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Q3 2023 Earnings Call
Nov 21, 2023, 7:30 a.m. ET


Prepared Remarks Questions and Answers Call Participants

Prepared Remarks:


Hello and thank you for standing by for Baidu’s third 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 your host for today’s conference, Juan Lin, Baidu’s director of investor relations.

Juan LinDirector of Investor Relations

Hello, everyone, and welcome to Baidu’s third 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; and Dou Shen, our EVP in charge of Baidu AI Cloud Group, ACG. 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 SEC and Hong Kong Stock Exchange.

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Baidu does not undertake any obligation to update any forward-looking statements except as required under applicable law. Our earnings press release and this call include discussions of certain unaudited non-GAAP financial measures. Our press release contains a reconciliation of unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and available on our IR website at 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.

Robin LiCo-Founder and Chief Executive Officer

Hello, everyone. Baidu Core delivered solid revenues, profits, and cash flow in Q3 despite navigating in a challenging macro climate for both our online marketing business and AI cloud business. I’m proud that our team managed to strengthen operational efficiency and maintain stable margins amid a full-scale reinvention of our product portfolio with ERNIE and ERNIE Bot. Today, I would like to share an update on the new opportunities that ERNIE and ERNIE Bot have opened up for us.

After that, I will discuss some key highlights of each of our businesses. Presently, we are in the midst of a broad-based platform shift, driven by generative AI and foundation models that is set to revolutionize every industry. On August 31st, we received the approval to deploy ERNIE Bot on a large scale and open ERNIE API to enterprise customers. Since then, we’ve witnessed a significant increase in queries handled by ERNIE Bot and through ERNIE API.

Moreover, we’ve received valuable feedback from these users and customers, enabling us to further refine our model’s performance. At Baidu World in October, we showcased our progress in ERNIE Bot and AI-native products. During that event, we introduced ERNIE 4.0, or EB4, our most advanced foundation model. We believe that EB4 is a GPT-4 level model, displaying human-level performance in understanding, content generation, complex reasoning, and memory retention.

These capabilities are crucial for developing AI-native applications and solutions. We are pleased to launch EB4 earlier than our expectations. It resulted from our unique end-to-end four-layer AI infrastructure, which helped enhance efficiency in model training. The input and feedback from our users and customers also played a big role.

In products, as I said, in the past, we continued to use ERNIE tools to reinvent our entire portfolio and introduce an AI-native experience. On the customer front, ERNIE Bot enables Baidu Search by generating direct answers to search queries, complementing traditional search. In the quarter, we initiated tests on our new features that recommend news feed-like information together with the generated search results and enable multi-run conversations to encourage further user expression. Our initial tests have received promising feedback.

We believe these features will help deepen user engagement and prolong time spend, unleashing new monetization opportunities. In particular, they benefit as verticals like healthcare, education, travel, legal, and auto, in which advertisers are willing to invest heavily in customer acquisition and reengagement. ERNIE Bot, our new AI-native product, serves as a versatile multi-run conversational AI assistant on both desktop and mobile. Given the exceptional performance of our large language model, we are confident in monetizing our services.

Starting from November 1st, EB4 was opened to the public through ERNIE Bot at a subscription fee of about $8 U.S. per month. This marks us as the first company in China to implement user charges, distinguished us from other models in the market. Our primary focus is to encourage seamless collaboration between users and AI copilots, which we believe is a key trend in the new era.

For example, with an AI copilot, Baidu Wenku has transformed into a one-stop shop for various document creation needs. We have already seen an increase in the paying user count, a trend that we expect to continue in the coming quarters. On the enterprise-facing product front, we recently introduced GBI, Generative Business Intelligence, with ERNIE Bot. GBI simplifies data analysis using natural language interaction, facilitating faster decision-making for business operations.

The introduction of GBI was prompted by the recognition that customers across various industries have the need for AI copilot to help them analyze data more efficiently. During our last earnings call, we also discussed how we use ERNIE Bot to create Baidu Comate, our AI coding assistant; and InfoFlow, our enterprise communication and collaboration platform. These products focused on boosting productivity and efficiency gains, and each of them presents upsell opportunities for our cloud customers. In fact, an increasing number of our cloud customers in China’s traditional industries and public sector have used the trial version and shown interest in these products and features.

Additionally, these products and features also allow us to acquire new customers across an even wider array of industries. In terms of ecosystem, we empower enterprises to leverage learning through API to create their own AI-native applications and solutions that will drive the development of generative AI and LLM. As more and more AI-native applications built on top of ERNIE become successful, whether developed by us or by our customers, ERNIE will likewise be successful. Now, over 10,000 enterprises are actively using ERNIE through API on a monthly basis.

This number has been growing quickly since we received the regulatory green light at the end of August. Currently, ERNIE is handling tens of millions of queries every day. Right now, a large and rising number of these queries come from the Baidu family of products as we have been pioneers in building AI-native products and have put a lot of effort into reinventing our offerings. In the first half of November, the number of daily external queries has increased by over 50% compared to the same period in October.

As we are actively assisting our cloud customers in creating AI-native applications, we believe there will be a continuous and significant rise in external queries in the future. We’re also actively attracting developers to connect their information and services to ERNIE Bot through plug-ins. With plug-ins, ERNIE can help people with more and more tasks, unlocking a wide range of possible use cases. As of today, hundreds of plug-ins have already been accessible through ERNIE.

The initial batch of third-party plug-ins include, CITIC Press Group, China Justice Big Data Institute, New Oriental, Autohome, and [Inaudible]. In summary, during the quarter, we made significant progress in using gen AI to revolutionize product usage and transform business operations for our users and customers. We believe that this is just the beginning. In the future, we are realigning resources to invest in this growth opportunity and shift away from lower priority efforts and improve efficiency for existing businesses, thus balancing investment and margins.

We are excited about the possibilities for Baidu, for our users, customers, partners, and the entire ecosystem. Now, let me recap the key highlights of each of our businesses. Mobile ecosystem continued to exhibit steady growth for both user metrics and financial performance in the quarter. Baidu App’s MAUs increased by 5% year over year to 663 million in September.

Search queries and content distributed by Baidu App remained resilient. In particular, videos distributed by Search and Feed within Baidu App both experienced a double-digit growth in third quarter. Baidu Core’s online marketing revenue increased by 5% year over year in the third quarter, consistently generating strong profit and cash flow for the group. This growth was driven by the continuous recovery in verticals such as healthcare and travel, among others.

In the quarter, we continued to use gen AI to help advertisers increase ROI and conversion on our platform. Starting from September, advertisers can engage with our new marketing platform. This platform supports natural language input and multi-run conversations, which help advertisers articulate their requirements more comprehensively, enabling us to formulate more effective campaign strategies for them. Moreover, we made ongoing enhancements to our monetization system, focusing on improving targeting capabilities and the auction system.

For example, Tarena Education, an IT professional education company, achieved an increase of 23.3% in conversion rate and 22.7% boost in ROI after using this enhanced platform and capabilities. We are still in the early stages of using gen AI to help advertisers achieve higher conversions and ROIs on our platform. Our efforts will ultimately lead to significant improvement in monetization capabilities and contribute to future revenue growth. In the quarter, we also used our AI capabilities to help merchants grow their sales on Baidu.

One example is how we help SMEs with livestream shopping. With ERNIE Bot, we introduced a tool that allow them to easily create their own digital human, generate live scripts, and more, significantly lowering the barrier and cost for livestreamers to sell merchandise on Baidu. Looking forward, we are optimistic that the growth of our online marketing revenue will continue to exceed China’s GDP growth. At the same time, we will continue to test AI-native marketing products that could potentially open up more opportunities than traditional general search ads.

This gives us confidence in Baidu’s long-term online marketing growth prospects. Turning to AI cloud. We continued to generate positive operating profit on a non-GAAP basis in the quarter as we remained focused on the healthiness of our business. Gen AI and LLM have brought us a lot of opportunities, which have strengthened our competitive advantages in cloud and increased our TAM.

A growing number of enterprises using ERNIE API to develop their own AI-native applications and solutions. We’re also helping customers build their own models efficiently by leveraging our unique four-layer AI infrastructure and our years of experience in building and using foundation models. Our LLM training is very complicated. It requires a large number of GPUs working simultaneously.

Any GPU failures can impact the entire process. We have developed ways to identify and address GPU failures quickly, leading to a significant reduction in training costs. Now, about 80 — about 98% of the training time, our platform is valid, setting an industry benchmark. We also have a set of different resources, including toolkits, datasets, for enterprise customers to easily fine-tune their customized models.

Gen AI has helped us grow our cloud customer base. A large number of cloud customers using ERNIE API are new customers. At the same time, some of our existing cloud customers have increased their spending with us because of generative AI. AI Cloud revenues declined by 2% year over year in the third quarter, mainly due to the weak demand in smart transportation projects.

We believe AI Cloud revenue should rebound to positive growth in the fourth quarter, driven by the increasing momentum in generative AI-related businesses. Also, since smart transportation revenue started to slow down in Q4 of last year, we will have an easier year-over-year comp base in Q4 this year. Moving on to intelligent driving. Our target remains unchanged, which is to achieve breakeven on the regional unit economics for robotaxi operation in a couple of years before turning operationally profitable.

To this end, we are strategically concentrating our resources on pivotal regions. Wuhan remains our largest operational area, and we believe it is also the largest region globally providing autonomous ride-hailing services, currently covering a population of about 2.7 million. In the third quarter, the portion of fully driverless orders within the overall order portfolio in Wuhan exceeded 40%. That’s up from 35% in Q2.

We are also particularly pleased to highlight that Apollo Go’s operations in Wuhan continue to expand. In late August, Apollo Go remains the first company in China to provide autonomous ride-hailing services to the general public at Wuhan Tianhe International Airport, one of the busiest airports in central China. The extended reach into the airport transfer involves longer travel distances, presenting an excellent opportunity for the future improvement of unit economics. All of this development contributed to the UE improvement, and we aim to reach regional UE breakeven in a couple of years.

In Q3, Apollo Go provided 821,000 rides to the public, marking a 73% increase year over year, and the cumulative order volume has surpassed 4.1 million by the end of Q3. As part of our executive reshuffle program, we have recently named Dr. Wang Yunpeng as corporate VP of Baidu, who will lead the Intelligent Driving Group. Yunpeng has been with us since 2012 and has been responsible for autonomous driving business since 2018.

I take great pride in seeing another business leader develop within Baidu. Zhenyu has taken a rotational position as CEO assistant and the chairman of the Technology Ethics Committee. Now, let’s proceed with Rong’s financial performance review.

Rong LuoChief Financial Officer

Thank you, Robin. Now, let me walk you through the details of our third quarter financial results. Total revenue was RMB 34.4 billion, increasing 6% year over year. Revenue from Baidu Core was RMB 26.6 billion, increasing 5% year over year.

Baidu Core’s online marketing revenue was RMB 19.7 billion, increasing 5% year over year. Baidu Core’s non-online marketing revenue was RMB 6.9 billion, up 6% year over year. Revenue from iQIYI was RMB 8 billion, increasing 7% year over year. Cost of revenue was RMB 16.3 billion, which remained essentially unchanged compared to the same period last year.

Operating expenses were RMB 11.9 billion, increasing 8% year over year, primarily due to an increase in channel spending, promotional marketing expenses, server depreciation expenses, and the server custody fees, which support ERNIE Bot research inputs. Baidu Core’s operating expenses were RMB 10.5 billion, increasing 10% year over year. Baidu Core’s SG&A expenses were RMB 4.8 billion, increasing 14%, 1-4, one year over year. SG&A accounting for 18%, 1-8, of Baidu Core revenue in the quarter, compared to 17%, 1-7, in the same period last year.

Baidu Core R&D expenses were RMB 5.6 billion, increasing 7% year over year. R&D accounting for 21% of Baidu Core revenue in the quarter, which maintained — unchanged from the same period last year. Operating income was RMB 6.3 billion. Baidu Core’s operating income was RMB 5.5 billion, and Baidu Core’s operating margin was 21%.

Non-GAAP operating income was RMB 7.6 billion, non-GAAP Baidu Core operating income was RMB 6.7 billion, and non-GAAP Baidu Core operating margin was 25%. Total other income net was RMB 1.9 billion, compared to the total other loss net of RMB 4.8 billion for the same period last year, mainly due to the first recognition of RMB 338 million gain versus RMB 3.1 billion loss for the same period last year from fair value changes in long-term investments; and second, a decrease in impairment of long-term investments by RMB 1.4 billion. Income tax expenses was RMB 1.3 billion, increasing 41% year over year, primarily due to an increase in profit before tax. Net income attributable to Baidu was RMB 6.7 billion, and diluted earnings per ADS were RMB 18.22.

Net income attributable to Baidu Core was RMB 6.4 billion, and net margin for Baidu Core was 24%. Non-GAAP net income attributable to Baidu was RMB 7.3 billion, and non-GAAP diluted earnings per ADS were RMB 20.40. Non-GAAP net income attributable to Baidu Core was RMB 7 billion, and non-GAAP net margin for Baidu Core was 26%. As of September 30, 2023, cash, cash equivalents, restricted cash, and short-term investments were RMB 202.7 billion, and cash, cash equivalents, restricted cash, and short-term investments excluding iQIYI was RMB 197.4 billion.

Free cash flow was RMB 6 billion, and free cash flow excluding iQIYI was RMB 5.2 billion. Baidu Core has approximately 35,000 employees as of 31st — as of September 30, 2023. With that, operator, let’s now open the call to questions.

Questions & Answers:


Thank you. We will now begin the question-and-answer session. [Operator instructions] Your first question comes from Alicia Yap with Citi. Please go ahead.

Alicia YapCiti — Analyst

Hello. Thank you. Good evening, Robin, Julius, and the management team. Thanks for taking my questions.

My question is on advertising. So, it seems like Baidu ad revenue growth is tracking slower than some of the internet peers. So, besides macro, can management elaborate any other reasons that contributed to the softer ad revenue growth? And then looking into the fourth quarter, have you seen any demand picking up? What is the e-commerce sector contribution and how will AI change the advertising outlook? Thank you.

Robin LiCo-Founder and Chief Executive Officer

Hi, Alicia. This is Robin. In Q3, apart from the macro weakness, online marketing revenue from e-commerce platforms was also relatively weak. Revenue from e-commerce platforms is one of our top revenue contributors, accounting for about 10% of our total online marketing revenue.

Like many other internet platform companies, we are building our own native e-commerce businesses. Revenue growth from our native e-commerce business is tracking very strong as we continue to improve the shopping experience on Baidu. I would like to highlight the strides we have made in our ad business gen AI. We are basically restructuring the overall ad platform, including creative construction, ad targeting, and the bidding mechanism.

These efforts have started to pay off, and the incremental revenue from these kind of initiatives are expected to reach the level of hundreds of millions RMB in the current quarter, which is the Q4 of this year. And looking forward, we are optimistic that the growth of our online marketing revenue will continue to exceed China’s GDP growth. Thank you.


The next question comes from Alex Yao with J.P. Morgan. Please go ahead.

Alex YaoJ.P. Morgan — Analyst

Thank you, management, for taking my question. I have a few questions on cloud revenue. I believe Robin mentioned that despite of moderate revenue decline in 4Q, the cloud revenue will — the growth rate will return to positive territory in Q4. And then from there, should we expect the cloud revenue to further accelerate into first half of 2024? With regard to the smart city projects, are there any more projects that are still at risk? And then more importantly, as you guys start to monetize the AI capability, when will AI start to contribute to the cloud revenue meaningfully? Lastly, any preliminary view on cloud revenue growth outlook for 2024? Thank you.

Dou ShenExecutive Vice President In Charge of Baidu AI Cloud Group, ACG

Hi, Alex. This is Dou. Thank you for your question. So, actually, as we mentioned before, so we have been focusing on improving the house for business for sustainable development.

And as a result, we have achieved non-GAAP operating profits in the past few quarters. As Robin already mentioned, due to the weak demand for intelligent transportation, cloud revenue experienced a slight decline in Q3. So, while excluding smart transportation, the rest of our AI cloud business showed a pretty solid growth. And we believe that cloud revenue will return to positive growth in the fourth quarter and the trend will continue down the road.

What is the more exciting side? We keep seeing new opportunities brought up by generative AI and large language models. Actually, last quarter, we already said that more and more customers across various sectors came to us for model training, application development, and solution enhancement. Although the current revenue from generative AI and LLM related to business is still very small, but it’s growing very fast. We have seen more and more enterprises proactively adopting these new technologies for productivity and efficiency gain.

Some of these customers, especially those from the internet education and the tech sectors, they have started to see efficiency gains through working with us. As a result, some of them have gradually increased their spending on our cloud services. Looking to Q4, we aim to leverage our leadership in generative AI and large language models to continuously attract new customers and encourage the existing customers to increase their spending on the Baidu AI Cloud. And we believe this should not only lead to long-term revenue growth but also continuous margin improvement.

Thank you, Alex.


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

Miranda ZhuangBank of America Merrill Lynch — Analyst

Thank you. Good evening. Thanks, management, for taking my question and congratulations on the results. My question is about ERNIE.

So, can management share with us the latest feedback for ERNIE 4 since the roll out last month? And any color on the contract signed on adopting ERNIE 4? And also, for consumer ends, how is the feedback after ERNIE Bot started to charge users a subscription fee? And lastly, among the various opportunities you mentioned, which one do you think can become the biggest revenue driver? Thank you.

Robin LiCo-Founder and Chief Executive Officer

Hi, Miranda, let me answer your questions. Since the release of EB4 in mid-October, we’re receiving positive feedbacks from both users and customers. Many enterprises have reached out to test EB4 and have been impressed with its capabilities. EB4 has gained a reputation for its advanced understanding and complex reasoning abilities.

Comparing to EB3 and EB5 and other LLMs in the market, we have noted that EB4 generates more structured and clearer responses and excels in coding. From November 1st, we started to charging enterprises and end users for using EB4, and we’ve seen a growing number of customers and users willing to pay for its use. We’re proud to be the first company to introduce a GPT-4-level model in China. EB4 further widen our lead over other LLMs in the market.

And we are the first LLM to charge end-user fees that sets us apart from other peers. And regarding your question about monetization opportunity, we see significant opportunities in AI-native applications, either devised by Baidu or by our customers who leverage our AI capabilities. If you look at our own products, we see significant opportunities in the new search and the revamped ad platform. The new search complements traditional search.

It can address complex questions that were previously unanswerable. It also enables users to conduct a more personalized and in-depth research various topics and projects. We will soon enable users to have multi-run conversation with us. As our for search, we’ll be able to talk with users in natural language.

And in multi-runs, it will create more potential on the commercial side, too. We are experimenting with a chatbot-type product for SMEs and brands. We believe this will not only help drive effective conversion but also allow us to eventually transform from a CPC model to a CPS model. And at the same time, our capabilities are — well, help our advertisers to better operate their business on Baidu.

Our ongoing effort to revamp the ad platform have already shown positive results, and we will continue leveraging generative AI and LLM to assist advertisers in achieving durable ROI growth on Baidu. In terms of empowering our customers with gen AI, as Dou just mentioned, customer needs are different now. Some customers still prefer to train their own model, but the GPU export restrictions will put the brakes on that. It will eventually become clear that training LLMs from scratch is very difficult, especially when trying to achieve emergent abilities.

Well, to turn to advanced LLMs available on the market like ERNIE for developing applications, as customers become more advanced in using LLM to create applications and more AI-native applications powered by ERNIE become more widely used, we should be able to see continuous revenue growth through model inferencing. Over the long term, inferencing should become a major source of revenue for ERNIE. Meanwhile, we will also help customers to fine-tune our existing model offerings to suit their customized needs in each scenario because our models are better, faster, and more cost effective. So, in summary, gen AI and LLM will bring us massive business opportunities.

We have already made good progress in commercialization so far, and this is just the beginning of a promising future. Thank you.


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

Gary YuMorgan Stanley — Analyst

Hi. Thank you, management, for the opportunity to ask questions. Can management share the latest advertiser feedback on the AI-powered ad system upgrade and how do you think about the level of revenue boost to the core ads in 2024 as it gets rolled out to more, even all advertisers? Thank you.

Robin LiCo-Founder and Chief Executive Officer

Yeah. We are very happy with the rapid AI transformation of our ad system and thrilled by the positive feedback from our advertisers. Overall, I think advertisers appreciate our efforts to help them improve their ROIs on our platform. Also, they are fond of our new features, which help them to be more productive.

As I mentioned in the prepared remarks, we put a lot of effort into using gen AI and LLMs to reinvent our app system over the past few quarters. Now, we have an integrated advertiser-facing marketing platform. Advertisers can use it to generate creative advertising materials. These materials have proved to deliver higher conversion rates than materials created by humans.

And our platform also allows advertisers to engage in natural language. By interacting with advertisers in multiple runs of conversation, our upgraded platform is able to better understand their intention. This allows us to create campaign strategies that deliver higher ROI. Moreover, it significantly reduces the time that ad managers need to spend creating campaigns and because even an experienced ad manager have to spend hours developing an advertising strategy.

And now, with an AI copilot, the process only takes like a few minutes. As of today, we have a few thousand of advertisers already migrated to our new platform. While this number is relatively small compared to our, you know, half million advertiser base, it is certainly growing very fast. In addition, we continue to use AI to improve our bidding system and ad targeting capabilities.

Such initiatives happened at the back end of the system, so advertisers may not directly perceive them, but they’ve observed improvements in their ad conversion and ROI. So, on average, advertisers using these capabilities probably achieved a high single-digit increase in conversions in Q3. All of our efforts should eventually attract advertisers to allocate more of their advertising budget on Baidu. As I previously mentioned, online marketing revenue related to our upgraded ad platform has been growing rapidly and already became meaningful.

And this is just the beginning, as I said. We are experimenting with AI chatbot, and chatbots could act as a replacement for landing page in the future. This is particularly useful in verticals where users typically research and engage in a long decision process before purchasing. Imagine searching for a training program and being directed to a bot instead of a web page.

With our AI chatbots, users can quickly learn about brand-specific information, product details, and other stuff. Although, I think that multi-run conversation is also very engaging. And for advertisers, it helps them to stay connected with potential customers and guide them at key decision-making points, leading to better conversion and even direct sales. We believe AI chatbot could work well with gen AI-powered new search and bring us more opportunities.

I mentioned earlier that the incremental revenue from this kind of initiative is expected to reach the level of hundreds of millions of RMB this current quarter, Q4, and this is certainly growing very fast. The trend should continue and further strengthen in the year of 2024. Thank you.


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

Wei XiongUBS — Analyst

Good evening, management. Thank you for taking my question. I want to follow up on your cloud business. So, could management share more color on how to think about the industry competitive landscape in China cloud market, especially among the internet cloud vendors and — as well as when competing with the telcos? And also, with the development in generative AI and the large language model, how do we assess our competitive advantage against peers? Do we expect the competition to intensify next year as other companies try to make efforts and catch up with us? Thank you.

Dou ShenExecutive Vice President In Charge of Baidu AI Cloud Group, ACG

Great question. This is Dou. As you, actually, may already noticed, the traditional cloud business is slowing down, while generative AI and large language models are thriving in and reshaping the competitive landscape of the cloud business industry. In the past, the focus in the cloud market was actually on a house, which is like a commodity and people are competing on pricing.

But now, with the rise of generative AI and the large language models, things are changing. There’s a growing interest among cloud customers coming to Baidu to utilize these sophisticated technologies to increase productivity and efficiency. They came to us, you know, not only because we have the most advanced AI technology, but also because we have experience and track record in using AI to help enterprises to solve problems. While some of them are still in the products experimental stages, but they have a firm belief in the new technology to rebuild their products and services because they have seen, you know, successful stories overseas.

That is why we are seeing the new technology is increasing our TAM and expanding our competitive edge. So, as Robin mentioned, EB4 is China’s first GPT-4-level model. He also shared that the positive initial feedbacks we have garnered for EB4. So, currently, our team are engaged in our dialogues with our clients, assisting them in extending the technology and utilizing ERNIE to redevelop their existing products and create new ones.

So, I can see that ERNIE has already helped us attract new customers in additional IT spending from existing customers. So, here, I would like to briefly bring up two points for our advantage compared to the players in the market. The first one is our unique four-layer AI infrastructure, which gives us the flexibility to make adjustments or innovations at every layer, you know, to be able to be compatible with other layers to keep driving efficiency in both model training and inference. And the second one, more specifically, is our capability to develop GPU networks or clusters for large language model training.

So, as Robin just said, you know, 98% of the training time on our AI infrastructure is valid. As a result, our customers, including several leading internet and tech companies, were increasing their investments in our service. Furthermore, we will continue to leverage our unique advantage of AI architecture to drive efficiency gains. It will help us to greatly reduce costs in model training and inference on our cloud, giving us the flexibility to offer more compelling prices to our customers and further strengthen our competitive edge in the market.

You know, regarding the competition from telecom operators, I would like to highlight our focus is on different market segments since we differentiate ourselves with our AI capabilities, in particularly, you know, ERNIE, as we have mentioned. Actually, it’s worth noting that, you know, we can cooperate and we are actually collaborating on many objects — projects as for other internet companies in China, so our strong AI capabilities and ERNIE are well recognized by the market, which will set us apart from our peers. To sum up, you know, we believe that our strong AI capabilities, and particularly in generative AI and large language models, will allow us to eventually become the market leader and gain share in the cloud market.


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

Lincoln KongGoldman Sachs — Analyst

Thank you, management, for taking my question. So, my question is also about ERNIE. So, given the successful upgrade of the ERNIE 4.0, what will be the future strategy for model iteration to solidify our attack on leadership? So, do we foresee any competition in the foundation model in industry, albeit to stabilize or intensify in the future? Thank you.

Robin LiCo-Founder and Chief Executive Officer

Hi, Lincoln. The AI chips we have in hand already allow us to launch EB4 we — ahead of the competition. To take our lead in LLMs to the next level, we will take an application-driven approach. We will let the AI-native apps tell us what to improve in ERNIE Bot capabilities.

Given that there are only a very limited number of AI-native apps on the market right now, the majority of ERNIE API costs are from internal apps are internal apps like Search, App, Wenku, etc. The rebuilding and restructuring of our existing products drive ERNIE innovation in the right direction. What is equally important is that we are helping enterprises use ERNIE to build their offerings, and we have seen that over 10,000 enterprises are using ERNIE through API costs on a monthly basis, which, you know, propels ERNIE’s improvement, too. We are also continuing to improve the efficiency of our models.

For example, compared to ERNIE Bot’s version — the ERNIE Bot version in March, inference cost of the current version has been reduced by 98%, basically resulting in a 50 times increase in QPS for the same amount of hardware or computing power. We are also able to do this using our unique four-layer architecture and leveraging our ability to do end-to-end optimization. Continued inference cost reduction has further strengthened our model’s competitive advantage, and it gives us the flexibility to offer more and more compelling pricing. From a long-term perspective, taking into account factors such as the scarcity of high performance chips, high demand for data, AI talent, and the huge upfront investments, the industry will soon transit into a consolidation stage.

We believe there will only be a select few foundation models in the market, and Baidu will certainly be one of them. In this stage of industry development, more and more enterprises will begin to leverage advanced foundation models like ERNIE to create AI-native products rather than spending resources on building their own large language models. So, we expect that the number of native apps based on ERNIE will reach millions in the future.

Lincoln KongGoldman Sachs — Analyst

Thank you.


The next question comes from James Lee with Mizuho. Please go ahead.

James LeeMizuho Securities — Analyst

Great. Thanks for taking my questions. Can you guys maybe quantify the investments related to AI and how that affects various cost items in your P&L? And should we expect these investments to accelerate over the next few quarters, I was thinking especially at the launch of ERNIE 4.0 and potentially higher inference costs as more people are using it? And then if we extrapolate that over longer term, how should we think about Baidu Core OPM over the next few years given all the moving parts, including revenue shift, investment in AI, and also your continued improvement in cloud profitability? Thanks.

Rong LuoChief Financial Officer

Hi, James. Let me take your questions. This is Julius. Currently, the primary investments for generative AI and large language models is centered around the computing power, which is recorded as powerful capex.

I think, in the past few quarters, we have put a lot of chips resources to training our new ERNIE models. And in the future, as more AI-native applications, which is powered by our ERNIE, become more widely used, we should put — we could put more resources in more important things. However, please note that all of these powerful AI-related hardware investments on our P&L is quite manageable because the — all hardware depreciations are spread all over a few years. And for example, like, all expenses linked to cutting power were used in training ERNIE are recorded as R&D depreciations.

And the model inferencing causes, which is highly related to the usage of the models, either internally or externally, and it should be supported with funding by the future developments. And moreover, this is where we are happy to see that our investment in generative AI and large language models are beginning to bear fruit. As Robin has mentioned just earlier, things were receiving the approval from regulatory and more additional revenue generated from ERNIE’s Bot by 2C or 2B businesses has been growing quite fast. While we are using the generative AI and language models to renovate our businesses, we are still keeping a close eye on making sure our Baidu cost earnings stay solid.

In Q3, we can see the mobile ecosystem continued its high margin, ensuring a very strong generation of cash flow, and AI cloud business continued its healthy growth and achieved profitability one more time. And look ahead, we expect that the traditional cloud business to remain quite profitable and the new opportunity arising from generative AI and large language models are also expected to have a favorable margin in the long term. For Intelligent Driving Businesses, our long-term growth opportunity, we’ll continue to invest with a mature pace. And all in all, we will concentrate our resources by reallocating them from non-core businesses to AI-related businesses.

All of this will be quite beneficial for our long-term growth. Thank you, James.


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

Thomas ChongJefferies — Analyst

Hi. Good evening. Thanks, management, for taking my questions and congratulations on a solid set of results. My question is on the chips side.

Can management comment about the impact on AI development after the further restriction of the chip export from the U.S.? How does that affect our AI product offerings and user experience, if any? Thank you.

Robin LiCo-Founder and Chief Executive Officer

Yeah. The restrictions on the chip export to China actually have a limited impact on Baidu in the near term. We have successfully launched EB4 in mid-October, our most advanced foundation model in China. It is a milestone for us.

And as I just said earlier, we have a substantial reserve of AI chips, which can help us keep improving ERNIE Bot for the next year or two. Also, inference requires less powerful chips, and we believe our chip reserves, as well as other alternatives, will be sufficient to support lots of AI-native apps for the end users. And in the long run, having difficulties in acquiring the most advanced chips inevitably impacts the pace of AI development in China. So, we are proactively seeking alternatives.

While these options are not as advanced as the best chips in the U.S., our unique four-layer AI architecture and the strength in AI algorithm will continue to help us improve efficiency and mitigate some of these challenges. For example, we have made some innovations in PaddlePaddle, our deep learning framework; and ERNIE, our foundation model, to allow them to be better compatible with different types of AI chips, both model training and inference tasks. But given that all the other Chinese companies face the same challenge, we believe we are actually best positioned to serve this market. As you probably know, in the past, some of our peers, they try to ride on the gen AI wave by investing in those start-ups to train foundation models, and they basically just sell the computing power to those start-ups.

We didn’t do that. You know, we try to optimize everything from the infrastructure layer to framework layer then to model layer then to app. So, we’ve invested in this kind of end-to-end optimization approach. Therefore, we can — for the same amount of computing power, we can do training more efficiently, more cost-effectively, and we can do inferencing faster and cheaper.

And as time passes by, I think more and more companies will realize that they don’t need to train their foundation models. They just need to develop AI-native apps based on Baidu’s foundation model, which is the best on the market. So, I’m really happy that we basically invested on this kind of end-to-end optimization front for many, many years, and it’s time for us to show that the investment is worth it. Thank you.


[Operator signoff]

Duration: 0 minutes

Call participants:

Juan LinDirector of Investor Relations

Robin LiCo-Founder and Chief Executive Officer

Rong LuoChief Financial Officer

Alicia YapCiti — Analyst

Alex YaoJ.P. Morgan — Analyst

Dou ShenExecutive Vice President In Charge of Baidu AI Cloud Group, ACG

Miranda ZhuangBank of America Merrill Lynch — Analyst

Gary YuMorgan Stanley — Analyst

Wei XiongUBS — Analyst

Lincoln KongGoldman Sachs — Analyst

James LeeMizuho Securities — Analyst

Thomas ChongJefferies — Analyst

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