, making ERNIE models more accessible and affordable. The introduction of Agent Builder allows for the easy creation of AI agents, further expanding the application of Baidu's AI technology across various sectors.

Strategic Focus on Autonomous Driving with Apollo Go

Baidu's Apollo Go, the largest autonomous ride-hailing service globally, offered approximately 826,000 rides in the first quarter, marking a 25% increase year-over-year. The company aims to achieve operational breakeven in key regions such as Wuhan. Baidu plans to expand its fully driverless fleet in Wuhan to 1,000 vehicles by year-end, which is expected to drive efficiency and cost reductions. The use of the new RT6 robotaxi is projected to significantly lower hardware costs, further aiding in profitability goals.

Challenges and Opportunities in Online Marketing amid Macroeconomic Headwinds

Baidu's online marketing revenue grew by 3% year-over-year. However, the company faces challenges due to a weak macroeconomic environment, particularly in the real estate and SME sectors. Despite these challenges, AI-driven improvements in advertising technology, such as ERNIE, have begun to enhance ad monetization rates. Incremental AI-related advertising revenue is expected to continue growing, helping to offset broader macroeconomic weaknesses.

Investment in Long-Term Growth

Baidu remains focused on long-term growth opportunities in Gen AI and AI Cloud. The company is strategically managing costs and streamlining operations to maintain profitability. Baidu's commitment to AI innovation is underscored by significant investments in GPU clusters and other AI infrastructure. As the adoption of ERNIE and other AI technologies expands, Baidu anticipates continuous revenue growth and improved efficiency across its business units.

Commitment to Shareholder Returns

Baidu has consistently repurchased shares, allocating 37% of free cash flow to this effort. The total number of shares outstanding began to decrease this quarter, reflecting the company’s strategy to prevent dilution and enhance shareholder value. Baidu plans to continue its share buyback program while remaining flexible to invest in high-growth opportunities within the AI domain.

Earnings Call Transcript 2024-Q1

[Operator]

Hello, and thank you for standing by for Baidu's First Quarter 2024 Earnings Conference Call. [Operator Instructions] Today's conference is being recorded. If you have any objection, you may disconnect at this time.

I would now like to turn the meeting over to your host for the conference, Juan Lin, Baidu's Director of Investor Relations.

[Juan Lin, executive]

Hello, everyone, and welcome to Baidu's First Quarter 2024 Earnings Conference Call. Baidu's earnings release was distributed earlier today, and you can find a copy on our IR website as well as on newswire services. On the call today, we have Robin Li, our Co-Founder and CEO; Rong Luo, our CFO; and Dou Shen, our EVP in charge of Baidu AI Cloud Group ACG.

After our prepared remarks, we will hold a Q&A session. Please note that the discussion today will contain forward-looking statements made under the safe harbor provisions of the U.S. Credit Securities Litigation Reform Act of 1995. Forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from our current expectations. For detailed discussions of these risks and uncertainties, please refer to our latest annual report and other documents filed with the SEC and Hong Kong Stock Exchange.

Baidu does not undertake any obligation to update any forward-looking statements, except as required under optical. Our earnings press release and this call include discussions of certain unaudited non-GAAP financial measures. Our press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and is available on our IR side at ir.baidu.com.

As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available on the website.

I will now turn the call over to our CEO, Robin.

[Yanhong Li, executive]

Hello, everyone. Our business continued to grow in the first quarter. Baidu's core total revenue increased by 4% year-over-year to RMB 23.8 billion, and the non-GAAP operating margin reached 23.5% and an improvement from a year ago. In particular, revenue growth from Baidu AI cloud accelerated to 12% year-over-year in the quarter while continuing to deliver operating profit on a non-GAAP basis. 2024 is the second year of our March on the Gen AI path. As we solidify our leadership position in foundation models, we are transforming the company from an Internet-centric business to an AI-first business. . Given that ERNIE is the most powerful in China, we are aggressively pushing the envelope for both our 2C business and 2B business to adopt earnings to provide better user experience. To increase advertiser ROI to enable developers to write agents and applications to let customers enjoy more effective and more efficient models. While we operate our legacy business in a challenging environment and experienced lower revenue growth in the near term, we remain confident that AI will bring us sustained growth in revenue and profit in the long run. We expect our [ cloud bins ] to accelerate and the loss of our robotaxi business to narrow for the rest of the year.

We expect mobile business to be soft in the near term and start to recover when Gen AI becomes the new core of our existing products next year. Looking beyond the near term, Gen AI and foundation models will bring us tremendous opportunities, offering a new innovation cycle. Enterprise and individual developers have swiftly transitioned from the fear of missing out on this opportunity to leveraging foundation models like ERNIE to build AI applications. Baidu is well prepared to benefit greatly from this technology transformation. We believe one of the most important long-term opportunities is model influencing which will be a key growth driver for our AI 12 revenue in the future.

In April, ERNIE handled about 200 million API calls daily, a significant jump from around 50 million in December last year. This considerable growth indicates the increasing adoption of ERNIE and points to strong future revenue potential from model inferencing. To accelerate the adoption of ERNIE, we are building a vibrant and healthy ecosystem around it. We believe ERNIE ecosystem well over time, contain millions of applications, especially agents developed by a diverse community of enterprise and individual developers across various industries meeting a wide range of needs in people's everyday life in work.

Our large user base in mobile and desktop will enable us to distribute these agents and apps to whoever needs it whenever appropriate. The anchor of this ecosystem is the ERNIE family of models, including our flagship models, ERNIE 3.5 and ERNIE 4.0. As well as the lightweight models we introduced in Q1. Throughout the quarter, we continued improving ERNIE's efficiency leveraging our unique proprietary 4-layer AI architecture and our strong ability in end-to-end optimization. For example, ERNIE has increased its trading efficiency to 5.1x and its inference cost is only about 1% compared to the March 2023 version. To make ERNIE increasingly accessible and affordable, we now offer 3 sets of tools on our mass platform.

Last quarter, we introduced an app builder and model builder for enterprise and individual developers to develop apps and build models. In April, we took a step further by introducing Agent Builder, a platform encompassing tools for easily creating AI agents. This is because we envision AI agent will become one of the most important forms of applications powered by Gen AI and foundation model. With the ability to use natural language as the programming language, developers will be able to build AI agents without the need to write a single line of code. Currently, new ERNIE agents are created on our platform every day, and together, they distributed millions of times per day, serving a wide range of verticals including education, legal, B2B, travel and more.

All these initiatives drive from our extensive experience and insights in building and running ERNIE, as well as developing AI native applications. We believe that ERNIE's true value will only be realized when numerous applications built on top of it are widely used by users and customers. I'm pleased to note that ERNIE is expanding its influence across smart devices through API. Last quarter, we proudly announced partnerships with renowned smartphone brands such as Samsung China and Honor, assisting them in enhancing their native app experiences using ERNIE. This quarter, we are excited to extend our collaboration with more leading smartphone makers such as Oppo, Vivo and Xiaomi, who leveraged ERNIE APIs to elevate user experience.

Moreover, our reach now extends beyond smartphones to include PCs and electric vehicles. ERNIE APIs are now utilized by Lenovo, top PC brand to empower its AI assistant in the default browser of its PCs. [ Neil ], China's leading smart EV manufacturer began using the ERNIE API to enhance the incoming experiences for its vehicles. This broadening of our partnerships into [ smart ] devices opens up ample opportunities for large-scale user adoption, paving the way for ERNIE enabled applications to become the entry point into the world of generated AI. In addition to the brands I just mentioned, we have also acquired many notable new customers such as Trip.com, [ Soto ], [indiscernible] and Singapore Tourism Board.

Another long-term opportunity is in our consumer-facing business. We have been reconstructing all of our consumer-facing products. Our goal is to build our proprietary AI native applications, potentially killer apps for the ERNIE ecosystem. By doing so, we should be able to generate new growth opportunities. For example, after rebuilding with Gen AI and [ LLM Baidu ], our one-stop shop for document creation experienced double-digit year-over-year increase in paying users in the first quarter. Penetration of earnings for Baidu search and feed took longer than expected because the user base is in the order of hundreds of millions, and these cases are generally very sensitive to cost and response time.

We need a wide range of ERNIE models in different sizes optimized for different scenarios for best price performance ratio. After trial and error for a few quarters, we are firming up our strategy. Going forward, we plan to accelerate the launch and adoption of new product features such as multimodel generating search results, multi-round interaction in search and more recently, distribution of ERNIE agents. We are at the forefront globally of this unique technological change, and we are confident in our abilities to innovate. By definition, we are operating in uncharted territory. As always, we want -- we want to be flexible to make timely adjustments with evolving consumer needs and how users incorporate new product features in their day-to-day life.

Now let me review the key highlights for each business for the first quarter. In the first quarter, AI cloud revenue reached RMB 4.7 billion, up 12% year-over-year and continued to generate operating profit on a non-GAAP basis. The revenue growth was mainly driven by Gen AI and foundation models. In the first quarter, such revenue accounted for 6.9% of total AI cloud revenue. Currently, the majority of this revenue is from model training, but revenue from model inferencing has been growing quickly. We believe revenue from Gen AI and foundation will continue to rise as customer adoption improves. For instance, within our internal cloud revenue by [indiscernible] other business groups, such as mobile ecosystem groups and intelligent driving group increasingly leveraging the power of ERNIE.

As a result, 15% of their payments to the AI Cloud Group are allocated to Gen AI and foundation model. Enterprises to Baidu AI cloud to train and host their models because they believe we have the most powerful and efficient AI infrastructure for model training and inferencing in China. Compared to our peers, we help enterprises to train model all sizes on our AI cloud while also reducing model inferencing cost. This is primarily a [ trigributable ] to 2 reasons. Number one, our self-developed 4-layer AI architecture has allowed us to innovate and optimize at each layer, enabling continuous efficiency. And number two, we have superior capabilities and insights in TPU cluster management, leveraging our technical expertise.

We can now integrate GPUs from various vendors into a unified computing cluster to [ Twin ] and LLS. Our platform has demonstrated very high efficiency with this setup on a GPU cluster that is [ post ] of [ entree ] even thousands of GPUs. This is an important breakthrough because of the limited availability of imported GPUs. Another growth driver for AI Cloud is cross-selling of our CPU cloud services to our GPU cloud customers. With the high recognition of our GPU cloud among existing and new customers. We have seen customers increasingly switch more and more of their CPU cloud usage to Baidu. Earlier on the mass side, we took many initiatives to make the ERNIE family of models increasingly affordable and efficient than open-sourced models.

So some highlights for this quarter. We have expanded and enhanced our ERNIE model portfolio, offering a total of 3 lightweight LLM and 2 test-specific LLM model builder. This model helps enterprises and professional developers, balanced model performance with cost in ERNIE to reach a broader audience for model development. In addition, our mixture of experts or MOE approach can [indiscernible] a user query into distinct tasks, assigning the most suitable models to handle each task and use ERNIE 3.5 or 4.0 only for the most complex tasks. This approach allows for faster responses and lower inferencing cost while maintaining similar performance level to using more models.

Last quarter, we introduced App Builder to develop [indiscernible] throughout the quarter, we continued in reaching and refining the tools for App Builder enabling developers to easily create AI [indiscernible] in just 3 steps on our platform. With the launch of Agent Builder in April, anyone can create an AI agent with just a few sentences on Baidu. Overall, we remain confident in the strong for our AI cloud revenue, and we aim to continue generating operating profit on a non-GAAP basis.

Mobile ecosystem has continued to deliver healthy margins and strong free cash flow. In the first quarter, our online marketing revenue grew by 3% year-over-year. Revenue growth was impacted by a challenging macro environment. At the same time, we have been pushing hard to transform the user experience from a traditional mobile product to generated AI experience. This transition is ongoing and monetization has not yet started. We all need to leverage ERNIE to reconstruct our monetization system for better conversion and efficiency gain. During the quarter, we further enhanced our ad targeting capabilities and scaled up real-time ad generation. These efforts resulted in an improvement in conversion and generated incremental revenue. ERNIE agents stand for a long-term opportunity for [indiscernible] upgrade to.

Recently, we have seen not only brand advertisers, but also SMEs gradually adopting earning agents. We have designed this agent for SMEs as virtual storefront and service desk, serving consumers around the clock. We believe that the use of agents can improve and ease sell-through rate, enhance their productivity and expand their reach among users. This will be an important step for us to transform our traditional CPC model to a significantly more efficient CPS model. And meanwhile, enhancing user experience on Baidu.

Going forward, I believe greater opportunities will arise from AI native apps, particularly for Gen AI [indiscernible]. Gen AI complements traditional search, expanding the total addressable market. Since Q2 last year, we have been reconstructing Baidu Search with ERNIE. Now more and more search results are generated by ERNIE in a growing variety of formats like text, image, third-party links, point of interest and [indiscernible]. These results are [ rally ] produced in real time to directly address users' questions and problems. By doing so, we have improved and will continue to enhance the search experience which is crucial for increasing the usage of Baidu Search. While user feedback on this product and feature renovations, has been encouraging. It is important to note that we are still in the early stages of reconstructing Baidu Search with ERNIE.

This process will likely take time given that Baidu Search has a history over 20 years and user behavior will evolve gradually. Overall, I believe that search will be one most likely killer app in the Gen AI era and we are on the right trajectory to capitalize on this potential. I mentioned ERNIE agents as an important opportunity for monetization. With newly introduced agent builder, creators, publishers and service providers will find it increasingly easy to build on Baidu. It is key to enhancing Baidu's content offerings and ultimately provide an AI native user experience on our platform.

Moving on to Intelligent Driving. We believe Apollo Go stands as the largest autonomous ride heating service provider globally, measured by the right provided to the public. In the first quarter, Apollo Go offered about 826,000 rights to the public, marking a 25% year-over-year increase. In April, the total number of ride surpassed 6 million. We are continuing to move forward -- move towards achieving unit economics breakeven for Apollo Go. To make this happen, our strategy is to reach breakeven in key regions and then replicate the success in other regions. To reach the regional breakeven point, we are focusing on scaling up a fully [ driverless ] ride heating service and enhance the utilization of each field. Wuhan, Apollo Go's largest regional operations is progressing towards this goal. In Wuhan, Apollo Go is gradually becoming an integral part of the city's transportation network.

Apollo Go more than doubled its operational area from a quarter ago, serving a population of over 7 million and achieving the remarkable milestone of crossing [ Yandi ] River with fully driverless vehicles as part of its expansion. Moreover, our vehicles started to operate 24/7 in Wuhan in early March, further expanding Apollo Go's reach and improving the vehicle utilization. All these progresses have led to the rapid growth of fully [indiscernible]. In Q1, the rights provided by fully driverless vehicles accounted for over 55% of the total ride in Wuhan, which is up from 45% in the fourth quarter last year.

The figure continues to rise, exceeding 70% in April, with expectations of sustained rapid growth ahead and reaching 100% in the coming quarters. Looking ahead, we plan to deploy RT6, our generation robotaxi in our Wuhan Apollo Go operation this year which will significantly reduce hardware depreciation costs. With the scaling of driverless operations and continuous improvement of cost structure, we believe Apollo Go will achieve operational UE breakeven in Wuhan in the near future. As Apollo Go continues to progress, we will closely monitor efficiency and persist in optimizing the operation of our overall intelligent driving business.

On Auto Solutions, our Apollo self-driving for ASD technology continue to evolve. I mentioned in our last earnings call that Apollo is a global pioneer in the use of visual foundation models in autonomous driving. Now our state-of-the-art autonomous driving solution solely reliant on vision is made available to OEMs. ASP can effectively navigate complex urban environments across over 100 cities in China, with plans to expand in to hundreds of cities in the coming months. This allows us to make advanced autonomous driving attainable across a broad spectrum of passenger vehicles. From high-end to economy models priced as low as RMB [ 150,000 ] and it serves as another proof of our technology leadership.

With that, let me turn the call over to Rong to go through the financial results.

[Rong Luo, executive]

Thank you, Robin. Now let me walk through the details of our first quarter financial results. Total revenues were RMB 31.5 billion, increasing 1% year-over-year. Revenue from Baidu [ Core ] was RMB 23.8 billion, increasing 4% year-over-year. Baidu [indiscernible] Online marketing revenue was RMB 17.7 billion, increasing 3% year-over-year. Baidu [indiscernible] online marketing revenue was RMB 6.8 billion, up 6% year-over-year, mainly driven by the AI Cloud business. Revenue for [indiscernible] was RMB 7.9 billion, decreasing 5% year-over-year. Cost of revenue was RMB 15.3 billion, increasing 1% year-over-year, primarily due to an increase in traffic acquisition costs and costs related to AI Cloud business partially offset by the decrease in content costs.

Operating expenses were RMB 10.7 billion, decreasing 2% year-over-year, primarily due to a decrease in personnel-related expenses and other R&D expenditures, partially offset by the increase in solar depreciation expenses and server custody fees, which support [indiscernible] research and development tools. Baidu costs operating expenses were RMB 9.4 billion, decreasing 1% year-over-year. Baidu Core SG&A expenses were RMB 4.5 billion, decreasing 1% year-over-year. SG&A accounting for 19%, 1-9 of Baidu costs revenue in this quarter compared to 20% in the same period last year. Baidu called R&D expenses were RMB 4.9 billion, decreasing 1% year-over-year. R&D accounting for 21% of Baidu costs revenue in this quarter compared to 22% in the same period last year.

Operating income was RMB 5.5 billion. Value cost operating income was 4.5 billion. And Baidu cost operating margin was 19%, 1-9 and non-GAAP operating income was RMB 6.7 billion. Non-GAAP Baidu Core operating income was RMB 5.6 billion, and non-GAAP Baidu Core operating margin was 23.5%. Total other income net was [indiscernible] billion, decreasing 52% year-over-year, primarily due to a decrease in fair value gain from long-term investments, partially offset by the increase in net foreign exchange gain. Income tax expenses was RMB 883 million compared to RMB 1.2 billion in the same period last year. Net income attributable to Baidu was RMB 5.4 billion, and diluted earnings per ADS were RMB 14.9. Net income attributable to Baidu Core was RMB 5.2 billion, and net margin for Baidu Core was [indiscernible]. Non-GAAP net income attributable to Baidu was RMB 7 billion.

Non-GAAP diluted earnings per ADS were RMB 19.91. Non-GAAP net income attributable to Baidu Core was RMB 6.6 billion, and non-GAAP net margin for Baidu Core was 28%. As of March 31, 2024, cash [ credence ] restricted cash and short-term investments were RMB 191.8 billion in cash, cash equivalents, restricted cash and short investments, excluding [ IT ], were RMB 185.8 billion. Free cash flow was RMB 4.2 billion. Free cash flow, excluding IT, was RMB 3.3 billion. Finally, Baidu Core had approximately 34,000 employees as of [ 31, 2024 ]. With that, operator, let's now open the call to questions.

[Operator]

[Operator Instructions] Your first question comes from Alicia Yap with Citigroup.

[Alicis a Yap, analyst]

So I wanted to ask, would you be able to quantify AI technology been helping Baidu to improve ad monetization rate. Can management share some feedback on those advertisers of who have adopted the system? In what kind of areas do they see the largest improvement? And are there any areas that can be further enhanced?

[Yanhong Li, executive]

Alicia, this is Robin. As you know, our monetization system was the first to benefit from Gen AI, generating several hundred million RMB per quarter in incremental revenue. Since the second half of last year, we have been utilizing ERNIE to upgrade our monetization system. It has seen various aspects of ad technology. This includes improving [ in ] capabilities, refining the auction system, automating creative generation and add strategy formation for our advertisers. Advertisers have seen better conversion and more sales leads. This improvement has motivated advertisers to increase their spending with Baidu. So in the first quarter, AI-related incremental advertising revenue grow on a quarter-over-quarter basis, and we expect this trend to continue. The incremental revenue has helped us mitigate the broader macro weakness and also brought us some time to reconstruct our user product with ERNIE.

As I emphasized in my opening remarks, we believe ERNIE offers a significant long-term [indiscernible] for our online marketing business. Agents function as virtual or domains, advertisers can establish their online presence and interact with potential customers using natural language through multiround conversations. The introduction of Agent Builder, advertisers can easily create customized ERNIE agents. When advertisers press their intentions to this agent, they can more effectively achieve their goals, whether it's helping potential customers understand their products or improving customer service quality. Agents can also help enrich our content offering and improve user experience on Baidu.

While still in with the ERNIE stage, ERNIE agents have helped some advertisers achieve better ROIs. For example, we have customer in online education. They used Agent Builder to create its AI agent, injecting it with key insights like product introduction and subject matter expertise, will continually providing feedback for refinement. This agent has significantly enhanced the company's online customer service by offering around-the-clock high-quality consultations. The adoption of ERNIE agent lead to a 20 print increase in ad conversion rate for this online education company. I think this is just the beginning. We believe agent will be a major form of content and services in the new AI era, we will continue to improve the capabilities of ERNIE agent.

Agents will not only elevate user experience, both conversion and ROI for advertisers, but also over time, foster increase in transactions directly generated on our platform. This shift should help us to transform our traditional CPC model into a more efficient CPS model.

[Operator]

Your next question comes from Gary Yu with Morgan Stanley.

[Gary Yu, analyst]

I have a question regarding the AI Cloud business. How has the price cut initiated by some of your key companies affected by AI Cloud business? And how should we think about the cloud revenue profitability as competition hits up? And also, how should we -- what should be the sustainable level of cloud growth outlook going forward?

[Dou Shen, executive]

Yes, Gary, this is Dou. As we have already mentioned, Gen AI and foundation models or transforming the cloud industry from a general purpose computing to AI computing. So this shift is reshipping the competitive landscape within the cloud industry presenting us with the valuable opportunity to establish ourselves as a leader in AI cloud. So we believe we offered China's most efficient AI infrastructure and the most advanced mass platform for our model training and inference. As a result, more and more enterprises are choosing us for our model training, fine-tuning and AI native app development on our public cloud. This increase in demand has significantly boosted our AI cloud revenue.

Actually, since the second quarter -- the second half of last year, so our AI cloud revenue growth has started to accelerate from a year-over-year decline in the third quarter to an 11% increase in the fourth quarter last year, and then further accelerated to 12% in the first quarter of this year. So the revenue acceleration was supported by 2 main factors. The incremental revenue directly generated by Gen AI and foundation models and also the new opportunities we brought to our legacy cloud business. So as Robin just mentioned, in the first quarter of this year, revenue from Gen AI and foundation models account for 6.9% of our AI Cloud revenue. And then our traditional CPU cloud businesses or capitalizing on the opportunities presented by Gen AI and foundation models, both factors were important growth drivers of our AI Cloud.

On a separate note, while smart transportation business remained subdued, its impact on overall AI Cloud business in Q1 was substantially smaller than the previous quarters. So overall, we expect our AI Cloud to continue benefiting from the make trend, maintaining strong revenue growth momentum in the upcoming quarters. On the profit side, Baidu AI Cloud continued to generate GAAP operating profit, as we have seen in previous quarters. We are committed to a sustainable and health revenue growth. During the quarter, we maintained our focus on achieving high-quality revenue growth by scaling down low-margin business. Regarding the business of the Gen AI and foundation models, the market is still at a very early stage. So our focus remains on educating the market and broadening our footprint across more enterprises.

Looking into the long run, so we expect the normalized margin for Gen AI and foundation models related business to improve further and to be higher than our traditional cloud business. Regarding the change of pricing policies of some competitors you just mentioned, right, it is actually pretty common for our cloud vendors to address their pricing for certain products. Now this is a trend we have observed multi times in the past. Given that our cloud offerings has expanded beyond the traditional CPU cloud to a high-value AI products and services so the industry changes on CPU cloud pricing has a minimum impact on the development of our AI Cloud.

Actually, for our cloud platform services by leveraging our unique proprietary 4-layer AI architecture and our strong ability in the end-to-end optimization, we have lowered ERNIE's inference cost to only 1% of the [ vary ] in March last year. This May, ERNIE handles about 200 million API calls or approximately 250 billion tokens daily. We are confident that the ERNIE's expanding adoption will continue to enhance its performance, boosting efficiency and then further reduce costs. It's also important to evaluate present performance ratio for different models at different workloads rather than just focusing on some superficial prices. So we believe our [indiscernible] AI infrastructure and advanced mass platform delivers the best value to our customers.

Looking forward, leveraging our strong AI capabilities, we aim to continuously attract new customers and encouraging existing ones to increase their spending on Baidu AI Cloud. At the same time, we aim to consistently generate positive non-GAAP operating profit.

[Operator]

Your next question comes from Alex Yao with JPMorgan.

[Alex Yao, analyst]

Given the chief shortage in China, help us by to maintain its commitment to delivery differentiate value while enhancing the leading advantage in [indiscernible] technology in China.

[Yanhong Li, executive]

Alex, we do think very differently in this aspect. We're taking an application-driven approach for our AI push. For example, solving all the high school mass problems using the most advanced LLM may not be the highest priority at this time. While generating convincing reasons for users to buy the right products, it's more important in a lot of applications. So with that in mind, we are taking advantage of our unique 4-layer AI tech stack to optimize the cost and performance of ERNIE models. And we make sure customers and developers can easily build applications using tools like Agent Builder, App Builder and Model Builder.

For the AI infrastructure layer, a key factor contributing to our high efficiency in model [ train ] and in France is our superior capability in GPU cluster management. We have recently made a breakthrough by integrating GPUs from different vendors into one large-scale unified computing cluster, allowing us to use less advanced chips for highly effective model training and inference. Our deep learning framework PaddlePaddle has through continuous innovation and enhancement helped reduce the cost of model training and inferencing on a constant basis. PaddlePaddle is compatible with over 50 different chips, many domestically designed and as developer community has grown to 13 million.

With ERNIE 3.5 and ERNIE 4.0, remain to be the flagship models for sophisticated tasks. We're making ERNIE more accessible and affordable by launching lightweight LLMs introducing toolkits for mono development and app development, applying MOE approach for model inference for better performance and lower cost. With our application-driven mindset, we have used early extensively to renovate our own products, and we have gained experience and insights in training and using ERNIE as well as developing AI applications on it. We're making all these capabilities available to our customers and developers. With all these efforts, we are fostering a vibrant and healthy ecosystem around ERNIE. You can see that we are actually taking a holistic approach to developing Gen AI and LLM which is very different from some of our competitors.

Our reserve and access to the chips on the market should be sufficient for us to support millions of AI applications in the future. And in the long run, I think China will form an ecosystem of its own probably with less powerful chips but most efficient homegrown software stack. There's ample room for innovation in the application layer, model layer and framework layer. With our self developed a 4-layer AI infrastructure as well as our strong R&D team, our dedication to AI and our application-driven approach in building an ecosystem around ERNIE, I'm quite confident that by will stand as a leader in China's AI ecosystem in the long term.

[Operator]

Your next question comes from Lincoln Kong with Goldman Sachs.

[Lincoln Kong, analyst]

So my question is about the enterprising business. So what's the major drag for the advertising growth if we compare with our peers? So what are the trends we have seen for the [indiscernible] budgets and advertiser sentiment, especially into second quarter, April and May? So how should we think about the normalized advertising growth for 2024?

[Yanhong Li, executive]

Yes. Our online marketing revenue grew by 3% year-over-year in the first quarter. Well, traditional search is maturing. We are working hard to renovate the user experience with Gen AI. Right now about 11% of our search result pages are filled with generated results. These results provide more accurate, better organized and bright answers to users' questions, and in some cases, enable users to do things they could not do before. We have not started the monetization of those Gen AI results. So it will take some time for revenue to catch up. And the weak macro also contributed to the softness of our ad business. Our advertisers come from a wide range of industries with the majority being SMEs.

This takes our advertising revenue highly sensitive to the macroenvironment, particularly to the off-line economy. In the first quarter, advertiser sentiment in some verticals such as real estate, and franchising remained weak, specifically in the real estate industry, not only was ad spending from developers and agencies muted but the impact also extended to both upstream and downstream sectors. For example, energy chemicals, machinery, building materials for the upstream and home renovation furniture, this kind of downstream also constrained at spending on our platform. Also many SMEs in offline sectors need more time to recover as they have been working hard in the past few years.

As we enter the second quarter, we have not seen improvements in advertiser segment. Given the limited visibility for sentiment improvement, and paired with the tough comp in Q2, our online marketing revenue should remain fundamentally solid. But from a growth perspective, soft over the next few quarters. Beyond the near-term challenges, we expect online marketing to remain a [indiscernible] for Baidu for the foreseeable future. [indiscernible] is one of the most popular apps in the Internet age, and Baidu remains the largest search engine in China with close to 700 million MAUs. Search will likely be one of the killer apps in the age of Gen AI. Technology innovation will enable us to better engage users with developers and merchants, directly connect users' intention with most relevant product and service offering in more natural ways.

[Operator]

Your next question comes from Thomas Chong with Jefferies.

[Thomas Chong, analyst]

My question is about how much more room do we see in cost cutting. Previously, we mentioned there will be a lag between investment and AI revenue contribution. How should we look at margin trends in 2024, if you intend to expand your AI offerings?

[Rong Luo, executive]

Thomas, thank you so much for your question. I think macro challenges are still winning on our marketing businesses. But we are confident that there still will be some ways for us to do to continue optimizing the operational efficiencies. We will strangely manage our cost expense for issues [indiscernible], and we will take some further steps as necessary including we try to streamline the organization structure to enhance the agility and support strategy flexibility. And we also will relocate the resources to prioritize the key strategic areas. If we take into our businesses for mobile ecosystem, I think we can still manage the costs and expenses. So the Mobile Systems Group continue to remain a strongly profitable and cash flow positive.

For AI Cloud, as Dou just mentioned, we will continue to phase out the low-margin businesses and products. So we can continue generating the operating profit and margins on a non-GAAP basis. If we look into the longer term, the normalized margin for the Gen AI-related Cloud businesses should be higher than the legacy cloud business. For other businesses, we aim to reduce our loss than as what we talked about in the past 3 quarters, particularly our intelligent driving business with more operational efficiency gains and the OE improvements for robotaxi. And many investors ask me how our investments in ERNIE [ impairment ] margins. In fact, our investments are mainly related to CapEx for modern training and inference.

In 2023, we have made a large purchase which has arrived in batch time at different times and the different depreciation startbase. While the annualized depreciation expenses will be available in the whole year 2024, the impact on our overall cost, expenses and quarterly earnings is quite predicable and manageable. The depreciation expenses are booked under the R&D expenses for computing power use training and the cost of revenue for computing power reviews for model inference and business expansions. In the first quarter, we can see that Baidu Cost, non-GAAP R&D and the cost of revenue both increased very slightly. While non-GAAP operating margin actually we're expanding to 23.5% due to our disciplined spending on other items such as SG&A.

We believe that [indiscernible] we have in hand are sufficient to support the trends of earnings for the next 1 or 2 years. And because of the limited availability of high-performance chips in China in this year 2024, we expect our CapEx to be smaller versus last year. In conclusion, the investments in Gen AI large imaging models will have a manageable impact on the near-term margins. And with our monetization of ERNIE's already taking off, we expect that more and more revenue and profit will be generated from that kind of businesses from both -- for both mobile ecosystem and AI Cloud. Overall, we believe that high-quality growth and investment should be well balanced. For many years now, we have delivered a solid track record of the top line growth with the very resolute cost disciplines, and we intend to continue building our futures on this kind of business.

[Operator]

Your next question comes from [indiscernible] with UBS.

[Unknown Analyst]

My question is about shareholder return. So how about we think about the execution pace of current RMB 5 billion buyback program, in addition to current buyback program, should we expect other diversified approach to improve shareholder return?

[Rong Luo, executive]

Yes. Thanks so much for your questions. And I think we highly value our shareholders, and we have been making efforts to increase the shareholder returns. We have consistently repurchased our shares from the market over the past 4 years, averaging around $1 billion annually. In total, we have allocated 37% of our free cash flow towards the -- our share buyback programs. I think during this period and going forward, we will continue to buy back more shares from the market as we believe in our loan growth opportunities and we are very committed to the shareholder returns. And in addition, we have utilized our current share repurchase program to prevent any significant increase in the total outstanding shares comp aiming to reduce the potential dilution of our shareholders' economies stated in Baidu.

In the year 2023, you can see that our total number of shares outstanding was flat year-over-year compared to a 1.2% increase in the year 2022 and a 3.2% increase in the year 2021. In this quarter, the total shares outstanding began to decrease. You can see that it has been declining by 0.5% as compared to the prior quarter. We are adopting a strategy of sustainable and recurring share buyback programs from open market. And at the same time, we take into consideration opportunities ahead of us. Now we are facing a huge opportunity in Gen AI foundation models, and we have structured a concrete plan to capitalize it. So we want to have the flexibility to invest as we consider necessary and in the best interest of long-term value to the shareholders. Furthermore, we believe that the most effective way to create values for shareholders is by building the strong business fundamentals.

Our core marketing business remains steady and we believe that AI will help us to build another growth engine. Thank you so much for the question.

[Operator]

Your next question comes from [indiscernible] with BofA Securities.

[Unknown Analyst]

My question is about robotaxi. So can management share more updates on the robotaxi initiatives and the geographical coverage for this year. And I think previously, you mentioned that Apollo Go will achieve operating EE breakeven in Wuhan in near future. I want to understand what's the logic behind efforts to continue to improve the UE. What's the projected size of the vehicle fleet for this year? And how will it potentially impact the cost take?

[Yanhong Li, executive]

Sure, Marina. Let me give you some more color on the robotaxi business. In 2023, Apollo Go made significant progress in improving the regional unit economics in key cities. Let me use Wuhan, Apollo Go's largest operation to explain how we achieved that. We kicked off Apollo Go commercial operations in a bank in 2022. Since then, we've witnessed a consistent enhancement in operational UE which can be attributed to the expanding scale of driverless operation and decreasing cost per vehicle. Regarding scale expansion, our vehicle fleet has been steadily growing. Compared to 1 year ago, our fully driving speed in Wuhan, has grown straight fold reaching about 300 vehicles today. Meanwhile, both the operational area and service hours for fully [ drivetrain ] operation have been consistently expanding. Thanks to the increasing recognition of our autonomous driving technology by the local government.

The operational coverage area for fully [indiscernible] service increased by eightfold from a year ago, now covering over 7 million people in Wuhan. Apollo Go operational hours also gradually expanded from only the off-peak hours in the beginning to add in peak hours to its operation and eventually extending to 24/7 in March of this year. The steel expansion resulted in a consistent improvement of UE in terms of revenue both daily rides per vehicle and distant ride have been growing. When it comes to cost, the majority is labor cost and hardware expenditures. We have been demonstrating consistent track record of safe operations, which help us to increase the deployment of fully [indiscernible] heading operation.

In April, the proportion of fully-driverless orders rose to 70%. That's up from only 10% in August 2022 and 45% Q4 of last year. We expect this figure to reach 100% in the coming quarters, thereby enabling us to minimize the cost related to safety officers. In addition to lowering the labor cost, we are steadfast in driving down hardware costs. The mass production time line of RT6, our sixth generation robotaxi remains on track adopting a battery swapping solution, the mass production price for RT6, excluding veteran, is below USD 30,000. We will use RT6 as the primary vehicle in the future fleet expansion, and it should help to significantly reduce the hardware depreciation cost for each vehicle and further improving and bring us closer to profitability.

Looking into this quarter, we plan to expand the fully driver fleet of our Wuhan operation to 1,000 vehicles by the end of the year, more than tripling from the end of last year. Our focus remains on improving regional UE and narrow the losses for Apollo Go business. With continued improvement in operational efficiency and cost reduction, we believe Apollo Go will achieve operational UE breakeven in Wuhan first. And once that's achieved, we can scale up the operations quickly. Thank you.

[Operator]

Ladies and gentlemen, that does conclude our conference for today. Thank you for participating. You may now disconnect.