Recently, the OmModel of Hangzhou Linker Technology passed the large-scale pre-training model system evaluation of the Ministry of Industry and Information Technology of China and obtained two S-level and three A+ reviews in 5 capability evaluation metrics, nine top-level and two advanced evaluations in 11 platform maturity evaluations. As a result, OmModel has become the first large model in China that passes this evaluation.
Dr. Tiancheng Zhao, Chief Scientist of Hangzhou Linker Technology, indicated that OmModel, as a new infrastructure in the AI field, solved the problems of data resources shortage and long R&D cycles in the AI implementation process. Compared with the traditional development mode, large models require less labeled data and shorter development cycles, which can effectively reduce the costs for the development and application of AI industrialization with the support of low-code development platforms.
The China Academy of Information and Communications Technology (CAICT) has established AIAE, an authoritative evaluation system for AI innovative application technology and product services, and formulated the "Large-scale Pre-training Model System Capability Assessment Method". OmModel of Hangzhou Linker Technology was evaluated and passed the assessment, which includes two parts: technical service capability and system function, and comprehensively evaluating the function.
Through the multimodal AI algorithm of large-scale self-supervised learning, OmModel integrates the language and visual modal understanding of "text + image + video" to complete large-scale pre-training on hundreds of millions of pictures, tens of thousands of videos, and billions of images and texts. The model learns to fuse multi-modal information, and obtains more accurate visual AI models with a smaller number of labeled samples, successfully coping with tens of millions of scenarios with a single system.
Excellent Technical Capabilities
As a Language Augmented Visual Model, OmModel supports few-shot learning and multimodal fusion, which can use multimodal co-learning algorithms to quickly perform AI modeling based on a small amount of annotated data. It can perform multimodal learning through alignment and conversion across different modalities and perform open-set object detection, outlier detection, image classification and etc. Image retrieval, visual question answering, visual common sense reasoning, semantic reference detection, and zero-sample multimodal can also be supported.
High Platform Maturity
Hangzhou Linker Technology launched the "Visual AI Application Development Factory" OmVision Studio based on OmModel, which reshapes visual algorithms production with a new process of "0-sample cold start, small-sample training, and online tuning". With data access, data annotation, model training, model fine-tuning, model compression, and other functions, it fulfills clients’ R&D needs at different stages and situations, providing a simple development process, and visualized implementation. At present, OmModel large model and system platform services have been applied in many fields such as radio and television media, energy and power, smart supervision, and government governance, promoting digital transformation in many enterprises.
Hangzhou Linker Technology will continuously promote the improvement of the pre-trained large models' implementation in technology development, product application, deployment services, etc., to adapt the industrial markets for AI practicality, adaptability, and inclusiveness.