Tag: nvidia

  • Nvidia Invests in MetAI: A Taiwanese Innovator Revolutionizing Digital Twins with AI

    Nvidia Invests in MetAI: A Taiwanese Innovator Revolutionizing Digital Twins with AI

    Nvidia is making significant strides in developing robotics and various industrial AI applications with the introduction of its Omniverse platform, and recently, Mega, an Omniverse Blueprint framework designed for creating digital twins to efficiently manage these applications. Additionally, Nvidia is investing in startups focused on digital twin technology to help propel this initiative.

    MetAI, based in Taiwan, has introduced a model capable of swiftly producing “SimReady” (simulation-ready) digital twins via AI and 3D technology. This process transforms CAD files into functional 3D environments within mere minutes.

    Nvidia has supported MetAI in its initial funding round, contributing to a $4 million seed round, marking the chip giant’s first investment in a Taiwanese startup. Other contributors to this funding round include a blend of strategic and financial investors, such as Kenmec Mechanical Engineering, Solomo Technology, SparkLabs Taiwan, Addin Ventures, and Upstream Ventures.

    The forthcoming phase of AI, termed generative physical AI, depends on accurately simulated environments to train and validate robots for autonomous systems, facilitating operational AI development prior to deployment. MetAI asserts that the digital twins it creates will play a pivotal role in this process.

    Daniel Yu, CEO and co-founder of MetAI, noted that digital twins have historically posed a significant barrier for physical AI due to the long development timelines, which could span months or even years.

    MetAI concentrates on AI-driven digital twins specifically designed for advanced semiconductor fabrication, intelligent warehouses, and automation. It also generates synthetic data within AI-enhanced digital twin environments.

    Renton Hsu, Yu’s co-founder and the CTO of MetAI, has expertise in 3D engineering and AI. He began his journey with digital twins while developing enterprise AI software applications, where they served as effective solutions in cases where clients lacked sufficient data for system training. This experience led him to the idea of applying this methodology to 3D systems, merging 3D technology with AI to formulate synthetic AI and 3D applications. Hsu collaborated with Yu, who has a background in digital transformation projects, and co-founder Dave Liu, COO, to establish MetAI.

    This breakthrough achievement earned them first place in a competition hosted by Nvidia, resulting in Hsu being recognised as a “Jetson AI ambassador” for the country.

    MetAI faces competition from numerous large and small corporations that have developed digital twin technologies for manufacturing, including Siemens Digital Industries, Dassault Systemes, Hexagon AB, Duality AI, and Intagles. In the realm of synthetic data, companies such as Sky Engine and Scale AI are among the many competitors.

    MetAI believes its approach stands out in the industry.

    Daniel Yu explained that while other companies focus on operational efficiencies or IoT integrations, MetAI employs generative models and AI-driven frameworks to produce digital twins aimed at training physical AI for real-world applications. This strategy not only speeds up the digital twin creation process but also guarantees their practical application in advanced automation systems, thereby bridging the divide between simulation and reality.

    MetAI distinguishes itself by generating artificial data within its AI-enabled digital twin environments. Yu highlighted that this capability allows users to create synthetic data tailored to specific operational needs, enhancing AI training and validation. Yu emphasised that rather than producing isolated datasets, MetAI constructs dynamic virtual worlds—realistic virtual environments that mimic real-world operation.

    This two-year-old startup, offering products ranging from vertical AI agents to digital twins, has secured several customers and is already generating revenue through partnerships with enterprises in the manufacturing and automation sectors. This year, it anticipates earning $3 million from a single project, according to Yu. Revenue streams include project-based income, product subscriptions, and licensing fees from ongoing developments.

    Nico Caprez, corporate development manager at Nvidia, remarked that MetAI’s integration with NVIDIA Omniverse signifies a crucial advancement for industrial digital twins and physical AI in simulations. The ability to generate scalable environments for AI training could potentially establish a new benchmark across industries, from manufacturing to robotics.

    In 2023, MetAI partnered with Kenmec to develop digital twins for automated warehouses. Their technology reportedly reduced the time required for warehouse digital twin simulations from thousands of hours to a mere 3 minutes, leading to substantial cost savings in operational and verification tasks.

    With the recent funding, MetAI plans to enhance its R&D team to accelerate development and implement its market strategies in response to rising demand. Furthermore, the Taiwan-based startup aims to open a U.S. office and move its headquarters in the latter half of 2025, according to Yu.

    Dave Liu explained that Taiwan serves as an experimental base where they collaborate with industry leaders to integrate in-depth vertical knowledge into their models, ensuring their solutions are both effective and scalable. Given Taiwan’s size and the demand for simulation-based solutions, the startup is targeting the U.S. market due to high labour costs and operational complexities. Their expansion strategy will provide both point solutions and comprehensive offerings, such as SaaS products and vertical AI agents designed for quick deployment in real-world scenarios across these sectors.

  • Hippocratic AI Secures 1 Million to Develop Patient-Centric AI Solutions

    Hippocratic AI Secures $141 Million to Develop Patient-Centric AI Solutions

    Hippocratic AI, a pioneering startup dedicated to developing AI solutions that manage non-diagnostic patient-facing tasks, has successfully secured an impressive $141 million in Series B funding. This investment, which brings the company’s valuation to $1.64 billion, was led by Kleiner Perkins, as the company announced on Thursday. This round of funding follows the $53 million raised nine months ago from General Catalyst and Andreessen Horowitz, alongside a $17 million investment from Nvidia five months prior. Notably, the startup is still in its infancy, having been established less than two years ago.

    While many healthcare-generative AI companies concentrate on alleviating administrative tasks, Hippocratic AI is tackling the pressing issue of healthcare professional shortages. The company is developing AI agents capable of performing straightforward tasks, including:

    • Pre-operating procedures
    • Remote patient monitoring
    • Appointment preparation

    In 2024, Hippocratic AI has also successfully signed contracts with 23 health systems and insurers. The new funding will be utilised to broaden the product’s reach into additional markets as well as expand internationally.

  • Nvidia Finalizes Purchase of AI Infrastructure Innovator Run:ai

    Nvidia Finalizes Purchase of AI Infrastructure Innovator Run:ai

    Nvidia has successfully finalised its acquisition of Run:ai, an Israeli startup specialising in the management and optimisation of AI hardware infrastructure.

    Following the merger, Run:ai has announced that its software, which is currently compatible exclusively with Nvidia products, will be made open source. This change means that competitors such as AMD and Intel can adapt the technology for their own hardware.

    “We are excited to build upon the successes we’ve achieved thus far, expand our skilled team, and enhance our product offerings and market presence,” Run:ai informed Bloomberg in a statement. “Open sourcing the software will allow it to reach a broader audience across the entire AI ecosystem.”

    Nvidia first announced its intention to acquire Run:ai in April, with sources revealing to StartupSuperb that the acquisition price was set at $700 million. However, the deal encountered regulatory challenges, as the European Commission and the U.S. Department of Justice initiated separate investigations to assess potential impacts on market competition.

    In December, the European Commission granted approval for the acquisition to proceed.