Baidu, Inc.

Hello, and thank you for standing by for Baidu's second quarter 2025 earnings conference call. At this time, all participants are in listen-only mode. After management's prepared remarks, there will be a question and answer session. Today's conference is being recorded. If you have any objections, you may disconnect at this time. I now like to turn the meeting over to your host for today's conference, Joanne Lin. Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's second quarter 2025 earnings conference call. Baidu's earnings release was distributed earlier today, and you can find a copy on our website, as well as our newswire services. On the call today, we have Robin Li, our co-founder and CEO, Chris Rongluo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG, Doshin, our EVP in charge of Baidu AI Cloud Group, ACG, and Henry Haijianhe, 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 Security 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 filings with SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forwarding 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 Q2, Baidu Core's total revenue was RMB 26.3 billion. Our AI cloud wins continued to gain momentum, growing 27% year-over-year to RMB 6.5 billion. Notably, Baidu Core's non-online marketing revenue exceeded RMB 10 billion for the first time. That's up 34% year-over-year. These performances helped offset the near-term headwinds in our online marketing business. This year marks Baidu's 20th anniversary as a public company. Over the past two decades, we've remained grounded in our belief in technology and innovation. technological advancement is unfolding at an unprecedented pace. We've embraced the megatrend with open minds, experimenting boldly, adapting quickly, and engaging deeply with AI frontiers. Amid rapid evolution, we've identified and doubled down on a few directions we believe hold the greatest long-term value. and are deepening our efforts with increasing clarity and confidence. Foundation model development remains a key focus area, where we are actively exploring the frontier of foundation model research and pushing the boundaries of AI capabilities. With an application-driven approach, we steer earnings iteration toward areas with real-world application value, such as the fundamental AI transformation of Baidu Search, and our industry-leading digital human technology. Take digital human as a prime example, which represents one of the best applications of our Ernie models. This quarter, powered by Ernie, our digital human technology reached new levels of realism and capabilities, matching or even exceeding human performance in certain scenarios. A standout case was a live stream featuring the digital human of Luo Yonghao, a top influencer in China. The seven-hour live stream generated tens of millions in GMV, fully powered by Ernie series models. Ernie 4.5 Turbo generated the complete script, including dialogue, tone, and action cues. closely mirroring the real person's communication style. Our multi-model capabilities delivered industry-leading visual realism with nuanced facial expressions, gestures, and body movements that responded naturally to conversation flow in real time, achieving next-level performance that sets new standards in digital human technology. Beyond this flagship case, Digital humans are empowering our broader merchant base with performance that already surpasses human life-straining hosts in many scenarios. Going forward, we will continue accelerating foundation model integration, strategically focusing our efforts on areas with application value where we can maintain our most competitive capabilities. Beyond the model capabilities, our unique four-layer end-to-end AI architecture has become a core competitive advantage and represents a key focus in our AI cloud bins, where our full-stack AI capabilities are driving healthy growth. As the infrastructure layer, we achieved a critical system engineering breakthrough this quarter, by completing the large-scale, stable deployment of pre-fill, decode, separation architecture. This breakthrough significantly improves inference concurrency and resource utilization while substantially reducing inference costs. The achievement was made possible by the end-to-end optimization enabled by our unique four-layer AI architecture, spanning infrastructure framework, models, and applications, which allows us to coordinate improvements across all layers. At the same time, each layer remains open, giving customers flexible choices between Baidu's proprietary and third-party options. As a result, we are continuously improving the cost effectiveness of our AI Cloud products and solutions reinforcing our position as China's top-tier cloud provider in the AI era. Meanwhile, our industry-leading math platform, QianFan, continues to evolve to better support enterprise clients in building models and facilitating AI application development. QianFan features a comprehensive model library covering nearly all mainstream foundation models on the market. This quarter, we further expanded the library with a range of new models, including our newly open-sourced early 4.5 series, additional third-party multi-model models, and other leading options, enabling greater flexibility across enterprise use cases. Leveraging our breakthrough in cloud infrastructure, Qianfan delivers enhanced stability, higher concurrency, and lower inference costs when running models. meeting our superior price performance. On the toolchain front, Qianfan's toolchains are among the most comprehensive, with industry-leading reinforcement learning and post-training tools for model development. In Q2, Qianfan was further enhanced to support a wider range of AI tools and functions that can be called via MCP or APIs. including Baidu's proprietary capabilities such as Baidu AI Search, Baidu Wiki, Baidu Maps, as well as selected third-party capabilities like payment services. This enhancement helps simplify AI application development and continue to solidify Xi'an Fund's leadership as one of China's top mass platforms. Apollo's driving remains one of the most promising areas we've long invested in, which represents a critical frontier in physical world AI. Following the successful validation of Urban's model at the end of last year, ApolloGo is now scaling rapidly. In Q2, ApolloGo provided over 2.2 million fully driverless rides to the public. that's up 148% year-over-year, marking our strongest quarterly growth in two years. Also, ApolloGo's global expansion has gained solid momentum, highlighted by two strategic partnerships with leading global ride-hailing platforms. In July, we announced a multi-year strategic partnership with Uber, Under this partnership, thousands of ApolloGo's fully autonomous vehicles will be deployed on the Uber platform across multiple international markets, with initial rollouts planned for Asia and the Middle East. This milestone was followed by our partnership with Lyft in August, which will also bring thousands of our fully autonomous vehicles to key European markets through the Lyft platform. starting with Germany and the United Kingdom and sailing across Europe over time. Our expansion into international markets is built on a strong foundation. In China, we have already achieved positive unit economics in markets where wide fares are much lower than those in major overseas markets. That's why these global partnerships are both logical and strategic. positioning us to capture greater value in higher fair markets while scaling efficiently. Our partners' global market presence, leveraging our partners' local market presence, we can accelerate market entry across different continents and achieve faster deployment while maintaining a cost-efficient asset-light business model. In markets we've already entered, We continue to make encouraging progress in Hong Kong, one of the world's most complex right-hand drive cities. We recently expanded our testing coverage to include Tung Chung and Southern District, advancing our open-road testing into more complex urban scenarios across both commercial and residential areas. Also, we further strengthened our presence in the Middle East In Dubai and Abu Dhabi, we started open road testing in designated areas in August. Notably, ApolloGo leads the world in right-hand drive robot taxi markets. This is a space where hardly any companies of our kind have entered, and we've made by far the most progress. The rapid progress we're making in Hong Kong really shows our global leadership. It's proof of how adaptable our technology is and how mature our operations have become across all kinds of environments. Our experience there provides us valuable insights for entering other right-hand drive markets, strengthening our confidence in scaling Apollo Go globally. With solid progress quarter by quarter, we are more confident than ever in ApolloGo's international potential. As China's largest autonomous ride-hailing service provider and a global leader in this space, ApolloGo combines industry-leading technology, extensive operational experience, and extraordinary safety records to bring safe, comfortable, and affordable autonomous ride-hailing services to more markets worldwide than anyone else. In our mobile ecosystem, transforming our products with AI remains a strategic priority, especially our legacy consumer-facing product, Baidu Search. Baidu is at the forefront of applying AI to transform Search globally. Rather than simply inserting AI summaries into search results, we are fundamentally revolutionizing the search experience by completely replacing static textual hyperlinks with intelligent, structured, and multimodal first AI-generated responses. These responses start with relevant multimodal content right at the top. making complex information more accessible to a broader user base and therefore creating a more intuitive experience. In Q2, our AI transformation continued to accelerate, with AI-generated content reaching over 50% of mobile search result pages by the end of June, up from 35% in April. By July, 64% of mobile search result pages contained AI-generated content presented in a structured and multi-model first format, marking the broader rollout of our innovative AI search experience. This AI transformation reached over 90% of Baidu app's monthly active users in July. with over 60% of such search result pages starting with rich media elements such as images or videos. As we advance our AI transformation, the expanding content ecosystem across Baidu provides meaningful support. Leveraging ongoing progress in general AI and multi-model capabilities, Baidu's AI-generated content has grown significantly in both scale and quality, providing more high-quality content for search results. AI-generated multimodal content, in particular, has seen rapid expansion. For example, daily AIGC video generation reached millions of units starting from May, and daily AIGC video distribution within Baidu app has grown rapidly. We're delighted to see sustained improvements in user metrics. In June, Baidu Apps MAU reached 735 million, representing a 5% year-over-year growth. The daily average time spent per user in Q2 increased by 4% year-over-year. Building on Search's ability to satisfy user intent, we are expanding its boundaries from providing smart answers to completing tasks and connecting real-world services. For instance, our agents engage users in multi-round conversations, connect them with relevant service providers when needed, and facilitate end-to-end task completion across multiple verticals. We believe this represents a meaningful expansion of what search can achieve, enabling users to seamlessly move from information to action. Now, let me review the key highlights of each bin sector this quarter. AI cloud revenue reached RMB 6.5 billion in Q2, up 27% year-over-year, with non-GAAP operating profit achieving year-over-year growth. The growth was primarily driven by the growing demand for our highly cost-effective end-to-end AI products and solutions. Within the enterprise cloud, which contributes the vast majority of AI cloud revenue, subscription-based revenue grow at a solid pace, signaling a healthier and more sustainable revenue structure. On the infrastructure layer, we continuously enhanced our resource management capabilities, achieving higher and higher infrastructure utilization. Through ongoing end-to-end optimization across our four layer AI architecture, combined with increasingly refined and efficient GPU resource management capabilities, our large scale key clusters have achieved over 90% utilization rates recently for key tasks. Our enhanced capabilities allow us to deliver better performance at lower costs and provide more competitive pricing for enterprise customers, establishing a virtuous circle where our growing customer base and diversified workloads further improve resource utilization, reinforcing our sustainable revenue model. In Q2, our customer portfolio continued to improve. Existing clients deepened the collaboration and increased spending, while mid-tier enterprise clients demonstrated strong growth momentum. Additionally, this quarter marked several strategic partnerships with prominent companies across key verticals, including a leading lifestyle platform and a top-tier gaming company in China. In the embodied AI industry, we have partnered with 20 companies cumulatively, including Shenzhen Institute of Artificial Intelligence and Robotics for Society. In autonomous driving, we established a partnership with Black Sesame Technologies on AI cloud infrastructure. These partnerships reflect the strong recognition of Baidu AI Cloud and affirm our competitive positioning in China's AI Cloud market. Building on our full-stack AI capabilities, we are not only serving enterprise clients, but also driving internal productivity and mass market AI adoption at the application layer. Internally, we've widely adopted CodeMate, our AI coding assistant for developers. CodeMate's capabilities continue to improve, enabling more agentic and efficient development workflow. In July, AI contributed to generating over 45% of our new code, with our developers providing oversight and approval. This has significantly boosted our engineering productivity and meaningfully enhanced our internal R&D efficiency. Externally, MiaoDA extends its AI development capabilities to the broader community. Following MiaoDA's official launch last quarter, we're now delivering true no-code capabilities that enable users to create applications from mini games to utility tools and websites through simple natural language conversations with AI, no programming expertise required. As of July, users have created around 200,000 applications on MiaoDAO, all built completely without writing a single line of code. We are continuously enhancing low-code capabilities as we work toward our mission to democratize AI and empower everyone to innovate. Moving to intelligent driving, in Q2, ApolloGo provided over 2.2 million fully driverless rides to the public, up 148% year over year. As of August, cumulative rides provided to the public have surpassed 14 million, underscoring the scale and the maturity of our fully driverless operations. As of June, ApolloGo's global footprint spans 16 cities. To date, our fleets have accumulated over 200 million autonomous kilometers with an outstanding safety record, which is a testament to the ability and safety of our autonomous driving technology. Beyond global partnerships like Uber and Lyft, we are accelerating the rollout of asset-light bins models domestically. This quarter, we established new partnerships with HelloRide and T3 Mobility, expanding our collaborative network with leading mobility service providers. Additionally, building on the partnership announced last quarter, ApolloGo's fully autonomous vehicle rental service officially went live on the Car, Inc. app, offering users a new access point to our ApolloGo fleet. These partnerships enable us to rapidly scale our services while leveraging partners' operational expertise and existing customer bases, creating an efficient path to broader market penetration. Going forward, we are confident to further accelerate our global expansion and capture significant value across multiple markets worldwide. For mobile ecosystem, we continue accelerating AI transformation of search in Q2. In today's highly competitive mobile internet market, where new products and technologies are emerging and evolving faster than ever, user needs and behaviors are constantly shifting. making it essential for us to keep upgrading at a rapid pace. While our AI transformation is progressing rapidly, it is still in the early stages, with considerable room for optimization before reaching its full potential. And we are not yet at the stage for large-scale monetization. Against this backdrop, we began prudent Small-scale monetization testing in Q2 with user experience remaining our top priority. Early results have been satisfying. For example, some queries that were previously difficult to monetize are now showing potential. Agents maintained strong performance in driving better conversion efficiency. further validating our effectiveness. In Q2, revenue generated by our agents for advertisers rose 50% quarter over quarter, contributing 13% of Baidu Core's online marketing revenue. That's up from 9% in Q1. In parallel, DigitalHuman gained traction innovative monetization avenue for our advertising business, particularly through AI-powered live streaming. We've seen steady growth in digital human adoption over recent quarters. Beyond serving live streaming hosts for merchants, they were being adopted at growing scale in healthcare, legal services, education, and automotive sectors. More advertisers recognize their value in boosting conversion performance through real-time user interaction and round-the-clock availability, leading to increased ad budget allocation toward digital humans. In Q2, revenue generated by digital humans increased by 55% quarter-over-quarter, contributing 3% of Baidu Core's online marketing revenue. To sum up, as we look ahead, Baidu will stay anchored in our long-term vision and move forward with greater focus and resolve as we continue to translate AI innovations into real-world value. Before we move to Q&A, I'd like to take a moment to welcome Henry, Mr. Hai-Jian He, who recently joined us as Chief Financial Officer. With that, let me turn the call over to Henry to go through the financial results.

Thank you, Robin, and hello, everyone. I'm delighted to join the Baidu team and looking forward to working with all of you. Now let me walk through the details of our second quarter financial results. Total revenues were 22.7 billion RMB, decreasing 4% year over year. Revenue from Baidu call was 26.3 billion RMB, decreasing 2% year-over-year. Baidu's online marketing revenue was 16.2 billion RMB, decreasing 15% year-over-year. Baidu's non-online marketing revenue was 10 billion RMB, up 34% year-over-year, primarily driven by the boost of AI cloud business. Within Baidu's non-online marketing revenue, AI cloud revenue was 6.5 billion RMB, increased by 27% year over year. Revenue from ITE was 6.6 billion RMB, decreasing 11% year over year. Cost of revenues was 18.4 billion RMB, increasing 12% year over year, primarily due to an increase in costs related to AI cloud business and content costs. Operating expenses were 11.1 billion RMB, decreasing 4% year over year, primarily due to a decrease in personnel-related expenses, partially offset by the increase in channel spending expenses. Baidu cost operating expenses was 9.7 billion RMB, decreasing 5% year-over-year. Baidu core SG&A expenses was 5 billion RMB, increasing 6% year-over-year. SG&A accounted for 19% of Baidu cost revenue in a quarter. compared to 18% in the same period of last year. Baidu Core R&D expenses were 4.7 billion RMB, decreasing 14% year over year. R&D accounted for 18% of Baidu Core's revenue in this quarter, compared to 20% in the same period of last year. Operating income was 3.3 billion RMB. Baidu Core's operating income was 3.3 billion. RMB, and Baidu core operating margin was 13%. Non-GAAP operating income was 4.4 billion RMB. Non-GAAP Baidu core operating income was 4.4 billion RMB, and the non-GAAP Baidu core operating margin was 17%. Total other income net was 4.9 billion RMB, increasing 531% year-over-year. primarily due to an increase in the fair value gain and a pickup of earnings from long-term investments, partially offset by an increase in the net foreign exchange loss arising from exchange rate fluctuation between RMB and the U.S. dollar. Income tax expenses was 881 million RMB compared to 1.1 billion RMB in the same period of last year. Net income attributed to Baidu was 7.3 billion RMB, and the diluted earning per ADS was 20.35 RMB. Net income attributed to Baidu Core was 7.4 billion RMB, and the net margin for Baidu Core was 28%. Non-GAAP net income attributed to Baidu was 4.8 billion RMB. Non-GAAP diluted earnings per ADS was 13.58 RMB. Non-GAAP net income attributed to Baidu Call was 4.8 billion RMB. And the non-GAAP net margin for Baidu Call was 18%. As of June 30, 2025, cash-cash equivalents, restricted cash, and short-term investments were 124.2 billion RMB. And the cash-cash equivalents, restricted cash, and short-term investments, excluding IHE, were 119.9 billion RMB. As of June 30, 2025, cash equivalents, short-term investments, and long-term time deposits and head-to-maturity investments for Baidu Core were 229.7 billion RMB. Free cash flow was negative 4.7 billion RMB, and free cash flow excluding IGE was negative 4.6 billion RMB, primarily due to the increase of investment in AI business. We define net cash position as total cash, cash equivalents, restricted cash, short-term investments, net, long-term time deposits, health and maturity investments, and others. Less total loans, convertible senior notes, and the notes payable. As of June 30, 2025, net cash position for Baidu was 155.1 billion RMB. Baidu Call has approximately 31,000 employees as of June 30, 2025. With that, operator, let's now open up the call for the questions. Thank you.

Ladies and gentlemen, we will now begin with the question and answer session. If you wish to ask a question, please press star 1 on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star 2. If you are on a speakerphone, please pick up the handset to ask a question. Your first question comes from Alicia Yap, Citigroup. Please go ahead.

Thank you. Good evening, management. Thanks for taking my questions and also welcome Henry as the new CFO. I have a question on your AI model. With the rapid model iteration, how do you view the current landscape? How do you position Ernie strategically in the market and its alignment with either broader business strategy? And we also have heard that you're planning to launch Ernie 5.0. could management share plans for earnings in the second half this year and also the key focus area for this next version. Thank you.

Hi, Alicia. This is Robin. Let me first give you our take on the current landscape. The pace of model iteration is faster than ever. We see multiple new models are launched almost every week. And each new generation is stronger than the last. In recent months, we've seen models grow more capable, reaching a stage where their deeper logic and greater creativity now enable them to propose entirely new solutions we've never seen before. And I believe this kind of innovative ability is getting stronger. Meanwhile, the foundation model landscape is becoming more diverse and clearly not a one-size-fits-all situation. Especially in China, similar to EVs, you always have a lot of choices. Different models excel at different tasks. Some are stronger in reasoning, some in coding, and some in multimodality. So we will continue to see a market where multiple models coexist at very reasonable prices. And the value creation will happen at the application level more than at the model level. Against this backdrop, Ernie's positioning is clear. We take an application-driven approach to innovation. In fact, we've taken this approach since the launch of Ernie first launched operating more than two years ago. Rather than spreading efforts across every possible direction, we stay focused on the strategic, the important areas that's valuable to us. We think we can deliver meaningful impact and assisting our leaderships. For example, as we advance AI search transformation, we direct our model capabilities toward generating and selecting multi-model search results. And our users love it. Our cloud customers also love it. They're paying for our search API for the purpose of RAG in their machine AI applications. Another example is our hyper-realistic digital human technology, which now matches and even exceeds real human performance in the live streaming e-commerce scenario. Our model is just better at convincing people to buy. Cloud customers are paying for this capabilities too. As we move into the second half and beyond, we will continue this acceleration. We're currently working on the next flagship version of Ernie with significant improvements across key capabilities and expect to launch it as soon as we are ready. In the meantime, we will continue to roll out iterations and updates on an ongoing basis. for our existing models. We also keep monitoring industry developments to ensure our technology roadmap captures the most promising market opportunities. Thank you.

Thank you.

Thank you. Your next question comes from Alex Yao from JP Morgan. Please go ahead.

Thank you, management, for taking my question. And Henry, all the best to your new role. So here is my question. How is the AI-powered search upgrade progressing in Q2 and Q3? Could management share updated metrics on how user behavior is shifting with the new experience? How should we think about the end game of AI search in terms of product formats, user reach, and lastly, commercial potential? Thank you.

Hi, Alex. Thank you so much for the question. This is Julius. I think Q2 will continue to accelerate AI search transformations. As Robin has just mentioned, Baidu leads globally in using AI to transform search. And maybe we are the most aggressive in revolutionizing the search. And we're probably the only company that has completely replaced the traditional links with intelligent AI answers that start with the multi-model content. This creates a more efficient, intuitive use experiences. And unlike the current AI answers or chatbots that remains mostly still is the tech space. Our focus remains at delivering the better use experiences. Beyond the MAUs and the time span improvements, the use exposed to AI search now shows higher UV and retention, indicating our next generation search experience is driving the stronger users' satisfaction. As for the end game of AI search, I think it's still an open question, but our part is quite clear. We are fundamentally restructuring search. First, instead of just indexing or linking to information, we are delivering the intelligent AI-generated answers that began with the relevant multi-model content. Multi-model content now appears more at the very top of AI answers, with an increasing portion being AI-generated. As high-quality AIGC content expands on our platform, it directly enriches the search results and broadens what we can offer to the users. And meanwhile, AI is also empowering the people across our ecosystem, from users, content creators, to advertisers and service providers, to produce more and better content. enabling those who were not traditional quantum creators to participate and making our whole ecosystem more vibrant. For example, in July, we have launched our MILS steamer, our proprietary video generation model to facilitate AIGC video creation at scale. The latest version of MILS steamer with significant update will be launched tomorrow afternoon. Just stay tuned. We are moving fast. And second, we're also evolving from finding information to completing tasks and connecting users with the real-world services. For example, through the MCPs, we have connected search to external capabilities, like our British Museum and Metropolitan Museum MCPs that can provide exhibition explanations right in search. For more complicated needs, our agents have to understand the user's intent and connect them with the services providers when the offline services are required. What we have done today is only the beginning and Search will continue advancing in capabilities and reach over time. In the third place, we're also working towards the shift from the general results to personalized pages. While AI search understands the individual's context, memories, and preference to generate the tailor-made responses, delivering the more intelligent, relevant, and personalized answers while better matching the users with the tools and services they need. And looking ahead, we will continue to accelerate AI transformation, which in the short term will weigh on revenue But over time, we believe the AI search will unlock exciting commercial possibilities, and the upside is substantial.

Thank you for your question, Alex. Thank you.

Next question comes from Gary Yu, Morgan Stanley. Please go ahead.

Hi, thank you, management, for the opportunity to ask questions. I have a question regarding the AI cloud revenue. Can management provide a breakdown of the current revenue mix and margin profile? What's the split between subscription-based and project-based revenue, and how do you see them evolving in the coming quarters? And also, what's the margin profile looking like in the near term and over the long term? Thank you.

Thank you, Gary. This is Doug. In Q2, AI cloud revenue grew 27% year-over-year to 6.5 billion RMB. For the first half of 2025, AI cloud revenue increased 34% year-over-year, accelerating from the low teens growth we saw in the first half of 2024. Enterprise cloud has consistently outgrown our overall AI cloud business. and remains the main growth driver. Now, within the enterprise cloud, subscription-based revenue accounts for more than half of the total and continued growing steadily in Q2. The growth was driven by strong momentum in subscription-based AI infrastructure, which grow over 50% year-over-year. We are seeing good traction with both top-tier and mid-tier customers. Mid-tier customers in particular delivered notable revenue growth as they continue expanding with us, reflecting our broadening customer base. The other part of the enterprise cloud is project-based revenue. Project-based revenue is typically linked to customer deployments and will inevitably fluctuate from quarter to quarter based on contract timing and project schedules. We are currently conducting a careful review of our project portfolio and aim to gradually reduce the proportion of project-based revenue for greater revenue stability. Turning to a personal cloud, which is a smaller part of our overall AI cloud business, over the recent quarters, we've integrated Baidu Drive with Venku and launched multiple new AI features. Recently, we opened up select AI features for free to encourage wider adoption. While this may involve some near-term trade-offs, we believe it helps deepen user engagement and positions us to benefit from broader AI adoption. On profitability, we achieved year-over-year growth in non-GAAP operating profit and maintained a healthy market, driven by a healthier revenue mix, tilted toward higher value offerings. While margins can move around from quarter to quarter due to dynamic market environments, We see clear potential for future improvement over the long run as we scale and optimize our mix. Thank you, Gary.

Thank you. Thank you. Our next question comes from Lincoln Kong from Goldman Sachs. Please go ahead.

Thank you, management, for taking my question. So my question is about the search. So actually, can management share more color on the reason AI search monetization testing? Because following your earlier comments on AI search opening up a new monetization opportunity, could you elaborate on that? And how are all advertising format and business model evolving? What will be the margin look like? Thank you.

Thank you, Lincoln. Let me ask you a question. I mentioned about the marginalization opportunities earlier, and let me elaborate over here. From a product perspective, while our AI transformations already covers a large portion of such results, we are still in the early stage with substantial room for improvement. We aim to further increase the penetration of multi-modal content in such results and continue building and enriching our AI-native ecosystems through MCP agents. And on the foundation, enable the deeper, broader, or higher quality connections to the real world services. As the AI transformations of wants and the use experiences improves, modernization opportunities will naturally follow. And also, the AI search brings the native apps that feels intuitive and integrate, enhancing rather than interrupting the use experiences. So the vast majority of keywords that were previously very difficult to monetize now can be monetized under AI Search, which should significantly expand our advertisement inventory over time. While initially we will be very conservative with monetization to ensure we get the user experience right, but the long-term upside is much higher. And during our AI transformations, we are moving from simply generating sales leads to enabling the real-world service delivery. This is a shift made possible by new AI-native commercial products, such as agents or digital humans. These innovative products allow us to better capture and serve the user needs through interactive conversations, while connecting the users with service providers in verticals like healthcare, travel, and education, where our agents and Digital humans have already proven modernization capabilities. Over the long term, the ability to fulfill the user needs end-to-end presents us with a way to drive a gradual transition from CPC to CPS, which offers a much higher ceiling for modernization. NEQ2, we have already begun the early testing of the AI search monetization. While it's still in early days, we have seen the world encouraging signals, and we believe this trend will continue over time. Let's say that we always pull user experiences first, so we drew a very deliberate approach to AI search monetization, and large-scale monetization has not started yet, and at the same time, we have been aggressively accelerating the AI search transformation, including changing those queries with the highest monetization capabilities. So in the near term, we do expect the revenue margin will remain under significant pressure. But long term, we believe these positions are where for stronger growth. Thank you.

Thank you.

Our next question comes from the line of Miranda Shuang with Bank of America Securities. Please go ahead.

Thank you for taking my question. My question is about cloud and GPU. So how should we assess the sustainability of the AI-driven cloud demand, especially against the backdrop of a soft economy and intensifying market competition? and also with the easing of the H20 chip restriction, has management seen any meaningful improvement in supply? How do you think about the chip constraint? Will it remain as a limiting factor for growth going forward? Thank you.

Hi, Miranda. I would take a lot of questions. Actually, we are seeing strong and growing demand for AI-driven cloud services as China's cloud market continues its shift toward AI-centric computing. The adoption of gene AI and foundation models is accelerating, and AI has become a strategic focus for more and more companies. From what we've observed, Demand is picking up across a wide range of sectors, not only from early adopters like tech and internet companies, but also from a broader set of industries like utilities, financial services, and the public sector. We're interested in AI-driven cloud solution is rising quickly. Meanwhile, technological advances are filling strong new demand from emerging sectors such as embodied AI. we are effectively capturing new opportunities and working with leading players in this field, including 20 of China's promising embodied AI startups, four of which are China's top humanoid robot companies. The reason we were able to capture opportunities so quickly is our unique competitive positioning. What differentiates us is our ability to deliver highly cost-effective end-to-end AI cloud products and solutions, thanks to our full stack AI capabilities. Taking our AI infra as an example, we keep improving utilization and efficiency through our industry-leading resource management capabilities. By dynamically allocating computing resources we can better match workloads with the suitable resources and manage demand fluctuations, delivering better performance at lower costs. As a result, we can provide cost-efficient, reliable, and scalable cloud services that makes it really easy for companies to adopt AI with minimal effort and scale it into real business impact. On your question about tips, our focus remains on building a flexible AI architecture that maximizes GPU utilization and supports a variety of tips, including domestic tips. This enables us to better serve customers as the supply environment evolves. Looking ahead, we believe that a self-sufficient supply chain together with increasingly mature homegrown software stacks, will form a solid foundation for sustainable innovation in China's AI ecosystem. And clearly, Baidu is well-positioned to lead the transition. Thank you.

Thank you. Next question comes from V Xiong, UBS. Please go ahead.

Sure. Thank you, management. Thank you for taking my question. Given the near-term headwinds on ad revenue and continued investment in AI, I wonder what are the plans for cost optimization and efficiency improvement that can help protect margins? How should we think about the margin trend in 2026 and beyond? Thank you.

Thank you. This is Henry. First of all, On the AI investment, we remain committed to investing in AI and have made substantial investments throughout this year, particularly in AI transformation of search. As Julius mentioned earlier, our core legacy product search is undergoing a radical transformation. Over the past several quarters, we have ramped up investments to accelerate this transformation, which we believe it's critical to drive long-term value. However, since the AI search monetization is still in very early stages and has yet to scale, our revenue and margins are under considerable pressure in the near term, with Q3 expected to be especially challenging. To help push in the near-term impact, we will actively drive internal efficiency gains. This includes strengthening resource coordination efforts across different business groups, and improving overall resource utilization efficiency. But also on the other end, while we are remaining committed to long-term AI investment, we'll be very prudent in managing the pace to avoid a future deterioration of fluctuation in margins. Looking further ahead, we see potential for margin improvement as our core advertising business recovers and is stabilized, and our non-advertising business both expand their revenue share and improving their own profitability. We believe our strategic direction and the disciplined execution should support a gradual recovery in profitability over time. Obviously, on an outlook front, I think before or around the end of this year, we expect to have a greater visibility into next year, and at that time, we will provide a clear outlook beyond the current quarters for the long term In parallel, we are carefully assessing different approaches to present and to unlock the hidden and unstated value of our assets. By doing so, we aim to strengthen our portfolio, create significant long-term value for shareholders, but also support sustainable growth over the long term of business.

Thank you. Thank you.

The next question comes from Thomas Chong, Jefferies. Please go ahead.

Hi, good evening. Thanks, management, for taking my question. My question is about the global autonomous driving landscape. We see it becomes increasingly competitive. How does ApolloGo assess its long-term defensation against peers? And how do the recent MUBRA and NIF partnership fit into your global expansion strategy, and what is the roadmap for achieving sustainable profitability? Thank you.

Yeah, I think autonomous driving is one of the most exciting frontiers where AI is transforming the physical world. And success in this field requires cutting edge technology, massive sustained investment, and disciplined execution over many years to achieve commercial operations at scale. One of the earliest entrants, we have built an unparalleled foundation across all these areas and become an undisputed global leader in this field. With our business model validated, our current focus is on running real-world operations at scale. And we have established global leadership in both left-hand and the right-hand drive robot taxing markets. In the left-hand drive market, we were the first to achieve UE breakeven. And all of our current operations in China, in mainland China, are fully driverless. Globally, we are among the very few capable of scaled fully driverless and commercial operations in a single, complex, large population area. And in the right-hand drive market, we lead the industry globally. In Hong Kong, we rapidly expanded our open-row testing and advanced into increasingly complex urban scenarios following regulatory approval. Our technology stack and operational expertise are highly transferable across geographies, allowing us to adapt efficiently to new markets and regulatory involvement. We also build a major advantage with RT6, the world's first and only production vehicle designed especially for level 4 autonomous driving from day one. Unlike some retrofitted cars, RT6 is a purpose build from the ground up with a focus on safety, system integration, and cost efficiency. It has the lowest unit cost globally for level 4, and is already running our commercial operations at scale, giving us a big edge for broader rollouts. With these strengths, we are confident about expanding to more cities worldwide, especially those with higher ride fares. Here's the picture. We have the world's lowest cost level four vehicle and most efficient operations. We first achieved UE breakeven in Wuhan, where taxifiers are over 30% cheaper than the tier one cities in China, and far below many overseas markets. Yet we still managed to prove our best model there. Such operational excellence and cost efficiency is unmatched globally. Expanding overseas means going from low fare markets to high fare markets, often with fares several times higher. Our huge cost advantage can deliver much stronger unit economics in most major cities worldwide. To accelerate our global expansion, we are also taking a proactive approach to global partnerships. As we mentioned in our prepared remarks, We announced our partnership with Uber in July and followed by Lyft in August. Our partnerships with these world-leading mobility platforms will help us enter and scale more quickly into global markets like Middle East, like Asia, like Europe. Looking ahead, we anticipate accelerating growth in ride volumes with our global operational fleet size multiplying. With that momentum, we are confident that ApolloGo will continue to lead the market and stay at the forefront of autonomous driving worldwide. Thank you.

Thank you.

Thank you. That does conclude our conference for today. Thank you for participating. You may now