Tencent Tang Daosheng: Enterprises closer to scenarios and data, with a future of big models

Tech 2023-07-08 15:10:51 Source: Network

On July 8th, at the 2023 World Artificial Intelligence Conference, Tang Daosheng, Senior Executive Vice President of Tencent Group and CEO of the Cloud and Smart Industry Group, stated that the universal big model has strong capabilities, but it cannot solve specific problems for many enterprises. The application of large models in enterprises needs to comprehensively consider factors such as industry specialization, data security, continuous iteration, and comprehensive costs

On July 8th, at the 2023 World Artificial Intelligence Conference, Tang Daosheng, Senior Executive Vice President of Tencent Group and CEO of the Cloud and Smart Industry Group, stated that the universal big model has strong capabilities, but it cannot solve specific problems for many enterprises. The application of large models in enterprises needs to comprehensively consider factors such as industry specialization, data security, continuous iteration, and comprehensive costs. Building your own exclusive model based on the industry model may be a better option for enterprises.

The universal big model can solve 70% -80% of problems in 100 scenarios, but it may not necessarily meet the needs of a certain enterprise scenario 100%. "Tang Daosheng said that the universal big model is generally trained based on extensive public literature and network information, and many professional knowledge and industry data accumulation are insufficient, leading to insufficient industry specificity and accuracy in the answers. However, users have high requirements and low fault tolerance for the professional services provided by the enterprise. Once the enterprise provides incorrect information to the public, it may cause serious consequences.

He stated that if enterprises are based on industry models and fine tune their own data, they can construct exclusive models and create highly available intelligent services. Moreover, the model has fewer parameters than general large models, resulting in lower training and reasoning costs, and easier model optimization.

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Tag: Tencent Tang Daosheng Enterprises closer to scenarios and data