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Robotics lab Genesis AI launches with $105M to develop universal robot foundation model and AI

Genesis AI Launches with $105M to Build Universal Robotics Foundation Model

Ashish Singh by Ashish Singh
July 11, 2025
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Genesis AI Launches with $105M to Build Universal Robotics Foundation Model

Physical AI is poised to become the next transformative frontier in artificial intelligence. While software-based AI has advanced rapidly in recent years, robotics has lagged in developing machines that can operate seamlessly in the real world. Genesis AI, a newly unveiled robotics company, is determined to change that narrative. Backed by $105 million in funding, the company is building a universal robotics foundation model and a full-stack robotics platform to unlock the potential of physical labor automation.

Genesis AI Launches to Address the Physical AI Gap

Genesis AI publicly launched with the announcement of $105 million in funding. The startup aims to pioneer a new generation of general-purpose robots driven by advanced AI systems that can understand and interact with the physical world. Company CEO Zhou Xian stated that the time has come for physical AI to catch up with its digital counterpart.

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According to Xian, digital AI has delivered breakthroughs in language, vision, and reasoning but has failed to transition those capabilities into real-world robotics. He emphasized that physical AI will shape the next chapter of human advancement by enabling robots to perform a wide range of tasks currently done by people.

Genesis AI plans to use its funding to develop a robotics foundation model (RFM) and a horizontal robotics platform. These efforts are designed to give robots cognitive, perceptual, and physical skills to handle complex, real-world environments.

Company CEO Zhou Xian stated that the time has come for physical AI to catch up with its digital counterpart.

The Strategy Behind the Robotics Foundation Model

At the core of Genesis AI’s mission is the development of a robotics foundation model. This model will combine digital AI knowledge with physical-world intelligence to create general-purpose robotics systems. Xian explained that Genesis AI’s approach will provide unmatched capability, scalability, and cost efficiency.

The company’s RFM will be trained using a mix of synthetic and real-world data. The goal is to build a model that can power robots capable of performing diverse physical tasks across multiple industries. Genesis AI said that it is developing its own in-house simulation tools and data engines to fuel this model.

The simulation system is designed to generate high-quality synthetic data at scale. Meanwhile, a separate data collection system will gather large volumes of real-world robot data. Together, these components will produce a unified and diverse dataset for model training.

A Full-Stack, Data-Centric Approach to Robotics

Genesis AI is taking a full-stack approach, meaning it is building the entire robotics software and hardware stack from the ground up. This includes physics simulation, generative modeling, and the robotics control stack.

The company said that its system will support scalability, robustness, and flexibility—qualities that are often missing in current robotics platforms. Genesis AI believes that its data-centric design will overcome the rigidity of traditional industrial robots, which often rely on brittle and inflexible software.

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Xian stated that the company’s method integrates foundational AI research with robotics expertise to create a cohesive platform that can scale efficiently across industries. Genesis AI’s strategy includes a unified simulation and data engine, capable of feeding large-scale data into its models.

At the core of Genesis AI’s mission is the development of a robotics foundation model. This model will combine digital AI knowledge with physical-world intelligence to create general-purpose robotics systems

Addressing a Multi-Trillion Dollar Problem

The potential impact of physical AI is vast. According to the International Federation of Robotics (IFR), physical labor accounts for $30 trillion to $40 trillion of global GDP. Yet, over 95% of that labor remains unautomated due to the limitations of current robotic systems.

Genesis AI sees an opportunity to unlock this untapped sector by creating robots that can handle tasks requiring mobility, dexterity, and reasoning. The company believes that general-purpose robots will address labor shortages faced by 75% of global companies.

Eclipse partner Charly Mwangi noted that even in industries considered highly automated, the robot-to-human ratio rarely exceeds 1:30. This is due to the inability of existing robots to handle the long tail of physical tasks that require real-world intelligence.

Genesis AI claims its platform will bridge this gap by enabling robots to perform a broader range of activities with reliability and affordability.

Expertise Driving the Vision

Genesis AI was co-founded by Zhou Xian and Théophile Gervet. Xian earned his Ph.D. in robotics from Carnegie Mellon University in 2024, while Gervet previously worked as a research scientist at Mistral AI and Skild AI.

The founding team includes specialists in physics simulation, computer graphics, robotics, and large-scale AI model training. Their collective experience spans academic research and industrial deployment, allowing Genesis AI to develop systems that combine theoretical rigor with practical implementation.

The company has offices in Palo Alto, California, and Paris, France. Its global presence is intended to support collaboration with research institutions and technology partners across both North America and Europe.

International Federation of Robotics (IFR), physical labor accounts for $30 trillion to $40 trillion of global GDP. Yet, over 95% of that labor remains unautomated due to the limitations of current robotic systems.

Investors Backing the Physical AI Revolution

The $105 million funding round was co-led by Eclipse and Khosla Ventures, with participation from Bpifrance, HSG, and notable tech figures Eric Schmidt and Xavier Niel.

These investors expressed strong belief in the promise of physical AI to reshape the labor economy. Mwangi stated that general-purpose robotics could unlock trillions of dollars in value by automating tasks that current systems cannot perform.

He pointed out that the labor bottleneck in physical tasks persists despite widespread digital transformation. Genesis AI’s approach, he said, is positioned to redefine the capabilities of robots in manufacturing, logistics, and healthcare.

A Commitment to Open-Source Collaboration

Genesis AI plans to open-source components of its robotics foundation model and data engine. The company said this move will accelerate development across the broader field of physical AI by enabling developers and researchers to build on its work.

By sharing key tools and datasets, Genesis AI aims to foster collaboration and community-led innovation. The company believes that open access to foundational components will support faster progress and broader adoption of physical AI technologies.

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Only 2,000 of these robots were in use by the global community with an AI capability, according to the firm. Genesis AI believes that with the help of its platform and its open-source push, it can quickly scale this figure and set a new standard of smart machines.

Building the Infrastructure for Scalable Robotics

Genesis AI is investing in scalable infrastructure so as to achieve its objectives. This encompasses high-fidelity simulation mechanisms, robotic hardware systems and machine learning pipelines.

The company’s dual data engine will combine synthetic and real-world data sources, creating a feedback loop that improves robot performance over time.

Genesis AI said its infrastructure will reduce the cost and complexity of deploying robots in dynamic environments. By supporting continuous data collection and model refinement, the platform is designed to adapt to real-world variability without extensive reprogramming.

A New Era for Labor Automation

Genesis AI is confident that general-purpose robots would lead to automation of most of the physical work in the various sectors. The first is that conventional industrial robot is not up to the task of performing activities that require dexterity, flexibility and decision-making.

Its robotics foundation model and full-stack platform aim to deliver a solution that is both cost-effective and adaptable. The company’s strategy includes generating data at scale, building robust models, and enabling real-world deployments that require minimal custom engineering.

 

Ashish Singh

Ashish Singh

Ashish — Senior Writer & Industrial Domain Expert Ashish is a seasoned professional with over 7 years of industrial experience combined with a strong passion for writing. He specializes in creating high-quality, detailed content covering industrial technologies, process automation, and emerging tech trends. Ashish’s unique blend of industry knowledge and professional writing skills ensures that readers receive insightful and practical information backed by real-world expertise. Highlights: 7+ years of industrial domain experience Expert in technology and industrial process content Skilled in SEO-driven, professional writing Leads editorial quality and content accuracy at The Mainland Moment

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