WEBVTT - TechStuff Looks at Robots

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<v Speaker 1>Brought to you by the reinvented two thousand twelve camera.

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<v Speaker 1>It's ready, Are you didn't touch? With technology? With tech

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<v Speaker 1>stuff from how stuff flix dot com. Hello, agaan everyone,

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<v Speaker 1>and welcome to text stuff. My name is Chris Paulette

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<v Speaker 1>and I'm an editor at how Stuff works dot com.

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<v Speaker 1>Sitting across from me, as is typical of days like this, Yeah,

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<v Speaker 1>Friday's That would be senior writer Jonathan Strickland. I looked

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<v Speaker 1>at my notes and I didn't like them. Hey was

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<v Speaker 1>that a quote? What were you actually saying that? It's

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<v Speaker 1>it's both both ay quote and it's true excellent that

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<v Speaker 1>those are always the best, right, Yes they are. So

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<v Speaker 1>today we're going to talk a little bit about robots,

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<v Speaker 1>which we before we started recording, we were I was

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<v Speaker 1>talking about robots. He was insisting on saying robots, So

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<v Speaker 1>I didn't think you would actually do it in the episode.

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<v Speaker 1>Of course I'm going to do it the sod. My

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<v Speaker 1>goal is to alienate all of our listeners until no

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<v Speaker 1>one's left. Uh, and I'm doing quite well, I think.

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<v Speaker 1>Uh No, so robots if you prefer. We we wanted

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<v Speaker 1>to talk about this mainly because there was kind of

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<v Speaker 1>a cool story and and really cool video that came

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<v Speaker 1>out recently recently as the recording of this podcast. This

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<v Speaker 1>is a March twenty three if you're if you guys

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<v Speaker 1>at home or wondering, because you know, of course we

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<v Speaker 1>published these well after we've recorded them. But the story

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<v Speaker 1>was about a company called Kiva. Yes, Kiva Systems technically,

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<v Speaker 1>and Kiva Systems makes robots. They make a warehouse robot

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<v Speaker 1>system that's all about finding and retrieving inventory using potentially

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<v Speaker 1>more than the thousand robots if you were to have

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<v Speaker 1>a really complex system. Now, most of the systems they've

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<v Speaker 1>they've incorporated have been smaller than that, but the idea

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<v Speaker 1>is really cool. And the reason they're in the news

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<v Speaker 1>right now is because, I mean, the company has been

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<v Speaker 1>around since two thousand three, in one form or another.

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<v Speaker 1>It started off as a with a different name, but anyway,

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<v Speaker 1>it's been around since two thousand three. The reason why

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<v Speaker 1>it's kind of hit the news recently is because another

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<v Speaker 1>company has acquired Keyva Systems. Yes, that would be Amazon

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<v Speaker 1>dot Com. Yes, for the princely sum of seven dred

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<v Speaker 1>and seventy five million dollars, so just under a billion um.

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<v Speaker 1>So yeah, this is a big news and you would think, oh, well,

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<v Speaker 1>that makes perfect sense that Amazon would go after something

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<v Speaker 1>like this, like they would at least employ a system

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<v Speaker 1>like this, if not actually go out and acquire it,

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<v Speaker 1>because I mean Amazon is all about warehouse management in

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<v Speaker 1>order to fulfill customer needs. So yeah, So the company

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<v Speaker 1>actually was started in two thousand three, as we said

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<v Speaker 1>a moment ago, by a guy named Mick mounts Um,

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<v Speaker 1>and he knows a lot about fulfillment. He actually kind

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<v Speaker 1>of learned the hard way by being part of a

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<v Speaker 1>company known as Webvan. So web Ban, for those who

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<v Speaker 1>don't remember, was an online service where you could actually

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<v Speaker 1>order groceries online and this company would go out and

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<v Speaker 1>fill the orders and deliver them to your door, so

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<v Speaker 1>that way you didn't have to go out to the

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<v Speaker 1>grocery store. And this this was one of those companies

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<v Speaker 1>that was was expanding very quickly just before the dot

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<v Speaker 1>com bubble burst and there was the big crash. So

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<v Speaker 1>if you've heard O our podcast about the dot com crash,

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<v Speaker 1>you probably heard us talk about web Ban. Part of

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<v Speaker 1>the problem they had was that the cost for their

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<v Speaker 1>system was greater than they had originally um projected, and

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<v Speaker 1>so they were not able to bring in enough revenue

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<v Speaker 1>to cover their costs and as a result that the

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<v Speaker 1>company itself collapsed. Yeah. Mr Mount seems to be one

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<v Speaker 1>of those people that learns from experience. Well, that seems

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<v Speaker 1>like a reasonably good thing to do. Yeah, that he

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<v Speaker 1>I think it kind of bugged him based on what

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<v Speaker 1>on the information that I've picked up up on on

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<v Speaker 1>doing the research and and he started thinking, you know what,

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<v Speaker 1>there's got to be a better way to handle UH

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<v Speaker 1>storage and fulfillment. So yeah, he has a very technical background.

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<v Speaker 1>Um you know, and uh, I believe as a matter

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<v Speaker 1>of fact, he's an m I T graduate, M I

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<v Speaker 1>T and Harvard Business School graduates, so he had he's

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<v Speaker 1>probably reasonably well equipped to handle this kind of technical

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<v Speaker 1>and the business background. He also partnered with two other people, uh,

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<v Speaker 1>Raphaelio Dondrea. Thanks there, Hoffey. It's hard for me to say.

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<v Speaker 1>Who was a engineering professor at Cornell and then at

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<v Speaker 1>e t H which is the Swiss Federal Institute of Technology. Yeah,

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<v Speaker 1>he had led Cornell to several UH tournament victories in

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<v Speaker 1>a in robotics competition. It's like the robo soccer games. Yeah. Yeah,

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<v Speaker 1>he he had actually helped design robots that were able

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<v Speaker 1>to uh to to accomplish goals in a very efficient way.

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<v Speaker 1>And so when Mounts was looking for potential folks too

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<v Speaker 1>to work with, Dendrea became one of the natural people

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<v Speaker 1>that he should see because of his his extensive experience

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<v Speaker 1>with the robotics. And then the third founder is Peter Wherman,

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<v Speaker 1>who is a multi agent systems expert and a former

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<v Speaker 1>professor of computer science with North Carolina State University. So, uh,

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<v Speaker 1>and I think they were friends first, they didn't. It

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<v Speaker 1>wasn't just one of those like personality. Yeah. So they

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<v Speaker 1>these these three men were combining their knowledge to try

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<v Speaker 1>and build out a system of robots that could fill

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<v Speaker 1>this need of being able to seek out inventory within

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<v Speaker 1>a warehouse, retrieve it and bring it back to someone

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<v Speaker 1>for packaging. So when you're filling an order for a customer,

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<v Speaker 1>you're working in a warehouse and you the order comes in.

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<v Speaker 1>A customer has asked for a particular kind of DDD player,

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<v Speaker 1>and that one DVD player is located on one shelf

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<v Speaker 1>in this massive warehouse. It takes a lot of time

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<v Speaker 1>for a human to track down which shelf it is,

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<v Speaker 1>walk to that section of the warehouse, retrieve it from

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<v Speaker 1>their walk back to the shipping department and ship that out.

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<v Speaker 1>So the idea here is that you would have a

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<v Speaker 1>robot system where as soon as an order comes in

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<v Speaker 1>and uh and a person is ready to ship it,

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<v Speaker 1>that person pushes a button, the robot zooms off exactly

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<v Speaker 1>to the point where the the item is lifts up

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<v Speaker 1>that entire shelf. Because the robots, if you were to

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<v Speaker 1>look at these things, they look kind of like room

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<v Speaker 1>buzz that are on steroids. You know. They're these sort

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<v Speaker 1>of sort of squarish robots that have rounded it rounded

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<v Speaker 1>corners um and they are they're low to the ground

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<v Speaker 1>and they run on wheels, and so when you look

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<v Speaker 1>at them, they don't you know, they're not humanoid or

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<v Speaker 1>anything like that. They what they do is they scoot

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<v Speaker 1>around on the floor underneath the shelves and then what

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<v Speaker 1>they have a little screw drive that comes up. It

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<v Speaker 1>lifts a platform up that lifts the shelves off the floor.

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<v Speaker 1>And in fact, the robot rotates in an opposite direction

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<v Speaker 1>of the screw at the same rate, so that the

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<v Speaker 1>platform remains from the shelf's perspective stationary, and just it

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<v Speaker 1>increases in height, but it does not rotate. Yeah. Now

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<v Speaker 1>if you if you think about it, this is this

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<v Speaker 1>is important because you have a vertical shelf. These are

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<v Speaker 1>essentially UM a rectangular prism going straight up. So the

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<v Speaker 1>base of the shelf is square and and is roughly

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<v Speaker 1>just larger than this robot. Um. But it goes up

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<v Speaker 1>and it's got stuff on it. Well, you know, if

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<v Speaker 1>you have things on the higher shelves but not necessarily

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<v Speaker 1>on the lower shelves, that's going to change the center

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<v Speaker 1>of gravity considerably. And if um, this this screw drive

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<v Speaker 1>didn't have that counter rotation, uh, it could cause the

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<v Speaker 1>shelf to topple or be unsteady. And the thing is UM.

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<v Speaker 1>When I first started getting interested in in the Kiva

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<v Speaker 1>story and was watching the videos, I was and that's

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<v Speaker 1>so cool watching the little bot outside spin like that.

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<v Speaker 1>It's really cute. UM. And then I realized that it's

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<v Speaker 1>being done for a very specific reason. And not only

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<v Speaker 1>is it cool looking, it's functional. Functional. Yeah. So it

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<v Speaker 1>lifts the shelf directly off the floor, and then it

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<v Speaker 1>will maneuver back to the person who has pushed the

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<v Speaker 1>button to fill this order. It then shines a laser

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<v Speaker 1>pointer essentially onto the particular item that needs to be

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<v Speaker 1>scanned and shipped, and so then the worker would pick

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<v Speaker 1>up that item, scan it, put it in a box,

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<v Speaker 1>and tape it up, and then it's ready to be

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<v Speaker 1>shipped out to the customer. UH. And then the robot

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<v Speaker 1>will take the shelf back to where it needs to be.

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<v Speaker 1>And meanwhile there's a computer system that's keeping track of

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<v Speaker 1>all of these movements. That's it's not just the movements

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<v Speaker 1>of the robots, but where the shelves are currently located,

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<v Speaker 1>what orders have gone out, and sort of an inventory

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<v Speaker 1>control system. So you've got you've got multiple layers of

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<v Speaker 1>software here. You've got a certain layer of software that's

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<v Speaker 1>in the robot, you have a certain layer of software

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<v Speaker 1>that's in the workers station where they are filling out orders,

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<v Speaker 1>and then you have the overall system. You have layers

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<v Speaker 1>in there as well, and there's a lot of overlaps

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<v Speaker 1>so that robots don't need to know necessarily everything every

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<v Speaker 1>other robots doing, but the system does. And the reason

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<v Speaker 1>for that is if you've got hundreds of robots all

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<v Speaker 1>going through this warehouse filling out orders, then there's a

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<v Speaker 1>lot of potential for collisions, which would be a bad thing.

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<v Speaker 1>You don't want like, oh, there's this one robot carrying

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<v Speaker 1>a shelf full of snow globes, and as other robot

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<v Speaker 1>carrying a shelf full of DVDs, and as other robot

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<v Speaker 1>carrying a shelf full of paint guns, and the three

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<v Speaker 1>of them converge, and then you have a combo that

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<v Speaker 1>just doesn't work even in a Reese's Peanut Buttercup kind

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<v Speaker 1>of universe. So it's sort of like a robot in

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<v Speaker 1>a china shop. Yeah, it really is. So the system

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<v Speaker 1>has to keep track of where all the robots are,

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<v Speaker 1>and the robots have various ways of the hecting what

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<v Speaker 1>other robots are nearby, so that way they can all

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<v Speaker 1>move through and reach their goals without colliding with one another.

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<v Speaker 1>And it's actually, if you watch the videos, it's it's

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<v Speaker 1>captivating to see how these robots will move within fifteen

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<v Speaker 1>centimeters of one another, get so close to each other,

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<v Speaker 1>and yet they'll stop in enough time allow one to

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<v Speaker 1>go through and the next one will pass on, and

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<v Speaker 1>and you multiply that by a hundred, and it's just

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<v Speaker 1>phenomenal to see this kind of it's almost like it's

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<v Speaker 1>almost like a BF ballet. Well, um, One of the

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<v Speaker 1>things too, that the computer system is doing, um to

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<v Speaker 1>handle this is it's not just inventory control, it's traffic

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<v Speaker 1>control as well. But the bots also have a part

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<v Speaker 1>in this. Now. Um, if you haven't seen this yet

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<v Speaker 1>and you're going to go check out a video, you

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<v Speaker 1>might have this picture in your head of a lot

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<v Speaker 1>of robotic carried shelves running around willy nilly. Well, that's

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<v Speaker 1>not exactly the way it works. If you look at

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<v Speaker 1>the videos closely, or even if you don't, you could

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<v Speaker 1>see their patterns on the floor and you might say,

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<v Speaker 1>you know, well, you know, they kind of look like tracks,

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<v Speaker 1>but they're not tracks. Um, not in the sense of

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<v Speaker 1>a railroad sort of system or tracks that are embedded

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<v Speaker 1>in the floor. The robots must follow, right, which is

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<v Speaker 1>which is kind of interesting too, because you know, something

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<v Speaker 1>like that would dramatically increase the cost of installing a

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<v Speaker 1>system like this. Instead, Um, it's an optical system. It

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<v Speaker 1>basically has barcodes, if you will, in the different pathways

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<v Speaker 1>that are are you know, painted onto the floor or

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<v Speaker 1>however they are attached. I'm not sure exactly how they

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<v Speaker 1>are are imprinted on the floor. Um. Anyway, the the

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<v Speaker 1>robots have scanning system built into the bottoms of them,

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<v Speaker 1>so they know, uh, the the UM control system can

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<v Speaker 1>tell them what path to follow, you know, get on

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<v Speaker 1>track number two because there's another robot coming back this

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<v Speaker 1>way on track number one, and it tells it how

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<v Speaker 1>far to go over and exactly where to go. UM.

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<v Speaker 1>And it's also very cool to watch the human employees

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<v Speaker 1>engage with this system because UM unlike past inventory systems

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<v Speaker 1>where a worker would have to walk down rows of

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<v Speaker 1>shelves to retrieve a particular item or two if something

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<v Speaker 1>comes back to put the item back where it belongs,

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<v Speaker 1>the shelves come to them. So they are standing at

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<v Speaker 1>their workstation UM ready to package things up. And uh,

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<v Speaker 1>it's it's very actually, I don't know if you've watched

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<v Speaker 1>any of these videos, these particular videos, not just the

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<v Speaker 1>traffic stuff. UM. It's actually kind of creepy because the

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<v Speaker 1>the employee will take off a box and we'll scan

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<v Speaker 1>it with a little handheld laser scanner and put it

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<v Speaker 1>down on their station and the shelf will just drive

0:12:51.920 --> 0:12:55.040
<v Speaker 1>off and the next one will move over to the

0:12:55.120 --> 0:12:58.000
<v Speaker 1>shelf space at their station and wait for them to

0:12:58.120 --> 0:13:01.040
<v Speaker 1>scan the item that that belongs. UH. In the in

0:13:01.080 --> 0:13:03.200
<v Speaker 1>the package. So you know, the person will put in

0:13:03.200 --> 0:13:05.439
<v Speaker 1>the package and tape it up and put the label

0:13:05.480 --> 0:13:08.280
<v Speaker 1>on it and send it down that the conveyor to

0:13:08.400 --> 0:13:11.960
<v Speaker 1>shipping um and then you know, this next box comes out,

0:13:12.000 --> 0:13:14.480
<v Speaker 1>they'll scan it and the shelf drives off on its

0:13:14.480 --> 0:13:17.320
<v Speaker 1>own um. And the same thing too for returns. The

0:13:17.360 --> 0:13:19.800
<v Speaker 1>shelf drives out, they'll put they'll scan an item, put

0:13:19.800 --> 0:13:22.880
<v Speaker 1>it on the shelf, and the shelf drives off. It's

0:13:22.920 --> 0:13:25.360
<v Speaker 1>really kind of weird, but the employees that I saw

0:13:25.400 --> 0:13:28.880
<v Speaker 1>interviewed said it's much less taxing and they can get

0:13:29.040 --> 0:13:32.760
<v Speaker 1>far more work done because they're retrieving more items or

0:13:32.880 --> 0:13:34.960
<v Speaker 1>or putting more items back on the shelf, and they

0:13:34.960 --> 0:13:37.000
<v Speaker 1>don't have to do nearly as much work to achieve

0:13:37.080 --> 0:13:40.680
<v Speaker 1>that because the shelves themselves are doing the work. Yeah,

0:13:40.679 --> 0:13:46.600
<v Speaker 1>and currently the robots UM the regular production model can

0:13:46.679 --> 0:13:52.160
<v Speaker 1>carry up to four which is a thousand pounds. That's

0:13:52.160 --> 0:13:53.440
<v Speaker 1>a lot of weight. It's a lot of weight, but

0:13:53.480 --> 0:13:56.319
<v Speaker 1>it's still they're working. They have other prototype models that

0:13:56.360 --> 0:13:59.000
<v Speaker 1>can carry much more than that because depending on what

0:13:59.120 --> 0:14:02.599
<v Speaker 1>you're shipping around maybe like for example, a warehouse that

0:14:02.720 --> 0:14:05.040
<v Speaker 1>has lots of masonry in it, it's going to be

0:14:05.160 --> 0:14:07.920
<v Speaker 1>really lots of heavy palettes and shelves and stuff. You

0:14:07.920 --> 0:14:10.160
<v Speaker 1>would have to have a robot capable caring much more

0:14:10.200 --> 0:14:14.400
<v Speaker 1>than a thousand pounds in that case. These these robots

0:14:14.440 --> 0:14:19.640
<v Speaker 1>do increase efficiency. I saw some projections that suggested that

0:14:20.240 --> 0:14:23.520
<v Speaker 1>a factory that uses conveyor belts and and you know,

0:14:23.640 --> 0:14:28.240
<v Speaker 1>more conventional systems to get materials to the people who

0:14:28.240 --> 0:14:31.880
<v Speaker 1>need to ship them out, that it might take for

0:14:32.040 --> 0:14:35.920
<v Speaker 1>a typical warehouse something like seventy five workers to be

0:14:36.000 --> 0:14:40.400
<v Speaker 1>able to um to to carry out the orders a

0:14:40.400 --> 0:14:42.160
<v Speaker 1>certain number of orders in a certain amount of time,

0:14:42.240 --> 0:14:44.680
<v Speaker 1>but in using this system would be more like twenty five.

0:14:45.320 --> 0:14:48.520
<v Speaker 1>So you've just reduced the need of your workforce significantly

0:14:48.880 --> 0:14:52.600
<v Speaker 1>and by fifty people, which means savings for the company.

0:14:52.960 --> 0:14:56.600
<v Speaker 1>This also brings us to another discussion that always comes

0:14:56.680 --> 0:15:00.480
<v Speaker 1>up when we talk about industrialization and autumns, Asian and

0:15:00.600 --> 0:15:04.840
<v Speaker 1>robots in particular, which is the concern that these systems

0:15:04.840 --> 0:15:09.880
<v Speaker 1>will replace human beings and reduce the need for human workers,

0:15:09.880 --> 0:15:15.240
<v Speaker 1>thus in a way contributing to the unemployment rate, which

0:15:15.280 --> 0:15:17.560
<v Speaker 1>is which is a legitimate concern. I mean there is

0:15:18.840 --> 0:15:21.040
<v Speaker 1>it is there is a legitimate concern that there are

0:15:21.320 --> 0:15:24.760
<v Speaker 1>certain systems involved that will reduce the need for people

0:15:24.760 --> 0:15:27.520
<v Speaker 1>to work and therefore more people will be out of work. Now,

0:15:27.560 --> 0:15:31.120
<v Speaker 1>this is a story that has been with us since

0:15:31.320 --> 0:15:34.600
<v Speaker 1>the dawn of the industrialization age. You've heard Chris talk

0:15:34.840 --> 0:15:39.040
<v Speaker 1>about the sabo that wooden shoes being thrown into a

0:15:39.120 --> 0:15:43.120
<v Speaker 1>loom in order to sabotage the loom, because these these

0:15:43.160 --> 0:15:46.600
<v Speaker 1>looms were somewhat you know, not automated in the sense

0:15:46.640 --> 0:15:49.640
<v Speaker 1>that we think about today, but they were following a program,

0:15:49.680 --> 0:15:54.880
<v Speaker 1>and we're reducing the needs of a skilled weaver so

0:15:54.960 --> 0:15:58.200
<v Speaker 1>that you know, you could have a semi unskilled worker

0:15:58.400 --> 0:16:01.040
<v Speaker 1>run this machine and they could produced the same sort

0:16:01.040 --> 0:16:03.960
<v Speaker 1>of quality of work that a skilled weaver could. That

0:16:04.240 --> 0:16:09.240
<v Speaker 1>raised concerns back in pre industrial Europe. Well that we've

0:16:09.280 --> 0:16:13.360
<v Speaker 1>seen that whole story unfold throughout the eras of of

0:16:13.600 --> 0:16:17.680
<v Speaker 1>industry and um there's been some people who say, sure,

0:16:18.080 --> 0:16:20.680
<v Speaker 1>it's going to take over those those manufacturing jobs, but

0:16:20.720 --> 0:16:23.000
<v Speaker 1>then they're gonna be more jobs opened up because you're

0:16:23.000 --> 0:16:25.400
<v Speaker 1>gonna have people who need to make the robots and

0:16:25.440 --> 0:16:30.040
<v Speaker 1>repair the robots, which is true, but it's not a

0:16:30.080 --> 0:16:34.360
<v Speaker 1>one to one. First of all, the skill set you

0:16:34.400 --> 0:16:37.000
<v Speaker 1>need to work on a factory floor, and the skill

0:16:37.040 --> 0:16:39.560
<v Speaker 1>set you need to maintain or build a robot are

0:16:39.720 --> 0:16:43.600
<v Speaker 1>dramatically different. Uh. It's not to say that someone can't

0:16:43.640 --> 0:16:47.080
<v Speaker 1>master both sets of skills, but it's just it's not

0:16:47.160 --> 0:16:52.960
<v Speaker 1>like it's automatically transferable. And secondly, you don't need as

0:16:53.000 --> 0:16:56.680
<v Speaker 1>many people building out or maintaining robots as you would

0:16:56.720 --> 0:17:00.560
<v Speaker 1>to maintain the number of people you need to maintain

0:17:00.680 --> 0:17:04.200
<v Speaker 1>or build the robots for a warehouse of robots, there's

0:17:04.240 --> 0:17:06.840
<v Speaker 1>fewer than the number of workers you would have if

0:17:06.840 --> 0:17:09.960
<v Speaker 1>there are no robots at all, right, for that same warehouse.

0:17:10.400 --> 0:17:12.280
<v Speaker 1>So no matter what, you still have people who are

0:17:12.320 --> 0:17:15.560
<v Speaker 1>not going to have work, at least not in that warehouse.

0:17:16.080 --> 0:17:20.280
<v Speaker 1>So what this really brings to light is that there

0:17:20.320 --> 0:17:24.439
<v Speaker 1>needs to be a focus in the education phase to

0:17:24.560 --> 0:17:28.000
<v Speaker 1>make sure that whatever education you are getting is going

0:17:28.040 --> 0:17:31.760
<v Speaker 1>to be uh something that is usable in the workforce,

0:17:32.320 --> 0:17:35.440
<v Speaker 1>because the skill sets that the workforce is looking for

0:17:35.880 --> 0:17:39.240
<v Speaker 1>may be dramatically different than what are being offered within

0:17:39.320 --> 0:17:45.200
<v Speaker 1>the education system. So the burden of responsibility falls on

0:17:45.640 --> 0:17:49.200
<v Speaker 1>not just the students, but the education system itself because

0:17:49.200 --> 0:17:51.640
<v Speaker 1>we have these education systems out there that are not

0:17:51.680 --> 0:17:55.000
<v Speaker 1>necessarily offering the same sort of courses that would be

0:17:55.080 --> 0:17:57.720
<v Speaker 1>useful to a person once they graduate to get a job.

0:17:58.600 --> 0:18:00.480
<v Speaker 1>And part of that is because the education system is

0:18:00.480 --> 0:18:04.440
<v Speaker 1>not terribly nimble. It's a it's an institution, and institutions

0:18:04.480 --> 0:18:08.680
<v Speaker 1>have a lot of of inertia gas and yet it's

0:18:08.720 --> 0:18:11.439
<v Speaker 1>really hard to get them to to respond quickly to

0:18:11.560 --> 0:18:14.840
<v Speaker 1>changing situations because that's just not in their nature. So

0:18:15.800 --> 0:18:20.040
<v Speaker 1>we do have this issue of robots potentially taking away

0:18:20.119 --> 0:18:23.320
<v Speaker 1>jobs and even jobs like not not just with the

0:18:23.400 --> 0:18:26.640
<v Speaker 1>KEYVA systems. I mean, that's one element, right, but this

0:18:26.720 --> 0:18:31.119
<v Speaker 1>goes across all all kinds of industries, not just warehouses.

0:18:31.600 --> 0:18:36.000
<v Speaker 1>We've seen other industries also affected by this UM. So

0:18:36.119 --> 0:18:42.840
<v Speaker 1>you've got that concern. Well, hopefully the ideal UM outcome

0:18:43.000 --> 0:18:46.240
<v Speaker 1>is that people will be able to start focusing on

0:18:46.400 --> 0:18:51.280
<v Speaker 1>the types of skills that robots really aren't designed to handle,

0:18:51.880 --> 0:18:54.119
<v Speaker 1>and that there will still be plenty of work to

0:18:54.119 --> 0:18:56.600
<v Speaker 1>go around. It's just that there has to be a

0:18:56.640 --> 0:18:59.680
<v Speaker 1>new focus on the type of work that you can

0:18:59.720 --> 0:19:04.360
<v Speaker 1>pursue to. It really starts to hit people who may

0:19:04.400 --> 0:19:07.920
<v Speaker 1>not have a lot of formal education. Uh, they are

0:19:07.960 --> 0:19:12.639
<v Speaker 1>at the greatest disadvantage in that their jobs, depending on

0:19:12.720 --> 0:19:15.119
<v Speaker 1>what industry there and their jobs maybe one of the

0:19:15.200 --> 0:19:20.160
<v Speaker 1>jobs that are easily converted to robotics. Uh. And they

0:19:20.200 --> 0:19:23.960
<v Speaker 1>are not. They don't have a background in education where

0:19:24.000 --> 0:19:28.760
<v Speaker 1>they can easily switch gears. Uh. So we're probably gonna

0:19:28.760 --> 0:19:35.439
<v Speaker 1>see continued bouts of of uncertainty and and and doubt.

0:19:36.400 --> 0:19:38.040
<v Speaker 1>Might as well throw fear in there to get the

0:19:38.040 --> 0:19:40.879
<v Speaker 1>whole fund in there. And uh, there's probably gonna be

0:19:40.960 --> 0:19:45.600
<v Speaker 1>some some rocky, some rocky travels between now and when

0:19:45.640 --> 0:19:49.560
<v Speaker 1>we reach our idyllic civilization where the robots cater to

0:19:49.600 --> 0:19:56.159
<v Speaker 1>our every need and we don't even have money anymore. Okay. Well, also,

0:19:56.800 --> 0:20:00.159
<v Speaker 1>you know, if you if you remember in the the

0:20:01.359 --> 0:20:05.040
<v Speaker 1>on the documentary Rocky three, Uh, they do have a robot.

0:20:05.880 --> 0:20:09.879
<v Speaker 1>They buy a robot Rocky I forgot about. And the

0:20:09.960 --> 0:20:12.720
<v Speaker 1>uncle gets to play with a robot. It always brings

0:20:12.760 --> 0:20:18.200
<v Speaker 1>him a frosty beverage. Yes, anyway, I mean, yeah, they're

0:20:18.240 --> 0:20:21.679
<v Speaker 1>they're Kiva's um by far not the only company to

0:20:21.720 --> 0:20:25.720
<v Speaker 1>be building uh equipment like this, that's true. And one

0:20:25.760 --> 0:20:29.000
<v Speaker 1>of the uh, you know, I've seen several I'm fascinated

0:20:29.040 --> 0:20:33.960
<v Speaker 1>by industrial machinery type programs in there. Many on our

0:20:34.440 --> 0:20:38.439
<v Speaker 1>parent companies networks where they make stuff in store stuff,

0:20:38.440 --> 0:20:40.480
<v Speaker 1>and I just find it fascinating to see. But one

0:20:40.520 --> 0:20:43.840
<v Speaker 1>of the advantages of the Kiva system UH is that

0:20:44.280 --> 0:20:46.480
<v Speaker 1>it is able to store things in a far more

0:20:46.560 --> 0:20:52.240
<v Speaker 1>dense fashion UH, therefore making the most of warehouse space. UM.

0:20:52.320 --> 0:20:55.560
<v Speaker 1>And it does that on a on a horizontal plane.

0:20:55.680 --> 0:20:58.520
<v Speaker 1>Because really these shelves are built UH and they can

0:20:58.560 --> 0:21:00.720
<v Speaker 1>be configured in a number of it s, you know,

0:21:00.800 --> 0:21:03.879
<v Speaker 1>depending on what the customer needs. UM. But they the

0:21:03.920 --> 0:21:06.440
<v Speaker 1>shelves are all the same more or less for for

0:21:06.480 --> 0:21:10.680
<v Speaker 1>these robots UM. However, I have seen warehouses that are

0:21:10.800 --> 0:21:14.560
<v Speaker 1>very very tall and they have rigid shelving UM and

0:21:14.600 --> 0:21:20.800
<v Speaker 1>their robotic systems that can travel horizontally and then vertically

0:21:20.880 --> 0:21:24.840
<v Speaker 1>up to a bin that could be stories high UM

0:21:24.920 --> 0:21:27.840
<v Speaker 1>and lifts it off with a forklift. You know. They

0:21:27.880 --> 0:21:30.960
<v Speaker 1>have optical readers very much the same as that Cuba

0:21:31.000 --> 0:21:34.280
<v Speaker 1>systems do, where there are codes on the bins and

0:21:34.280 --> 0:21:36.280
<v Speaker 1>it can scan the code and say, okay, well the

0:21:36.359 --> 0:21:40.280
<v Speaker 1>beIN in a fourteen level six is the one that

0:21:40.320 --> 0:21:41.960
<v Speaker 1>I need. And it goes up and with the little

0:21:42.000 --> 0:21:44.560
<v Speaker 1>forklift it you know, pulls out the bin and moves

0:21:44.600 --> 0:21:47.639
<v Speaker 1>the parts down to the assembly line. UM, and I

0:21:47.840 --> 0:21:52.200
<v Speaker 1>find that completely fascinating, but really that that maximizes the

0:21:52.320 --> 0:21:56.479
<v Speaker 1>use of the human workers that are there. UM. So

0:21:56.800 --> 0:21:59.600
<v Speaker 1>I think there is a trade off to be made, UM,

0:21:59.640 --> 0:22:03.600
<v Speaker 1>because these systems do and UH make the work a

0:22:03.640 --> 0:22:07.680
<v Speaker 1>lot less taxing for for those people, and it does

0:22:07.720 --> 0:22:11.800
<v Speaker 1>give them UH an opportunity to be more productive at

0:22:11.840 --> 0:22:14.600
<v Speaker 1>their jobs, which I think, at least for some people,

0:22:14.600 --> 0:22:18.679
<v Speaker 1>would be more more fulfilling. Also, the robots, especially in

0:22:18.680 --> 0:22:22.160
<v Speaker 1>the again in the Kiva systems, because you know, I've

0:22:22.200 --> 0:22:25.880
<v Speaker 1>done primarily that research for this UH for this podcast,

0:22:26.080 --> 0:22:29.960
<v Speaker 1>that the systems are more quiet than the conveyor belt systems.

0:22:30.000 --> 0:22:32.600
<v Speaker 1>Some of the employees that they interviewed for one of

0:22:32.600 --> 0:22:36.560
<v Speaker 1>the news reports UM said that whereas before in the

0:22:37.080 --> 0:22:39.600
<v Speaker 1>conveyor areas they used to have to shout to make

0:22:39.640 --> 0:22:43.160
<v Speaker 1>themselves heard UM when they needed to, you know, talk

0:22:43.160 --> 0:22:46.800
<v Speaker 1>to one another, in the robotics room, they basically can

0:22:46.800 --> 0:22:49.919
<v Speaker 1>talk in a normal voice. UM. There are fewer injuries,

0:22:50.200 --> 0:22:53.439
<v Speaker 1>which also seems like it would be a boon for employees,

0:22:53.480 --> 0:22:56.159
<v Speaker 1>but that, of course only applies so long as the

0:22:56.280 --> 0:22:59.600
<v Speaker 1>robots don't develop sentients and decided to kill all humans

0:23:02.000 --> 0:23:04.760
<v Speaker 1>and they follow the laws of robotics, we should be

0:23:04.800 --> 0:23:09.600
<v Speaker 1>pretty much all right, all right, um, and there's a um,

0:23:09.600 --> 0:23:12.280
<v Speaker 1>you know, better climate control to which is a cost savings.

0:23:12.320 --> 0:23:17.719
<v Speaker 1>Hopefully they will pass the savings on to the workers. Well, here,

0:23:17.760 --> 0:23:20.760
<v Speaker 1>the thing is the efficiencies and the you know, as

0:23:20.800 --> 0:23:24.960
<v Speaker 1>you improve efficiencies, then ideally that means you can either

0:23:25.320 --> 0:23:27.639
<v Speaker 1>do one of two things. You keep prices the same

0:23:27.760 --> 0:23:31.560
<v Speaker 1>and your profit margins go up, or you reduce prices

0:23:31.600 --> 0:23:36.440
<v Speaker 1>and you pass the savings on to everyone else. But yeah,

0:23:36.480 --> 0:23:38.800
<v Speaker 1>it all depends on how the company works. But yeah,

0:23:38.840 --> 0:23:43.719
<v Speaker 1>I mean it's these systems are in general, I think

0:23:43.760 --> 0:23:46.720
<v Speaker 1>they're a good thing. In the short term, they're definitely

0:23:46.720 --> 0:23:49.320
<v Speaker 1>going to be something that could potentially cause a lot

0:23:49.359 --> 0:23:53.200
<v Speaker 1>of upheaval, but in the long term, I think that

0:23:53.280 --> 0:23:56.800
<v Speaker 1>it's you know, it's definitely a benefit. Yeah, yeah, I

0:23:56.840 --> 0:24:00.280
<v Speaker 1>think so. Um. By the way, in case you're undering,

0:24:00.600 --> 0:24:04.160
<v Speaker 1>although Amazon did did make this purchase, and it's unclear

0:24:04.240 --> 0:24:08.200
<v Speaker 1>whether they were going to continue to allow other competitors

0:24:08.240 --> 0:24:10.760
<v Speaker 1>to buy these systems at this point because it is

0:24:10.840 --> 0:24:13.880
<v Speaker 1>a pretty new deal, I would imagine they would continue

0:24:13.920 --> 0:24:16.560
<v Speaker 1>just because of be another stream of revenue. But yeah, well,

0:24:16.600 --> 0:24:19.320
<v Speaker 1>you know, they're never to be smart company, but who knows,

0:24:19.400 --> 0:24:21.639
<v Speaker 1>they might say this is well when which case, it

0:24:21.680 --> 0:24:24.480
<v Speaker 1>gives an opportunity to a competitor to come out with

0:24:24.520 --> 0:24:28.840
<v Speaker 1>their own system and um people like Toys r US

0:24:29.000 --> 0:24:33.360
<v Speaker 1>and Timberland UM. Several Amazon subsidiaries have been using these

0:24:33.359 --> 0:24:36.240
<v Speaker 1>devices for for quite some time, like Quidsy, which owns

0:24:36.320 --> 0:24:39.880
<v Speaker 1>a wag dot com which is a pet food uh company,

0:24:39.880 --> 0:24:42.760
<v Speaker 1>and diapers dot com and soap dot com uh, plus

0:24:43.160 --> 0:24:46.840
<v Speaker 1>Zappos UM and they also I think Walgreens was using

0:24:46.840 --> 0:24:53.440
<v Speaker 1>it as well. Walgreens uses it crighton barrel uh, stap Laze, oh, Staples. Oh.

0:24:53.520 --> 0:24:59.200
<v Speaker 1>I always wondered about that. Yes, the gap sacks fifth.

0:24:59.600 --> 0:25:02.080
<v Speaker 1>You have to mind the gap, especially if you're in

0:25:02.080 --> 0:25:05.440
<v Speaker 1>the UK. UM. But yeah, so they already had a

0:25:05.440 --> 0:25:09.320
<v Speaker 1>pretty good client base. UM. But really that that princely

0:25:09.400 --> 0:25:11.960
<v Speaker 1>some when you think about it is of seven seventy

0:25:12.000 --> 0:25:14.760
<v Speaker 1>five million that what that was the second highest Amazon

0:25:14.840 --> 0:25:20.399
<v Speaker 1>acquisition UM after Zappos, which it picked up for eighty

0:25:20.440 --> 0:25:23.560
<v Speaker 1>seven million dollars. But Amazon has said that they're going

0:25:23.600 --> 0:25:27.320
<v Speaker 1>to uh bring their total of warehouses up to sixty nine,

0:25:27.440 --> 0:25:31.760
<v Speaker 1>opening seventeen new warehouses. So this acquisition over the long haul,

0:25:31.880 --> 0:25:34.000
<v Speaker 1>is going to save the company quite a bit of money,

0:25:34.440 --> 0:25:37.119
<v Speaker 1>especially if they can build out their warehouses with this

0:25:37.200 --> 0:25:41.359
<v Speaker 1>technology instead of retrofitting. O ye, if they building it

0:25:41.359 --> 0:25:44.280
<v Speaker 1>out with it in mind so that they maximize that

0:25:44.320 --> 0:25:49.120
<v Speaker 1>efficiency and uh, then you know they'll they'll definitely benefit

0:25:49.119 --> 0:25:54.000
<v Speaker 1>from that. By the way, do you know what company

0:25:54.000 --> 0:25:58.280
<v Speaker 1>built the very first industrial robot? The very first industrial robot?

0:25:58.920 --> 0:26:03.640
<v Speaker 1>Was it Honda Unimation Nation in nineteen fifty six. They

0:26:03.640 --> 0:26:06.280
<v Speaker 1>were developed from there was a fellow named George da

0:26:06.320 --> 0:26:12.320
<v Speaker 1>Vole who created the patents for a a automated robotics

0:26:12.400 --> 0:26:16.480
<v Speaker 1>system and these were using hydraulics that would pass very

0:26:16.520 --> 0:26:20.320
<v Speaker 1>heavy objects from one point to another that we're twelve

0:26:20.359 --> 0:26:24.240
<v Speaker 1>ft apart from each other. So kind of the great

0:26:24.280 --> 0:26:27.480
<v Speaker 1>great granddaddy of the Cuba Systems robots. Yeah, it also

0:26:27.560 --> 0:26:30.959
<v Speaker 1>bring heavy things to you. Well, um you know, like

0:26:31.000 --> 0:26:33.800
<v Speaker 1>I said, I love watching this this equipment and especially

0:26:33.840 --> 0:26:38.360
<v Speaker 1>the uh well, a lot of the manufacturing robots um,

0:26:38.359 --> 0:26:40.760
<v Speaker 1>which is a little different from these logistics machines, but

0:26:41.720 --> 0:26:44.480
<v Speaker 1>the ones that used the suction cups and they'll pick

0:26:44.560 --> 0:26:48.359
<v Speaker 1>up say a very heavy car part or a piece

0:26:48.359 --> 0:26:51.000
<v Speaker 1>of a prefab house or something like that. They'll just

0:26:51.080 --> 0:26:54.440
<v Speaker 1>lift it and move it around like it's nothing. Um,

0:26:54.480 --> 0:26:56.399
<v Speaker 1>which is why when they turn on us, we have

0:26:56.560 --> 0:27:00.480
<v Speaker 1>no hope. So on that done, on that time, out

0:27:00.480 --> 0:27:02.880
<v Speaker 1>of here. Not a happy note, Yeah, I'm not happy. Note.

0:27:02.920 --> 0:27:06.280
<v Speaker 1>We're going to uhas, Chris, We're gonna wrap this up.

0:27:06.359 --> 0:27:10.000
<v Speaker 1>So guys, if you have any discussions, you'd have something

0:27:10.000 --> 0:27:13.000
<v Speaker 1>that you think we should cover, let us know. Let's

0:27:13.000 --> 0:27:15.480
<v Speaker 1>know on Facebook or Twitter handle there is Tech Stuff

0:27:15.640 --> 0:27:18.600
<v Speaker 1>h s W or you can always send us an email.

0:27:19.040 --> 0:27:23.040
<v Speaker 1>Our email addresses tech Stuff at Discovery dot com and

0:27:23.119 --> 0:27:25.680
<v Speaker 1>Chris and I will talk to you again really soon.

0:27:27.920 --> 0:27:30.480
<v Speaker 1>Be sure to check out our new video podcast, Stuff

0:27:30.520 --> 0:27:33.159
<v Speaker 1>from the Future. Join how Stuff Work staff as we

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