Robots that learn like humans: they’re here
One of the topics that has captured my imagination in recent months is the way that generative algorithms will soon be widely used in the physical world through the development of robots that, like ourselves, learn by imitating.
The fruits of what has become known as “the OpenAI Mafia”, former employees of the company who have left to set up their own startups, have not been long in coming: Covariant, which emerged from the dismantling of the company’s robotics team due to the lack of data needed to train its robots, is building industrial robots capable of training themselves by imitating videos, which is basically equivalent to a ChatGPT for robots. The idea is to provide robotic mechanisms with ways to learn tasks that work in the same way as large language models (LLMs), and that are powered by observation, allowing them to carry out all kinds of movements or tasks that are physically compatible with their characteristics.
The idea a robot can perform tasks without having to go through a costly and rigid programming process, as was traditionally the case with the eye-catching videos of robots dancing or doing parkour, and instead simply copy any task, opens the door to the idea of replacing many blue-collar tasks with machines capable of working round the clock with unbeatable performance and precision.
