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HKU professor's startup Yisheng Technology secures hundreds of millions in angel funding to develop memory systems for robots.

HKU professor's startup Yisheng Technology secures hundreds of millions in angel funding to develop memory systems for robots.

硬氪首发 | 港大教授成立的忆生科技获数亿天使轮融资,致力于为机器人造一套记忆系统

TranscEngram, a robotics startup focused on developing autonomous intelligence, has successfully secured hundreds of millions in angel funding. The investment round saw participation from a diverse group of industry and state-owned enterprises, including Charoen Pokphand Group’s China National Pharmaceutical, Pudong Venture Capital, and several others. Founded in September 2023 by leading AI experts, including Professor Ma Yi from the University of Hong Kong, TranscEngram aims to create a unified system for robots that mimics human cognitive processes through a "brain + cerebellum" architecture. This innovative approach seeks to advance the field of explainable embodied intelligence by enabling robots to learn through a closed-loop of perception, prediction, and interaction. The newly acquired funds will primarily support the development of advanced models for embodied control and physical world modeling, as well as the establishment of research and industrial bases in Shenzhen and Shanghai. The company’s technology promises to enhance robots' capabilities in self-correction and continuous evolution, moving towards commercial applications. TranscEngram's unique memory system allows robots to learn from vast amounts of data without relying on fixed programming, significantly improving their performance in multi-tasking scenarios. The startup is currently focusing on high-end service sectors, such as hotel operations and flexible manufacturing in aerospace, aiming to automate and optimize these industries. With research and data centers established in major cities, TranscEngram is collaborating with leading robotics firms to integrate its innovative solutions into existing production processes, enhancing efficiency and adaptability in real-world applications.

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