Robots that deliver coffee to your suite of rooms are swell, but robotics enters another phase when machines can use Deep Learning to grow and adapt. Of course, we might not always like what they do with their newfound knowledge. From Technology.org:

In the near future we may have household robots to handle cooking, cleaning and other menial tasks. They will be teachable: Show the robot how to operate your coffee machine, and it will take over from there.

But suppose you buy a new, different coffee maker. Will you have to start over?

“The robot already has seen two or three coffee machines; it should be able to figure out how to use this one,” said Ashutosh Saxena, assistant professor of computer science. In robotics work up to now, he noted, a robot must be trained for each task and always positioned in the same relationship to the machine and its controls.

In his Robot Learning Lab, Saxena is making robots more adaptable. A new deep-learning algorithm developed by Saxena and graduate student Jaeyong Sung enables a robot to operate a machine it has never seen before, by consulting the instruction manual – probably available online – and drawing on its experience with other machines that have similar controls.

One thing that makes this hard is the “noise” in natural language instructions. Do you turn on the machine with a “knob” or a “switch?” Do you dispense coffee by pulling a “handle” or a “lever?” And then, where is that control on the machine, and what’s the proper way to manipulate it? For this, the robot draws on a database of recorded actions.

“We use a deep learning neural network that can tell the robot which action in a database is the closest to the one it has to perform,” Sung explained.•

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“Press the button to start grinding”: