Nvidia is reportedly pivoting its strategy from solely focusing on artificial intelligence (AI) chipsets to embracing robotics and embodied AI technologies. The Santa Clara-based technology giant is exploring new opportunities to furnish processing capabilities and training for robots, especially in light of intensified competition within the AI hardware sector. An Nvidia executive recently indicated that the company is planning to train AI agents in simulated environments to better equip them for real-world applications. Earlier this year, Nvidia also introduced its AI platform called Generalist Robot 00 Technology (GR00T), aimed at humanoid robots.
Nvidia Looks Towards Robotics as an Untapped Space
According to a report from the Financial Times, Nvidia is positioning itself to become a leading platform for robotics processing and AI-driven simulation training. Deepu Talla, Nvidia’s Vice-President of Robotics, remarked to the publication that the “ChatGPT moment” for physical AI and robotics is imminent.
This strategic shift might imply a reduced emphasis on AI chipsets and GPUs, which have traditionally been the primary contributors to the company’s impressive valuation of $3.6 trillion (approximately Rs. 307.9 lakh crores). The report notes that the decision to explore new avenues comes amid growing competition in the AI semiconductor landscape.
Major players in the industry, including AMD, Intel, and Snapdragon, have recently introduced AI chipsets equipped with neural processing units (NPUs). While Nvidia remains dominant in the GPU realm, the entry of cloud computing powerhouses such as Amazon, Google, and Microsoft presents a challenge that could significantly impact Nvidia’s revenue stream.
The report outlines Nvidia’s intention to establish itself as a “full stack” provider for robotics, combining hardware acceleration with software solutions for training. Recently, Jim Fan, who leads the Embodied AI division at Nvidia, disclosed plans to train embodied AI agents—robots equipped with sensors and mechanical components—using simulations to prepare them for practical challenges.
Furthermore, Nvidia is set to unveil Jetson Thor, a chipset developed within the company’s Isaac Robotics Platform, which powers its GR00T platform for simulation-based training. This system leverages generative AI to innovate training methodologies for humanoid robots, reducing the need for extensive coding.
Talla emphasized that the strategic focus on robotics comes in light of advancements in generative AI models, which enable the training of robots within simulated environments. He noted, “In the past 12 months [this gap] has matured sufficiently that we can now carry out experiments in simulation, combining with generative AI, that we could not do two years ago. We provide the platform for enabling all of these companies to do any of those tasks.”
