APUS Li Tao: AI large models must have 'six elements” to achieve value creation

[Global Network Technology Comprehensive Report] "Although large models seem to be 'omnipotent', not all models can be verified in practice, and not all models can create real value." 10 On March 24, at the 3rd China Software Summit and Programmers Festival, Li Tao, chairman and CEO of APUS, proposed the "six elements" view of AI large model value creation. He believes that the goal of the development of large AI models is value creation, and to achieve value creation, "six elements" must be present: strong computing power, global knowledge base, high-quality data, continuously evolving algorithms, value alignment, and scenario integration value creation .

Under the trend of AI reconstructing the industry, Li Tao pointed out that large models play the role of "operating system" at the bottom, responsible for integrating, scheduling and allocating resources such as computing power, data and applications to comprehensively promote the construction of industrial networks

Using large models as the driving force not only brings about changes in the Internet industry, but also brings about iterative upgrades of IT elements. Li Tao believes that with the popularization of AI, natural language will be widely used in programming in the future, and people can talk directly to machines; at the same time, functional positions such as programmers, product managers, and designers will also transform into "designers" of needs. By handing over tedious, mechanical, and repetitive work to large models and handing over value-creating work to people, social resource allocation will be more reasonable.

Although some models already look "smart", there are still problems such as inconsistent values. In this regard, APUS believes that in China, the research and development of AI applications still needs to be based on China's large-scale models. Therefore, China's large-scale model manufacturers should have an independent consciousness and assume the responsibility of independent innovation; at the same time, they should establish differentiated barriers according to the needs of the Chinese market, create accurate AI large-scale models that meet China's needs and values, and create new AI productivity

The current large model market is still in the exploratory period of commercial implementation. It has long been an industry consensus that large models can create good AI applications and serve market needs well. Li Tao pointed out: "China's digital construction is a continuous iterative process, which requires a large model 'base' to support the rapid transformation of intelligent scenarios. Facing complex needs, APUS will continue to customize large AI models for the Chinese market to integrate AI applications with value creation. ”

He shared that in terms of data, APUS has formed unique global user data and high-quality corpora based on its global business and 2.4 billion global users in the past 9 years; at the same time, APUS cooperates with domestic corpus manufacturers to jointly build oriented A "red corpus" of Chinese market and positive values. In terms of computing power, APUS has invested in the construction of two major intelligent computing centers around the world, and has linked up with cloud computing manufacturers to provide demanders with a variety of computing power combinations and flexible expansion solutions, helping enterprises and developers achieve rapid implementation of research and development and significantly reduce costs.

APUS has currently cooperated with multiple industry partners, including medical, network information, manufacturing and e-commerce, to develop large-scale industry solutions, using artificial intelligence technology to help partners upgrade hardware infrastructure and build basic model platforms. And promote innovation in specific business applications

At the same time, APUS also continues to open up its ecosystem and build flexible industrial collaboration. For example, the APUS large model has opened model plug-ins, and developers can independently access external models and solve complex scene requirements through the capabilities of "model groups".

Finally, Li Tao said: "We expect that APUS large models can play a fundamental role in thousands of industries; we also expect more developers to join the APUS ecosystem and use large models to create more viable AI applications."

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