Amulya Vishwanath, who spent seven years leading product marketing for NVIDIA’s robotics platforms, says robotics is currently in its “Lego era,” with the basic building blocks like actuators, robotic hands, software, and safety standards still being rebuilt.
This view runs counter to those who believe that robotics, powered by a general foundation model, is about to have its “ChatGPT moment” — that day when the shockingly capable chatbot was launched in late 2022. (General Intuition CEO Pim de Witte told Equity earlier this year that a single general foundation model would make much of today’s specialized robotics work redundant, and be that moment.)
On this episode of TechCrunch’s Equity podcast, Dominic-Madori Davis caught up with Vishwanath to discuss where she’s writing first checks as the founder and managing partner of Techable VC. They also talked about what she’s learned as one of the first women executives to spin out of Nvidia and launch her own early-stage firm investing in physical AI across robotics, materials science, and life sciences.
Listen to the full episode to hear more about:
Why Vishwanath defines physical AI as more than robots: “a molecule, a material, a medicine,” or a machine on a factory line.
What she means by “conscious automation.”
Why the best opportunities solve big problems like family-run factories that can't find workers to surgeons facing burnout.
Why she wants founders to see their VC as their moat, and how years at NVIDIA built the network she now uses for due diligence and customer introductions.
Where she thinks the U.S. and China each have the edge, and why humanoids should be good for more than dancing.
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Chapters:
00:00 Intro
01:03 Amulya’s path from Intel to Nvidia, and why she left
04:39 What physical AI meant in 2018 vs. now
06:12 Beyond dancing robots: industrial and surgical use cases
09:31 What “conscious automation” means
12:12 Cutting through the hype: the “Lego era” of robotics
16:43 Why your VC should be your moat
20:30 Biggest bottlenecks for physical AI founders
22:30 U.S. vs. China in physical AI
25:43 Are humanoids just for entertainment?
28:10 The most promising near-term areas
29:22 Outro
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