Self-variable Robotics closes hundreds of millions of dollars in Series A funding, led by Meituan Battle Capital

May 12 news, the public number "Intelligent Emergence" today issued an article, with the body intelligence company "automaton"The company has recently completed a multi-billion dollar Series AFinancingfunded byMeituan (Japanese company)Battle Capital led the investment and was followed by American Dragon Pearl. This post was filed under the category of AutovariancerobotOfficial Forwarding.

Self-variable Robotics closes hundreds of millions of dollars in Series A funding, led by Meituan Battle Capital

According to the article, the round of financing will be used to continue accelerating theFully self-developed end-to-end generalized embodied intelligence macromodelingSimultaneous iteration with the robot ontology, as well as collaboration and landing of intelligent solutions for multiple future application scenarios.

In addition to the hundreds of millions of dollars of Pre-A++ round financing led by Lightspeed Photosynthesis and Junlian Capital disclosed to the public in February this year, Variable Robotics also completed hundreds of millions of dollars of Pre-A+++ round financing invested by Huaying Capital, Yunqi Capital, and GF CITIC prior to the Series A financing.In less than a year and a half since its inception, Variable Robotics has completed 7 rounds of financing, with a cumulative amount of over 1 billion RMB..

1AI inquiry was informed that Self-Variant Robotics was founded in December 2023, and is committed to realizing the ultimate goal of general-purpose robotics -- general-purpose robots that autonomously perform tasks through interaction, perception, and action just like a human being, with efficient generalization and migration capabilities -- through the development of general-purpose large models of embodied intelligence.

Founder and CEO of Variable Robotics, Dr. Qian Wang graduated from Tsinghua University with a master's degree, and was one of the first researchers in the world to propose attention mechanisms in neural networks. During his PhD, he participated in a number of Robotics Learning researches at top robotics labs in the U.S., and his research experience covers almost all fields related to robotics operations and home service robots.

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