Moore Threads has announced the open-source release of its audio understanding model, MooER, making it the first large-scale open-source speech model based on domestically produced full-feature GPUs. MooER supports Chinese and English speech recognition and translation, utilizing a three-part model structure that demonstrates robust multilingual processing capabilities. The inference code and a model trained on 5000 hours of data have been released as open source, with plans to further open-source training code and an enhanced version trained on 80,000 hours of data. In comparative testing, MooER-5K has shown outstanding performance, achieving a Chinese CER of 4.21% and an English WER of 17.98%, particularly.

Recently, Moore Threads and Shiyin Intelligence announced a strategic partnership to jointly promote the application of domestically produced full-function GPUs in industry large model solutions. The two parties have completed the adaptation work of the Moore Threads Kuaguo Computing Cluster with Shiyin Intelligence's 'A Leaf Light Boat' multimodal large model, integrating their respective advantageous resources in the field of artificial intelligence, and are committed to providing a more intelligent and efficient service experience.

Recently, Moore Threads and the all-subject educational AI model 'Shizhe AI' jointly announced that they have completed the training and testing of their large model. Utilizing Moore Threads' KUAE supercomputing cluster, Shizhe AI successfully completed the intensive training of a 7 billion parameter model in one week, achieving the expected training efficiency and fully demonstrating the capabilities of the domestically produced all-functional GPU for trillion-scale training.