Baidu, Inc. Q2 FY2023 Earnings Call

Hello and thank you for standing by for Baidu's Second Quarter 2023 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 the host for today's conference, Juan Lin, Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's second quarter 2023 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 Robin Li, our Co-Founder and CEO; Rong Luo, our CFO; Dou Shen, our EVP, in charge of Baidu, AI, cloud Group, ACG; Zhenyu Li, our SVP, in charge of Baidu's Intelligent Driving. 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. Private Securities Litigation Reform Act of 1995. Forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from our current expectations. For detailed discussions of these risks and uncertainties, please refer to our latest Annual Report and other documents filed with the SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements except as required under applicable law. Our earnings press release and this call includes 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. I'm pleased with our financial performance in the second quarter. Revenue from online marketing increased by 15% year-over-year, reflecting improvement in the advertiser segment. In Q2, non-GAAP operating profit for mobile ecosystem continued to strengthen and AI cloud, once again, delivered positive operating profit. At the same time, we are facing tremendous opportunities in foundation models or more broadly AGI. Today, I would like to share an update on our ongoing business transformation by utilizing ERNIE and ERNIE Bot as well as our achievements in the field. After that, I'll briefly go over the operational highlights for each of our business. Over the past few months, foundation models have captured the imagination of people and businesses around the world. It is becoming increasingly clear that foundation models will fundamentally transform work across the industry, boosting overall productivity and accelerating the wider democratization of AI innovation. Right now, we are in the midst of the rolling period. This is due to the fact that the hard work we poured into generative AI over the years is now beginning to bear fruit. This pivotal and transformative opportunity is setting the stage for Baidu's future success and we couldn't be more excited about it. On product and service front, we're using ERNIE and ERNIE Bot to improve, review and create new offerings. On the product side, we are reinventing our products building AI native apps. Providing search, AI has played an important role for many years in driving innovation and improving user experience, resulting in a consistent increase in the percentage of third quarter satisfied by one-shot search results. It means the first search results displayed on the result page that can provide a satisfactory response to a search query. We're using ERNIE Bot to enhance the search experience, making Baidu search capable of answering complex questions that were previously unanswerable. For example, please prompt a marketing campaign proposal for a smartphone launch event, or what kind of new energy vehicles would be suitable for a family of six with a budget of RMB300,000. ERNIE Bot also enables Baidu's search to assist users with more personalized and in-depth research on a topic or project. The feedback from users who have tested these new features has been positive. Another example of product innovation is Baidu Wenku, where many users search for articles, papers, books or campaigns to create documents of a wide range of topics in many formats. We're currently beta testing an AI assistant feature that can generate customized content for users based on their request. User engagement and retention among Baidu Wenku’s testing users for such a feature show significant improvement. For example, users have doubled their time spent on Wenku after trying out the AI assistant feature, and they are more likely to become paying users. Currently, Wenku has over 100 million monthly active users, and we believe such an intelligent feature will help Wenku attract even more users and convert non-paying users to paying users once it is rolled-out on a larger scale. Generative AI offers broad horizons for our online marketing business and we are actively using the technology to build and review our marketing products. Actually, our online marketing business has relied on AI for years to provide more value to advertisers. Last quarter, we shared our progress on using the AIGC to automate ad creation in text format, which led to an increase in conversion rates. This quarter, we further enable advertisers to use AIGC to generate images and video apps with natural language. In Q2, we further improved our monetization system by leveraging generative AI to broaden ad campaign keywords to user search queries, driving better monetization for advertisers. For example, an online professional education company's ad conversion increased by about 16% in August after using these new features. We are consistently enhancing our system by using generative AI and we expect to introduce more and more new features in the coming months. Additionally, we have been leveraging generative AI to enhance our auction system, so that it can better match ads to search queries and search intent. Such improvement helped increase Baidu search ECPM in Q2 and contributed to the year-over-year growth in online marketing revenue in the quarter. We are also in active conversations with advertisers to get their input on how to further make our marketing products work best for them. Meanwhile, we will continue to leverage ERNIE and ERNIE Bot to help advertisers create sophisticated ad campaigns and improve ROI on Baidu. One other initiative I'd like to mention here is that internally, we introduced an AI assistant within our info flow, Baidu's self-developed enterprise communication and collaboration platform. The AI assistant automates various workflows such as summarizing meeting notes, chat history and workplace content, drafting documents, generating drafts, facilitating knowledge Q&A, and completing tasks such as creating meeting invites, applying for vacation days, and conducting data analysis using natural language. This assistance helps our employees work more productively. We plan to open up the intelligent features of info flow to our customers in the future. Alongside our own products, we are empowering cloud customers to build their transformative products and services using ERNIE Bot. In Q2, the number of corporates connecting to ERNIE Bot continued to grow. Foundation models, large language models and generative AI are expanding our total addressable market, attracting new customers while also increasing sales to our existing customers. We are also using ERNIE and ERNIE Bot to help customers in various industries address real-world challenges with unprecedented effectiveness and competence. This further strengthens the capabilities of ERNIE and ERNIE Bot, empowering them to take on more significant roles in solving industry-specific issues. For example, in the software development industry, we launched Baidu Comet, an AI coding assistant to the public in June. By the Comet, people in coding can be used in multiple programming languages. It has now been widely adopted by Baidu's own R&D team. Who have reported a meaningful improvement in their productivity after using Comet. As of today, more than 100 organizations have tested the Comet, and some of them have already decided to purchase Baidu Comet to boost productivity in coding. In the healthcare industry, we are solidifying our presence by utilizing industry expertise and sales networks developed through our collaboration with leading hospitals in China. Chongqing has limited a traditional Chinese medicine clinic chain using our early-based model developed for the healthcare industry to support doctors and their patient care. Our AI assistant helps doctors write notes for patients, analyze medical images and make informed clinical decisions among other tasks. It also helps patients find the most suitable doctor and department and provides pre-consultation service online. Furthermore, we've developed tools for model training and fine-tuning, data processing, labeling and more. These tools help to lower the threshold and cost for enterprises to use foundation models on Baidu and support them to train and operate their purpose-built models efficiently. Additionally, Baidu AI cloud stands out as our AI-optimized cloud infrastructure makes us a top-performing platform for training and serving foundation models, including large language models. This is why more and more enterprises are upping their digital spend on our cloud infrastructure to capture the new AI opportunities. This is particularly obvious among Internet and tech companies as they are early adopters of generative AI and foundation models. Shifting our focus to technology, as Baidu we maintained an unwavering commitment to improving earnings. During Q2, we unveiled ERNIE 3.5, our latest state-of-the-art foundation model powered by PaddlePaddle. Notably, PaddlePaddle enhancements enabled our self-developed four-layer AI architecture to operate more seamlessly than ever before. Significantly improving the framework's compatibility with ERNIE and demonstrating engineering excellence. As a result, compared to ERNIE 3.0 in March, ERNIE 3.5 passed triple training throughput and its queries per second, or QPS, for inference has increased by more than 30 times. Additionally, I'm proud to note that IDC recently reported that ERNIE 3.5 surpassed peers in many areas such as algorithm, industry coverage, developer tools and ecosystem. As compared to ERNIE 3.0, 3.5 is capable of producing safer, more responsible, and more creative responses, making significant improvements in question answering, reasoning, and coding. ERNIE 3.5 is now powering ERNIE Bot, with plugins to expand its functionality to cover real-time and precise information, long text summaries, data analysis and visualization, text-to-video conversion, and facilitate pilot dialogues that include images. We are committed to enriching our ecosystem by adding more high-quality plugins, particularly from third parties, to contribute to the advancement of China's foundation model. On the ecosystem front, we are determined to make ERNIE the most popular foundation model in China. Importantly, we believe foundation models should be able to support problem-solving capabilities for various industries well. As a result, we need to work collaboratively with our partners such as enterprises and AI developers to continually build industry models and solutions. Our 8 million developers on PaddlePaddle are the anchor that we can leverage to build a community for ERNIE. To foster a vibrant ecosystem, we hosted the Baidu ERNIE Cup Innovation Challenge. It attracted almost 1,000 startups to submit their ideas and prototypes, covering various fields, encompassing productivity towards developers, sales and marketing companies, entertainment companies, social platforms, middleware developers, as well as applications across different industries, including education, healthcare, finance, etc. We have also launched a venture fund of RMB1 billion to support startups in developing all kinds of AI-native applications, which will complement our organic growth. On regulation, Baidu was recently appointed as a leader of China's LLM Standardization Task Force at the World AI Conference. This position signifies national-level recognition and endorsement of our foundation models and AI capabilities. While we are still waiting for the green light for large-scale rollout of ERNIE Bot, we have observed that the Chinese government has been increasingly supportive of the development opportunities of AI and LLM. As a market leader, we believe Baidu is well capable of benefiting from the opportunity and contributing to this mega trend in China. Now let's have a quick look at the second quarter operating highlights for each business. Revenue from AI Cloud increased by 5% year-over-year to RMB4.5 billion in the quarter. And AI Cloud maintained positive non-GAAP operating profit. Our business has become healthier than ever, laying a solid foundation for future growth. On intelligent driving, in Q2, the rights provided by Apollo Go increased by about 150% year-over-year to around 714,000, resulting in accumulated rides exceeding RMB3.3 million, which is greater than our closest competitor by order of magnitude. This leadership in operation implies competitive advantages in data quantity and quality, better models, and greater safety ratings. In addition, Apollo Go has widened its footprint in fully driverless ride-hailing services in more settings. In mid-June, Apollo Go received a permit from the Shenzhen Pingshan government to offer 40 driverless ride-hailing services to the public. In early July, in Shanghai, we were allowed to conduct fully driverless testing on open roads as well. With the expansion of the area and fleet size for fully driverless operation along with the improvement of operational efficiency, we witnessed growth not only in the total average daily orders, but also in the portion of fully driverless orders within the overall order portfolio. This highlights a promising pathway for improving the unit economics of autonomous driving. In particular, in Wuhan, where we initiated fully driverless ride-hailing services one year ago, the unit economics continued to improve in the past few quarters. On the revenue side, the average daily order volume and revenue per order have surged, propelling total revenue to grow. Meanwhile, the cost per kilometer per car is decreasing as well, thanks to improved operational efficiency. Finally, on our mobile ecosystem, our users continue to grow with Baidu Apps, MAUs increasing by 8% year-over-year to RMB677 million in June. Also in June, videos distributed by Baidu App achieved double-digit growth year-over-year. Baidu remained a significant platform for users seeking a wide range of content such as information, products, and services. The revenue growth rate for online marketing accelerated in Q2 aided by strengths in wireless verticals with offline exposure, including healthcare, business services, local services, and travel. At the same time, revenue from e-commerce demonstrated strength and outperformed in the quarter. Non-GAAP operating profit for mobile ecosystems grew steadily year-over-year in the quarter. The mobile ecosystem continued to generate robust cash flow to fund our investments in AI, particularly in foundation models and generative AI. We are confident that revenue, profit, and cash flow generated from our mobile ecosystem will remain strong in the future. With that, let me turn the call over to Rong to go through our financial results.

Thank you, Robin. Now let me walk us through the details of our second quarter financial results. Total revenue was RMB34.1 billion, increasing 15% year-over-year, revenue from Baidu Core was RMB26.4 billion, increasing 14% year-over-year. Baidu Core's online marketing revenue was RMB19.6 billion, increasing 15% year-over-year. Baidu Core's non-online marketing revenue was RMB6.8 billion, up 12% year-over-year. In Q2, AI cloud revenue increased by 5% year-over-year to RMB4.5 billion. Revenue for IT was RMB7.8 billion, increasing 17% year-over-year. Cost of revenue was RMB16.2 billion, increasing 7% year-over-year. Baidu Core's cost of revenue was RMB10.6 billion, increasing 4% year-over-year. Operating expenses were RMB12.7 billion, increasing 14% year-over-year, primarily due to an increase in channel spending, promotional marketing expenses, server depreciation expenses, and cloud-related expenses, which support ERNIE Bot research, improved and partially offset by a decrease in personnel-related expenses. Baidu cost operating expenses were RMB11.3 billion, increasing 15% year-over-year. Baidu Core SG&A expenses were RMB5.3 billion, increasing 34% year-over-year. SG&A accounted for 20% of Baidu Core revenue in the quarter compared to 17% in the same period last year. Baidu Core R&D expenses were RMB5.9 billion, increasing 2% year-over-year, accounting for 23% of Baidu Core revenue in the quarter, decreased from 25% the same period last year. Operating income was RMB5.2 billion, Baidu Core's operating income is RMB4.6 billion, and Baidu Core's operating margin was 17%. Non-GAAP operating income was RMB7.3 billion, and non-GAAP Baidu Core's operating income was RMB6.5 billion, with a 25% operating margin. Total other income was RMB1.4 billion compared to RMB151 million in the same period last year, primarily due to the increase in net foreign exchange gain and net interest income, partially offset by the increase of fair value loss from long-term investments. The income tax expense was RMB1.3 billion, compared to RMB25 million in the same period last year. The lower level for income tax expenses in the second quarter of 2022 is primarily due to the reversal of certain tax expenses based on the 2021 tax return. Apart from the reversals, the main reason for the increase in income tax expenses is the increase in profit before tax year-over-year. Net income attributable to Baidu was RMB5.2 billion and diluted earnings per ADS was RMB14.17. Net income attributable to Baidu Core was RMB5 billion and net margin for Baidu Core was 19%. Non-GAAP net income attributable to Baidu was RMB8 billion, non-GAAP diluted earnings per ADS was RMB22.5. Non-GAAP net income attributable to Baidu Core was RMB7.7 billion. Non-GAAP net margin for Baidu Core was 29%. As of June 30, 2023, cash, cash equivalents, restricted cash and short-term investments were RMB201.5 billion in cash, cash equivalents, restricted cash and short-term investments excluding iQIYI, RMB196.9 billion. Free cash flow was RMB7.9 billion, and free cash flow excluding iQIYI was RMB7.1 billion. Baidu Core had approximately 35 solid employees as of June 30, 2023. With that, operator, let's now open the call to questions.

Thank you. We will now begin the question-and-answer session. The first question today comes from Alicia Yap with Citigroup. Please go ahead.

Hi, thank you. Good evening, management, thanks for taking my questions. Congrats on the solid results. So can management provide an update on the current state of the advertising industry, including how online and offline platforms are recovering? Can management also share about the pace of recovery for key industry and which ones have stronger seasonality? And then in addition, can management also discuss the main drivers for growth in this industry? Finally, what are the medium-term growth targets for advertising as we are now already behind the pandemic and with the current latest macro situation? Thank you.

Hi, Alicia, this is Robin. Let me answer your question. Our online marketing revenue increased by 15% year-over-year last quarter. A number of factors contributed to this growth. On the vertical side as we are coming out of the pandemic, many offline verticals like healthcare, business services, local services, and travel continue to outperform. For example, in healthcare, we saw solid year-over-year growth in both search queries and ECPM, which lead to revenue trends. We think this momentum will continue. The offline sector contributes a sizable amount to total online marketing revenue for Baidu. Meanwhile, e-commerce continues to grow in Q2 and remains a top revenue contributor. In markets like e-commerce, it's highly competitive, so more and more merchants are realizing the value of Baidu, and they come to us to acquire new users and buyers and invite their existing buyers to come back and buy more. For the second half of the year, we should continue to see a clear recovery trend for our online marketing business. Also remember, search remains the most effective form of performance-based advertising. This is because users approach search with clear intent, and search ads allow us to connect this intention directly with the most relevant product and service offerings. In fact, the ECPM for our search outgrew other ad formats in the quarter, reflecting the effectiveness. Due to the relatively high comp base in Q3, the growth rate might not be as high as Q2, but it should well outperform China's GDP growth. Additionally, we have more immersive video features. More and more users are watching short videos on Baidu. Short videos distributed through the Baidu App again grew by double-digit in Q2. As a result, revenue from short videos continues to grow quite well, contributing meaningfully to the overall online marketing revenue growth. Looking into the mid- to long term, I believe both user traffic growth and monetization upgrades are important growth drivers for our online marketing business. And on the user side, I talked about our MAUs; it grew by 8% year-over-year in Baidu App growth rate in June. If we look at search, we are renovating the Baidu Search step-by-step using ERNIE Bot. We believe it will provide users with an innovative and intuitive experience, which will help our mobile ecosystem gain traffic and increase user time spent. And on the monetization side, we've been leveraging AI to improve ad targeting capabilities and our bidding system for a number of years. Now with ERNIE and ERNIE Bot, we are further upgrading the game. I mentioned earlier that we have made some major improvements in advertising technology by using LLM and Generative AI. Along with more innovative and personalized ads, I believe there is lots of room for growth in this aspect, and I look forward to further breakthroughs. Such improvements in monetization technology have started to contribute to revenue and ECPM growth starting from this quarter in Q3. Thank you.

The next question comes from Gary Yu with Morgan Stanley. Please go ahead.

Hi, thank you for the opportunity to ask a question and congrats on the solid set of results. I have a couple of questions related to AI product and monetization. First, can management share some insight on how users have responded to the integration of ERNIE Bot in multiple products? Any new developments of features that have come up with the ERNIE Bot offerings that help with market growth in the China Internet and specifically in the mobile Internet sector? And also, lastly, I would like to know more about the monetization aspects and how they play a role in your advertising business? Plus, I would like an update on key industries and use cases related to the business side. Can you provide additional information on the business model and also potential revenue? Specifically, I would like to gain a better understanding of the financial impact on cloud performance.

Hi, Gary, let me answer the consumer-facing products part of your question, and I'll have Dou talk about the enterprise side, especially the cloud business. I think it's clear we are in a paradigm shift in our business with our early commitment to AI; we saw this time coming. We are reinventing our consumer-facing products with an AI-native mindset. As I mentioned in my opening remarks, we are rebuilding our search experience. Users who are testing our ERNIE Bot-enabled Baidu search and Baidu App tend to ask more questions that were not frequently searched in the past and we tend to have multi-round conversations and interactions. This is quite different from the user behavior for traditional search. Therefore, it's an incremental business for us. We are using generative AI to construct direct answers to user queries. This typically creates better and easier to understand answers than text from existing web pages. We see increases in click-through rates and user retention rates for these kinds of changes. We also launched the testing version of the ERNIE Bot App, a step along app that is built upon our latest generative AI and LLM. It aims to serve users as a personal assistant. We see ERNIE Bot as a potential new traffic gateway that can connect users to various applications, including Baidu and other third-party applications, to address users' needs. We also launched ERNIE Bot plug-ins like search and chat. Developers will soon be able to submit their applications as ERNIE Bot plug-ins. For Baidu Core, the AI assistant feature on average user time spent more than doubled and the seven-day retention rate has increased by almost 10%. With the AI assistant, I will not be surprised if we can convert more users into paying accounts and charge a premium for the new AI functions in the future. Overall, we are highly encouraged by user feedback. This is just the beginning for us to reconstruct all the products and businesses with LLM and Generative AI. Very importantly, we have also seen promising opportunities to lift the monetization capability by rebuilding our advertising system. As I mentioned in the prepared remarks, ERNIE and ERNIE Bot allow us to continue improving our targeting and bidding system. All in all, I believe that generative AI will help us gain market share of many products and ultimately become a new growth driver for our online marketing business.

Gary, for your second part. So for the impact on our cloud business, I would first mention that the beauty of the foundation model and Generative AI is that it can help organizations in many industries to increase productivity and efficiency. We see more and more enterprises willing to adopt such latest AI technologies and that’s why we will say the new technology is increasing our demand. Specifically, ERNIE and ERNIE Bot have been helping our customers from different industries to handle their business challenges more effectively, ranging from software, Internet, healthcare, education, brand finance, and even to the public sector. So they use ERNIE and ERNIE Bot to train models, build applications, and improve solutions for efficiency gains, such as improving their customer service, producing different kinds of content, providing knowledge searches within their organizations, as well as increasing their sales and marketing efforts. As to the business models you just asked, I think it's still at its very early stage, and it's evolving. We have our preference, but we are pretty open and want to take any effort to speed up the growth of generative AI. So in addition to providing AI computing infrastructure to our customers, we also consider charging customers for the usage of ERNIE and ERNIE Bot or using our AI applications. We can also charge our customers for retraining or operating their own models on our platform or we can deploy the foundation models to our customers' private cloud on a project basis. We expect the revenue generated from such new opportunities to be gradual, but we believe the long-term potential is significant. So we'll continue to invest in ERNIE and ERNIE Bot to serve our customers well for the long term. That's it, Gary.

The next question comes from Lincoln Kong with Goldman Sachs. Please go ahead.

Thank you, management, for addressing my question and congratulations on the quarter. My question is regarding the cloud business. Could management explain the main reason for the revenue slowdown in the cloud segment this quarter? When do we anticipate the revenue will begin to pick up and accelerate again? Looking ahead to the second half of 2023, what is the expected trajectory for revenue growth? What factors will influence this? Additionally, I am interested in whether the profit breakeven at a non-GAAP operating level is sustainable, and what the current trend is for AI cloud profitability.

Okay. Thank you for the question. I'll take it. So cloud revenue grew 5% year-over-year in Q2, and we continue to generate profit on a non-GAAP operating level. This means that our business is becoming healthier, laying a solid foundation for sustainable growth in the future. The growth rate was mainly dragged by government-related projects, which took longer to recover after the pandemic. However, many enterprise-related products in key verticals like manufacturing, utilities, and internet services have demonstrated quite solid growth in Q2. As I just mentioned before, we see strong interest from existing and new customers in Generative AI, so while some of them directly leverage ERNIE or ERNIE Bot to enhance their products to improve operational efficiency. Some of them actually choose our AI infrastructure as the foundation for their models and applications. Though it may take a little while to see significant revenue contributions, this opens up a very new space for our cloud business where we're already in a leading position. So on the profit side, we believe we can keep generating operating profit from AI Cloud as we did in the previous quarters. This indicates that actually our business is becoming increasingly healthy. We are going to keep standardizing our AI solutions that can effectively address AI critical pain points and then replicate them from one project to another, which will further grow the margin and profit.

The next question comes from Kenneth Fong with Credit Suisse. Please go ahead.

Hi, good evening management. Thank you for taking my questions and congrats on the solid quarter results. I have a question regarding generative AI, regarding the recently introduced interim measures to regulate generative AI service by the government. Could you provide insight into whether this suggests an imminent authorization of the large language models? Additionally, do you have a projected timeline for the rollout of the applications utilizing these models? Thank you.

Thank you for your question, Ken. We're seeing the government continue to support tech innovation, including AI and foundation models. I think a good sign of this is that the new guidelines and specifications that came out in mid-July about how to use generating AI technology and related services in China. This is a new version, and it went into effect, I think, on August 15. Compared to the previous version, this version is more of co-innovation than regulation. We are still waiting for the green light for the large-scale rollout of ERNIE Bot for its use in consumer-facing applications. But as I said before, the government has increasingly recognized ERNIE and ERNIE Bot, which we believe provides a good foundation for the eventual release of ERNIE Bot on a large scale. Generative AI is pretty new, and it's understandable that people might have concerns about things like user privacy, IP protection, and AI ethics, so there should be certain regulatory requirements in place. At Baidu, we have accumulated extensive experience in providing appropriate information to the vast amount of Internet users. We are a leader in not only AI technology for commercial purposes but also in using AI for good. In fact, we are working closely with the regulators and other organizations to push the development and proper usage of generative AI. So we believe we are well positioned to benefit from this opportunity and contribute to this mega trend of generative AI in China. While we don't have an exact date for everything, the trend is very promising, and we are quite optimistic about the future of a better regulatory environment.

The next question comes from Wei Xiong with UBS. Please go ahead.

Hey, good evening management. Thank you for taking my questions and congrats on the solid results. My question is also related to the foundation model. How can we assess Baidu's foundation model's performance compared to other Chinese peers? How should we perceive the balance between industry-specific models versus foundation models when thinking about the future AI landscape? Now we have more companies offering or focusing on models tailored to specific industries. How does management perceive the landscape in terms of opportunities and competition? What are our competitive edges? Thank you.

These are very good questions. When it comes to foundation models in China, ERNIE 3.5 clearly stands out. People have witnessed the fast iteration and improvement over the past five to six months. Our unique full-stack AI capabilities differentiate us from our competitors and give us an edge in the market. As mentioned in my prepared remarks, an IDC report recently published named ERNIE 3.5 as a leader across various metrics. Like many other technologies, the speed of innovation for foundation models depends on the application that uses the model. Baidu is an AI company with a strong portfolio of Internet products, and these products are all being reviewed and reconstructed with ERNIE Bot, driving the innovation of ERNIE in the right direction. In our work, we know what kind of problems to solve. I think many other peers don't really know; they just open domain testing sets to evaluate the effectiveness of their models. We also have tens of thousands of cloud customers testing our ERNIE Bot. They provide valuable feedback that propels improvements too. As for the industry-specific models you mentioned, they should be built upon the most powerful foundation model. I think that with time, foundation models are rapidly evolving given their strong capabilities to learn new subjects and gain industry insights. Stand-alone industry-specific models will have a hard time keeping up with the pace of innovation. Since ERNIE 3.5 became available, an increasing number of customers have told us that ERNIE 3.5 is visibly more advanced than ERNIE 3.0 and has helped them solve a growing number of pain points. We are working towards ERNIE 4.0 and should launch it by the end of the year. I believe that ultimately, only a select few companies will reach this level of advancement for foundation models, and Baidu will be one of them. During this transitional period, we are focused on multiple initiatives to drive the adoption of the foundation model. We’re working hard to build early applications and solutions for different industries as exemplified by Baidu Comet. With the upgrade to ERNIE 3.5, we are swiftly rolling out to empower enterprises to create industry-specific models and applications that tackle their own challenges. We also offer a mass platform, which includes not only ERNIE but also a variety of models. This allows businesses to easily view, fine-tune, and operate their own models using their own data. We provide a set of valuable tools on our platform, enabling our customers to enhance their model training and application development. Of course, enterprises can directly access ERNIE's capabilities through API to enhance their businesses. Recognizing that in the early stages, enterprises prioritize security; we do provide flexibility in using our foundation model services on both public and private clouds. Our self-developed four-layer AI architecture is our core competitive advantage because we deliver better model performance to our customers, as shown in testing phases over the past few months. Our strength lies in model training efficiency and cost-effectiveness, attracting more enterprises to partner with us. We gain more industry know-how and insights, building a reinforcing positive cycle to further improve ERNIE. Our ultimate goal is to cultivate an AI-native ecosystem centered around ERNIE. We believe that the true power of the foundation model lies in driving a wide array of high-quality AI-native applications, much like an operating system. Some of the applications are built by us, while most will be built by our ecosystem partners to address industry-specific challenges. To enhance this ecosystem, we're happy to invest in other companies to complement our organic growth. Just as I mentioned in the prepared remarks, we hosted the Baidu ERNIE Cup Innovation Challenge and launched a large venture fund to support startups in developing all kinds of AI-native applications. To sum up, we will continue to improve ERNIE, making it easy to use, and help enterprises in any industry to retain or fine-tune models on top of ERNIE, but more importantly, leverage ERNIE and ERNIE Bot to develop their own applications. We aim to make ERNIE the preferred choice among AI developers, so that more applications will be built upon ERNIE and make our ecosystem vibrant.

The next question comes from Miranda Zhuang with Bank of America. Please go ahead.

Thank you. Good evening, management. Thanks for taking my question. Recently, open source AI models have attracted significant market attention. Could management provide your insights into Baidu's perspectives on this front and the strategy regarding open source versus closed AI models? Thanks.

Thank you, Miranda. This is a very interesting question. I believe there are quite different views on this. I think both open source and closed source foundation models will coexist for a while. In fact, we have already seen many models trained on top of the open-source foundation models powering tons of applications even today on our cloud platform. However, it's really tough for our open-source foundation models to keep evolving and getting better due to the lack of effective feedback loops, which play a super important role in improving the foundation models. Additionally, building and upgrading foundation models can be very expensive. It is important to build a durable business model to fund the sustainable improvement of the foundation models so that they can finally provide long-term value to the market. For us, it’s our priority that ERNIE keeps evolving quickly and remains the market leader, attracting more customers to use our platform to create innovative apps and improve their business. With feedback from real-world scenarios, we can further improve our foundation models. Looking ahead, I believe there will be a limited supply of advanced foundation models, whether open-source or closed-source or even industry-specific available in the market. As we just discussed, as the industry progresses, enterprises will need advanced models to develop more sophisticated applications, but ERNIE will be one of the few foundation models that can satisfy those evolving demands in the long run.

The next question comes from Alex Yao with JPMorgan. Please go ahead.

Thank you, management for taking the question and congrats on the strong quarter. I have a couple of questions on the margin outlook. Considering the opportunities of AIGC and large language models, how should we think about the investment trajectory for the second half of this year? Additionally, once we start large-scale rollouts, what direct costs will be incurred, and how should we compare the margins of ERNIE Bot or large language model-related products to the existing businesses like search, etc.? More broadly, could management also provide directional color on the trend of Baidu Core margins as we look into the second half of this year after the significant cost reduction and efficiency improvements implemented last year? What will be the key drivers of profit moving forward? Thank you.

Thank you, Alex. Let me take your questions. This is Rong. I think previously, Robin has already talked about a lot of our opportunities with ERNIE and ERNIE Bot. So in the first place, I would like to reiterate that we are highly committed to long-term investments in these promising areas. To support the fast upgrade of our services, we have invested in compensation infrastructures. If you look into our cash flow statement, you probably can see that Baidu's capital expenditures in Q2 have increased year-over-year. The increase is mainly due to hardware purchases to support the training and iterations of all AI campaigns such as ERNIE and ERNIE Bot. But the impact on the income statement side is quite manageable, because such hardware depreciations will generally spread over the next few years, and the impact on near-term profitability is not substantial. The investment is expected to continue and the magnitude of the future investments will be highly correlated to the pace of actual business expansions rather than only supporting the model training, which means that in the near future, the spending will be sponsored by the incremental revenue generated from our ERNIE Bots and will formulate our positive virtual cycles. Regarding the margins for the financial model and related products, I believe it's a little bit early to discuss at this current stage as the business model is still evolving. As Robin mentioned earlier, search advertising could become more customized, resulting in increased ROI for advertisers. The additions to cloud services, as Dou just spoke about, will improve various industries and enhance efficiencies across different sectors. From a long-term perspective, we believe that customers will be increasingly motivated to leverage our services to enhance their efficiencies, increasing our pricing power and resulting in higher margins, as compared to the current cloud business. If we look into the second half of this year for the mobile ecosystem, we will continue to serve as a cash cow for the group in the long run. Our goal for mobile systems is to consistently achieve high margins. For the AI cloud side, we aim to achieve profitability on a non-GAAP operating level and improve margins over time. For intelligent driving, while we firmly believe there's a huge long-term opportunity, we will continue to ensure we invest and measure pace. As a whole, our main focus is on developing a sustainable growth strategy for each business that prioritizes long-term thinking. In addition, we plan to invest in ERNIE and ERNIE Bot to take advantage of the huge opportunities presented by the foundation models.

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

Good evening. Thanks, management for taking my questions and congratulations on the strong results. I have two questions. The first is about our Robo taxi business. Management mentioned that the unit economics in some cities are improving. Could management share the logic and the efforts taken behind it? What are your plans regarding city expansion and the volume market for fully driverless operations in the upcoming quarters? In addition, when can we expect the Altice 6 vehicle to be launched? What's the projected size of the vehicle fleet for this year? And how could it potentially impact the cost? My second question is on Auto Solutions, which vehicle models will hit the road in the latter half of this year and next year? How should we size up the financial impact on the books?

Thanks for the attention. This is Robin. I will start with the Robo taxi section. Our autonomous taxi service is rapidly gaining traction in major cities, providing valuable data that is instrumental in enhancing our driver technology. This data is critical for improving efficiency and the overall experience of our operations. As a result, we have received strong interest from both customers and regulators, enabling us to expand into new locations and significantly increase ride numbers. This positive feedback regarding our large operations has also driven improvements in our models, which in turn drives the expansion of our operations, putting us at the forefront of the global autonomous driving technology landscape. On the logic behind the improvement, I would like to take Wuhan's operation as an example. We have continued to scale up service in Wuhan over the past year. If you compare the situation from one year ago, you may note that, firstly, our fully driverless fleet has expanded significantly, growing from five vehicles a year ago to almost 200 in August this year. Secondly, the operational area for free service has expanded about fifteen-fold in Wuhan. Meanwhile, our operation has further expanded, covering both morning and evening, as well as late-night operations. Certainly, we are now serving more passengers per trip, becoming one of the largest providers of fully driverless services in the world. The proportion of fully driverless orders compared to all our operations has increased from 10% last August to 55% in July this year. All the progress contributes to the improvement of our unit economics. Looking ahead, we will continue to focus on enhancing operational intensity and average revenues in cities like Beijing and Wuhan to further expand the fleet size and operational area of driverless operations, thus improving unit economics. Next year, we aim to enter into new markets to conduct fully driverless ride-hailing services and expand the scale of fleet drivers for commercial operations. The timeline for the launch of the Altice 6 vehicle is proceeding as planned. It brings us significant cost advantages, with mass production costs lowered by 50% compared to the previous generation. This will greatly improve our operational economics, pushing us closer to profitability. Last, regarding our Auto Solutions business, we are currently providing advanced driving products to meet safety and performance standards, catering to consumer demand for convenience and efficiency. The competition in China's EV market has led to a general decline in profitability, with OEMs softening their demand for integration and leaning towards cost-cutting measures which have affected and is expected to impact our automotive solutions in the short term. However, we believe that we have a huge market opportunity ahead in the long run, driven by consumer demand for intelligent driving. We plan to launch our safety navigation pilot product, Apollo safety driving, to the market later this year. In conclusion, we believe that changes in the auto industry are heading towards intelligent driving, presenting exciting opportunities for the future, and we will capitalize on this change with cutting-edge technologies and sensible business models. Thank you.

This concludes our question-and-answer session and does conclude our conference for today. Thank you for participating. You may now disconnect.