‌Can SenseTime become a very powerful AI company?

‌SenseTime is expected to become a very powerful AI company. SenseTime's business revenue in the field of generative AI has increased significantly. In the first half of 2024, the revenue of generative AI business increased by 256%, accounting for 60% of the total revenue.

SenseTime Technology has achieved rapid iteration of models and reduced inference costs through the deep collaboration of its large device SenseCore and large models, which has given it a favorable position in the market competition.

SenseTime CEO said that SenseTime has determined the "three-in-one" new AI strategy.

On the occasion of SenseTime's tenth anniversary, SenseTime Chairman and CEO Xu Li issued an internal letter, mentioning for the first time the company's newly established "big device-big model-application" trinity strategy, and announced that it will build a more centralized and efficient organizational structure around strategy and core resources to accelerate the lightweight process of organization and management.

In the internal letter, Xu Li also elaborated on his understanding of traditional AI 1.0 and generative large model AI 2.0. He pointed out that "AI 1.0 is seen as special-purpose intelligence, focusing on single tasks and information processing; while AI 2.0 is seen as general-purpose intelligence, emphasizing multi-tasking and content generation." In his opinion, "although such a description is simple and easy to understand, it is not completely accurate, because there is no clear boundary between general and special, and the implementation of AI must be scenario-based, such as the application of generative large models in vertical fields."

"In our opinion, an important difference between AI 1.0 and AI 2.0 lies in the change in AI cost structure." Xu Li said.

In the traditional AI 1.0 era, the main cost of model production lies in the investment of R&D personnel. In the generative large model AI 2.0 era, the cost of model production mainly lies in the investment of computing resources. The popularization and commercialization of generative large model AI needs to be committed to reducing the production and use costs of large models, which will inevitably combine large models to iterate and optimize computing power, and also need to iterate large model design and application according to the characteristics of computing resources.

Xu Li pointed out that in the field of generative big model AI, SenseTime's core strategy is to achieve seamless integration of big computing devices, big models and applications, drive models with applications, and drive computing power optimization with models. We have established a trinity strategy of "big devices-big models-applications" to improve the efficiency of computing resources through order-of-magnitude optimization and serve our customers well. We are committed to becoming the big model service provider who understands computing power the most, and the computing power service provider who understands big models the most.