APUS and Baidu Alliance build ecological consensus and release AI capabilities to developers

On September 13, APUS attended the "2023 Baidu Alliance Conference" with the theme of "Common Future from AI" to build ecological consensus with the Baidu Alliance. APUS founder and CEO Li Tao participated in a roundtable discussion at the conference and expressed his unique views on AI from being available to everyone to industrial restructuring and its impact on the developer ecosystem.

APUS large model builds a smart base

As a partner of Baidu Alliance for many years, APUS relies on its advantages in products, technology, and business models to bring products and services to more than 200 countries and regions around the world, with a cumulative user base of over 2.4 billion, and through alliance advertising, self-sales, ADX forms a closed business loop and has gained the trust and recognition of Baidu Alliance.

This year, APUS marks the transformation of artificial intelligence with the launch and application of the 100-billion-level multi-modal general artificial intelligence large model "APUS Large Model", and is committed to making the APUS Large Model a "large model built for China". We have innovatively developed a number of client-side artificial intelligence products such as "Jian Bi Cheng Hua" to help make AI available to everyone. At the same time, we have implemented industrial applications such as the APUS Network Information Model and the APUS Medical Model to pave the way for innovative cooperation with the Baidu Alliance. Build a smarter AI capability base.

"Large models are the soul of the AI ​​era and a tool for creating wealth in the future." During the roundtable discussion, Li Tao once again emphasized the critical significance and commercial value of large models to the AI ​​era, and sorted out the impact of the technological revolution on human civilization. Important impact: The first and second industrial revolutions solved the problem of "how to improve the efficiency of the execution system" and let machines replace people; the third scientific and technological revolution, the "information age", improved our perception capabilities and processed data by collecting information and uploading it. The rapid transmission not only makes information more transparent and credible, but also leads the progress of commercialization. Now, the problem we want to solve is to "digitize and network the final decision-making" to form a complete closed loop from perception to decision-making to execution. This is the beginning of the fourth technological revolution in human society.

Li Tao believes that the emergence of generative artificial intelligence will reconstruct the original Internet applications and comprehensively revolutionize fields and industries including smart manufacturing, smart government affairs, smart writing, smart finance and other fields. He said: “The fourth wave of technology will promote the upgrading of the entire industry and trigger disruption by improving the efficiency of existing information systems, transforming and reconstructing existing products and services, and creating new scenarios and new species. social changes." Li Tao predicted that one year later, people may witness the emergence of new species of generative artificial intelligence

The advancement of ecological consensus means that people’s common understanding of protecting the environment and ecosystems is constantly deepening. This means that more and more people are becoming aware of the importance of environmental issues and are willing to take action to protect our planet. Through education, publicity and policy promotion, we can further strengthen ecological consensus and promote sustainable development and the construction of ecological civilization

Li Tao believes that the key to becoming a master of dragon training in the AI ​​era is to regard AI as the future business direction and realize it through the dual support of large models and applications. At present, the competition for large models is fierce, but limited large model suppliers cannot meet the unlimited application market demand, so developers will inject continuous power into the development of artificial intelligence

(APUS Li Tao spoke at the roundtable discussion at the main forum of the conference) can be rewritten as: Li Tao from APUS delivered a speech at the roundtable seminar at the main forum of the conference

APUS opened the API interface to developers soon after the launch of the large model. We are willing to integrate APUS AI capabilities into the Baidu platform to provide developers with better support and services and jointly build a new industrial ecosystem. With the development of large models and the release of capabilities, convenient tools, low-threshold deployment and lower costs will drive developers to the peak of innovation

Li Tao believes that for developers, large models are both opportunities and challenges. First, large AI models that provide proprietary industry paradigms need to be identified. Secondly, we need to stand on higher shoulders and build a better architecture to solve unresolved problems in the traditional Internet field, such as digital agriculture, digital trade and digital services. It is also necessary to deeply explore the applications of life scenarios that people have not yet thought of, so that AI can not only provide capabilities for traditional traffic management, but also discover new wealth creation opportunities

At present, the development of my country's artificial intelligence industry is booming, which is inseparable from the continuous efforts of the model layer and application layer, and is closely related to the innovative breakthroughs of developers. APUS and Baidu Alliance will use this conference as an opportunity to further build ecological consensus, provide developers with fertile ground for digital innovation, and build a solid foundation for artificial intelligence to revolutionize hundreds of industries, extend more scenario applications, and create a more viable industrial ecosystem. Large model base.

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