Deep reinforcement learning promises to change the way robots are taught to do tasks
Computer programming is one of the jobs of the future. Right?
Maybe not, as Japanese industrial robot maker Fanuc demonstrates with their latest robot that learns on the job.
The MIT Technology Review describes how the robot analyses a task and fine tunes its own operations to do the task properly.
Fanuc’s robot uses a technique known as deep reinforcement learning to train itself, over time, how to learn a new task. It tries picking up objects while capturing video footage of the process. Each time it succeeds or fails, it remembers how the object looked, knowledge that is used to refine a deep learning model, or a large neural network, that controls its action.
While machines running on deep reinforcement learning won’t completely make programmers totally redundant, it shows basic operations even in those fields are going to be increasingly automated. Just knowing a programming language is not necessarily a passport to future prosperity.
Another aspect flagged in the MIT article is how robots can learn in parallel, so groups can work together to understand and optimise tasks.
While Fanuc and the MIT article are discussing small groups of similar computers working together it’s not hard to see this working on a global scale. What happens when your home vacuum cleaner starts talking to a US Air Force autonomous drone remains to be seen.
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