شركة موشن برين تجمع ما يقرب من 100 مليون يوان في جولة تمويل ما قبل الفئة أ: أستاذ في جامعة فودان ورئيس علماء سابق في إنتل يصنعان "عقلًا" للروبوتات

Chinese startup Motion Brain (眸深智能) has raised nearly 100 million yuan (approximately $13.8 million) in a Pre-A funding round. Investors included the industry investment platform Jinyue Investment, co-founded by a major Chinese asset management company, a Hong Kong consortium, and several public companies, as well as Chuanghehui Capital and previous investor Xuhui Capital. This is the second round in two months, following a Pre-A round of 300 million yuan in May 2026. Additionally, a Pre-A+ round of 500 million yuan is in the process of closing. Since the beginning of the year, the company's valuation has increased more than tenfold. Motion Brain was founded in January 2025 by Professor Chen Tao, director of the Deep Learning Laboratory at Fudan University; former Intel chief scientist in China Zhang Yimin; and serial entrepreneur Mu Zelin. Key employees have experience at Huawei HiSilicon, Intel, and Nvidia. The company has been building its technological foundation since 2022. It developed the MLD (Latent Space Diffusion Model), which for the first time globally mapped movements into latent space and applied a diffusion model to generate natural motions. In September 2023, it introduced MotionGPT, a model that breaks down human poses into approximately 3,000 "motion tokens" (analogous to tokens in LLMs), enabling robots to perform new actions without special training (Zero-Shot). By 2026, seven generations of models had been released. Based on these, the company created STI-WM (Spatial-Temporal Integrated World Action Model), a framework for long-term planning, closed-loop control, and physical interaction, which uses a ratio of 80% internet videos, 10% motion capture data, and 10% real robot data, reducing the need for real data by 90% and increasing accuracy to 99%. The T²MB (Task*Task Motion Brain) model, announced in March, allows robots to learn autonomously on-site without sending data to the cloud, improving task execution accuracy by up to 25%. The company's developments are already cited in Nvidia's latest models (ARDY). Its technical edge includes compressing models from hundreds of billions to tens of billions of parameters, reducing on-device latency from 200 to 10 milliseconds, cutting computation costs from 200,000 to 10,000 yuan per model, and adapting to Chinese chips (HiSilicon Ascend, Horizon Robotics, Enflame). The compression work won the IJCAI 2025 Best Paper Award, the only one for a mainland Chinese team in the past five years.