华为哈勃押注,成立仅半年融资三连跳,这家公司凭什么成为“世界模型黑马”?
机器人大讲堂·2026-01-20 09:11

Core Viewpoint - Manifold AI, founded by a former key member of SenseTime, aims to redefine embodied intelligence through its World Model technology, enabling robots to not only perceive but also predict physical interactions in their environment [1][4][12]. Group 1: Financing and Growth - Manifold AI has completed over 300 million yuan in financing within just seven months of its establishment, showcasing a rapid fundraising pace that reflects strong market interest in "Physical AI" [2][7]. - The company has successfully raised funds in three rounds: a seed round led by Inno Angel Fund, followed by two angel rounds, each exceeding 100 million yuan [4][7]. - The latest funding round included notable investors such as Meihua Venture Capital, Junlian Capital, and Huawei Hubble, indicating a strong backing from the industry [1][9]. Group 2: Technology Development - Manifold AI's technology focuses on World Model Action (WMA), which allows robots to predict physical state changes based on first-person perspective videos, moving beyond traditional visual-language models (VLM) [12][14]. - The company's WorldScape model enables robots to simulate and interact with their environment autonomously, marking a shift from mere execution of pre-set codes to possessing "brain-like" capabilities [14][15]. - Manifold AI is developing multiple specialized models, including DriveScape for autonomous driving, RoboScape for physical interaction, and AirScape for drones, all built on the foundational WorldScape model [15]. Group 3: Future Aspirations - The company aims to equip over 10% of robots in the market with its "Manifold Brain," pushing the boundaries of Physical AI agents [19][20]. - The long-term vision includes transitioning World Models from experimental stages to practical applications in warehouses, factories, and homes within the next three years [20][21]. - The strategy emphasizes creating a universal embodied world model while simultaneously commercializing sub-domain models to generate revenue and support further development [20].