A London robotics startup co-founded by a robotics professor and his student, which is building an AI model which claims to have discovered a new, quick way of teaching robots physical jobs, has raised a record $40m seed round, it said today.
Emerging out of stealth today, startup Machenta says the seed funding round, co-led by Creandum and Union Square Ventures, is the largest seed round raised by a robotics company in the UK to date.
The startup was co-founded by Edward Johns, a professor of robot learning at Imperial College, London, and his PhD student Vitalis Vosylius. Machenta is building an AI model that enables robots to learn new tasks quickly, unlike existing methods which can be expensive and time-consuming involving many demonstrations.
Johns likens Machenta's method to "physical vibe coding", saying its model learns tasks immediately.
Machenta has trained its AI model in simulation leveraging computer generated environments, without the use of any real-world data.
It says that once trained, the model can instruct a robot to perform varying tasks immediately, such as packaging, assembling, and tidying, after seeing it performed just once.
The work behind Machenta began six years ago at Imperial College London, where Johns focused on the question of whether a robot could one day learn new physical skills as quickly as a human?
Johns said: “Intelligence is not so much about what you can already do, it’s about how quickly you can learn to do something new. Humans don’t need to see the same thing over and over before they can do it. If you take some objects, and show somebody what to do with them, they’ll probably then be able to do the same task immediately. We’ve spent years trying to understand what it would take for robots to learn at the speed of a human. That is what instant robot learning is about.”
The funds will be used to scale its tech and expand its team, which numbers around a dozen, in its London King's Cross office.