Even more recently they have been working on a platform named Mega which is an Omniverse Blueprint framework that creates digital twins that operate this application. Even more so, they are also investing in twin startups that can help them get the effort off the ground.
MetAI, a company developed in Taiwan has developed a model that can generate “SimReady” meaning simulation-ready digital twins using AI and 3D technology by converting CAD files into 3D environments that are functional within minutes.
Nvidia is now backing MetAI in its first round of funding which is a $4 million seed round that has become the chip manufacturer’s first investment into a Taiwanese startup. In this round, there are also other strategic and financial investors among them including Kenmec Mechanical Engineering, Addin Ventures, Solomon Technology, and SparkLabs Taiwan.
The next developments in AI technology were known as generative physical AI, which relies on physically accurate simulated environments that can train and validate robots that are used in autonomous systems for building operational AI before being used.
Daniel Yu, the CEO and co-founder of MetAI said in an interview “Digital twins have long been seen as a barrier to entry for physical AI due to the months or even years of effort required for development,”.
It’s also worth mentioning that MetAI focuses on AI-powered digital twins that are tailored to develop semiconductor fabs, intelligent warehouses, and automation. Even more so, it also creates synthetic data within AI-enabled digital twin environments.
MetAI’s co-founder and CTO Renton Hsu, has a large background in 3D engineering and AI, and his first interaction with digital twins was while building enterprise AI software applications. Those AI twins were introduced in situations where clients did not have enough data to train their systems.
Some of theri competitors are small companies that are building digital twin technology for manufacturing, including Siemens Digital Industries, Dassault Systems, Hexagon AB, and Duality AI. However, MetAI creators think that they are different from those companies as they come with a new approach.
Yu stated “Unlike competitors that prioritize operational efficiencies or IoT integrations, MetAI leverages generative models and AI-driven layouts to create digital twins designed for physical AI training and implementation in real-world operations,” and that. “This approach not only accelerates the creation of digital twins but also ensures their direct usability for advanced automation systems like robotics, bridging the gap between simulation and reality.”
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