IoT Coffee Talk: Episode 285 - "IoT Sports Center" (The World Series Edition!)

All right, we are here. Welcome to IoT All right, we are here. Welcome to IoT Coffee Talk. Coffee Talk. Coffee Talk. >> Yeah, you only have a bottle of water. >> Yeah, you only have a bottle of water. >> Yeah, you only have a bottle of water. Do you have your coffee? Do you have your coffee? Do you have your coffee? >> I already have it. I don't have it right >> I already have it. I don't have it right >> I already have it. I don't have it right in front of me, but I had it already. in front of me, but I had it already. in front of me, but I had it already. It's weird cuz I'm in the central time It's weird cuz I'm in the central time It's weird cuz I'm in the central time zone in the US and so it's at 10:30 in zone in the US and so it's at 10:30 in zone in the US and so it's at 10:30 in the morning. So, a little bit later than the morning. So, a little bit later than the morning. So, a little bit later than it used to be when I was in Seattle. So, it used to be when I was in Seattle. So, it used to be when I was in Seattle. So, had coffee a while ago, you know, had coffee a while ago, you know, had coffee a while ago, you know, already working for the day, you know, already working for the day, you know, already working for the day, you know, doing. Do you plan and do you plan to doing. Do you plan and do you plan to doing. Do you plan and do you plan to meet next week at Embed Wall North meet next week at Embed Wall North meet next week at Embed Wall North America? America? America? >> You know, I looked I looked at the >> You know, I looked I looked at the >> You know, I looked I looked at the flights. It was going to cost me $1,000 flights. It was going to cost me $1,000 flights. It was going to cost me $1,000 to fly from Houston to LA, which sounds to fly from Houston to LA, which sounds to fly from Houston to LA, which sounds crazy. I mean, that's that's what I crazy. I mean, that's that's what I crazy. I mean, that's that's what I would expect to spend to fly to Europe would expect to spend to fly to Europe would expect to spend to fly to Europe or something, you know? or something, you know? or something, you know? >> Exactly. >> Exactly. >> Exactly. >> So, I don't think I'm going to come. I'm >> So, I don't think I'm going to come. I'm >> So, I don't think I'm going to come. I'm not very happy about it, but you know, I not very happy about it, but you know, I not very happy about it, but you know, I don't know. Like, we're So, you know, don't know. Like, we're So, you know, don't know. Like, we're So, you know, not that our audience cares. I'm in the not that our audience cares. I'm in the not that our audience cares. I'm in the middle of a bunch of stuff. My wife and middle of a bunch of stuff. My wife and middle of a bunch of stuff. My wife and I are in Houston. We just made an offer I are in Houston. We just made an offer I are in Houston. We just made an offer on a house in Houston. Um, and so going on a house in Houston. Um, and so going on a house in Houston. Um, and so going through that, already had the through that, already had the through that, already had the inspection. Everything looks okay. And inspection. Everything looks okay. And inspection. Everything looks okay. And so, yeah, so we're about to buy a house.

so, yeah, so we're about to buy a house. so, yeah, so we're about to buy a house. We're selling a house in Seattle. Um, We're selling a house in Seattle. Um, We're selling a house in Seattle. Um, >> very cool. Congratulations. >> very cool. Congratulations. >> very cool. Congratulations. >> Thanks. Yeah, it's crazy. Uh, so yeah, >> Thanks. Yeah, it's crazy. Uh, so yeah, >> Thanks. Yeah, it's crazy. Uh, so yeah, there's a lot going on. Uh, we've there's a lot going on. Uh, we've there's a lot going on. Uh, we've literally been living in an Airbnb in literally been living in an Airbnb in literally been living in an Airbnb in Houston for a while. [laughter] Houston for a while. [laughter] Houston for a while. [laughter] >> So, >> So, >> So, It's, you know, got to do what you got It's, you know, got to do what you got It's, you know, got to do what you got to do, right? Uh, and so, yeah, it's to do, right? Uh, and so, yeah, it's to do, right? Uh, and so, yeah, it's kind of kind of bizarre. No doubt about kind of kind of bizarre. No doubt about kind of kind of bizarre. No doubt about it. But yes, I'm definitely going to it. But yes, I'm definitely going to it. But yes, I'm definitely going to miss uh embedded world. That should be a miss uh embedded world. That should be a miss uh embedded world. That should be a lot of fun. Does it look like do you lot of fun. Does it look like do you lot of fun. Does it look like do you look like a lot of people are going to look like a lot of people are going to look like a lot of people are going to come to IoT Stars? come to IoT Stars? come to IoT Stars? >> Yeah, I think we will have a full room. >> Yeah, I think we will have a full room. >> Yeah, I think we will have a full room. We have 175 uh space pe people. Yeah, We have 175 uh space pe people. Yeah, We have 175 uh space pe people. Yeah, room for 175 people. So, looks like room for 175 people. So, looks like room for 175 people. So, looks like Yeah, we are going to do a sold out. Yeah, we are going to do a sold out. Yeah, we are going to do a sold out. >> Oh, good. That's great. >> Oh, good. That's great. >> Oh, good. That's great. >> That's very That's very good to hear. >> That's very That's very good to hear. >> That's very That's very good to hear. That's exciting. That's exciting. That's exciting. >> Yeah, we have a full program that it >> Yeah, we have a full program that it >> Yeah, we have a full program that it looks uh very spectacular. looks uh very spectacular. looks uh very spectacular. >> Yeah, I love it. >> Yeah, I love it. >> Yeah, I love it. >> So, we are super excited. Yeah. >> So, we are super excited. Yeah. >> So, we are super excited. Yeah. >> Yeah, that's good. Oh, >> Yeah, that's good. Oh, >> Yeah, that's good. Oh, >> hey. Our Swiss friend.

>> hey. Our Swiss friend. >> hey. Our Swiss friend. >> Our Swiss friend. You know, >> Our Swiss friend. You know, >> Our Swiss friend. You know, >> what's up, team? >> what's up, team? >> what's up, team? >> Hey. Hey. We're just sitting here >> Hey. Hey. We're just sitting here >> Hey. Hey. We're just sitting here talking about IoT Stars next week at talking about IoT Stars next week at talking about IoT Stars next week at Embedded World in beautiful Anaheim, Embedded World in beautiful Anaheim, Embedded World in beautiful Anaheim, California, California, California, >> home of the uh you know what the >> home of the uh you know what the >> home of the uh you know what the difference is between a Dodger dog and a difference is between a Dodger dog and a difference is between a Dodger dog and a hot dog at Anaheim Stadium. hot dog at Anaheim Stadium. hot dog at Anaheim Stadium. >> Oh god. What? >> Oh god. What? >> Oh god. What? >> You can buy a Dodger dog in October and >> You can buy a Dodger dog in October and >> You can buy a Dodger dog in October and November. November. November. >> Oh, ouch. Ouch. >> Oh, ouch. Ouch. >> Oh, ouch. Ouch. >> Sorry, Mark. It's a baseball It's a It's >> Sorry, Mark. It's a baseball It's a It's >> Sorry, Mark. It's a baseball It's a It's a baseball analogy. Uh, but basically a baseball analogy. Uh, but basically a baseball analogy. Uh, but basically one team is still playing, the other one one team is still playing, the other one one team is still playing, the other one is done. is done. is done. >> Yes. Have you guys Have you been >> Yes. Have you guys Have you been >> Yes. Have you guys Have you been watching the series? watching the series? watching the series? >> No, because it happens in the middle of >> No, because it happens in the middle of >> No, because it happens in the middle of the night and you know, I I I can't do the night and you know, I I I can't do the night and you know, I I I can't do it. So, I just wake up, look at look it. So, I just wake up, look at look it. So, I just wake up, look at look what's happened. But if it goes to a what's happened. But if it goes to a what's happened. But if it goes to a game seven, I've already committed that game seven, I've already committed that game seven, I've already committed that I'm just going to watch this thing live I'm just going to watch this thing live I'm just going to watch this thing live >> because it has to be done. >> because it has to be done. >> because it has to be done. >> Absolutely. the final or >> Absolutely. the final or >> Absolutely. the final or >> yeah it's the it's the world >> yeah it's the it's the world >> yeah it's the it's the world championship which I you know I always championship which I you know I always championship which I you know I always do with quotation marks being that do with quotation marks being that do with quotation marks being that they're not it's not the world cup where they're not it's not the world cup where they're not it's not the world cup where you have many countries participating you have many countries participating you have many countries participating but that's what we call it.

but that's what we call it. but that's what we call it. >> Yes. So um yeah so Toronto Blue Jays >> Yes. So um yeah so Toronto Blue Jays >> Yes. So um yeah so Toronto Blue Jays against the Los Angeles Dodgers and and against the Los Angeles Dodgers and and against the Los Angeles Dodgers and and the surprise the surprise the surprise >> to all the experts is that Toronto is >> to all the experts is that Toronto is >> to all the experts is that Toronto is taking it to them. Oh wow. taking it to them. Oh wow. taking it to them. Oh wow. >> Everybody said, "Oh, you know, cuz >> Everybody said, "Oh, you know, cuz >> Everybody said, "Oh, you know, cuz obviously I'm a Seattle Mariner fan and obviously I'm a Seattle Mariner fan and obviously I'm a Seattle Mariner fan and we were fighting out against Toronto uh we were fighting out against Toronto uh we were fighting out against Toronto uh in the championship, you know, and I in the championship, you know, and I in the championship, you know, and I remember all the expert analysts go, "It remember all the expert analysts go, "It remember all the expert analysts go, "It doesn't matter if the Mariners or the doesn't matter if the Mariners or the doesn't matter if the Mariners or the Blue Jays make it. It won't make any Blue Jays make it. It won't make any Blue Jays make it. It won't make any difference. You know, Otani and the difference. You know, Otani and the difference. You know, Otani and the Dodgers are going to destroy them." And Dodgers are going to destroy them." And Dodgers are going to destroy them." And that's not what's happened at all. You that's not what's happened at all. You that's not what's happened at all. You know, I they I think there are a lot of know, I they I think there are a lot of know, I they I think there are a lot of um um um how do I say this? If we take sports how do I say this? If we take sports how do I say this? If we take sports analysis analysis analysis before an event happens before an event happens before an event happens and then the analysts are completely and then the analysts are completely and then the analysts are completely wrong in in sports, they tend to get wrong in in sports, they tend to get wrong in in sports, they tend to get beat up, you know, like it's it's beat up, you know, like it's it's beat up, you know, like it's it's common, but never from McKenzie or BCG.

common, but never from McKenzie or BCG. common, but never from McKenzie or BCG. [laughter] >> You're right. cover like hey man like >> You're right. cover like hey man like you said all these things and it didn't you said all these things and it didn't you said all these things and it didn't pan out like why are you getting another pan out like why are you getting another pan out like why are you getting another contract contract contract >> exactly >> exactly >> exactly >> what are you doing >> what are you doing >> what are you doing >> right you know >> right you know >> right you know >> no going back to baseball I never watch >> no going back to baseball I never watch >> no going back to baseball I never watch any games sorry for that uh but uh do any games sorry for that uh but uh do any games sorry for that uh but uh do you think there is a lot of technology you think there is a lot of technology you think there is a lot of technology involved on that sport well there is involved on that sport well there is involved on that sport well there is this this movie from Brad Pit right uh this this movie from Brad Pit right uh this this movie from Brad Pit right uh >> um monster no what was the monster ball >> um monster no what was the monster ball >> um monster no what was the monster ball or or or >> no moneyball money >> no moneyball money >> no moneyball money >> that was a good >> that was a good >> that was a good And that was about data science, right? And that was about data science, right? And that was about data science, right? >> Yeah, it's statistics. >> Yeah, it's statistics. >> Yeah, it's statistics. >> Yes, 100%. >> Yes, 100%. >> Yes, 100%. >> Yeah, >> Yeah, >> Yeah, >> I I think it it's um I think it's gone >> I I think it it's um I think it's gone >> I I think it it's um I think it's gone too far. And and I have I have evidence too far. And and I have I have evidence too far. And and I have I have evidence going back at least 5 years talking to a going back at least 5 years talking to a going back at least 5 years talking to a friend about how close gambling was friend about how close gambling was friend about how close gambling was getting into professional sports. getting into professional sports. getting into professional sports. And I I'll come back to data in a And I I'll come back to data in a And I I'll come back to data in a second. But you know, if we take second. But you know, if we take second. But you know, if we take baseball, uh there's been many gambling baseball, uh there's been many gambling baseball, uh there's been many gambling scandals throughout, you know, its scandals throughout, you know, its scandals throughout, you know, its history. the the big one was the uh history. the the big one was the uh history. the the big one was the uh Robu, correct me if I get the year Robu, correct me if I get the year Robu, correct me if I get the year wrong, but it was either the 1918 or wrong, but it was either the 1918 or wrong, but it was either the 1918 or 1916 White sock scandals where basically 1916 White sock scandals where basically 1916 White sock scandals where basically uh some of the guys in the team, I think uh some of the guys in the team, I think uh some of the guys in the team, I think it was four or five of them were in it was four or five of them were in it was four or five of them were in cahoots with a with a loan charge of the cahoots with a with a loan charge of the cahoots with a with a loan charge of the gamblers and they were losing or you

gamblers and they were losing or you gamblers and they were losing or you know on purpose big scandal the sanctity know on purpose big scandal the sanctity know on purpose big scandal the sanctity of the game was of the game was of the game was >> but I about technology not gambling. >> but I about technology not gambling. >> but I about technology not gambling. >> I'm going to come back to that. >> I'm going to come back to that. >> I'm going to come back to that. >> Oh, okay. Okay. Okay. Got it. Got it. >> Oh, okay. Okay. Okay. Got it. Got it. >> Oh, okay. Okay. Okay. Got it. Got it. Got it. Got it. Got it. >> I want to give you again. I'm giving you >> I want to give you again. I'm giving you >> I want to give you again. I'm giving you context because you're not a baseball context because you're not a baseball context because you're not a baseball head. I'll make it shorter. There's big head. I'll make it shorter. There's big head. I'll make it shorter. There's big gambling scandals in the history of gambling scandals in the history of gambling scandals in the history of baseball. It was baseball. It was baseball. It was >> Yes. And it's talked about how, you >> Yes. And it's talked about how, you >> Yes. And it's talked about how, you know, it should never be allowed again. know, it should never be allowed again. know, it should never be allowed again. Now we have uh companies like FanDuel, Now we have uh companies like FanDuel, Now we have uh companies like FanDuel, like uh I mean they're sponsoring the like uh I mean they're sponsoring the like uh I mean they're sponsoring the games. Uh they're sponsoring the the TV games. Uh they're sponsoring the the TV games. Uh they're sponsoring the the TV uh the TV parts of the game. They're uh the TV parts of the game. They're uh the TV parts of the game. They're advertising at the stadium and I grew advertising at the stadium and I grew advertising at the stadium and I grew up, you know, betting, but you know, I'm up, you know, betting, but you know, I'm up, you know, betting, but you know, I'm talking about like you're betting a talking about like you're betting a talking about like you're betting a dollar a week here. So, not nothing uh dollar a week here. So, not nothing uh dollar a week here. So, not nothing uh that would be an issue, but baseball has that would be an issue, but baseball has that would be an issue, but baseball has gone from betting on who's going to win gone from betting on who's going to win gone from betting on who's going to win or how many scores are you going to get or how many scores are you going to get or how many scores are you going to get in the team to will the first pitch be a in the team to will the first pitch be a in the team to will the first pitch be a strike? Will the fir would this guy do a strike? Will the fir would this guy do a strike? Will the fir would this guy do a home run?

home run? home run? Everything everything and even in Everything everything and even in Everything everything and even in between even in in between breaks like between even in in between breaks like between even in in between breaks like you know if you if you I've been to a you know if you if you I've been to a you know if you if you I've been to a lot of games where you're betting with lot of games where you're betting with lot of games where you're betting with your friend I'll bet you a beer that your friend I'll bet you a beer that your friend I'll bet you a beer that when the catcher throws the ball to the when the catcher throws the ball to the when the catcher throws the ball to the mound is going to fall in the monat even mound is going to fall in the monat even mound is going to fall in the monat even you you can gamble on that. So now you you can gamble on that. So now you you can gamble on that. So now coming back to data, coming back to data, coming back to data, it's there's so there's there's a lot of it's there's so there's there's a lot of it's there's so there's there's a lot of data to support the gamification of data to support the gamification of data to support the gamification of professional sports. And some of that professional sports. And some of that professional sports. And some of that data is absolutely being utilized to not data is absolutely being utilized to not data is absolutely being utilized to not only not only place the bets, only not only place the bets, only not only place the bets, but to make the uh make the spread, make but to make the uh make the spread, make but to make the uh make the spread, make the odds. the odds. the odds. So anyway, so um I'm not a fan, but I So anyway, so um I'm not a fan, but I So anyway, so um I'm not a fan, but I will say I have $25 on the Dodgers will say I have $25 on the Dodgers will say I have $25 on the Dodgers winning game six and scoring under eight winning game six and scoring under eight winning game six and scoring under eight and a half runs. And that is the most and a half runs. And that is the most and a half runs. And that is the most I've bet on a game in the past eight I've bet on a game in the past eight I've bet on a game in the past eight years. So that tells you how healthy my years. So that tells you how healthy my years. So that tells you how healthy my gambling is.

gambling is. gambling is. >> He's a healthy gambler like Pete Rose. >> He's a healthy gambler like Pete Rose. >> He's a healthy gambler like Pete Rose. Yeah. Yeah. I I always wanted to to see Yeah. Yeah. I I always wanted to to see Yeah. Yeah. I I always wanted to to see how the all these gambling platforms are how the all these gambling platforms are how the all these gambling platforms are synchronized with each other. So you synchronized with each other. So you synchronized with each other. So you cannot do this bet and completely the cannot do this bet and completely the cannot do this bet and completely the opposite in another platform and make opposite in another platform and make opposite in another platform and make money money money >> with one or the other. >> with one or the other. >> with one or the other. >> Actually you you can but mathematically >> Actually you you can but mathematically >> Actually you you can but mathematically you're you you'll never be ahead. you're you you'll never be ahead. you're you you'll never be ahead. >> Yeah. But this is because they talk each >> Yeah. But this is because they talk each >> Yeah. But this is because they talk each other right? Well, again, I can give you other right? Well, again, I can give you other right? Well, again, I can give you I can give you the old school I can give you the old school I can give you the old school >> speaking that that shouldn't work 100% >> speaking that that shouldn't work 100% >> speaking that that shouldn't work 100% of the times. of the times. of the times. >> Well, the thing is that again, I'm going >> Well, the thing is that again, I'm going >> Well, the thing is that again, I'm going to give you the non-technical old school to give you the non-technical old school to give you the non-technical old school way of making the odds. Uh, say for way of making the odds. Uh, say for way of making the odds. Uh, say for example, Vegas will have a single book example, Vegas will have a single book example, Vegas will have a single book and you will have many many even illegal and you will have many many even illegal and you will have many many even illegal uh uh operations that will take the odds uh uh operations that will take the odds uh uh operations that will take the odds from Vegas. So Vegas was setting the from Vegas. So Vegas was setting the from Vegas. So Vegas was setting the standard of who's favorite, you know, standard of who's favorite, you know, standard of who's favorite, you know, who's, you know, who's the underdog. So who's, you know, who's the underdog. So who's, you know, who's the underdog. So it gets copied, meaning if you had the it gets copied, meaning if you had the it gets copied, meaning if you had the strategy of betting, I'm going to put strategy of betting, I'm going to put strategy of betting, I'm going to put money on both teams, it doesn't really money on both teams, it doesn't really money on both teams, it doesn't really matter which platform you use, you you matter which platform you use, you you matter which platform you use, you you you don't make any money.

you don't make any money. you don't make any money. Um, and I'll give you um here I'm going Um, and I'll give you um here I'm going Um, and I'll give you um here I'm going to look at yesterday's spread. to look at yesterday's spread. to look at yesterday's spread. Uh, where is this thing? Uh, where is this thing? Uh, where is this thing? >> But he doesn't play. He doesn't gamble, >> But he doesn't play. He doesn't gamble, >> But he doesn't play. He doesn't gamble, but he still but he still but he still >> No, no, but yeah, cuz I I have >> No, no, but yeah, cuz I I have >> No, no, but yeah, cuz I I have yesterday's spread. So yesterday, if I yesterday's spread. So yesterday, if I yesterday's spread. So yesterday, if I if I if I wanted to make $100 on the if I if I wanted to make $100 on the if I if I wanted to make $100 on the Dodgers to win, they're the favorite. So Dodgers to win, they're the favorite. So Dodgers to win, they're the favorite. So I'll have to wager I'll have to wager I'll have to wager 166 166 166 to get a 100 bucks. to get a 100 bucks. to get a 100 bucks. >> Oh. >> Oh. >> Oh. >> Now the Blue Jays, they're the underdog. >> Now the Blue Jays, they're the underdog. >> Now the Blue Jays, they're the underdog. So, if I put $100 on the Blue Jays, I So, if I put $100 on the Blue Jays, I So, if I put $100 on the Blue Jays, I double my money. double my money. double my money. So, it's like, okay, so if I'm gonna bet So, it's like, okay, so if I'm gonna bet So, it's like, okay, so if I'm gonna bet $200, and I'm just going to bet on both $200, and I'm just going to bet on both $200, and I'm just going to bet on both teams teams teams in this case with the odds that I played in this case with the odds that I played in this case with the odds that I played yesterday, yesterday, yesterday, uh, I will come ahead about $20. uh, I will come ahead about $20. uh, I will come ahead about $20. >> But, but you don't need to put the same >> But, but you don't need to put the same >> But, but you don't need to put the same uh amount of money for each. You know uh amount of money for each. You know uh amount of money for each. You know what I mean? No, but I could just call what I mean? No, but I could just call what I mean? No, but I could just call you and say, "Hey, Mark, you play the you and say, "Hey, Mark, you play the you and say, "Hey, Mark, you play the Blue Jays. I'm going to play the Blue Jays. I'm going to play the Blue Jays. I'm going to play the Dodgers." And we split the winnings and Dodgers." And we split the winnings and Dodgers." And we split the winnings and now we have $10, which if we were now we have $10, which if we were now we have $10, which if we were betting millions like Rob does with his betting millions like Rob does with his betting millions like Rob does with his >> millions, >> millions, >> millions, >> it might make millions.

>> it might make millions. >> it might make millions. >> Yes. Like, you know, hypothetical uh >> Yes. Like, you know, hypothetical uh >> Yes. Like, you know, hypothetical uh trade this morning for instance, like trade this morning for instance, like trade this morning for instance, like you know, 2 days ago, Amazon lays off you know, 2 days ago, Amazon lays off you know, 2 days ago, Amazon lays off what 14 or 15,000 employees. Yesterday what 14 or 15,000 employees. Yesterday what 14 or 15,000 employees. Yesterday they blew out their numbers in a giant they blew out their numbers in a giant they blew out their numbers in a giant way on cloud. This morning you might way on cloud. This morning you might way on cloud. This morning you might have a on the open buy order for Amazon have a on the open buy order for Amazon have a on the open buy order for Amazon stock speculating that it's going to go stock speculating that it's going to go stock speculating that it's going to go up because of those two factors. up because of those two factors. up because of those two factors. >> Yeah. >> Yeah. >> Yeah. >> Is that gambling? It's just information >> Is that gambling? It's just information >> Is that gambling? It's just information you know it might work, it might not, you know it might work, it might not, you know it might work, it might not, you know. Um you know. Um you know. Um >> yeah but you know this is all IoT >> yeah but you know this is all IoT >> yeah but you know this is all IoT related because people are making related because people are making related because people are making actuating so making wagers making bets. actuating so making wagers making bets. actuating so making wagers making bets. >> Yeah >> Yeah >> Yeah >> based on based on acquired data >> based on based on acquired data >> based on based on acquired data >> and >> and >> and back to baseball and and data. So you back to baseball and and data. So you back to baseball and and data. So you know things that I didn't grow up with know things that I didn't grow up with know things that I didn't grow up with that at first was really interesting. that at first was really interesting. that at first was really interesting. Um, you know, in baseball, you know, you Um, you know, in baseball, you know, you Um, you know, in baseball, you know, you have the dimensions of the ballpark. So, have the dimensions of the ballpark. So, have the dimensions of the ballpark. So, you would have a good idea of how far you would have a good idea of how far you would have a good idea of how far the ball traveled, you know, oh, 400 ft the ball traveled, you know, oh, 400 ft the ball traveled, you know, oh, 400 ft or 420, you know, whatever it is. And or 420, you know, whatever it is. And or 420, you know, whatever it is. And you know for the last few years we've you know for the last few years we've you know for the last few years we've had technology that I forget the name of had technology that I forget the name of had technology that I forget the name of the company but they started with tennis the company but they started with tennis the company but they started with tennis that was uh um measuring the accuracy of that was uh um measuring the accuracy of that was uh um measuring the accuracy of ins and outs in tennis and they were ins and outs in tennis and they were ins and outs in tennis and they were following the the trajectory of of the following the the trajectory of of the following the the trajectory of of the ball which which for tennis actually ball which which for tennis actually ball which which for tennis actually turned out to be easy because of the turned out to be easy because of the turned out to be easy because of the color of the ball. And now they've color of the ball. And now they've color of the ball. And now they've implemented that many years ago for

implemented that many years ago for implemented that many years ago for baseball. So you can see the little, you baseball. So you can see the little, you baseball. So you can see the little, you know, the little graphic that tells you know, the little graphic that tells you know, the little graphic that tells you not only how far did the ball travel, not only how far did the ball travel, not only how far did the ball travel, but velocity exit, which like we didn't but velocity exit, which like we didn't but velocity exit, which like we didn't care, but now it's like a thing cuz now care, but now it's like a thing cuz now care, but now it's like a thing cuz now you can measure how hard someone, you you can measure how hard someone, you you can measure how hard someone, you know, make contact with the ball. Uh, so know, make contact with the ball. Uh, so know, make contact with the ball. Uh, so it's it's it's super cool to see all it's it's it's super cool to see all it's it's it's super cool to see all this uh PowerBI this uh PowerBI this uh PowerBI uh going into going into baseball. Um, uh going into going into baseball. Um, uh going into going into baseball. Um, but anyway, I I'm a I'm a romantic when but anyway, I I'm a I'm a romantic when but anyway, I I'm a I'm a romantic when it comes to the game. So, love the game, it comes to the game. So, love the game, it comes to the game. So, love the game, >> you know. Can we can we profile David? >> you know. Can we can we profile David? >> you know. Can we can we profile David? Um, you know, and say that because he Um, you know, and say that because he Um, you know, and say that because he originates from a particular location originates from a particular location originates from a particular location that he would be more inclined to be a that he would be more inclined to be a that he would be more inclined to be a baseball fan. baseball fan. baseball fan. >> Dominican Republic, largest >> Dominican Republic, largest >> Dominican Republic, largest largest minority in baseball largest minority in baseball largest minority in baseball >> and the best. >> and the best. >> and the best. >> It's a world champion. No. >> It's a world champion. No. >> It's a world champion. No. >> [laughter] >> [laughter] >> [laughter] >> Well, yeah. In direct >> Well, yeah. In direct >> Well, yeah. In direct one of the Olympic champions, baseball one of the Olympic champions, baseball one of the Olympic champions, baseball Olympic champions.

Olympic champions. Olympic champions. >> I don't know. >> I don't know. >> I don't know. >> Um, well, there's um I mean there is >> Um, well, there's um I mean there is >> Um, well, there's um I mean there is >> you what? No, >> you what? No, >> you what? No, >> there is a there's a tournament that >> there is a there's a tournament that >> there is a there's a tournament that happens every couple of years sanctioned happens every couple of years sanctioned happens every couple of years sanctioned by Major League Baseball. It's called by Major League Baseball. It's called by Major League Baseball. It's called the World Baseball Classic. the World Baseball Classic. the World Baseball Classic. >> Okay. >> Okay. >> Okay. >> Uh and right now in I don't know Cuba >> Uh and right now in I don't know Cuba >> Uh and right now in I don't know Cuba because Cuba's Cuba is having more because Cuba's Cuba is having more because Cuba's Cuba is having more issues than usual. issues than usual. issues than usual. >> Okay. as of recent, but Dominican >> Okay. as of recent, but Dominican >> Okay. as of recent, but Dominican Republic, Puerto Rico, Venezuela, Republic, Puerto Rico, Venezuela, Republic, Puerto Rico, Venezuela, Kuraka, uh, and I think Colombia, uh, Kuraka, uh, and I think Colombia, uh, Kuraka, uh, and I think Colombia, uh, they play baseball now, like now the they play baseball now, like now the they play baseball now, like now the Winter League is happening right now, Winter League is happening right now, Winter League is happening right now, but that's that's a localized by country but that's that's a localized by country but that's that's a localized by country championship. But, uh, great, uh, very championship. But, uh, great, uh, very championship. But, uh, great, uh, very analog experience, analog experience, analog experience, >> like if you want to listen, if you want >> like if you want to listen, if you want >> like if you want to listen, if you want to feel like it's Vince Cully narrating to feel like it's Vince Cully narrating to feel like it's Vince Cully narrating a game from 30 years ago, you listen to a game from 30 years ago, you listen to a game from 30 years ago, you listen to Dominican baseball. There's no Dominican baseball. There's no Dominican baseball. There's no technology. We barely have two TV technology. We barely have two TV technology. We barely have two TV cameras in there. cameras in there. cameras in there. >> I love it. >> I love it. >> I love it. >> But it's great. It's >> But it's great. It's >> But it's great. It's >> Yeah. Yes. So, that's the big thing >> Yeah. Yes. So, that's the big thing >> Yeah. Yes. So, that's the big thing there, Mark. You know, the DR is a there, Mark. You know, the DR is a there, Mark. You know, the DR is a baseball machine. They just pump them baseball machine. They just pump them baseball machine. They just pump them out, you know, like literally at birth.

out, you know, like literally at birth. out, you know, like literally at birth. They're popping out. They put a ball cap They're popping out. They put a ball cap They're popping out. They put a ball cap on them, give them a mitt and a bat, and on them, give them a mitt and a bat, and on them, give them a mitt and a bat, and they're just in it. they're just in it. they're just in it. >> Well, because like IoT and developer >> Well, because like IoT and developer >> Well, because like IoT and developer relations, right? Yeah. the develop the relations, right? Yeah. the develop the relations, right? Yeah. the develop the developer community, Major League developer community, Major League developer community, Major League Baseball teams. Baseball teams. Baseball teams. >> Yep. >> Yep. >> Yep. >> Going to the community of developers, >> Going to the community of developers, >> Going to the community of developers, handing out SDKs and free sandboxes, handing out SDKs and free sandboxes, handing out SDKs and free sandboxes, >> right? >> right? >> right? >> Which will be like having minor league >> Which will be like having minor league >> Which will be like having minor league affiliation teams in the island and affiliation teams in the island and affiliation teams in the island and you're advertising your webinars about you're advertising your webinars about you're advertising your webinars about edge AI and what Quakum's doing with edge AI and what Quakum's doing with edge AI and what Quakum's doing with Arduino, which means who sponsor this Arduino, which means who sponsor this Arduino, which means who sponsor this ballpark. So, it's uh it's planting ballpark. So, it's uh it's planting ballpark. So, it's uh it's planting seeds like IoT and uh anyway, it's it's seeds like IoT and uh anyway, it's it's seeds like IoT and uh anyway, it's it's uh it's been a long tradition. Yeah, uh it's been a long tradition. Yeah, uh it's been a long tradition. Yeah, there it is. There's some here. there it is. There's some here. there it is. There's some here. >> Look at that beautiful Oh, that's a >> Look at that beautiful Oh, that's a >> Look at that beautiful Oh, that's a queue. That's a dragon wing. Wow. Wow. queue. That's a dragon wing. Wow. Wow. queue. That's a dragon wing. Wow. Wow. Wow. You're from the future. Wow. You're from the future. Wow. You're from the future. >> Nice. And uh and yeah, so now for for >> Nice. And uh and yeah, so now for for >> Nice. And uh and yeah, so now for for many years, the Dominicans have been the many years, the Dominicans have been the many years, the Dominicans have been the largest minority in the uh in the game largest minority in the uh in the game largest minority in the uh in the game of baseball. like uh like like Arduino of baseball. like uh like like Arduino of baseball. like uh like like Arduino like Qualcomm hopes Arduino is going to like Qualcomm hopes Arduino is going to like Qualcomm hopes Arduino is going to be the largest minority in the game of be the largest minority in the game of be the largest minority in the game of industrial IoT.

industrial IoT. industrial IoT. >> Okay. Going back to baseball. So >> Okay. Going back to baseball. So >> Okay. Going back to baseball. So actually in the Paris Olympic Games uh actually in the Paris Olympic Games uh actually in the Paris Olympic Games uh they the Basil was not uh they the Basil was not uh they the Basil was not uh >> included >> included >> included >> but the last one 2020 in Japan or 2021 >> but the last one 2020 in Japan or 2021 >> but the last one 2020 in Japan or 2021 in the Olympic Games in Tokyo. The gold in the Olympic Games in Tokyo. The gold in the Olympic Games in Tokyo. The gold medal was for Japan. medal was for Japan. medal was for Japan. The runners up were for United States The runners up were for United States The runners up were for United States and third place Dominican Republic. and third place Dominican Republic. and third place Dominican Republic. >> Wow, that's good. >> Wow, that's good. >> Wow, that's good. >> Nice. >> Nice. >> Nice. >> That's right. We can't forget about >> That's right. We can't forget about >> That's right. We can't forget about Japan, David. I mean, Japanese baseball. Japan, David. I mean, Japanese baseball. Japan, David. I mean, Japanese baseball. >> Yeah, >> Yeah, >> Yeah, >> the uh the J the [snorts] >> the uh the J the [snorts] >> the uh the J the [snorts] team called the Giants. I forgot which team called the Giants. I forgot which team called the Giants. I forgot which city and I'm not going to try to city and I'm not going to try to city and I'm not going to try to pronounce it, but um the pronounce it, but um the pronounce it, but um the >> it's not we're really going to talk >> it's not we're really going to talk >> it's not we're really going to talk about sports this whole thing. I'm about sports this whole thing. I'm about sports this whole thing. I'm trying to bring this into IoT so people trying to bring this into IoT so people trying to bring this into IoT so people don't don't fall asleep. don't don't fall asleep. don't don't fall asleep. >> Lots of stats, lots of data. >> Lots of stats, lots of data. >> Lots of stats, lots of data. >> Yeah. But when I think of deploying IoT >> Yeah. But when I think of deploying IoT >> Yeah. But when I think of deploying IoT on cellular versus Laura, it's almost on cellular versus Laura, it's almost on cellular versus Laura, it's almost like cultural thing. Like if you've been like cultural thing. Like if you've been like cultural thing. Like if you've been to a baseball game in the US, it's so to a baseball game in the US, it's so to a baseball game in the US, it's so different than being in a baseball game different than being in a baseball game different than being in a baseball game in Japan in terms of in Japan in terms of in Japan in terms of >> I'll give you my the the the example >> I'll give you my the the the example >> I'll give you my the the the example that was the most shocking to me. So I that was the most shocking to me. So I that was the most shocking to me. So I was a Dodger season ticket holder for was a Dodger season ticket holder for was a Dodger season ticket holder for eight years and the rivalry, the biggest eight years and the rivalry, the biggest eight years and the rivalry, the biggest one is with another West Coast team, the one is with another West Coast team, the one is with another West Coast team, the Giants. And it's nasty. It's it's uh you Giants. And it's nasty. It's it's uh you Giants. And it's nasty. It's it's uh you know people get into fights which I know people get into fights which I know people get into fights which I don't condone but it's like you're going

don't condone but it's like you're going don't condone but it's like you're going at each other but in Tokyo at each other but in Tokyo at each other but in Tokyo uh the fans respect each other in such a uh the fans respect each other in such a uh the fans respect each other in such a way that you chant for your team and I'm way that you chant for your team and I'm way that you chant for your team and I'm going to respectfully let you chant and going to respectfully let you chant and going to respectfully let you chant and when you're done when you're done when you're done it's my turn. And that was shocking to it's my turn. And that was shocking to it's my turn. And that was shocking to me. Like they were they they were in the me. Like they were they they were in the me. Like they were they they were in the same venue for the love of the same same venue for the love of the same same venue for the love of the same sport but rooting for separate teams and sport but rooting for separate teams and sport but rooting for separate teams and everyone gave each other grace. everyone gave each other grace. everyone gave each other grace. >> But in Chavis Ravine were killing each >> But in Chavis Ravine were killing each >> But in Chavis Ravine were killing each other in the bleachers just because you other in the bleachers just because you other in the bleachers just because you wearing the wrong colors. Um so yeah, wearing the wrong colors. Um so yeah, wearing the wrong colors. Um so yeah, different uh uh you know different different uh uh you know different different uh uh you know different cultures do the same thing. Baseball uh cultures do the same thing. Baseball uh cultures do the same thing. Baseball uh quite uh quite different. So it's cool. quite uh quite different. So it's cool. quite uh quite different. So it's cool. >> Wow. you know, back to profiling. Let's >> Wow. you know, back to profiling. Let's >> Wow. you know, back to profiling. Let's profile the Japanese now. You know, uh profile the Japanese now. You know, uh profile the Japanese now. You know, uh you're right, they're very friendly, you're right, they're very friendly, you're right, they're very friendly, very polite people in my experience very polite people in my experience very polite people in my experience being there. And even long before I ever being there. And even long before I ever being there. And even long before I ever went there, I remember as a kid, you went there, I remember as a kid, you went there, I remember as a kid, you know, watching music videos on MTV and know, watching music videos on MTV and know, watching music videos on MTV and some of them be live and you'd see one some of them be live and you'd see one some of them be live and you'd see one that's like a live concert of a band that's like a live concert of a band that's like a live concert of a band performing in Japan. And what did you performing in Japan. And what did you performing in Japan. And what did you notice? everyone is sitting down with notice? everyone is sitting down with notice? everyone is sitting down with their hands folded politely watching their hands folded politely watching their hands folded politely watching this concert instead of standing up this concert instead of standing up this concert instead of standing up going, you know, and I was like, "Wow, going, you know, and I was like, "Wow, going, you know, and I was like, "Wow, that's different," you know, and yet I I that's different," you know, and yet I I that's different," you know, and yet I I saw that over and over again, you know, saw that over and over again, you know, saw that over and over again, you know, in different videos, concerts and stuff in different videos, concerts and stuff in different videos, concerts and stuff like that. So there, you know, it's a like that. So there, you know, it's a like that. So there, you know, it's a [clears throat] cultural thing. I think [clears throat] cultural thing. I think [clears throat] cultural thing. I think they're more polite, maybe reserved. I they're more polite, maybe reserved. I they're more polite, maybe reserved. I don't know.

don't know. don't know. >> Oh my gosh. Speaking of Speaking of >> Oh my gosh. Speaking of Speaking of >> Oh my gosh. Speaking of Speaking of polite and reserved, here's Bill Pooh polite and reserved, here's Bill Pooh polite and reserved, here's Bill Pooh Pew in the house. What the hell is going Pew in the house. What the hell is going Pew in the house. What the hell is going on, man? on, man? on, man? >> Dude, I'm loving the gear. >> Dude, I'm loving the gear. >> Dude, I'm loving the gear. >> Oh. Oh, you like that? It's It's It's >> Oh. Oh, you like that? It's It's It's >> Oh. Oh, you like that? It's It's It's that kind of weather around here right that kind of weather around here right that kind of weather around here right about now. about now. about now. >> Yes, I'm aware since I'm down in Tahas >> Yes, I'm aware since I'm down in Tahas >> Yes, I'm aware since I'm down in Tahas with you and I can't believe how nice with you and I can't believe how nice with you and I can't believe how nice and crisp and cool it is. and crisp and cool it is. and crisp and cool it is. >> But I love I love the match, the >> But I love I love the match, the >> But I love I love the match, the coloring, the the hat. I love the orange coloring, the the hat. I love the orange coloring, the the hat. I love the orange accent. That's accent. That's accent. That's >> That's what we do, man. I mean, look, >> That's what we do, man. I mean, look, >> That's what we do, man. I mean, look, for those that don't know, Overwatch You know, it's, you know, it's I thought You know, it's, you know, it's I thought um I mean, Bill, I haven't seen you in a um I mean, Bill, I haven't seen you in a um I mean, Bill, I haven't seen you in a while. I thought that your the logo of while. I thought that your the logo of while. I thought that your the logo of the I I don't know. I Overwatch. I think the I I don't know. I Overwatch. I think the I I don't know. I Overwatch. I think it's an it's a video game like esports it's an it's a video game like esports it's an it's a video game like esports or Okay. Okay. That's all I know. I or Okay. Okay. That's all I know. I or Okay. Okay. That's all I know. I thought that was a new logo for True thought that was a new logo for True thought that was a new logo for True North. And I'm going to tell you why. North. And I'm going to tell you why. North. And I'm going to tell you why. because it looks like there's two hands because it looks like there's two hands because it looks like there's two hands like I don't know like client and like I don't know like client and like I don't know like client and consultant like coming together and consultant like coming together and consultant like coming together and they're pointing to the North Star and I they're pointing to the North Star and I they're pointing to the North Star and I thought that was your new logo. I'm thought that was your new logo. I'm thought that was your new logo. I'm serious man.

serious man. serious man. >> That that's a good idea. >> That that's a good idea. >> That that's a good idea. >> Well, don't take it from Overwatch. They >> Well, don't take it from Overwatch. They >> Well, don't take it from Overwatch. They probably have money and will sue you for probably have money and will sue you for probably have money and will sue you for >> Yeah. No, I mean that part I'm just >> Yeah. No, I mean that part I'm just >> Yeah. No, I mean that part I'm just saying that's a good idea. saying that's a good idea. saying that's a good idea. >> Wow. When I was when I was when we were >> Wow. When I was when I was when we were >> Wow. When I was when I was when we were putting all of this together, I was like putting all of this together, I was like putting all of this together, I was like I was like, you know, we need a singular I was like, you know, we need a singular I was like, you know, we need a singular logo. That would have been like to do logo. That would have been like to do logo. That would have been like to do something a play on that. Yeah, that something a play on that. Yeah, that something a play on that. Yeah, that would have been the thing right there. would have been the thing right there. would have been the thing right there. >> Oh, yeah. >> Oh, yeah. >> Oh, yeah. >> Make sure make sure make sure Stephanie >> Make sure make sure make sure Stephanie >> Make sure make sure make sure Stephanie knows it was my idea before she uh sends knows it was my idea before she uh sends knows it was my idea before she uh sends you a new logo tomorrow. you a new logo tomorrow. you a new logo tomorrow. >> Well, she'll she'll she'll see the >> Well, she'll she'll she'll see the >> Well, she'll she'll she'll see the recording and and we're we're we're recording and and we're we're we're recording and and we're we're we're talking about I mean, a bunch of stuff talking about I mean, a bunch of stuff talking about I mean, a bunch of stuff coming for 2026. I mean, coming for 2026. I mean, coming for 2026. I mean, >> we are excited about 2026 for True >> we are excited about 2026 for True >> we are excited about 2026 for True North, man. North, man. North, man. >> Yes, sir. Yes, sir. I mean, we got we >> Yes, sir. Yes, sir. I mean, we got we >> Yes, sir. Yes, sir. I mean, we got we got Oh my goodness. So, the fellas just got Oh my goodness. So, the fellas just got Oh my goodness. So, the fellas just came back from GTC 20 uh GTC DC. came back from GTC 20 uh GTC DC. came back from GTC 20 uh GTC DC. >> Yeah. >> Yeah. >> Yeah. >> Where they showcased uh the digital twin >> Where they showcased uh the digital twin >> Where they showcased uh the digital twin built on Metropolis. built on Metropolis. built on Metropolis. >> Oh, tell us more. So the first >> Oh, tell us more. So the first >> Oh, tell us more. So the first implementation of the smart city implementation of the smart city implementation of the smart city blueprint from Nvidia.

blueprint from Nvidia. blueprint from Nvidia. >> Okay. >> Okay. >> Okay. >> Wow. Wow. >> Wow. Wow. >> Wow. Wow. >> Interesting. >> Interesting. >> Interesting. >> Yeah. Yeah. So now now it now it's all >> Yeah. Yeah. So now now it now it's all >> Yeah. Yeah. So now now it now it's all it's all onward and upward from here. it's all onward and upward from here. it's all onward and upward from here. >> So are you aligning yourself with what >> So are you aligning yourself with what >> So are you aligning yourself with what Nvidia is doing? Nvidia is doing? Nvidia is doing? >> No. >> No. >> No. >> Okay. All right. Just I was curious. >> Okay. All right. Just I was curious. >> Okay. All right. Just I was curious. >> I was about to ask Bale. I was >> I was about to ask Bale. I was >> I was about to ask Bale. I was >> stick to our true north. Oh, clever. >> stick to our true north. Oh, clever. >> stick to our true north. Oh, clever. >> What what it is is I mean it's it's just >> What what it is is I mean it's it's just >> What what it is is I mean it's it's just like we've been saying all along, right? like we've been saying all along, right? like we've been saying all along, right? I mean, I get a lot of conversations I mean, I get a lot of conversations I mean, I get a lot of conversations around and I and I mean I've been kind around and I and I mean I've been kind around and I and I mean I've been kind of laying low lately just really of laying low lately just really of laying low lately just really grinding on what what we're trying to do grinding on what what we're trying to do grinding on what what we're trying to do and turn these things into, you know, and turn these things into, you know, and turn these things into, you know, recurring revenue opportunities. But, recurring revenue opportunities. But, recurring revenue opportunities. But, uh, it's almost like it's time and and uh, it's almost like it's time and and uh, it's almost like it's time and and Rob, I will enlist your help on this. Rob, I will enlist your help on this. Rob, I will enlist your help on this. We've got to break down this whole We've got to break down this whole We've got to break down this whole definition of digital twins, models, definition of digital twins, models, definition of digital twins, models, streaming data, and what it means. streaming data, and what it means. streaming data, and what it means. >> Yeah. >> Yeah. >> Yeah. >> Because I will I I can't tell you how >> Because I will I I can't tell you how >> Because I will I I can't tell you how many countless conversations I've had many countless conversations I've had many countless conversations I've had around, you know, so what model are you around, you know, so what model are you around, you know, so what model are you are you using the Purdue model and are are you using the Purdue model and are are you using the Purdue model and are you using this? And I'm like, people you using this? And I'm like, people you using this? And I'm like, people want to pop off with words and things want to pop off with words and things want to pop off with words and things that they've heard as opposed to that they've heard as opposed to that they've heard as opposed to substantive conversation around the substantive conversation around the substantive conversation around the implementation and the use of data from implementation and the use of data from implementation and the use of data from the ground up the ground up the ground up >> to deliver these insights and outcomes.

>> to deliver these insights and outcomes. >> to deliver these insights and outcomes. >> Maybe we need to >> Maybe we need to >> Maybe we need to >> maybe create >> maybe create >> maybe create >> Oh, go ahead, Dave. I'm sorry. >> Oh, go ahead, Dave. I'm sorry. >> Oh, go ahead, Dave. I'm sorry. >> No, no. When they ask you if you're >> No, no. When they ask you if you're >> No, no. When they ask you if you're going to use the Purdue model, just tell going to use the Purdue model, just tell going to use the Purdue model, just tell them no, no, no. I'm going to use ISA them no, no, no. I'm going to use ISA them no, no, no. I'm going to use ISA 95, which is the same thing, but they 95, which is the same thing, but they 95, which is the same thing, but they don't know. don't know. don't know. No, I've got a whole breakdown on No, I've got a whole breakdown on No, I've got a whole breakdown on standards and implementations and a standards and implementations and a standards and implementations and a comparison. Not a what is good, better, comparison. Not a what is good, better, comparison. Not a what is good, better, best, but because there it it it really best, but because there it it it really best, but because there it it it really that's not the conversation to have. that's not the conversation to have. that's not the conversation to have. It's not my my twin is better than It's not my my twin is better than It's not my my twin is better than yours. It's my twin is used for yours. It's my twin is used for yours. It's my twin is used for streaming data, real time insights, streaming data, real time insights, streaming data, real time insights, 100%. 100%. 100%. I don't use a model that lives in the I don't use a model that lives in the I don't use a model that lives in the cloud that gets retrained. cloud that gets retrained. cloud that gets retrained. The Purdue model is just that. It is a The Purdue model is just that. It is a The Purdue model is just that. It is a model that then is put in and used and model that then is put in and used and model that then is put in and used and it's trained and all of that stuff, but it's trained and all of that stuff, but it's trained and all of that stuff, but it's very good in specific areas that it's very good in specific areas that it's very good in specific areas that we're not that great in, we're not that great in, we're not that great in, >> dude. But you know what's I think this >> dude. But you know what's I think this >> dude. But you know what's I think this is um is um is um the Purdue model, the way you know how the Purdue model, the way you know how the Purdue model, the way you know how was born. First of all, it's a physical was born. First of all, it's a physical was born. First of all, it's a physical representation of a plant floor.

representation of a plant floor. representation of a plant floor. >> Yes. >> Yes. >> Yes. >> Right. And and remember that the first >> Right. And and remember that the first >> Right. And and remember that the first level is level zero. It's down into level is level zero. It's down into level is level zero. It's down into instrumentation instrumentation instrumentation and it's a few levels before we get to and it's a few levels before we get to and it's a few levels before we get to the cloud. I don't know why it's it's the cloud. I don't know why it's it's the cloud. I don't know why it's it's almost 2026 and we're still still almost 2026 and we're still still almost 2026 and we're still still getting wrapped around the axle getting wrapped around the axle getting wrapped around the axle um on this. It's um time to beat time to um on this. It's um time to beat time to um on this. It's um time to beat time to beat people up with this, man. beat people up with this, man. beat people up with this, man. >> Well, it exact. I mean where where >> Well, it exact. I mean where where >> Well, it exact. I mean where where you're saying it is exactly what we're you're saying it is exactly what we're you're saying it is exactly what we're articulating because when you go model articulating because when you go model articulating because when you go model you know that model zero through I mean you know that model zero through I mean you know that model zero through I mean once you actually hit models uh that are once you actually hit models uh that are once you actually hit models uh that are trained at level four the Purdue model trained at level four the Purdue model trained at level four the Purdue model kind of starts to to it kind of starts kind of starts to to it kind of starts kind of starts to to it kind of starts to have challenges AI ML model to have challenges AI ML model to have challenges AI ML model deployment type stuff right um because deployment type stuff right um because deployment type stuff right um because it the constraints are like you know it the constraints are like you know it the constraints are like you know strict one-way data flow which prevents strict one-way data flow which prevents strict one-way data flow which prevents the the push down um computer vision uh the the push down um computer vision uh the the push down um computer vision uh you know defect detections and trained you know defect detections and trained you know defect detections and trained and everything like that that there's and everything like that that there's and everything like that that there's issues in the cloud with that as far as issues in the cloud with that as far as issues in the cloud with that as far as that goes multi-sight digital twins that goes multi-sight digital twins that goes multi-sight digital twins there's challenges there so I mean we there's challenges there so I mean we there's challenges there so I mean we get into a lot of that stuff and I think get into a lot of that stuff and I think get into a lot of that stuff and I think that it's really time to to go back to that it's really time to to go back to that it's really time to to go back to the education of where we're at today the education of where we're at today the education of where we're at today versus where we were you know 20 30 versus where we were you know 20 30 versus where we were you know 20 30 years ago years ago years ago >> you know what Bill maybe we should write >> you know what Bill maybe we should write >> you know what Bill maybe we should write a document a manifesto a white paper or a document a manifesto a white paper or a document a manifesto a white paper or whatever that says this is what we say a whatever that says this is what we say a whatever that says this is what we say a digital twin is and how you have twins digital twin is and how you have twins digital twin is and how you have twins of twins, parent, child, peer, all that of twins, parent, child, peer, all that of twins, parent, child, peer, all that multi-sight and everything. I don't care multi-sight and everything. I don't care multi-sight and everything. I don't care about the whole Purdue thing and all

about the whole Purdue thing and all about the whole Purdue thing and all those ISA 95 people. You know what? Cuz those ISA 95 people. You know what? Cuz those ISA 95 people. You know what? Cuz we are so rogue and I think what we're we are so rogue and I think what we're we are so rogue and I think what we're going to come up with is what I would going to come up with is what I would going to come up with is what I would call the Lukembbach model. call the Lukembbach model. call the Lukembbach model. [laughter] And it's going to work in Texas, I And it's going to work in Texas, I think. And as it turns out, if you're in think. And as it turns out, if you're in think. And as it turns out, if you're in manufacturing, you could make a whole manufacturing, you could make a whole manufacturing, you could make a whole living just here. living just here. living just here. >> Yeah, you could. >> Yeah, you could. >> Yeah, you could. >> Yes. You know, um Jake, the >> Yes. You know, um Jake, the >> Yes. You know, um Jake, the manufacturing millennial, uh I don't manufacturing millennial, uh I don't manufacturing millennial, uh I don't personally know him, but I follow a personally know him, but I follow a personally know him, but I follow a couple of people that follow him. He did couple of people that follow him. He did couple of people that follow him. He did a a self-commissioned infographic. So, a a self-commissioned infographic. So, a a self-commissioned infographic. So, he said, I believe him. he said, I believe him. he said, I believe him. >> Self-commissioned. >> Self-commissioned. >> Self-commissioned. >> Yeah. Well, cuz you know, it's >> Yeah. Well, cuz you know, it's >> Yeah. Well, cuz you know, it's >> I love making infographics. >> I love making infographics. >> I love making infographics. >> Canva probably. Yeah. Well, he did a >> Canva probably. Yeah. Well, he did a >> Canva probably. Yeah. Well, he did a snapshot. He did a snapshot of his home snapshot. He did a snapshot of his home snapshot. He did a snapshot of his home state of uh Michigan. And I remember state of uh Michigan. And I remember state of uh Michigan. And I remember it's Michigan because Kalamazoo is in it's Michigan because Kalamazoo is in it's Michigan because Kalamazoo is in Michigan. And Derek Jeter, number two, Michigan. And Derek Jeter, number two, Michigan. And Derek Jeter, number two, New York Yankees, the greatest shortstop New York Yankees, the greatest shortstop New York Yankees, the greatest shortstop that ever lived, is from Kalamazoo.

that ever lived, is from Kalamazoo. that ever lived, is from Kalamazoo. Sorry, I had to do the baseball thing Sorry, I had to do the baseball thing Sorry, I had to do the baseball thing again. again. again. >> Of course, >> Of course, >> Of course, >> he did. He was highlighting >> he did. He was highlighting >> he did. He was highlighting uh manufacturing outfits that were doing uh manufacturing outfits that were doing uh manufacturing outfits that were doing robotic implementations, specifically robotic implementations, specifically robotic implementations, specifically robotic implementations in Michigan. And robotic implementations in Michigan. And robotic implementations in Michigan. And he had like 70 companies just in one he had like 70 companies just in one he had like 70 companies just in one category, just in manufacturing. So to category, just in manufacturing. So to category, just in manufacturing. So to Rob's point that if you're doing certain Rob's point that if you're doing certain Rob's point that if you're doing certain valuable things in manufacturing valuable things in manufacturing valuable things in manufacturing just in the state of Texas, you've got just in the state of Texas, you've got just in the state of Texas, you've got you've you've got the prospects to uh to you've you've got the prospects to uh to you've you've got the prospects to uh to be able to pull something off. They're be able to pull something off. They're be able to pull something off. They're there. If I go asking anybody, most there. If I go asking anybody, most there. If I go asking anybody, most anybody here in this large shenzhen like anybody here in this large shenzhen like anybody here in this large shenzhen like city of Houston, which is the number one city of Houston, which is the number one city of Houston, which is the number one manufacturing city in America, and I ask manufacturing city in America, and I ask manufacturing city in America, and I ask them all about ISA 95 and Purdue, they them all about ISA 95 and Purdue, they them all about ISA 95 and Purdue, they might be like, "Boy, what you talking might be like, "Boy, what you talking might be like, "Boy, what you talking about? Let's just go get done and about? Let's just go get done and about? Let's just go get done and make some money." A lot of people don't make some money." A lot of people don't make some money." A lot of people don't give a about all that stuff. give a about all that stuff. give a about all that stuff. There's a lot of purists and we know There's a lot of purists and we know There's a lot of purists and we know them all in this industrial IoT space them all in this industrial IoT space them all in this industrial IoT space that we've been living in and they live that we've been living in and they live that we've been living in and they live and die by that stuff and a whole lot of and die by that stuff and a whole lot of and die by that stuff and a whole lot of them didn't make any money. [laughter] them didn't make any money. [laughter] them didn't make any money. [laughter] >> Nope.

>> Nope. >> Nope. >> Nope. >> Nope. >> Nope. >> And so it's like I just don't care, you >> And so it's like I just don't care, you >> And so it's like I just don't care, you know? know? know? >> But I think I think it's prudent to >> But I think I think it's prudent to >> But I think I think it's prudent to actually wrap it around the use cases. I actually wrap it around the use cases. I actually wrap it around the use cases. I mean because the biggest thing that I mean because the biggest thing that I mean because the biggest thing that I hate is I won't say I hate I dislike hate is I won't say I hate I dislike hate is I won't say I hate I dislike strongly is disinformation. disinformation because it's being disinformation because it's being disseminated and those that disseminated and those that disseminated and those that half-heartedly accept it are going to go half-heartedly accept it are going to go half-heartedly accept it are going to go down the track and they're going to down the track and they're going to down the track and they're going to realize that they're stuck. realize that they're stuck. realize that they're stuck. >> Yeah, >> Yeah, >> Yeah, >> I didn't get what I thought I was going >> I didn't get what I thought I was going >> I didn't get what I thought I was going to get. I thought it did this. Yeah, but to get. I thought it did this. Yeah, but to get. I thought it did this. Yeah, but no, that's not really what we do. We do no, that's not really what we do. We do no, that's not really what we do. We do this and we do it very well. I mean, but this and we do it very well. I mean, but this and we do it very well. I mean, but it is take a moment, take a step back it is take a moment, take a step back it is take a moment, take a step back and and figure out what problem you're and and figure out what problem you're and and figure out what problem you're trying to solve. M what? trying to solve. M what? trying to solve. M what? >> Again, >> Again, >> Again, >> we're not supposed to just go build a >> we're not supposed to just go build a >> we're not supposed to just go build a platform or something. We have to we platform or something. We have to we platform or something. We have to we have to figure out what kind of problem have to figure out what kind of problem have to figure out what kind of problem they want to solve. they want to solve. they want to solve. >> You have to figure out what problem >> You have to figure out what problem >> You have to figure out what problem you're trying to solve. I mean, you're trying to solve. I mean, you're trying to solve. I mean, >> there's there's a lot, you know, and you >> there's there's a lot, you know, and you >> there's there's a lot, you know, and you know, in in But again, you know, that's know, in in But again, you know, that's know, in in But again, you know, that's kind of what we've been doing uh over kind of what we've been doing uh over kind of what we've been doing uh over the course of the past, you know, few the course of the past, you know, few the course of the past, you know, few weeks that I've missed being here is, weeks that I've missed being here is, weeks that I've missed being here is, you know, really hunkering down going, you know, really hunkering down going, you know, really hunkering down going, "All right, we're at the end of the "All right, we're at the end of the "All right, we're at the end of the year. I got to get some of these year. I got to get some of these year. I got to get some of these contracts signed. I gotta get, you know, contracts signed. I gotta get, you know, contracts signed. I gotta get, you know, lined up for resources and everything to lined up for resources and everything to lined up for resources and everything to kick off the work in 2026.

kick off the work in 2026. kick off the work in 2026. >> And um, you know, get some get some nice >> And um, you know, get some get some nice >> And um, you know, get some get some nice press releases out there that are proof press releases out there that are proof press releases out there that are proof points. So, not, you know, a press points. So, not, you know, a press points. So, not, you know, a press release for the sake of a press release, release for the sake of a press release, release for the sake of a press release, but really but really but really >> there's a lot of press release marketers >> there's a lot of press release marketers >> there's a lot of press release marketers out there that they think marketing out there that they think marketing out there that they think marketing equals press release. equals press release. equals press release. >> Yes. [laughter] And you know and and and >> Yes. [laughter] And you know and and and >> Yes. [laughter] And you know and and and really you know it's again it's like really you know it's again it's like really you know it's again it's like it's not so much about the tech. The the it's not so much about the tech. The the it's not so much about the tech. The the the tech is the tech. It's always going the tech is the tech. It's always going the tech is the tech. It's always going to change and evolve you know but to change and evolve you know but to change and evolve you know but it's it's about what problem you're it's it's about what problem you're it's it's about what problem you're trying to solve and how you're trying to solve and how you're trying to solve and how you're delivering value to your customers. delivering value to your customers. delivering value to your customers. >> Absolutely. >> Absolutely. >> Absolutely. >> Wow. >> Wow. >> Wow. >> Uh Bill let me go back to Metropolis uh >> Uh Bill let me go back to Metropolis uh >> Uh Bill let me go back to Metropolis uh for a sec. for a sec. for a sec. >> Yeah. So how how's edge AI and digital >> Yeah. So how how's edge AI and digital >> Yeah. So how how's edge AI and digital twins twins twins interacting among each others? Oh, that interacting among each others? Oh, that interacting among each others? Oh, that so that is like well I mean because so that is like well I mean because so that is like well I mean because we're edge-based anyway from the very we're edge-based anyway from the very we're edge-based anyway from the very beginning beginning beginning >> very edgy >> very edgy >> very edgy >> and that's what it was right but then >> and that's what it was right but then >> and that's what it was right but then there's there's things that we just there's there's things that we just there's there's things that we just because of what we do we're just not because of what we do we're just not because of what we do we're just not that great at right which is video like that great at right which is video like that great at right which is video like we don't I'm like we don't do anything we don't I'm like we don't do anything we don't I'm like we don't do anything with that but if you're looking at if with that but if you're looking at if with that but if you're looking at if you're looking at Nvidia and you're you're looking at Nvidia and you're you're looking at Nvidia and you're looking at Metropolis you're looking at looking at Metropolis you're looking at looking at Metropolis you're looking at Cosmos and things of that that video and Cosmos and things of that that video and Cosmos and things of that that video and inference detection there then becomes inference detection there then becomes inference detection there then becomes something insightful in terms of what it something insightful in terms of what it something insightful in terms of what it is that we're doing, right? And and it's is that we're doing, right? And and it's is that we're doing, right? And and it's a it's a it's an interesting thing. One a it's a it's an interesting thing. One a it's a it's an interesting thing. One of these one of these within the next of these one of these within the next of these one of these within the next two times that we meet, I will show you

two times that we meet, I will show you two times that we meet, I will show you an example of what that is because an example of what that is because an example of what that is because literally, let's take the example of literally, let's take the example of literally, let's take the example of what we're doing with with one of our what we're doing with with one of our what we're doing with with one of our customers. They're in a park. They're customers. They're in a park. They're customers. They're in a park. They're like, you know what? We've got Laura like, you know what? We've got Laura like, you know what? We've got Laura sensors on the on the the paper towel sensors on the on the the paper towel sensors on the on the the paper towel dispensers on the bathroom doors on I dispensers on the bathroom doors on I dispensers on the bathroom doors on I mean all over [clears throat] the place. mean all over [clears throat] the place. mean all over [clears throat] the place. Huge huge part some odd 65 cameras and Huge huge part some odd 65 cameras and Huge huge part some odd 65 cameras and they're like and we want to twin the they're like and we want to twin the they're like and we want to twin the whole thing. Well, so it from our point whole thing. Well, so it from our point whole thing. Well, so it from our point of view it was like well operationally of view it was like well operationally of view it was like well operationally you want that streaming data and that's you want that streaming data and that's you want that streaming data and that's what we do. That's not what Metropolis what we do. That's not what Metropolis what we do. That's not what Metropolis or Cosmos or any of them do. They don't or Cosmos or any of them do. They don't or Cosmos or any of them do. They don't they don't show you the operational they don't show you the operational they don't show you the operational impact, but they're very good at at impact, but they're very good at at impact, but they're very good at at taking the video. And the edge part of taking the video. And the edge part of taking the video. And the edge part of it is the Orurin. it is the Orurin. it is the Orurin. Orin is awesome. Orin is awesome. Orin is awesome. >> I mean, for video and for camera >> I mean, for video and for camera >> I mean, for video and for camera connections. A single Orin can support connections. A single Orin can support connections. A single Orin can support up up to 100 cameras. up up to 100 cameras. up up to 100 cameras. >> What's an Orin? I don't know what that >> What's an Orin? I don't know what that >> What's an Orin? I don't know what that is. is. is. >> That's an orin. It's a It's a hardware >> That's an orin. It's a It's a hardware >> That's an orin. It's a It's a hardware made by Nvidia.

made by Nvidia. made by Nvidia. >> Okay. >> Okay. >> Okay. >> Yeah. >> Yeah. >> Yeah. >> To run. >> To run. >> To run. it it it lines up with our story and it it it lines up with our story and it it it lines up with our story and what we do now even even on the what we do now even even on the what we do now even even on the Metropolis side and everything like Metropolis side and everything like Metropolis side and everything like that. You have um the models that are that. You have um the models that are that. You have um the models that are there, right? And the models are trained there, right? And the models are trained there, right? And the models are trained and if you add new cameras now you got and if you add new cameras now you got and if you add new cameras now you got to take it down. You got to retrain the to take it down. You got to retrain the to take it down. You got to retrain the models to include those cameras and models to include those cameras and models to include those cameras and everything. But what if when you put everything. But what if when you put everything. But what if when you put those things up, we are the intermediary those things up, we are the intermediary those things up, we are the intermediary because we're the operation side and we because we're the operation side and we because we're the operation side and we unidirectionally feed the data to unidirectionally feed the data to unidirectionally feed the data to Metropolis. Metropolis. Metropolis. >> Wow. >> Wow. >> Wow. >> You don't have to you don't have to >> You don't have to you don't have to >> You don't have to you don't have to retrain that that data. Your model stays retrain that that data. Your model stays retrain that that data. Your model stays updated. updated. updated. >> But Bill, let I mean, I'm only here to >> But Bill, let I mean, I'm only here to >> But Bill, let I mean, I'm only here to ask the dumb questions. This is how I've ask the dumb questions. This is how I've ask the dumb questions. This is how I've been here for years. Um, if you have a been here for years. Um, if you have a been here for years. Um, if you have a deployment with X amount of cameras and deployment with X amount of cameras and deployment with X amount of cameras and they're trained on whatever it is that they're trained on whatever it is that they're trained on whatever it is that the customer for the business problem the customer for the business problem the customer for the business problem decided to train them on and then one decided to train them on and then one decided to train them on and then one day you add two more cameras to a new day you add two more cameras to a new day you add two more cameras to a new area of this geography, area of this geography, area of this geography, why why why what would be the reasons to have to what would be the reasons to have to what would be the reasons to have to retrain when you already have a model retrain when you already have a model retrain when you already have a model and you just have new feats?

and you just have new feats? and you just have new feats? something something something >> you you watch because because what is >> you you watch because because what is >> you you watch because because what is that what is that camera actually that what is that camera actually that what is that camera actually looking at? One, does that camera run looking at? One, does that camera run looking at? One, does that camera run applications? Two, does that camera does applications? Two, does that camera does applications? Two, does that camera does that camera uh you know where is it that camera uh you know where is it that camera uh you know where is it located geospatially? You I mean you got located geospatially? You I mean you got located geospatially? You I mean you got to have some geospatial awareness about to have some geospatial awareness about to have some geospatial awareness about that camera. Uh three, so that the model that camera. Uh three, so that the model that camera. Uh three, so that the model now has to be it has to be retrained. now has to be it has to be retrained. now has to be it has to be retrained. You can't just introduce that and it You can't just introduce that and it You can't just introduce that and it automatic automatically knows, oh, automatic automatically knows, oh, automatic automatically knows, oh, you're at lat latl long x and you have you're at lat latl long x and you have you're at lat latl long x and you have these applications running and this is these applications running and this is these applications running and this is the inference that we're going to run on the inference that we're going to run on the inference that we're going to run on you. You've got to run that through for you. You've got to run that through for you. You've got to run that through for a while before you actually land on its a while before you actually land on its a while before you actually land on its train and it knows what it's looking for train and it knows what it's looking for train and it knows what it's looking for and these are the anomalies that it's and these are the anomalies that it's and these are the anomalies that it's detecting. detecting. detecting. >> So, let me say this so that a dumbass >> So, let me say this so that a dumbass >> So, let me say this so that a dumbass like me can understand. So, if I have a like me can understand. So, if I have a like me can understand. So, if I have a deployment of cameras and I'm looking deployment of cameras and I'm looking deployment of cameras and I'm looking for, let's just say I'm looking for for, let's just say I'm looking for for, let's just say I'm looking for speeding cars. That's that's my model. speeding cars. That's that's my model. speeding cars. That's that's my model. >> Yeah. >> Yeah. >> Yeah. >> If someone speeds, tell me about it. >> If someone speeds, tell me about it. >> If someone speeds, tell me about it. >> And now I deploy two new cameras.

>> And now I deploy two new cameras. >> And now I deploy two new cameras. >> Yeah. >> Yeah. >> Yeah. >> To look for speeding cars, but it's two >> To look for speeding cars, but it's two >> To look for speeding cars, but it's two new streets that we hadn't covered new streets that we hadn't covered new streets that we hadn't covered before. before. before. You're telling me that I cannot just You're telling me that I cannot just You're telling me that I cannot just copy paste the model and tell Okay. See, copy paste the model and tell Okay. See, copy paste the model and tell Okay. See, and for every for the our 2.3 billion and for every for the our 2.3 billion and for every for the our 2.3 billion people that are watching, the way I'm people that are watching, the way I'm people that are watching, the way I'm positioning this question is based on a positioning this question is based on a positioning this question is based on a common belief, but [snorts] now you're common belief, but [snorts] now you're common belief, but [snorts] now you're getting expert answers that is not a getting expert answers that is not a getting expert answers that is not a copype copype copype go. So, Bill, please. go. So, Bill, please. go. So, Bill, please. No, but I mean but but but but the at No, but I mean but but but but the at No, but I mean but but but but the at the end of the day the the the element the end of the day the the the element the end of the day the the the element of because that's just that that one of because that's just that that one of because that's just that that one part of it. But when you start thinking part of it. But when you start thinking part of it. But when you start thinking about okay, well now I want to actually about okay, well now I want to actually about okay, well now I want to actually walk through that park and I want to I walk through that park and I want to I walk through that park and I want to I want to get that experience or I want to want to get that experience or I want to want to get that experience or I want to walk through those streets. That's where walk through those streets. That's where walk through those streets. That's where it shines. We don't do that. you're it shines. We don't do that. you're it shines. We don't do that. you're you're not you know or if you actually you're not you know or if you actually you're not you know or if you actually want to um query the model or the twin want to um query the model or the twin want to um query the model or the twin that side of the twin you want to query that side of the twin you want to query that side of the twin you want to query it you're not talking to our operational it you're not talking to our operational it you're not talking to our operational dashboard you're not going to inject any dashboard you're not going to inject any dashboard you're not going to inject any large language model into the large language model into the large language model into the operational dashboard that is your operational dashboard that is your operational dashboard that is your operational dashboard it's telling you operational dashboard it's telling you operational dashboard it's telling you what's happening at any moment in time what's happening at any moment in time what's happening at any moment in time so the com combination of the to create so the com combination of the to create so the com combination of the to create something that has not been done yet. So something that has not been done yet. So something that has not been done yet. So you're you're you're able to do things

you're you're you're able to do things you're you're you're able to do things in real time and you're able to look at in real time and you're able to look at in real time and you're able to look at it and and keep your your model updated. it and and keep your your model updated. it and and keep your your model updated. >> But David, you don't start from a >> But David, you don't start from a >> But David, you don't start from a scratch every time that you deploy a new scratch every time that you deploy a new scratch every time that you deploy a new camera. No simulation. So you start from camera. No simulation. So you start from camera. No simulation. So you start from a foundational model that more or less a foundational model that more or less a foundational model that more or less understand what is a car. No. In your understand what is a car. No. In your understand what is a car. No. In your use case. use case. use case. >> Yeah. >> Yeah. >> Yeah. >> No, it has this shape. It is the only >> No, it has this shape. It is the only >> No, it has this shape. It is the only problem is the context that Bill problem is the context that Bill problem is the context that Bill mentioned, right? So the camera can be mentioned, right? So the camera can be mentioned, right? So the camera can be in another angle in another type of in another angle in another type of in another angle in another type of position. Uh maybe it's sunny more hours position. Uh maybe it's sunny more hours position. Uh maybe it's sunny more hours or maybe it's in a tunnel and it's or maybe it's in a tunnel and it's or maybe it's in a tunnel and it's always dark. Um so or the lights go uh always dark. Um so or the lights go uh always dark. Um so or the lights go uh no against the camera. So there are no against the camera. So there are no against the camera. So there are multiple uh things that can affect the multiple uh things that can affect the multiple uh things that can affect the model. So it will need like uh to to get model. So it will need like uh to to get model. So it will need like uh to to get a retrain to to get properly a retrain to to get properly a retrain to to get properly It's not like, you know, I I think and It's not like, you know, I I think and It's not like, you know, I I think and and and Mark, you I think you can attest and and Mark, you I think you can attest and and Mark, you I think you can attest this. It's not like I'm saying that you this. It's not like I'm saying that you this. It's not like I'm saying that you have to go back to square one and that have to go back to square one and that have to go back to square one and that whole whatever it took three weeks to, whole whatever it took three weeks to, whole whatever it took three weeks to, you know, fully train it and go, "Yeah, you know, fully train it and go, "Yeah, you know, fully train it and go, "Yeah, we're good." It's it's not that. But you we're good." It's it's not that. But you we're good." It's it's not that. But you will have to retrain.

will have to retrain. will have to retrain. So, because we're operational So, because we're operational So, because we're operational and everything is done on the fly, we're and everything is done on the fly, we're and everything is done on the fly, we're just all we're looking bits flying just all we're looking bits flying just all we're looking bits flying and we're saying this is what happened. and we're saying this is what happened. and we're saying this is what happened. This is what happened. That's what This is what happened. That's what This is what happened. That's what happened at that time. happened at that time. happened at that time. >> You You guys are giving me ideas on how >> You You guys are giving me ideas on how >> You You guys are giving me ideas on how I'm going to beat the singularity. I'm I'm going to beat the singularity. I'm I'm going to beat the singularity. I'm just going to switch hands [laughter] just going to switch hands [laughter] just going to switch hands [laughter] and the camera is going to be so and the camera is going to be so and the camera is going to be so confused that they're not able to track confused that they're not able to track confused that they're not able to track my movements as I, you know, go in and my movements as I, you know, go in and my movements as I, you know, go in and out of the house. out of the house. out of the house. >> It's your 60 frames per second camera. >> It's your 60 frames per second camera. >> It's your 60 frames per second camera. >> Yeah. Yeah. Yeah. [laughter] >> I love it. >> I love it. >> But you have to understand that a camera >> But you have to understand that a camera >> But you have to understand that a camera is not a camera anymore, right? It's not is not a camera anymore, right? It's not is not a camera anymore, right? It's not something that you press a button something that you press a button something that you press a button >> and the light gets in a material and the >> and the light gets in a material and the >> and the light gets in a material and the camera shutter speed no longer matters. camera shutter speed no longer matters. camera shutter speed no longer matters. >> Wow. >> Wow. >> Wow. >> As a matter of fact, >> As a matter of fact, >> As a matter of fact, are you going to Smart City E Expo? are you going to Smart City E Expo? are you going to Smart City E Expo? You're not. You're not. You're not. >> I'm going to North America. >> I'm going to North America. >> I'm going to North America. >> OH, OKAY.

>> OH, OKAY. >> OH, OKAY. >> ARE YOU GOING to Barcelona? >> ARE YOU GOING to Barcelona? >> ARE YOU GOING to Barcelona? Well, Travis, I mean, one of our guys is Well, Travis, I mean, one of our guys is Well, Travis, I mean, one of our guys is going to be out there. Um, and and he's going to be out there. Um, and and he's going to be out there. Um, and and he's going to be there and, going to be there and, going to be there and, uh, North Texas Innovation Alliance is uh, North Texas Innovation Alliance is uh, North Texas Innovation Alliance is there with the city of Frisco. Um, and there with the city of Frisco. Um, and there with the city of Frisco. Um, and AMS, our partner, is going to be there AMS, our partner, is going to be there AMS, our partner, is going to be there showing showing our stuff. It's showing showing our stuff. It's showing showing our stuff. It's >> do two events at the same date. That's >> do two events at the same date. That's >> do two events at the same date. That's completely stupid. And Badwell and Smart completely stupid. And Badwell and Smart completely stupid. And Badwell and Smart City Expo, same exact dates. Like, what? City Expo, same exact dates. Like, what? City Expo, same exact dates. Like, what? >> Yeah, it should be. I mean, so they're >> Yeah, it should be. I mean, so they're >> Yeah, it should be. I mean, so they're uh they're they're headed to uh uh they're they're headed to uh uh they're they're headed to uh Barcelona now. Um you know, Barcelona now. Um you know, Barcelona now. Um you know, unfortunately, I'm missing this one unfortunately, I'm missing this one unfortunately, I'm missing this one because I've got to get these so and because I've got to get these so and because I've got to get these so and contracts done. Somebody's got to do contracts done. Somebody's got to do contracts done. Somebody's got to do >> someone's got to keep the lights on. >> someone's got to keep the lights on. >> someone's got to keep the lights on. >> Exactly. >> Exactly. >> Exactly. >> Business doesn't go. Exactly. Money >> Business doesn't go. Exactly. Money >> Business doesn't go. Exactly. Money never sleeps. That's what Gordon Gecko never sleeps. That's what Gordon Gecko never sleeps. That's what Gordon Gecko told me when I was told me when I was told me when I was >> when he was my mentor. >> when he was my mentor. >> when he was my mentor. >> Bill, you know what, Bill? Ju just let >> Bill, you know what, Bill? Ju just let >> Bill, you know what, Bill? Ju just let uh you know, MCP take care of all your uh you know, MCP take care of all your uh you know, MCP take care of all your uh Yeah, uh Yeah, uh Yeah, >> you're done with MCP.

>> you're done with MCP. >> you're done with MCP. >> Yeah. Yeah, you know me. Hey, so we have >> Yeah. Yeah, you know me. Hey, so we have >> Yeah. Yeah, you know me. Hey, so we have we have less than a minute recording we have less than a minute recording we have less than a minute recording because the guy that takes all of the because the guy that takes all of the because the guy that takes all of the money for these streams, Leonard, he's money for these streams, Leonard, he's money for these streams, Leonard, he's on an aeroplane. on an aeroplane. on an aeroplane. >> Aerop. >> Aerop. >> Aerop. >> So, I'm going to uh force us to bring us >> So, I'm going to uh force us to bring us >> So, I'm going to uh force us to bring us out. Folks, you've made it to the end of out. Folks, you've made it to the end of out. Folks, you've made it to the end of another baseball digital twin edge AI another baseball digital twin edge AI another baseball digital twin edge AI episode of IoT Coffee Talk where you get episode of IoT Coffee Talk where you get episode of IoT Coffee Talk where you get facts, you get dumb questions from these facts, you get dumb questions from these facts, you get dumb questions from these from this guy and [clears throat] expert from this guy and [clears throat] expert from this guy and [clears throat] expert answers to help you and your community answers to help you and your community answers to help you and your community become elevated, educated in here. So, become elevated, educated in here. So, become elevated, educated in here. So, thank you for watching. Remember, thank you for watching. Remember, thank you for watching. Remember, elevate our kids.org. elevate our kids.org. elevate our kids.org. >> Elevate communities to try to close the >> Elevate communities to try to close the >> Elevate communities to try to close the digital divide. Uh, I'm not gonna say digital divide. Uh, I'm not gonna say digital divide. Uh, I'm not gonna say anything about Brendan Carr in the FCC anything about Brendan Carr in the FCC anything about Brendan Carr in the FCC at this point, but you know what he up at this point, but you know what he up at this point, but you know what he up to. [music] We're doing the other thing.