Former Nvidia robotics lead Amulya Vishwanath has launched Techable VC to invest in 'Physical AI' startups, focusing on foundational hardware, actuators, and safety standards. Moving beyond viral robotics hype, the fund aims to integrate technology into manufacturing and healthcare workflows. For Indian investors, this signals a shift toward utility-driven automation, which is increasingly critical for the country's manufacturing and pharmaceutical sectors.
Amulya Vishwanath, a former executive at Nvidia’s robotics division, has launched a new venture capital firm called Techable VC. The firm is set to focus on the growing field of 'Physical AI'—a term used to describe artificial intelligence that interacts with the physical world, rather than just operating in software. This move comes as the robotics industry shifts its focus from viral, social-media-friendly demos toward practical, industrial utility.
Vishwanath believes the robotics sector is currently in its 'Lego era.' In this foundational phase, the primary challenges are not just software algorithms, but the basic building blocks like advanced actuators, sensors, and rigorous safety protocols. According to her strategy, the industry must prioritize these infrastructure elements before expecting a widespread, transformative 'ChatGPT moment' in robotics. Her thesis argues that the future of automation lies in solving specific, high-value problems rather than just building humanoid robots that can perform basic tasks for entertainment.
Techable VC plans to invest across several areas, including materials science, life sciences, and pharmaceutical manufacturing. The goal is to facilitate what Vishwanath calls 'conscious automation'—integrating technology directly into workflows to solve acute labor shortages and improve precision in critical sectors like surgery. By leveraging her experience from Nvidia, the firm aims to provide more than just financial capital, offering technical validation and industry connections to help startups navigate the complex process of hardware development.
For investors, particularly in the Indian market, this trend reflects a broader global transition in industrial automation. India has been aggressively pushing for manufacturing growth through initiatives like 'Make in India.' As Indian manufacturers aim to compete globally, the demand for high-end automation—ranging from automated warehouses to precision manufacturing tools—is growing. While software-led AI has dominated the news cycle, the shift toward 'Physical AI' underscores the need for better hardware, robotics, and safety technology in the real economy.
However, investing in hardware-based AI presents risks that differ from pure software investments. Building physical systems is capital-intensive, requires longer development cycles, and faces greater regulatory hurdles regarding safety and physical interaction. Startups in this space must prove not only that their technology works in a lab but also that it can be scaled reliably and safely in factories, hospitals, and other professional environments. Profitability for such companies often depends on their ability to replace or significantly improve traditional, manual processes, which requires high adoption rates and low failure rates.
Investors should monitor how 'Physical AI' companies manage these risks. The real-world performance of these technologies, the development of industry-wide safety standards, and the ability of startups to scale their hardware production at a competitive cost will be key indicators of success. The next phase for this sector will likely be defined by whether these companies can move beyond prototypes to deliver measurable productivity gains for large-scale industrial and healthcare customers.