2023 Generative AI Industry Market Analysis: ERNIE Bot User Base Surpasses 100 Million
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Baidu CTO: ERNIE Bot User Base Surpasses 100 Million
On December 28th, at the 10th WAVE SUMMIT Deep Learning Developer Conference, Wang Haifeng, Baidu's Chief Technology Officer and Director of the National Engineering Research Center for Deep Learning Technology and Applications, announced that ERNIE Bot's user base has exceeded 100 million. This milestone achievement marks significant progress for Baidu in the field of artificial intelligence.
Wang Haifeng revealed that since receiving approval to open services to the public on August 31st, the number of user queries to ERNIE Bot has been steadily increasing, largely in sync with the performance improvements of the ERNIE large model. More and more users are trusting and using ERNIE Bot, which fully demonstrates Baidu's technical prowess and market competitiveness in the AI sector.
Wang Haifeng disclosed at the conference that since August 31st of this year, when it was approved to open services to the public, the number of user queries has been on a continuous rise, largely keeping pace with the performance enhancements of the ERNIE large model.
Baidu's founder, Chairman, and CEO Robin Li stated in an internal letter that as humanity enters the AI era, the IT technology stack has undergone fundamental changes. Previously, it was essentially divided into three layers: the chip layer, the operating system layer, and the application layer. Now, it can be divided into four layers: the chip layer, the framework layer, the model layer, and the application layer. Baidu is one of the few AI companies globally with a full-stack layout, encompassing leading in-house technologies at every level—from the high-end Kunlun chips to the PaddlePaddle deep learning framework, and the ERNIE pre-trained large model—enabling end-to-end optimization and significantly improving efficiency.
According to reports, Baidu did not start from scratch in developing generative AI products. The company possesses the essential elements for artificial intelligence: computing power, algorithms, and data. With strategic deployments across four technological layers—chips, frameworks, models, and applications—Baidu has established comprehensive advantages in generative AI technology, both in China and globally.
Since 2019, Baidu has been deeply involved in pre-training model research and development, launching ERNIE 1.0. After nearly four years of accumulation, in March of this year, Baidu became the first among global tech giants to release the knowledge-enhanced large language model ERNIE Bot. By October, the foundational model of ERNIE Bot was upgraded to version 4.0, significantly enhancing its four core capabilities: understanding, generation, logic, and memory. Over the past two months, its overall performance has improved by 32%. Singapore's Lianhe Zaobao reported that Baidu has integrated ERNIE Bot into several flagship products, including search and maps.
In November, Baidu released its unaudited financial report for Q3 2023. The data showed revenue of 34.447 billion yuan (RMB, same below), with Baidu's net profit (non-GAAP) reaching 7.3 billion yuan, a year-on-year increase of 23%. Both revenue and net profit exceeded market expectations.
Bank of Communications International released a research report stating that ERNIE Bot, benefiting from Baidu's traffic, search product advantages, and technological and financial support, is poised for rapid growth. The report is optimistic about its potential to restructure Baidu's product portfolio and drive revenue growth.
Wenxin Yiyan has launched a professional version priced at 59.9 yuan per month and a joint membership with Wenxin Yige at 99 yuan per month, available for C-end users. Since its public release on August 31, Wenxin Yiyan has reached a user base of 70 million, with 4,300 scenarios and 2,492 applications.
Generative AI (AIGC, Artificial Intelligence Generated Content) is a significant milestone marking the transition from AI 1.0 to AI 2.0.
The accumulation and integration of technologies such as GAN, CLIP, Transformer, Diffusion, pre-trained models, multimodal techniques, and generative algorithms have spurred the explosion of AIGC. Continuous algorithmic innovation, the qualitative leap in AIGC capabilities driven by pre-trained models, and the diversification of AIGC content through multimodal approaches have endowed AIGC with more versatile and robust foundational capabilities.
Generative AI Industry Market Analysis
From the progression of computational intelligence to perceptual intelligence and then to cognitive intelligence, AIGC has opened the door to cognitive intelligence for human society. Through training on large-scale datasets, AI has acquired knowledge across multiple domains. With appropriate model adjustments, it can now accomplish tasks in real-world scenarios.
AIGC holds milestone significance for human society and artificial intelligence. In the short term, it transforms fundamental productivity tools; in the medium term, it reshapes social production relations; and in the long term, it drives qualitative breakthroughs in overall societal productivity. Within this transformation of productivity tools, production relations, and productive forces, the value of data—a key production factor—is vastly amplified.
AIGC elevates data as a core resource of the era, accelerating the digital transformation of society to some extent.
Since the beginning of this year, general artificial intelligence, represented by cognitive large models, has sparked a global wave of enthusiasm. International companies like OpenAI, Microsoft, and Google continue to invest heavily, while domestically, a 'thousand-model battle' has emerged, with numerous high-tech enterprises competing in R&D. According to the China AI Large Model Map Research Report released by the Ministry of Science and Technology, China and the U.S. lead significantly in the number of large models released globally, accounting for over 80% of the total.
Meanwhile, large models are seen as a new engine for corporate transformation. McKinsey's report, The Economic Potential of Generative AI: The Next Productivity Frontier, indicates that applying the 63 analyzed generative AI use cases across industries could add $2.6 trillion to $4.4 trillion annually to the global economy. This estimate excludes all potential generative AI applications—if unstudied applications are included, the economic impact could double.
Specifically, industry players widely believe that the generative AI market is poised for explosive growth on the demand side, potentially forming two trillion-dollar markets for both consumer (C-end) and enterprise (B-end) applications. Enterprises' demand for generative AI is surging, and general-purpose models will inevitably revolutionize the traditional AI market, with productivity gains significantly boosting industrial development.