The Researchers from the University of California, Berkeley, have launched a start-up, Embodied Intelligence, Inc., to use the latest techniques of deep reinforcement learning and artificial intelligence to make industrial robots easily teachable. Robots today must be programmed by writing computer code, but imagine donning a VR headset and virtually guiding a robot through a task, like you would move the arms of a puppet, and then letting the robot take it from there. That's the vision of Pieter Abbeel, a professor of electrical engineering and computer science at the University of California, Berkeley, and his students, Peter Chen, Rocky Duan and Tianhao Zhang, who have launched a startup, Embodied Intelligence Inc., to use the latest techniques of deep reinforcement learning and artificial intelligence to make industrial robots easily teachable. "Right now, if you want to set up a robot, you program that robot to do what you want it to do, which takes a lot of time and a lot of expertise," said Abbeel, who is currently on leave to turn his vision into reality. "With our advances in machine learning, we can write a piece of software once -- machine learning code that enables the robot to learn -- and then when the robot needs to be equipped with a new skill, we simply provide new data."

How to make machines learn on their own similar to humans? This is the pivotal question for the development of artificial intelligence. To develop intelligent machines and systems (artificial intelligence), we need to understand how human intelligence and learning work. For this, we will explore the ideas behind reinforcement learning. In the process, we will also explore answers to these seemingly unrelated questions.

RLAI research is research directed toward the long-standing goals of AI (understanding the mind, reproducing human abilities) and is based on reinforcement learning ideas (learning from and while interacting with the world). RLAI research does not include all that is currently thought of as AI research, only that which addresses problems or issues that people regularly encounter in their everyday lives. Similarly, RLAI research does not include research that uses RL methods to solve problems that people do not face and excel at. There is a delimited and fruitful area of research at the confluence of the most ambitious goals of AI and the solution ideas that are arising from RL research.