Latest / Automated with Brian Heater / Building Robots That Work for People: Amazon’s Playbook for Scaled Automation

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Building Robots That Work for People: Amazon’s Playbook for Scaled Automation · Automated with Brian Heater

0:01
SPEAKER_00: You put people at the center of the robotics universe.
0:03
SPEAKER_00: Always.
0:05
SPEAKER_00: Right?
0:05
SPEAKER_00: Always you put people at the center.
0:07
SPEAKER_00: Like your employees, your frontline employees, the women and men who design these systems.
0:12
SPEAKER_00: You make it for people.
0:14
SPEAKER_00: It's not people against machines, it's people and machines working together.
0:19
SPEAKER_00: And the onus is on us in order to make it responsible, accountable, and ethical for human consumption.
0:33
SPEAKER_01: Hey everyone, welcome to yet another episode of Automated.
0:36
SPEAKER_01: My name is Brian Heater.
0:37
SPEAKER_01: I am the managing editor at A3.
0:40
SPEAKER_01: Uh this week we have a great conversation with Amazon's chief technologist and generally affable gentleman, Ty Brady.
0:48
SPEAKER_01: We basically go down Ty's resume and discuss how he helped Amazon amass a 1 million robot army.
0:55
SPEAKER_01: We talk jobs, humanoids, AGI, moonshots, spaceships, numbers, and all of that fun stuff.
1:03
SPEAKER_01: If you're enjoying the show, please like, subscribe, maybe tell a few friends.
1:07
SPEAKER_01: Now sit back, relax, and watch me and type ready talk for about 45 minutes or so.
1:14
SPEAKER_01: So I have to say Chief Technologist is a pretty good title, but for my money, it's tough to beat principal spacecraft engineer.
1:28
SPEAKER_00: How about just Geeks Anonymous?
1:31
SPEAKER_00: No, I don't I'm not sure about that.
1:33
SPEAKER_00: I'll tell you, uh I I uh I love roboticists.
1:37
SPEAKER_00: I do love roboticists, I like uh technologists.
1:40
SPEAKER_00: Uh I don't know, I like all things nerdy.
1:43
SPEAKER_00: So whatever title it is, as long as I'm building something, I'm I feel like I'm pretty good.
1:46
SPEAKER_01: Aaron Powell You obviously, you know, undergrad, you studied aerospace.
1:50
SPEAKER_01: Um you you you entered that world, you stayed in that world for a really long time.
1:55
SPEAKER_01: You you saw yourself really getting into and staying in aerospace and space exploration?
2:01
SPEAKER_00: Aaron Ross Powell Well, I'll tell you how it all started.
2:03
SPEAKER_00: Here we go, Brian.
2:04
SPEAKER_00: Here's how it all started.
2:05
SPEAKER_00: Okay.
2:05
SPEAKER_00: All right, let's go.
2:06
SPEAKER_00: Uh it's in the 70s, late 70s.
2:08
SPEAKER_00: I loved Star Wars as a kid.
2:10
SPEAKER_00: Like space and robots is was my damn.
2:13
SPEAKER_01: Very familiar story to stand like.
2:15
SPEAKER_01: Literally everybody in this industry has that.
2:18
SPEAKER_00: Isn't that amazing?
2:19
SPEAKER_00: Just the power of uh a storytelling.
2:21
SPEAKER_00: I'll I'll share another story.
2:22
SPEAKER_00: So uh I I loved R2D2.
2:24
SPEAKER_00: Like R2D2 is definitely my bot.
2:27
SPEAKER_00: Uh but I'm gonna uh share another very uh personal story is that when just at that moment in 1977, and that moment when Star Wars came out, I'm like, oh, that's really cool.
2:36
SPEAKER_00: Uh my family's not really the tech family at all.
2:41
SPEAKER_00: Is that I had one teacher, one single teacher who who said to our class, our fifth grade class, is anyone interested in computers?
2:51
SPEAKER_00: I just saw Star Wars and I'm like, hey, that seems pretty cool.
2:54
SPEAKER_00: Uh I'm interested.
2:55
SPEAKER_00: So I raised my hand, and another kid raised his hand.
2:57
SPEAKER_00: And it turns out this teacher was on the uh the board for a technical high school in the county.
3:03
SPEAKER_00: I grew up in a kind of a one-stop light town.
3:06
SPEAKER_00: And uh this technical high school, they had a DEC PDP eight.
3:11
SPEAKER_00: And I didn't know anything about computers, and I thought he surely knew about computers because he's asking about it, and we show up there because it's like the 70s.
3:18
SPEAKER_00: Uh we show up there in his car, uh, and there's a computer boxed that hasn't been used in six months.
3:28
SPEAKER_00: And uh so we looked to our teacher and like, hey, what's going on?
3:32
SPEAKER_00: Uh he was like, I don't know, let's bust out the manual and start to figure this stuff out.
3:36
SPEAKER_00: So uh over the next three months, I kind of figured out how to do a little bit of programming, how to write my name, uh, and I was hooked.
3:45
SPEAKER_00: I love computers.
3:46
SPEAKER_00: And then the 80s comes around, and we have the personal computer revolution.
3:49
SPEAKER_00: I'm like, oh my gosh, I can actually I had a TI994A, shout out to all my homies out there that know that that's the first 16-bit computer that was going on.
3:57
SPEAKER_00: I really learned to program and I fell in love with computing, uh, all things uh software.
4:03
SPEAKER_00: Uh I could go to any local arcade and kind of rip off uh that game maniacally and program at my house.
4:10
SPEAKER_00: I love that.
4:11
SPEAKER_00: Then I started doing uh radio control uh airplanes as well in the early 80s.
4:17
SPEAKER_00: Uh and I said, wouldn't it be an amazing, awesome world if I can combine my love for radio control and computers all into a one thing?
4:26
SPEAKER_00: And lo and behold, that's the field of robotics.
4:29
SPEAKER_00: So I just what's one person, it's just how one person can make a huge difference in someone's life.
4:34
SPEAKER_01: It's wild, you know, especially now looking at how competitive things are.
4:38
SPEAKER_01: Like sometimes it's just about being the right place at the right time and literally being the one of two people raising your hand.
4:46
SPEAKER_01: And that's all it takes.
4:47
SPEAKER_00: Yeah, that's all it takes.
4:48
SPEAKER_00: And there's definitely just some some luck involved.
4:50
SPEAKER_00: There's a a passion and a drive for sure.
4:54
SPEAKER_00: I came to uh Boston, uh, sight unseen.
4:57
SPEAKER_00: This was the hub of the computer universe.
5:00
SPEAKER_00: Like digital was here, Apollo was here, Wang was here, Mercury Computer was here.
5:04
SPEAKER_00: It was all in Boston, and I wanted to be a part of that.
5:07
SPEAKER_00: I just wanted to be a part of that.
5:09
SPEAKER_00: Now comes miracle number two is that I couldn't afford college.
5:13
SPEAKER_00: And uh for the goodness of some anonymous donors, folks that were given back to Boston University, has allowed me to go to school on a scholarship.
5:21
SPEAKER_00: And I came to Boston uh knowing how to program with in and I loved aerospace.
5:25
SPEAKER_00: Like I, you know, wanted to put robots in space.
5:28
SPEAKER_00: That's that was just kind of my dream.
5:30
SPEAKER_00: Uh, and I got into aerospace, and it turns out that the combining uh my skills in software and my love of computers with more of a mechanical degree actually was really helpful in the in the realm of robotics.
5:45
SPEAKER_00: So I got involved uh actually with a lab at BU because one of the professors said, Hey, you're pretty good at programming.
5:51
SPEAKER_00: Jeez, uh, did you really do this yourself?
5:54
SPEAKER_00: I'm like, Yeah, I love this.
5:55
SPEAKER_00: And so he invited me part of uh the lab that he was running.
5:59
SPEAKER_00: It was a graduate student lab, I was the only under undergraduate uh in it.
6:02
SPEAKER_00: And in that lab, uh they were these these are some legends, they were working on Voyager, like Vija, you know, the Voyager.
6:09
SPEAKER_00: They did a Faraday Cup for Voyager, and it was incredible just to be around these luminaries, these icons of of space travel.
6:17
SPEAKER_00: Like it was just, you know, your heart actually beats a little bit faster.
6:21
SPEAKER_00: And uh there were two professors at MIT, and uh they kind of they knew how much I loved to build and how much with the passion I had for robotics and and for space.
6:30
SPEAKER_00: And so they invited me when I graduated to be a full-time employee at MIT.
6:35
SPEAKER_00: And that was a dream come true.
6:38
SPEAKER_01: There is this special kind of I think fearlessness that you have when you're younger and when you you don't know how much you don't know when you're an undergrad and you feel like sure, like of course I'm going, I'll join these like graduate students and these legends.
6:53
SPEAKER_01: And yeah, no problem.
6:55
SPEAKER_01: I can absolutely compete with these folks.
6:58
SPEAKER_00: Yeah, it's it's funny.
6:59
SPEAKER_00: Compete's actually not the word.
7:01
SPEAKER_00: It's just like, could I could I help build?
7:04
SPEAKER_00: Could I be a part of of something uh uh amazing?
7:08
SPEAKER_00: And you know, my time at MIT, and I by the way, I I applied to MIT when I was an undergrad, you know, going to look for schools and summarily you know rejected.
7:19
SPEAKER_00: Like, oh my gosh, I know computers so well and rejected.
7:23
SPEAKER_00: So then when I went to MIT as a staff research engineer there, with that awesome title that I grew into, um, I learned to be a builder.
7:33
SPEAKER_00: And I had some incredible mentors around me, like people that really cared, people that would give me, give time to me and share their craft and share, you know, actually what's how to build things from the ground up, how to work with a team, how to do some really cutting-edge uh technologies.
7:52
SPEAKER_00: And uh that was transformational in my life.
7:55
SPEAKER_00: It really gave me the the confidence that what I was doing could actually make a giant difference.
8:00
SPEAKER_00: We built spacecraft.
8:01
SPEAKER_00: We built a spacecraft in the mid-90s called Hetty.
8:04
SPEAKER_00: Um we did, you know, talk about one hat or two hats.
8:07
SPEAKER_00: I probably wore 10 different hats, whether it's hardware, software, thermal, dynamic systems, astrophysics, like you name it.
8:13
SPEAKER_00: We were we were all kind of in on it uh to build this spacecraft.
8:17
SPEAKER_00: And what it really gave me is it just gave me confidence and and and it sat it's it's still with me.
8:24
SPEAKER_00: I will tell you, it's still with me, this the generosity of people and and the kindness that uh one can offer, particularly around education, of what an impact that can be for any young girl, young boy uh out there with their own aspirations.
8:38
SPEAKER_00: You know, I mean Star Wars is 1977 and New Hope, how appropriately named, a New Hope.
8:44
SPEAKER_01: So you really got a crash course.
8:46
SPEAKER_01: I mean, you know, not only were you there and not only were you getting your masters, but you were also uh an employee at the time.
8:51
SPEAKER_01: So you were working with the people who are really doing the work.
8:56
SPEAKER_00: Yeah, not only that, like I've seen some really incredible things in in my career.
9:01
SPEAKER_00: Uh the birth of the per personal computer, like I said, that was really that was a really big deal.
9:07
SPEAKER_00: But when I came uh in 1990 to MIT, the internet literally just started.
9:12
SPEAKER_00: I I know it's weird and hard to think about, but the internet just began.
9:17
unknown: Right.
9:18
SPEAKER_00: So now we can really share our learnings and our love of computing and building things and building these robotic systems with each other.
9:26
SPEAKER_00: We can share software, we can share techniques, and it was a lot easier than you know, just one-on-one type of uh interactions.
9:32
SPEAKER_00: It was a many-to-one and a one-to-many type of interaction.
9:36
SPEAKER_00: And to be at a place like MIT at the birth of the internet was really, really incredible.
9:40
SPEAKER_00: Uh, so that had a profound uh impact as far as my learning uh would go.
9:45
SPEAKER_00: And it's by the way, you're at MIT, right?
9:48
SPEAKER_00: So a lot of folks would you you'd meet different universities and folks, industry, folks from the outside.
9:53
SPEAKER_00: And uh it was really an incredible time.
9:55
SPEAKER_00: But uh what I learned most and probably the deepest thing that I learned is just to be good to yourself and have confidence.
10:04
SPEAKER_00: I took a class every semester.
10:05
SPEAKER_00: I was there, you can take classes for free.
10:07
SPEAKER_00: And finally, uh a professor said, Didn't I see you a couple years ago?
10:10
SPEAKER_00: I'm like, Yeah, he goes, haven't you graduated yet?
10:12
SPEAKER_00: I'm like, No, I'm just taking classes because I love it.
10:14
SPEAKER_00: He goes, Listen, how many classes have you taken?
10:17
SPEAKER_00: I think I was at 10.
10:19
SPEAKER_00: He goes, uh, why don't we just get you a degree?
10:22
SPEAKER_00: So I matriculated in 99 and got my uh got my master's in uh uh yeah, it was it was kind of funny.
10:32
SPEAKER_01: Yeah, it it it's really interesting hearing you talk about that process because looking at it from the outside, you know, taking a kind of um bird's eye view of your your CV.
10:43
SPEAKER_01: Um I was going to ask you whether the plan was to kind of stick around academics, but now it seems pretty clear to me that that that wasn't necessarily that you just wanted to be in and around rockets in and around airspace.
10:55
SPEAKER_01: You weren't you weren't trying to become like a tenured professor or anything.
10:59
SPEAKER_00: No, I really would and I still it's I still have this desire and love.
11:03
SPEAKER_00: I still just want to build things, uh uh kind of a startup mentality, even an insurgent mindset at times of you know, how can we really use technology for the benefit of people?
11:13
SPEAKER_00: Uh how can we build things that uh help people do their jobs better?
11:17
SPEAKER_00: How can we build things to make their work uh place safer?
11:21
SPEAKER_00: That's uh that's been with me.
11:23
SPEAKER_00: Uh it's still with me.
11:25
SPEAKER_00: Uh it's it is funny.
11:26
SPEAKER_00: Like I we build machines and and I really index and I have, I'm super proud of the technologies, like it's some a lot of some worlds first, actually.
11:34
SPEAKER_00: I'm really proud of that.
11:35
SPEAKER_00: But it's you know, when I reflect back, it's it's always about the people.
11:38
SPEAKER_00: I can I can share with you the heartbreaks and I can share with you the the accomplishments and uh you know how we uh picked each other up when we needed it.
11:47
SPEAKER_00: Like I like to say that kindness is a parachute for failure.
11:52
SPEAKER_00: But it's a force multiplier for success.
11:55
SPEAKER_00: And when people are kind to each other, especially in times of failure, you can you can fall back on each other and it it it softens that blow.
12:03
SPEAKER_00: And we all have failures.
12:04
SPEAKER_00: I would when we we all should learn from our failures, but that doesn't mean it doesn't hurt.
12:08
SPEAKER_00: It hurts.
12:09
SPEAKER_00: But when you you surround yourself with kind people and you you actively make kindness a an action word, um, it makes a huge difference, right?
12:18
SPEAKER_00: The successes are even higher and the lows are are a lot softer.
12:23
SPEAKER_01: Yeah, and and the lesson that I learned early on in covering robotics, and this was actually, I think, around the first tech crunch robotics event at MIT that you were at.
12:34
SPEAKER_01: Uh I learned how at that time, and even, you know, so obviously to a slightly lesser extent, but even now, how small the industry is, how in some ways kind of insular it is in that you really are working with the same people over and over again, and that you really do like end up connecting with the those people that you went to school with or that that taught you at MIT, you know, 20, 30, 40 years ago.
12:58
SPEAKER_01: So just yet another reason to be kind to people.
13:02
SPEAKER_00: Yeah.
13:02
SPEAKER_00: I mean, how amazing is that though?
13:04
SPEAKER_00: Like I know that you had Mark Rayburn on and I knew Mark back in the 90s, and he's an amazing person.
13:09
SPEAKER_00: And you know, we have Colin Angle's part of the community as well, and Cynthia Brazil and Russ T.
13:15
SPEAKER_00: Drake, and like these are all they're friends.
13:18
SPEAKER_00: These are friends.
13:18
SPEAKER_00: We're really close to that community.
13:20
SPEAKER_00: And I think that we see this incredible technology in physical AI that that that we're developing, and that that there's so much growth that can happen in that.
13:31
SPEAKER_00: That we don't compete.
13:32
SPEAKER_00: Like I that's where I got a little allergic to that word.
13:34
SPEAKER_00: We don't really compete uh with each other.
13:36
SPEAKER_00: What we do is we try to lift each other up uh because there's it's it can have such a profound impact on people's lives in making uh the workplace better, and making the home better, and making and allowing us to actually, I mean, if you want to get super meta, I I I'm in this game because it allows us to be more human, allows us to connect with each other even more closely, right?
13:57
SPEAKER_00: Our technology uh allows that.
13:59
SPEAKER_00: Of course, you have to be mindful of how you build that technology so that people use it in the right ways and with the right protection and responsible and accountable, uh, for sure.
14:08
SPEAKER_00: But the goal, I think the goal that we all have is for allow us to be more intelligent, more capable, more human, more connected to one another.
14:17
SPEAKER_01: There's competing, and and competing isn't necessarily like always a bad word, right?
14:21
SPEAKER_01: I mean, there is healthy competition, but the but the nature of that competition, and and we're kind of getting to this a bit of a transition period for you as as we're again going down your CV, um, the nature of competition does tend set tend to start to change a little bit as you move into the commercial space.
14:41
SPEAKER_00: It does.
14:41
SPEAKER_00: I mean, I I was a competitive cyclist for almost 20 years, and it's it is funny that, you know, I mean, I definitely know what competition can do.
14:49
SPEAKER_00: And I think that there's even something when you compete against somebody that you both have shared kind of the trials and tribulations.
14:58
SPEAKER_00: You both have gone through that pain.
14:59
SPEAKER_00: And and I think that there's mutual r respect there.
15:02
SPEAKER_01: Uh when you shared a very unique experience that the only the two or very few of you have experienced.
15:09
SPEAKER_01: Yeah, yeah.
15:09
SPEAKER_00: I think that's that's absolutely right.
15:10
SPEAKER_00: And and especially when you compete with the team, like your teammates are are part of your your journey.
15:17
SPEAKER_00: Uh, like I have uh from my my cycling team back in the 90s and uh the early 2000s, uh we're still lifelong friends.
15:25
SPEAKER_00: Like my kids hang out with their kids, and you know it, I mean, there's a real bond uh there.
15:30
SPEAKER_00: So and I think that bond, to bring it back to robotics, is there in the the robotics community.
15:34
SPEAKER_00: I mean, we we know each other for sure.
15:37
SPEAKER_00: I mean, we couldn't believe when when Amazon actually bought Kiva Systems in 2012.
15:42
SPEAKER_00: It was not that long ago.
15:44
SPEAKER_00: But in 2012,$785 million.
15:46
SPEAKER_00: I can tell you every single roboticist has said, oh my gosh, oh my goodness, are you kidding me?
15:51
SPEAKER_00: A robotics company actually sold for something with the units of millions, right?
15:55
SPEAKER_00: I mean, it was kind of unheard of.
15:57
SPEAKER_00: But boy, Amazon knew what they were doing.
16:00
SPEAKER_00: Jeff knew what he was doing there because it was really not the robotics, it was the idea of a goods-to-person fulfillment uh system that he saw.
16:08
SPEAKER_00: And from that investment, you know, here we are with Amazon Robotics, the world's largest manufacturer of industrial mobile robots with more than a million robots out there that we've manufactured in in Massachusetts.
16:19
SPEAKER_01: I'm really trying to wrap my brain around the nature of how time works, like in and around the robotics field, because yeah, 2012, especially in relation to that story, does feel like an incredibly long amount of time ago.
16:34
SPEAKER_00: That's right.
16:35
SPEAKER_00: I joined in 2015.
16:36
SPEAKER_00: So I actually just uh had my 10-year anniversary inside of uh Amazon.
16:39
SPEAKER_00: And it's been a it's an incredible journey from just a couple of buildings where our systems were operating at, to now we have more than 300 robotics-enabled facilities.
16:49
SPEAKER_00: We are in not only world-class leaders in mobility, uh, but also in manipulation and in storage and sortation uh and perception as well.
16:57
SPEAKER_00: I'm really proud of the work that the many, many women and men that have done uh truly are pioneers uh doing their technology development through through project context.
17:07
SPEAKER_00: And our context is very straightforward.
17:09
SPEAKER_00: Like we deliver goods, we want to have the world's largest selection of goods at a low cost, deliver right through the door.
17:14
SPEAKER_00: And that context, that framing allows us what's to accelerate technology development in just the most basic of ways.
17:22
SPEAKER_01: Prior to Amazon, you spent a number of years at Draper Laboratory.
17:27
SPEAKER_01: And it strikes me that in a sense, and I don't know if this is deliberate, probably not, but that really was kind of a a bit of a transitional space between pure research and really starting to kind of commercialize or at least you know really productize uh technology.
17:46
SPEAKER_00: Indeed, Brian, and I love that you've done your your homework there.
17:49
SPEAKER_00: There was a little time in between that's kind of uh actually funny.
17:52
SPEAKER_00: I did graduate uh from MIT and it happened to be dot com.
17:56
SPEAKER_00: It was uh 1999 and 2000.
17:58
SPEAKER_00: And uh if you wanted to do okay and if you wanted, you know, maybe make a little bit of scratch in dot com, uh, you really need to have two attributes.
18:08
SPEAKER_00: Uh the first was, uh, did you have a degree from MIT?
18:11
SPEAKER_00: And I did.
18:12
SPEAKER_00: I'm like, okay, I'm gonna I have a child on the way, I'm gonna need a house.
18:14
SPEAKER_00: So I got one of those.
18:16
SPEAKER_00: And the second attribute was were you were you breathing?
18:18
SPEAKER_00: And I was breathing.
18:20
SPEAKER_00: So I did uh have a little bit of uh consulting time in between.
18:24
unknown: Yeah.
18:26
SPEAKER_01: Uh Spacecast Solutions, Inc., yeah.
18:29
SPEAKER_00: That's right.
18:30
SPEAKER_00: That's right.
18:30
SPEAKER_00: Very good.
18:31
SPEAKER_00: Uh then um dot com starts to wane, uh, let's say.
18:35
SPEAKER_00: Uh, and uh I joined Draper Laboratory, and it was a great experience for me.
18:39
SPEAKER_00: What there was uh if the prior decade was about building, uh this was about leadership.
18:45
SPEAKER_00: Uh I led teams uh to do some really cutting-edge novel work.
18:49
SPEAKER_00: We flew the first MEMS gyro uh integrated into a star camera, the first CMOS uh star camera where we uh put those uh together, uh got the patent for that, flew in space, it was a tremendous success, first time the world's ever seen that.
19:02
SPEAKER_00: Uh and then we uh had a team really focus on lunar landing, uh precision lunar landing, the the ability to land anywhere on the moon, too, whether inside of 100 meters under any lighting condition.
19:13
SPEAKER_00: And we did a lot of fun stuff, inclusive of uh doing the really one of the first vertical takeoff, vertical landing rockets, way before you know uh what you see out there today.
19:23
SPEAKER_00: This is in 2010, 2011, where we'd have a rocket kind of take off and land, uh mimicking how it would land on the moon.
19:31
SPEAKER_00: Some really great stuff uh that we did using train relative navigation and and actually using the same software that you would actually use on the moon.
19:40
SPEAKER_00: I led a team uh uh uh to do the autonomy guidance, navigation, and control uh on that system, working really closely uh with NASA.
19:50
SPEAKER_00: And uh while we never got to the moon while I was at uh Draper, um uh a friend of mine, a co-worker inside of NASA, uh Tim Crane, uh, or Dr.
20:00
SPEAKER_00: Tim Crane, I should say, uh, he started Intuitive Machines and was the first commercial company to actually land on the moon using a lot of the techniques and the technologies that we discovered the decade prior.
20:12
SPEAKER_00: So I'm really proud of that uh that as well.
20:14
SPEAKER_00: But it's really a time of leadership and you know how to lead teams and how to uh lead technology in a way that uh the world hasn't seen.
20:22
SPEAKER_00: And I really did enjoy my time there.
20:24
SPEAKER_00: In 2015, I was approached by Amazon saying, we really want to expand our portfolio.
20:29
SPEAKER_00: We want to just be more than just uh Kiva.
20:32
SPEAKER_00: Uh we want to get into manipulation, we want to get into uh different sorts of uh uh systems that can store goods and sort goods.
20:40
SPEAKER_00: Uh and I love that.
20:42
SPEAKER_00: I love uh kind of that mindset of uh invent and simplify and think big and learn and be curious.
20:49
SPEAKER_00: Uh that's my mindset, and uh those are also leadership principles inside of uh Amazon.
20:53
SPEAKER_00: So I knew it was a fit and uh joined Amazon and uh you know here we go.
20:58
SPEAKER_00: So quite a quite a wet resume of uh robots.
21:02
SPEAKER_00: Oh, I also uh co-founded Master Robotics in between.
21:04
SPEAKER_00: I forgot to tell you that.
21:07
SPEAKER_01: Right before I joined as an aside, I I I had I have to ask, you know, uh like what what that conversation was like that got you to leave, you know, not not drapered necessarily, but this this very specific career path, this this trajectory, this um, you know, this idea that you had had in your head since you were a kid and saw Star Wars and wanted to build rockets to uh, you know, again, primarily focusing on robots for warehouse and logistics and fulfillment centers.
21:42
SPEAKER_01: That's quite a shift.
21:45
SPEAKER_00: It does seem that way.
21:46
SPEAKER_00: And I will tell you that you know, in my career, I've been I've been very blessed, like I said, with great teammates and a great support system.
21:54
SPEAKER_00: Uh and I was, of course, approached by some of the big tech companies.
22:00
SPEAKER_00: Companies uh during that time.
22:01
SPEAKER_00: And I'm like, hey, I'm happy what I'm doing.
22:03
SPEAKER_00: I'm I'm good.
22:04
SPEAKER_00: I I like what we're doing.
22:05
SPEAKER_00: But when Amazon came, it was a little bit different, and I'll tell you why.
22:10
SPEAKER_00: My journey is kind of from rockets to robots uh for sure.
22:14
SPEAKER_00: But why when Amazon came to town and we had the initial conversation, it was about application, right?
22:21
SPEAKER_00: It wasn't just in the digital world, it was about true application.
22:26
SPEAKER_00: And if it's something that I learned at MIT was is that that that forcing function of constraints and making something work in the real world.
22:33
SPEAKER_00: And also I had a giant advantage of now this actually ties e-commerce and aerospace together, is that when you're at the scale of Amazon and you ship literally billions and billions of packages, like literally, then precision matters.
22:50
SPEAKER_00: Like you can't be, you know, nine out of ten good.
22:53
SPEAKER_00: You have to be 99.99.
22:54
SPEAKER_00: And that's like what we think in aerospace terms, high reliability, high quality.
23:00
SPEAKER_00: So I knew I had an advantage there, but I was really impressed with uh the fact that uh they they have purpose.
23:10
SPEAKER_00: They have purpose, right?
23:12
SPEAKER_00: And if you're if you're listening, if you're listening to this podcast, no matter what field that you're in, you need three things.
23:20
SPEAKER_00: And I credit Pam Reeves for for really sharing this with me.
23:23
SPEAKER_00: You need purpose, you need strategy, and you need operations.
23:27
SPEAKER_00: Purpose, strategy, and operations, right?
23:29
SPEAKER_00: The purpose for Amazon is really straightforward.
23:31
SPEAKER_00: Have the world's largest selection of goods at a low cost, delivered right to the customer's door.
23:37
SPEAKER_00: That's our purpose.
23:38
SPEAKER_00: And that has shown that that that works.
23:40
SPEAKER_00: And when you do it well, you spin the flywheel as Jeff calls it, and it continues to grow jobs and grow opportunity.
23:47
SPEAKER_00: Our strategy is actually really straightforward.
23:51
SPEAKER_00: Our strategy, of course, is in our leadership principles that Amazon has, but you can even hear Andy talk about it.
23:57
SPEAKER_00: Like we we we tend to operate like the world's largest startup.
24:00
SPEAKER_00: And I like that.
24:01
SPEAKER_00: I like that scrappy mentality.
24:02
SPEAKER_00: I like the experimentalist mentality, I like the let's go build uh type of thing, uh build things mentality.
24:08
SPEAKER_00: And I I in robotics, uh, one of the things that I'm that uh is very obvious, I I think is obvious, is that we're what we're trying to do is have a world-class capability in the basics of robotics.
24:23
SPEAKER_00: Not the hype of robotics, but the basics of robotics.
24:25
SPEAKER_00: Can we move things?
24:26
SPEAKER_00: Can we manipulate things?
24:27
SPEAKER_00: Can we store things?
24:29
SPEAKER_00: Can we sort things?
24:30
SPEAKER_00: Can we perceive the world around us and can we path things?
24:33
SPEAKER_00: Just the basics.
24:34
SPEAKER_00: Some you might call them primitives.
24:37
SPEAKER_00: And in order to really achieve a world-class capability in this, you need that project context, the purpose that we have, right?
24:45
SPEAKER_00: So that's our strategy.
24:46
SPEAKER_00: We want to have a world-class uh capability and just the the basics.
24:50
SPEAKER_00: Um and if we can eliminate the menial, the mundane, and the repetitive with the basics, that's gonna be better for our employees.
24:57
SPEAKER_00: That's gonna be better for people.
24:58
SPEAKER_00: All right.
24:59
SPEAKER_00: So now our operations turn into how can we enable people with the best tool set possible out there?
25:06
SPEAKER_00: How can we create a safer environment for our folks with robotics?
25:10
SPEAKER_00: And how can we have our folks be more productive using that tool set?
25:14
SPEAKER_00: That is a really hard problem.
25:16
SPEAKER_00: The onus isn't on the operator, the onus is on us, the roboticists, in order to make our tools simple, uh, not complex, or in order to make our tools actually have utility and to have the high reliability in the real world.
25:29
SPEAKER_00: That gains us a tremendous advantage.
25:31
SPEAKER_00: Because when we do that, that that spins that flywheel back to we're getting better at the basics.
25:36
SPEAKER_00: Now, if you want the the that was a long way to get to this where why I get really excited and why I even took this job, you have to be able to think all the way through that that life cycle.
25:46
SPEAKER_00: And I do believe that what Amazon is doing in robotics is truly pioneering work.
25:52
SPEAKER_00: And I do believe that by mastering the fundamentals of robotics through application will allow us not only to transform e-commerce is what we have seen.
26:01
SPEAKER_00: We've created hundreds of thousands of jobs, we've created a safer environment for our employees.
26:06
SPEAKER_00: We have 1.5 million plus employees out there that we use our robotics uh for.
26:12
SPEAKER_00: But I believe that the fundamentals of robotics will actually start to transcend different sectors, whether it's in agriculture, or it's in fishing, or it's in automotive, or it's in healthcare, that the work that we're doing, this collaborative robotics philosophy that we have, will actually start to impact these other areas.
26:29
SPEAKER_00: And when we do that, that's actually creating a very positive change for the world.
26:37
SPEAKER_00: It's allowing us to be more intelligent, more capable, and more human to each other, and still with the greatest value of human-to-human connection, with the greatest value of a person having a great job in a safe environment and allowing them uh to do productive things, right?
26:53
SPEAKER_00: That excites me.
26:54
SPEAKER_00: And there's no other company in the world that can do that.
26:57
SPEAKER_01: But you do understand why you know people are always questioned whether these these whether technology can and will make job, human jobs less human and whether they they will displace jobs.
27:10
SPEAKER_01: I mean, these are very real, real concerns.
27:12
SPEAKER_01: And and you know, and and how how how do you have those conversations with people and how has that conversation evolved over time?
27:24
SPEAKER_00: You have to put your you have to put your money where your mouth is, first of all.
27:27
SPEAKER_00: Like I'm really proud that Amazon has committed more than$1.2 billion in upskilling more than 700,000 employees.
27:34
SPEAKER_00: Right?
27:34
SPEAKER_00: You you have to any a responsible company will put money into upskilling because the workforce will change.
27:41
SPEAKER_00: There's no doubt about that.
27:42
SPEAKER_00: Jobs will change.
27:43
SPEAKER_01: So let's let's break that down real quick.
27:45
SPEAKER_01: So upskilling, obviously, you know, it it varies from person to person, from place to place, from job to job.
27:52
SPEAKER_01: But like what's what's a concrete example of upskilling in the real world?
27:57
SPEAKER_00: Okay.
27:57
SPEAKER_00: So uh first of all, I'll just say that no no other company in the history of the United States for sure has created more jobs than Amazon.
28:05
SPEAKER_00: Like just created jobs through their productivity gains uh and and by uh treating our employees with the respect that they deserve and giving them the tool sets through robotics uh that the world has never seen.
28:17
SPEAKER_00: So let me give you a concrete example.
28:18
SPEAKER_00: So one is that we have our career choice uh program where any of our employees from day one when they they start, that we will bring the classroom actually right to a fulfillment center.
28:28
SPEAKER_00: And if they're interested in science and tech or actually just about any field, we'll pay for that schooling.
28:33
SPEAKER_00: It's very near and dear to my heart.
28:35
SPEAKER_00: If the employee uh wants to pursue it, we'll we'll do that for them.
28:39
SPEAKER_00: I like that.
28:40
SPEAKER_00: Another one that actually is uh very close to us is our robotic apprenticeship program, where if somebody is working in the on the front lines and they uh say, hey, that's a really cool Proteus robot that we have over there.
28:52
SPEAKER_00: I love what you're doing with Hercules or that sparrow.
28:55
SPEAKER_00: It's amazing.
28:56
SPEAKER_00: Uh, we will teach folks actually how to be, if they're interested in being an apprentice, we will give them an apprenticeship program.
29:02
SPEAKER_00: And they go through the apprenticeship program, they'll get about 40% more pay.
29:05
SPEAKER_00: And they're doing something that they love.
29:07
SPEAKER_00: So we're seeing a real big uptick in that.
29:09
SPEAKER_00: Like these are concrete real-world examples, what employers can do in order to help.
29:15
SPEAKER_00: Uh that's that's with our with our employees.
29:18
SPEAKER_00: We also have to have a mindset towards our future generation, right?
29:21
SPEAKER_00: So, our Amazon future engineers, we've we put uh millions of 50 million plus into uh scholarships for high school kids to go to college.
29:29
SPEAKER_00: I love that.
29:30
SPEAKER_00: That's very relatable uh to me.
29:32
SPEAKER_00: We're a sponsor of Mass Robotics.
29:33
SPEAKER_00: I know that would be a giant shocker, uh, but I'm really proud of that, right?
29:37
SPEAKER_00: Because it's the world's largest uh nonprofit uh uh for incubation of uh robotic startups in the world.
29:45
SPEAKER_00: Like that's really, really incredible.
29:47
SPEAKER_01: You mentioned um being the world's largest startup, and and and it strikes me that you know there's there's a few ways in which that's kind of manifesting itself.
29:56
SPEAKER_01: Um obviously there's a lot of the sort of the day one research that's happening, um, the stuff that's happening behind the scenes.
30:03
SPEAKER_01: There's the you know, industrial innovation fund, which is actually like funding a lot of startups.
30:08
SPEAKER_01: Um, and then something that's uh that really just sort of uh came to light recently that I I think is probably close to maybe some of the work at Draper and close to maybe closer to what TRI is doing, maybe close to what Mark is doing over at RAI is um the work at Amazon Frontier AI and Robotics, Amazon Far, which like that's a direct product of your hiring Peter Abel and the rest of the Bravarian team.
30:38
SPEAKER_00: Yeah, yeah.
30:38
SPEAKER_00: Yeah, it's a super some, I don't know if you've seen it's a really, really exciting early stage uh research that that we're doing uh over there.
30:46
SPEAKER_00: I think it's uh like you know, while we are applied, absolutely.
30:50
SPEAKER_00: We are all about application, but it's also I think a good thing to think about moonshots and like what what is the art of possible?
30:57
SPEAKER_00: Look, we are experimentalists at heart.
30:59
SPEAKER_00: I have my own lab and we do really cool things to see what is possible, what's cutting edge, what's hype, what's not hype.
31:06
SPEAKER_00: Uh it's it's kind of the fun part of robotics, uh, for sure.
31:10
SPEAKER_00: We're learning.
31:11
SPEAKER_00: We're we're totally learning.
31:12
SPEAKER_00: Uh, and we want to build a proof of concept.
31:14
SPEAKER_00: And the whole point is can we ultimately assist our people on the front line?
31:20
SPEAKER_00: Where it's going, I couldn't tell you.
31:22
SPEAKER_00: It's too early stage, right?
31:25
SPEAKER_00: But uh it's definitely uh, I'd say really exciting.
31:29
SPEAKER_01: So, so you know, you you you know, you know, we have to get to this at some point in the scale of what's hype and what isn't hype, where where does bipedal humanoid robots fall?
31:44
SPEAKER_00: So I'd there's let me start with a quote first.
31:47
SPEAKER_00: It's Roy Omar, it's one, he's a technologist from uh SRI, and he has a quote that we tend to overestimate the benefits of technology in the short run and underestimate the benefits of technology in the long run.
32:00
SPEAKER_00: And I think that there's something there.
32:02
SPEAKER_00: I really do, right?
32:03
SPEAKER_00: So, you know, are we peak hype right now?
32:06
SPEAKER_00: I'm not sure.
32:07
SPEAKER_00: We're probably I think we're definitely in the overestimation part.
32:09
SPEAKER_00: Like I can tell you it's it's really easy to make a YouTube video.
32:12
SPEAKER_00: It is.
32:13
SPEAKER_00: I can cut, I can edit, and you know, we can make something.
32:16
SPEAKER_00: Uh it's really hard to have your robots operational every day, shipping billions of packages and creating a safer environment for our employees.
32:24
SPEAKER_00: And that's what we're not that's only what we can do, that's what we are doing.
32:28
SPEAKER_00: Um, and that high reliability, real-world applications actually I what I think is driving the field.
32:35
SPEAKER_00: Don't get me wrong.
32:35
SPEAKER_00: I love uh for especially the next generation to get inspired about the potential of robotics and what robotics can do.
32:43
SPEAKER_00: I love that, uh, for sure.
32:44
SPEAKER_00: But when it comes to uh bipedal humanoids, which is what your your question, like absolutely, am I interested in the bipedal nature of mobility?
32:53
SPEAKER_00: Of course.
32:53
SPEAKER_00: Whether it has two legs or four legs or six legs or or one or is it wheeled?
32:58
SPEAKER_00: Like, we're interested in anything that moves, uh, for sure.
33:01
SPEAKER_00: Right?
33:01
SPEAKER_00: Like we want to understand what when's there a use case, what's the problem that we're trying to solve uh with robotics, and it's good to have you know different modalities in in your toolbox.
33:15
SPEAKER_00: So the bipedal part is is uh totally uh interesting.
33:20
SPEAKER_00: Um you know, I think it's just uh again, early stages.
33:25
SPEAKER_01: Yeah, yeah.
33:26
SPEAKER_01: So so if if I'm understanding, you know, it's that uh these will be useful, but right now it's it's just the very practical problem.
33:36
SPEAKER_01: And and this is speaking as somebody again who is involved in you know helping um uh scale and deploy a million robots is actually like getting these things in into making them reliable and getting them out in large numbers into the real world.
33:50
SPEAKER_00: Yeah, I think the foundation models are like really incredible.
33:52
SPEAKER_00: There's that so again, I want to I want to get specific with with my language here.
33:58
SPEAKER_00: Like there's large language models, right, that uses language.
34:01
SPEAKER_00: I I almost call it conversational AI, right?
34:04
SPEAKER_00: So it's language in, language out, uh summarize this document for me, merge these two things.
34:09
SPEAKER_00: Chat GPT.
34:10
SPEAKER_00: Yeah, you know, that's a language, like that's uh uh conversational.
34:14
SPEAKER_00: I okay.
34:15
SPEAKER_00: In robotics, there's it you're not teaching it through language.
34:18
SPEAKER_00: I mean, you can use language in order to task it, but it's really learning through prior data and prior actions in the unstructured uh world, right?
34:27
SPEAKER_00: Or even in the structured world.
34:29
SPEAKER_00: So we've built we're building up that foundation model.
34:32
SPEAKER_00: There's another uh, you know, while we're just on AI, so I actually put it in three buckets, if you're interested.
34:38
SPEAKER_00: You still don't know.
34:39
SPEAKER_00: I I love to hear about buckets.
34:41
SPEAKER_00: So the first bucket is conversational, is what I said.
34:44
SPEAKER_00: Yeah.
34:44
SPEAKER_00: The second one is actually creative AI.
34:47
SPEAKER_00: And this is AI that allows a person to be more creative with their own ideas.
34:53
SPEAKER_00: And the assistant is helping them, right?
34:56
SPEAKER_00: So uh, for example, inside of Amazon, we can ask a generative AI system to lay out a building for us.
35:04
SPEAKER_00: Given this amount of input, given this amount of output, given the economics that are around uh the the this area, what size building and how should that building be laid out?
35:12
SPEAKER_00: Sure, we can and what we'll find like uh almost exclusively is that that building can't actually be built.
35:20
SPEAKER_00: It's missing something.
35:21
SPEAKER_00: But what it'll do some physics and yeah, it's just but what it'll do is it'll inspire the actual solutions designers, the the architects are actually laying out the buildings and go, oh hey, there's a choke point over there.
35:34
SPEAKER_00: Oh, I didn't really realize why that's working so well.
35:36
SPEAKER_00: It allows a person to be more creative in their job.
35:39
SPEAKER_00: So then it's human output given AI input, right?
35:45
SPEAKER_00: I actually even have a side story.
35:47
SPEAKER_00: I'm a I'm I I I do like to paint every now and then.
35:49
SPEAKER_00: Like I'm a I'm a terrible painter, uh, but I enjoy it.
35:52
SPEAKER_00: I like to kind of find the zen.
35:55
SPEAKER_00: And uh I have a Boston Terrier, and I asked uh a generator to say, Could you generate for me a Boston Terrier in a kayak uh thinking pensively about the starry night uh with um in the style of Vincent Van Gogh.
36:14
SPEAKER_00: Right?
36:15
SPEAKER_00: And voila, out comes this prompt, and I see about five different images.
36:19
SPEAKER_00: And what it did for me is it's like I didn't really think about that pose, or I didn't think about even that it's something as crazy as what I just just told you, but it invoked a creative side of me, and I decided to take one of the prompts and uh and one of the outputs from the prompt and paint it myself, right?
36:36
SPEAKER_00: So that's my own creative.
36:38
SPEAKER_00: Okay, it can inspire you.
36:39
SPEAKER_00: The third bucket is operational, right?
36:42
SPEAKER_00: So the operational AI is when it's embedded actually into the system using generative AI in order to make the task more productive or create a safer environment.
36:51
SPEAKER_00: A great example of that is our Deep Fleet, where we have, again, 10 plus years of an algorithm in order to optimize the movement of two or three or four thousand robots at a time inside one of our facilities.
37:04
SPEAKER_00: And Deepfleet uh within a year using generative AI end-to-end allows us to do to be about 10% more efficient in the movement of those drives.
37:12
SPEAKER_00: Like real, like whoa.
37:14
SPEAKER_00: And now it's operational, right?
37:15
SPEAKER_00: Our generative AI, in order to help our damage detection algorithms, we generate packages that have dents on it and scratches and marks, and it we use a as a test, or generative AI in order to optimize the trajectories of our robotic arms.
37:27
SPEAKER_00: Like we're using that dent now.
37:29
SPEAKER_00: So many, many examples of generative AI that are really changing the game for us.
37:33
SPEAKER_00: Uh if you can get to, and they're not no, no, none of the three buckets are better than the others.
37:39
SPEAKER_00: They just have different purposes and functions, right?
37:42
SPEAKER_00: I think you should be at least in one or two or three.
37:46
SPEAKER_00: If you're if you're doing anything uh productive, you should probably be in one, two, or three.
37:51
SPEAKER_01: Yeah, and and but that's also where it's important to again start setting realistic realistic expectations, you know, from somebody who doesn't understand the nature of how these things work.
38:02
SPEAKER_01: Well, you know, it can write a story.
38:03
SPEAKER_01: So of course, you know, we're close to to you know, AGI, you know, of course it can tell a robot how to do this.
38:10
SPEAKER_01: And then, you know, that that compounded with, as you said, the the ease with which somebody can create a flashy uh YouTube video.
38:19
SPEAKER_01: I feel like we're maybe not doing ourselves any favors as far as setting those realistic expectations.
38:25
SPEAKER_01: Uh, you know, at Amazon, uh, you know, as a company who, again, has a very strong investment in real-world robots doing real-world things, what can you do to help temper expectations?
38:39
SPEAKER_00: Well, first it's a mindset, and I've had this mindset for quite a while.
38:43
SPEAKER_00: Uh, I'm gonna just quote a book uh by Jim Collins.
38:46
SPEAKER_00: It's called Built to Last.
38:47
SPEAKER_00: If you haven't read that book, it's it's a fascinating reading.
38:50
SPEAKER_00: It's about how companies can survive for 50 or more years and what are the common characteristics in in those companies, right?
38:55
SPEAKER_00: For longevity.
38:57
SPEAKER_00: And there's a really great uh mental model that is uh put forward.
39:04
SPEAKER_00: The quote goes be the clockmaker, not the timeteller.
39:10
SPEAKER_00: So be the clock maker, not the timeteller.
39:15
SPEAKER_00: Meaning get into it.
39:17
SPEAKER_00: Dive headfirst into what it is that you are doing, not just use it as a as a service, but in at least in robotics, that's what we're doing.
39:27
SPEAKER_00: We're getting we're getting knee deep, arm deep, completely immersed uh in building responsible, accountable, and ethical physical AI systems um in order to help people be more productive.
39:42
SPEAKER_00: And it works.
39:43
SPEAKER_00: Like, for example, our Shreveport building that we just announced this past spring, 2,500 new jobs, brand new jobs uh down there, 10 times the amount of robotics we've ever done.
39:53
SPEAKER_00: We can process orders 25% faster in that building.
39:56
SPEAKER_00: There's 30% more demand for more skilled uh workers.
40:00
SPEAKER_00: Our apprenticeship uh program is taking off there.
40:02
SPEAKER_00: This works.
40:03
SPEAKER_00: It's creating jobs, it's allowing people to focus on what matters at work, uh, and it's really changing the game when it comes to our customer obsession in order to get the right good at the right time right to the customer's door.
40:17
SPEAKER_01: This is maybe a like a too big overly broad question, but when you say what do you mean when you say ethical AI?
40:25
SPEAKER_00: That means that you always have people at you put people at the center of the robotics universe.
40:31
SPEAKER_00: Always.
40:33
SPEAKER_00: Right?
40:33
SPEAKER_00: Always you put people at the center.
40:35
SPEAKER_00: Like your employees, your frontline employees, the women and men who designed these systems, you make it for people.
40:42
SPEAKER_00: It's not people against machines, it's people and machines working together.
40:47
SPEAKER_00: And the onus is on us in order to make it responsible, accountable, and ethical for human consumption.
40:55
SPEAKER_01: My understanding is um uh after talking to a few people that um obviously sort of the the big first really kind of publicized work that Amazon was doing in terms of exploration with the humanoid form factor in industrial warehouse setting was the the 2023 partnerships with agility.
41:14
SPEAKER_01: But the company was exploring some sort of bipedal form factors prior to that, right?
41:19
SPEAKER_01: That was something that you had sort of considered actually uh whether or not it would make sense to uh fit that into the processes that you had in place.
41:30
SPEAKER_00: Well, I remember in the 90s, speaking of Mark Raybert, like this with this like in the locomotion lab, like it is just truly about you know how to walk through difficult terrain, right?
41:41
SPEAKER_00: It's fascinating.
41:42
SPEAKER_00: It's a fascinating uh subject uh for sure.
41:44
SPEAKER_00: Um I know in the early days of agility as well that they had that in mind as well.
41:50
SPEAKER_00: Like they uh I think they've they've shown like a pretty famous video of uh almost a a chicken of how a chicken just kind of can make its way across variable terrain, kind of with the the physical intelligence, right?
42:01
SPEAKER_00: The physical intelligence that is new.
42:03
SPEAKER_00: And I I again I applaud those type of efforts of anything that we can do to advance the state of mobility.
42:10
SPEAKER_00: Uh I applaud.
42:11
SPEAKER_01: It strikes me that that you will explore technology.
42:14
SPEAKER_01: You know, I I think maybe around that time it was again like early days of agility, they were showing off Cassie.
42:20
SPEAKER_01: Explore the potential, realize maybe this isn't the time, we're not quite ready, but don't but but then you don't count it out, right?
42:27
SPEAKER_01: Then you realize that the time will come and then we will try again to integrate this into the system.
42:34
SPEAKER_00: Yeah, and that it's it's it's such a good thought because I mean remember, like it's a full spectrum when it comes to robotics, right?
42:42
SPEAKER_00: There's there's early technology readiness levels or TRL was what we used to call it in aerospace, where there's ideation and there's proof of concept of like, is this possible?
42:53
SPEAKER_00: And I always remind the team, it's like we don't do technology for technology's sake, right?
42:58
SPEAKER_00: What problem are we trying to solve?
42:59
SPEAKER_00: And even in the ideation phase, we have to stay sharp and focused on what's the problem we're trying to solve in front of us.
43:05
SPEAKER_00: And if we see a problem that we want to solve, whether it's a new sortation or a new storage uh capability or uh a new manipulation capability, then that a lot that gives us the focus in order to advance our technologies.
43:17
SPEAKER_00: But it's not over then.
43:18
SPEAKER_00: Like there's so many steps in it for it to get to the fulfillment center, right?
43:22
SPEAKER_00: Yeah.
43:22
SPEAKER_00: It's it's commonly known as the valley of death, right?
43:25
SPEAKER_00: So you have early stage ideation going on with even a proof of concept on this side.
43:30
SPEAKER_00: And on the far side, you have your your operational users, and they really don't want any change.
43:34
SPEAKER_00: They want stuff that works.
43:35
SPEAKER_00: Like they don't have time to mess around with like, I need I need good tools, I need professional tools, and they have to work, right?
43:43
SPEAKER_00: And they're resistant to change.
43:45
SPEAKER_00: So what happens in between?
43:46
SPEAKER_00: Well, if you're resistant to change, you're not going to pull something through.
43:50
SPEAKER_00: And on the other side, if you have no idea what the application is, you're not gonna push something through.
43:54
SPEAKER_00: But I think Amazon strikes a really great balance in between where we have product managers that Understand what technologies that we do we need to evolve.
44:03
SPEAKER_00: They will reach out to me and to my team and to our robotics in general to say, hey, if we can just solve this, that would be a really big win for us.
44:12
SPEAKER_00: So that puts it in the pipeline for us and helps pull it through that valley of death because there is application.
44:18
SPEAKER_00: But every time that we do that, I mean every single time that we do it, we may convince ourselves it's working great in the lab.
44:24
SPEAKER_00: And we're like, oh my gosh, yeah, this is it.
44:27
SPEAKER_00: And then we'll go to the actual environment, TRL seven.
44:31
SPEAKER_00: We're in the actual environment, and we'll go to one quarter of one floor in one building and try it with real uh users, real frontline employees, and we will listen directly to their feedback.
44:44
SPEAKER_00: And we like to hear it exactly the way that they say it.
44:47
SPEAKER_00: Like you don't get to change a single word about what how they're saying what's good or what's bad uh about it.
44:53
SPEAKER_00: And this is after it's gone through, and we have 9,000 plus safety engineers, right?
44:57
SPEAKER_00: We have manufacturing engineers that are involved in this.
45:00
SPEAKER_00: Like there's a lot of process in order for it to even get to the floor.
45:03
SPEAKER_00: And then we will learn and we will iterate.
45:05
SPEAKER_00: And if it's not working, we'll iterate.
45:08
SPEAKER_00: And if we we can't iterate it well enough for our employees, it's gone.
45:12
SPEAKER_00: It's like we we go back to the drawing board because it's not it's not amplifying human potential, it's not augmenting what the employee is capable of of doing.
45:23
SPEAKER_00: If it's a replacement strategy, other than the menial, the mundane, and the repetitive, we want to make it better.
45:29
SPEAKER_00: Okay.
45:29
SPEAKER_00: So even if a one quarter of one floor, we'll go to one floor and then maybe we even go to one building, and it's still not good enough.
45:36
SPEAKER_00: Right.
45:36
SPEAKER_00: When we start to roll something out for what we call general availability, that is really a big deal.
45:41
unknown: Right.
45:41
SPEAKER_00: It's a so there's so many steps in between of like what we're doing in the lab to actually is it deployed on the front lines?
45:47
SPEAKER_00: And when it hits the front lines, it works.
45:49
SPEAKER_00: It works really well.
45:51
SPEAKER_01: I feel like what could maybe maybe the most public-facing and one of the most interesting examples of this is actually it takes us outside of the warehouse floor, is Scout, right?
46:01
SPEAKER_01: Because Scout, to me, I'm looking at Scout and it's like, of course, Amazon is exploring last mile delivery robot that makes that makes perfect sense, uh, well publicized, you know, that at least at that point, you know, from where I sit, it seems like that those those experiments didn't quite work out quite like Amazon was hoping.
46:23
SPEAKER_01: And then obviously, like folks like me in the media are like, all right, this, you know, this is gone, blah, blah, blah.
46:28
SPEAKER_01: That's what the stories are about.
46:29
SPEAKER_01: Um but an example like that, I I, you know, I I can't imagine that that that specific um pilot didn't work.
46:41
SPEAKER_01: So you or or whoever at Amazon is suddenly saying, all right, well, we're not doing last mile delivery robots anymore.
46:50
SPEAKER_00: Well, you know, we also had Firephone as well, right?
46:52
SPEAKER_00: So I mean, sure.
46:54
SPEAKER_00: Right?
46:54
SPEAKER_00: Sure.
46:55
SPEAKER_00: That's a big one.
46:56
SPEAKER_00: Slightly different example, but yeah.
46:58
SPEAKER_00: What you learned from it.
46:58
SPEAKER_00: And Scout look, again, what problem you're trying to solve?
47:02
SPEAKER_00: Uh one of the things that we saw in Scout that we we we didn't like is it we call attended delivery.
47:10
SPEAKER_00: When you get your packages today, those packages show up outside your door, ready to go, and it's it's you, you know, you you get your goods.
47:18
SPEAKER_00: But if in an attended delivery, if you have to rendezvous and schedule with a robot, that that's adding friction.
47:23
SPEAKER_00: That's not that's not customer customer obsession, right?
47:26
SPEAKER_00: That is not insisting on the highest standard for for our customer.
47:30
SPEAKER_00: Right.
47:30
SPEAKER_00: So we need to really to go back to the uh be vocally self-critical that we're not to what problem we're trying to solve.
47:37
SPEAKER_00: We weren't really on there.
47:38
SPEAKER_00: Uh and we really needed to uh I'd say better that system, right?
47:46
SPEAKER_00: That that's yeah, so if as much as I love to, I mean, I I love technology and I love a cool robot.
47:52
SPEAKER_00: I love for sure, you gotta think about what problem you're trying to solve.
47:55
SPEAKER_00: I think Scout is a good example of like, hey, we need to go back to the drawing board.
48:00
SPEAKER_01: Obviously, for Amazon, robots really majorly starting in um the the warehouse in these fulfillment centers, really scaling that up, you know, one million units.
48:11
SPEAKER_01: Um, you know, you've got your consumer uh work over here, but um eventually, and you and you alluded to this before in terms of agriculture and other things, but eventually seeing starting to see some of that work filter out into other things that Amazon does and other parts just of the world generally.
48:29
SPEAKER_00: Absolutely.
48:29
SPEAKER_00: I mean, we started uh in what we call the structured fields, right?
48:32
SPEAKER_00: So structured fields with with Hercules with QR codes and robots and fences.
48:37
SPEAKER_00: Uh now uh we're moving towards semi-structured, uh, like with Proteus, for example, fully safety certified, working around people, moving carts of goods uh to the dock doors uh at will, uh, working uh amazingly uh beautiful.
48:50
SPEAKER_00: So from structured to semi-structured uh is something that we are mastering uh right now.
48:55
SPEAKER_00: So I wouldn't be surprised uh, you know, the for us to continue to innovate in all ways for our customers, whether it's you know, even in the uh less structured environment.
49:04
SPEAKER_01: Ty, always a pleasure speaking with you.
49:06
SPEAKER_01: Great sweater.
49:07
SPEAKER_01: Hope to talk to you soon.
49:09
SPEAKER_00: Looking sharp, Brian.
49:10
SPEAKER_00: Always great to see you too.
49:11
SPEAKER_00: Take care, my friend.
49:14
SPEAKER_01: Really wonderful conversation.
49:16
SPEAKER_01: Thank you so much to Ty for taking the time out of his schedule to set that up.
49:20
SPEAKER_01: Uh, thanks to Andy at Amazon for helping set up that interview.
49:24
SPEAKER_01: Thanks to Maureen and VN, the humans, and Frankie the dog for the production and editing this week.
49:32
SPEAKER_01: And thanks to you for sitting long enough to hear this outro.
49:36
SPEAKER_01: Please like and subscribe, and don't forget to sign up for our weekly newsletter of the same name.
49:43
SPEAKER_01: And we will see you next week for another episode of Automated.