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商汤-W(00020.HK):实现“云端边”全栈AI布局 赋能客户获广泛认可

Shangtang-W (00020.HK): Achieving a “cloud-side” full-stack AI layout empowers customers and is widely recognized

國投證券 ·  Apr 24

Event: On April 23, the company held the 2024 Technical Exchange Day and released the 5.0 version of the new big model.

The new Japan-Japan Big Model 5.0 capabilities have been upgraded again to improve the end-side capability layout. The company's technical capability iteration is mainly reflected in: 1) the launch of the 5.0 version of the Japan-Japan New Big Model, which uses a hybrid expert architecture, and the context window during reasoning reached about 200K, fully benchmarking GPT4-Turbo in terms of mathematics, reasoning and coding capabilities; 2) releasing the “Shangtang End-Side Big Model” for terminal devices, and the “Shangtang Enterprise Big Model All-in-One” for various fields such as finance, coding, medical care, and government affairs. At this point, the company has completed the full-stack layout of the big model on the “cloud side” and formed a comprehensive product system.

It has scarce AI full-stack capabilities and has strong market competitiveness. The company has been deeply involved in the AI field for many years and has formed a deep accumulation: 1) It is one of the purest AI companies in China, with faster response speed and stronger learning ability to iterate on cutting-edge algorithm capabilities; 2) It has a controllable computing power of 12,000 GPUs, and has achieved 10,000 card interconnection cluster training capabilities, maintaining 90% acceleration efficiency and leading engineering capabilities; 3) It has empowered leading customers in various fields such as government, finance, healthcare, the Internet, and automobiles. The above accumulation not only guarantees the company's leading technical capabilities, but is also expected to be commercialized faster.

Generative AI revenue is growing rapidly, embracing change and completing business restructuring. In 2023, the company's generative AI business grew rapidly, achieving revenue of 1.284 billion, an increase of 199.9% year over year, and the revenue share increased from 10.4% in 2022 to 34.8%. With generative AI as its strategic direction, the company implemented a business restructuring in 2023, dividing the original non-generative AI business into the traditional AI sector for smart cities, smart living, and smart business, and adjusted the business layout to the three major directions of traditional AI, generative AI, and smart cars. Facing the wave of new technology, the company was able to quickly complete organizational adjustments, laying a solid foundation for subsequent development.

Empowering customers are widely recognized, and performance growth can be expected. In the process of implementing this circular generative AI technology, the company has enabled customers such as Jinshan Office, Haitong Securities, Xiaomi, and Reading Wen Group to iterate and upgrade their business, and has been widely recognized. Thanks to the word-of-mouth spread of successful cases, the company is expected to be the first to receive orders from new customers, fully benefiting from the growth dividends brought by the release of market demand, thereby driving rapid growth in performance.

Investment suggestion: Generative AI is gradually moving from technology to application, driving the growth in demand for commercial orders. Based on technical capabilities and customer reputation, the company is expected to gain a certain market share and drive performance growth. The company is expected to achieve revenue of 4.521/57.10/7.077 billion in 2024 to 2026, respectively. The company was given 7 times PS in 2024, corresponding to a 6-month target price of HK$1.02 (the exchange rate of RMB 1:1.08 against HKD), maintaining a “buy-A” rating.

Risk warning: Risk of customer budget growth falling short of expectations, worsening competitive landscape, higher than expected growth in R&D investment, and rapid technology iteration.

The translation is provided by third-party software.


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