Alibaba has made an investment in an enterprise specializing in embodied AI.

According to the Enterprise Early Warning Bulletin, Force Robot has successfully completed a Series A+ financing round worth hundreds of millions of yuan, with Alibaba (China) Network Technology Co., Ltd. serving as the sole lead investor.

Back in February of this year, Force Robot had just secured a 200 - million - yuan angel - round financing. The investors in this round included Legend Capital, Jiukun Venture Capital, and Qiming Venture Partners.

The Series A financing round was led by NIO Capital. Hongtai Fund, Legend Star, Wuxi Venture Capital, and Zhengjing Fund also made follow - on investments. Among the existing investors, Legend Capital made an oversubscribed follow - on investment, while Qiming Venture Partners and Jiukun Venture Capital participated in the follow - on as well.

It is reported that the total amount raised in the Series A and Series A+ rounds is close to 1 billion yuan.

Established in 2024, Force Robot's core technology lies in an end - to - end embodied AI large model. This model can directly process perceptual inputs and generate action outputs without the need for intermediate steps, achieving true end - to - end intelligent control.

It is reported that the core founding team of Force Robot comes from Megvii, a well - known Chinese AI company. The team members include Fan Haoqiang, Zhou Erjin, and Wang Tiancai.

In July 2011, Fan Haoqiang, then a high school freshman and one of the four Chinese team members, scored 599 (out of 600) and won second place at the 23rd International Olympiad in Informatics (IOI) held in Pattaya, Thailand. In the same year, while still a high school student, he joined Megvii as employee number 6.

Fan Haoqiang was awarded a full scholarship to Tsinghua University and enrolled in the 'Yao Class' - the Computer Science Experimental Class.

During his time in the 'Yao Class', he also worked at Megvii. Despite the challenge of balancing work and studies, he consistently ranked first in his class. During his freshman military training, he even completed a paper for the ICCV (one of the top international conferences in computer vision).

Zhou Erjin, a native of Shaoxing with both parents being teachers, attended Shaoxing No.1 High School. He represented China at the 2009 International Olympiad in Informatics in Plovdiv, Bulgaria, and won a silver medal. In 2010, as a high school sophomore, he won a gold medal at the National Olympiad in Informatics. In 2011, he won another gold medal at the International Olympiad in Informatics.

In 2011, Zhou Erjin enrolled in the Department of Electronic Engineering at Tsinghua University.

Wang Tiancai entered the College of Electronic and Information Engineering at Southwest University in 2013 and later joined Megvii as a senior researcher.

Behind them stands Tang Wenbin, the co - founder of Megvii.

Tang Wenbin, a native of Shaoxing, Zhejiang, has won numerous awards. He claimed first prize in the National Olympiad in Informatics League and a gold medal in the National Olympiad in Informatics. As a high school sophomore, he was admitted to Tsinghua University (Class of 2006, Computer Science Department). Later, he became the first recipient of the 'Yao Award' gold medal and served as the head coach of Tsinghua University's Informatics Olympiad team for seven consecutive years.

In October 2011, Tang Wenbin, along with his 'Yao Class' classmates Yin Qi and Yang Mu, co - founded Beijing Megvii Technology Co., Ltd. Tang invited Fan Haoqiang, who was still a high school student, to join Megvii before he even entered university, making Fan employee number 6. He also invited Zhou Erjin, then a sophomore, for an internship at Megvii, where Zhou became employee number 12.

What is Force Robot's goal?

Its goal is simple yet powerful: to transform robots into 'intelligent colleagues' in our work and daily lives, rather than machines that require constant supervision.

Firstly, it equips robots with a 'superbrain'. This brain does not rely on rigid programming. Instead, it learns to perceive the world, understand different scenarios, and make independent decisions through large models. It can see, hear, and comprehend its surroundings and then act autonomously. It's like installing the intelligence of GPT into a physical body that can walk, move, and grasp objects.

Secondly, this robot does not need step - by - step instructions. You don't have to tell it, 'Move left first, then grab the object, and then place it there'.

Imagine saying, 'Help me organize the warehouse before I get home' as you leave the office. The robot will automatically carry out the task the next day without requiring constant monitoring at every step.

You can give it instructions in natural language, such as 'This area is messy. Clear this first, and then move that over here'. It not only understands but also knows what you truly expect it to do, rather than just following literal commands.

The above represents Force Robot's long - term goals. End - to - end large model robots are among the 'most challenging directions' in the field of AI + hardware integration, as they require machines to 'understand the world and act like humans' rather than simply executing pre - programmed tasks.

The industry self - media platform Embodied AI Lecture Hall predicts that Force Robot's future market opportunities will mainly focus on two scenarios: logistics robots and industrial smart manufacturing upgrades. Leveraging the founding team's expertise in logistics scenes accumulated at Megvii and breakthroughs in end - to - end embodied algorithms, the technology can be rapidly deployed in essential scenarios such as warehouse automation and flexible manufacturing. For example, end - to - end algorithm optimization can enable better cluster scheduling of four - way shuttles, addressing issues like high - density storage and dynamic picking.

This article does not constitute any investment advice. It also references reports from sources such as China Youth Daily, for which we express our gratitude.