Amulya Vishwanath, formerly of NVIDIA, states that robotics remains in its “Lego era” because core components like actuators and robotic hands are still under development. This perspective opposes the expectation that a general foundation model will trigger an immediate breakthrough similar to ChatGPT in late 2022. Vishwanath, now managing partner at Techable VC, argues that safety standards and software integration require rebuilding before physical AI can scale effectively. She joins Dominic-Madori Davis on the Equity podcast to explain why current specialised robotics work cannot yet be replaced by a single model. Her transition from product marketing to early-stage investing highlights the gap between theoretical potential and practical deployment in materials science and life sciences.
The industry faces significant hurdles before achieving widespread adoption of autonomous physical systems. Current limitations prevent the replacement of specialised hardware with general-purpose software solutions. Investors must wait for foundational technologies to stabilise before expecting mass market disruption.
* Actuators and robotic hands require further iteration.
* Safety standards are currently being rebuilt.
* Specialised robotics work remains essential for now.
