再获融资！穹彻智能获阿里投资，加速具身智能全链路技术突破

Core Insights - Noematrix, a startup focused on embodied intelligence, recently completed a new funding round led by Alibaba, with participation from existing shareholders. The funds will be used to accelerate technology product development, application implementation, and industry ecosystem expansion [2] Group 1: Company Overview - Noematrix was established at the end of 2023 and has shown strong capital attraction, raising several hundred million RMB in Pre-A++ and Pre-A+++ funding rounds within two years [5] - The company is co-founded by Lu Cewu, a prominent scholar in embodied intelligence, and Wang Shiquan, founder of Feixi Technology. Lu has been engaged in embodied intelligence research since 2015 [2][5] Group 2: Technological Advancements - Noematrix has developed the Noematrix Brain 2.0, an upgraded product that incorporates object concept learning capabilities, enabling embodied agents to understand causal reasoning related to physical objects [5][11] - The company has made significant breakthroughs in key technology areas, including a no-ontology data collection scheme, a universal end-to-end model solution, and a scalable human-machine collaboration deployment system [8][11] Group 3: Market Applications - Noematrix has established partnerships with leading companies in the retail and home sectors to deliver integrated hardware and software solutions for embodied intelligence [9] - The retail sector focuses on high-frequency measurable processes such as restocking and inventory, while the home sector tests the model's advantages in complex tasks like cleaning and organizing [9] Group 4: Future Outlook - The company anticipates that as the generalization ability of its model surpasses scene barriers, the marginal costs of large-scale delivery will decrease, leading to predictable commercial expansion [9] - Noematrix aims to continuously provide innovative and practical embodied intelligence solutions to its clients and partners, leveraging its advanced model products and data-to-model closed-loop capabilities [9]