Baidu, Inc.

for Beidou's first quarter 2025 earnings conference call. At this time, all participants are in a 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 would now like to turn the meeting over to your host for today's conference, Juan Lin, Beidou's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's first 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 on Newswire services. On the call today, we have Rodney, our co-founder and CEO, Julius Rongluo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG, Daosheng, our EVP in charge of Baidu AI Cloud Group, ACG, and Jackson Junjiehe, our interim 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 follow-looking statements except as required under applicable law. Our earnings press release and this call include discussions of certain annuitant non-GAAP financial measures. Our press release contains a reconciliation of the annuitant non-GAAP measures to the annuitant 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. We kicked off 2025 with a solid start. In the first quarter, Baidu Core's total revenue reached RMB 25.5 billion, representing a 7% year-over-year increase. The growth was primarily due attributable to the robust performance of our AI cloud bins. In Q1, AI cloud revenue reached $6.7 billion, increased by 42% year-over-year, representing a significant acceleration for our cloud bins. Such performance reinforces the widespread market recognition of our distinctive AI capabilities underpinned by our unique four-layer AI architecture, while affirming the ongoing demand for our full-stack end-to-end AI products and solutions. Notably, AI Cloud accounted for 26% of Baidu Core revenue, up from 20% a year ago, reflecting the growing significance of our AI Cloud business within our business portfolio. Throughout the first quarter, amid rapid evolution across the AI landscape, advancing our AI capabilities remains our core priority. We have accelerated the iteration of our foundation models, allowing us to maintain our leading position as one of the top players in this dynamic field. In March, we released Ernie 4.5 and Ernie X1, Ernie 4.5 is our first flagship model with multi-model capabilities, and it excels at understanding, analyzing, and processing multi-model content precisely. Ernie X1, our first reasoning model, brings advanced reasoning capabilities with best-in-class function calling, tackling complex problems with extended chains of thought. Notably, both Ernie 4.5 and Ernie X1 come with highly competitive pricing. Furthermore, in April at Baidu Create 2025, we unveiled their upgraded version, Ernie 4.5 Turbo and Ernie X1 Turbo, which feature enhanced performance and dramatically lower pricing. making them among the most cost-effective options on the market. Our rapid and continuous cost reductions stem from our unique four-layer AI architecture and full stack capabilities. This distinctive architecture enables end-to-end optimization at every layer, spanning infrastructure, framework, models, and applications. allowing us to holistically enhance both performance and efficiency. As a result, we deliver superior performance and stability at highly competitive pricing, positioning us to offer industry-leading foundation models and AI solutions with exceptional price performance ratios. With stronger capabilities and lower pricing, foundation models are becoming increasingly accessible enabling diverse applications at scale, and unlocking significant value across industries. Beyond the model iterations, we are also taking steps to make AI more open and collaborative. As previously announced, we plan to open source our most advanced Ernie 4.5 series of models on June 30th. a move that reflects both our technological confidence and our efforts to make earning more accessible. In parallel, we are proactively embracing open standards such as the Model Context Protocol, or MCP, which provides easier access to AI-powered tools and further lowers barriers to AI development. As development becomes Simpler, we expect to see a growing number of AI applications emerging on our platform. Together, these efforts echo our consistent application-driven approach to innovation and our determination to make AI more accessible, applicable, and impactful. In our AI cloud business, we are strengthening Qianfan, our industry-leading math platform, to better support developers and enterprise clients in building models and facilitating AI applications. Qianfan boasts a comprehensive model library of foundation models, covering nearly all mainstream options on the market. It offers not only our own early family of models, but also a wide range of open source and third-party models. including the latest reasoning and multi-model models. This breadth allows individual developers and enterprise clients to choose suitable models with greater flexibility. Importantly, Qianfan provides these models with industry-leading cost effectiveness. When running models like DeepSeq, Qianfan achieves what we believe to be some of the lowest inference costs in the industry today. with lightning speed and massive concurrency. Qianfan also delivers an expanding toolchain, continuously enriched to provide the most comprehensive and user-friendly toolkits for AI development. This quarter, complementing our existing app builder, model builder, and agent builder, we introduced Data Builder to support AI data processing and preparation. while rolling out system-wide upgrades across the entire toolchain to further improve efficiency and ease of use. First, we enhanced the model builder to support the customized development of reasoning models by incorporating advanced training techniques, including reinforcement learning methods like RFT and GRPO. Second, We extended our fine-tuning capabilities to multi-model models, offering multi-model reinforcement learning techniques and enabling full process support from model building and training to evaluation and development. Third, as foundation models grow in size, model distillation has become essential for enterprise adoption. Hence, we introduced a one-click distillation feature that streamlines the previous multi-step process. With our expanded model library now covering reasoning models, enterprise clients can effortlessly build smaller models that maintain reasoning capabilities with reduced costs, making it easier to adopt advanced AI technology. Together, these enhancements significantly strengthened Chiang Mai's toolchain, lowering the barriers for AI adoption and enabling faster, more efficient innovation across diverse use cases. On our legacy consumer-facing product, Baidu Search, we accelerated its AI transformation with an unrelenting focus on enhancing user experience. Our journey exemplifies how complex AI capabilities can be applied to create meaningful improvements that directly benefit our hundreds of millions of users. After exploring and validating for several quarters and with consistent positive user feedback, we established a relatively mature and scalable product framework for our GenAI enabled search early this year. Building on this, we are determined to further accelerate the AI transformation of search. In April, about 35% of mobile search result pages contain AI-generated content, increasing from 22% in January. We are further enhancing the search experience by prioritizing multi-model content, including images, videos, agents, digital humans, and live-streaming. We believe this is a more effective way to present search results, as it aligns with evolving user preferences and better addresses the growing complexity of search queries. The distribution of multi-model content has been rapidly increasing. This trend reflects our continued progress in delivering a more intuitive and effective search experience. Also, the volume of content accessible within Baidu has continued to expand, particularly with the empowerment of foundation models. One example is AI-generated digital human videos, which have surged over 30-fold from the beginning of 2025 through April, in just a few months. The growing volume of content enriches what users can discover and provides access to a more expansive information landscape. Our efforts have led to consistent improvements in user experience. Users exposed to AI-generated search results find their search intent fulfilled more easily and quickly, indicating they get the desired information more efficiently. These users are also increasingly inclined to search for more varied questions or topics, have demonstrated higher retention over time. We're delighted to see more users can enjoy this improvement. In March, the MAU of Baidu app increased by 7% year over year, reaching 724 million. We firmly believe that agents and intelligent Digital humans represent promising real-world applications of AI technology that will open up vast market opportunities ahead. Last quarter, I introduced the convergence of agents and intelligent digital humans, a powerful combination that brings together foundation models capabilities and digital human technology. Today, they are already widely deployed throughout our mobile ecosystem effectively supporting different scenarios across industries. At our recent Baidu Create 2025, I further introduced an upgraded version of intelligent digital human with hyper-realistic interactions, delivering natural conversation with vivid facial expressions and fluid human-like gestures. In the future, we believe they can match or even outperform humans in certain scenarios. We're preparing to launch and scale our next generation hyper-realistic digital humans into production soon. Now turning to intelligent driving, which represents another compelling frontier of our AI applications in the physical world. As highlighted last quarter, Apollo Goal our autonomous ride-hailing service has successfully validated its BINS model in the key operational region with highly complex transport conditions and cost-sensitive local passengers. And it has achieved 100% fully driverless operations in mainland China. This gives us strong confidence to expand into international markets with higher pricing for ride-hailing service. where we aim to replicate and further optimize our proven approach. In Q1, we reached critical milestones in international expansion, with ApolloGo entering both Dubai and Abu Dhabi, aiming to provide safe, comfortable, and affordable autonomous ride-hailing services in the booming markets. In May, we began open-road validation testing in Dubai, and we expect to start testing in Abu Dhabi soon. Meanwhile, we have also expanded our testing area in Hong Kong and obtained permission to conduct open road testing with designated passengers in April. With over 1,000 fully driverless vehicles now deployed globally, we continue to solidify our position as world's leading autonomous ride-hailing service provider. we are scaling up our services globally. Looking ahead, we will deepen our presence in existing markets while strategically entering new ones, capturing broader growth opportunities worldwide. Now, let me review the key highlights for each business for the first quarter. AI cloud revenue reached $6.7 billion in Q1, delivering a strong year-over-year increase of 42% with non-GAAP operating profit remaining positive. Chain AI and foundation model-related revenue recorded triple-digit year-over-year growth, as accelerating AI adoption across multiple sectors drove a notable increase in customer demand for our highly cost-effective AI cloud services. As mentioned earlier, we also upgraded our math platform, Qianfan, with an expanded model library and more comprehensive toolkits, extending support for the training and fine-tuning of multi-model and reasoning models to further facilitate AI-native application development. On applications, you may recall that at Baidu World last October, we previewed MiaoDa, which delivers no-code capabilities. In this quarter, we officially launched MiaoDa, making it available to everyone, programmer or not. MiaoDa reflects our vision to democratize AI and empower more people outside the developer community to create innovative applications with natural language inputs. The growing market recognition of our AI expertise continues to drive strong customer growth. In Q1, we deepened our collaboration with existing clients while also expanding our customer base with new partnerships. We worked with a wide range of leading enterprises such as China Merchant Group and a top e-commerce company in China, further validating our position as the AI partner of choice. Our client pipeline remains healthy we saw strong growth in the automotive sector and began expanding into emerging verticals, such as embodied artificial intelligence, where we recently entered into a strategic partnership with Beijing Humanoid Robot Innovation Center, the developer of the Tiangong Ultra Humanoid Robot. For our mobile ecosystem, we accelerated the AI transformation of search in Q1 while continuing to improve the efficiency of our monetization approaches. Agents continue to demonstrate enhanced efficiency as a monetization channel for our advertising business. In March, over 29,000 advertisers had daily ad spending through agents, with many demonstrating increased willingness to allocate more of their ad budget to our agents. Adoption spans sectors like healthcare, education, lifestyle services, B2B, real estate, and business services, including legal services. In Q1, revenue generated by our agents for advertisers increased 30-fold year-over-year, accounting for 9% of Baidu Core's online marketing revenue. On the other hand, Our industry-leading intelligent digital humans have proven their transformative value across many scenarios. For example, our digital humans serve as live streaming hosts for merchants on our platform. Over the past few quarters, tens of thousands of such digital humans have been live streaming on our platform every month, serving not just the merchants, but also expanding into fields like legal services, healthcare, education, and more. turning to intelligent driving, as just highlighted. ApolloGo made solid progress with its international expansion. Following our entry into Dubai and Abu Dhabi, our global footprint now spans 15 cities. Backed by our validated BINS model and proven operational expertise, we aim to further broaden our presence across more cities globally. In terms of ride volume, we are seeing clear acceleration. ApolloGo provided approximately 1.4 million rides to the public in Q1, representing a robust year-over-year growth of 75%. As of May 2025, the cumulative rides provided to the public have exceeded 11 million. Meanwhile, we continue to scale up our service capabilities in cities where we have long been operating. Also, we are exploring asset light bins models as a key strategic direction for our future growth, and we have started to see early adoption in certain areas recently. In May, ApolloGo entered into a long-term strategic partnership with Car, Inc., China's leading auto rental service provider, to introduce fully autonomous vehicle rental services and explore new models for smart mobility together. As our technology and operations mature at scale, we see significant opportunities and commercial sustainability across more use cases and regions. Combined with our regionally validated BINS model and global expansion efforts, we believe we are well positioned to create substantial value and reshape the future of mobility in the coming years. Looking back at the quarter's developments, we are seeing encouraging progress in AI applications across the board, from enterprise services to consumer-facing products and intelligent mobility. AI technologies are beginning to generate tangible, meaningful value through applications, which embodies the ultimate goal of our application-driven innovation and aligns perfectly with our longstanding strategic focus on AI. With that, let me turn the call over to Jackson to go through the financial results.