Infiforce, a Chinese robotics startup, has raised nearly $150 million in Series A and Series A+ funding rounds. The capital will fuel the development of its AtomBrain system and expand robot deployments across industrial and commercial sectors.
TL;DR
- Infiforce raises $150M to develop embodied-AI models and expand DataGrid infrastructure.
- Funding will support robot deployments in manufacturing, logistics, and commercial services.
- Infiforce's Ego data approach aims to train models using first-person recordings, potentially reducing data collection costs.
What happened
Infiforce has secured nearly $150 million in Series A and Series A+ rounds, led by Dunhong Asset Management and state-owned investment platforms. The funding round also saw participation from Zhejiang University Science and Technology Innovation Group, Yandu State-owned Assets Management, Lishui State-owned Assets Management, and existing shareholder Genesis Partners Venture Capital.
The capital will be primarily allocated to three key areas: the development of the AtomBrain embodied-intelligence system and causal world models, the expansion of the DataGrid AI infrastructure, and the deployment of various robots in manufacturing and commercial environments.
Infiforce's approach centers around Ego data, which involves first-person recordings of people interacting with the physical world. This data, combined with the Atom series of world models and AtomBrain, aims to provide a common intelligence layer across different robot forms.
Why it matters
For developers, Infiforce's Ego data approach could offer a more efficient way to collect training data for robotics applications, potentially reducing costs and accelerating development.
Startup founders and investors should take note of Infiforce's rapid expansion and the growing interest in embodied-AI models. The company's focus on industrial and commercial applications presents significant opportunities for innovation and market growth.
The competitive landscape in robotics and AI is heating up, with companies racing to develop more capable and versatile robotic systems. Infiforce's funding and technological advancements position it as a key player in this evolving market.
Key facts
- Infiforce raised nearly $150 million in Series A and Series A+ rounds.
- The funding was led by Dunhong Asset Management and state-owned investment platforms, with participation from several other investors.
- Infiforce's robots and systems are being tested or commercialized in over 30 Chinese cities and more than 100 scenarios.
- The company's AtomVLA model recorded a 97% success rate on the Libero robot-learning benchmark.
- Infiforce's HiMem-WAM model achieved a 97.7% success rate in benchmark testing.
- The company's third-generation AIM world model scored 93.1% on RoboTwin 2.0.
- Infiforce's SAM3D method reached a 99.1% success rate on the Libero benchmark.
- The funding will support the development of the AtomBrain system, expansion of DataGrid infrastructure, and deployment of various robots.
Context
Infiforce is part of a broader trend in the AI industry focused on developing embodied-AI models that can operate effectively in the physical world. These models aim to bridge the gap between digital intelligence and real-world applications, enabling robots to perform complex tasks in various environments.
The company's Ego data approach is a notable innovation in the field of robotics. By leveraging first-person recordings, Infiforce aims to create more versatile and adaptable robotic systems that can learn from human interactions and experiences.
As the AI and robotics industries continue to evolve, companies like Infiforce are at the forefront of developing technologies that could revolutionize industrial and commercial sectors. The company's recent funding round underscores the growing interest and investment in embodied-AI models and their potential applications.