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    Meet The Clever Robot That's Ready to Take On Your Shopping Addiction

    Robots are historically pretty bad at picking things up. But that's changing thanks to startups like Kindred, which is mixing advanced AI with remote controls to create robots that can pick and sort through objects at dizzying rates.

    Released on 03/01/2018

    Transcript

    [Host] This is the result of your

    online shopping addiction.

    It's a picker robot.

    Its job is to sort through goods

    in an order fulfillment center.

    A task that's traditionally been difficult

    for machines.

    But that's changing.

    Thanks in large part to a mix of AI

    and some good old fashioned human hand-holding.

    I guarantee you take for granted

    how many things you can pick up.

    What comes so naturally to you is

    difficult for a lot of robots.

    But not these picker robots

    at a startup called Kindred.

    They're able to grab a variety of items

    and hold them for a barcode scanner

    and file them in the right cubby hole.

    The big opportunity in e-commerce

    is that there are millions and millions of

    different types of objects.

    Packaging keeps changing,

    some are soft and squishy,

    some are hard, some are heavy, some are soft.

    And there's no way you can program that.

    The challenge for us is

    constantly learning all these new objects

    fast enough to respond to our customers.

    [Host] But fear not.

    The robots still need our help

    learning how to tackle these new objects.

    The team at Kindred lets the robot

    try and grasp objects on its own.

    This is known as reinforcement learning.

    Meaning, it gets a digital thumbs-up

    whenever it does something right.

    And adjusts its behavior accordingly.

    Humans also refine the robot's skills by

    remotely piloting the machine.

    [Man] The human controller guides the arm and the gripper

    to pick up the objects,

    and we use all that data from the gripper

    from the servers from the arm

    to feed our algorithms.

    So the next time they see the same shape,

    we know how to pick it up.

    [Host] This approach provides a flexibility

    that's essential in a job like order fulfillment.

    Not only does the robot need to know how to

    manipulate a galaxy of different objects,

    it has to adapt on the fly to

    novel products.

    So let's say that coats come into season

    for a retailer like Gap.

    Which is, in fact, testing Kindred's robot.

    The machine needs to know how to deal

    with that new shape.

    [George] As winter arrives and we get new objects

    we can start learning of those new objects,

    and then when summer comes back,

    we might see objects we've used before

    and we can switch back to those algorithms

    to pick up those objects.

    Or we might see a whole new class of objects.

    I don't know, maybe

    sombreros become popular one summer

    and now we need to learn how to pick up sombreros.

    [Host] Adaptability is crucial for e-commerce robots.

    Or any robot for that matter.

    We can't just program the machines to manipulate

    each and every one of the dizzying number of objects

    in our world.

    They'll have to think on their own.

    And when that doesn't work,

    we have to be prepared to step in and help

    until they get the hang of things.

    Yes, that'll make us babysitters.

    But better to babysit than let the machines

    get carried away with things.

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