Robotics may be attracting hopes for a sudden leap in capability, but Amulya Vishwanath says the field is still working through more basic challenges. In her view, the essential pieces of robotics are being rebuilt, leaving the technology in what she calls its “Lego era.”
Robotics is still assembling its foundations
Vishwanath spent seven years leading product marketing for NVIDIA’s robotics platforms. She now sees unfinished work across several parts of the field: actuators, robotic hands, software, and safety standards.
These pieces matter because a robot depends on more than a capable model. Its physical components must move and handle objects, its software must support those actions, and safety standards must address how it operates. Vishwanath’s description suggests that progress in robotics depends on bringing these elements together, not only improving one part of the system.
The “Lego era” label captures that picture: the pieces are important, but the larger capability is still being assembled. It also helps explain why impressive expectations for robotics may run ahead of what the field can deliver today.
The case for a robotics “ChatGPT moment”
Some people expect robotics to reach a defining turning point through a general foundation model. The comparison is to the arrival of ChatGPT, which the article describes as a shockingly capable chatbot launched in late 2022.
General Intuition CEO Pim de Witte offered one version of that forecast earlier this year. He told Equity that a single general foundation model would make much of today’s specialized robotics work redundant and become the field’s breakthrough moment.
That prediction puts the model at the center of the story: one broad system could potentially replace many specialized efforts. Vishwanath’s view points to a different set of requirements. If the hardware, software, and safety foundations remain under construction, a general model by itself may not be enough to produce a comparable shift in robotics.
Why the disagreement matters
The two views describe different paths to progress. One anticipates a leap driven by a general-purpose model; the other emphasizes the unfinished components that let robots operate in the physical world. The distinction matters for understanding what a robotics breakthrough would require.
Vishwanath’s perspective does not dismiss the possibility of major advances. Instead, it frames the current moment as foundational work. The field may need its physical and technical building blocks to develop alongside its models before broader capabilities can take hold.
That framing also tempers expectations. A chatbot can be judged through its responses, while robotics involves physical action as well as software. The source article does not claim that models are irrelevant; it presents Vishwanath’s argument that the surrounding systems and standards are still being rebuilt.
From NVIDIA to early-stage investing
Vishwanath discussed these ideas on TechCrunch’s Equity podcast with Dominic-Madori Davis. The conversation also covered where she is writing her first checks as founder and managing partner of Techable VC.
Her firm invests at an early stage in physical AI across robotics, materials science, and life sciences. The range reflects an interest in technologies tied to the physical world, while her experience at NVIDIA gives context to her view of robotics’ current building blocks.
She also discussed what she has learned as one of the first women executives to spin out of Nvidia and launch her own early-stage firm. Together, her experience in robotics platforms and her investing role inform a measured assessment: the field has potential, but its next phase depends on foundational work as well as advances in AI models.