Physical AI is taking artificial intelligence into robotics, enabling machines to navigate and act in the physical world. In this video interview, .lumen founder Cornel Amariei explains how the company first applied physical AI to glasses that guide blind people, why it is now extending that experience into robotics, and why its principle is to build technology that helps people.
Recorded following his keynote at IMAP’s Fall Conference in Bucharest, the accompanying interview explores the ideas behind .lumen’s technology and Cornel’s approach to entrepreneurship: take part in building the next phase of AI, focus on problems worth solving, and “make meaning, not money.”
Cornel describes physical AI as applying artificial intelligence to robotics. While most people currently experience AI through large language models, he sees another field developing around robots that can do things which are currently extremely difficult or impossible for them to do.
“We all know large language models, what ChatGPT, OpenAI and Anthropic is doing. But there’s another thing coming. We call it physical AI, which mostly means robots.”
In the video, Cornel explains why he wants .lumen to contribute directly to that development rather than simply watch it happen elsewhere.
.lumen first applied physical AI to glasses designed to guide people who cannot see through the world around them. Cornel presents that work as the foundation for what the company is now doing with robots.
“What we did with the glasses for the blind, we actually brought physical AI to people who cannot see in order to guide them through the world. And we do that for now for robots.”
The connection between the two is central to the interview: both involve using AI to help navigate the physical world, with the goal of solving practical human problems.
Cornel points to situations where people cannot always have medicine delivered or receive care and assistance when they need it because there are simply not enough people available to provide that support.
He believes robotics can help by enabling machines to travel and navigate the world and carry out tasks that can support people in those situations.
“I want to be part of the part of AI which is helping people, rather than watching other people inventing it.”
For Cornel, that is the reason to work on physical AI: not technology for its own sake, but AI applied to problems where it can help people directly.
“Make meaning, not money” is .lumen’s number-one value. In the interview, Cornel is clear that this does not mean the company does not want to make money. It means starting with the problem and the people who need a solution, rather than making money the first objective.
“We want to fall in love with problems and bring solutions which have one goal, to help people.”
His view is that if a company solves a meaningful problem and helps people, money can follow. The order matters: understand the problem, build a solution that helps, and allow the commercial outcome to come afterwards.
The interview also moves beyond technology into Cornel’s view of entrepreneurship and leadership. He believes people can do extraordinary work when founders create the right context for them to share ideas, identify problems, and work in a way that allows them to shine.
He gives the example of a colleague he considers one of the best industrial designers in the world. In Cornel’s view, the talent was already there; the context and the problem allowed that person to produce the best work of his life.
“Our job as founders, as entrepreneurs, as businessmen, team players, and family members, is to actually build that context for the people around us.”
Cornel brings together three themes that are often discussed separately: physical AI and robotics, the human problems technology can solve, and the role founders play in creating the conditions for people to do exceptional work.
Watch the video interview HERE to hear directly from Cornel Amariei on how .lumen is taking its experience in blind navigation into robotics, why he wants to help shape the development of physical AI, and what “make meaning, not money” means in practice.
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