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SenseTime Ranks Among Top 3 in China’s GenAI IaaS Service Market in H2 2023, According to IDC Tracker
A recent report by International Data Corporation (IDC) ranked SenseTime, a leading software company, among the top 3 providers of Generative AI Infrastructure as a Service (GenAI IaaS) in China for the second half of 2023. This accolade also solidifies the company’s leading position in the rapidly growing GenAI IaaS market.
According to "IDC China Semiannual Intelligent Computing Services Tracker, 2023H2”, the overall size of China's intelligent computing services market reached RMB 11.41 billion in the second half of 2023, representing a year-on-year growth of 85.8%. The GenAI IaaS market experienced exponential growth, reaching a market size of RMB 3.22 billion. The report showed that SenseTime is one of the top 3 GenAI IaaS providers in China, which places it among market leaders in the cloud computing infrastructure segment.
Currently, SenseTime's SenseCore AI Infrastructure enables unified scheduling of computing networks across the nation, with new computing nodes established in Shanghai, Shenzhen, Guangzhou, Fuzhou, Jinan and Chongqing. SenseTime's total operating computing power reached 12,000 petaFLOPS in Q1 2024, and it is expected to reach 25,000 petaFLOPS by the end of the year to meet the growing demands of the GenAI market.
The IDC report highlighted that industry players like SenseTime rapidly gained market share by capitalizing on the GenAI IaaS market momentum. By strategically building its capabilities before the emergence of the GenAI trend, SenseTime could leverage its resources and comprehensive technical capabilities in large models and SenseCore for the GenAI IaaS market. As a result, the company has successfully captured the third-largest market share in China.
In 2023, China’s GenAI development entered a pivotal year of development with an exponential surge in demand for intelligent computing power. Leveraging its foresight into the evolution of AI large models and the industry’s demand for intelligent computing power, SenseTime has been committed to building AI computing infrastructure since 2018. The company had developed SenseCore, a new-generation AI-native infrastructure that is highly efficient, cost-effective, and scalable. Centered on the development, generation, and application of AI large model, SenseCore empowers a new paradigm of AI production, providing a one-stop solution to fulfill the entire pipeline from data processing and model building to application deployment.
By utilizing SenseCore, SenseTime offers businesses and developers with inclusive, flexible, and open AI infrastructure products and services. The AI-native cloud infrastructure layer of SenseCore is designed to provide agile, flexible, scalable, secure, and reliable AI infrastructure. SenseTime has developed a proprietary AI scheduling system and distributed AI storage system to support a variety of domestically-developed AI chips, resulting in a streamlined, high-performance, and unified AI application development framework. This framework significantly enhances the productivity of R&D teams and accelerates the integration of AI capabilities with real-world application scenarioses.
Empowered by the robust computing power of SenseCore and guided by the Scaling Law, SenseTime’s "SenseNova" Large Model has been upgraded significantly and. Earlier this month month, SenseTime launched "SenseNova 5.5", which showed a 30% improvement in overall performance compared to "SenseNova 5.0". SenseTime also introduced "SenseNova 5o", the first real-time multimodal model in China, which provides a new AI interaction model on par with GPT-4o’s streaming interaction capabilities.
GenAI has evolved from unimodality to multimodality, transitioning from general-purpose to industry-specific applications, and progressing from training models to real-world deployments. The demand for GenAI IaaS has grown exponentially among customers. With its efficient, user-friendly, and inclusive intelligent computing capabilities, SenseTime’s SenseCore has become the preferred choice for customers across industries for large model training with low barriers to entry, and inference deployment.
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