Hello, and thank you for standing by for Baidu's Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Today's conference is being recorded. If you have any objections, you may disconnect at this time. I would now like to turn the meeting over to your host for today's conference, Juan Lin, Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's Third Quarter 2025 Earnings Conference Call. Baidu's earning release was distributed earlier today, and you can find a copy on our website as well as on Newswire Services. On the call today, we have Robin Li, our Co-Founder and CEO; Julius Rong Luo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG; Dou Shen, our EVP in charge of Baidu AI Cloud Group ACG; and Henry Haijian He, our CFO. 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 our filings with SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements, except as required under applicable law. 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 website at ir.baidu.com. As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available on Baidu's IR website. I will now turn the call over to our CEO, Robin.

Hello, everyone. In Q3, Baidu Core reported total revenue of RMB 24.7 billion, AI Cloud revenue reached RMB 6.2 billion, increasing 21% year-over-year sustaining value growth momentum. Apollo Go's growth accelerated sharply. We delivered over 3 million fully driverless operational rides in Q3, representing 212% year-over-year growth, up from 148% last quarter. This quarter demonstrated how AI is driving transformative value across our business. From enterprise services to consumer-facing products to smart mobility, our AI capabilities are delivering proven tangible impact at scale. Starting with the enterprise side, where our AI Cloud business continues to scale with healthy momentum and deliver measurable business impact. In Q3, AI Cloud continued its strong growth trajectory. Within AI Cloud, the areas most central to AI achieved the fastest growth. In particular, subscription-based revenue from AI accelerator infrastructure surged to 128% year-over-year, becoming the primary driver of AI Cloud's expansion. This reflects both a healthy shift towards a more recurring, structurally healthier revenue model and the strong demand for our AI products and solutions. Our ability to serve this growing demand stems from our early and strategic deployment across Baidu's full stack in AI architecture, spanning infrastructure, framework, models and applications, which allows us to support enterprises at every stage of their AI journey. At the infrastructure layer, our AI infrastructure is among the most advanced in China powered by a diverse mix of domestic and international high-performance computing resources, including our own self-developed AI computing architecture. Through continuous technical innovation, we drive performance and efficiency improvements while consistently reducing inference costs. Additionally, our industry-leading resource management capabilities significantly boost utilization and scalability. These advantages make our AI infrastructure reliable, scalable and highly cost effective for enterprise clients. And the model layer, we feature our self-developed early foundation model, which continues to iterate rapidly.…

Thank you, Robin, and hello, everyone. Robin just mentioned our AI-powered businesses, and I'd like to elaborate. Based on ongoing feedback from investors and to better reflect valuation drivers based on our current portfolio, we are introducing a new AI native view this quarter cut across business groups to track AI-empowered assets company-wide. This new view organized our business according to the nature of our products and services, helping investors better understand the fundamental valuation drivers across our diverse product and service offerings. Going forward, we will provide business updates through this AI native view on an ongoing basis, while continuing to disclose results under the existing reporting methods, giving investors complementary lenses to assess the value of our portfolio. From this AI native view, we have a rich array of AI in power assets. We are highlighting 3 categories this quarter. AI Cloud Infra, AI applications and AI native marketing services. First, AI Cloud Infra, which refers to the AI infrastructure and platform services we provide to enterprises and public sector. In Q3, revenue from AI Cloud Infra reached RMB 4.2 billion, up 33% year-over-year. We operate one of China's most advanced AI accelerator infrastructure, enabling highly efficient and cost-effective training and inference across diverse enterprise workloads. Within AI Cloud Infra, subscription-based AI accelerator infrastructure revenue grew 128% year-over-year. Second, AI Applications. These are AI-native or AI-powered product offerings addressing specific use cases for individuals and enterprises, including our flagship software products such as Baidu Wenku, Baidu Drive and digital employee. AI is transforming how applications create value, enabling far more powerful capabilities that address real-world scenarios more effectively. We built a leading and comprehensive portfolio across both individuals and enterprises. Most of our AI applications are based on sticky subscription models, delivering high-quality revenue. In Q3, AI Applications…

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

My question is on ERNIE 5.0 that was unveiled at Baidu World recently? And then so how will the new model drive the next stage of application such as the digital humans? And what are the key focus area for earnings, future iterations and also the differentiation?

Alicia, this is Robin. Over the past couple of years, I've been repeatedly saying that we're taking an application-driven approach when it comes to earnings iteration. At the Baidu World just a few days ago, we unveiled ERNIE 5.0, our first native omni-model foundation model. It has reached world-class levels in omni-model understanding, creative writing and instruction following, which are very important capabilities to our current and future product portfolio. From ERNIE 4.5 and ERNIE X1 in March to ERNIE 5.0 in November, ERNIE keeps getting better. Digital humans are a good example. Powered by ERNIE, they deliver fluent, contextually accurate and highly expressive dialogue. These are capabilities rooted in ERNIE's language strength. Beyond language, our model also drives visual realism, appearance, movement and even subtle micro expressions, all synchronized with the conversation. When these elements come together, the performance of our digital humans is truly exceptional and genuinely persuasive, capable of driving user engagement and purchasing decisions. ERNIE also powers FM agent, our self-evolving agent that significantly improves enterprise efficiency. It has proven to be very effective in industries like manufacturing, energy, finance, transportation and logistics. Similarly, our AI search and cloud business benefit from ERNIE's capabilities, too. Although ERNIE has delivered remarkable results for these applications, we see a lot of room for improvement. We like to see digital humans sell better than real humans in all kinds of live streaming e-commerce across many product categories. We like to see FM agents find better and better solutions in more complicated scenarios in all industries. We like to see AI-generated content to match users' interest better than KOL-generated content. We like to see ERNIE-based agents to be able to tell which piece of content has better quality regarding certain topics and so on and so forth. These are the areas where none of the existing models do a good job, not even close. So we aim to solve this problem. The application-driven approach actually reflects our deep conviction in where AI value will ultimately reside. While economic value today sits largely at the infrastructure layer, in a healthier AI ecosystem, the greatest value should come from applications where products deliver real impact to users, advertisers and enterprises. Going forward, I think no foundation model can be better than anyone at any aspect. We will continue to focus on making ERNIE strongest where it matters most for our portfolio. Baidu has always been a company with strong belief in technology, and we will continue investing decisively in areas where technology can create real measurable value. So staying close to applications ensures a sustainable path forward for AI development.

And our second question today comes from Lincoln Kong at GS.

So my question is about the Cloud business. So in the third quarter, we have seen Cloud growth has slightly moderated. So are we seeing any changes in terms of the Cloud demand? And should we expect a re-acceleration in the coming quarters? So what's your outlook for the next year? And what are the key drivers that should support the sustainable growth of our cloud business?

This is Dou. Thank you, Lincoln. If you look at our year-to-date performance, our Cloud business is growing well above the industry average. Well, for quarter-to-quarter, there can be some variability, but the overall trend is strong, and we remain very confident about this growth trajectory going forward. On the demand side, enterprises are applying AI across every aspect of the operations, driving strong broad-based demand for AI-centric Cloud services. Within AI cloud, the area most closely tied to AI workloads is scaling the [indiscernible]. Our clients are using our cloud not only for model training, but increasingly for inference tasks. In Q3, AI Cloud Infra revenue reached RMB 4.2 billion, up 33% year-over-year, outpacing overall cloud growth. And the subscription-based AI accelerator infrastructure revenue grew 128% year-over-year, accelerating from around 50% last quarter. This results both strong -- reflects both strong underlying AI-driven demand and a healthier revenue mix. This momentum is supported by our full-stack AI capabilities. At the infrastructure layer, our high-performance AI infrastructure, especially self-developed AI computing architecture continues to see strong adoption driven by superior performance, efficiency and cost effectiveness. Many can start with AI Infrastructure and then expand to additional offerings over time. Also, our Qianfan MaaS platform has been upgraded to be agent-centric. With expanded model libraries, integrated tools and strengthened support for complex agent workflows, Qianfan provides best-in-class agent infrastructure, enabling enterprises to easily build and deploy AI agents at scale. At the application layer, we provide applications that can be readily applied to real business scenarios. Our cloud growth is not just about investment in AI infrastructure, we attach huge importance to applications. We have a comprehensive portfolio of AI products and solutions that is growing very fast, including digital employee, Yijian, Miaoda, FM agent and so on. So we firmly believe AI applications will create substantial value in our cloud businesses in the long term. So to sum up, if we look at our cloud business on an annualized basis, we believe that our full-stack AI capabilities and the strong demand for AI-centric cloud services will enable healthy, scalable and sustainable growth in the future. Thank you.

And our next question comes from Alex Yao with JPMorgan.

The Baidu application evolves into an AI application and web search becomes a building feature for AI chatbots. The line between search and chatbot is getting blurry. How are -- based on your observation, how are user behaviors changing? And what is your competitive strategy going forward?

Alex, let me answer your questions. And AI chatbot actually [Technical Difficulty] and evolve very quickly. So it's necessary to stay flexible to offer different products for different scenarios. And within Baidu, we leverage the chatbot capabilities through 2 complementary offerings. The first one is the ERNIE assistant, which is the built-in chatbot inside the Baidu App. This supports multi-round conversations function, calling and thanks for its deep integration with search. Since many users assess the ERNIE assistant directly from search, so you can draw on query contacts and interaction history to deliver a more relevant and personalized answers. It also connects to a set of tools through MPT, allowing the users to move seamlessly from information discovery to task compaction. And the ERNIE assistant is growing quite fast in our app. You can see that the conversation logs have increased around fivefold year-over-year and the DAU has surpassed 12 million with a very strong month-over-month momentum. And we expect this trend to be further continued in the coming few quarters. In parallel, we also offer the ERNIE bot as a stand-alone chatbot application. While it shares Core capabilities behind ERNIE assistants, the ERNIE bot takes an experimental and innovative approach with a near-term focus on improving retention and long-term ambition to compete at the forefront of the chatbot category. And for example, it provides some cutting-edge multimodel features such as the AI images or [ comic-style ] generations which have been especially popular among the younger users. And looking ahead, we believe the chatbots are not only all ultimate form of AI applications, the future of AI interactions will be multimodel real-time generative and interactive. And for example, at the most recent Baidu World, we have showcased the upgraded [indiscernible] digital human, which is capable of the instant interactions through the real-time voices and video like live conversations. As many of you may recall that we even had a very small technical hiccup during the live demo, which actually proved that it was truly real time and not prerecorded. And once resolved the digital human responding very vividly and deliver dynamic back and forth conversations that feel generally human. So we will continue to bring these advanced capabilities into search, making it more intelligent, personalized and capable of completing tasks. This continuous innovation is how we intend to capture the long-term opportunities in the AI area and strengthen our competitive advantages. Thank you, Alex.

Our next question today comes from Gary Yu of Morgan Stanley.

And also appreciate the additional disclosure on AI-powered businesses. Could management share more on the growth outlook and also the profitability of Baidu new AI-powered businesses? And how will these categories help accelerate our overall revenue growth going forward?

Thank you, Gary. This is Henry. Let me provide some background on this new AI-native views. Based on the investor feedback, we are seeing a need for greater transparency into our high-growth AI businesses. These views organize our portfolios by product nature, giving investors clearer visibility into the underlying value drivers. We will maintain both this AI native view and our existing reporting methods in parallel, offering complementary perspectives on our business performance. From this new perspective, I think we have a rich portfolio of AI-empowered assets. Let me give some highlights here. First of all, for the AI Cloud Infra, this part includes our industry-leading AI infrastructures containing self-developed AI computing architecture, cloud infrastructure and a best-in-class MaaS platform. As AI adoption accelerates, demand for robust infrastructure is growing and our differentiated capabilities position us well. We are capturing long-term sustainable revenue and expect margin to improve as utilization increases. Secondly, for the AI applications, this part includes flagship products, for example, of our Baidu Wenku and Baidu Drive. AI has significantly enhanced functionalities across these products. We have one of the China's broadest AI application portfolios, and most of these applications are subscription based and contributing to higher quality revenue and margins. Third, for the AI native marketing services, including agents and digital humans, this reflects how AI unlock greater efficiency and drive the second growth curve in our advertising business throughout enhanced engagement, conversation and ROI. This quarter, AI-native marketing services reached 18% of our Baidu Core's online marketing revenue, up from 4% a year ago, and we expect penetration to continue rising as adoption broadens. Customers are embracing these result-driven AI solutions and are willing to pay for tangible gains in productivities and marketing efficiency. Importantly, this AI-empowered business reinforce one another across Baidu's ecosystem. And AI embeds deeper across products. So we expect accelerating growth of these businesses. So when we're looking ahead, we remain confident in their revenue and profitability potential, which we believe will support for a stronger growth trajectory for Baidu over time. Thank you, Gary.

And our next question today comes from Miranda Zhuang with BofA Securities.

The question is about the Robotaxi business. So Apollo Go has been accelerating growth this year. So looking ahead, can management update us on Apollo Go for next year and beyond, including your global expansion plans. And how do unit economics look across different markets? And how does management view the long-term profitability potential of the Robotaxi business?

This is Robin. If you remember, our Robotaxi's journey started in 2013. So this is our 13th year. Today, Apollo Go is one of the world's largest robotaxi service providers. And as of November, we have provided over 17 million rides cumulatively, a level very few players globally have achieved. In China, we are the undisputed market leader. Through the first 3 quarters this year, our ride volumes were over 15x higher than our nearest domestic peers according to publicly disclosed data. All these rides are fully driverless, demonstrating unmatched operational scale and technological excellence. Scale matters a lot. The reason we are able to achieve a leading position in autonomous driving technology on a global basis is that we have the scale. We have encountered many issues, corner cases others have not seen. We were able to train our models to handle those cases and become smarter and smarter. I think robotaxi has reached a tipping point, both here in China and in the U.S. There are enough people who have chance to experience driverless rides and the word of mouth has created positive social media feedback, which I think will propel the opening or loosening of related regulations. For 2026 and beyond, we will continue to scale up our operations, both domestically and internationally. We will add more cars in our existing cities. We will expand to more cities. We will accumulate more fully driverless mileage and further improve our technology based on the operational data we gathered on the road. And yes, we need more data to train our models. Better models make the cars safer and faster. We will continue to drive down the cost per mile through technological innovation and operational efficiency. Right now, a few cities have achieved positive unit economics. As we scale, we hope to see more cities turn positive in 2026. Also, we're scaling through flexible business models, including asset-light models, we are very -- we are ready to enter any city quickly once regulatory and market conditions allow. As of October, Apollo Go's global footprint reaches 22 cities with significant progress in Europe, Middle East and Hong Kong. We're confident that UE will continue to improve as we scale. So in summary, for 2026 and beyond, we expect strong growth across 3 areas: rapid growth in ride volumes and [ fee ] size, geographic expansion in new markets -- into new markets and accelerated adoption of new business models. We believe Apollo Go is well positioned for continued global expansion and long-term profitability. Thank you.

And our next question today comes from Thomas Chong of Jefferies.

My question is about how is AI search monetization progressing? And what feedback are you seeing from advertisers and users? Can AI native marketing services offset traditional ad business? And how should we think about core advertising profitability going forward?

Thomas, this is Julius. In October, nearly 70%, 7-0 of the mobile search result pages have content AI generated and multi-model first content. This format is quite unique to us, and we are the first or maybe only one doing this. We expect this level to remain relatively stable as we have largely covered the query types where the AI meaningfully improved the user experiences. Our focus now has shifted to improving the quality, particularly the rich media content like images, videos, and we are seeing very clear improvement in content quality this quarter, which translate directly into the better user experiences. And we can see that the users retention is higher and the users exposed to the AI search results are initiating 6% more queries and spending more time with us. This tells us that users are finding real value in AI search and engaging more deeply. On monetization, we are actively testing and seeing some encouraging early results. First, we are testing MCP in the commercial modules in the AI search. For example, our e-commerce MCP module peaked nearly RMB 6 million in daily GMV during the recent Double 11 shopping festival. This is a very early stage, but the results are quite encouraging. Second, agents for advertisers are generating over RMB 25 million in daily revenue, and we expect this to grow as we bring more agents into the earning assistance as well. And third, we have started testing the digital human live streaming with the real-time interaction capabilities, try to explore the new ways to create engaging commercial experiences. And looking ahead, we see the significant monetization potential for AI search, and we will continue testing actively. However, our near-term priority still remains the user experiences over immediate monetization. This AI transformation is necessary for long-term competitiveness and will inevitably create a near-term pressure on both revenue and margins. So we believe this is the right trade-off to capture the large opportunities ahead. Thank you.

And our final question today comes from Wei Xiong with UBS.

Actually, I have a few questions here. First, just a quick one. Could you please explain this quarter's asset impairment and its rational? And second, what are your CapEx plans for next year? And how should we think about the margin trajectory as AI revenues grow? And lastly, could we please have an update on shareholder returns once the current buyback program expires?

Thanks, Xiong. First of all, on your first question on asset impairment, the background is we are accelerating investments in the latest AI computing technologies without any hesitation. So as part of this effort, we have conducted a comprehensive review of our infrastructure portfolio. Some of the existing assets no longer meet today's computing efficiency requirements. So we actually proactively did some impairments. After this onetime of impairment, our asset base and portfolio profile is in a much healthy position and better aligned with advanced AI computing demand and higher value application scenarios going forward. Second, on the capital expenditures, we are maintaining a high level of investment. Just to give you one example. Since Baidu launched ERNIE in March of 2023, we have invested well above RMB 100 billion in the AI investment. Going forward, we will continue increasing our investment intensity in the AI area. We do expect to see greater operational leverage as our AI business scales. We're executing on 3 fronts. First of all, the asset review and impairments have left us with a leaner and more efficient asset base. Second, we are investing with a discipline to ensure capital efficiency. And of course, thirdly, we are enhancing utilization of our AI infrastructure, for example, through dynamic allocation of capacity across internal products and external cloud services. So as a result of these initiatives, we believe Q3 represents a low point for margins. Looking to next year, we will strive to improve our non-GAAP operational income and margins as these benefits start to flow through. So on your last point regarding shareholder returns, under the plan and program authorized in 2023, we have already bought back a worth of USD 2.3 billion in shares. We are currently reviewing the future buyback mechanism. We understand we also think it is important to provide a greater certainty and clarity to reduce volatility of buyback programs going forward. We're also actively exploring diversified return mechanisms, for example, setting a dividend policy potentially. Together, these efforts aim to deliver more consistent values to our shareholders. Thank you.

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