Ex-Nvidia-turned-VC Amulya Vishwanath: ‘Physical AI is in its LEGO era’

Vishwanath announced that her new venture capital firm, Techable Ventures, will concentrate on early‑stage companies creating the hardware and software foundations for robotics—what she calls “physical AI.” Drawing on her seven‑year stint at Nvidia and prior roles at a pre‑Intel acquisition and at Molex‑owned Interconnect Systems, she argues that the sector is still assembling basic components such as robotic hands and actuators. By treating these pieces as interchangeable LEGO bricks, she expects a future where modular, general‑purpose and specialized robots can be rapidly combined into more sophisticated systems. Her firm’s value proposition is not just capital but a talent pipeline, positioning founders against talent‑draining giants like Anthropic and Nvidia.

The “LEGO era” framing mirrors the early days of the internet and the Industrial Revolution, where a handful of standards and platforms eventually unlocked massive scale. In robotics, the lack of universal software stacks, standardized actuation interfaces, and modular hardware has kept progress fragmented. Vishwanath’s emphasis on building reusable building blocks aligns with broader industry moves—such as the rise of open‑source robot operating systems (ROS) and modular actuator kits—that aim to lower entry barriers. By targeting this foundational layer, Techable hopes to capture upside before the market consolidates around a few dominant architectures, much as early cloud investors profited before AWS and Azure became de‑facto standards.

If the analogy holds, the next inflection point will be a breakthrough that stitches together these modular components into a seamless, general‑purpose robotic platform, sparking a wave of applications akin to the generative‑AI explosion. Risks include the possibility that hardware integration timelines lag behind software advances, and that large incumbents could acquire promising modules before a true ecosystem emerges. Watch for early funding rounds in actuator‑standardization startups, partnerships with open‑source robotics communities, and any signal that talent pipelines are shifting away from big AI labs toward specialized robotics teams.