Is AI what Robotics needs? with Jasmine Lawrence Campbell

Maybe you've been involved in a Maybe you've been involved in a Microsoft 365 migration, optimizing your Microsoft 365 migration, optimizing your Microsoft 365 migration, optimizing your environment, maybe prepping for environment, maybe prepping for environment, maybe prepping for co-pilot, and then you've probably heard co-pilot, and then you've probably heard co-pilot, and then you've probably heard the name Sharegate. It rarely gets the the name Sharegate. It rarely gets the the name Sharegate. It rarely gets the spotlight, but everything runs on what spotlight, but everything runs on what spotlight, but everything runs on what they build. Mergers, restructures, they build. Mergers, restructures, they build. Mergers, restructures, tenant sprawl, it figures it out as they tenant sprawl, it figures it out as they tenant sprawl, it figures it out as they handle everything from migrating data handle everything from migrating data handle everything from migrating data from tenant to tenant to making sure from tenant to tenant to making sure from tenant to tenant to making sure that AI and co-pilot is ready to be that AI and co-pilot is ready to be that AI and co-pilot is ready to be rolled out securely and responsibly. rolled out securely and responsibly. rolled out securely and responsibly. They make chaos feel like business as They make chaos feel like business as They make chaos feel like business as usual. And Sharegate, it's the sidekick usual. And Sharegate, it's the sidekick usual. And Sharegate, it's the sidekick that helps them do it. Sharegate is an that helps them do it. Sharegate is an that helps them do it. Sharegate is an out-of-the-box tool that simplifies the out-of-the-box tool that simplifies the out-of-the-box tool that simplifies the chaos that it faces. Assess, migrate, chaos that it faces. Assess, migrate, chaos that it faces. Assess, migrate, optimize. It's that simple. Now, whether optimize. It's that simple. Now, whether optimize. It's that simple. Now, whether it's tenant to tenant, Microsoft it's tenant to tenant, Microsoft it's tenant to tenant, Microsoft Exchange, Google to M365, or getting Exchange, Google to M365, or getting Exchange, Google to M365, or getting visibility on your data hygiene in order visibility on your data hygiene in order visibility on your data hygiene in order to prep for co-pilot rollouts, ShareGate to prep for co-pilot rollouts, ShareGate to prep for co-pilot rollouts, ShareGate helps it migrate quickly, cleanly, and helps it migrate quickly, cleanly, and helps it migrate quickly, cleanly, and with minimal drama. Go to sharegate.com. with minimal drama. Go to sharegate.com. with minimal drama. Go to sharegate.com. It's one tool, fast migrations and It's one tool, fast migrations and It's one tool, fast migrations and co-pilot co-pilot co-pilot [Music] ready. Hi, I'm Scott Hansselman. This is ready. Hi, I'm Scott Hansselman. This is another episode of Hansel Minutes. Today another episode of Hansel Minutes. Today another episode of Hansel Minutes. Today I'm talking with Jasmine Lawrence I'm talking with Jasmine Lawrence I'm talking with Jasmine Lawrence Campbell. She is a a technical product Campbell. She is a a technical product Campbell. She is a a technical product manager at Escape and Robotics. She's manager at Escape and Robotics. She's manager at Escape and Robotics. She's worked at companies like Microsoft and worked at companies like Microsoft and worked at companies like Microsoft and Nvidia. She has both a bachelor's from Nvidia. She has both a bachelor's from Nvidia. She has both a bachelor's from Georgia Institute of Technology and a

Georgia Institute of Technology and a Georgia Institute of Technology and a master's from University of Washington. master's from University of Washington. master's from University of Washington. Thank you so much for hanging out with Thank you so much for hanging out with Thank you so much for hanging out with me today. Hey Scott, thanks for having me today. Hey Scott, thanks for having me today. Hey Scott, thanks for having me. Um, man, I just tell you when I look me. Um, man, I just tell you when I look me. Um, man, I just tell you when I look at people's LinkedIn and they're just so at people's LinkedIn and they're just so at people's LinkedIn and they're just so epic, I just feel bad about my own epic, I just feel bad about my own epic, I just feel bad about my own LinkedIn. You've got a you've done so LinkedIn. You've got a you've done so LinkedIn. You've got a you've done so much. No, don't feel bad, Scott. You'll much. No, don't feel bad, Scott. You'll much. No, don't feel bad, Scott. You'll you'll measure up to me one day. One day you'll measure up to me one day. One day you'll measure up to me one day. One day I'll get on your level. One day I'll get I'll get on your level. One day I'll get I'll get on your level. One day I'll get on your level. Honestly, you're a role on your level. Honestly, you're a role on your level. Honestly, you're a role model for me. I I love what you do to model for me. I I love what you do to model for me. I I love what you do to advocate for developers. Oh, well that's advocate for developers. Oh, well that's advocate for developers. Oh, well that's very sweet. I appreciate that. I love very sweet. I appreciate that. I love very sweet. I appreciate that. I love that you are not only quietly building that you are not only quietly building that you are not only quietly building and quietly grinding, but then when you and quietly grinding, but then when you and quietly grinding, but then when you do something, you go out and you talk do something, you go out and you talk do something, you go out and you talk about it and you tell people about it about it and you tell people about it about it and you tell people about it and then you bring them in and you help and then you bring them in and you help and then you bring them in and you help them as well. You lift up other people them as well. You lift up other people them as well. You lift up other people and I appreciate you. Absolutely. Thank and I appreciate you. Absolutely. Thank and I appreciate you. Absolutely. Thank you so much. I think a lot of my vision you so much. I think a lot of my vision you so much. I think a lot of my vision can't be accomplished by just me and can't be accomplished by just me and can't be accomplished by just me and what I'm able to carry on my shoulder. what I'm able to carry on my shoulder. what I'm able to carry on my shoulder. So if I can inspire other people to get So if I can inspire other people to get So if I can inspire other people to get involved, leverage their skills or you involved, leverage their skills or you involved, leverage their skills or you know support other people who want to be know support other people who want to be know support other people who want to be a part of the work that is what I will a part of the work that is what I will a part of the work that is what I will do. And you won't stop because I think do. And you won't stop because I think do. And you won't stop because I think uh I'm trying to remember when I met you uh I'm trying to remember when I met you uh I'm trying to remember when I met you but like you have started a but like you have started a but like you have started a non-technical company and led it and non-technical company and led it and non-technical company and led it and like you can buy Eden Bodyworks products like you can buy Eden Bodyworks products like you can buy Eden Bodyworks products in stores today even still. But then you in stores today even still. But then you in stores today even still. But then you are also like you've been a roboticist are also like you've been a roboticist are also like you've been a roboticist and you've been an AIM ML expert since and you've been an AIM ML expert since and you've been an AIM ML expert since before everyone was talking about it before everyone was talking about it before everyone was talking about it before it was cool. Yeah, I'm going to before it was cool. Yeah, I'm going to before it was cool. Yeah, I'm going to take that for sure. Did you feel like take that for sure. Did you feel like take that for sure. Did you feel like when AI became like a thing that people when AI became like a thing that people when AI became like a thing that people had in their mouths, you were like, had in their mouths, you were like, had in their mouths, you were like, "Hey, now I told y'all a decade ago, you "Hey, now I told y'all a decade ago, you "Hey, now I told y'all a decade ago, you know?" No, I'm not a futurist. I more know?" No, I'm not a futurist. I more know?" No, I'm not a futurist. I more have been trying to navigate my career have been trying to navigate my career have been trying to navigate my career and figuring out like where the money is

and figuring out like where the money is and figuring out like where the money is going to go because one of the going to go because one of the going to go because one of the challenges for me as I started my career challenges for me as I started my career challenges for me as I started my career in robotics was that I wasn't passionate in robotics was that I wasn't passionate in robotics was that I wasn't passionate about manufacturing. I wasn't passionate about manufacturing. I wasn't passionate about manufacturing. I wasn't passionate about optimizing warehouses but that's about optimizing warehouses but that's about optimizing warehouses but that's where a lot of the impact was happening. where a lot of the impact was happening. where a lot of the impact was happening. I'm excited to see today's innovations I'm excited to see today's innovations I'm excited to see today's innovations because it's really driving an because it's really driving an because it's really driving an investment in like vertical AI or like investment in like vertical AI or like investment in like vertical AI or like singlepurpose robotics if I can call it singlepurpose robotics if I can call it singlepurpose robotics if I can call it that even though there's even more that even though there's even more that even though there's even more excitement around um general AI or um excitement around um general AI or um excitement around um general AI or um general artificial intelligence but for general artificial intelligence but for general artificial intelligence but for me it's been really finding an me it's been really finding an me it's been really finding an organization that's committed to doing organization that's committed to doing organization that's committed to doing something that we can actually something that we can actually something that we can actually productize because as you mentioned in productize because as you mentioned in productize because as you mentioned in my background I'm used to getting things my background I'm used to getting things my background I'm used to getting things into the hands of customers and making into the hands of customers and making into the hands of customers and making sure the experiences are wholesome and sure the experiences are wholesome and sure the experiences are wholesome and inclusive. Yeah. Um, you said something inclusive. Yeah. Um, you said something inclusive. Yeah. Um, you said something that I want to I want to start with that I want to I want to start with that I want to I want to start with because I think it's a great way to because I think it's a great way to because I think it's a great way to understand because most people think understand because most people think understand because most people think about robots, they think about Will about robots, they think about Will about robots, they think about Will Smith, i, robot, they think about Smith, i, robot, they think about Smith, i, robot, they think about promises that billionaires have made promises that billionaires have made promises that billionaires have made about robots and they want a Rosie the about robots and they want a Rosie the about robots and they want a Rosie the robot to fold their clothes, right? Like robot to fold their clothes, right? Like robot to fold their clothes, right? Like I think about the stuff that I dislike I think about the stuff that I dislike I think about the stuff that I dislike the most. It's the dishwasher and it's the most. It's the dishwasher and it's the most. It's the dishwasher and it's the folding the clothes. But you said the folding the clothes. But you said the folding the clothes. But you said singlepurpose robots and that feels like singlepurpose robots and that feels like singlepurpose robots and that feels like from a manufacturing perspective, maybe from a manufacturing perspective, maybe from a manufacturing perspective, maybe this is a overstatement, but a solved this is a overstatement, but a solved this is a overstatement, but a solved problem. Like I've seen robots move at problem. Like I've seen robots move at problem. Like I've seen robots move at speed pick and placing stuff, but I speed pick and placing stuff, but I speed pick and placing stuff, but I still can't get one in my house to fold still can't get one in my house to fold still can't get one in my house to fold my laundry. Yeah, that's a very great my laundry. Yeah, that's a very great my laundry. Yeah, that's a very great question. Thank you so much for this question. Thank you so much for this question. Thank you so much for this softball. Um, so in factories, there are softball. Um, so in factories, there are softball. Um, so in factories, there are very constrained environments, right, very constrained environments, right, very constrained environments, right, that are not dynamic at all. There are that are not dynamic at all. There are that are not dynamic at all. There are strict boundaries and regulations around strict boundaries and regulations around strict boundaries and regulations around how humans and robots come into contact

how humans and robots come into contact how humans and robots come into contact or interact with each other or not in or interact with each other or not in or interact with each other or not in these environments. You want a robot in these environments. You want a robot in these environments. You want a robot in your home that can adapt to your home your home that can adapt to your home your home that can adapt to your home every single day. And you know your kids every single day. And you know your kids every single day. And you know your kids are going to leave their shoes one place are going to leave their shoes one place are going to leave their shoes one place in one day. Rug's going to be in a in one day. Rug's going to be in a in one day. Rug's going to be in a position another day. And so it's a position another day. And so it's a position another day. And so it's a combination of like it's not the combination of like it's not the combination of like it's not the shortage of the capability of the robot shortage of the capability of the robot shortage of the capability of the robot to do it, but to do it in a dynamic and to do it, but to do it in a dynamic and to do it, but to do it in a dynamic and adaptive way that is honestly only made adaptive way that is honestly only made adaptive way that is honestly only made possible by machine learning and a possible by machine learning and a possible by machine learning and a combination of human in the loop. Right? combination of human in the loop. Right? combination of human in the loop. Right? We've seen uh I've recently read an We've seen uh I've recently read an We've seen uh I've recently read an article about Roombas, right? They've article about Roombas, right? They've article about Roombas, right? They've been in the market for 20 years even and been in the market for 20 years even and been in the market for 20 years even and they're still having challenges where they're still having challenges where they're still having challenges where with object detection where the robot is with object detection where the robot is with object detection where the robot is designed for its single purpose of designed for its single purpose of designed for its single purpose of cleaning the floor and it will see some cleaning the floor and it will see some cleaning the floor and it will see some dog poop on the rug and say, "I should dog poop on the rug and say, "I should dog poop on the rug and say, "I should clean that." And because it's not clean that." And because it's not clean that." And because it's not effective at um cleaning that, you'll effective at um cleaning that, you'll effective at um cleaning that, you'll have more poop in your house than you have more poop in your house than you have more poop in your house than you ever wanted. So, it's really figuring ever wanted. So, it's really figuring ever wanted. So, it's really figuring out how do you make this thing the best out how do you make this thing the best out how do you make this thing the best candidate's job. Now, if this Roomba candidate's job. Now, if this Roomba candidate's job. Now, if this Roomba Roomba also had to fold your laundry and Roomba also had to fold your laundry and Roomba also had to fold your laundry and put your shoes away and dust your put your shoes away and dust your put your shoes away and dust your countertops, the complexity of the countertops, the complexity of the countertops, the complexity of the problem really raises. So, it's been problem really raises. So, it's been problem really raises. So, it's been really exciting for me to try and find a really exciting for me to try and find a really exciting for me to try and find a place where we can fully investigate a place where we can fully investigate a place where we can fully investigate a use case and and make it the best that use case and and make it the best that use case and and make it the best that it can be and then offer that globally.

it can be and then offer that globally. it can be and then offer that globally. I feel like I as a let's pretend I'm a I feel like I as a let's pretend I'm a I feel like I as a let's pretend I'm a lay person and I'll speak for on behalf lay person and I'll speak for on behalf lay person and I'll speak for on behalf of like non-technical parent like uh of like non-technical parent like uh of like non-technical parent like uh I've got my phone I'm holding up here, I've got my phone I'm holding up here, I've got my phone I'm holding up here, right? And it's 12 million times more right? And it's 12 million times more right? And it's 12 million times more powerful than my Commodore 64 that I got powerful than my Commodore 64 that I got powerful than my Commodore 64 that I got when I started. But my Roomba, and I'm when I started. But my Roomba, and I'm when I started. But my Roomba, and I'm not talking about Roomba, the company, I not talking about Roomba, the company, I not talking about Roomba, the company, I love you all. I'm talking about Roomba love you all. I'm talking about Roomba love you all. I'm talking about Roomba like Kleenex. It's just a generic word like Kleenex. It's just a generic word like Kleenex. It's just a generic word for the disc that walks around my house. for the disc that walks around my house. for the disc that walks around my house. My Roomba is dumb as hell, right? It's My Roomba is dumb as hell, right? It's My Roomba is dumb as hell, right? It's just dumb. And it was dumb when it was just dumb. And it was dumb when it was just dumb. And it was dumb when it was bouncing around randomly. And now it has bouncing around randomly. And now it has bouncing around randomly. And now it has LAR and radar and cameras and it's still LAR and radar and cameras and it's still LAR and radar and cameras and it's still dumb. Help me understand why my phone is dumb. Help me understand why my phone is dumb. Help me understand why my phone is so powerful and my Roomba is so dumb. so powerful and my Roomba is so dumb. so powerful and my Roomba is so dumb. That is a great question. That is a That is a great question. That is a That is a great question. That is a great question. I don't know. I have to great question. I don't know. I have to great question. I don't know. I have to put my like speculative product head on. put my like speculative product head on. put my like speculative product head on. I think like I said, it's it's the I think like I said, it's it's the I think like I said, it's it's the variance of the different environments. variance of the different environments. variance of the different environments. I don't know why it's not smarter yet. I don't know why it's not smarter yet. I don't know why it's not smarter yet. It's probably older algorithms. And It's probably older algorithms. And It's probably older algorithms. And honestly, I'm not sure if every person honestly, I'm not sure if every person honestly, I'm not sure if every person is your Roomba connected to the is your Roomba connected to the is your Roomba connected to the internet. Yeah. So, I have a Robo Rock internet. Yeah. So, I have a Robo Rock internet. Yeah. So, I have a Robo Rock and it's quite sophisticated and I love and it's quite sophisticated and I love and it's quite sophisticated and I love their their app. Um, and there's also their their app. Um, and there's also their their app. Um, and there's also open- source software for people who open- source software for people who open- source software for people who don't want a cloud enabled. Yeah. robot don't want a cloud enabled. Yeah. robot don't want a cloud enabled. Yeah. robot because people don't want, you know, because people don't want, you know, because people don't want, you know, their inside of their house being sent their inside of their house being sent their inside of their house being sent off to a foreign country, which is off to a foreign country, which is off to a foreign country, which is valid. No, these are the trade-offs, valid. No, these are the trade-offs, valid. No, these are the trade-offs, right? Because if everything has to right? Because if everything has to right? Because if everything has to happen on the device itself and it has happen on the device itself and it has happen on the device itself and it has limited compute because of how it's limited compute because of how it's limited compute because of how it's being manufactured, it really limits being manufactured, it really limits being manufactured, it really limits what it can do, what it can see, how it what it can do, what it can see, how it what it can do, what it can see, how it can see, right? It's maybe not doing um can see, right? It's maybe not doing um can see, right? It's maybe not doing um also, sorry, some of the sensor data

also, sorry, some of the sensor data also, sorry, some of the sensor data might not be leveraged for each one of might not be leveraged for each one of might not be leveraged for each one of the capabilities. So, for example, it the capabilities. So, for example, it the capabilities. So, for example, it might have that um LAR or time offlight might have that um LAR or time offlight might have that um LAR or time offlight sensor, but it might only be used for sensor, but it might only be used for sensor, but it might only be used for detecting ledges and making sure it detecting ledges and making sure it detecting ledges and making sure it doesn't fall down the stairs or get doesn't fall down the stairs or get doesn't fall down the stairs or get trapped under a couch that it might not trapped under a couch that it might not trapped under a couch that it might not fit under. Um, yeah, there's a lot of fit under. Um, yeah, there's a lot of fit under. Um, yeah, there's a lot of options. I think there's just been a lot options. I think there's just been a lot options. I think there's just been a lot of innovation in the last even 5 years of innovation in the last even 5 years of innovation in the last even 5 years on what sensors and computing and um you on what sensors and computing and um you on what sensors and computing and um you know there's also this challenge of like know there's also this challenge of like know there's also this challenge of like hey maybe your rula has like a perfect hey maybe your rula has like a perfect hey maybe your rula has like a perfect slam-based map of your your house so it slam-based map of your your house so it slam-based map of your your house so it kind of knows where things are but it's kind of knows where things are but it's kind of knows where things are but it's not it's like making that new every day. not it's like making that new every day. not it's like making that new every day. It's not doing any kind of predictive It's not doing any kind of predictive It's not doing any kind of predictive forecasting of like hey this was here forecasting of like hey this was here forecasting of like hey this was here this was there um or even having the this was there um or even having the this was there um or even having the knowledge of like this is a movable knowledge of like this is a movable knowledge of like this is a movable object versus a fixed structure. So even object versus a fixed structure. So even object versus a fixed structure. So even our understanding of the world could be our understanding of the world could be our understanding of the world could be incomplete in in making your device seem incomplete in in making your device seem incomplete in in making your device seem pretty dumb. And I want to uh expand one pretty dumb. And I want to uh expand one pretty dumb. And I want to uh expand one of your acronyms there. You just said a of your acronyms there. You just said a of your acronyms there. You just said a slam-based map. Like if you throw it out slam-based map. Like if you throw it out slam-based map. Like if you throw it out like everyone would know that like everyone would know that like everyone would know that simultaneous localization and mapping, simultaneous localization and mapping, simultaneous localization and mapping, right? So this is how to map an unknown right? So this is how to map an unknown right? So this is how to map an unknown environment. Talk about that because I environment. Talk about that because I environment. Talk about that because I know it's doing that kind of work. Yeah.

know it's doing that kind of work. Yeah. know it's doing that kind of work. Yeah. So basically it'll it'll walk it'll walk So basically it'll it'll walk it'll walk So basically it'll it'll walk it'll walk around uh zoom around and kind of taking around uh zoom around and kind of taking around uh zoom around and kind of taking I think a lot of people use lasers I think a lot of people use lasers I think a lot of people use lasers nowadays calculating the distance nowadays calculating the distance nowadays calculating the distance between itself and other I think we call between itself and other I think we call between itself and other I think we call them like landmarks in the environment them like landmarks in the environment them like landmarks in the environment and assess like hey I think I'm here and and assess like hey I think I'm here and and assess like hey I think I'm here and in relation to whatever surface this in relation to whatever surface this in relation to whatever surface this laser is bouncing off of I'm going to laser is bouncing off of I'm going to laser is bouncing off of I'm going to draw a boundary that this might be a draw a boundary that this might be a draw a boundary that this might be a edge or a wall and it will go around edge or a wall and it will go around edge or a wall and it will go around this environment as many times as needed this environment as many times as needed this environment as many times as needed to form a complete map. So if you think to form a complete map. So if you think to form a complete map. So if you think about like a top- down map that you about like a top- down map that you about like a top- down map that you might use not even at the fidelity of might use not even at the fidelity of might use not even at the fidelity of like a Google maps but like something like a Google maps but like something like a Google maps but like something something like a pirate map level right something like a pirate map level right something like a pirate map level right so like outlines and the edges honestly so like outlines and the edges honestly so like outlines and the edges honestly um that's essentially what you get out um that's essentially what you get out um that's essentially what you get out of SLAM. Now what you can do is really of SLAM. Now what you can do is really of SLAM. Now what you can do is really pair that map with some of the other pair that map with some of the other pair that map with some of the other sensors on the robot like the sensors sensors on the robot like the sensors sensors on the robot like the sensors that track how many rotations the wheel that track how many rotations the wheel that track how many rotations the wheel has had like using the odometer. has had like using the odometer. has had like using the odometer. combining a lot of this information, you combining a lot of this information, you combining a lot of this information, you can know where you are in the can know where you are in the can know where you are in the environment and and where these environment and and where these environment and and where these landmarks that you're running into might landmarks that you're running into might landmarks that you're running into might be. So, yeah, a lot that was a really be. So, yeah, a lot that was a really be. So, yeah, a lot that was a really innovative um solution for getting innovative um solution for getting innovative um solution for getting navigation indoors. All of this falls navigation indoors. All of this falls navigation indoors. All of this falls apart obviously as things move in the apart obviously as things move in the apart obviously as things move in the environment or as we step outside your environment or as we step outside your environment or as we step outside your front door and go into the real world.

front door and go into the real world. front door and go into the real world. Yeah, it's pretty tough. It's so Yeah, it's pretty tough. It's so Yeah, it's pretty tough. It's so interesting the rel the the having interesting the rel the the having interesting the rel the the having conversations with about something like conversations with about something like conversations with about something like a robot with someone like you who knows a robot with someone like you who knows a robot with someone like you who knows what they're talking about and then what they're talking about and then what they're talking about and then trying to explain it to like a trying to explain it to like a trying to explain it to like a nontechnical friend or parent because nontechnical friend or parent because nontechnical friend or parent because when you were saying like the number of when you were saying like the number of when you were saying like the number of rotations of the wheel I'm imagining rotations of the wheel I'm imagining rotations of the wheel I'm imagining myself you know pretend you're blind you myself you know pretend you're blind you myself you know pretend you're blind you close your eyes you know that your foot close your eyes you know that your foot close your eyes you know that your foot is a foot long you put your hands out in is a foot long you put your hands out in is a foot long you put your hands out in front of you and you walk around but if front of you and you walk around but if front of you and you walk around but if your foot slips once you're off by a your foot slips once you're off by a your foot slips once you're off by a foot Yeah. And if the wheel slips on the foot Yeah. And if the wheel slips on the foot Yeah. And if the wheel slips on the Roomba because it hits something Roomba because it hits something Roomba because it hits something slippery, now it completely is off. So slippery, now it completely is off. So slippery, now it completely is off. So the rest of the map is off by this, but the rest of the map is off by this, but the rest of the map is off by this, but then it has to selforrect. It's really then it has to selforrect. It's really then it has to selforrect. It's really interesting math. It really is. And interesting math. It really is. And interesting math. It really is. And honestly, I think what is the one of the honestly, I think what is the one of the honestly, I think what is the one of the most exciting and endearing aspects of most exciting and endearing aspects of most exciting and endearing aspects of robotics to me is that in your example, robotics to me is that in your example, robotics to me is that in your example, people have no conscious sense of how people have no conscious sense of how people have no conscious sense of how they navigate the world. They completely they navigate the world. They completely they navigate the world. They completely underestimate all the parts of their underestimate all the parts of their underestimate all the parts of their brains and the proprioception and blah brains and the proprioception and blah brains and the proprioception and blah blah blah that goes into us being able blah blah that goes into us being able blah blah that goes into us being able to navigate the world. The rumor only to navigate the world. The rumor only to navigate the world. The rumor only seems dumb because we underestimate what seems dumb because we underestimate what seems dumb because we underestimate what intelligence is, which honestly has yet intelligence is, which honestly has yet intelligence is, which honestly has yet to be defined. But when you try to um to be defined. But when you try to um to be defined. But when you try to um quantify these things, it gets really quantify these things, it gets really quantify these things, it gets really challenging. But what I love is that it challenging. But what I love is that it challenging. But what I love is that it it helps me to pursue a deeper it helps me to pursue a deeper it helps me to pursue a deeper understanding of the world of physics of understanding of the world of physics of understanding of the world of physics of my body and other bodies like animals my body and other bodies like animals my body and other bodies like animals and nature and really figure out what we and nature and really figure out what we and nature and really figure out what we can learn from these precedents that can learn from these precedents that can learn from these precedents that have been set by the world around us.

have been set by the world around us. have been set by the world around us. Yeah. You use one of my favorite words, Yeah. You use one of my favorite words, Yeah. You use one of my favorite words, proprioception, right? This idea of proprioception, right? This idea of proprioception, right? This idea of kinesthesia, the uh the ability to like kinesthesia, the uh the ability to like kinesthesia, the uh the ability to like for example walk on a path of uneven for example walk on a path of uneven for example walk on a path of uneven stones. It just works. like we just do stones. It just works. like we just do stones. It just works. like we just do it and babies can do it within a couple it and babies can do it within a couple it and babies can do it within a couple of years of life and robots still have of years of life and robots still have of years of life and robots still have trouble with that. It's so true. It's trouble with that. It's so true. It's trouble with that. It's so true. It's like you know that um pin the tail on like you know that um pin the tail on like you know that um pin the tail on the donkey is a is a great game that I the donkey is a is a great game that I the donkey is a is a great game that I like to use to explain to people like like to use to explain to people like like to use to explain to people like why people can be so good at that. They why people can be so good at that. They why people can be so good at that. They really understand where they are in the really understand where they are in the really understand where they are in the world relative to themselves and other world relative to themselves and other world relative to themselves and other things in the environment. Yeah. So things in the environment. Yeah. So things in the environment. Yeah. So robots really do struggle with that. robots really do struggle with that. robots really do struggle with that. They struggle with interpreting what They struggle with interpreting what They struggle with interpreting what they see and understand based on the they see and understand based on the they see and understand based on the limited sensors and not all the sensors limited sensors and not all the sensors limited sensors and not all the sensors are given the same fidelity. It's like are given the same fidelity. It's like are given the same fidelity. It's like today we have these super high today we have these super high today we have these super high definition photos that our phones are definition photos that our phones are definition photos that our phones are able to take and you know some robots able to take and you know some robots able to take and you know some robots don't have the ability to process that don't have the ability to process that don't have the ability to process that large volume of data or make smart large volume of data or make smart large volume of data or make smart inferences or guesses based on that inferences or guesses based on that inferences or guesses based on that data. So they're working on ones and data. So they're working on ones and data. So they're working on ones and zeros my friend.

zeros my friend. zeros my friend. Have some empathy. I know you should Have some empathy. I know you should Have some empathy. I know you should have some empathy. But it's it's funny have some empathy. But it's it's funny have some empathy. But it's it's funny though because if you look at like though because if you look at like though because if you look at like Reddit in any of the like, you know, Reddit in any of the like, you know, Reddit in any of the like, you know, robot vacuum Reddits, people are like, robot vacuum Reddits, people are like, robot vacuum Reddits, people are like, "My robot's so dumb." Like for example, "My robot's so dumb." Like for example, "My robot's so dumb." Like for example, literally day before yesterday, one of literally day before yesterday, one of literally day before yesterday, one of my sons left the door shut to their my sons left the door shut to their my sons left the door shut to their bedroom and somehow the robot has bedroom and somehow the robot has bedroom and somehow the robot has decided that they live in a different decided that they live in a different decided that they live in a different house. So like the door was shut once house. So like the door was shut once house. So like the door was shut once and now the robot just sits there and and now the robot just sits there and and now the robot just sits there and goes computer says no. Like I can't I goes computer says no. Like I can't I goes computer says no. Like I can't I can't get over there. And I walked it. can't get over there. And I walked it. can't get over there. And I walked it. It was like like taking taking a dog It was like like taking taking a dog It was like like taking taking a dog that didn't want to like go down the that didn't want to like go down the that didn't want to like go down the stairs and I was like you can go you can stairs and I was like you can go you can stairs and I was like you can go you can the door is open. The robot said no it's the door is open. The robot said no it's the door is open. The robot said no it's not door is shut. There's just too much not door is shut. There's just too much not door is shut. There's just too much risk of it violating its understanding risk of it violating its understanding risk of it violating its understanding of reality. You can think about it as of reality. You can think about it as of reality. You can think about it as like a irrational fear right but it's like a irrational fear right but it's like a irrational fear right but it's only acting on the information that only acting on the information that only acting on the information that exists in its hard drives. We as humans exists in its hard drives. We as humans exists in its hard drives. We as humans we can accept variance and change like we can accept variance and change like we can accept variance and change like pretty quickly when it comes to some pretty quickly when it comes to some pretty quickly when it comes to some things but just robots aren't always things but just robots aren't always things but just robots aren't always that flexible. Uh, and I think that, you that flexible. Uh, and I think that, you that flexible. Uh, and I think that, you know, what an area that I got really know, what an area that I got really know, what an area that I got really passionate about when I was at Google passionate about when I was at Google passionate about when I was at Google was human in the loop, right? That, you was human in the loop, right? That, you was human in the loop, right? That, you know, you would never just leave your know, you would never just leave your know, you would never just leave your toddler out and say, "Hey, yeah, why toddler out and say, "Hey, yeah, why toddler out and say, "Hey, yeah, why don't you just explore the world and don't you just explore the world and don't you just explore the world and figure it out? Why don't you just put figure it out? Why don't you just put figure it out? Why don't you just put everything in your mouth and and do everything in your mouth and and do everything in your mouth and and do that?" We learn a lot that way, but that?" We learn a lot that way, but that?" We learn a lot that way, but there's a lot of coaching and mentoring there's a lot of coaching and mentoring there's a lot of coaching and mentoring that goes into human development. And I that goes into human development. And I that goes into human development. And I think robotics is in the same realm. So, think robotics is in the same realm. So, think robotics is in the same realm. So, if you went into your app that controls if you went into your app that controls if you went into your app that controls and supports your robot, you could and supports your robot, you could and supports your robot, you could probably say, "Hey, I think I got the probably say, "Hey, I think I got the probably say, "Hey, I think I got the wrong idea. refresh the map, walk around wrong idea. refresh the map, walk around wrong idea. refresh the map, walk around again and see what reality truly is. Or again and see what reality truly is. Or again and see what reality truly is. Or there's been a problem, why don't you

there's been a problem, why don't you there's been a problem, why don't you check again? If you could verbally check again? If you could verbally check again? If you could verbally communicate or nudge the robot to do the communicate or nudge the robot to do the communicate or nudge the robot to do the right thing, it would be able to learn right thing, it would be able to learn right thing, it would be able to learn easily. But just like you said, you easily. But just like you said, you easily. But just like you said, you change the environment, it goes, that's change the environment, it goes, that's change the environment, it goes, that's different. Let me look again. And then different. Let me look again. And then different. Let me look again. And then its assumptions are incorrect. Yeah. And its assumptions are incorrect. Yeah. And its assumptions are incorrect. Yeah. And that showcases, I think, the gap between that showcases, I think, the gap between that showcases, I think, the gap between the hardware, which might be ready, and the hardware, which might be ready, and the hardware, which might be ready, and the software, which is way farther away the software, which is way farther away the software, which is way farther away than we think. Yeah, as you said, than we think. Yeah, as you said, than we think. Yeah, as you said, there's sensors that it has that we there's sensors that it has that we there's sensors that it has that we might not be using fully. Yeah, might not be using fully. Yeah, might not be using fully. Yeah, absolutely. And there are sensors that absolutely. And there are sensors that absolutely. And there are sensors that it could use that we don't have a it could use that we don't have a it could use that we don't have a digitized version of it like smell. digitized version of it like smell. digitized version of it like smell. Smell is still something an Smell is still something an Smell is still something an underutilized underutilized underutilized um sense that we're not leveraging in um sense that we're not leveraging in um sense that we're not leveraging in robotics. Touch, we might have like robotics. Touch, we might have like robotics. Touch, we might have like force, right? There are like force force, right? There are like force force, right? There are like force torque sensors like if you or bump torque sensors like if you or bump torque sensors like if you or bump sensors or things like that that can sensors or things like that that can sensors or things like that that can tell us when there's been contact. But tell us when there's been contact. But tell us when there's been contact. But what degree of contact, what temperature what degree of contact, what temperature what degree of contact, what temperature of contact, what is the texture of that of contact, what is the texture of that of contact, what is the texture of that contact? Am I is something slipping out contact? Am I is something slipping out contact? Am I is something slipping out of my hand? Do I have a decent grip on of my hand? Do I have a decent grip on of my hand? Do I have a decent grip on it? These types of things there are only it? These types of things there are only it? These types of things there are only uh early early prototypes and models of uh early early prototypes and models of uh early early prototypes and models of getting this type of feedback from from getting this type of feedback from from getting this type of feedback from from the environment for a computer. And then the environment for a computer. And then the environment for a computer. And then like once you get that feedback, you like once you get that feedback, you like once you get that feedback, you have to figure out how do I integrate have to figure out how do I integrate have to figure out how do I integrate that into all the other knowledge that I that into all the other knowledge that I that into all the other knowledge that I know. How much do I weight that input of know. How much do I weight that input of know. How much do I weight that input of how hot something is to whether or not I how hot something is to whether or not I how hot something is to whether or not I should or can pick it up.

should or can pick it up. should or can pick it up. Tell me if you think that this analogy Tell me if you think that this analogy Tell me if you think that this analogy works or this is a story that you can works or this is a story that you can works or this is a story that you can relate to because I'm going to guess relate to because I'm going to guess relate to because I'm going to guess based on your personality that when you based on your personality that when you based on your personality that when you bring your grocery bags from the back of bring your grocery bags from the back of bring your grocery bags from the back of the car to the house, you are like, I am the car to the house, you are like, I am the car to the house, you are like, I am not doing this in two Yeah. one trip. I not doing this in two Yeah. one trip. I not doing this in two Yeah. one trip. I am not doing one trip. So then it's am not doing one trip. So then it's am not doing one trip. So then it's like, okay, I've got this many knees and like, okay, I've got this many knees and like, okay, I've got this many knees and I've got 10 fingers and I'm going to I've got 10 fingers and I'm going to I've got 10 fingers and I'm going to like and then the ability to hold all of like and then the ability to hold all of like and then the ability to hold all of these things and not have them slip. these things and not have them slip. these things and not have them slip. That's that is I always think to myself, That's that is I always think to myself, That's that is I always think to myself, what an interesting robotics program what an interesting robotics program what an interesting robotics program problem. Yeah. Yeah. The robot would problem. Yeah. Yeah. The robot would problem. Yeah. Yeah. The robot would totally get like just the milk and go totally get like just the milk and go totally get like just the milk and go and then just the chips and then go. But and then just the chips and then go. But and then just the chips and then go. But I'm like I'll be damned if I'm going to I'm like I'll be damned if I'm going to I'm like I'll be damned if I'm going to go and make more than one trip. But I'm go and make more than one trip. But I'm go and make more than one trip. But I'm like, it would be impossible to imagine like, it would be impossible to imagine like, it would be impossible to imagine what kind of algorithm would be involved what kind of algorithm would be involved what kind of algorithm would be involved to go and get all of those things on to go and get all of those things on to go and get all of those things on just two hands. And I'm going to tell just two hands. And I'm going to tell just two hands. And I'm going to tell you, I'm going to put my big product you, I'm going to put my big product you, I'm going to put my big product manager hat on and and also my manager hat on and and also my manager hat on and and also my accessibility hat. So when I think about accessibility hat. So when I think about accessibility hat. So when I think about what it human can do, I don't always what it human can do, I don't always what it human can do, I don't always think that is the best way. Honestly, we think that is the best way. Honestly, we think that is the best way. Honestly, we have to take our little narcissistic have to take our little narcissistic have to take our little narcissistic hats off and and really think about is hats off and and really think about is hats off and and really think about is there another way that that task could there another way that that task could there another way that that task could have been done, right? Because when you have been done, right? Because when you have been done, right? Because when you were at the grocery store, you could were at the grocery store, you could were at the grocery store, you could have put all the groceries in a cart and have put all the groceries in a cart and have put all the groceries in a cart and that cart could have been really easy that cart could have been really easy that cart could have been really easy for a forklift or a two-hand robot to for a forklift or a two-hand robot to for a forklift or a two-hand robot to pick up that entire cart rather than you pick up that entire cart rather than you pick up that entire cart rather than you having the expectation that it has to having the expectation that it has to having the expectation that it has to weasel its um arms and endectors through weasel its um arms and endectors through weasel its um arms and endectors through all those tiny little paper bag loops all those tiny little paper bag loops all those tiny little paper bag loops and all that tension, right? So, there and all that tension, right? So, there and all that tension, right? So, there are ways that we can adapt to wanting to are ways that we can adapt to wanting to are ways that we can adapt to wanting to integrate AI and robotics into our integrate AI and robotics into our integrate AI and robotics into our lives. And so, I really love what

lives. And so, I really love what lives. And so, I really love what happened. I think it's the 35th happened. I think it's the 35th happened. I think it's the 35th anniversary of the um kind of ADA laws anniversary of the um kind of ADA laws anniversary of the um kind of ADA laws in the US. And so all these things like in the US. And so all these things like in the US. And so all these things like curb cuts of uh alternative feedbacks of curb cuts of uh alternative feedbacks of curb cuts of uh alternative feedbacks of like lights for our fire alarms. All like lights for our fire alarms. All like lights for our fire alarms. All these different things are actually these different things are actually these different things are actually really beneficial in robots being able really beneficial in robots being able really beneficial in robots being able to not have to fit our expectations of to not have to fit our expectations of to not have to fit our expectations of them, but for us to make adjustments in them, but for us to make adjustments in them, but for us to make adjustments in our world so that they can help us. our world so that they can help us. our world so that they can help us. That's a really that's a good reminder That's a really that's a good reminder That's a really that's a good reminder because sometimes I'll be watching a because sometimes I'll be watching a because sometimes I'll be watching a movie or I'll be looking in the mirror movie or I'll be looking in the mirror movie or I'll be looking in the mirror and I'll just go man some funny looking and I'll just go man some funny looking and I'll just go man some funny looking people. You know what I mean? Like what people. You know what I mean? Like what people. You know what I mean? Like what a what a weird decision it was to have a what a weird decision it was to have a what a weird decision it was to have the thumbs oriented this way. No, the thumbs oriented this way. No, the thumbs oriented this way. No, really. I mean, even in school when I really. I mean, even in school when I really. I mean, even in school when I So, I'm um I left hand when I write, but So, I'm um I left hand when I write, but So, I'm um I left hand when I write, but I'm right-hand dominant for almost every I'm right-hand dominant for almost every I'm right-hand dominant for almost every other activity. Same. And yeah, and so other activity. Same. And yeah, and so other activity. Same. And yeah, and so like even living in a world where you're like even living in a world where you're like even living in a world where you're like, "Wow, 95% of scissors weren't made like, "Wow, 95% of scissors weren't made like, "Wow, 95% of scissors weren't made for me or like doors open in an awkward for me or like doors open in an awkward for me or like doors open in an awkward direction or like I can eat and brush my direction or like I can eat and brush my direction or like I can eat and brush my teeth with different." It's just a very teeth with different." It's just a very teeth with different." It's just a very strange world. But these assumptions strange world. But these assumptions strange world. But these assumptions that we make based on how we think that we make based on how we think that we make based on how we think people are supposed to be, we put these people are supposed to be, we put these people are supposed to be, we put these expectations on devices that are a tenth expectations on devices that are a tenth expectations on devices that are a tenth or 1% as intelligent or dynamic and or 1% as intelligent or dynamic and or 1% as intelligent or dynamic and flexible as we are, and then we call flexible as we are, and then we call flexible as we are, and then we call them stupid. though. M. Yeah. So, we them stupid. though. M. Yeah. So, we them stupid. though. M. Yeah. So, we have this funny little disc that runs have this funny little disc that runs have this funny little disc that runs around the house in vacuums. We don't around the house in vacuums. We don't around the house in vacuums. We don't have really good I would think it's a have really good I would think it's a have really good I would think it's a fair statement uh commercially available fair statement uh commercially available fair statement uh commercially available uh close folders, but I've seen some uh close folders, but I've seen some uh close folders, but I've seen some nonhumanoid robots uh like Hello Robot nonhumanoid robots uh like Hello Robot nonhumanoid robots uh like Hello Robot has a really cool open- source robot

has a really cool open- source robot has a really cool open- source robot that's effectively a Roomba with a that's effectively a Roomba with a that's effectively a Roomba with a really long stick and then a long arm. really long stick and then a long arm. really long stick and then a long arm. They call it a manipulator. Mhm. Do you They call it a manipulator. Mhm. Do you They call it a manipulator. Mhm. Do you think that we're going to see what are think that we're going to see what are think that we're going to see what are we going to see first? A bunch of little we going to see first? A bunch of little we going to see first? A bunch of little tiny Roomba like individual devices or tiny Roomba like individual devices or tiny Roomba like individual devices or something in the middle that's a something in the middle that's a something in the middle that's a non-humanoid robot or are we going to non-humanoid robot or are we going to non-humanoid robot or are we going to see one of these like the billionaire see one of these like the billionaire see one of these like the billionaire walking around robots in a suit by robot walking around robots in a suit by robot walking around robots in a suit by robot style? That's a great question. I mean, style? That's a great question. I mean, style? That's a great question. I mean, when I was growing up, the movie that when I was growing up, the movie that when I was growing up, the movie that really stuck out to me was Bsentennial really stuck out to me was Bsentennial really stuck out to me was Bsentennial Man with Robin Williams. This just like Man with Robin Williams. This just like Man with Robin Williams. This just like whole helper robot. I'm telling you, my whole helper robot. I'm telling you, my whole helper robot. I'm telling you, my career wouldn't be where it was if I career wouldn't be where it was if I career wouldn't be where it was if I didn't have such a lofty vision as didn't have such a lofty vision as didn't have such a lofty vision as something to aspire to over the next, something to aspire to over the next, something to aspire to over the next, you know, 50 to 80 years of my life. So, you know, 50 to 80 years of my life. So, you know, 50 to 80 years of my life. So, like, yes, I want to say I want to say like, yes, I want to say I want to say like, yes, I want to say I want to say yes, Scott, that's what we're going to yes, Scott, that's what we're going to yes, Scott, that's what we're going to get and it's going to be here in 24 get and it's going to be here in 24 get and it's going to be here in 24 months. But I just I can't say that months. But I just I can't say that months. But I just I can't say that that's true, right? I think that we have that's true, right? I think that we have that's true, right? I think that we have so much to learn incrementally and a lot so much to learn incrementally and a lot so much to learn incrementally and a lot of what you see on these humanoid robots of what you see on these humanoid robots of what you see on these humanoid robots is a lot of demos and you're not seeing is a lot of demos and you're not seeing is a lot of demos and you're not seeing a caveat of like how much was this video a caveat of like how much was this video a caveat of like how much was this video sped up under what conditions was this sped up under what conditions was this sped up under what conditions was this demo accomplished and there's not a lot demo accomplished and there's not a lot demo accomplished and there's not a lot of transparency about you know is this of transparency about you know is this of transparency about you know is this robot teley operated or operated by robot teley operated or operated by robot teley operated or operated by someone in a computer far away um or is someone in a computer far away um or is someone in a computer far away um or is this a fully autonomous being these this a fully autonomous being these this a fully autonomous being these types of things aren't exposed so it's types of things aren't exposed so it's types of things aren't exposed so it's really hard to judge how far that really hard to judge how far that really hard to judge how far that technology is and when I see that lack technology is and when I see that lack technology is and when I see that lack transparency. I always just have to transparency. I always just have to transparency. I always just have to assume this isn't what I this isn't what assume this isn't what I this isn't what assume this isn't what I this isn't what I think that it is. So I really think I think that it is. So I really think I think that it is. So I really think it's much more promising the type of it's much more promising the type of it's much more promising the type of work that Hello Robot and others are work that Hello Robot and others are work that Hello Robot and others are doing to find a robot, pick a very

doing to find a robot, pick a very doing to find a robot, pick a very precise domain and get super effective precise domain and get super effective precise domain and get super effective at doing that and then relying on at doing that and then relying on at doing that and then relying on something that we call transfer something that we call transfer something that we call transfer learning, right? The ability to take learning, right? The ability to take learning, right? The ability to take some of the skill sets and some of the some of the skill sets and some of the some of the skill sets and some of the tips and tricks that you've learned from tips and tricks that you've learned from tips and tricks that you've learned from one task and apply it to another. So, one task and apply it to another. So, one task and apply it to another. So, for example, I was thinking about, hey, for example, I was thinking about, hey, for example, I was thinking about, hey, what if we had a robot that could what if we had a robot that could what if we had a robot that could actually like move your vacuum around, actually like move your vacuum around, actually like move your vacuum around, right? Instead of a Ruba, move your right? Instead of a Ruba, move your right? Instead of a Ruba, move your vacuum around and learn how to navigate vacuum around and learn how to navigate vacuum around and learn how to navigate it across what is a horizontal surface. it across what is a horizontal surface. it across what is a horizontal surface. And then we take that learning and we And then we take that learning and we And then we take that learning and we say, "Okay, robot, now paint my wall." say, "Okay, robot, now paint my wall." say, "Okay, robot, now paint my wall." Because it's a very similar motion to Because it's a very similar motion to Because it's a very similar motion to vacuuming just on a vertical surface. vacuuming just on a vertical surface. vacuuming just on a vertical surface. And so, I really see, you know, skills And so, I really see, you know, skills And so, I really see, you know, skills being transferred to things like that. being transferred to things like that. being transferred to things like that. But I'm not saying that we don't need to But I'm not saying that we don't need to But I'm not saying that we don't need to work on um I'll say some like unifying work on um I'll say some like unifying work on um I'll say some like unifying infrastructure, right? some like master infrastructure, right? some like master infrastructure, right? some like master brain that can, you know, understand brain that can, you know, understand brain that can, you know, understand which skill do I need to pull out of my which skill do I need to pull out of my which skill do I need to pull out of my tool box in the way that our brains do tool box in the way that our brains do tool box in the way that our brains do today. Um, but yeah, it is it's a lot of today. Um, but yeah, it is it's a lot of today. Um, but yeah, it is it's a lot of work. So, become a STEM person and join work. So, become a STEM person and join work. So, become a STEM person and join us in the fight to make smarter robots us in the fight to make smarter robots us in the fight to make smarter robots that help people. that help people. that help people. One of the things that I said recently One of the things that I said recently One of the things that I said recently about uh large language models that was about uh large language models that was about uh large language models that was that if you are a curious person then it that if you are a curious person then it that if you are a curious person then it will be like putting on an Iron Man suit will be like putting on an Iron Man suit will be like putting on an Iron Man suit and then you'll just be running around and then you'll just be running around and then you'll just be running around and your brain is going to but if you're and your brain is going to but if you're and your brain is going to but if you're incurious you don't ask the kind of incurious you don't ask the kind of incurious you don't ask the kind of questions that you're asking then it questions that you're asking then it questions that you're asking then it could end up making you less smart could end up making you less smart could end up making you less smart because you're just going to depend on because you're just going to depend on because you're just going to depend on it too much. I've heard a lot of people it too much. I've heard a lot of people it too much. I've heard a lot of people thinking that VLMs, very large language thinking that VLMs, very large language thinking that VLMs, very large language models, are going to be the kick in the models, are going to be the kick in the models, are going to be the kick in the pants that robotics need, but but they pants that robotics need, but but they pants that robotics need, but but they don't think about the the small models, don't think about the the small models, don't think about the the small models, the small vision models and things like the small vision models and things like the small vision models and things like that. People are saying, why don't you that. People are saying, why don't you that. People are saying, why don't you just hook chat GPT up to the robot?

just hook chat GPT up to the robot? just hook chat GPT up to the robot? Yeah. Yeah. No, that's a great question Yeah. Yeah. No, that's a great question Yeah. Yeah. No, that's a great question and I think it will definitely help, but and I think it will definitely help, but and I think it will definitely help, but I just don't think it's the end of it. I just don't think it's the end of it. I just don't think it's the end of it. Right. So to your point, if it ca if it Right. So to your point, if it ca if it Right. So to your point, if it ca if it came to um having a conversation with came to um having a conversation with came to um having a conversation with the robot, like strictly dialogue with the robot, like strictly dialogue with the robot, like strictly dialogue with no like embodied action, then like yeah, no like embodied action, then like yeah, no like embodied action, then like yeah, let's totally get chatbt into every let's totally get chatbt into every let's totally get chatbt into every robot. Like I wish my Google Home or my robot. Like I wish my Google Home or my robot. Like I wish my Google Home or my Alexa had, you know, the capabilities to Alexa had, you know, the capabilities to Alexa had, you know, the capabilities to level up information for me in the same level up information for me in the same level up information for me in the same way that Chatbtd does. But like I way that Chatbtd does. But like I way that Chatbtd does. But like I mentioned, it's that gap of turning mentioned, it's that gap of turning mentioned, it's that gap of turning words into actions. Humans have this words into actions. Humans have this words into actions. Humans have this same challenge. Okay, you've told me same challenge. Okay, you've told me same challenge. Okay, you've told me that you want me to make you a cup of that you want me to make you a cup of that you want me to make you a cup of mint tea and you want me to put it on mint tea and you want me to put it on mint tea and you want me to put it on your desk, but now I have to figure out your desk, but now I have to figure out your desk, but now I have to figure out how do I break that down into smaller how do I break that down into smaller how do I break that down into smaller tasks? How do I physically achieve those tasks? How do I physically achieve those tasks? How do I physically achieve those tasks and um I'm reading this book uh tasks and um I'm reading this book uh tasks and um I'm reading this book uh what is the name of it? It's called what is the name of it? It's called what is the name of it? It's called Living with Robots. Um and in this book, Living with Robots. Um and in this book, Living with Robots. Um and in this book, it's kind of saying that, you know, a it's kind of saying that, you know, a it's kind of saying that, you know, a lot of what humans do is not just lot of what humans do is not just lot of what humans do is not just planning, but replanning. What happens planning, but replanning. What happens planning, but replanning. What happens if you're out of mint tea? What happens if you're out of mint tea? What happens if you're out of mint tea? What happens if I don't know how to put the faucet if I don't know how to put the faucet if I don't know how to put the faucet in? What happens if you know in my mind in? What happens if you know in my mind in? What happens if you know in my mind my timer is that the you know kettle my timer is that the you know kettle my timer is that the you know kettle goes off in 3 minutes and it takes 3 goes off in 3 minutes and it takes 3 goes off in 3 minutes and it takes 3 minutes and 10 seconds like all of the minutes and 10 seconds like all of the minutes and 10 seconds like all of the all of the the changes and and issues all of the the changes and and issues all of the the changes and and issues that come up during that plan executing that come up during that plan executing that come up during that plan executing is quite challenging and so I just don't is quite challenging and so I just don't is quite challenging and so I just don't think that those models are fully ready think that those models are fully ready think that those models are fully ready for that type of work but people are for that type of work but people are for that type of work but people are working on it. I've seen some really working on it. I've seen some really working on it. I've seen some really interesting um diagrams where they're interesting um diagrams where they're interesting um diagrams where they're talking about again model a little bit talking about again model a little bit talking about again model a little bit egotistical here. They're modeling the egotistical here. They're modeling the egotistical here. They're modeling the human brain where like okay this part of human brain where like okay this part of human brain where like okay this part of the brain would be that model and this

the brain would be that model and this the brain would be that model and this part of the brain would be that model. part of the brain would be that model. part of the brain would be that model. So then rather than some kind of use a So then rather than some kind of use a So then rather than some kind of use a model as a superbrain it's like this is model as a superbrain it's like this is model as a superbrain it's like this is in charge of just the touch of the hands in charge of just the touch of the hands in charge of just the touch of the hands and this model. So like a mixture of and this model. So like a mixture of and this model. So like a mixture of experts. experts. experts. Yeah, I think that's a great way to Yeah, I think that's a great way to Yeah, I think that's a great way to work. I think it also just gives you the work. I think it also just gives you the work. I think it also just gives you the opportunity to evaluate again product opportunity to evaluate again product opportunity to evaluate again product manager hat evaluate what success manager hat evaluate what success manager hat evaluate what success metrics look like for that skill and metrics look like for that skill and metrics look like for that skill and then really figuring out how those met then really figuring out how those met then really figuring out how those met metrics integrate into the success of a metrics integrate into the success of a metrics integrate into the success of a task right if you can't see if you can't task right if you can't see if you can't task right if you can't see if you can't feel if you can't do those things feel if you can't do those things feel if you can't do those things effectively then the risk of or the effectively then the risk of or the effectively then the risk of or the potential of that task being potential of that task being potential of that task being accomplished is very very low it also accomplished is very very low it also accomplished is very very low it also lets you know where are the problems lets you know where are the problems lets you know where are the problems like what system might be at fault if like what system might be at fault if like what system might be at fault if something fails right if I misgraphing something fails right if I misgraphing something fails right if I misgraphing something is because I didn't see it or something is because I didn't see it or something is because I didn't see it or I didn't reach far far enough or I didn't reach far far enough or I didn't reach far far enough or whatever it happens to be. So, it makes whatever it happens to be. So, it makes whatever it happens to be. So, it makes the experience a little bit more I the experience a little bit more I the experience a little bit more I forgot the word for it. Uh less of a forgot the word for it. Uh less of a forgot the word for it. Uh less of a black box. I'll say eas easily black box. I'll say eas easily black box. I'll say eas easily auditable. Yes. And that is something auditable. Yes. And that is something auditable. Yes. And that is something when we're using machine learning that when we're using machine learning that when we're using machine learning that it's very very tough to have, right?

it's very very tough to have, right? it's very very tough to have, right? It's often this black box that we're It's often this black box that we're It's often this black box that we're like, I'm going to give you inputs, like, I'm going to give you inputs, like, I'm going to give you inputs, you're going to give me outputs. I don't you're going to give me outputs. I don't you're going to give me outputs. I don't care where they are as long as they're care where they are as long as they're care where they are as long as they're the ones that I was expecting. So yeah, the ones that I was expecting. So yeah, the ones that I was expecting. So yeah, I think with a collection of models, I think with a collection of models, I think with a collection of models, it's a little bit easier to interpret, it's a little bit easier to interpret, it's a little bit easier to interpret, but you still need that central but you still need that central but you still need that central decision-m algorithm in the decision-m algorithm in the decision-m algorithm in the end. Have you seen uh you remember in end. Have you seen uh you remember in end. Have you seen uh you remember in the movie Interstellar, there was TARS, the movie Interstellar, there was TARS, the movie Interstellar, there was TARS, which is the giant flat robot with the which is the giant flat robot with the which is the giant flat robot with the it looks like a slab, like a monolith, it looks like a slab, like a monolith, it looks like a slab, like a monolith, and it walks. Someone made a thing and it walks. Someone made a thing and it walks. Someone made a thing called GP TARS where they made a little called GP TARS where they made a little called GP TARS where they made a little tiny TARS uh that walks around and it's tiny TARS uh that walks around and it's tiny TARS uh that walks around and it's plugged into chat GPT and the person is plugged into chat GPT and the person is plugged into chat GPT and the person is Oh, I saw Johnny 5 on Reddit actually. Oh, I saw Johnny 5 on Reddit actually. Oh, I saw Johnny 5 on Reddit actually. See you kind of stuff. I had a young See you kind of stuff. I had a young See you kind of stuff. I had a young person on who has a robot that she made person on who has a robot that she made person on who has a robot that she made that is open source that helps teach that is open source that helps teach that is open source that helps teach indigenous languages. We're seeing more indigenous languages. We're seeing more indigenous languages. We're seeing more people put robots on their shoulder like people put robots on their shoulder like people put robots on their shoulder like a parrot. You know, that's very cool. a parrot. You know, that's very cool. a parrot. You know, that's very cool. That's brings me to the question around That's brings me to the question around That's brings me to the question around augmentation versus automation because augmentation versus automation because augmentation versus automation because there are things you might want to there are things you might want to there are things you might want to automate like the company that you work automate like the company that you work automate like the company that you work at Escape has automatic massage at Escape has automatic massage at Escape has automatic massage platforms and then there's personal platforms and then there's personal platforms and then there's personal augmentation like uh I guess an augmentation like uh I guess an augmentation like uh I guess an exoskeletons are really having a moment exoskeletons are really having a moment exoskeletons are really having a moment right now. Yeah. Oh my goodness. Yes.

right now. Yeah. Oh my goodness. Yes. right now. Yeah. Oh my goodness. Yes. Yeah. Yeah. And I'm I'm a big proponent Yeah. Yeah. And I'm I'm a big proponent Yeah. Yeah. And I'm I'm a big proponent of augmentation where possible. I think of augmentation where possible. I think of augmentation where possible. I think automation takes a a depth of task automation takes a a depth of task automation takes a a depth of task analysis that most companies are not analysis that most companies are not analysis that most companies are not willing to do. um you know just fully willing to do. um you know just fully willing to do. um you know just fully understanding every single thing that understanding every single thing that understanding every single thing that goes into that all the intricacies and goes into that all the intricacies and goes into that all the intricacies and dependencies it's really tough but to dependencies it's really tough but to dependencies it's really tough but to give someone a superpower to say hey give someone a superpower to say hey give someone a superpower to say hey what is the job part of your job that what is the job part of your job that what is the job part of your job that you hate the most or what's the piece of you hate the most or what's the piece of you hate the most or what's the piece of it that is taking up the most time that it that is taking up the most time that it that is taking up the most time that would might be the most valuable to get would might be the most valuable to get would might be the most valuable to get rid of and really helping them do that rid of and really helping them do that rid of and really helping them do that right like one of my favorite right like one of my favorite right like one of my favorite augmentation solutions is reclaim right augmentation solutions is reclaim right augmentation solutions is reclaim right that will just like shuffle your that will just like shuffle your that will just like shuffle your calendar around so that you have um a calendar around so that you have um a calendar around so that you have um a break for lunch or um that you're break for lunch or um that you're break for lunch or um that you're one-on-one with your mentee doesn't get, one-on-one with your mentee doesn't get, one-on-one with your mentee doesn't get, you know, too far off in the week. So, you know, too far off in the week. So, you know, too far off in the week. So, really taking something off your plate really taking something off your plate really taking something off your plate that you don't have to worry about. Can that you don't have to worry about. Can that you don't have to worry about. Can you override it? Of course. Can you tell you override it? Of course. Can you tell you override it? Of course. Can you tell it to ignore certain meetings? it to ignore certain meetings? it to ignore certain meetings? Absolutely. You remain in control, but Absolutely. You remain in control, but Absolutely. You remain in control, but the goal is that it's focused on the goal is that it's focused on the goal is that it's focused on achieving a task that you no longer achieving a task that you no longer achieving a task that you no longer desire to do. Yeah, we call that uh toil desire to do. Yeah, we call that uh toil desire to do. Yeah, we call that uh toil at work. If it focuses on removing toil, at work. If it focuses on removing toil, at work. If it focuses on removing toil, like you just mentioned, reclaim, like you just mentioned, reclaim, like you just mentioned, reclaim, reclaim.ai, AI, plug it into your reclaim.ai, AI, plug it into your reclaim.ai, AI, plug it into your Outlook or your your Google, and it it Outlook or your your Google, and it it Outlook or your your Google, and it it it does it without training any data on it does it without training any data on it does it without training any data on your stuff. It's doing it with local your stuff. It's doing it with local your stuff. It's doing it with local models. Um, I I like the idea of it models. Um, I I like the idea of it models. Um, I I like the idea of it taking the most tedious parts of my taking the most tedious parts of my taking the most tedious parts of my life. I'm working on the boring parts of life. I'm working on the boring parts of life. I'm working on the boring parts of running a podcast. Like, one of the running a podcast. Like, one of the running a podcast. Like, one of the things that I think the people who things that I think the people who things that I think the people who listen to the show are very well known listen to the show are very well known listen to the show are very well known is that I don't do well at show notes.

is that I don't do well at show notes. is that I don't do well at show notes. I'm the worst. I will say, I'm going to I'm the worst. I will say, I'm going to I'm the worst. I will say, I'm going to go ahead and put that in the show notes. go ahead and put that in the show notes. go ahead and put that in the show notes. Like, you just mentioned a book. And I'm Like, you just mentioned a book. And I'm Like, you just mentioned a book. And I'm like, "Oh, yeah. Living with robots with like, "Oh, yeah. Living with robots with like, "Oh, yeah. Living with robots with Ruth Alet and Patricia Vargas. I will Ruth Alet and Patricia Vargas. I will Ruth Alet and Patricia Vargas. I will add it to the show notes." No one is add it to the show notes." No one is add it to the show notes." No one is ever going to I'm never going to do ever going to I'm never going to do ever going to I'm never going to do that. So, I'm working on some that. So, I'm working on some that. So, I'm working on some automations that will do the automations that will do the automations that will do the transcripts, validate those Google with transcripts, validate those Google with transcripts, validate those Google with Bing or whatever, find the book, and add Bing or whatever, find the book, and add Bing or whatever, find the book, and add show notes. Like, cuz I hate that part show notes. Like, cuz I hate that part show notes. Like, cuz I hate that part of the job. That's amazing. See, I've of the job. That's amazing. See, I've of the job. That's amazing. See, I've got a platform that I just started got a platform that I just started got a platform that I just started using. I think it's based out of the UK using. I think it's based out of the UK using. I think it's based out of the UK called Jamie, and it's a a notetaker for called Jamie, and it's a a notetaker for called Jamie, and it's a a notetaker for the background. It's a bot list platform the background. It's a bot list platform the background. It's a bot list platform that allows me to get uh notes for that allows me to get uh notes for that allows me to get uh notes for meetings that I'm in that are for my own meetings that I'm in that are for my own meetings that I'm in that are for my own personal use, but without kind of personal use, but without kind of personal use, but without kind of inviting that person, that bot person to inviting that person, that bot person to inviting that person, that bot person to the meeting, which can be very awkward the meeting, which can be very awkward the meeting, which can be very awkward and really change the way people and really change the way people and really change the way people communicate when they feel like they're communicate when they feel like they're communicate when they feel like they're being supervised. That platform will being supervised. That platform will being supervised. That platform will summarize the notes for me, assuming summarize the notes for me, assuming summarize the notes for me, assuming that all of my things that I'm recording that all of my things that I'm recording that all of my things that I'm recording are quote unquote meetings. But what are quote unquote meetings. But what are quote unquote meetings. But what you're saying is like, hey, I wish I you're saying is like, hey, I wish I you're saying is like, hey, I wish I could take that bot and actually tell it could take that bot and actually tell it could take that bot and actually tell it this isn't a meeting. This is a podcast. this isn't a meeting. This is a podcast. this isn't a meeting. This is a podcast. These are show notes. And so when I These are show notes. And so when I These are show notes. And so when I reference materials, put it in this kind reference materials, put it in this kind reference materials, put it in this kind of format or even, hey, here's a of format or even, hey, here's a of format or even, hey, here's a predefined, you know, word template and predefined, you know, word template and predefined, you know, word template and I want you to callull my notes into this I want you to callull my notes into this I want you to callull my notes into this format because that's how I like my show format because that's how I like my show format because that's how I like my show notes um styled. And that is like the notes um styled. And that is like the notes um styled. And that is like the refinement that we get to do with these refinement that we get to do with these refinement that we get to do with these LLMs. That's what I love about these LLMs. That's what I love about these LLMs. That's what I love about these technologies recently is there's so much technologies recently is there's so much technologies recently is there's so much more personalization that we can put in more personalization that we can put in more personalization that we can put in there versus um some of the older things there versus um some of the older things there versus um some of the older things that we were doing even like um image that we were doing even like um image that we were doing even like um image classification type of tools in the past classification type of tools in the past classification type of tools in the past where they're like I recognize these where they're like I recognize these where they're like I recognize these things and these things only and to add things and these things only and to add things and these things only and to add anything to these things it requires a

anything to these things it requires a anything to these things it requires a whole bunch of technical engineering whole bunch of technical engineering whole bunch of technical engineering work to get that boosted. So I really u work to get that boosted. So I really u work to get that boosted. So I really u I really appreciate that piece of it. I really appreciate that piece of it. I really appreciate that piece of it. Yeah, it feels like this I we're hearing Yeah, it feels like this I we're hearing Yeah, it feels like this I we're hearing this term agentic a lot and we're going this term agentic a lot and we're going this term agentic a lot and we're going to talk about it at all the everyone's to talk about it at all the everyone's to talk about it at all the everyone's going to be talking about agentic. Uh, going to be talking about agentic. Uh, going to be talking about agentic. Uh, and it's just like in the old days I and it's just like in the old days I and it's just like in the old days I would have just wrote a like a bash would have just wrote a like a bash would have just wrote a like a bash script and ran a crown a cron job. And I script and ran a crown a cron job. And I script and ran a crown a cron job. And I know it's me going against what I know it's me going against what I know it's me going against what I usually say, which is don't say just usually say, which is don't say just usually say, which is don't say just because it minimizes work, but little because it minimizes work, but little because it minimizes work, but little tiny augmentation tasks that reduce toil tiny augmentation tasks that reduce toil tiny augmentation tasks that reduce toil that always has a human in the loop to that always has a human in the loop to that always has a human in the loop to get the tedium and the gross parts of my get the tedium and the gross parts of my get the tedium and the gross parts of my job like weekly reports and newsletters job like weekly reports and newsletters job like weekly reports and newsletters and stuff like that. No, that makes and stuff like that. No, that makes and stuff like that. No, that makes sense. uh what I remember from school sense. uh what I remember from school sense. uh what I remember from school are the 3Ds of robotics and it was are the 3Ds of robotics and it was are the 3Ds of robotics and it was really kind of a guiding light of the really kind of a guiding light of the really kind of a guiding light of the types of things we should be attempting types of things we should be attempting types of things we should be attempting to uh create solutions for and that's to uh create solutions for and that's to uh create solutions for and that's dull, dirty and dangerous, right? These dull, dirty and dangerous, right? These dull, dirty and dangerous, right? These are bottom of the barrel tasks. When it are bottom of the barrel tasks. When it are bottom of the barrel tasks. When it comes to dull, that's what I would say comes to dull, that's what I would say comes to dull, that's what I would say is your toil. These boring things like is your toil. These boring things like is your toil. These boring things like meeting notes and filtering emails and meeting notes and filtering emails and meeting notes and filtering emails and stuff like that. And then uh dirty, stuff like that. And then uh dirty, stuff like that. And then uh dirty, right? This is like exploring the ocean right? This is like exploring the ocean right? This is like exploring the ocean or sorting our trash or you know some of or sorting our trash or you know some of or sorting our trash or you know some of these things that are um even like these things that are um even like these things that are um even like distributing co vaccines distributing distributing co vaccines distributing distributing co vaccines distributing them not administering them into them not administering them into them not administering them into people's bodies but distributing them people's bodies but distributing them people's bodies but distributing them these dangerous things that are high these dangerous things that are high these dangerous things that are high risk for human beings um you know these risk for human beings um you know these risk for human beings um you know these are the types of things that a lot of are the types of things that a lot of are the types of things that a lot of the things that you know in the the things that you know in the the things that you know in the beginning I wanted to work on because of beginning I wanted to work on because of beginning I wanted to work on because of the limitations of technology were great the limitations of technology were great the limitations of technology were great but now that I'm working in the wellness but now that I'm working in the wellness but now that I'm working in the wellness tech space where does massage fit is it tech space where does massage fit is it tech space where does massage fit is it dull see so this is the thing so when I

dull see so this is the thing so when I dull see so this is the thing so when I started Ed researching what Escape does, started Ed researching what Escape does, started Ed researching what Escape does, I was thinking to myself, well gosh, I was thinking to myself, well gosh, I was thinking to myself, well gosh, there's some really talented people that there's some really talented people that there's some really talented people that do really talented work and I wouldn't do really talented work and I wouldn't do really talented work and I wouldn't want to take that work away from them. want to take that work away from them. want to take that work away from them. But then there are also people who might But then there are also people who might But then there are also people who might need a massage every single day or need a massage every single day or need a massage every single day or someone has lympadeema, they might need someone has lympadeema, they might need someone has lympadeema, they might need massage three times a day and it's not massage three times a day and it's not massage three times a day and it's not reasonable nor is it feasible for them reasonable nor is it feasible for them reasonable nor is it feasible for them to go and have a person do that. So I to go and have a person do that. So I to go and have a person do that. So I think two things can be true. Yeah, I think two things can be true. Yeah, I think two things can be true. Yeah, I agree. And I definitely see us more in agree. And I definitely see us more in agree. And I definitely see us more in the augmentation camp, right? Like when the augmentation camp, right? Like when the augmentation camp, right? Like when I think about kind of the physical I think about kind of the physical I think about kind of the physical stress, the demands on a human being to stress, the demands on a human being to stress, the demands on a human being to deliver highquality massage to, you deliver highquality massage to, you deliver highquality massage to, you know, 10 plus appointments per day, like know, 10 plus appointments per day, like know, 10 plus appointments per day, like their careers can be really limited by their careers can be really limited by their careers can be really limited by their their physical pressure. And so if their their physical pressure. And so if their their physical pressure. And so if we can extend that by even just I'll do we can extend that by even just I'll do we can extend that by even just I'll do I'll do the warm-up part of the massage I'll do the warm-up part of the massage I'll do the warm-up part of the massage and you do the deep sensitive work and you do the deep sensitive work and you do the deep sensitive work between the tendons, like we can between the tendons, like we can between the tendons, like we can collaborate and be a team. So collaborate and be a team. So collaborate and be a team. So collaborative robotics is something that collaborative robotics is something that collaborative robotics is something that maybe you see in picking and packing in maybe you see in picking and packing in maybe you see in picking and packing in a in a factory and things like that, but a in a factory and things like that, but a in a factory and things like that, but bringing it into the intimacy of the bringing it into the intimacy of the bringing it into the intimacy of the real world where we're like physically real world where we're like physically real world where we're like physically sharing work and a dynamic space is is sharing work and a dynamic space is is sharing work and a dynamic space is is so exciting. Yeah. The idea that a one so exciting. Yeah. The idea that a one so exciting. Yeah. The idea that a one robot arm and plus a person, that's robot arm and plus a person, that's robot arm and plus a person, that's augmentation. But then in trying to sell augmentation. But then in trying to sell augmentation. But then in trying to sell a thing which is like massuses are no a thing which is like massuses are no a thing which is like massuses are no longer needed cuz I have a massage chair longer needed cuz I have a massage chair longer needed cuz I have a massage chair that I got many many years ago and I'm that I got many many years ago and I'm that I got many many years ago and I'm very happy with. I do not feel like it very happy with. I do not feel like it very happy with. I do not feel like it replaces a massage masseuse. It's it's replaces a massage masseuse. It's it's replaces a massage masseuse. It's it's not a massage vending machine. Do you not a massage vending machine. Do you not a massage vending machine. Do you know what I mean? And even a vending know what I mean? And even a vending know what I mean? And even a vending machine is reliant on a human to restock machine is reliant on a human to restock machine is reliant on a human to restock it. So maybe that's not even a great it. So maybe that's not even a great it. So maybe that's not even a great example. But yeah, there's there's example. But yeah, there's there's example. But yeah, there's there's something that technology will never something that technology will never something that technology will never bring, right? That social intimacy,

bring, right? That social intimacy, bring, right? That social intimacy, those conversations, the relationship those conversations, the relationship those conversations, the relationship you build with your your therapist or you build with your your therapist or you build with your your therapist or your masseuse. And like we're under no your masseuse. And like we're under no your masseuse. And like we're under no mistake that we're not, you know, mistake that we're not, you know, mistake that we're not, you know, ultimately replacing that, but really ultimately replacing that, but really ultimately replacing that, but really learning from that experience, making it learning from that experience, making it learning from that experience, making it feel safe, making it feel comfortable. feel safe, making it feel comfortable. feel safe, making it feel comfortable. like these are things that we're um you like these are things that we're um you like these are things that we're um you know we're trying to proliferate in a know we're trying to proliferate in a know we're trying to proliferate in a lot of our technology. So yeah, it's lot of our technology. So yeah, it's lot of our technology. So yeah, it's step by step. All right, so my last step by step. All right, so my last step by step. All right, so my last question as we head out because you've question as we head out because you've question as we head out because you've been doing this for so long, what would been doing this for so long, what would been doing this for so long, what would you recommend if someone is listening you recommend if someone is listening you recommend if someone is listening and they are either uh an adult who is and they are either uh an adult who is and they are either uh an adult who is interested in the space or maybe they interested in the space or maybe they interested in the space or maybe they have young people in the space, do they have young people in the space, do they have young people in the space, do they go and build a Raspberry Pi tank or what go and build a Raspberry Pi tank or what go and build a Raspberry Pi tank or what what platform do they play with? Oh man, what platform do they play with? Oh man, what platform do they play with? Oh man, there are so many. There are so many. Um there are so many. There are so many. Um there are so many. There are so many. Um I really love Adafruit. It's a great I really love Adafruit. It's a great I really love Adafruit. It's a great website with a lot of um projects that website with a lot of um projects that website with a lot of um projects that you can do out of the box if you're I you can do out of the box if you're I you can do out of the box if you're I would say like maybe high school and would say like maybe high school and would say like maybe high school and college level. They have kits with, you college level. They have kits with, you college level. They have kits with, you know, step-by-step instructions. They know, step-by-step instructions. They know, step-by-step instructions. They have videos on YouTube. It's really have videos on YouTube. It's really have videos on YouTube. It's really great. And then there's Kiwi Co. if great. And then there's Kiwi Co. if great. And then there's Kiwi Co. if you've got kids like middle school and you've got kids like middle school and you've got kids like middle school and below, like even up to 5 years old. Um below, like even up to 5 years old. Um below, like even up to 5 years old. Um I'm actually in their robot coder I'm actually in their robot coder I'm actually in their robot coder starter kit that really helps you starter kit that really helps you starter kit that really helps you develop a career of robotics without any develop a career of robotics without any develop a career of robotics without any code, right? really understanding what code, right? really understanding what code, right? really understanding what is path planning um what are sensors is path planning um what are sensors is path planning um what are sensors different things like that and then I different things like that and then I different things like that and then I would say if you are like high school or would say if you are like high school or would say if you are like high school or college level and above there's college level and above there's college level and above there's platforms like Udacity and Corsera that platforms like Udacity and Corsera that platforms like Udacity and Corsera that have amazing programs that were have amazing programs that were have amazing programs that were co-developed with leading um AI and co-developed with leading um AI and co-developed with leading um AI and technology companies really helping you technology companies really helping you technology companies really helping you grow job ready skills right I actually grow job ready skills right I actually grow job ready skills right I actually teach a course on Udacity uh for AI teach a course on Udacity uh for AI teach a course on Udacity uh for AI product management that a lot of people

product management that a lot of people product management that a lot of people have taken not because they you know have taken not because they you know have taken not because they you know want to go out in the field but just to want to go out in the field but just to want to go out in the field but just to better understand the industry and better understand the industry and better understand the industry and better understand how they might better understand how they might better understand how they might influence the direction that it goes influence the direction that it goes influence the direction that it goes either as a creator or even as a either as a creator or even as a either as a creator or even as a consumer. So, those would be some of my consumer. So, those would be some of my consumer. So, those would be some of my resources. There's definitely more on my resources. There's definitely more on my resources. There's definitely more on my my website. I'm a huge proponent of STEM my website. I'm a huge proponent of STEM my website. I'm a huge proponent of STEM education in general. So, uh education in general. So, uh education in general. So, uh organizations like Black Girls Code or organizations like Black Girls Code or organizations like Black Girls Code or code.org also have a lot of great code.org also have a lot of great code.org also have a lot of great resources whether you're a student or an resources whether you're a student or an resources whether you're a student or an educator. So, cool. Thank you so much educator. So, cool. Thank you so much educator. So, cool. Thank you so much for chatting with me today, Jess. No, for chatting with me today, Jess. No, for chatting with me today, Jess. No, thanks for having me and thanks for thanks for having me and thanks for thanks for having me and thanks for letting me just wax poetic about my letting me just wax poetic about my letting me just wax poetic about my passions. Absolutely. I will hopefully passions. Absolutely. I will hopefully passions. Absolutely. I will hopefully get the show notes updated, but if I get the show notes updated, but if I get the show notes updated, but if I don't, you can always go to jasmine.com don't, you can always go to jasmine.com don't, you can always go to jasmine.com and take a look at her portfolio. Also and take a look at her portfolio. Also and take a look at her portfolio. Also take a look uh at her sometimes she has take a look uh at her sometimes she has take a look uh at her sometimes she has STEM scholarships and things as well and STEM scholarships and things as well and STEM scholarships and things as well and links to all the things that we've been links to all the things that we've been links to all the things that we've been talking about. talking about. talking about. This has been another episode of Hansel This has been another episode of Hansel This has been another episode of Hansel Minutes and we'll see you again next Minutes and we'll see you again next Minutes and we'll see you again next week. week. week. [Music]