Techable VC’s Amulya Vishwanath Says Physical AI Is in Its “Lego Era”

After leading product marketing for robotics platforms at NVIDIA for seven years, Amulya Vishwanath launched Techable VC, an early-stage investment firm, and now invests in physical AI as its founder and managing partner. On TechCrunch’s “Equity” podcast, she discussed the scope of physical AI, where the robotics industry stands today, and what she looks for in potential investments. She described the industry’s current state as a “Lego era,” in which its basic components are still being put together.

Physical AI Doesn’t Have to Take the Form of a Robot

When people hear “physical AI,” they may picture videos of humanoid robots walking or dancing. But Vishwanath’s definition is much broader. She includes “molecules, materials, pharmaceuticals,” as well as machines working on factory lines.

In other words, physical AI isn’t about adding more types of robots; it’s about AI reaching beyond screens to act on the physical world. AI that generates text or images is extending its reach into real-world materials and processes. Seen that way, potential investments aren’t limited to robotics companies. Her fund focuses on three areas: robotics, materials science, and life sciences.

I find this broader definition persuasive. Developing new drugs and materials involves repeated rounds of prototyping and testing. Bringing AI into that process could change how time is spent in laboratories and factories. Even without a visible robot arm, AI can still act on the physical world.

Rebuilding the Components Before the ChatGPT Moment

There’s a big expectation in robotics: ChatGPT arrived in late 2022, and chatbot capabilities suddenly drew widespread attention. Some believe a similar moment will come for robots, powered by general-purpose foundation models. On “Equity” this year, General Intuition CEO Pim de Witte said that a single general-purpose model could make much of today’s specialized robot development unnecessary.

Vishwanath sees things differently. She says the fundamentals—actuators (power components), robot hands, software, and safety standards—are still being rebuilt. That’s what she means by the “Lego era.” Until the blocks’ shapes and specifications are standardized, even the smartest blueprint won’t produce the finished product you want.

This is something I’d encourage readers to picture. A chatbot operates entirely on a screen. A robot, by contrast, moves physical objects and works near people. Without precise, durable components and standards that prevent accidents, even the smartest model can’t be deployed in the field. The unglamorous work of building the foundations behind flashy demos may be where the real contest in this field is.

Labor Shortages and Pressure on Healthcare Guide Investment Decisions

So what criteria does she use when writing her first check? One idea raised on the podcast was that the best opportunities come from businesses that solve major problems. Examples included a family-owned factory unable to find workers and surgeons facing burnout.

Rather than asking how novel the technology is, the focus is on whose problem it solves and how. That approach matters not only to investors, but also to executives and managers looking to bring AI into their businesses. Whether it’s a factory short on workers or an overburdened healthcare setting, what’s needed isn’t hype but a system that works reliably.

She also describes this approach as “conscious automation.” The term can be understood as a call to design automation around the challenges on the ground, rather than simply replacing work that people have been doing.

An Investor’s Network Can Also Be an Advantage for Founders

Another striking aspect is how she works with founders. She believes a VC should itself be a competitive advantage—a “moat”—for its portfolio companies. Rather than simply providing capital and walking away, she wants to help protect and grow the businesses she backs.

That support is built on the network she developed during her years at NVIDIA. She says she draws on those connections to assess prospective investments’ technology and make customer introductions. Her seven years working with NVIDIA’s robotics platforms appear to have given her both a strong eye for technology and connections within the industry.

For physical AI businesses, success depends more than it does for software-only startups on access to real-world settings such as factories, hospitals, and research institutions. An investor who can offer more than funding and show founders a path into those settings can be a valuable ally. Vishwanath is also one of the earliest female executives to leave NVIDIA and launch her own early-stage investment fund.

The show also explored the respective strengths of the U.S. and China, and the idea that humanoid robots should be useful for more than just dancing. The future of robotics is entering an era in which it is defined less by flashy videos than by painstaking deployment in real-world settings.