Baidu, Inc.

Hello and thank you for standing by for Baidu's second quarter and fiscal year 2024 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 would now like to turn the meeting over to your host for today's conference, Jim Lynn. Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's second quarter 2024 earnings conference call. Baidu's earnings release was distributed earlier today, and you can find a copy on our website as well as our newsletter services. On the call today, we have Robin Li, our co-founder and CEO, Rong Luo, our CFO and adoption, our EVP in charge of Baidu AI Cloud Group, ACG. After our surprise 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 documents filed 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 inaudible non-GAAP financial measures. Our press release contains a reconciliation of the inaudible non-GAAP measures to the inaudible most directly comfortable 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. Baidu Core flow revenue grows slightly to RMB 26.7 billion in Q2. Thanks to the continuous acceleration of our AI cloud business, despite the headwinds in our online marketing business, Even with the ongoing investment in AI, Baidu Core's non-GAAP operating margin improved by close to 2 percentage points year-over-year to 26%, and non-GAAP operating profit grew by 8% year-over-year. Thanks to the operational efficiency gains, we continue to implement. Despite the near-term pressure, we remain fully confident in our strategic direction and the transformative potential of GenAI and foundation models. As we move further into 2024, we are happy to observe a significant change as Baidu is scaling AI to address real-world problems and generate substantial value both externally and internally. Central to this effort is our commitment to making EARLY increasingly affordable and accessible. I'd like to highlight some key points of our progress. The scaling of AI is accelerating at a breakneck pace, reflecting the real value that EARLY creates for people and for business alike. We find that the most tangible benefit from AI comes from the adoption and use of applications built on top of LLMs. Just three months ago, we announced that Ernie handled about 200 million API calls daily. Recently, it surpassed 600 million, or over 1 trillion tokens are generated every day. To make Ernie more affordable, we continue to expand our model portfolio and enhance our model capabilities to meet diverse customer needs. Last quarter, we launched three lightweight Ernie models, and they have quickly gained traction among enterprises and developers. Building on this momentum, we introduced Ernie 4.0 Turbo in June. It offers superior capabilities compared to Ernie 4.0 for typical use cases, yet it's designed to be much cheaper and faster to run. Our current lineup now includes our flagship models Ernie 3.5 and Ernie 4.0, and the enhanced model Ernie 4.0 Turbo, and several lightweight models, This diverse portfolio allows us to accommodate the varying needs of our customers, optimizing for performance, cost, and latency. In May, we made a strategic move to make API calls free of charge for three lightweight earning models. That's earning speed, earning light, and earning timing. And in July, we significantly lowered the price of API calls for the two Ernie flagship models, Ernie 3.5 and Ernie 4.0. This decision is rooted in our commitment to enabling wider access to Ernie and making AI accessible to all. At the same time, we continue to lower the cost of model inference. One optimization of note this quarter is the upgrade of PaddlePaddle. our open source deep learning framework to version 3.0. This upgrade significantly improves the framework's compatibility with our AI infrastructure and learning, which we expect will further help reduce model inference costs in the future. I briefly mentioned earlier that Baidu scales AI to address real-world problems and generate substantial value. both externally and internally. I'd like to discuss this in more detail. Externally, we have empowered our AI cloud customers to achieve greater efficiency and scalability by using Ernie. Our solutions have enabled clients to optimize their operations and realize significant benefits across various initiatives. Let me offer you some use cases to illustrate the real business problems we have addressed and how we add value to our customers. In the healthcare industry, Dr. Burnout is one of the greatest challenges. By leveraging early speed and our model builder, we help a healthcare automation solution provider to train and fine-tune an industry-specific model that enables automatically generated medical records for doctors. This solution significantly reduces the administrative burden on doctors, a major factor in burnout, and enhances clinical efficiency. After two months of model deployment, doctors using it were able to treat 50% more patients on average. In the recruitment industry, we have collaborated with a recruiting service company. By leveraging earnings capabilities through API calls, our customer has significantly upgraded the matching process between job descriptions and resumes. The smart matching upgrade has reduced labor costs in this process by over 50%, measured by total working hours. while maintaining high quality results. This automation allows the customer to expand its services to a broader client base, thereby increasing revenue generating capability and demonstrating the tangible benefits of integrating earning into its operations. The customer is very satisfied with the result and is now exploring new collaboration opportunities. In the public service sector, we utilize the early speed to deliver tailored, personalized, and scalable services, addressing challenges like limited resources and efficiency needs. This is particularly valuable in China's grassroots public services, where shortages in manpower make large-scale, personalized services challenging. We have collaborated with the customer to help over 6,000 villages in China improve public services, offering citizens more personalized and efficient support. Since the large-scale launch of this service in April, its daily usage has surged over 15-fold to more than 2 million times per day, helping locals handle tasks such as household registrations, social security inquiries, and tax declarations. Internally, we have accelerated the renovation of Baidu Search with Ernie, significantly enhancing our consumer-facing products at large scale. Generative AI is transforming user search experience, pushing beyond traditional boundaries. Since the second half of last year, we have been testing early powered features on a small scale. This quarter, our focus has shifted to substantially amplifying search capabilities with advanced AI features. Currently, 18% of search result pages contain generated content, up from 11% in mid-May. This AI generated search results deliver more accurate and direct answers, enhancing content quality, and providing previously unattainable information. This improvement has led to increased user satisfaction and engagement, as more users are now turning to Baidu Search for more complex queries, increasing Baidu Search's versatility. AI-generated search results may reduce ad impressions and therefore have a negative short-term impact on monetization, but they provide significant value to our users. By prioritizing long-term user experience over immediate revenue and profits, we see the strategic implementation of generative search as essential to driving future success. AI investments are fostering deeper user interactions. New interactive features enable users to refine their questions through multi-round conversations, enhancing the overall user experience. Additionally, there is a significant increase in users utilizing text and image creation tools within search. This development open doors for long-term value creation. Last quarter, I mentioned that we planned to accelerate the distribution of earning agents. So far, we have seen more and more developers, advertisers, and partners gather on our platform to develop innovative AI agents. Earning agent distribution within Baidu increased dramatically in July. exceeding 8 million daily, more than double the number in May. Currently, the most frequently used agents by users are for content creation, personal insights such as personality testing, and tools such as translation and schedule planning. At the same time, we also see a trend of earning agents being more widely developed and applied both internally and externally. Our first college application assistant agent is one example of how early agents are being distributed within Baidu to assist users with complex problem solving and decision making. Every year after China's National College entrance examination, Selecting universities after checking exam results is crucial for the 10 million plus candidates. In June, Baidu launched an innovative college application assistant agent, which is designed to meet personalized needs for selecting universities and majors. Following the national college entrance exam, the peak daily active users of the agent approached 2 million, highlighting its significant impact and utility. While all these new features for more sophisticated user needs have not yet been monetized, they are a transformative force for search and are crucial for our future success. This strategic focus positions us to capture substantial long-term growth opportunities. transforming the usage of search and solidifying our leadership in the AI-driven search landscape. Our one-stop shop for document creation is another example of how Baidu scales AI to address real-world problems and generate substantial value. As our most pioneering internal product to embrace generative AI and LLMs, Baidu Wenku is now reaping the benefits of its product renovation efforts. In the second quarter, Wenku's subscription revenue marked a year-over-year increase in high teams. AI is rejuvenating the platform with comprehensive content understanding and generation capabilities, while continuously improving in versatility. Since May, Baidu Wenku has launched new features resonating particularly well with young users, such as crafting lengthy documents with tens of thousands of characters, building and editing PowerPoint presentations, and creating children's picture books with natural language guidance. The heightened engagement underscores Wenku's appeal to the next generation and signals promising future growth. Moving from the digital realm to addressing changes and scaling AI in physical world, our decade-long dedication to autonomous driving innovation and longstanding investment is bearing fruit. ApolloGo, our autonomous ride-hailing service, has recently achieved two significant breakthroughs. It's establishing a robust foundation for making commuting more affordable and benefiting more people through technological innovations. First, since June 19, building on our proven track record of safe operations, ApolloGo has successfully transitioned to offering 100% fully driverless ride-hailing services in practically the entire Wuhan municipality. This means all vehicles are now operating without the need for human safety officers on board, a major step forward in making autonomous ride-hailing business commercially viable. Another milestone was the large-scale open-road testing of our sixth generation autonomous vehicle, the RT6. Equipped with a battery swapping solution, RT6 is competitively priced at below $30,000 for mass production. After thorough testing, we plan to officially roll out RT6 into our fleet establishing a strong foundation for further substantial cost reductions in our public operations. All in all, our efforts to scale AI to solve real-world problems fully align with our broader vision of creating a more efficient, equitable, and sustainable future. Looking at how our efforts are yielding promising results, we believe we are well positioned to capitalize on the growing demand for AI-driven applications. By leveraging AI to address complex challenges, we can continue our journey of innovation and growth, and create long-lasting value for our stakeholders. I want to thank our employees for their effort and contribution, and our customers and shareholders for their trust in us. Now, let me re-ask the key highlights for each business for the second quarter. AI Cloud revenue reached RMB 5.1 billion, marking a consecutive acceleration to 14% year-over-year growth while sustaining non-GAAP operating profitability in the second quarter. The strong growth is mostly attributable to the following two factors. First, GenAI-related revenue continued its robust momentum, accounting for nearly 9% of our total AI cloud revenue in Q2, up from 6.9% in the previous quarter. As more enterprises integrate GenAI and foundation models into their daily operations They increasingly come to us thanks to our reputation as China's most advanced and cost-effective AI infrastructure provider and our excellent math platform for model training and inference. During the quarter, we further advanced our AI infrastructure management, enhancing our ability to combine GPUs from more vendors for optimal training and hosting of models. This ensures flexibility, reliability, and efficiency, positioning us to capture a larger share of the GPU cloud and LLM market. We also continued to develop a tool case on our mass platform for our customers and partners, enabling the early family of models to deliver a superior price performance ratio. We're proud that our model builder now supports the full model development lifecycle, including data management, fine-tuning, evaluation, optimization, and prompt engineering. A major upgrade has been the introduction of diverse hybrid training data science. spanning from general to specialized industry-tailored data sets. This enables efficient fine-tuning and ensures high performance for industry-specific applications while retaining strong general LLM capabilities. Also, thanks to our continuous refinement to App Builder, the number of AI native apps on our cloud now runs into the hundreds of thousands. These applications span a wide array of industries and scenarios, from online education and e-commerce to public service sectors, and are integrated into both online platforms and smart devices. The second major driver of AI Cloud revenue acceleration is cross-selling of our CPU Cloud services to our GPU Cloud customers. In Q2, we continue to observe an increase in CPU spending among our GPU Cloud customers. We see that our strong brand recognition in GPU Cloud is helping us win businesses in the CPU Cloud industry. With revenue acceleration, AI Cloud business continue to deliver positive non-gap operating profit and improved margins. Legacy Cloud saw margin expansion And GenAI-related businesses are expected to have higher normalized margin compared to the traditional cloud service. Overall, we remain confident in the strong growth outlook for our AI cloud revenue, and we aim to continue generating non-GAAP operating profits going forward. For mobile ecosystem, FibreCourse Online Marketing Revenue declined by 2% year-over-year in the second quarter due to broader macroeconomic challenges, competition, and our aggressive AI-driven search renovation. Key offline verticals such as real estate, franchising, and automobile remained subdued. Despite these challenges, we remain committed to optimizing our operations to maintain both a healthy margin and cash flow while accelerating the AI-made transformation of our products. In Q2, incremental ad revenue from GenAI and LLM enhancements to our advertising system continue to grow quarter over quarter, driven by the ongoing reconstruction of our monetization system and marketing platform. We envision Earning Agent as a compelling opportunity for our ad business. Earning Agent has the potential to revolutionize our traditional CPC model into a more efficient CPS model in the future, as it transitions from pre-sale consultations to catalyzing more direct sales on our platform. Serving as a virtual salesperson, Earning Agent empowers advertisers to provide more personalized content and product introduction, thereby ensuring better presale consultation. Early adopters from the education, legal, and B2B sectors are pioneering early agent and have already seen a notable increase in effective sales leads. We're proud to see that 16,000 advertisers already have their own early agents. which are now being distributed on the Baidu platform. Looking ahead, we believe Ernie Agent is poised to deepen its penetration and broaden its reach across more sectors, unlocking promising potential for our advertising business. And moving into intelligent driving. I mentioned earlier that ApolloGo has made remarkable breakthroughs in Wuhan achieved 100% fully driverless operations in practically the entire municipality, reducing Q2 cost per vehicle by more than half compared to Q2 of last year. On top of that, ApolloGo has started scalable testing of the latest RT6 vehicles on open roads. These two factors are critical milestones in our strategy aimed at reaching UE break-even in targeted cities. In addition to cost reduction, ApolloGo's operations continue to offer more expedient services. In Wuhan, its services is now available to 9 million people. The number of ApolloGo's pickup points at the end of June has increased by over three-fold from the previous quarter, enhancing accessibility and convenience for passengers. The deepening of our operational footprint and increased station density have propelled visualization rate for our vehicles, significantly driving up the daily rides per vehicle and the distance per ride. Nationwide, ApolloGo provided about 899,000 rides to the public in the second quarter marking a 26% year-over-year increase. In July, the cumulative rise provided to the public surpassed 7 million. Even with these milestones, our share in the entire ride-hailing service market is very small. It will take many years for us to reach a meaningful market share in China or elsewhere. Looking ahead, we are committed to providing increasingly affordable, convenient, and safe travel for more passengers and drive long-term, sustainable growth. We will remain resolute in executing on our operational strategy, aimed at boosting efficiency and steering our intelligent driving business towards profitability. In summary, by extrapolating the ongoing progress from leveraging earnings to revolutionize product usage and transform business operations for our users, customers, and developers, and driven by a deep belief in technological innovation, we aim to create value for society and contribute to the greater good. With that, let me turn the call over to Rong to go through the financial results. Thank you, Robin.