IoT Coffee Talk: Episode 292 - "6th Annual Christmas Special" (The Lump of Coal of Invention)

Merry Christmas Merry Christmas to you. to you. to you. >> Merry [singing] >> Merry [singing] >> Merry [singing] Christmas Christmas Christmas to you. Merry Christmas. >> Yeah. Merry Christmas. >> Yeah. Merry Christmas. Christmas to to you. >> Yeah. >> Yeah. >> Wow. You know, Leonard, that was >> Wow. You know, Leonard, that was >> Wow. You know, Leonard, that was awesome. awesome. awesome. >> Yeah. You know, the way you looked there >> Yeah. You know, the way you looked there >> Yeah. You know, the way you looked there at the m at the end when you were kind at the m at the end when you were kind at the m at the end when you were kind of doing the weird mouth thing and of doing the weird mouth thing and of doing the weird mouth thing and shake. You look like Adam Sandler when shake. You look like Adam Sandler when shake. You look like Adam Sandler when he was doing his Hanukkah song actually, he was doing his Hanukkah song actually, he was doing his Hanukkah song actually, [laughter] [laughter] [laughter] >> which I think is a much better song that >> which I think is a much better song that >> which I think is a much better song that we could do. we could do. we could do. >> Yeah, >> Yeah, >> Yeah, >> if you remember the lyrics. >> if you remember the lyrics. >> if you remember the lyrics. >> Yeah. Next time we'll have a Hanukkah >> Yeah. Next time we'll have a Hanukkah >> Yeah. Next time we'll have a Hanukkah special. How's that song? special. How's that song? special. How's that song? >> That Adam Sandler thing was the funniest >> That Adam Sandler thing was the funniest >> That Adam Sandler thing was the funniest thing ever. Oh my god. >> Hello. Hello. Hello. That's when you >> Hello. Hello. Hello. That's when you found out that Han Solo was Jewish.

found out that Han Solo was Jewish. found out that Han Solo was Jewish. >> There you go. >> There you go. >> There you go. >> Order. >> Order. >> Order. >> There you go. Order Jewish, right? >> There you go. Order Jewish, right? >> There you go. Order Jewish, right? [laughter] [laughter] [laughter] >> I think he was talking about someone >> I think he was talking about someone >> I think he was talking about someone else. But yes, there was a big Now, else. But yes, there was a big Now, else. But yes, there was a big Now, you're right. The song was about a lot you're right. The song was about a lot you're right. The song was about a lot of reveals, I suppose. Yes, sure. of reveals, I suppose. Yes, sure. of reveals, I suppose. Yes, sure. >> Here you go. >> Here you go. >> Here you go. >> Indiana Jones. >> Indiana Jones. >> Indiana Jones. >> Yeah. >> Yeah. >> Yeah. >> Cool. >> Cool. >> Cool. >> All right. All right. Here we are. >> All right. All right. Here we are. >> All right. All right. Here we are. >> Welcome to IoT Coffee Talk. >> Welcome to IoT Coffee Talk. >> Welcome to IoT Coffee Talk. Uh Christmas holiday special. Uh Christmas holiday special. Uh Christmas holiday special. >> This seventh. >> This seventh. >> This seventh. >> This is >> This is >> This is >> seventh holiday special. Wow. >> seventh holiday special. Wow. >> seventh holiday special. Wow. >> We're going to hit a decade, man. We're >> We're going to hit a decade, man. We're >> We're going to hit a decade, man. We're going to hit a decade. It's crazy. Then, going to hit a decade. It's crazy. Then, going to hit a decade. It's crazy. Then, you know, we won't you know, we won't you know, we won't >> I feel like we just started this thing. >> Yeah. >> Yeah. >> Oh my gosh. Oh my gosh. >> Oh my gosh. Oh my gosh. >> Oh my gosh. Oh my gosh. >> We're We're going to have to have a >> We're We're going to have to have a >> We're We're going to have to have a pandemic pandemic pandemic 10th year anniversary. 10th year anniversary. 10th year anniversary. >> That's right. That's what come back. >> That's right. That's what come back. >> That's right. That's what come back. >> Oh my gosh, that's awesome. >> Oh my gosh, that's awesome. >> Oh my gosh, that's awesome. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> And welcome Alistister. What's up?

>> And welcome Alistister. What's up? >> And welcome Alistister. What's up? [laughter] [laughter] [laughter] >> It's good to have you. Freaking IoT. >> It's good to have you. Freaking IoT. >> It's good to have you. Freaking IoT. >> Remember the last one I did of these was >> Remember the last one I did of these was >> Remember the last one I did of these was I think I can't remember where the hell I think I can't remember where the hell I think I can't remember where the hell we were, but we were at some event um we were, but we were at some event um we were, but we were at some event um either embedded world or might have been either embedded world or might have been either embedded world or might have been >> Oh, yeah. We I think we were at IoT >> Oh, yeah. We I think we were at IoT >> Oh, yeah. We I think we were at IoT Stars in Barcelona a few years ago. Stars in Barcelona a few years ago. Stars in Barcelona a few years ago. >> Yeah. for MWC. That's right. >> Yeah. for MWC. That's right. >> Yeah. for MWC. That's right. >> Yes, that was fun. >> Yes, that was fun. >> Yes, that was fun. >> Absolutely. That's good stuff. >> Absolutely. That's good stuff. >> Absolutely. That's good stuff. >> Woohoo. IoT stars for the win. >> Woohoo. IoT stars for the win. >> Woohoo. IoT stars for the win. >> Yes. >> Yes. >> Yes. >> Yeah. I got to say that was about the >> Yeah. I got to say that was about the >> Yeah. I got to say that was about the best thing about Embedded World um here best thing about Embedded World um here best thing about Embedded World um here in in Anaheim was the IoT Stars event. in in Anaheim was the IoT Stars event. in in Anaheim was the IoT Stars event. >> That's what I heard. That was the >> That's what I heard. That was the >> That's what I heard. That was the highlight. highlight. highlight. >> Yeah. I mean, Embedded World got better. >> Yeah. I mean, Embedded World got better. >> Yeah. I mean, Embedded World got better. I went to the last one last year in I went to the last one last year in I went to the last one last year in Austin, which I think was the kind of Austin, which I think was the kind of Austin, which I think was the kind of the Ignore. the Ignore. the Ignore. Yeah. Um, Yeah. Um, Yeah. Um, >> okay. >> okay. >> okay. >> And it was busier than that, but it was >> And it was busier than that, but it was >> And it was busier than that, but it was still, still, still, >> yeah, >> yeah, >> yeah, >> you know, it was the usual echo chamber. >> you know, it was the usual echo chamber. >> you know, it was the usual echo chamber. Lots of people talking to each other Lots of people talking to each other Lots of people talking to each other about where the customers are.

about where the customers are. about where the customers are. >> Are they not many? Not many, you know, >> Are they not many? Not many, you know, >> Are they not many? Not many, you know, not many. not many. not many. >> Have you seen any customers? No. >> Have you seen any customers? No. >> Have you seen any customers? No. >> Has anyone seen a customer? >> Has anyone seen a customer? >> Has anyone seen a customer? >> I'd be surprised. Uh, I'd be interested >> I'd be surprised. Uh, I'd be interested >> I'd be surprised. Uh, I'd be interested to see if they do it next year. I don't to see if they do it next year. I don't to see if they do it next year. I don't know. Or maybe scale. know. Or maybe scale. know. Or maybe scale. >> I think they problem it's run by the >> I think they problem it's run by the >> I think they problem it's run by the Nermberg Messa. You know, that's who Nermberg Messa. You know, that's who Nermberg Messa. You know, that's who runs embedded world. And so it's it's runs embedded world. And so it's it's runs embedded world. And so it's it's and they're used to, you know, embedded and they're used to, you know, embedded and they're used to, you know, embedded world Nerburgg is 100,000 people and world Nerburgg is 100,000 people and world Nerburgg is 100,000 people and like seven halls and like seven halls and like seven halls and >> you know it's hard to translate that >> you know it's hard to translate that >> you know it's hard to translate that [snorts and clears throat] [snorts and clears throat] [snorts and clears throat] >> somewhere else and to get the critical >> somewhere else and to get the critical >> somewhere else and to get the critical mass. So I don't know. We'll see. mass. So I don't know. We'll see. mass. So I don't know. We'll see. >> Too many events, too many things to go >> Too many events, too many things to go >> Too many events, too many things to go to as you guys know. It's like every to as you guys know. It's like every to as you guys know. It's like every week there's three things in week there's three things in week there's three things in >> different parts of the world. So, >> different parts of the world. So, >> different parts of the world. So, >> are we going to >> are we going to >> are we going to >> doing a live event from CES in a few >> doing a live event from CES in a few >> doing a live event from CES in a few weeks? weeks? weeks? >> Yeah, we should do a live stream from >> Yeah, we should do a live stream from >> Yeah, we should do a live stream from folks. I'll be there. I don't know who folks. I'll be there. I don't know who folks. I'll be there. I don't know who else. Rob, you're there. Leonard's else. Rob, you're there. Leonard's else. Rob, you're there. Leonard's there. there. there. >> Yeah, everybody's there. >> Yeah, everybody's there. >> Yeah, everybody's there. >> Alistar will be there. >> Alistar will be there. >> Alistar will be there. >> Heck yeah. >> Heck yeah. >> Heck yeah. >> Steve will be there. >> Steve will be there. >> Steve will be there. >> Yeah. >> Yeah. >> Yeah. >> Stephanie's gonna be there, right?

>> Stephanie's gonna be there, right? >> Stephanie's gonna be there, right? >> Stephanie will be there. So, >> you know, >> you know, >> do something >> do something >> do something >> from uh, you know, Guy Fier's uh, >> from uh, you know, Guy Fier's uh, >> from uh, you know, Guy Fier's uh, restaurant or something, you know. restaurant or something, you know. restaurant or something, you know. >> Yeah. >> Yeah. >> Yeah. >> What are you eating there, bro? >> What are you eating there, bro? >> What are you eating there, bro? >> Broccoli. >> Broccoli. >> Broccoli. >> Broccoli in the morning. >> Broccoli in the morning. >> Broccoli in the morning. >> That's the weirdest thing I've ever >> That's the weirdest thing I've ever >> That's the weirdest thing I've ever heard of. Broccoli in the morning. heard of. Broccoli in the morning. heard of. Broccoli in the morning. >> Yeah, I know. My wife My wife gave it to >> Yeah, I know. My wife My wife gave it to >> Yeah, I know. My wife My wife gave it to me. I have no explanation. me. I have no explanation. me. I have no explanation. >> It's I had uh Rob, you'll appreciate >> It's I had uh Rob, you'll appreciate >> It's I had uh Rob, you'll appreciate this. I had I had breakfast at Chase's this. I had I had breakfast at Chase's this. I had I had breakfast at Chase's Pancake Corral this morning, didn't I? Pancake Corral this morning, didn't I? Pancake Corral this morning, didn't I? >> Chase's I haven't been there in forever. >> Chase's I haven't been there in forever. >> Chase's I haven't been there in forever. Wow. Wow. Wow. >> Yeah. Some sourdough pancakes. Sourdough >> Yeah. Some sourdough pancakes. Sourdough >> Yeah. Some sourdough pancakes. Sourdough pancakes and uh coffee and eggs. pancakes and uh coffee and eggs. pancakes and uh coffee and eggs. >> It's nice. >> It's nice. >> It's nice. >> Outstanding. Outstanding. I love >> Outstanding. Outstanding. I love >> Outstanding. Outstanding. I love >> Pancake Crow. So, everyone anyone comes >> Pancake Crow. So, everyone anyone comes >> Pancake Crow. So, everyone anyone comes to Bellev. They've been around since to Bellev. They've been around since to Bellev. They've been around since like whatever since before Bellev was like whatever since before Bellev was like whatever since before Bellev was Belleview basically. Belleview basically. Belleview basically. >> Absolutely. Back when Bellev was just >> Absolutely. Back when Bellev was just >> Absolutely. Back when Bellev was just one flashing light. one flashing light. one flashing light. >> One red light. >> One red light. >> One red light. >> One red light. Absolutely. Yeah. How did >> One red light. Absolutely. Yeah. How did >> One red light. Absolutely. Yeah. How did I live in Seattle for 10 years and never I live in Seattle for 10 years and never I live in Seattle for 10 years and never find it? find it? find it? >> Uh, well, it's on it's on Belleview, so >> Uh, well, it's on it's on Belleview, so >> Uh, well, it's on it's on Belleview, so if you're a Seattleite, you might not.

if you're a Seattleite, you might not. if you're a Seattleite, you might not. It's tucked away in kind of the south It's tucked away in kind of the south It's tucked away in kind of the south Belleview area. Belleview area. Belleview area. >> Yeah, I lived in Magnolia, so the the >> Yeah, I lived in Magnolia, so the the >> Yeah, I lived in Magnolia, so the the going to Belleview is like the sitting going to Belleview is like the sitting going to Belleview is like the sitting in traffic, you know. in traffic, you know. in traffic, you know. >> Yes. Yes. It's down in souy. >> Yes. Yes. It's down in souy. >> Yes. Yes. It's down in souy. >> Souy Belle is souy part of Belleview. >> Souy Belle is souy part of Belleview. >> Souy Belle is souy part of Belleview. The tough part of The tough part of The tough part of >> the mean streets of Belle. Yeah. >> the mean streets of Belle. Yeah. >> the mean streets of Belle. Yeah. Absolutely. [laughter] Absolutely. [laughter] Absolutely. [laughter] Yeah. You know, my first my first Yeah. You know, my first my first Yeah. You know, my first my first startup I ever worked for, this company, startup I ever worked for, this company, startup I ever worked for, this company, Realtime Data, they were down in Souy Realtime Data, they were down in Souy Realtime Data, they were down in Souy Belleue. There was like a Bellefield Belleue. There was like a Bellefield Belleue. There was like a Bellefield office park, um, which there were all office park, um, which there were all office park, um, which there were all these buildings that looked like kind of these buildings that looked like kind of these buildings that looked like kind of on stilts. It seemed like it was in a on stilts. It seemed like it was in a on stilts. It seemed like it was in a swamp. Um, but yes, it was like swamp. Um, but yes, it was like swamp. Um, but yes, it was like >> they got a good deal on the land, but >> they got a good deal on the land, but >> they got a good deal on the land, but they just had they just had they just had >> they got a good deal. Exactly. And so, >> they got a good deal. Exactly. And so, >> they got a good deal. Exactly. And so, uh, to make sure you don't have to worry uh, to make sure you don't have to worry uh, to make sure you don't have to worry about flooding, we we build them like about flooding, we we build them like about flooding, we we build them like beach houses on beach houses on beach houses on >> Well, these days, you know, it's not a >> Well, these days, you know, it's not a >> Well, these days, you know, it's not a bad idea around here to have some stilts bad idea around here to have some stilts bad idea around here to have some stilts on your properties. on your properties. on your properties. >> Yeah, absolutely. >> Yeah, absolutely. >> Yeah, absolutely. >> Did were you affected at all by all this >> Did were you affected at all by all this >> Did were you affected at all by all this flooding, Pete? flooding, Pete? flooding, Pete? >> No, fortunately, we're kind of a little >> No, fortunately, we're kind of a little >> No, fortunately, we're kind of a little bit up on We're kind of up on a bit of a bit up on We're kind of up on a bit of a bit up on We're kind of up on a bit of a hill here. So, um, you know, I'm in the hill here. So, um, you know, I'm in the hill here. So, um, you know, I'm in the northern part of Bellev, right near northern part of Bellev, right near northern part of Bellev, right near Microsoft campus. So, there's nothing Microsoft campus. So, there's nothing Microsoft campus. So, there's nothing really really really >> flooding wise going on here. We're not >> flooding wise going on here. We're not >> flooding wise going on here. We're not in the lowlands or by the rivers. So, in the lowlands or by the rivers. So, in the lowlands or by the rivers. So, but yeah, folks down in those areas, but yeah, folks down in those areas, but yeah, folks down in those areas, man, it's tough.

man, it's tough. man, it's tough. >> Yeah, >> Yeah, >> Yeah, >> tough. It's going to it's going to rain >> tough. It's going to it's going to rain >> tough. It's going to it's going to rain for the rest of the week, too, probably. for the rest of the week, too, probably. for the rest of the week, too, probably. So, So, So, >> Oh, man. >> Oh, man. >> Oh, man. >> brutal. >> brutal. >> brutal. >> Hey guys. Yeah, before we go any >> Hey guys. Yeah, before we go any >> Hey guys. Yeah, before we go any further, um let's do our disclaimer and further, um let's do our disclaimer and further, um let's do our disclaimer and uh so um take us seriously everyone uh uh so um take us seriously everyone uh uh so um take us seriously everyone uh at your own risk. So, this is IoT coffee at your own risk. So, this is IoT coffee at your own risk. So, this is IoT coffee talk. talk. talk. >> Make sure you put that >> Make sure you put that >> Make sure you put that >> it's unfiltered, >> it's unfiltered, >> it's unfiltered, unedited. It it it's about to get nasty unedited. It it it's about to get nasty unedited. It it it's about to get nasty up in here as they say. up in here as they say. up in here as they say. >> Oh my god. >> Oh my god. >> Oh my god. >> I think a great poet that's a quote from >> I think a great poet that's a quote from >> I think a great poet that's a quote from a great poet of a great poet of a great poet of >> Yeah. Yeah. And don't make don't make >> Yeah. Yeah. And don't make don't make >> Yeah. Yeah. And don't make don't make financial decisions or stock purchases financial decisions or stock purchases financial decisions or stock purchases based on anything we say, you know. based on anything we say, you know. based on anything we say, you know. >> Yeah. And take out insurance, right? And >> Yeah. And take out insurance, right? And >> Yeah. And take out insurance, right? And any risk that you assume, any risk that you assume, any risk that you assume, >> uh it's all on you peoples. So, uh that >> uh it's all on you peoples. So, uh that >> uh it's all on you peoples. So, uh that and hey, um this is really important. and hey, um this is really important. and hey, um this is really important. We're at the end of the year, so it's We're at the end of the year, so it's We're at the end of the year, so it's time for a tax deduction, time for a tax deduction, time for a tax deduction, [laughter] [laughter] [laughter] >> even though we're not specialists, but >> even though we're not specialists, but >> even though we're not specialists, but hey, make a donation, right? Um, hey, make a donation, right? Um, hey, make a donation, right? Um, >> Elevate Communities at >> Elevate Communities at >> Elevate Communities at www.elevatecommunities.org.

And And >> we're going to start kicking this off in >> we're going to start kicking this off in >> we're going to start kicking this off in the the first part of the year, right? the the first part of the year, right? the the first part of the year, right? And we're going to And we're going to And we're going to >> we're going to have some sessions to >> we're going to have some sessions to >> we're going to have some sessions to talk about what some of these blueprints talk about what some of these blueprints talk about what some of these blueprints will look like to enable communities and will look like to enable communities and will look like to enable communities and being more resilient and prepared for being more resilient and prepared for being more resilient and prepared for natural disasters which are becoming natural disasters which are becoming natural disasters which are becoming more frequent and we'll probably have more frequent and we'll probably have more frequent and we'll probably have more of them. I mean, you know, Seattle, more of them. I mean, you know, Seattle, more of them. I mean, you know, Seattle, I mean, earlier I mean, earlier I mean, earlier flooding and stuff like that, I think flooding and stuff like that, I think flooding and stuff like that, I think that could save tons of lives, that could save tons of lives, that could save tons of lives, >> you know. So, that's >> you know. So, that's >> you know. So, that's >> maybe IoT sensors could help with that. >> maybe IoT sensors could help with that. >> maybe IoT sensors could help with that. I don't know. You know, I don't know. You know, I don't know. You know, >> maybe I think you need generative AI. >> maybe I think you need generative AI. >> maybe I think you need generative AI. >> No, you need generative AI data centers >> No, you need generative AI data centers >> No, you need generative AI data centers with nuclear power plants next to them. with nuclear power plants next to them. with nuclear power plants next to them. So, So, So, >> yes. [laughter] Yes. >> yes. [laughter] Yes. >> yes. [laughter] Yes. >> Melting the ice cap so that we causes >> Melting the ice cap so that we causes >> Melting the ice cap so that we causes flooding and Yeah, flooding and Yeah, flooding and Yeah, >> that's right. Really cool. I love that. >> that's right. Really cool. I love that. >> that's right. Really cool. I love that. >> But um Yeah. And of course, merry new >> But um Yeah. And of course, merry new >> But um Yeah. And of course, merry new year. Merry new year. year. Merry new year. year. Merry new year. >> Merry new year. >> Merry new year. >> Merry new year. >> Not yet. But we just had to do that. >> Not yet. But we just had to do that. >> Not yet. But we just had to do that. >> Not yet. >> Not yet. >> Not yet. >> Yeah.

>> Yeah. >> Yeah. >> Exactly. And we wanted to welcome >> Exactly. And we wanted to welcome >> Exactly. And we wanted to welcome Alistar Fulton. Alistar Fulton. Alistar Fulton. >> This is his first time actually on the >> This is his first time actually on the >> This is his first time actually on the show and he's one of those people who show and he's one of those people who show and he's one of those people who always talked about being on the show always talked about being on the show always talked about being on the show and never pulled the trigger and of and never pulled the trigger and of and never pulled the trigger and of course everyone knows him as a IoT course everyone knows him as a IoT course everyone knows him as a IoT legend. You know, he used to work with legend. You know, he used to work with legend. You know, he used to work with Rob right back in Maros Microsoft. Rob right back in Maros Microsoft. Rob right back in Maros Microsoft. >> We've done that twice. >> We've done that twice. >> We've done that twice. >> We've done that twice. [clears throat] >> We've done that twice. [clears throat] >> We've done that twice. [clears throat] Yeah. Yeah. Yeah. >> World. >> World. >> World. >> Absolutely. >> Absolutely. >> Absolutely. >> You're with Blues, which was really >> You're with Blues, which was really >> You're with Blues, which was really cool, right? cool, right? cool, right? >> Yeah. Yep. >> Yeah. Yep. >> Yeah. Yep. >> Yeah. And then now you're you're on to >> Yeah. And then now you're you're on to >> Yeah. And then now you're you're on to things. things. things. >> Tell us. >> Tell us. >> Tell us. >> Yeah. >> Yeah. >> Yeah. >> Just drop some knowledge on us, Alistar. >> Just drop some knowledge on us, Alistar. >> Just drop some knowledge on us, Alistar. What are you up to now, man? What's the What are you up to now, man? What's the What are you up to now, man? What's the latest? I'm doing too many things, I latest? I'm doing too many things, I latest? I'm doing too many things, I think, is the is the I I think I I that think, is the is the I I think I I that think, is the is the I I think I I that I kept reading all these things about I kept reading all these things about I kept reading all these things about portfolio careers and then somehow by portfolio careers and then somehow by portfolio careers and then somehow by accident I ended up um before actually accident I ended up um before actually accident I ended up um before actually before I joined Blues taking on a couple before I joined Blues taking on a couple before I joined Blues taking on a couple of different um more advisory stuff. Um of different um more advisory stuff. Um of different um more advisory stuff. Um but now yeah, that's kind of I'm I'm I'm but now yeah, that's kind of I'm I'm I'm but now yeah, that's kind of I'm I'm I'm doing an acquisition search. I'm doing doing an acquisition search. I'm doing doing an acquisition search. I'm doing some fundraising. I'm doing there's a some fundraising. I'm doing there's a some fundraising. I'm doing there's a lot of companies in the space where you lot of companies in the space where you lot of companies in the space where you know without without without delving know without without without delving know without without without delving into the seriousness of it too soon. You into the seriousness of it too soon. You into the seriousness of it too soon. You know know know there's lots and lots of different um there's lots and lots of different um there's lots and lots of different um tools and technologies and everything tools and technologies and everything tools and technologies and everything else in it as we all know that's never else in it as we all know that's never else in it as we all know that's never been a problem. The problem never has been a problem. The problem never has been a problem. The problem never has been technology. The problem has been been technology. The problem has been been technology. The problem has been figuring out how to package a product figuring out how to package a product figuring out how to package a product that customers can buy and how to put it

that customers can buy and how to put it that customers can buy and how to put it in the hands of those customers. So a in the hands of those customers. So a in the hands of those customers. So a lot of what I do and have always done as lot of what I do and have always done as lot of what I do and have always done as Rob attest I I'm the least technical Rob attest I I'm the least technical Rob attest I I'm the least technical person you've ever met. Uh probably um person you've ever met. Uh probably um person you've ever met. Uh probably um >> I can pretend I can pretend to be >> I can pretend I can pretend to be >> I can pretend I can pretend to be technical with with you know technical with with you know technical with with you know >> you know what I always done is try to >> you know what I always done is try to >> you know what I always done is try to figure out the business side of things figure out the business side of things figure out the business side of things and and you know so the companies I'm and and you know so the companies I'm and and you know so the companies I'm working with at the moment they span working with at the moment they span working with at the moment they span there's a couple of companies that work there's a couple of companies that work there's a couple of companies that work in this in the solution space in the in this in the solution space in the in this in the solution space in the water industry you know there's one water industry you know there's one water industry you know there's one company that works very much on the company that works very much on the company that works very much on the hardware space you know it's helping hardware space you know it's helping hardware space you know it's helping figure out well how do you actually grow figure out well how do you actually grow figure out well how do you actually grow this market and and it boils down to how this market and and it boils down to how this market and and it boils down to how do you package something so that it do you package something so that it do you package something so that it delivers an ROI in a reasonable time delivers an ROI in a reasonable time delivers an ROI in a reasonable time frame and how do you actually give frame and how do you actually give frame and how do you actually give customers something that they can can customers something that they can can customers something that they can can and want to buy and that starts with and want to buy and that starts with and want to buy and that starts with talking to them and listening to them. talking to them and listening to them. talking to them and listening to them. And so that's what I'm I'm helping And so that's what I'm I'm helping And so that's what I'm I'm helping companies do at the moment. It's like companies do at the moment. It's like companies do at the moment. It's like you guys have figured out how to do you guys have figured out how to do you guys have figured out how to do something that's really tough and and something that's really tough and and something that's really tough and and solve it in a really interesting way solve it in a really interesting way solve it in a really interesting way right now. Let's go from that stage to right now. Let's go from that stage to right now. Let's go from that stage to the next stage which is turning into the next stage which is turning into the next stage which is turning into something that delivers value to something that delivers value to something that delivers value to customers. customers. customers. >> Rob, I think he's turning into a dirty >> Rob, I think he's turning into a dirty >> Rob, I think he's turning into a dirty word on IoT coffee.

word on IoT coffee. word on IoT coffee. >> No, he's turning into a dirty word. >> No, he's turning into a dirty word. >> No, he's turning into a dirty word. What? What? What? >> Consult. >> Consult. >> Consult. >> No, no, no. I was one of those. >> No, no, no. I was one of those. >> No, no, no. I was one of those. >> I I I I saved my time. I'm I my all of >> I I I I saved my time. I'm I my all of >> I I I I saved my time. I'm I my all of my passings have been exolved. my passings have been exolved. my passings have been exolved. [laughter] [laughter] [laughter] >> Absolutely. >> Absolutely. >> Absolutely. >> Wow. >> Wow. >> Wow. >> Many years ago, I was a management >> Many years ago, I was a management >> Many years ago, I was a management consultant who turned up in in consultant who turned up in in consultant who turned up in in three-piece suits and and and spouted three-piece suits and and and spouted three-piece suits and and and spouted nonsense. nonsense. nonsense. You made you you made some big things You made you you made some big things You made you you made some big things happen back in the UK a long time ago. happen back in the UK a long time ago. happen back in the UK a long time ago. I'm thinking of what O2 and stuff like I'm thinking of what O2 and stuff like I'm thinking of what O2 and stuff like that. that. that. >> Yeah. Yeah. >> Yeah. Yeah. >> Yeah. Yeah. >> What What was that all about back then? >> What What was that all about back then? >> What What was that all about back then? That was some cool stuff. That was some cool stuff. That was some cool stuff. >> So I I joined O2 um I I I had been >> So I I joined O2 um I I I had been >> So I I joined O2 um I I I had been before that working as a consultant a before that working as a consultant a before that working as a consultant a lot with with Vodafone um doing uh lot with with Vodafone um doing uh lot with with Vodafone um doing uh service provider acquisitions and service provider acquisitions and service provider acquisitions and customer lifetime value and all those customer lifetime value and all those customer lifetime value and all those sorts of things. Um, and I got sorts of things. Um, and I got sorts of things. Um, and I got head-hunted by uh into into what was BT head-hunted by uh into into what was BT head-hunted by uh into into what was BT Selnner on the basis of that to and they Selnner on the basis of that to and they Selnner on the basis of that to and they were like, we're going to demerge from were like, we're going to demerge from were like, we're going to demerge from British Telecom and you know, we think British Telecom and you know, we think British Telecom and you know, we think you might help be able to help us out you might help be able to help us out you might help be able to help us out with some of that. So I first went to to with some of that. So I first went to to with some of that. So I first went to to what what was BT Sellet and and you know what what was BT Sellet and and you know what what was BT Sellet and and you know became O2 um to help figure out how to became O2 um to help figure out how to became O2 um to help figure out how to separate the company from BT and separate the company from BT and separate the company from BT and figuring out who got what assets and you figuring out who got what assets and you figuring out who got what assets and you know one one of the one of the funniest know one one of the one of the funniest know one one of the one of the funniest meetings I've ever had in my life still meetings I've ever had in my life still meetings I've ever had in my life still remains the meeting in which the BT team remains the meeting in which the BT team remains the meeting in which the BT team accepted and realized that they had to accepted and realized that they had to accepted and realized that they had to pay for the 3G licenses while we had to

pay for the 3G licenses while we had to pay for the 3G licenses while we had to have them. That was that [laughter] have them. That was that [laughter] have them. That was that [laughter] was was was >> we have to pay. >> we have to pay. >> we have to pay. >> I was like really we have to but we pay >> I was like really we have to but we pay >> I was like really we have to but we pay for it and you have for it and you have for it and you have >> like yeah stock split >> like yeah stock split >> like yeah stock split >> what about think of grandma's stock >> what about think of grandma's stock >> what about think of grandma's stock portfolio when the stocks split. So I portfolio when the stocks split. So I portfolio when the stocks split. So I did that for a while. I worked with um did that for a while. I worked with um did that for a while. I worked with um CEO Dave Mlade who's great and and the CEO Dave Mlade who's great and and the CEO Dave Mlade who's great and and the CFO who then became the CEO Matthew Key. CFO who then became the CEO Matthew Key. CFO who then became the CEO Matthew Key. Um after we demerged I I spent a couple Um after we demerged I I spent a couple Um after we demerged I I spent a couple of years roving around the company of years roving around the company of years roving around the company looking for things to fix. Um, and that looking for things to fix. Um, and that looking for things to fix. Um, and that was everything from network performance was everything from network performance was everything from network performance in inside the M25, so in London, in inside the M25, so in London, in inside the M25, so in London, outsourcing the network operations to outsourcing the network operations to outsourcing the network operations to Erikson. Um, god rebrand retail stores. Erikson. Um, god rebrand retail stores. Erikson. Um, god rebrand retail stores. I I was played a small part in the O2 I I was played a small part in the O2 I I was played a small part in the O2 rebrand. Um, and then I spent a couple rebrand. Um, and then I spent a couple rebrand. Um, and then I spent a couple of years running this massive program of years running this massive program of years running this massive program that was that was that was targeted at solving kind of kind of the targeted at solving kind of kind of the targeted at solving kind of kind of the unsolved problem because BT like most, unsolved problem because BT like most, unsolved problem because BT like most, you know, most companies in the time, you know, most companies in the time, you know, most companies in the time, they bought up, you know, service they bought up, you know, service they bought up, you know, service providers when all of that reabsorption providers when all of that reabsorption providers when all of that reabsorption happened and just stuck it all together happened and just stuck it all together happened and just stuck it all together with duct tape. You know, they there with duct tape. You know, they there with duct tape. You know, they there were there were something like 30 were there were something like 30 were there were something like 30 billing engines at various places in the billing engines at various places in the billing engines at various places in the company. 370 core IT systems. Um, and company. 370 core IT systems. Um, and company. 370 core IT systems. Um, and so, uh, I' I'd spent quite a long time, so, uh, I' I'd spent quite a long time, so, uh, I' I'd spent quite a long time, like I said, the prior couple of years, like I said, the prior couple of years, like I said, the prior couple of years, highlighting, you know, here are the highlighting, you know, here are the highlighting, you know, here are the problems, here's the stack list, here problems, here's the stack list, here problems, here's the stack list, here are the things we need to solve. And the are the things we need to solve. And the are the things we need to solve. And the biggest nastiest one at the bottom was biggest nastiest one at the bottom was biggest nastiest one at the bottom was this this huge program. And in the end, this this huge program. And in the end, this this huge program. And in the end, my boss said to me, you keep going on my boss said to me, you keep going on my boss said to me, you keep going on about this, like, you know, figure it about this, like, you know, figure it about this, like, you know, figure it out. So, uh, we we and a few colleagues out. So, uh, we we and a few colleagues out. So, uh, we we and a few colleagues of mine, um, spent, uh, well, it was a

of mine, um, spent, uh, well, it was a of mine, um, spent, uh, well, it was a 2-year, um, heavy lift to begin with to 2-year, um, heavy lift to begin with to 2-year, um, heavy lift to begin with to basically rebuild a telco, um, with IBM. basically rebuild a telco, um, with IBM. basically rebuild a telco, um, with IBM. So I lived down at IBM Hersley um and So I lived down at IBM Hersley um and So I lived down at IBM Hersley um and migrate [clears throat] all of the migrate [clears throat] all of the migrate [clears throat] all of the customer bases across and then you know customer bases across and then you know customer bases across and then you know did that for a bunch of years. Um and did that for a bunch of years. Um and did that for a bunch of years. Um and then in 2004 I left the UK and went off then in 2004 I left the UK and went off then in 2004 I left the UK and went off and did other things. So so yeah it was and did other things. So so yeah it was and did other things. So so yeah it was really good. It was those early days of really good. It was those early days of really good. It was those early days of telco and the energy of we went from telco and the energy of we went from telco and the energy of we went from fourth player in a four player market to fourth player in a four player market to fourth player in a four player market to fifth player in the five player market fifth player in the five player market fifth player in the five player market when H3 Hutchinson came in pre-metric. when H3 Hutchinson came in pre-metric. when H3 Hutchinson came in pre-metric. Um, and we went from that to to being Um, and we went from that to to being Um, and we went from that to to being number one. Um, which was an amazing, number one. Um, which was an amazing, number one. Um, which was an amazing, you know, thing to be able to you know, thing to be able to you know, thing to be able to participate in and just like see, you participate in and just like see, you participate in and just like see, you know, a team like achieve that outcome know, a team like achieve that outcome know, a team like achieve that outcome when they've been beaten down for for when they've been beaten down for for when they've been beaten down for for years. years. years. >> Yeah. That's incredible. That's >> Yeah. That's incredible. That's >> Yeah. That's incredible. That's incredible. Wow. You did a lot of stuff. incredible. Wow. You did a lot of stuff. incredible. Wow. You did a lot of stuff. >> Not about technology, about people, >> Not about technology, about people, >> Not about technology, about people, right? right? right? >> It is the business. Yeah. Well, it's so >> It is the business. Yeah. Well, it's so >> It is the business. Yeah. Well, it's so funny, you know, like like lately, you funny, you know, like like lately, you funny, you know, like like lately, you know, we've talked about this whole know, we've talked about this whole know, we've talked about this whole multicloud thing and companies and AWS multicloud thing and companies and AWS multicloud thing and companies and AWS and others go, "Why would you find and others go, "Why would you find and others go, "Why would you find yourself doing a multicloud? I don't yourself doing a multicloud? I don't yourself doing a multicloud? I don't understand." It's just what Alistar's understand." It's just what Alistar's understand." It's just what Alistar's talking about. It's the all this M&A talking about. It's the all this M&A talking about. It's the all this M&A activity. All of a sudden, you've activity. All of a sudden, you've activity. All of a sudden, you've acquired another business and they're acquired another business and they're acquired another business and they're using a different cloud. [laughter] using a different cloud. [laughter] using a different cloud. [laughter] >> They're using Asure and whatever.

>> They're using Asure and whatever. >> They're using Asure and whatever. >> Think about the US. >> Think about the US. >> Think about the US. >> Yeah. Think about the US. Telos's in the >> Yeah. Think about the US. Telos's in the >> Yeah. Think about the US. Telos's in the US. when I, you know, first time I went US. when I, you know, first time I went US. when I, you know, first time I went up to Seattle was for AT&T. We're doing up to Seattle was for AT&T. We're doing up to Seattle was for AT&T. We're doing um back in the day we brought in the Tom um back in the day we brought in the Tom um back in the day we brought in the Tom architecture you know the you know telco architecture you know the you know telco architecture you know the you know telco operating model and architecture and we operating model and architecture and we operating model and architecture and we tried to unravel the massive spaghetti tried to unravel the massive spaghetti tried to unravel the massive spaghetti mess that they had legacy systems trying mess that they had legacy systems trying mess that they had legacy systems trying to figure out how to integrate the data to figure out how to integrate the data to figure out how to integrate the data you know create workflows and then the you know create workflows and then the you know create workflows and then the all this stuff uh became the precursor all this stuff uh became the precursor all this stuff uh became the precursor and predecessor to OSSBSS right because and predecessor to OSSBSS right because and predecessor to OSSBSS right because we were using seable to layer on top a we were using seable to layer on top a we were using seable to layer on top a uh you know that whole CRM layer. Um but uh you know that whole CRM layer. Um but uh you know that whole CRM layer. Um but it was a bunch of disconnected systems. it was a bunch of disconnected systems. it was a bunch of disconnected systems. It it's incredible and It it's incredible and It it's incredible and >> wow >> wow >> wow >> and that that that's why it's funny when >> and that that that's why it's funny when >> and that that that's why it's funny when people say hey you know just you know do people say hey you know just you know do people say hey you know just you know do single platform blah blah blah you know single platform blah blah blah you know single platform blah blah blah you know you can have a single system do you can have a single system do you can have a single system do everything. Good freaking everything. Good freaking everything. Good freaking did that really was Vodafone at the did that really was Vodafone at the did that really was Vodafone at the time. So Vodafone's motives operandi was time. So Vodafone's motives operandi was time. So Vodafone's motives operandi was you know you you acquire and the whole you know you you acquire and the whole you know you you acquire and the whole service provider model was kind of a service provider model was kind of a service provider model was kind of a crazy thing for a period where you know crazy thing for a period where you know crazy thing for a period where you know the government basically said retail the government basically said retail the government basically said retail operations and network operations need operations and network operations need operations and network operations need to be to be to be >> um and you know when they when they >> um and you know when they when they >> um and you know when they when they rolled that back it was like a you know rolled that back it was like a you know rolled that back it was like a you know everyone went out to try and buy everyone went out to try and buy everyone went out to try and buy Vodafone you know had probably the Vodafone you know had probably the Vodafone you know had probably the deepest pockets they also you know day deepest pockets they also you know day deepest pockets they also you know day zero after the acquisition closed you zero after the acquisition closed you zero after the acquisition closed you know the low loader would turn up they'd

know the low loader would turn up they'd know the low loader would turn up they'd rip out the the entire you know back end rip out the the entire you know back end rip out the the entire you know back end and replace it with the vod ifying back and replace it with the vod ifying back and replace it with the vod ifying back end which I mean end which I mean end which I mean >> honestly was painful but it gave them a >> honestly was painful but it gave them a >> honestly was painful but it gave them a degree of agility to setting new tariffs degree of agility to setting new tariffs degree of agility to setting new tariffs I mean if you create a new tariff and I mean if you create a new tariff and I mean if you create a new tariff and you have to roll it out through 37 I you have to roll it out through 37 I you have to roll it out through 37 I think it was billing engines I mean think it was billing engines I mean think it was billing engines I mean forget about it takes 18 months to forget about it takes 18 months to forget about it takes 18 months to change a tariff vodafone could do that change a tariff vodafone could do that change a tariff vodafone could do that in a month um and so they that's why in a month um and so they that's why in a month um and so they that's why they at everybody else's lunch for a they at everybody else's lunch for a they at everybody else's lunch for a good period good period good period >> I mean yeah >> I mean yeah >> I mean yeah >> I think one of the best roles and most >> I think one of the best roles and most >> I think one of the best roles and most sustainable roles is systems integrator sustainable roles is systems integrator sustainable roles is systems integrator you I mean, as much as there's all this you I mean, as much as there's all this you I mean, as much as there's all this talk that, [clears throat] talk that, [clears throat] talk that, [clears throat] >> oh, we don't need coders or developers >> oh, we don't need coders or developers >> oh, we don't need coders or developers or tech people anymore, no, you need or tech people anymore, no, you need or tech people anymore, no, you need people who can stitch all this stuff people who can stitch all this stuff people who can stitch all this stuff together cuz it doesn't happen by together cuz it doesn't happen by together cuz it doesn't happen by itself, right? And all these folks going itself, right? And all these folks going itself, right? And all these folks going bonkers about MCP, they think that, oh, bonkers about MCP, they think that, oh, bonkers about MCP, they think that, oh, hey, you know, the agent will just know. hey, you know, the agent will just know. hey, you know, the agent will just know. No, it won't know. [laughter] No, it won't know. [laughter] No, it won't know. [laughter] What the hell are you talking about? So, What the hell are you talking about? So, What the hell are you talking about? So, there's more and more talk about MCP and there's more and more talk about MCP and there's more and more talk about MCP and how it's some sort of panacia for how it's some sort of panacia for how it's some sort of panacia for systems integration. I just I laugh and systems integration. I just I laugh and systems integration. I just I laugh and you know there was um an analyst who's you know there was um an analyst who's you know there was um an analyst who's just going crazy over the stuff and I just going crazy over the stuff and I just going crazy over the stuff and I just put one uh one little phrase it just put one uh one little phrase it just put one uh one little phrase it says the problem is going to be the says the problem is going to be the says the problem is going to be the human language right it it's imprecise human language right it it's imprecise human language right it it's imprecise especially English or you know especially English or you know especially English or you know non-Chinese languages are very imprecise non-Chinese languages are very imprecise non-Chinese languages are very imprecise there's a thing called semantic there's a thing called semantic there's a thing called semantic specificity specificity specificity uh which I'm going to pontificate about uh which I'm going to pontificate about uh which I'm going to pontificate about up in here up in here up in here >> oh my god in living color. Here we

>> oh my god in living color. Here we >> oh my god in living color. Here we [laughter] go. Yes. [laughter and snorts] [laughter and snorts] >> Let me secrete my conversation. >> Let me secrete my conversation. >> Let me secrete my conversation. >> Absolutely. >> Absolutely. >> Absolutely. >> To your general direction. >> To your general direction. >> To your general direction. >> There's no writing, I think. >> There's no writing, I think. >> There's no writing, I think. >> Yes. >> Yes. >> Yes. >> But you know what I'm saying? It's like >> But you know what I'm saying? It's like >> But you know what I'm saying? It's like human language is imprecise. And so this human language is imprecise. And so this human language is imprecise. And so this idea that somehow agents are going to idea that somehow agents are going to idea that somehow agents are going to understand everything precisely and then understand everything precisely and then understand everything precisely and then give you the outcomes that you're give you the outcomes that you're give you the outcomes that you're expecting that configuration. It's a expecting that configuration. It's a expecting that configuration. It's a freaking freaking freaking >> doesn't even work for a nano banana. I >> doesn't even work for a nano banana. I >> doesn't even work for a nano banana. I mean how's it going to work for mean how's it going to work for mean how's it going to work for [laughter] [laughter] [laughter] a a a >> break >> break >> break it's even worse like that. We talked it's even worse like that. We talked it's even worse like that. We talked about that on the show. The problem is about that on the show. The problem is about that on the show. The problem is actually when it comes to system actually when it comes to system actually when it comes to system integration, you're usually talking integration, you're usually talking integration, you're usually talking about information stored in databases about information stored in databases about information stored in databases >> and and language model are not designed >> and and language model are not designed >> and and language model are not designed to read databases. They are designed to to read databases. They are designed to to read databases. They are designed to read the imprecise read the imprecise read the imprecise >> human language and assidate some of the >> human language and assidate some of the >> human language and assidate some of the time. So that nobody has still cracked time. So that nobody has still cracked time. So that nobody has still cracked the issue of how do I transform all this the issue of how do I transform all this the issue of how do I transform all this structure SQL or even sequential data in structure SQL or even sequential data in structure SQL or even sequential data in something that gen AI can use. Mhm.

something that gen AI can use. Mhm. something that gen AI can use. Mhm. >> Yeah. >> Yeah. >> Yeah. >> By the way, I like your uh Dimmitri, I >> By the way, I like your uh Dimmitri, I >> By the way, I like your uh Dimmitri, I like your wallpaper there. like your wallpaper there. like your wallpaper there. [clears throat] [clears throat] [clears throat] >> I always admire that as well. >> I always admire that as well. >> I always admire that as well. >> Yeah. AI generated, man. >> Yeah. AI generated, man. >> Yeah. AI generated, man. >> Wow. Wow. Yeah. You know, um we we >> Wow. Wow. Yeah. You know, um we we >> Wow. Wow. Yeah. You know, um we we Anyway. Yeah. Yeah. So, Anyway. Yeah. Yeah. So, Anyway. Yeah. Yeah. So, >> you don't even know what you're saying, >> you don't even know what you're saying, >> you don't even know what you're saying, do you, Leonard? Just like do you, Leonard? Just like do you, Leonard? Just like >> I'm just reading his wallpaper, which >> I'm just reading his wallpaper, which >> I'm just reading his wallpaper, which now everyone's going to do. now everyone's going to do. now everyone's going to do. >> Something about sitting on zero trust >> Something about sitting on zero trust >> Something about sitting on zero trust something. something. something. I thought Yeah, the zero's MFA enrolled. I thought Yeah, the zero's MFA enrolled. I thought Yeah, the zero's MFA enrolled. >> Yeah, MFA enrolled. >> Yeah, MFA enrolled. >> Yeah, MFA enrolled. [clears throat] [clears throat] [clears throat] >> I think the wallpaper's real and >> I think the wallpaper's real and >> I think the wallpaper's real and Dimmitri's AI generated. Dimmitri's AI generated. Dimmitri's AI generated. >> Maybe that's what it is. I think that's >> Maybe that's what it is. I think that's >> Maybe that's what it is. I think that's what what what >> Exactly. That's what it is. >> Exactly. That's what it is. >> Exactly. That's what it is. >> We're actually getting close to that. By >> We're actually getting close to that. By >> We're actually getting close to that. By the way, well, the way, well, the way, well, >> systems integration is the job of the >> systems integration is the job of the >> systems integration is the job of the future. future. future. >> Exactly. >> Exactly. >> Exactly. >> AI plumbers, AI baby, >> AI plumbers, AI baby, >> AI plumbers, AI baby, >> people that are willing to get their >> people that are willing to get their >> people that are willing to get their hands dirty always have work. people hands dirty always have work. people hands dirty always have work. people that are willing to get their hands that are willing to get their hands that are willing to get their hands dirty and uh dirty and uh dirty and uh >> gap of the ugly.

>> gap of the ugly. >> gap of the ugly. >> Yeah, it is. It's it's reality. So, >> Yeah, it is. It's it's reality. So, >> Yeah, it is. It's it's reality. So, >> yeah. >> yeah. >> yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Great advice to all you people out there >> Great advice to all you people out there >> Great advice to all you people out there looking for a job. Be willing to get looking for a job. Be willing to get looking for a job. Be willing to get your hands dirty. Go do the ugly stuff. your hands dirty. Go do the ugly stuff. your hands dirty. Go do the ugly stuff. Do stuff that people don't want to do. Do stuff that people don't want to do. Do stuff that people don't want to do. Do unin interesting things. Do unin interesting things. Do unin interesting things. >> Go after boring businesses. Yeah. >> Go after boring businesses. Yeah. >> Go after boring businesses. Yeah. >> Hasn't that always been that's been IoT? >> Hasn't that always been that's been IoT? >> Hasn't that always been that's been IoT? I think you know where you look at where I think you know where you look at where I think you know where you look at where solutions have been adopted. I mean it's solutions have been adopted. I mean it's solutions have been adopted. I mean it's like Rob certainly takes there's an old like Rob certainly takes there's an old like Rob certainly takes there's an old English saying where there's muck English saying where there's muck English saying where there's muck there's brass you know where there's there's brass you know where there's there's brass you know where there's where there's to do there's cash where there's to do there's cash where there's to do there's cash and boring jobs which have marginal and boring jobs which have marginal and boring jobs which have marginal you know value per unit but can in the you know value per unit but can in the you know value per unit but can in the mass do something that's that's you know mass do something that's that's you know mass do something that's that's you know that's always been I think um the place that's always been I think um the place that's always been I think um the place of traction of traction of traction the new fun exciting stuff is is I don't the new fun exciting stuff is is I don't the new fun exciting stuff is is I don't see that's I don't think that's what IoT see that's I don't think that's what IoT see that's I don't think that's what IoT is really about. It is about solving is really about. It is about solving is really about. It is about solving mundane problems, you know, at mundane problems, you know, at mundane problems, you know, at >> um in a way that people don't want to >> um in a way that people don't want to >> um in a way that people don't want to do. You can't be bothered to do. do. You can't be bothered to do. do. You can't be bothered to do. >> Yeah. >> Yeah. >> Yeah. >> Yeah. You're right. >> Yeah. You're right. >> Yeah. You're right. >> True. >> True. >> True. >> You know, I remember getting I remember >> You know, I remember getting I remember >> You know, I remember getting I remember talk I don't know if you know this guy talk I don't know if you know this guy talk I don't know if you know this guy Steve saying he was the CEO Concur, you Steve saying he was the CEO Concur, you Steve saying he was the CEO Concur, you know, Concur like travel inside, know, Concur like travel inside, know, Concur like travel inside, >> you know, they're in Belleview and they >> you know, they're in Belleview and they >> you know, they're in Belleview and they ultimately got acquired by SAP. But his ultimately got acquired by SAP. But his ultimately got acquired by SAP. But his talk his he was like yeah we just went talk his he was like yeah we just went talk his he was like yeah we just went after the most uninteresting boring after the most uninteresting boring after the most uninteresting boring business that no one was interested in business that no one was interested in business that no one was interested in doing you know corporate travel doing you know corporate travel doing you know corporate travel and what's funny I don't know if they and what's funny I don't know if they and what's funny I don't know if they changed it now this is a techy thing but changed it now this is a techy thing but changed it now this is a techy thing but for years whenever I'd use Concur I for years whenever I'd use Concur I for years whenever I'd use Concur I would notice it was still using classic

would notice it was still using classic would notice it was still using classic ASP classic active server pages when I ASP classic active server pages when I ASP classic active server pages when I say that that's ASP from the '9s like say that that's ASP from the '9s like say that that's ASP from the '9s like this interpreted thing with VBScript it this interpreted thing with VBScript it this interpreted thing with VBScript it wasn't net or anything wasn't net or anything wasn't net or anything And And And >> I I I always sometimes I'm like this >> I I I always sometimes I'm like this >> I I I always sometimes I'm like this tech contrarian, you know, when people tech contrarian, you know, when people tech contrarian, you know, when people say you need this latest, greatest, say you need this latest, greatest, say you need this latest, greatest, whatever, and you can't scale unless you whatever, and you can't scale unless you whatever, and you can't scale unless you have that. I'm like, that is such BS. have that. I'm like, that is such BS. have that. I'm like, that is such BS. You'd be amazed at what you can do with You'd be amazed at what you can do with You'd be amazed at what you can do with old stuff. And Concur is a great old stuff. And Concur is a great old stuff. And Concur is a great example. It was all built on old stuff example. It was all built on old stuff example. It was all built on old stuff and it works fine, you know? and it works fine, you know? and it works fine, you know? >> I know. I remember you upsetting lots of >> I know. I remember you upsetting lots of >> I know. I remember you upsetting lots of engineers doing that. engineers doing that. engineers doing that. >> Yeah, absolutely. >> Yeah, absolutely. >> Yeah, absolutely. >> Do that crap. You just do it this way. >> Do that crap. You just do it this way. >> Do that crap. You just do it this way. This is a much simpler way. This is a much simpler way. This is a much simpler way. >> Yeah, but it's through the >> Yeah, but it's through the >> Yeah, but it's through the Absolutely. Absolutely. Um, you know, Absolutely. Absolutely. Um, you know, Absolutely. Absolutely. Um, you know, it's been refreshing. I've seen some, it's been refreshing. I've seen some, it's been refreshing. I've seen some, uh, you know, big-time tech people uh, you know, big-time tech people uh, you know, big-time tech people making some comments in the press around making some comments in the press around making some comments in the press around like startups building whatever it is, like startups building whatever it is, like startups building whatever it is, and they feel the need right away to and they feel the need right away to and they feel the need right away to make sure that it's designed to for make sure that it's designed to for make sure that it's designed to for global scale and a bunch of other hard global scale and a bunch of other hard global scale and a bunch of other hard things and and and that's the that's the things and and and that's the that's the things and and and that's the that's the right way to do it. And the the reality right way to do it. And the the reality right way to do it. And the the reality is it's like, you know what, if you're is it's like, you know what, if you're is it's like, you know what, if you're lucky, if you're still in business 5 lucky, if you're still in business 5 lucky, if you're still in business 5 years from now, maybe you can worry years from now, maybe you can worry years from now, maybe you can worry about that. Why don't you just get it about that. Why don't you just get it about that. Why don't you just get it working on some kind of low scale that working on some kind of low scale that working on some kind of low scale that you can get to market really really you can get to market really really you can get to market really really fast, you know, and just get something fast, you know, and just get something fast, you know, and just get something out there. So many people spend so much, out there. So many people spend so much, out there. So many people spend so much, they overengineer things. Um, you know, they overengineer things. Um, you know, they overengineer things. Um, you know, and they're like, "Oh, and they're like, "Oh, and they're like, "Oh, >> your customer get in the hand of your >> your customer get in the hand of your >> your customer get in the hand of your customer. Your customer will tell you customer. Your customer will tell you customer. Your customer will tell you faster than you will ever figure out faster than you will ever figure out faster than you will ever figure out yourself where you got it wrong and yourself where you got it wrong and yourself where you got it wrong and you're not trying to figure out how to

you're not trying to figure out how to you're not trying to figure out how to get it right." get it right." get it right." >> Are you saying that if your VP is back, >> Are you saying that if your VP is back, >> Are you saying that if your VP is back, Rob? Are you defending the Rob? Are you defending the Rob? Are you defending the >> No, not necessarily. But but but I'll >> No, not necessarily. But but but I'll >> No, not necessarily. But but but I'll have conversations with folks and and have conversations with folks and and have conversations with folks and and they'll, you know, it's like they'll, you know, it's like they'll, you know, it's like I would say these days whatever it is I would say these days whatever it is I would say these days whatever it is you're building, you know, if it's some you're building, you know, if it's some you're building, you know, if it's some kind of web app or whatever and you're kind of web app or whatever and you're kind of web app or whatever and you're using a D, you know, use Postgress or using a D, you know, use Postgress or using a D, you know, use Postgress or whatever, just build that thing and get whatever, just build that thing and get whatever, just build that thing and get it working and maybe it'll scale to it working and maybe it'll scale to it working and maybe it'll scale to thousands of people or whatever and it's thousands of people or whatever and it's thousands of people or whatever and it's not going to scale to millions, but not going to scale to millions, but not going to scale to millions, but that's okay. Um because it does seem that's okay. Um because it does seem that's okay. Um because it does seem contrarian because I hear lots of people contrarian because I hear lots of people contrarian because I hear lots of people who are just like no you got to go all who are just like no you got to go all who are just like no you got to go all in and build the you know you need to in and build the you know you need to in and build the you know you need to build this on Cosmos DB or something build this on Cosmos DB or something build this on Cosmos DB or something like that and have global scale by day like that and have global scale by day like that and have global scale by day one and it's like you don't actually you one and it's like you don't actually you one and it's like you don't actually you know because you probably won't be in know because you probably won't be in know because you probably won't be in business statistically speaking you're business statistically speaking you're business statistically speaking you're already not going to make it which already not going to make it which already not going to make it which really sucks to say that [laughter] really sucks to say that [laughter] really sucks to say that [laughter] >> but you might have a better chance you >> but you might have a better chance you >> but you might have a better chance you know know know >> it's like like >> it's like like >> it's like like It was like that agriculture IoT stuff I It was like that agriculture IoT stuff I It was like that agriculture IoT stuff I would do and people were saying I was would do and people were saying I was would do and people were saying I was like let me give you some hint. I could like let me give you some hint. I could like let me give you some hint. I could build something that would cover every build something that would cover every build something that would cover every farm in the state of Washington on a farm in the state of Washington on a farm in the state of Washington on a single server and a single database. I'm single server and a single database. I'm single server and a single database. I'm not worried about that IoT for that. I'm not worried about that IoT for that. I'm not worried about that IoT for that. I'm just getting little chirps of data every just getting little chirps of data every just getting little chirps of data every 30 minutes. Give me a break. It's 30 minutes. Give me a break. It's 30 minutes. Give me a break. It's nothing. I always remind people nothing. I always remind people nothing. I always remind people especially I love the people say if especially I love the people say if especially I love the people say if you're not using some kind of Cassandra you're not using some kind of Cassandra you're not using some kind of Cassandra or you know whatever NoSQL database you or you know whatever NoSQL database you or you know whatever NoSQL database you can't scale. was like, "Have you ever can't scale. was like, "Have you ever can't scale. was like, "Have you ever heard of the stock market?" I go, "You

heard of the stock market?" I go, "You heard of the stock market?" I go, "You know, it's down there in New York. You know, it's down there in New York. You know, it's down there in New York. You know, they've got this whole stock know, they've got this whole stock know, they've got this whole stock exchange running on Oracle relational exchange running on Oracle relational exchange running on Oracle relational databases doing billions of transactions databases doing billions of transactions databases doing billions of transactions a day. a day. a day. >> It's cybase. It's not Oracle. It's >> It's cybase. It's not Oracle. It's >> It's cybase. It's not Oracle. It's >> Oracle. It's Oracle. It used to be >> Oracle. It's Oracle. It used to be >> Oracle. It's Oracle. It used to be cybase. It's Oracle." Um, but [laughter] cybase. It's Oracle." Um, but [laughter] cybase. It's Oracle." Um, but [laughter] but the but the the talk the message but the but the the talk the message but the but the the talk the message there though is this old that there though is this old that there though is this old that apparently is out of fashion actually is apparently is out of fashion actually is apparently is out of fashion actually is doing the most serious transactional doing the most serious transactional doing the most serious transactional load of anything on the planet. And so load of anything on the planet. And so load of anything on the planet. And so it's like, you know, if it can do that, it's like, you know, if it can do that, it's like, you know, if it can do that, I can probably handle little tiny bits I can probably handle little tiny bits I can probably handle little tiny bits of data from a moisture sensor. of data from a moisture sensor. of data from a moisture sensor. >> Green screen. >> Green screen. >> Green screen. >> So >> So >> So >> there you go. Are you saying that if >> there you go. Are you saying that if >> there you go. Are you saying that if you're building an industrial IoT you're building an industrial IoT you're building an industrial IoT platform, you don't need to build your platform, you don't need to build your platform, you don't need to build your old cloud? old cloud? old cloud? >> What? [laughter] >> What? [laughter] >> What? [laughter] >> What? >> What? >> What? >> Hey, man, you're insulting my history. >> Hey, man, you're insulting my history. >> Hey, man, you're insulting my history. >> No, but the but Well, yeah. Well, yes, >> No, but the but Well, yeah. Well, yes, >> No, but the but Well, yeah. Well, yes, we remember things about certain uh we remember things about certain uh we remember things about certain uh executives at GE thinking they needed to executives at GE thinking they needed to executives at GE thinking they needed to build a cloud for predicts and dropping build a cloud for predicts and dropping build a cloud for predicts and dropping billions of dollars that would turn into billions of dollars that would turn into billions of dollars that would turn into a write-off and ultimately lead to the a write-off and ultimately lead to the a write-off and ultimately lead to the destruction of GE digital and then the destruction of GE digital and then the destruction of GE digital and then the whole company. So, yeah.

whole company. So, yeah. whole company. So, yeah. >> Yeah. You know, you know what was weird >> Yeah. You know, you know what was weird >> Yeah. You know, you know what was weird that the talk that the talk that the talk >> I was >> I was >> I was >> Yeah. And you know the talk >> Yeah. And you know the talk >> Yeah. And you know the talk >> nobody listened to me but I was there. >> nobody listened to me but I was there. >> nobody listened to me but I was there. >> The thing I mean the thing is a lot of >> The thing I mean the thing is a lot of >> The thing I mean the thing is a lot of this is you know the the the I have the this is you know the the the I have the this is you know the the the I have the privilege now of of drawing on years of privilege now of of drawing on years of privilege now of of drawing on years of screwing things up and getting it wrong screwing things up and getting it wrong screwing things up and getting it wrong to say to people like don't do that. to say to people like don't do that. to say to people like don't do that. That's a really bad idea cuz I tried That's a really bad idea cuz I tried That's a really bad idea cuz I tried that before and it didn't [laughter] that before and it didn't [laughter] that before and it didn't [laughter] work. So but with the startups I I'm work. So but with the startups I I'm work. So but with the startups I I'm working with it's like look solve focus working with it's like look solve focus working with it's like look solve focus on the thing where you're building on the thing where you're building on the thing where you're building unique IP where you you are solving a unique IP where you you are solving a unique IP where you you are solving a problem that no one else has solved. problem that no one else has solved. problem that no one else has solved. building a hypers scale cloud solution, building a hypers scale cloud solution, building a hypers scale cloud solution, you if you're lucky, you're going to get you if you're lucky, you're going to get you if you're lucky, you're going to get acquired by someone who already knows acquired by someone who already knows acquired by someone who already knows how to do that better than you do and how to do that better than you do and how to do that better than you do and knows how to do that like this. Spend knows how to do that like this. Spend knows how to do that like this. Spend your investor's money on trying to solve your investor's money on trying to solve your investor's money on trying to solve that problem. Even if you're trying to that problem. Even if you're trying to that problem. Even if you're trying to do it in a different way, it doesn't do it in a different way, it doesn't do it in a different way, it doesn't matter. Spend your investor's money on matter. Spend your investor's money on matter. Spend your investor's money on solving the thing that no one else has solving the thing that no one else has solving the thing that no one else has solved and just stick the rest of it solved and just stick the rest of it solved and just stick the rest of it together. You know, like you said, Rob, together. You know, like you said, Rob, together. You know, like you said, Rob, as long as it works, you know, as long as long as it works, you know, as long as long as it works, you know, as long as you can deliver a a service to your as you can deliver a a service to your as you can deliver a a service to your customer to the extent to which they can customer to the extent to which they can customer to the extent to which they can give you feedback and you can figure out give you feedback and you can figure out give you feedback and you can figure out how to improve it, you're good. You how to improve it, you're good. You how to improve it, you're good. You know, focus on that.

know, focus on that. know, focus on that. >> Focus on the other stuff. >> Focus on the other stuff. >> Focus on the other stuff. >> Yeah. Based on what you just said, >> Yeah. Based on what you just said, >> Yeah. Based on what you just said, Alistar, it seems like, you know, we Alistar, it seems like, you know, we Alistar, it seems like, you know, we have a culture now of, you know, have a culture now of, you know, have a culture now of, you know, companies that don't focus on actually companies that don't focus on actually companies that don't focus on actually building a business like Bill, right? Um building a business like Bill, right? Um building a business like Bill, right? Um what we have are a bunch of companies what we have are a bunch of companies what we have are a bunch of companies that are chasing uh that exit right and that are chasing uh that exit right and that are chasing uh that exit right and a lot of that is about catering to hyped a lot of that is about catering to hyped a lot of that is about catering to hyped driven um demand expectations right so driven um demand expectations right so driven um demand expectations right so at some point the hope is okay something at some point the hope is okay something at some point the hope is okay something like metaverse industrial metaverse like metaverse industrial metaverse like metaverse industrial metaverse we'll call ourselves that and hopefully we'll call ourselves that and hopefully we'll call ourselves that and hopefully we'll get picked up by you know one of we'll get picked up by you know one of we'll get picked up by you know one of these big big players who's banking on these big big players who's banking on these big big players who's banking on uh you know this nonsense and then we'll uh you know this nonsense and then we'll uh you know this nonsense and then we'll have an exit and um we'll go on to our have an exit and um we'll go on to our have an exit and um we'll go on to our next thing. And I mean I next thing. And I mean I next thing. And I mean I and that's probably one of the issues and that's probably one of the issues and that's probably one of the issues that we have out there and and why I that we have out there and and why I that we have out there and and why I think you know when I talk to a lot of think you know when I talk to a lot of think you know when I talk to a lot of um startups um startups um startups that seems to be their mentality and that seems to be their mentality and that seems to be their mentality and they're rather than married and having they're rather than married and having they're rather than married and having an appetite actually rather than having an appetite actually rather than having an appetite actually rather than having an appetite for real numbers they don't an appetite for real numbers they don't an appetite for real numbers they don't give a They want the biggest give a They want the biggest give a They want the biggest number possible and um you know I have number possible and um you know I have number possible and um you know I have to keep telling them these numbers are to keep telling them these numbers are to keep telling them these numbers are BS and if you actually want to you know BS and if you actually want to you know BS and if you actually want to you know build a real business this shouldn't be build a real business this shouldn't be build a real business this shouldn't be your this aren't the numbers you want to your this aren't the numbers you want to your this aren't the numbers you want to go by go by go by and so

and so and so >> the AI kind of >> the AI kind of >> the AI kind of >> yeah bubble at the moment I mean it's >> yeah bubble at the moment I mean it's >> yeah bubble at the moment I mean it's like a lot of the investors the VCs that like a lot of the investors the VCs that like a lot of the investors the VCs that I work with I mean they're sick and I work with I mean they're sick and I work with I mean they're sick and tired of hearing these massive pitches tired of hearing these massive pitches tired of hearing these massive pitches that we're going build this AI based that we're going build this AI based that we're going build this AI based thing that's going to be and there's thing that's going to be and there's thing that's going to be and there's going to be 10 billion [clears throat] going to be 10 billion [clears throat] going to be 10 billion [clears throat] customers and customers and customers and >> we have a magenta framework. >> we have a magenta framework. >> we have a magenta framework. >> Yeah. And it it's we're doing the same >> Yeah. And it it's we're doing the same >> Yeah. And it it's we're doing the same thing with AI that we did with IoT. We thing with AI that we did with IoT. We thing with AI that we did with IoT. We we're AI is the is the solution for we're AI is the is the solution for we're AI is the is the solution for everything when you know in reality you everything when you know in reality you everything when you know in reality you know for operating businesses. The know for operating businesses. The know for operating businesses. The challenge in an operating business is challenge in an operating business is challenge in an operating business is getting a bunch of people to do a getting a bunch of people to do a getting a bunch of people to do a sensible set of things at the same time sensible set of things at the same time sensible set of things at the same time in a way that delivers value to a in a way that delivers value to a in a way that delivers value to a customer. And an AI is not going to do customer. And an AI is not going to do customer. And an AI is not going to do that for you. you know, there are some that for you. you know, there are some that for you. you know, there are some some folks that I'm working with at the some folks that I'm working with at the some folks that I'm working with at the moment actually. It's like look, the the moment actually. It's like look, the the moment actually. It's like look, the the the what you're building is not going to the what you're building is not going to the what you're building is not going to solve for this wider human operational solve for this wider human operational solve for this wider human operational problem. People don't behave logically. problem. People don't behave logically. problem. People don't behave logically. Even if the system is telling them to do Even if the system is telling them to do Even if the system is telling them to do X, you know, they actually need to want X, you know, they actually need to want X, you know, they actually need to want to do X and doing X needs to make sense to do X and doing X needs to make sense to do X and doing X needs to make sense in the broader context of what they're in the broader context of what they're in the broader context of what they're trying, you know, you can't because I do trying, you know, you can't because I do trying, you know, you can't because I do what I we're I think we're already there what I we're I think we're already there what I we're I think we're already there with AI. We're in this huge great big with AI. We're in this huge great big with AI. We're in this huge great big hype, you know, cycle. Everyone's hype, you know, cycle. Everyone's hype, you know, cycle. Everyone's running around with their head on fire running around with their head on fire running around with their head on fire trying to figure out what their AI trying to figure out what their AI trying to figure out what their AI strategy is. Large enterprises are strategy is. Large enterprises are strategy is. Large enterprises are buying small startups just so that they buying small startups just so that they buying small startups just so that they can check the box. You know, I spent $50 can check the box. You know, I spent $50 can check the box. You know, I spent $50 million on this startup. Not sure what million on this startup. Not sure what million on this startup. Not sure what the product is. Um I'm not sure what the the product is. Um I'm not sure what the the product is. Um I'm not sure what the value is, but it's an AI thing. So now value is, but it's an AI thing. So now value is, but it's an AI thing. So now we've got an AI strategy [clears throat] we've got an AI strategy [clears throat] we've got an AI strategy [clears throat] and we've got chief AI officer who used and we've got chief AI officer who used and we've got chief AI officer who used to be the CEO. You know, we're going to to be the CEO. You know, we're going to to be the CEO. You know, we're going to spend the same kind of nuclear winter spend the same kind of nuclear winter spend the same kind of nuclear winter that we spent in IoT for 10 years

that we spent in IoT for 10 years that we spent in IoT for 10 years wondering what the hell, you know, we wondering what the hell, you know, we wondering what the hell, you know, we did. Well, yeah, I agree. Yeah. Same did. Well, yeah, I agree. Yeah. Same did. Well, yeah, I agree. Yeah. Same same crap, different flavor is I say and same crap, different flavor is I say and same crap, different flavor is I say and it's going to really cut out of the it's going to really cut out of the it's going to really cut out of the money the investment space because, you money the investment space because, you money the investment space because, you know, investors are already deeply know, investors are already deeply know, investors are already deeply cynical cynical cynical >> and so getting them to to put cash into >> and so getting them to to put cash into >> and so getting them to to put cash into real real real >> but I don't agree it's you know >> but I don't agree it's you know >> but I don't agree it's you know >> I don't agree it's the same Um so >> I don't agree it's the same Um so >> I don't agree it's the same Um so AI digative it's very tangible and IoT AI digative it's very tangible and IoT AI digative it's very tangible and IoT was not. was not. was not. >> I did say different flavor should >> I did say different flavor should >> I did say different flavor should >> okay >> okay >> okay >> taste different. Well, I think you also >> taste different. Well, I think you also >> taste different. Well, I think you also have to separate you have to separate have to separate you have to separate have to separate you have to separate the kind of IT AI workloads versus OT AI the kind of IT AI workloads versus OT AI the kind of IT AI workloads versus OT AI workloads. So, workloads. So, workloads. So, >> I think there's a difference there. So, >> I think there's a difference there. So, >> I think there's a difference there. So, I think there's a lot of IT AI workloads I think there's a lot of IT AI workloads I think there's a lot of IT AI workloads stuff that's very stuff that's very stuff that's very >> loosey goosey in terms of return on >> loosey goosey in terms of return on >> loosey goosey in terms of return on investment, right? But investment, right? But investment, right? But >> if it's done with if it's done with >> if it's done with if it's done with >> if it's done with if it's done with purpose for OT then you know then it can purpose for OT then you know then it can purpose for OT then you know then it can have a lot of tangible benefits if it's have a lot of tangible benefits if it's have a lot of tangible benefits if it's thought out ahead of time thought out ahead of time thought out ahead of time >> in terms of really you know like >> in terms of really you know like >> in terms of really you know like manufacturing defects and agriculture manufacturing defects and agriculture manufacturing defects and agriculture and healthcare and like there's a lot of and healthcare and like there's a lot of and healthcare and like there's a lot of problems to be solved out there if you problems to be solved out there if you problems to be solved out there if you think it through from the OT side but a think it through from the OT side but a think it through from the OT side but a lot of the IT you know I have a really lot of the IT you know I have a really lot of the IT you know I have a really cool foundational model that's better cool foundational model that's better cool foundational model that's better than someone else's and I put some APIs than someone else's and I put some APIs than someone else's and I put some APIs on it and then I raise a bunch of money on it and then I raise a bunch of money on it and then I raise a bunch of money around it. That's I think I just around it. That's I think I just around it. That's I think I just described Open AI by the way, but described Open AI by the way, but described Open AI by the way, but [laughter] um [laughter] um [laughter] um who's currently worth $900 billion.

who's currently worth $900 billion. who's currently worth $900 billion. >> I know. I know. I saw that the >> I know. I know. I saw that the >> I know. I know. I saw that the investment in their mind investment in their mind investment in their mind >> in their mind. >> in their mind. >> in their mind. >> It's also the language we're using >> It's also the language we're using >> It's also the language we're using because pretty much is now AI is pretty because pretty much is now AI is pretty because pretty much is now AI is pretty much synonymous to geni. What you much synonymous to geni. What you much synonymous to geni. What you describe the data word is machine describe the data word is machine describe the data word is machine learning and there's a lot of value in learning and there's a lot of value in learning and there's a lot of value in machine learning if you have the right machine learning if you have the right machine learning if you have the right data for the right things and and that's data for the right things and and that's data for the right things and and that's a lot of value. The problem is that this a lot of value. The problem is that this a lot of value. The problem is that this whole open AI gen AI I talk to the thing whole open AI gen AI I talk to the thing whole open AI gen AI I talk to the thing and I keep on saying that I think the I and I keep on saying that I think the I and I keep on saying that I think the I I think that that will have a more I think that that will have a more I think that that will have a more profound impact in in humanity in profound impact in in humanity in profound impact in in humanity in general because we're touching language general because we're touching language general because we're touching language so it creates so much this is what you so it creates so much this is what you so it creates so much this is what you got we debate that pretty much at every got we debate that pretty much at every got we debate that pretty much at every episode and the one saying I think it episode and the one saying I think it episode and the one saying I think it touches language and it consequences touches language and it consequences touches language and it consequences >> the issue with chat bots the reason why >> the issue with chat bots the reason why >> the issue with chat bots the reason why and we've always been you know humans and we've always been you know humans and we've always been you know humans have always been infatuated with kind of have always been infatuated with kind of have always been infatuated with kind of like mechanical representation of like mechanical representation of like mechanical representation of humanity going back to the Egyptians humanity going back to the Egyptians humanity going back to the Egyptians frankly. Uh but when we talk when we now frankly. Uh but when we talk when we now frankly. Uh but when we talk when we now have AI that we can talk to even going have AI that we can talk to even going have AI that we can talk to even going back to Eliza it drives some sort of back to Eliza it drives some sort of back to Eliza it drives some sort of thing in our reptile brain that says thing in our reptile brain that says thing in our reptile brain that says well if this thing is behaving like me well if this thing is behaving like me well if this thing is behaving like me then maybe I'm a computer too like maybe then maybe I'm a computer too like maybe then maybe I'm a computer too like maybe maybe uh maybe my intelligence and my maybe uh maybe my intelligence and my maybe uh maybe my intelligence and my existence is comes into question because existence is comes into question because existence is comes into question because I'm now talking to something that seems I'm now talking to something that seems I'm now talking to something that seems to have an existence in and of itself.

to have an existence in and of itself. to have an existence in and of itself. So, I think that that's something that So, I think that that's something that So, I think that that's something that like gets people really like freaked out like gets people really like freaked out like gets people really like freaked out kind of subliminally when they start kind of subliminally when they start kind of subliminally when they start interacting with these things. They interacting with these things. They interacting with these things. They start questioning your freaked out start questioning your freaked out start questioning your freaked out value. value. value. >> We're all freaked out right now. >> We're all freaked out right now. >> We're all freaked out right now. >> I'm freaked out right now [laughter] by >> I'm freaked out right now [laughter] by >> I'm freaked out right now [laughter] by what you just said. what you just said. what you just said. >> Aren't you Are you freaked out in the >> Aren't you Are you freaked out in the >> Aren't you Are you freaked out in the real world or is it imaginary? real world or is it imaginary? real world or is it imaginary? >> That's true to say. >> That's true to say. >> That's true to say. >> We're in the matrix. We're in the >> We're in the matrix. We're in the >> We're in the matrix. We're in the matrix. So, that's interesting, Pete. matrix. So, that's interesting, Pete. matrix. So, that's interesting, Pete. So, if OpenAI is worth 900 billion So, if OpenAI is worth 900 billion So, if OpenAI is worth 900 billion >> and we [clears throat] come up with the >> and we [clears throat] come up with the >> and we [clears throat] come up with the money to buy them, when we go to their money to buy them, when we go to their money to buy them, when we go to their offices and we open the big vault, will offices and we open the big vault, will offices and we open the big vault, will we find all that kind of money cash we find all that kind of money cash we find all that kind of money cash sitting in that vault? sitting in that vault? sitting in that vault? >> I would assume we would. >> I would assume we would. >> I would assume we would. >> Or is or is the vault empty with a bunch >> Or is or is the vault empty with a bunch >> Or is or is the vault empty with a bunch of of of >> Well, no. Ironically, their their 900 >> Well, no. Ironically, their their 900 >> Well, no. Ironically, their their 900 billion value is based on a bunch of billion value is based on a bunch of billion value is based on a bunch of debt that they've piled up that they debt that they've piled up that they debt that they've piled up that they will recoup sometime in the future. or will recoup sometime in the future. or will recoup sometime in the future. or so. Unfortunately, it's all so. Unfortunately, it's all so. Unfortunately, it's all >> it's all based on the premise of future >> it's all based on the premise of future >> it's all based on the premise of future revenue. revenue. revenue. >> I I think the institutions are not going >> I I think the institutions are not going >> I I think the institutions are not going to they'll probably won't go for it, you to they'll probably won't go for it, you to they'll probably won't go for it, you know. So, it'll be know. So, it'll be know. So, it'll be >> Yeah.

>> Yeah. >> Yeah. >> It's just like when Larry Olson briefly >> It's just like when Larry Olson briefly >> It's just like when Larry Olson briefly became the richest man in the world became the richest man in the world became the richest man in the world because Open AI says, "We're going to because Open AI says, "We're going to because Open AI says, "We're going to buy $300 billion worth of Oracle OCI buy $300 billion worth of Oracle OCI buy $300 billion worth of Oracle OCI compute." And then instantly it we don't compute." And then instantly it we don't compute." And then instantly it we don't have the money to ever pay for that, but have the money to ever pay for that, but have the money to ever pay for that, but we're going to say it in a press we're going to say it in a press we're going to say it in a press release. Well, well, that's how Oracle release. Well, well, that's how Oracle release. Well, well, that's how Oracle stock got tanked. I mean, they came out stock got tanked. I mean, they came out stock got tanked. I mean, they came out with results with results with results >> and everyone said, "Okay, so you have >> and everyone said, "Okay, so you have >> and everyone said, "Okay, so you have 500 billion in backlog of which 300 500 billion in backlog of which 300 500 billion in backlog of which 300 billion is this open AI thing that may billion is this open AI thing that may billion is this open AI thing that may not happen. So, what's going on here?" not happen. So, what's going on here?" not happen. So, what's going on here?" And then the investors said, "This And then the investors said, "This And then the investors said, "This doesn't smell good." And so, the stock doesn't smell good." And so, the stock doesn't smell good." And so, the stock tank now, of course, the stock is back tank now, of course, the stock is back tank now, of course, the stock is back up now because apparently the Tik Tok up now because apparently the Tik Tok up now because apparently the Tik Tok deals deals deals >> and uh it's a buy now. So they're going >> and uh it's a buy now. So they're going >> and uh it's a buy now. So they're going to run it on Oracle infrastructure, but to run it on Oracle infrastructure, but to run it on Oracle infrastructure, but which by the way that porting exercise which by the way that porting exercise which by the way that porting exercise will take at least 5 years of work to will take at least 5 years of work to will take at least 5 years of work to actually move anything over to Oracle actually move anything over to Oracle actually move anything over to Oracle from Bite Dance's internal platforms. from Bite Dance's internal platforms. from Bite Dance's internal platforms. >> You know what I heard when I was at the >> You know what I heard when I was at the >> You know what I heard when I was at the Oracle event is that and they had one of Oracle event is that and they had one of Oracle event is that and they had one of the Bite Dance executives there. They the Bite Dance executives there. They the Bite Dance executives there. They say they already run Tik Tok on Oracle say they already run Tik Tok on Oracle say they already run Tik Tok on Oracle infrastructure. I don't know how much of infrastructure. I don't know how much of infrastructure. I don't know how much of it or where or which region or whatever, it or where or which region or whatever, it or where or which region or whatever, but they acted like they're already but they acted like they're already but they acted like they're already doing it. So, I don't know.

doing it. So, I don't know. doing it. So, I don't know. >> We'll see. We'll see. >> We'll see. We'll see. >> We'll see. We'll see. >> But their stocks back up now because >> But their stocks back up now because >> But their stocks back up now because they got out of the open AI kind of they got out of the open AI kind of they got out of the open AI kind of promisary note business. promisary note business. promisary note business. >> A lot of people bought the dip. >> A lot of people bought the dip. >> A lot of people bought the dip. >> Yeah, if you bought the dip. That was >> Yeah, if you bought the dip. That was >> Yeah, if you bought the dip. That was good. good. good. >> That was good. Although sometimes you >> That was good. Although sometimes you >> That was good. Although sometimes you buy on the dip and it stays dipped. So, buy on the dip and it stays dipped. So, buy on the dip and it stays dipped. So, that's that's that's >> Yes. All you people who bought on the >> Yes. All you people who bought on the >> Yes. All you people who bought on the dip for Enron stock, it turned out it dip for Enron stock, it turned out it dip for Enron stock, it turned out it kept dipping and dipping. kept dipping and dipping. kept dipping and dipping. >> So here this is Enron was proof that a >> So here this is Enron was proof that a >> So here this is Enron was proof that a stock can go to zero. stock can go to zero. stock can go to zero. >> Yeah. So here's an interesting thing. Uh >> Yeah. So here's an interesting thing. Uh >> Yeah. So here's an interesting thing. Uh a new headline. Tenscent obtains access a new headline. Tenscent obtains access a new headline. Tenscent obtains access to Nvidia Blackwell chips via Japanese to Nvidia Blackwell chips via Japanese to Nvidia Blackwell chips via Japanese third party. Um, that's well this this third party. Um, that's well this this third party. Um, that's well this this goes back to a comment that we made goes back to a comment that we made goes back to a comment that we made really long time ago about how the chips really long time ago about how the chips really long time ago about how the chips don't really matter as much as access to don't really matter as much as access to don't really matter as much as access to uh AI supercomputing uh AI supercomputing uh AI supercomputing um services and so um you know uh like um services and so um you know uh like um services and so um you know uh like when I was in Taiwan there were a bunch when I was in Taiwan there were a bunch when I was in Taiwan there were a bunch of this is about a year and a half ago of this is about a year and a half ago of this is about a year and a half ago right because this was at um right because this was at um right because this was at um what do you call it competit what do you call it competit what do you call it competit bunch Taiwanese companies just spinning bunch Taiwanese companies just spinning bunch Taiwanese companies just spinning up um GPU as a service businesses or up um GPU as a service businesses or up um GPU as a service businesses or these you know mini NeoClouds to cater these you know mini NeoClouds to cater these you know mini NeoClouds to cater to the Chinese. So um or you clients or to the Chinese. So um or you clients or to the Chinese. So um or you clients or customers but it end up I think a lot of customers but it end up I think a lot of customers but it end up I think a lot of that the customers that they were

that the customers that they were that the customers that they were talking about were Chinese customers. So talking about were Chinese customers. So talking about were Chinese customers. So yeah, I mean, you know, when you don't yeah, I mean, you know, when you don't yeah, I mean, you know, when you don't understand the technology, um, you come understand the technology, um, you come understand the technology, um, you come up with misguided, you know, policy and up with misguided, you know, policy and up with misguided, you know, policy and things. things. things. >> But are these Japanese folks in trouble >> But are these Japanese folks in trouble >> But are these Japanese folks in trouble legally because of finding out that legally because of finding out that legally because of finding out that they're funneling stuff? they're funneling stuff? they're funneling stuff? >> No, but you're going to probably see >> No, but you're going to probably see >> No, but you're going to probably see some sort of reaction to that. you know, some sort of reaction to that. you know, some sort of reaction to that. you know, for I'll give you a historical anecdote for I'll give you a historical anecdote for I'll give you a historical anecdote which somehow relates to submarines which somehow relates to submarines which somehow relates to submarines because, you know, I I don't know how to because, you know, I I don't know how to because, you know, I I don't know how to talk about anything else. Way back when talk about anything else. Way back when talk about anything else. Way back when in the 1980s during the height of the in the 1980s during the height of the in the 1980s during the height of the Cold War, it was discovered that a Cold War, it was discovered that a Cold War, it was discovered that a prominent Japanese company you've heard prominent Japanese company you've heard prominent Japanese company you've heard of before Toshiba of before Toshiba of before Toshiba actually had the plans for the LA actually had the plans for the LA actually had the plans for the LA technology to make the silent propeller technology to make the silent propeller technology to make the silent propeller >> that American submarines had. and they >> that American submarines had. and they >> that American submarines had. and they gave that information to the Soviets gave that information to the Soviets gave that information to the Soviets and that was kind of a big deal and and that was kind of a big deal and and that was kind of a big deal and there was a vote in Congress in the US there was a vote in Congress in the US there was a vote in Congress in the US over this and it came within one vote of over this and it came within one vote of over this and it came within one vote of permanently banning Toshiba from ever permanently banning Toshiba from ever permanently banning Toshiba from ever selling anything in the United States selling anything in the United States selling anything in the United States for all time. Um, but it but it didn't for all time. Um, but it but it didn't for all time. Um, but it but it didn't pass. But some of us know what Toshiba pass. But some of us know what Toshiba pass. But some of us know what Toshiba did. And so anyway, it's just a random did. And so anyway, it's just a random did. And so anyway, it's just a random trivia there of a third party company trivia there of a third party company trivia there of a third party company helping out someone that maybe you're helping out someone that maybe you're helping out someone that maybe you're not a fan of.

not a fan of. not a fan of. >> Yeah. Yeah. Exactly. >> Yeah. Yeah. Exactly. >> Yeah. Yeah. Exactly. >> There's your trivia for the day. Your >> There's your trivia for the day. Your >> There's your trivia for the day. Your submarine trivia. submarine trivia. submarine trivia. >> Yes. >> Yes. >> Yes. >> I mean, it's inevitable. It's >> I mean, it's inevitable. It's >> I mean, it's inevitable. It's inevitable. you know, the the the whole inevitable. you know, the the the whole inevitable. you know, the the the whole kind of functioning of the gray market kind of functioning of the gray market kind of functioning of the gray market in silicon, which you know, spent a few in silicon, which you know, spent a few in silicon, which you know, spent a few years in, it's it's, you know, you can years in, it's it's, you know, you can years in, it's it's, you know, you can you can you can decide that you don't you can you can decide that you don't you can you can decide that you don't want to sell to someone and then, you want to sell to someone and then, you want to sell to someone and then, you know, one of your distributors, you know, one of your distributors, you know, one of your distributors, you know, takes one of your chips, gives it know, takes one of your chips, gives it know, takes one of your chips, gives it to your competitor, they clone this, to your competitor, they clone this, to your competitor, they clone this, they clone the firmware, they, you know, they clone the firmware, they, you know, they clone the firmware, they, you know, and hey, you have another Laura chip in and hey, you have another Laura chip in and hey, you have another Laura chip in the world. Um, the world. Um, the world. Um, >> right, >> right, >> right, >> it's inevitable. All you can do, I >> it's inevitable. All you can do, I >> it's inevitable. All you can do, I think, is is is stay ahead of the train. think, is is is stay ahead of the train. think, is is is stay ahead of the train. I mean, if you if you focus your I mean, if you if you focus your I mean, if you if you focus your activity on trying to prevent other activity on trying to prevent other activity on trying to prevent other people from figuring out how to do what people from figuring out how to do what people from figuring out how to do what you figured out how to do, rather than you figured out how to do, rather than you figured out how to do, rather than spending your time figuring out what spending your time figuring out what spending your time figuring out what next thing your customer wants and next thing your customer wants and next thing your customer wants and >> then then you're ultimately going to >> then then you're ultimately going to >> then then you're ultimately going to lose, you know, you stay ahead of the lose, you know, you stay ahead of the lose, you know, you stay ahead of the train if you carry on, you know, train if you carry on, you know, train if you carry on, you know, delivering more value. Um, it doesn't delivering more value. Um, it doesn't delivering more value. Um, it doesn't matter what's in the rearview mirror. If matter what's in the rearview mirror. If matter what's in the rearview mirror. If other people are copying what you did 10 other people are copying what you did 10 other people are copying what you did 10 years ago, years ago, years ago, >> you're already you're already moving on.

>> you're already you're already moving on. >> you're already you're already moving on. Well, that was a that was a great Yeah. Well, that was a that was a great Yeah. Well, that was a that was a great Yeah. Go ahead. Go ahead. Go ahead. >> I have a question for my American >> I have a question for my American >> I have a question for my American friends because I I didn't understand friends because I I didn't understand friends because I I didn't understand why now uh Chinese companies can buy uh why now uh Chinese companies can buy uh why now uh Chinese companies can buy uh the Nvidia H200 GPUs. the Nvidia H200 GPUs. the Nvidia H200 GPUs. No. And uh so No. And uh so No. And uh so context context context >> Yeah. But just to give some context no >> Yeah. But just to give some context no >> Yeah. But just to give some context no when US ban no these all these um GPU when US ban no these all these um GPU when US ban no these all these um GPU chips uh no to get acquired by Chinese chips uh no to get acquired by Chinese chips uh no to get acquired by Chinese companies they start developing all the companies they start developing all the companies they start developing all the ecosystem to create their own GPUs no ecosystem to create their own GPUs no ecosystem to create their own GPUs no and they today have kind of a 800 GPUs and they today have kind of a 800 GPUs and they today have kind of a 800 GPUs technologies already made by themselves technologies already made by themselves technologies already made by themselves and now [laughter] and now [laughter] and now [laughter] you're open till H200 GPU so um why do you're open till H200 GPU so um why do you're open till H200 GPU so um why do you have any explanation on that? No, I you have any explanation on that? No, I you have any explanation on that? No, I think I think Rob just explained it. think I think Rob just explained it. think I think Rob just explained it. >> It's pretty simple. >> It's pretty simple. >> It's pretty simple. >> It's just Yeah. Yeah. Yeah. Jensen wants >> It's just Yeah. Yeah. Yeah. Jensen wants >> It's just Yeah. Yeah. Yeah. Jensen wants to sell GPUs to the Chinese and and to sell GPUs to the Chinese and and to sell GPUs to the Chinese and and because that that was a big money maker because that that was a big money maker because that that was a big money maker for them.

for them. for them. >> And so he went and had a one-on-one, you >> And so he went and had a one-on-one, you >> And so he went and had a one-on-one, you know, with Trump. know, with Trump. know, with Trump. >> And anyone who knows how to get Trump to >> And anyone who knows how to get Trump to >> And anyone who knows how to get Trump to do something you want to do is you go in do something you want to do is you go in do something you want to do is you go in there and you do a lot of sucking up. there and you do a lot of sucking up. there and you do a lot of sucking up. And you tell them, "Gosh, you're a And you tell them, "Gosh, you're a And you tell them, "Gosh, you're a really powerful man, Donald. And gosh, I really powerful man, Donald. And gosh, I really powerful man, Donald. And gosh, I love what you've done with the Oval love what you've done with the Oval love what you've done with the Oval Office. I like all the gilded gold stuff Office. I like all the gilded gold stuff Office. I like all the gilded gold stuff you put everywhere. It's amazing. The you put everywhere. It's amazing. The you put everywhere. It's amazing. The plaque. Love the plaques. And so plaque. Love the plaques. And so plaque. Love the plaques. And so basically, you go in, everyone knows the basically, you go in, everyone knows the basically, you go in, everyone knows the playbook now. You go suck up to Trump playbook now. You go suck up to Trump playbook now. You go suck up to Trump and tell him he's the most amazing guy and tell him he's the most amazing guy and tell him he's the most amazing guy ever. And he goes, "I love you, Jensen. ever. And he goes, "I love you, Jensen. ever. And he goes, "I love you, Jensen. Yes, you can sell H200s to to China." Yes, you can sell H200s to to China." Yes, you can sell H200s to to China." Now, obviously, she he has come out and Now, obviously, she he has come out and Now, obviously, she he has come out and said, "I'm not going to allow any of you said, "I'm not going to allow any of you said, "I'm not going to allow any of you guys to buy any Nvidia chips at all guys to buy any Nvidia chips at all guys to buy any Nvidia chips at all recently." You know, and you're right, recently." You know, and you're right, recently." You know, and you're right, Huawei is making what is it? Ascends. Is Huawei is making what is it? Ascends. Is Huawei is making what is it? Ascends. Is that the name of their channel from that the name of their channel from that the name of their channel from >> And they're they're not great, but >> And they're they're not great, but >> And they're they're not great, but they're going to this they're going to this they're going to this >> it's what Alistair was saying. >> it's what Alistair was saying. >> it's what Alistair was saying. Everyone's going to figure this Everyone's going to figure this Everyone's going to figure this out, out, out, >> you just got to keep racing ahead. >> you just got to keep racing ahead. >> you just got to keep racing ahead. >> And this is what's even worse. And this >> And this is what's even worse. And this >> And this is what's even worse. And this goes back to Alistair's um comment goes back to Alistair's um comment goes back to Alistair's um comment earlier. It's like rather than focusing earlier. It's like rather than focusing earlier. It's like rather than focusing on preventing others from using your on preventing others from using your on preventing others from using your your stuff or you know uh having your stuff or you know uh having your stuff or you know uh having [clears throat] you know maybe [clears throat] you know maybe [clears throat] you know maybe backfilled your markets that you backfilled your markets that you backfilled your markets that you previously competing in uh look for the previously competing in uh look for the previously competing in uh look for the next thing you know innovate you know um next thing you know innovate you know um next thing you know innovate you know um and um the Chinese are not tethered to and um the Chinese are not tethered to and um the Chinese are not tethered to our semiconductor uh industry and our semiconductor uh industry and our semiconductor uh industry and technology road maps. They can create

technology road maps. They can create technology road maps. They can create their own. That gives them a lot of their own. That gives them a lot of their own. That gives them a lot of latitude and the problem for us is they latitude and the problem for us is they latitude and the problem for us is they have scale. have scale. have scale. >> Yeah. >> Yeah. >> Yeah. >> They have immediate scale. So >> They have immediate scale. So >> They have immediate scale. So >> they have demand >> they have demand >> they have demand >> scale easily. >> scale easily. >> scale easily. >> The I think Silicon Valley thinking that >> The I think Silicon Valley thinking that >> The I think Silicon Valley thinking that somehow everything that they do is uh somehow everything that they do is uh somehow everything that they do is uh gospel is completely delusional. gospel is completely delusional. gospel is completely delusional. um the Chinese can very quickly pick up um the Chinese can very quickly pick up um the Chinese can very quickly pick up any standard and go and you know maybe any standard and go and you know maybe any standard and go and you know maybe even the government will force it right even the government will force it right even the government will force it right and the adoption will be extremely rapid and the adoption will be extremely rapid and the adoption will be extremely rapid and they will be able to work through and they will be able to work through and they will be able to work through all the issues very quickly like they've all the issues very quickly like they've all the issues very quickly like they've done on with IoT and 5G done on with IoT and 5G done on with IoT and 5G >> and then they leaprog >> and then they leaprog >> and then they leaprog >> but the primary and then you know in >> but the primary and then you know in >> but the primary and then you know in terms of material sciences terms of material sciences terms of material sciences um these uh you know uh networking um these uh you know uh networking um these uh you know uh networking interconnect all these other factors interconnect all these other factors interconnect all these other factors that actually go into the system. It I that actually go into the system. It I that actually go into the system. It I don't think Chinese are behind and I don't think Chinese are behind and I don't think Chinese are behind and I don't think Link is that much of a don't think Link is that much of a don't think Link is that much of a magical thing as everyone thinks and if magical thing as everyone thinks and if magical thing as everyone thinks and if you want to consider the fact that uh you want to consider the fact that uh you want to consider the fact that uh companies like Huawei and ZT are leaders companies like Huawei and ZT are leaders companies like Huawei and ZT are leaders in networking and that a lot of the in networking and that a lot of the in networking and that a lot of the supercomputing networking looks a lot supercomputing networking looks a lot supercomputing networking looks a lot like telco networking.

like telco networking. like telco networking. I don't know. You do the simple math and I don't know. You do the simple math and I don't know. You do the simple math and this fixation on chips. Every, you know, this fixation on chips. Every, you know, this fixation on chips. Every, you know, you watch CNBC, they still talk about you watch CNBC, they still talk about you watch CNBC, they still talk about the chip. It's like, no one gives a the chip. It's like, no one gives a the chip. It's like, no one gives a about the chip anymore. They haven't about the chip anymore. They haven't about the chip anymore. They haven't given a about the chip for 2 years. given a about the chip for 2 years. given a about the chip for 2 years. It's about the system, the rack, the, It's about the system, the rack, the, It's about the system, the rack, the, you know, the cluster, the data center, you know, the cluster, the data center, you know, the cluster, the data center, and now the freaking campus, right? So, and now the freaking campus, right? So, and now the freaking campus, right? So, >> it's it's accommodation. But and by the >> it's it's accommodation. But and by the >> it's it's accommodation. But and by the way I I don't know if it's rumors it's way I I don't know if it's rumors it's way I I don't know if it's rumors it's true but I've seen there seems to be true but I've seen there seems to be true but I've seen there seems to be some recent recent development with some recent recent development with some recent recent development with China actually developing alternative to China actually developing alternative to China actually developing alternative to what ASML is doing. what ASML is doing. what ASML is doing. >> So which is really going to the >> So which is really going to the >> So which is really going to the >> so that's the real that's the real lynch >> so that's the real that's the real lynch >> so that's the real that's the real lynch pin if you can get the lithography pin if you can get the lithography pin if you can get the lithography >> exactly >> exactly >> exactly >> tech uh in house and not dependency on >> tech uh in house and not dependency on >> tech uh in house and not dependency on one company in Amsterdam one company in Amsterdam one company in Amsterdam >> uh then that's a big deal. But like >> uh then that's a big deal. But like >> uh then that's a big deal. But like going back to Rob's point, you know, not going back to Rob's point, you know, not going back to Rob's point, you know, not every solution requires, you know, this every solution requires, you know, this every solution requires, you know, this kind of um just invented yesterday kind of um just invented yesterday kind of um just invented yesterday technology at scale to solve lots of technology at scale to solve lots of technology at scale to solve lots of problems. And so even if the Huawei problems. And so even if the Huawei problems. And so even if the Huawei chips are not exactly, you know, as chips are not exactly, you know, as chips are not exactly, you know, as powerful as the latest blackwells, they powerful as the latest blackwells, they powerful as the latest blackwells, they may be a lot more efficient, by the way.

may be a lot more efficient, by the way. may be a lot more efficient, by the way. And by the way, that's where China I And by the way, that's where China I And by the way, that's where China I think is going to leaprog is much more think is going to leaprog is much more think is going to leaprog is much more efficient AI than anyone else is doing. efficient AI than anyone else is doing. efficient AI than anyone else is doing. So they're going to use a lot less power So they're going to use a lot less power So they're going to use a lot less power and get a lot more performance out of and get a lot more performance out of and get a lot more performance out of them. No question about it. And because them. No question about it. And because them. No question about it. And because they have to because they have to. they have to because they have to. they have to because they have to. >> No, but they are getting it cuz look at >> No, but they are getting it cuz look at >> No, but they are getting it cuz look at their models. They're more efficient and their models. They're more efficient and their models. They're more efficient and they basically are, you know, pretty they basically are, you know, pretty they basically are, you know, pretty much at the top of the list. Now there's much at the top of the list. Now there's much at the top of the list. Now there's diminishing returns uh on each iteration diminishing returns uh on each iteration diminishing returns uh on each iteration of these models. Bigger is not better. of these models. Bigger is not better. of these models. Bigger is not better. Um actually it boils down to who has the Um actually it boils down to who has the Um actually it boils down to who has the better data and who has the quality better data and who has the quality better data and who has the quality tokens. And the bottom line is the tokens. And the bottom line is the tokens. And the bottom line is the Chinese do Chinese do Chinese do >> and it has to do with their language. >> and it has to do with their language. >> and it has to do with their language. There's that's something that no other There's that's something that no other There's that's something that no other culture can overcome. culture can overcome. culture can overcome. >> Yeah. >> Yeah. >> Yeah. >> So the centralized nature of China. I >> So the centralized nature of China. I >> So the centralized nature of China. I mean if you look at what the American mean if you look at what the American mean if you look at what the American government is trying to do at the moment government is trying to do at the moment government is trying to do at the moment with aggregating different data sources with aggregating different data sources with aggregating different data sources into one pool to use for you know into one pool to use for you know into one pool to use for you know whatever purposes you end up using it whatever purposes you end up using it whatever purposes you end up using it for. The Chinese have been done that for. The Chinese have been done that for. The Chinese have been done that since day one. Um so the data sets now since day one. Um so the data sets now since day one. Um so the data sets now there's the regional government there's the regional government there's the regional government structure and principalities and what structure and principalities and what structure and principalities and what have you that complicates this a little have you that complicates this a little have you that complicates this a little bit but if you're looking at the the bit but if you're looking at the the bit but if you're looking at the the depth and the breadth of the data set depth and the breadth of the data set depth and the breadth of the data set they have on what people do they have on what people do they have on what people do >> it's far more consolidated already than >> it's far more consolidated already than >> it's far more consolidated already than any other geography in the world and I any other geography in the world and I any other geography in the world and I agree with you I mean it doesn't matter agree with you I mean it doesn't matter agree with you I mean it doesn't matter whether your chip is a 2 nm chip or 90 whether your chip is a 2 nm chip or 90 whether your chip is a 2 nm chip or 90 nm it doesn't matter if you're feeding nm it doesn't matter if you're feeding nm it doesn't matter if you're feeding quality well-labeled data into an LL M

quality well-labeled data into an LL M quality well-labeled data into an LL M of any form. It more data better data of any form. It more data better data of any form. It more data better data always wins. always wins. always wins. >> That's right. It's the data stupid. >> That's right. It's the data stupid. >> That's right. It's the data stupid. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> Yeah. >> It is it is in the end glorified in our >> It is it is in the end glorified in our >> It is it is in the end glorified in our regression. It's just layer and layers regression. It's just layer and layers regression. It's just layer and layers of them. So of them. So of them. So >> it is only the data. >> it is only the data. >> it is only the data. >> Yeah. Yeah. I mean people people I think >> Yeah. Yeah. I mean people people I think >> Yeah. Yeah. I mean people people I think think too conventionally about language. think too conventionally about language. think too conventionally about language. There's so much nuance. It's incredible. There's so much nuance. It's incredible. There's so much nuance. It's incredible. It's an amazing field to study. But when It's an amazing field to study. But when It's an amazing field to study. But when it's when you look at it in relations to it's when you look at it in relations to it's when you look at it in relations to what people are trying to do with large what people are trying to do with large what people are trying to do with large language model, language models in language model, language models in language model, language models in general, right? Um it's far more nuanced general, right? Um it's far more nuanced general, right? Um it's far more nuanced than what I've observed people than what I've observed people than what I've observed people um how people have talked about it, um how people have talked about it, um how people have talked about it, right? It it's um it's a huge factor. I right? It it's um it's a huge factor. I right? It it's um it's a huge factor. I know that Nvidia has put it on its map know that Nvidia has put it on its map know that Nvidia has put it on its map now. uh and the early notions that now. uh and the early notions that now. uh and the early notions that English is the best language for um for English is the best language for um for English is the best language for um for AI. I think AI. I think AI. I think >> whoever said whoever said that this is >> whoever said whoever said that this is >> whoever said whoever said that this is computer computer computer >> there are a lot of people there are a >> there are a lot of people there are a >> there are a lot of people there are a lot of people because they were looking lot of people because they were looking lot of people because they were looking at it in terms of tokens the token at it in terms of tokens the token at it in terms of tokens the token efficiency but efficiency but efficiency but >> well they don't understand how token >> well they don't understand how token >> well they don't understand how token works you works you works you you pretty much do not need token you pretty much do not need token you pretty much do not need token >> look look but the thing is is that when >> look look but the thing is is that when >> look look but the thing is is that when you talk to people who are doing things you talk to people who are doing things you talk to people who are doing things at the engineering level below they they at the engineering level below they they at the engineering level below they they typically don't know what's happening typically don't know what's happening typically don't know what's happening above right they just deal with the above right they just deal with the above right they just deal with the requirements from a system perspective

requirements from a system perspective requirements from a system perspective Right. Uh so there are these disconnects Right. Uh so there are these disconnects Right. Uh so there are these disconnects in the western world and in China there in the western world and in China there in the western world and in China there isn't their engineers know full stack isn't their engineers know full stack isn't their engineers know full stack there because they have to they they there because they have to they they there because they have to they they don't assume that they have CUDA that's don't assume that they have CUDA that's don't assume that they have CUDA that's going to h deal with everything below it going to h deal with everything below it going to h deal with everything below it for a general purpose accelerator. They for a general purpose accelerator. They for a general purpose accelerator. They go below CUDA to optimize everything. go below CUDA to optimize everything. go below CUDA to optimize everything. they had to go and look at the entire they had to go and look at the entire they had to go and look at the entire system architecture or whatever they're system architecture or whatever they're system architecture or whatever they're constrained with to figure out how to do constrained with to figure out how to do constrained with to figure out how to do um what they needed to do in order to um what they needed to do in order to um what they needed to do in order to compete or you know develop working compete or you know develop working compete or you know develop working models. So so in a lot of ways I think models. So so in a lot of ways I think models. So so in a lot of ways I think CUDA has been has hamstrung the AI CUDA has been has hamstrung the AI CUDA has been has hamstrung the AI community because you just assume it's community because you just assume it's community because you just assume it's there. It's like, "Oh, hey, we just use there. It's like, "Oh, hey, we just use there. It's like, "Oh, hey, we just use CUDA." And then Nvidia does all the lazy CUDA." And then Nvidia does all the lazy CUDA." And then Nvidia does all the lazy work for you, you know, or the work for you, you know, or the work for you, you know, or the complicated work for you, and you just complicated work for you, and you just complicated work for you, and you just be lazy. be lazy. be lazy. >> Just ability. >> Just ability. >> Just ability. >> Be lazy. >> Be lazy. >> Be lazy. >> Wow. So, basically, you're saying the >> Wow. So, basically, you're saying the >> Wow. So, basically, you're saying the Chinese are using assembler.

Chinese are using assembler. Chinese are using assembler. >> What? [snorts] Yeah. >> What? [snorts] Yeah. >> What? [snorts] Yeah. >> No, no, it's not a joke. It's not a >> No, no, it's not a joke. It's not a >> No, no, it's not a joke. It's not a joke. They literally freaking do joke. They literally freaking do joke. They literally freaking do assembly language. I mean down at the assembly language. I mean down at the assembly language. I mean down at the kernel level it's you're you know you're kernel level it's you're you know you're kernel level it's you're you know you're you're you're you're you're you're you're know you're joking but it's not a joke. know you're joking but it's not a joke. know you're joking but it's not a joke. It's absolutely true. >> Kernel programming >> Kernel programming >> everyone use it in the low level. >> everyone use it in the low level. >> everyone use it in the low level. Everyone use it. Everyone use it. Everyone use it. >> Yeah. >> Yeah. >> Yeah. >> And and zeros and ones. >> And and zeros and ones. >> And and zeros and ones. >> A small group of people who know how to >> A small group of people who know how to >> A small group of people who know how to do that stuff. Yeah. do that stuff. Yeah. do that stuff. Yeah. >> Uh they have apparently they have a crap >> Uh they have apparently they have a crap >> Uh they have apparently they have a crap ton in China that know how to do ton in China that know how to do ton in China that know how to do >> Yeah. >> Yeah. >> Yeah. >> because they they engineer everything >> because they they engineer everything >> because they they engineer everything for deep seat. That's what that was for deep seat. That's what that was for deep seat. That's what that was about probably 20% of the entire about probably 20% of the entire about probably 20% of the entire exercise. And obviously they did a bunch exercise. And obviously they did a bunch exercise. And obviously they did a bunch of other stuff above the stack. of other stuff above the stack. of other stuff above the stack. >> But we about whether it's thing we've >> But we about whether it's thing we've >> But we about whether it's thing we've learned about business and technology is learned about business and technology is learned about business and technology is when you're put under tremendous when you're put under tremendous when you're put under tremendous constraints that's when true innovation constraints that's when true innovation constraints that's when true innovation comes out. you you know when it's easy comes out. you you know when it's easy comes out. you you know when it's easy and you have plenty of money and all and you have plenty of money and all and you have plenty of money and all this time and all this tech this time and all this tech this time and all this tech >> you don't do great things it's it seems >> you don't do great things it's it seems >> you don't do great things it's it seems paradoxical when you have no money and paradoxical when you have no money and paradoxical when you have no money and constraints like has been placed upon constraints like has been placed upon constraints like has been placed upon >> uh the Deep Seek folks you know look >> uh the Deep Seek folks you know look >> uh the Deep Seek folks you know look what they did what they did what they did >> yeah it's pretty crazy >> yeah it's pretty crazy >> yeah it's pretty crazy >> I mean also if you go back like 10 15 >> I mean also if you go back like 10 15 >> I mean also if you go back like 10 15 years the only country that was growing years the only country that was growing years the only country that was growing embedded engineers was China embedded engineers was China embedded engineers was China >> having Yeah >> having Yeah >> having Yeah >> and that knowledge that know you said >> and that knowledge that know you said >> and that knowledge that know you said Rob that knowledge of working within an Rob that knowledge of working within an Rob that knowledge of working within an extremely constrained environment with a extremely constrained environment with a extremely constrained environment with a tiny little processor inside. I think it

tiny little processor inside. I think it tiny little processor inside. I think it breeds a it breeds a mentality that you breeds a it breeds a mentality that you breeds a it breeds a mentality that you can extend to to you know to working in can extend to to you know to working in can extend to to you know to working in the in you know the lower levels of the the in you know the lower levels of the the in you know the lower levels of the stack that that you people are stack that that you people are stack that that you people are self-sufficient. You're not you haven't self-sufficient. You're not you haven't self-sufficient. You're not you haven't got a big fat processor and plenty of got a big fat processor and plenty of got a big fat processor and plenty of storage and no limitation on on on storage and no limitation on on on storage and no limitation on on on power. You just that's not your world. power. You just that's not your world. power. You just that's not your world. You're you're working in a a mode of You're you're working in a a mode of You're you're working in a a mode of starvation and it makes you do it makes starvation and it makes you do it makes starvation and it makes you do it makes you do you do you do >> more creative things. >> more creative things. >> more creative things. >> Yeah. Yeah. Yeah, >> Yeah. Yeah. Yeah, >> Yeah. Yeah. Yeah, >> just like the original Windows NT team >> just like the original Windows NT team >> just like the original Windows NT team having to build Windows NT on low-end having to build Windows NT on low-end having to build Windows NT on low-end OS2 boxes that had like whatever 4 megab OS2 boxes that had like whatever 4 megab OS2 boxes that had like whatever 4 megab RAM or something like that. And that RAM or something like that. And that RAM or something like that. And that insane constraints that all the insane constraints that all the insane constraints that all the engineers hated was the key to success, engineers hated was the key to success, engineers hated was the key to success, you know. Yeah, go figure. you know. Yeah, go figure. you know. Yeah, go figure. >> Well, the this is the this is the the >> Well, the this is the this is the the >> Well, the this is the this is the the the core of the the human aspect. The the core of the the human aspect. The the core of the the human aspect. The human excels when you are under human excels when you are under human excels when you are under constraint. It's called natural constraint. It's called natural constraint. It's called natural selection. So just selection. So just selection. So just >> pressure if you think about it this is >> pressure if you think about it this is >> pressure if you think about it this is >> stress.

>> stress. >> stress. >> If you're too you have too much >> If you're too you have too much >> If you're too you have too much resources you end up being lazy and you resources you end up being lazy and you resources you end up being lazy and you do less. do less. do less. >> You be lazy. Yeah. I mean if you think >> You be lazy. Yeah. I mean if you think >> You be lazy. Yeah. I mean if you think about the impact of AI I mean I about the impact of AI I mean I about the impact of AI I mean I everywhere around me everybody's you everywhere around me everybody's you everywhere around me everybody's you chat GPT particularly claude you know chat GPT particularly claude you know chat GPT particularly claude you know the the the the going back to your point the the the the going back to your point the the the the going back to your point earlier to visual relationships with LLMs as their relationships with LLMs as their boyfriend girlfriend and I is is is boyfriend girlfriend and I is is is boyfriend girlfriend and I is is is utterly insane but the dependency upon utterly insane but the dependency upon utterly insane but the dependency upon chat GPT to tell me what the answer to chat GPT to tell me what the answer to chat GPT to tell me what the answer to blah blah blah is is stripping people of blah blah blah is is stripping people of blah blah blah is is stripping people of their ability to the it's the very their ability to the it's the very their ability to the it's the very foundational layer of learning which is foundational layer of learning which is foundational layer of learning which is finding data, assimilating data, finding data, assimilating data, finding data, assimilating data, distinguishing good data from bad. you distinguishing good data from bad. you distinguishing good data from bad. you know the our mental process as humans. know the our mental process as humans. know the our mental process as humans. You've got to wonder in in 20 years time You've got to wonder in in 20 years time You've got to wonder in in 20 years time are kids coming out of college going to are kids coming out of college going to are kids coming out of college going to be capable of of actual you know n be capable of of actual you know n be capable of of actual you know n >> yeah and actually the and the the >> yeah and actually the and the the >> yeah and actually the and the the education system is doing the the wrong education system is doing the the wrong education system is doing the the wrong thing which is trying to prevent them thing which is trying to prevent them thing which is trying to prevent them from using them instead of teaching them from using them instead of teaching them from using them instead of teaching them how to use them the right way. I I have how to use them the right way. I I have how to use them the right way. I I have very I have very dark vision of what's very I have very dark vision of what's very I have very dark vision of what's going to happen because my my my my going to happen because my my my my going to happen because my my my my personal theory is that advertising is personal theory is that advertising is personal theory is that advertising is going to disappear going to disappear going to disappear >> the way [clears throat] we know it >> the way [clears throat] we know it >> the way [clears throat] we know it >> because it's going to be embedded into >> because it's going to be embedded into >> because it's going to be embedded into the answers that all those systems give the answers that all those systems give the answers that all those systems give you and that we drive you to behave and you and that we drive you to behave and you and that we drive you to behave and buy some stuff. So, it's the fundamental

buy some stuff. So, it's the fundamental buy some stuff. So, it's the fundamental problem Google has because they have to problem Google has because they have to problem Google has because they have to go from a place where you type a query go from a place where you type a query go from a place where you type a query and you bombard some ads to you give an and you bombard some ads to you give an and you bombard some ads to you give an answer and you inject, oh, by the way, answer and you inject, oh, by the way, answer and you inject, oh, by the way, there's this new product you might want there's this new product you might want there's this new product you might want to buy at a discount that you're just to buy at a discount that you're just to buy at a discount that you're just discussing. discussing. discussing. >> Yeah. But I also think, you know, I >> Yeah. But I also think, you know, I >> Yeah. But I also think, you know, I recently po posted about the AI slot recently po posted about the AI slot recently po posted about the AI slot problem, right? I don't think they're problem, right? I don't think they're problem, right? I don't think they're immune either. Um, I think everyone immune either. Um, I think everyone immune either. Um, I think everyone thinks that somehow these guys are the thinks that somehow these guys are the thinks that somehow these guys are the masters of the universe. It's more like masters of the universe. It's more like masters of the universe. It's more like they created Frankenstein. they created Frankenstein. they created Frankenstein. >> Yeah. and they will become a victim of >> Yeah. and they will become a victim of >> Yeah. and they will become a victim of it as well. I'm almost 1,000%. it as well. I'm almost 1,000%. it as well. I'm almost 1,000%. >> I'm not saying that they're going to >> I'm not saying that they're going to >> I'm not saying that they're going to succeed, but succeed, but succeed, but >> No, no, but but even in that capacity, >> No, no, but but even in that capacity, >> No, no, but but even in that capacity, even in that capacity will not be, you even in that capacity will not be, you even in that capacity will not be, you won't have see the efficacy. If I were won't have see the efficacy. If I were won't have see the efficacy. If I were to, you know, go back into my Damon to, you know, go back into my Damon to, you know, go back into my Damon weigh-ins mode here, you're not going to weigh-ins mode here, you're not going to weigh-ins mode here, you're not going to see that efficacy that people think. see that efficacy that people think. see that efficacy that people think. It's going to be a show. Um, and It's going to be a show. Um, and It's going to be a show. Um, and they're going to they're going to have a they're going to they're going to have a they're going to they're going to have a a lot of trouble uh reigning this thing a lot of trouble uh reigning this thing a lot of trouble uh reigning this thing in and controlling it. Um, and you know, in and controlling it. Um, and you know, in and controlling it. Um, and you know, think about it that think about it that think about it that when you're when the corpus of data is, when you're when the corpus of data is, when you're when the corpus of data is, you know, progressively getting worse you know, progressively getting worse you know, progressively getting worse and worse, right? It's based on sloth, and worse, right? It's based on sloth, and worse, right? It's based on sloth, then eventually um idiocracy becomes the then eventually um idiocracy becomes the then eventually um idiocracy becomes the mean and the it becomes a basis of fact.

mean and the it becomes a basis of fact. mean and the it becomes a basis of fact. And And And everybody is going to be I mean dude everybody is going to be I mean dude everybody is going to be I mean dude >> look at where the new Jaywalk remember >> look at where the new Jaywalk remember >> look at where the new Jaywalk remember Jay Leno's Jaywalk Jay Leno's Jaywalk Jay Leno's Jaywalk >> Hollywood Boulevard right and you had a >> Hollywood Boulevard right and you had a >> Hollywood Boulevard right and you had a bunch of people and didn't know crap bunch of people and didn't know crap bunch of people and didn't know crap >> guess what the new Jaywok >> guess what the new Jaywok >> guess what the new Jaywok >> is Harvard University it's Colia it's >> is Harvard University it's Colia it's >> is Harvard University it's Colia it's any university you go to these guys any university you go to these guys any university you go to these guys don't know how to think it it's like don't know how to think it it's like don't know how to think it it's like ridiculous right so now you have like uh ridiculous right so now you have like uh ridiculous right so now you have like uh what is his name um the uh Singaporean what is his name um the uh Singaporean what is his name um the uh Singaporean or the Malaysian comedian guy, uh, or the Malaysian comedian guy, uh, or the Malaysian comedian guy, uh, Ronnie Chain, going around interviewing Ronnie Chain, going around interviewing Ronnie Chain, going around interviewing college students about the use of college students about the use of college students about the use of generative AI. These these guys are generative AI. These these guys are generative AI. These these guys are these kids are morons. these kids are morons. these kids are morons. >> I I everybody >> I I everybody >> I I everybody watch the movie Deiocracy again. I mean, watch the movie Deiocracy again. I mean, watch the movie Deiocracy again. I mean, I think that should be the the national I think that should be the the national I think that should be the the national curriculum of a very watching Deocracy curriculum of a very watching Deocracy curriculum of a very watching Deocracy at least three times. at least three times. at least three times. >> And, [laughter] >> And, [laughter] >> And, [laughter] you know, you're right. Then then look you know, you're right. Then then look you know, you're right. Then then look around you at the world and see where around you at the world and see where around you at the world and see where [laughter] we're going.

[laughter] we're going. [laughter] we're going. >> Required coursework, not civics. >> Required coursework, not civics. >> Required coursework, not civics. Idiocracy. [laughter] >> You look at the you look at the >> You look at the you look at the president character in Idiocracy. president character in Idiocracy. president character in Idiocracy. >> The the the wrestler. I mean like Dave >> The the the wrestler. I mean like Dave >> The the the wrestler. I mean like Dave Supreme. Supreme. Supreme. >> Yeah, I know. I mean, >> Yeah, I know. I mean, >> Yeah, I know. I mean, >> your monthly playlist should be >> your monthly playlist should be >> your monthly playlist should be Idiocracy, Idiocracy, Idiocracy, Brazil, The Matrix, and Hackers, of Brazil, The Matrix, and Hackers, of Brazil, The Matrix, and Hackers, of course. course. course. >> Yeah. [laughter] >> Yeah. [laughter] >> Yeah. [laughter] >> All right. >> All right. >> All right. >> Is our future going to be Is our future >> Is our future going to be Is our future >> Is our future going to be Is our future going to be in the Matrix, or is our going to be in the Matrix, or is our going to be in the Matrix, or is our future going to be in Logan's Run? future going to be in Logan's Run? future going to be in Logan's Run? >> Uh, Logan's Run. Another one. Yeah, >> Uh, Logan's Run. Another one. Yeah, >> Uh, Logan's Run. Another one. Yeah, >> we talked about this before. In the >> we talked about this before. In the >> we talked about this before. In the middle, it's middle, it's middle, it's >> so Soilent Green is what? >> so Soilent Green is what? >> so Soilent Green is what? Oh, it's going to be Brazil. It's going Oh, it's going to be Brazil. It's going Oh, it's going to be Brazil. It's going to be Brazil. to be Brazil. to be Brazil. >> Actually, that >> Actually, that >> Actually, that >> that intro to Idiocracy is amazing >> that intro to Idiocracy is amazing >> that intro to Idiocracy is amazing because because because >> it's the best intro ever. [laughter] >> it's the best intro ever. [laughter] >> it's the best intro ever. [laughter] >> But we froze our eggs cuz we know one >> But we froze our eggs cuz we know one >> But we froze our eggs cuz we know one day we're going to do the [laughter] day we're going to do the [laughter] day we're going to do the [laughter] Me being one of the dumbest people on Me being one of the dumbest people on Me being one of the dumbest people on the planet are having 20 kids.

the planet are having 20 kids. the planet are having 20 kids. [laughter] >> Anyway, all right. [laughter] >> Anyway, all right. [laughter] >> Merry Christmas everyone. Happy Hanukkah. Happy Hanukkah. >> Happy >> Happy >> Happy I knew talking to you guys this morning I knew talking to you guys this morning I knew talking to you guys this morning would make me feel optimistic about the would make me feel optimistic about the would make me feel optimistic about the world. world. world. [laughter] [laughter] [laughter] >> This is what we do. >> This is what we do. >> This is what we do. >> This is what we >> This is what we >> This is what we >> That's right. That's right. >> That's right. That's right. >> That's right. That's right. >> We're helping. Trust me, we're helping. >> We're helping. Trust me, we're helping. >> We're helping. Trust me, we're helping. [laughter] [laughter] [laughter] >> Grounding. We're grounding people. Um >> Grounding. We're grounding people. Um >> Grounding. We're grounding people. Um All right. So, yeah. There you go. All right. So, yeah. There you go. All right. So, yeah. There you go. >> There you go. >> There you go. >> There you go. You want to take us out, Rob? You want to take us out, Rob? You want to take us out, Rob? >> Thanks so much for joining us, you know, >> Thanks so much for joining us, you know, >> Thanks so much for joining us, you know, on this idiocracy infused conversation on this idiocracy infused conversation on this idiocracy infused conversation here. Um, I hope you've learned here. Um, I hope you've learned here. Um, I hope you've learned something. something. something. I don't know. You probably didn't learn I don't know. You probably didn't learn I don't know. You probably didn't learn anything actually. Um, yeah. Yes. But anything actually. Um, yeah. Yes. But anything actually. Um, yeah. Yes. But remember, you don't need all the stuff remember, you don't need all the stuff remember, you don't need all the stuff you think you need to do great things, you think you need to do great things, you think you need to do great things, you know. So, that's okay. Just go do you know. So, that's okay. Just go do you know. So, that's okay. Just go do it. Just start. And, uh, which is so it. Just start. And, uh, which is so it. Just start. And, uh, which is so important. people, a lot of people feel important. people, a lot of people feel important. people, a lot of people feel like they need perfection and everything like they need perfection and everything like they need perfection and everything around them before they can start this around them before they can start this around them before they can start this great thing. And it's just not true.

great thing. And it's just not true. great thing. And it's just not true. Constraint is the miracle uh that makes Constraint is the miracle uh that makes Constraint is the miracle uh that makes innovation happen. And so remember that innovation happen. And so remember that innovation happen. And so remember that when you're all stressed out and you when you're all stressed out and you when you're all stressed out and you don't think you have what you need to do don't think you have what you need to do don't think you have what you need to do what you want to do. Um so that's all what you want to do. Um so that's all what you want to do. Um so that's all good. Uh we're looking forward to really good. Uh we're looking forward to really good. Uh we're looking forward to really amping up things with our new Elevate amping up things with our new Elevate amping up things with our new Elevate communities uh in 2026 as we've migrated communities uh in 2026 as we've migrated communities uh in 2026 as we've migrated from Elevate Our Kids. And so that's from Elevate Our Kids. And so that's from Elevate Our Kids. And so that's we're going to do a lot of great stuff we're going to do a lot of great stuff we're going to do a lot of great stuff and a lot of tech and things that we're and a lot of tech and things that we're and a lot of tech and things that we're good at. you know, let's apply what good at. you know, let's apply what good at. you know, let's apply what we're good at to taking on some of the we're good at to taking on some of the we're good at to taking on some of the biggest problems uh in the world because biggest problems uh in the world because biggest problems uh in the world because we care about that stuff. Um and also, we care about that stuff. Um and also, we care about that stuff. Um and also, how about the Seahawks last night how about the Seahawks last night how about the Seahawks last night >> in the game against the Rams? Wow. That >> in the game against the Rams? Wow. That >> in the game against the Rams? Wow. That might have been the best game of the might have been the best game of the might have been the best game of the year. I've never seen anything like it. year. I've never seen anything like it. year. I've never seen anything like it. What a comeback. Wow. So, sometimes What a comeback. Wow. So, sometimes What a comeback. Wow. So, sometimes learn from football. You got to go for learn from football. You got to go for learn from football. You got to go for things. It might mean going for two things. It might mean going for two things. It might mean going for two twice in overtime to win the game. And twice in overtime to win the game. And twice in overtime to win the game. And there you go. So, I love that. And also, there you go. So, I love that. And also, there you go. So, I love that. And also, my biggest bit of advice is when you're my biggest bit of advice is when you're my biggest bit of advice is when you're uncertain about a decision, whatever, uncertain about a decision, whatever, uncertain about a decision, whatever, just listen to Marshon Lynch. Whatever just listen to Marshon Lynch. Whatever just listen to Marshon Lynch. Whatever he tells [laughter] you is what you he tells [laughter] you is what you he tells [laughter] you is what you should go with. So, remember, listen to should go with. So, remember, listen to should go with. So, remember, listen to Beast Mode. That's the the wisdom of Beast Mode. That's the the wisdom of Beast Mode. That's the the wisdom of Yoda.

Yoda. Yoda. >> And we are out. Adios. >> And we are out. Adios. >> And we are out. Adios. >> Yes. Done with zero alcohol. >> Yes. Done with zero alcohol. >> Yes. Done with zero alcohol. [music]