Robotics Still Assembling Its Foundations, Says Former Nvidia Executive

Amulya Vishwanath, who spent seven years overseeing product marketing for Nvidia's robotics platforms, told industry observers that the sector is still in a formative "Lego era," where core components such as actuators, robotic hands, software frameworks and safety protocols are being re‑engineered from the ground up.

The analogy reflects a broader reality: unlike generative AI models that have surged to mainstream awareness with tools like ChatGPT, robotics lacks a single breakthrough that can instantly translate into widespread consumer or enterprise adoption. Instead, developers are busy standardising the building blocks that will eventually enable more sophisticated, plug‑and‑play machines.

Vishwanath highlighted that many of today's robotic systems still rely on bespoke hardware configurations and fragmented software stacks. This fragmentation hampers scalability and raises costs, preventing the kind of rapid iteration that has characterised the recent AI boom. By contrast, the AI community benefits from open‑source libraries, shared model weights and a clear path from research to product.

Industry analysts note that the current focus on modularity is a necessary prelude to broader deployment. Standardised actuators and interchangeable grippers, for example, could allow a single software platform to control a diverse array of physical devices, much as a common API lets developers build applications across multiple AI models.

Safety standards also remain in flux. As robots move from isolated industrial settings into collaborative spaces alongside humans, regulators and manufacturers must converge on protocols that ensure reliable operation without endangering users. Vishwanath said that establishing these norms is as critical as any hardware innovation, because trust will ultimately dictate market acceptance.

Despite the challenges, investment in robotics continues to rise, fueled in part by advances in perception, manipulation and edge computing. Companies are betting that once the foundational pieces are in place, a wave of applications—from warehouse automation to home assistance—could emerge with a speed comparable to the recent AI surge.

Looking ahead, Vishwanath expects the next few years to see incremental consolidation of components and software tools, paving the way for more seamless integration. When those standards solidify, the sector may finally experience a tipping point that mirrors the rapid diffusion of large language models, turning robotics from a niche engineering pursuit into a mainstream technology.