IoT Coffee Talk: Episode 266 - "Underwater Basket Weaving (The College Major for an AI Future)"

I have trouble pulling off an entire I have trouble pulling off an entire song. song. song. [Music] Hey Hey [Music] [Music] [Music] and we know the tune. Nice. And I I and we know the tune. Nice. And I I and we know the tune. Nice. And I I don't want to risk screwing up even more don't want to risk screwing up even more don't want to risk screwing up even more because I am extremely jetlagged. I because I am extremely jetlagged. I because I am extremely jetlagged. I think you caught the essence of that think you caught the essence of that think you caught the essence of that song. That was good. Oh my god. I song. That was good. Oh my god. I song. That was good. Oh my god. I watched an air guitar contest on TV. watched an air guitar contest on TV. watched an air guitar contest on TV. Like I didn't I didn't know like they Like I didn't I didn't know like they Like I didn't I didn't know like they actually had it on TV. Is that Is that actually had it on TV. Is that Is that actually had it on TV. Is that Is that ESPN Plus or something? No, ESPN Plus or something? No, ESPN Plus or something? No, they don't even have that on. Oh my god.

they don't even have that on. Oh my god. they don't even have that on. Oh my god. These people are just like running These people are just like running These people are just like running around the stage dressed in hair and around the stage dressed in hair and around the stage dressed in hair and everything at makeup and playing air everything at makeup and playing air everything at makeup and playing air guitar contests for like a $100,000 guitar contests for like a $100,000 guitar contests for like a $100,000 first prize. First prize. Serious? Yeah, first prize. First prize. Serious? Yeah, first prize. First prize. Serious? Yeah, I was on the table. I was like I'm like, I was on the table. I was like I'm like, I was on the table. I was like I'm like, "Honey, you got to look at this. Look at "Honey, you got to look at this. Look at "Honey, you got to look at this. Look at these idiots." I thought it was just me these idiots." I thought it was just me these idiots." I thought it was just me in the shower. in the shower. in the shower. So, you go to college for four years, So, you go to college for four years, So, you go to college for four years, you come home and you become an air you come home and you become an air you come home and you become an air guitarist and you know, right? Sounds guitarist and you know, right? Sounds guitarist and you know, right? Sounds weird. weird. weird. Oh my gosh. Yeah. Data diva is here. Oh my gosh. Yeah. Data diva is here. Oh my gosh. Yeah. Data diva is here. What is this? Data diva iPhone What is this? Data diva iPhone What is this? Data diva iPhone DRC business. Will she put her picture DRC business. Will she put her picture DRC business. Will she put her picture on? Yeah. Debbie. Oh, I know. on? Yeah. Debbie. Oh, I know. on? Yeah. Debbie. Oh, I know. Yeah. Hey, how's it going? Hey, how are Yeah. Hey, how's it going? Hey, how are Yeah. Hey, how's it going? Hey, how are you guys here? A little icon thing is is you guys here? A little icon thing is is you guys here? A little icon thing is is like gone. Oh, you know, I'm dial in like gone. Oh, you know, I'm dial in like gone. Oh, you know, I'm dial in from on a different phone. Do you want from on a different phone. Do you want from on a different phone. Do you want me to dial in on my other phone? Yeah, me to dial in on my other phone? Yeah, me to dial in on my other phone? Yeah, maybe because this looks like really maybe because this looks like really maybe because this looks like really weird. Okay. Yeah, let me let me log off weird. Okay. Yeah, let me let me log off weird. Okay. Yeah, let me let me log off of this and then go on the other one.

of this and then go on the other one. of this and then go on the other one. Okay. Okay. Okay. So, hey everyone. Welcome to IoT Coffee So, hey everyone. Welcome to IoT Coffee So, hey everyone. Welcome to IoT Coffee Talk. Uh remember um take us seriously Talk. Uh remember um take us seriously Talk. Uh remember um take us seriously at your your own risk at your peril. at your your own risk at your peril. at your your own risk at your peril. Yeah. So you have to you're going to Yeah. So you have to you're going to Yeah. So you have to you're going to have to mine through our nonsense, have to mine through our nonsense, have to mine through our nonsense, right? In order to get the good insights right? In order to get the good insights right? In order to get the good insights and and and takeaways that are going to takeaways that are going to takeaways that are going to revolutionize your whole business and revolutionize your whole business and revolutionize your whole business and transform industries, right? So, um, transform industries, right? So, um, transform industries, right? So, um, yeah, we're we're doing all this for yeah, we're we're doing all this for yeah, we're we're doing all this for the love of the kids, okay? K through 12 the love of the kids, okay? K through 12 the love of the kids, okay? K through 12 IoT Coffee Talk. We have, um, a charity, IoT Coffee Talk. We have, um, a charity, IoT Coffee Talk. We have, um, a charity, Elevate our Kids at www.elevatorids.org, Elevate our Kids at www.elevatorids.org, Elevate our Kids at www.elevatorids.org, where we're trying to help bridge the where we're trying to help bridge the where we're trying to help bridge the digital divide for kids K through 12. digital divide for kids K through 12. digital divide for kids K through 12. And we hope you have it in your hearts And we hope you have it in your hearts And we hope you have it in your hearts to donate, you know, uh, and help these to donate, you know, uh, and help these to donate, you know, uh, and help these kids out, right? We need uh to foster kids out, right? We need uh to foster kids out, right? We need uh to foster bright futures for everyone in this age bright futures for everyone in this age bright futures for everyone in this age of AI where the AI gods are going after of AI where the AI gods are going after of AI where the AI gods are going after our jobs and our purpose, our jobs and our purpose, our jobs and our purpose, right? Isn't that right, Pete? That's right? Isn't that right, Pete? That's right? Isn't that right, Pete? That's the rumor. Mr. Edge AI, the rumor. Mr. Edge AI, the rumor. Mr. Edge AI, it's all going to happen. That's the it's all going to happen. That's the it's all going to happen. That's the crazy thing, right?

crazy thing, right? crazy thing, right? It's all new young people that are It's all new young people that are It's all new young people that are screwing it up to the old people, you screwing it up to the old people, you screwing it up to the old people, you know? know? know? I thought it was the old people who I thought it was the old people who I thought it was the old people who screwed it up for the young people the screwed it up for the young people the screwed it up for the young people the other way around. I don't know. other way around. I don't know. other way around. I don't know. Yeah, actually you're right. Yeah. So, Yeah, actually you're right. Yeah. So, Yeah, actually you're right. Yeah. So, uh Yeah. Welcome everybody. How's it uh Yeah. Welcome everybody. How's it uh Yeah. Welcome everybody. How's it going? So, Leonard, it sounds you going? So, Leonard, it sounds you going? So, Leonard, it sounds you mentioned your jet lag. Where did you mentioned your jet lag. Where did you mentioned your jet lag. Where did you fly in from? Oh, I was in Copenhagen fly in from? Oh, I was in Copenhagen fly in from? Oh, I was in Copenhagen for DTW uh TM Forums Digital for DTW uh TM Forums Digital for DTW uh TM Forums Digital Transformation World Ignite 2025. I Transformation World Ignite 2025. I Transformation World Ignite 2025. I haven't I hadn't been to one uh in about haven't I hadn't been to one uh in about haven't I hadn't been to one uh in about two years, two three years. Um just two years, two three years. Um just two years, two three years. Um just because you know there wasn't a lot because you know there wasn't a lot because you know there wasn't a lot happening with telco and digital happening with telco and digital happening with telco and digital transformation. Everybody was kind of transformation. Everybody was kind of transformation. Everybody was kind of down and out about it right uh again down and out about it right uh again down and out about it right uh again uh victim of hype cycles and um you know uh victim of hype cycles and um you know uh victim of hype cycles and um you know there was all this talk about private there was all this talk about private there was all this talk about private networks and uh freaking you know uh networks and uh freaking you know uh networks and uh freaking you know uh metaverse and all this other nonsense. metaverse and all this other nonsense. metaverse and all this other nonsense. So actually I think a lot of the So actually I think a lot of the So actually I think a lot of the metaverse nonsense sucked the oxygen out metaverse nonsense sucked the oxygen out metaverse nonsense sucked the oxygen out of the room for all of the 5G moni you of the room for all of the 5G moni you of the room for all of the 5G moni you know like transformation modernization know like transformation modernization know like transformation modernization topics that I was trying to right and um topics that I was trying to right and um topics that I was trying to right and um yeah because remember everybody was so yeah because remember everybody was so yeah because remember everybody was so preoccupied with hey we're a metaverse preoccupied with hey we're a metaverse preoccupied with hey we're a metaverse company oh we're in the metaverse is company oh we're in the metaverse is company oh we're in the metaverse is going to change every oh you need to going to change every oh you need to going to change every oh you need to have a metaverse ready network right have a metaverse ready network right have a metaverse ready network right I I I'm serious Yes. Yeah. People have

I I I'm serious Yes. Yeah. People have I I I'm serious Yes. Yeah. People have to remember this crap because this is to remember this crap because this is to remember this crap because this is this is like a lineage of uh stupidity, this is like a lineage of uh stupidity, this is like a lineage of uh stupidity, right? It is. I mean, you know, right? It is. I mean, you know, right? It is. I mean, you know, everybody wants, you know, talks about everybody wants, you know, talks about everybody wants, you know, talks about data lineage lineage. We need stupidity data lineage lineage. We need stupidity data lineage lineage. We need stupidity lineage, right? Where we're able to lineage, right? Where we're able to lineage, right? Where we're able to track all the stupid crap that we've track all the stupid crap that we've track all the stupid crap that we've done so that we don't make the same done so that we don't make the same done so that we don't make the same mistakes again. But, you know, as they mistakes again. But, you know, as they mistakes again. But, you know, as they say, we need a say, we need a say, we need a we need a way back machine. Yeah. We we need a way back machine. Yeah. We we need a way back machine. Yeah. We need to start a cryptocurrency in a uh need to start a cryptocurrency in a uh need to start a cryptocurrency in a uh you know uh distributed ledger to track you know uh distributed ledger to track you know uh distributed ledger to track historical stupidity. Maybe there's a historical stupidity. Maybe there's a historical stupidity. Maybe there's a way to mine the LinkedIn posts. We can way to mine the LinkedIn posts. We can way to mine the LinkedIn posts. We can mine LinkedIn posts going back over mine LinkedIn posts going back over mine LinkedIn posts going back over time. time. time. Guys, there's no way we have enough CPUs Guys, there's no way we have enough CPUs Guys, there's no way we have enough CPUs and GPUs to and GPUs to and GPUs to We can invent a new thing. It's called We can invent a new thing. It's called We can invent a new thing. It's called stupidity as a service, right? SAS. stupidity as a service, right? SAS. stupidity as a service, right? SAS. Yeah. It's called the internet. It's Yeah. It's called the internet. It's Yeah. It's called the internet. It's called the internet, man. Yeah. Yeah. called the internet, man. Yeah. Yeah. called the internet, man. Yeah. Yeah. Yeah. But I mean that that that's I Yeah. But I mean that that that's I Yeah. But I mean that that that's I think the whole problem with FOMO. FOMO think the whole problem with FOMO. FOMO think the whole problem with FOMO. FOMO fosters um just you know just rampant fosters um just you know just rampant fosters um just you know just rampant stupidity. You know just people making stupidity. You know just people making stupidity. You know just people making up stuff and everyone becoming lemmings up stuff and everyone becoming lemmings up stuff and everyone becoming lemmings that are ready to go jump off the cliff that are ready to go jump off the cliff that are ready to go jump off the cliff or run off the cliff with everyone else.

or run off the cliff with everyone else. or run off the cliff with everyone else. I mean yeah of course you can't really I mean yeah of course you can't really I mean yeah of course you can't really listen to journalists right? So they're listen to journalists right? So they're listen to journalists right? So they're just looking for the next shiny object just looking for the next shiny object just looking for the next shiny object to talk about. They don't know what the to talk about. They don't know what the to talk about. They don't know what the hell they're talking about. True. True. hell they're talking about. True. True. hell they're talking about. True. True. So anyway, the hype cycle. Yeah, it was So anyway, the hype cycle. Yeah, it was So anyway, the hype cycle. Yeah, it was good. Speaking of Speaking of the hype good. Speaking of Speaking of the hype good. Speaking of Speaking of the hype cycle. Uhhuh. Welcome, Rob. Oh yeah, he cycle. Uhhuh. Welcome, Rob. Oh yeah, he cycle. Uhhuh. Welcome, Rob. Oh yeah, he is the hype cycle. What's up? Happy is the hype cycle. What's up? Happy is the hype cycle. What's up? Happy midsummer, everyone. midsummer, everyone. midsummer, everyone. June. June. June. Yeah, I think it's the solstice. It's Yeah, I think it's the solstice. It's Yeah, I think it's the solstice. It's the solstice. the solstice. the solstice. Tomorrow I get to stay at the beach as Tomorrow I get to stay at the beach as Tomorrow I get to stay at the beach as long as possible. That's right. Right. long as possible. That's right. Right. long as possible. That's right. Right. Really? Isn't it like really really hot? Really? Isn't it like really really hot? Really? Isn't it like really really hot? Not not with the breeze coming off the Not not with the breeze coming off the Not not with the breeze coming off the ocean the last two. Okay. Lucky you. ocean the last two. Okay. Lucky you. ocean the last two. Okay. Lucky you. Lucky you. Everyone else is like s Lucky you. Everyone else is like s Lucky you. Everyone else is like s sizzling, baking, and steaming, right? sizzling, baking, and steaming, right? sizzling, baking, and steaming, right? Yeah. Welcome to the new world. Yeah, Yeah. Welcome to the new world. Yeah, Yeah. Welcome to the new world. Yeah, Bob. All you have to do is go uh up to Bob. All you have to do is go uh up to Bob. All you have to do is go uh up to the middle of Alaska for 97 degree days. the middle of Alaska for 97 degree days. the middle of Alaska for 97 degree days. Man, not a bad deal. Not a bad deal.

Man, not a bad deal. Not a bad deal. Man, not a bad deal. Not a bad deal. Yeah. I grow my best wine up in Alaska Yeah. I grow my best wine up in Alaska Yeah. I grow my best wine up in Alaska these days. Really been a real game these days. Really been a real game these days. Really been a real game changer for me. Never thought that I'd changer for me. Never thought that I'd changer for me. Never thought that I'd be able to buy so much cheap land for my be able to buy so much cheap land for my be able to buy so much cheap land for my new vineyards. It's not ice wine either, new vineyards. It's not ice wine either, new vineyards. It's not ice wine either, is it? Is it? No, we're getting some is it? Is it? No, we're getting some is it? Is it? No, we're getting some good cabs and straws, so it's all good cabs and straws, so it's all good cabs and straws, so it's all working out. Yeah, I'll be in Alaska at working out. Yeah, I'll be in Alaska at working out. Yeah, I'll be in Alaska at the end of August, I'll come out there the end of August, I'll come out there the end of August, I'll come out there and till with you. Excellent. Love the and till with you. Excellent. Love the and till with you. Excellent. Love the tilling. Yeah. I think this this time of tilling. Yeah. I think this this time of tilling. Yeah. I think this this time of year is when you know like how um during year is when you know like how um during year is when you know like how um during Christmas Mariah Care's uh you know, Christmas Mariah Care's uh you know, Christmas Mariah Care's uh you know, Christmas um album the only way she Christmas um album the only way she Christmas um album the only way she makes $3 million a year. Yeah. Yeah. I makes $3 million a year. Yeah. Yeah. I makes $3 million a year. Yeah. Yeah. I think I think uh this time of year is think I think uh this time of year is think I think uh this time of year is when Nelly uh record sales go up with when Nelly uh record sales go up with when Nelly uh record sales go up with that one tune that he has is like what that one tune that he has is like what that one tune that he has is like what what is that tune? It's getting hot. what is that tune? It's getting hot. what is that tune? It's getting hot. It's getting hot in here. So take off It's getting hot in here. So take off It's getting hot in here. So take off all your clothes. Yeah. Exactly. So all your clothes. Yeah. Exactly. So all your clothes. Yeah. Exactly. So yeah, we all love Nelly at this time of yeah, we all love Nelly at this time of yeah, we all love Nelly at this time of year, especially in Vegas. There you go.

year, especially in Vegas. There you go. year, especially in Vegas. There you go. Yeah. where we're where all the tech Yeah. where we're where all the tech Yeah. where we're where all the tech companies want to converge us on a companies want to converge us on a companies want to converge us on a monthly basis, which is ridiculous. I monthly basis, which is ridiculous. I monthly basis, which is ridiculous. I have to go I have to go back there on have to go I have to go back there on have to go I have to go back there on Monday. Damn it. Oh my god. I just got Monday. Damn it. Oh my god. I just got Monday. Damn it. Oh my god. I just got home and I got to go back again on home and I got to go back again on home and I got to go back again on Monday, man. It's just backtoback Vegas Monday, man. It's just backtoback Vegas Monday, man. It's just backtoback Vegas sizzles. sizzles. sizzles. Well, if you guys need a break, you Well, if you guys need a break, you Well, if you guys need a break, you know, we're we're going to be in Milan know, we're we're going to be in Milan know, we're we're going to be in Milan first week of July. Although, I was first week of July. Although, I was first week of July. Although, I was going to say it's going to be hot. So, going to say it's going to be hot. So, going to say it's going to be hot. So, I'll be there. That's when I'll be I'll be there. That's when I'll be I'll be there. That's when I'll be there, too. All right. Come by. do live there, too. All right. Come by. do live there, too. All right. Come by. do live a live broadcast that Friday the 11th or a live broadcast that Friday the 11th or a live broadcast that Friday the 11th or whatever it is. Yeah. No, have fun. I whatever it is. Yeah. No, have fun. I whatever it is. Yeah. No, have fun. I can't make it out. I had this just way can't make it out. I had this just way can't make it out. I had this just way too much travel for me. Yeah, I could too much travel for me. Yeah, I could too much travel for me. Yeah, I could imagine. I will be with you guys in imagine. I will be with you guys in imagine. I will be with you guys in spirit. So, have fun. Good. No, it'll be spirit. So, have fun. Good. No, it'll be spirit. So, have fun. Good. No, it'll be it'll be fun time. We're going to be it'll be fun time. We're going to be it'll be fun time. We're going to be packed packed, but I So I was looking at packed packed, but I So I was looking at packed packed, but I So I was looking at the weather forecast. I mean, it'll be the weather forecast. I mean, it'll be the weather forecast. I mean, it'll be like mid mid 80s high 80s. Not the end like mid mid 80s high 80s. Not the end like mid mid 80s high 80s. Not the end of the world. Yeah, I'm going to be in of the world. Yeah, I'm going to be in of the world. Yeah, I'm going to be in Lugano at the World Championships for 13 Lugano at the World Championships for 13 Lugano at the World Championships for 13 days, leaving next Tuesday and it's like days, leaving next Tuesday and it's like days, leaving next Tuesday and it's like 85 basketball the basketball 85 basketball the basketball 85 basketball the basketball championship.

championship. championship. 85 but as low as 70 in Lugano. Love 85 but as low as 70 in Lugano. Love 85 but as low as 70 in Lugano. Love that. I've been to Lugano. That's that. I've been to Lugano. That's that. I've been to Lugano. That's awesome, dude. Tell me what to do. awesome, dude. Tell me what to do. awesome, dude. Tell me what to do. Keep scooting on over to Lake Ko. That's Keep scooting on over to Lake Ko. That's Keep scooting on over to Lake Ko. That's what you got to do. Yeah, I will do that what you got to do. Yeah, I will do that what you got to do. Yeah, I will do that on my first on my first on my first Thursday when we don't have a game going Thursday when we don't have a game going Thursday when we don't have a game going over. Awesome. Yeah. Um over. Awesome. Yeah. Um over. Awesome. Yeah. Um yeah. Hey um Pete, you should check out yeah. Hey um Pete, you should check out yeah. Hey um Pete, you should check out um the catalyst program that TM forum um the catalyst program that TM forum um the catalyst program that TM forum has for it. It's really good. You got has for it. It's really good. You got has for it. It's really good. You got you might want to just study that you might want to just study that you might want to just study that because they put together such a great because they put together such a great because they put together such a great program. What did you learn? What did I program. What did you learn? What did I program. What did you learn? What did I learn? Um what I learned. It's not what learn? Um what I learned. It's not what learn? Um what I learned. It's not what I learned typically because I do such I learned typically because I do such I learned typically because I do such broad research. It's more of I go in broad research. It's more of I go in broad research. It's more of I go in there just to see whether or not um you there just to see whether or not um you there just to see whether or not um you know these folks that are talking all know these folks that are talking all know these folks that are talking all this fluffy innovation stuff actually this fluffy innovation stuff actually this fluffy innovation stuff actually know what they're talking about. And um know what they're talking about. And um know what they're talking about. And um what I'm what I'm seeing is that even what I'm what I'm seeing is that even what I'm what I'm seeing is that even through these catalyst um projects that through these catalyst um projects that through these catalyst um projects that that you have um operators as well as that you have um operators as well as that you have um operators as well as the vendors collaborate on, they're the vendors collaborate on, they're the vendors collaborate on, they're discovering this stuff is so hard, you discovering this stuff is so hard, you discovering this stuff is so hard, you know. And you know, one of the things know. And you know, one of the things know. And you know, one of the things that they keep bringing up is how the that they keep bringing up is how the that they keep bringing up is how the data is the problem. There's readiness data is the problem. There's readiness data is the problem. There's readiness issues from a operational standpoint or, issues from a operational standpoint or, issues from a operational standpoint or, you know, change management. All you know, change management. All you know, change management. All prototypical, you know, stuff that prototypical, you know, stuff that prototypical, you know, stuff that everyone brings up every single, everyone brings up every single, everyone brings up every single, you know, tech hype cycle. Uh, but one you know, tech hype cycle. Uh, but one you know, tech hype cycle. Uh, but one of the things that they don't realize is of the things that they don't realize is of the things that they don't realize is that with AI, we brought up on the show,

that with AI, we brought up on the show, that with AI, we brought up on the show, it's about knowledge. If your knowledge it's about knowledge. If your knowledge it's about knowledge. If your knowledge is crap, your data, it can be good. your is crap, your data, it can be good. your is crap, your data, it can be good. your AI still is going to be crap. You know AI still is going to be crap. You know AI still is going to be crap. You know what I'm saying? And so, um, I don't what I'm saying? And so, um, I don't what I'm saying? And so, um, I don't think they've come to that realization think they've come to that realization think they've come to that realization yet, but like, you know, in most yet, but like, you know, in most yet, but like, you know, in most instances, there's this whole instances, there's this whole instances, there's this whole realization, but there are some realization, but there are some realization, but there are some companies that are ahead of the curve. companies that are ahead of the curve. companies that are ahead of the curve. You can tell and it's probably because You can tell and it's probably because You can tell and it's probably because they, you know, follow me and they, you know, follow me and they, you know, follow me and follow Next Research that goes without follow Next Research that goes without follow Next Research that goes without saying. I mean, I have to I have to say, saying. I mean, I have to I have to say, saying. I mean, I have to I have to say, man, you just read my stuff. It's like, man, you just read my stuff. It's like, man, you just read my stuff. It's like, holy You know, you called it two holy You know, you called it two holy You know, you called it two years ago. No, no, I actually have years ago. No, no, I actually have years ago. No, no, I actually have people send me stuff. They say, "Look at people send me stuff. They say, "Look at people send me stuff. They say, "Look at this Mackenzie report. You talked about this Mackenzie report. You talked about this Mackenzie report. You talked about this you know, 16 months ago as 18 this you know, 16 months ago as 18 this you know, 16 months ago as 18 months ago." I mean, the evidence is months ago." I mean, the evidence is months ago." I mean, the evidence is there. It's not like I'm making this there. It's not like I'm making this there. It's not like I'm making this stuff up, but it, you know, there are stuff up, but it, you know, there are stuff up, but it, you know, there are are companies that I do talk to, so they are companies that I do talk to, so they are companies that I do talk to, so they follow my stuff. they're they they're follow my stuff. they're they they're follow my stuff. they're they they're they're they're they're being much more sensible about the the being much more sensible about the the being much more sensible about the the um the AI. Um the other thing is that um the AI. Um the other thing is that um the AI. Um the other thing is that the biggest challenge and it's one of my the biggest challenge and it's one of my the biggest challenge and it's one of my top takes for um the event was uh top takes for um the event was uh top takes for um the event was uh carrier grade is the most important carrier grade is the most important carrier grade is the most important vector. I mean you can imagine all kinds vector. I mean you can imagine all kinds vector. I mean you can imagine all kinds of crap right? Making a carrier grade is of crap right? Making a carrier grade is of crap right? Making a carrier grade is the primary vector of innovation that the primary vector of innovation that the primary vector of innovation that people need to focus on because you can people need to focus on because you can people need to focus on because you can concoct anything in your imagination concoct anything in your imagination concoct anything in your imagination about how AI can do XYZ.

about how AI can do XYZ. about how AI can do XYZ. Figuring out those little artifacts the Figuring out those little artifacts the Figuring out those little artifacts the architectures the structures that can architectures the structures that can architectures the structures that can make that idea make that idea make that idea uh telco grade uh telco grade uh telco grade is the biggest problem. And then what's is the biggest problem. And then what's is the biggest problem. And then what's your vector? Victor. your vector? Victor. your vector? Victor. Yeah. Yeah. Yeah. I just love that word, Rob. You know, I just love that word, Rob. You know, I just love that word, Rob. You know, vector. Oh my god. But that's all but vector. Oh my god. But that's all but vector. Oh my god. But that's all but but you're talking about but you're talking about but you're talking about commercialization of going from the P to commercialization of going from the P to commercialization of going from the P to the deployment to a commercialized the deployment to a commercialized the deployment to a commercialized deployment that's actually robust and deployment that's actually robust and deployment that's actually robust and sustainable in the real world. And sustainable in the real world. And sustainable in the real world. And that's and there's always a big gap that's and there's always a big gap that's and there's always a big gap there between I made this tech and I there between I made this tech and I there between I made this tech and I actually deployed it for like an actually deployed it for like an actually deployed it for like an extended period of time. So that carrier extended period of time. So that carrier extended period of time. So that carrier grade to me is another way of saying grade to me is another way of saying grade to me is another way of saying like squeezing all the bugs and like squeezing all the bugs and like squeezing all the bugs and performance issues out and s and so that performance issues out and s and so that performance issues out and s and so that it's really predictable and reliable and it's really predictable and reliable and it's really predictable and reliable and supportable and that's a that's supportable and that's a that's supportable and that's a that's unglamorous work by the way very unglamorous work by the way very unglamorous work by the way very unglamorous work but there's always this unglamorous work but there's always this unglamorous work but there's always this gap and we see it all the time gap and we see it all the time gap and we see it all the time especially in the and I see it in the especially in the and I see it in the especially in the and I see it in the edge space too. It's like you've got edge space too. It's like you've got edge space too. It's like you've got this cool thing, but it's like, okay, I this cool thing, but it's like, okay, I this cool thing, but it's like, okay, I want to deploy 100,000 of them across want to deploy 100,000 of them across want to deploy 100,000 of them across all these oil wells. It's like, okay, all these oil wells. It's like, okay, all these oil wells. It's like, okay, there's a big gap. There's a lot of work there's a big gap. There's a lot of work there's a big gap. There's a lot of work there. Doesn't seem like it cuz it's there. Doesn't seem like it cuz it's there. Doesn't seem like it cuz it's working here, but on your desk, in the working here, but on your desk, in the working here, but on your desk, in the lab, it works. But that's a that's a lab, it works. But that's a that's a lab, it works. But that's a that's a that's an opportunity gap there. I just that's an opportunity gap there. I just that's an opportunity gap there. I just love the term carrier grade. You know, love the term carrier grade. You know, love the term carrier grade. You know, carrier grade used to mean something a carrier grade used to mean something a carrier grade used to mean something a long time ago. It meant specialized long time ago. It meant specialized long time ago. It meant specialized hardware that was the most expensive hardware that was the most expensive hardware that was the most expensive thing possible for mobile networks. It thing possible for mobile networks. It thing possible for mobile networks. It meant you were running AIX and from IBM

meant you were running AIX and from IBM meant you were running AIX and from IBM or Solaris, you know, hardcore Unix and or Solaris, you know, hardcore Unix and or Solaris, you know, hardcore Unix and then carrier grade. Well, there's the then carrier grade. Well, there's the then carrier grade. Well, there's the carrier grade as Pete's talking about, carrier grade as Pete's talking about, carrier grade as Pete's talking about, but carrier grade was a telco but carrier grade was a telco but carrier grade was a telco terminology and and now, you know, terminology and and now, you know, terminology and and now, you know, they've been trying desperately to not they've been trying desperately to not they've been trying desperately to not be carrier grade for years. They're be carrier grade for years. They're be carrier grade for years. They're trying to go commodity servers, run fast trying to go commodity servers, run fast trying to go commodity servers, run fast and break things. Yeah. And so it's like and break things. Yeah. And so it's like and break things. Yeah. And so it's like do like meta do you know just you know do like meta do you know just you know do like meta do you know just you know have let the software hold it together have let the software hold it together have let the software hold it together like all the clouds servers are failing. like all the clouds servers are failing. like all the clouds servers are failing. Yeah. Maybe your call drops, maybe it Yeah. Maybe your call drops, maybe it Yeah. Maybe your call drops, maybe it doesn't. Whatever. No big deal. Right. doesn't. Whatever. No big deal. Right. doesn't. Whatever. No big deal. Right. Yeah. You're you're good. Yeah. Yeah. You're you're good. Yeah. Yeah. You're you're good. Yeah. Yeah. No, it's true. It's lost a little Yeah. No, it's true. It's lost a little Yeah. No, it's true. It's lost a little bit of its luster in terms of uh bit of its luster in terms of uh bit of its luster in terms of uh terminology, but I get it. Yeah. And oh, terminology, but I get it. Yeah. And oh, terminology, but I get it. Yeah. And oh, the other thing I discovered is a lot of the other thing I discovered is a lot of the other thing I discovered is a lot of people know about our show. people know about our show. people know about our show. You know, the first thing, especially if You know, the first thing, especially if You know, the first thing, especially if I bump into Eric for a second, they go, I bump into Eric for a second, they go, I bump into Eric for a second, they go, "Oh, yeah. You play guitar and you hang "Oh, yeah. You play guitar and you hang "Oh, yeah. You play guitar and you hang out with Rob."

Yeah. Nelly. Yeah. And um it's pretty Yeah. Nelly. Yeah. And um it's pretty funny. Yeah. Pretty funny. funny. Yeah. Pretty funny. funny. Yeah. Pretty funny. Yeah. IoT Buffy talk community, you Yeah. IoT Buffy talk community, you Yeah. IoT Buffy talk community, you know, whether it's MWC or DJ, you know, whether it's MWC or DJ, you know, whether it's MWC or DJ, you haven't been there in a while, people haven't been there in a while, people haven't been there in a while, people jump out of the woodworks and you know, jump out of the woodworks and you know, jump out of the woodworks and you know, the first thing they they don't know if the first thing they they don't know if the first thing they they don't know if this is a tech podcast or if this is this is a tech podcast or if this is this is a tech podcast or if this is like Millie vanilla. I think in addition to many other issues I think in addition to many other issues that we can talk about with AI, I think that we can talk about with AI, I think that we can talk about with AI, I think especially when you're trying to deploy especially when you're trying to deploy especially when you're trying to deploy something where accuracy is important, something where accuracy is important, something where accuracy is important, vital in in fact, uh it it just doesn't vital in in fact, uh it it just doesn't vital in in fact, uh it it just doesn't cut it, right? So people trying to do be cut it, right? So people trying to do be cut it, right? So people trying to do be AI first and stuff, I mean it just it AI first and stuff, I mean it just it AI first and stuff, I mean it just it just doesn't work that way. Yeah. Yeah. just doesn't work that way. Yeah. Yeah. just doesn't work that way. Yeah. Yeah. Yeah. anything deterministic. I mean AI Yeah. anything deterministic. I mean AI Yeah. anything deterministic. I mean AI is inherently an indeterministic system. is inherently an indeterministic system. is inherently an indeterministic system. So you want to be this is the issue like So you want to be this is the issue like So you want to be this is the issue like like aerospace has with AI, right? The like aerospace has with AI, right? The like aerospace has with AI, right? The aerospace industry which you know needs aerospace industry which you know needs aerospace industry which you know needs to be very deterministic and very to be very deterministic and very to be very deterministic and very buttoned up and all the data needs to buttoned up and all the data needs to buttoned up and all the data needs to have, you know, provenance and have, you know, provenance and have, you know, provenance and integrity. Um and you start you can't integrity. Um and you start you can't integrity. Um and you start you can't just kind of throw a a Jetson box in just kind of throw a a Jetson box in just kind of throw a a Jetson box in there and starting it. Well, but I mean there and starting it. Well, but I mean there and starting it. Well, but I mean we we we we talked about that on the we we we we talked about that on the we we we we talked about that on the show several times. I think show several times. I think show several times. I think it's statistical is based on existing it's statistical is based on existing it's statistical is based on existing text. So it's so I always say the same text. So it's so I always say the same text. So it's so I always say the same thing. If you're looking to learn about thing. If you're looking to learn about thing. If you're looking to learn about the subject area that has been very well

the subject area that has been very well the subject area that has been very well documented for years, it will be of documented for years, it will be of documented for years, it will be of fantastic help. But if you're trying to fantastic help. But if you're trying to fantastic help. But if you're trying to create something totally new or create something totally new or create something totally new or demonstrate something that has not been demonstrate something that has not been demonstrate something that has not been crafted yet, it will just generate crafted yet, it will just generate crafted yet, it will just generate garbage. It is as simple as that. So garbage. It is as simple as that. So garbage. It is as simple as that. So it's very funny because there was this it's very funny because there was this it's very funny because there was this uh that was published in France uh that was published in France uh that was published in France yesterday but I think it's based on MIT yesterday but I think it's based on MIT yesterday but I think it's based on MIT research where they actually looked at research where they actually looked at research where they actually looked at how people cognitively behave when they how people cognitively behave when they how people cognitively behave when they write an essay with AI without AI and it write an essay with AI without AI and it write an essay with AI without AI and it actually shows that you basically you actually shows that you basically you actually shows that you basically you become more dumb if you write essays become more dumb if you write essays become more dumb if you write essays with genai which I would say you make with genai which I would say you make with genai which I would say you make total sense because what you expected to total sense because what you expected to total sense because what you expected to do with an essay is to write new do with an essay is to write new do with an essay is to write new thinking about a new subject. So if you thinking about a new subject. So if you thinking about a new subject. So if you if you expect GI to help you is that if you expect GI to help you is that if you expect GI to help you is that you're totally wrong. So now GI can help you're totally wrong. So now GI can help you're totally wrong. So now GI can help you learn about the subject and then you learn about the subject and then you learn about the subject and then form your mind and write something. But form your mind and write something. But form your mind and write something. But if the use case that is wrong, we're if the use case that is wrong, we're if the use case that is wrong, we're trying to use those things for replace trying to use those things for replace trying to use those things for replace human cognition. Yeah, for me it's human cognition. Yeah, for me it's human cognition. Yeah, for me it's fantastic to just to get access to fantastic to just to get access to fantastic to just to get access to knowledge. Now if it's an edge science, knowledge. Now if it's an edge science, knowledge. Now if it's an edge science, I'm not going to ask Jai. If I want to I'm not going to ask Jai. If I want to I'm not going to ask Jai. If I want to learn about roofing, which I'm doing at learn about roofing, which I'm doing at learn about roofing, which I'm doing at the moment for whatever reason, the moment for whatever reason, the moment for whatever reason, fantastic. Because there's tons of fantastic. Because there's tons of fantastic. Because there's tons of things that have been written about things that have been written about things that have been written about roofing. Yeah. Yeah. I agree with you, roofing. Yeah. Yeah. I agree with you, roofing. Yeah. Yeah. I agree with you, man. I I was doing that with like I had man. I I was doing that with like I had man. I I was doing that with like I had uh um you know, do-it-yourself project uh um you know, do-it-yourself project uh um you know, do-it-yourself project that I had to do for one of the rent, that I had to do for one of the rent, that I had to do for one of the rent, you know, properties that I have. And you know, properties that I have. And you know, properties that I have. And yeah, it was helpful. You take a picture

yeah, it was helpful. You take a picture yeah, it was helpful. You take a picture to how to Yeah. Yeah. But that's not to how to Yeah. Yeah. But that's not to how to Yeah. Yeah. But that's not necessarily generative AI. That's the necessarily generative AI. That's the necessarily generative AI. That's the problem. Everyone thinks that that's problem. Everyone thinks that that's problem. Everyone thinks that that's generative AI. Yeah, it is search. You generative AI. Yeah, it is search. You generative AI. Yeah, it is search. You know, like circle, what do you call know, like circle, what do you call know, like circle, what do you call circle to search on Google? Yeah. I I circle to search on Google? Yeah. I I circle to search on Google? Yeah. I I can't tell you how many people think can't tell you how many people think can't tell you how many people think that's generative AI. It's not. Yeah. that's generative AI. It's not. Yeah. that's generative AI. It's not. Yeah. And when you go and you actually bother And when you go and you actually bother And when you go and you actually bother to ask questions, right? Humans should to ask questions, right? Humans should to ask questions, right? Humans should be good at doing, you discover, hey, oh, be good at doing, you discover, hey, oh, be good at doing, you discover, hey, oh, so this is how you designed it and this so this is how you designed it and this so this is how you designed it and this is how it work. Oh, this has nothing to is how it work. Oh, this has nothing to is how it work. Oh, this has nothing to do with generative A. So, but Demetri, I do with generative A. So, but Demetri, I do with generative A. So, but Demetri, I I want to know why Dimmitri is uh I want to know why Dimmitri is uh I want to know why Dimmitri is uh researching roofies. I don't understand researching roofies. I don't understand researching roofies. I don't understand that. No, roofing. Roofing. Oh, roofing. that. No, roofing. Roofing. Oh, roofing. that. No, roofing. Roofing. Oh, roofing. Okay, roof. Got it. No, but he's going Okay, roof. Got it. No, but he's going Okay, roof. Got it. No, but he's going out clubbing tonight and he was out clubbing tonight and he was out clubbing tonight and he was researching roofies. No, that was a long researching roofies. No, that was a long researching roofies. No, that was a long time ago. We know what he Okay. All time ago. We know what he Okay. All time ago. We know what he Okay. All right. Way past that. Bring it back to right. Way past that. Bring it back to right. Way past that. Bring it back to the center here. He's been the center here. He's been the center here. He's been rehabilitated. He's out of jail. Let's rehabilitated. He's out of jail. Let's rehabilitated. He's out of jail. Let's not bring him back. All right. No to not bring him back. All right. No to not bring him back. All right. No to jail. My mistake. I misheard. No, but jail. My mistake. I misheard. No, but jail. My mistake. I misheard. No, but but I I I'm not totally in agreement but I I I'm not totally in agreement but I I I'm not totally in agreement with you, Leonard, here because I do with you, Leonard, here because I do with you, Leonard, here because I do believe that the problem with search is believe that the problem with search is believe that the problem with search is that there's so much content you can that there's so much content you can that there's so much content you can distill it. And one thing that Gai is distill it. And one thing that Gai is distill it. And one thing that Gai is good at is finding patterns. It's true.

good at is finding patterns. It's true. good at is finding patterns. It's true. That's true. So again, but again, you That's true. So again, but again, you That's true. So again, but again, you have to look at the scope of what you're have to look at the scope of what you're have to look at the scope of what you're looking for. You have to look for things looking for. You have to look for things looking for. You have to look for things that you know or have good confidence that you know or have good confidence that you know or have good confidence that the field has been researched and that the field has been researched and that the field has been researched and there's enough good quality information there's enough good quality information there's enough good quality information about it. And no, but but think about about it. And no, but but think about about it. And no, but but think about how search works, okay? Typically what how search works, okay? Typically what how search works, okay? Typically what we used to do is we used to tag content, we used to do is we used to tag content, we used to do is we used to tag content, right? You tag content, there's metadata right? You tag content, there's metadata right? You tag content, there's metadata that describes um the content and then that describes um the content and then that describes um the content and then now with generative AI, it infers what now with generative AI, it infers what now with generative AI, it infers what that particular artifact, you know, that that particular artifact, you know, that that particular artifact, you know, that document, whatever it is, is right. And document, whatever it is, is right. And document, whatever it is, is right. And you know uh generative AI also leverages you know uh generative AI also leverages you know uh generative AI also leverages meta data. And so as we know on the meta data. And so as we know on the meta data. And so as we know on the internet tagging is not consistent. The internet tagging is not consistent. The internet tagging is not consistent. The the metadata is not consistent. A lot of the metadata is not consistent. A lot of the metadata is not consistent. A lot of is actually crap. And you have had over is actually crap. And you have had over is actually crap. And you have had over years this effort by the search engine years this effort by the search engine years this effort by the search engine companies to make the data better, companies to make the data better, companies to make the data better, right? the metadata better so that you right? the metadata better so that you right? the metadata better so that you can find uh content or at least they can find uh content or at least they can find uh content or at least they could um then control what you could see could um then control what you could see could um then control what you could see more accurately, right? That really is more accurately, right? That really is more accurately, right? That really is the purpose. So balancing, you know, how the purpose. So balancing, you know, how the purpose. So balancing, you know, how do we mic how do we somehow enable our do we mic how do we somehow enable our do we mic how do we somehow enable our marketing microtargeting ad engine with marketing microtargeting ad engine with marketing microtargeting ad engine with valuable s search results, right? That's

valuable s search results, right? That's valuable s search results, right? That's been their goal. And with generative AI, been their goal. And with generative AI, been their goal. And with generative AI, there's this this uh layer of in there's this this uh layer of in there's this this uh layer of in inference that adds all of the inference that adds all of the inference that adds all of the challenges that generative AI engines challenges that generative AI engines challenges that generative AI engines bring to the table, right? Um where I bring to the table, right? Um where I bring to the table, right? Um where I mean it is the hallucinations and mean it is the hallucinations and mean it is the hallucinations and that that doesn't necessarily make that that doesn't necessarily make that that doesn't necessarily make things better. That's why like uh what things better. That's why like uh what things better. That's why like uh what do you call it? Over uh what do you call do you call it? Over uh what do you call do you call it? Over uh what do you call it? The AI overviews, they freaking it? The AI overviews, they freaking it? The AI overviews, they freaking suck. I I don't care what people say. suck. I I don't care what people say. suck. I I don't care what people say. You know, I consistently find uh massive You know, I consistently find uh massive You know, I consistently find uh massive hallucinations and all the results if hallucinations and all the results if hallucinations and all the results if you actually click through everything you actually click through everything you actually click through everything and you act you test the results, right? and you act you test the results, right? and you act you test the results, right? M uh so I I mean I you know what and M uh so I I mean I you know what and M uh so I I mean I you know what and also when I go you know when I was at also when I go you know when I was at also when I go you know when I was at DTW and other conferences is always DTW and other conferences is always DTW and other conferences is always confirmed this stuff is is early we confirmed this stuff is is early we confirmed this stuff is is early we can't push out these agentic frameworks can't push out these agentic frameworks can't push out these agentic frameworks because this is early days you know because this is early days you know because this is early days you know we're piloting maybe or experimenting we're piloting maybe or experimenting we're piloting maybe or experimenting with some customers but this stuff is with some customers but this stuff is with some customers but this stuff is not out there you know and if it is out not out there you know and if it is out not out there you know and if it is out there what is it one of the CISOs got up there what is it one of the CISOs got up there what is it one of the CISOs got up on stage at Cisco Live and says if on stage at Cisco Live and says if on stage at Cisco Live and says if anyone says that they have an answer and anyone says that they have an answer and anyone says that they have an answer and they know what the solution is. They're they know what the solution is. They're they know what the solution is. They're they're a liar. That's what he said on they're a liar. That's what he said on they're a liar. That's what he said on stage and then everyone clapped.

stage and then everyone clapped. stage and then everyone clapped. I mean, you know what I'm saying? And I mean, you know what I'm saying? And I mean, you know what I'm saying? And so, how many bullshitters are out there, so, how many bullshitters are out there, so, how many bullshitters are out there, you know, much? It's incredible, m, you you know, much? It's incredible, m, you you know, much? It's incredible, m, you know, I mean, look what Ericson did. know, I mean, look what Ericson did. know, I mean, look what Ericson did. Ericson's thing was no BS. OSSBS. Ericson's thing was no BS. OSSBS. Ericson's thing was no BS. OSSBS. No BS. Freaking love it. Yeah. And I had No BS. Freaking love it. Yeah. And I had No BS. Freaking love it. Yeah. And I had a chat with Matt uh Matt, you know, Matt a chat with Matt uh Matt, you know, Matt a chat with Matt uh Matt, you know, Matt Carlson, right? Yeah. He didn't he Carlson, right? Yeah. He didn't he Carlson, right? Yeah. He didn't he didn't talk to me about any kind of didn't talk to me about any kind of didn't talk to me about any kind of stuff. I mean, he was like just stuff. I mean, he was like just stuff. I mean, he was like just straight up real. And then AWS, their straight up real. And then AWS, their straight up real. And then AWS, their partner, when they were talking about partner, when they were talking about partner, when they were talking about Agentic, they're very thoughtful. In Agentic, they're very thoughtful. In Agentic, they're very thoughtful. In fact, they took more of a model of, you fact, they took more of a model of, you fact, they took more of a model of, you know, instead of taking the man out of know, instead of taking the man out of know, instead of taking the man out of the middle, putting the man out in the the middle, putting the man out in the the middle, putting the man out in the periphery as well as the AI in the periphery as well as the AI in the periphery as well as the AI in the periphery. So you have to think about periphery. So you have to think about periphery. So you have to think about all this stuff as full life cycle and all this stuff as full life cycle and all this stuff as full life cycle and figure out okay how do we how do we you figure out okay how do we how do we you figure out okay how do we how do we you know leverage automation concepts to put know leverage automation concepts to put know leverage automation concepts to put AI as well as um you know the person in AI as well as um you know the person in AI as well as um you know the person in the periphery to uh drive reliable or the periphery to uh drive reliable or the periphery to uh drive reliable or carriergra uh automation intelligent carriergra uh automation intelligent carriergra uh automation intelligent automation right that that's kind of automation right that that's kind of automation right that that's kind of like the the thinking that everyone is like the the thinking that everyone is like the the thinking that everyone is settling in all the stuff is going to be settling in all the stuff is going to be settling in all the stuff is going to be hybrid so the stuff that Jensen talked hybrid so the stuff that Jensen talked hybrid so the stuff that Jensen talked talks about where everything is going to talks about where everything is going to talks about where everything is going to be autonomous and blah blah blah and be autonomous and blah blah blah and be autonomous and blah blah blah and accelerated computing. Absolutely not.

accelerated computing. Absolutely not. accelerated computing. Absolutely not. Absolutely not. Absolutely not. Absolutely not. That's nonsense. Yeah, but that story That's nonsense. Yeah, but that story That's nonsense. Yeah, but that story sells shovels, right? The sells shovels, right? The sells shovels, right? The setting. It is. But it it when the setting. It is. But it it when the setting. It is. But it it when the ground truth, right, it's at edge AI, ground truth, right, it's at edge AI, ground truth, right, it's at edge AI, right? The ground truth says no. right? The ground truth says no. right? The ground truth says no. Wow. What do you do? There you go. Wow. What do you do? There you go. Wow. What do you do? There you go. How, you know, how are you going to How, you know, how are you going to How, you know, how are you going to reconcile that? Leonard's just blowing reconcile that? Leonard's just blowing reconcile that? Leonard's just blowing up everyone else. I know. Leonard's just up everyone else. I know. Leonard's just up everyone else. I know. Leonard's just causing just I'm trying to help. Setting causing just I'm trying to help. Setting causing just I'm trying to help. Setting it on fire. It's all on fire. it on fire. It's all on fire. it on fire. It's all on fire. I mean, it's just it's the fact. Yeah. I mean, it's just it's the fact. Yeah. I mean, it's just it's the fact. Yeah. It's just not realistic. It's just not realistic. It's just not realistic. Yeah. Yeah. I mean, there we're seeing a Yeah. Yeah. I mean, there we're seeing a Yeah. Yeah. I mean, there we're seeing a lot of people doing it wrong ways, so lot of people doing it wrong ways, so lot of people doing it wrong ways, so we're trying to tell them how to do it we're trying to tell them how to do it we're trying to tell them how to do it the right way. Sure. Sure. Yeah. I see the right way. Sure. Sure. Yeah. I see the right way. Sure. Sure. Yeah. I see Bill's on. Bill, what's up? I I'm just Bill's on. Bill, what's up? I I'm just Bill's on. Bill, what's up? I I'm just enjoying the conversation. enjoying the conversation. enjoying the conversation. I mean, it's a lot of what a lot of what I mean, it's a lot of what a lot of what I mean, it's a lot of what a lot of what um I mean, and you're seeing it across um I mean, and you're seeing it across um I mean, and you're seeing it across other industries that, you know, I mean, other industries that, you know, I mean, other industries that, you know, I mean, when it's made its way into the utility when it's made its way into the utility when it's made its way into the utility industry, industry, industry, you know, you know, you know, there should be widespread panic.

there should be widespread panic. there should be widespread panic. Um I agree. Oh my. they can't control Um I agree. Oh my. they can't control Um I agree. Oh my. they can't control the grid or the devices on the grid or the grid or the devices on the grid or the grid or the devices on the grid or any of that stuff today any of that stuff today any of that stuff today uh in a meaningful way. Um and yet uh in a meaningful way. Um and yet uh in a meaningful way. Um and yet they're they're talking about they're they're talking about they're they're talking about implementing AI and Agentic Frameworks implementing AI and Agentic Frameworks implementing AI and Agentic Frameworks and I'm like and I'm like and I'm like who the hell are you talking to? Yeah, I who the hell are you talking to? Yeah, I who the hell are you talking to? Yeah, I think I think a lot of folks are think I think a lot of folks are think I think a lot of folks are thinking of agentic frameworks as a code thinking of agentic frameworks as a code thinking of agentic frameworks as a code word for replacing human jobs with AI. word for replacing human jobs with AI. word for replacing human jobs with AI. That's like when they say agentic That's like when they say agentic That's like when they say agentic frameworks, they're like, well, I'm frameworks, they're like, well, I'm frameworks, they're like, well, I'm going to have I'm going to create these going to have I'm going to create these going to have I'm going to create these agents, an army of agents instead of agents, an army of agents instead of agents, an army of agents instead of employees. Like the H the it becomes the employees. Like the H the it becomes the employees. Like the H the it becomes the HR department, right? is like, "Yeah, HR department, right? is like, "Yeah, HR department, right? is like, "Yeah, um, I'm going to have all these folks, um, I'm going to have all these folks, um, I'm going to have all these folks, these agents do all this stuff and then these agents do all this stuff and then these agents do all this stuff and then I'll I won't have to hire as many I'll I won't have to hire as many I'll I won't have to hire as many people, which I think is going to be people, which I think is going to be people, which I think is going to be just end in a very big That's just end in a very big That's just end in a very big That's disastrous. That's the equivalent of disastrous. That's the equivalent of disastrous. That's the equivalent of Alexander Haye claiming to be in charge Alexander Haye claiming to be in charge Alexander Haye claiming to be in charge of the inside asylum." That's right.

of the inside asylum." That's right. of the inside asylum." That's right. Okay. Interesting metaphor. I mean, it Okay. Interesting metaphor. I mean, it Okay. Interesting metaphor. I mean, it it is it when you look at it, that's how it is it when you look at it, that's how it is it when you look at it, that's how ridiculous it it sounds, right? I mean, ridiculous it it sounds, right? I mean, ridiculous it it sounds, right? I mean, right. Um, well, now that being said, I right. Um, well, now that being said, I right. Um, well, now that being said, I can look at I look at we've all been in can look at I look at we've all been in can look at I look at we've all been in the in the customer customer service the in the customer customer service the in the customer customer service queue. I mean, probably on a daily queue. I mean, probably on a daily queue. I mean, probably on a daily basis, there's some sort of customer basis, there's some sort of customer basis, there's some sort of customer support scenario we're all part of. And support scenario we're all part of. And support scenario we're all part of. And certainly that area can use a much certainly that area can use a much certainly that area can use a much better kind of AI backend and aentic AI better kind of AI backend and aentic AI better kind of AI backend and aentic AI framework to help people answer framework to help people answer framework to help people answer questions with the most mundane things questions with the most mundane things questions with the most mundane things possible. Oh, yeah. So there's lots of possible. Oh, yeah. So there's lots of possible. Oh, yeah. So there's lots of areas here that'll get improved on a areas here that'll get improved on a areas here that'll get improved on a daily basis and make businesses a lot daily basis and make businesses a lot daily basis and make businesses a lot more efficient. more efficient. more efficient. Unfortunately, they're trying to deploy Unfortunately, they're trying to deploy Unfortunately, they're trying to deploy in the wrong places, right? So whenever in the wrong places, right? So whenever in the wrong places, right? So whenever I hear whenever I hear a company, they I hear whenever I hear a company, they I hear whenever I hear a company, they want to go AI first. Basically, that want to go AI first. Basically, that want to go AI first. Basically, that means that they're putting they're means that they're putting they're means that they're putting they're they're firing humans so that I become they're firing humans so that I become they're firing humans so that I become their employee their employee their employee when I deal with them because I have to when I deal with them because I have to when I deal with them because I have to do all the work now. Yeah, do all the work now. Yeah, do all the work now. Yeah, take your customer service thing, Pete, take your customer service thing, Pete, take your customer service thing, Pete, to another level, too. So, I own uh a to another level, too. So, I own uh a to another level, too. So, I own uh a percentage of a company out of Illinois percentage of a company out of Illinois percentage of a company out of Illinois that is a onshore that is a onshore that is a onshore customer experience tech support firm or customer experience tech support firm or customer experience tech support firm or IoT.

IoT. IoT. We have won some serious deals over the We have won some serious deals over the We have won some serious deals over the last couple of months from companies last couple of months from companies last couple of months from companies that were only doing chat bots for that were only doing chat bots for that were only doing chat bots for support and no one wanted to talk to a support and no one wanted to talk to a support and no one wanted to talk to a chatbot. They wanted nobody does they chatbot. They wanted nobody does they chatbot. They wanted nobody does they wanted to talk to a US onshore human wanted to talk to a US onshore human wanted to talk to a US onshore human being. Now if I'm the screen guy and I'm being. Now if I'm the screen guy and I'm being. Now if I'm the screen guy and I'm using AI in the old you talk about using AI in the old you talk about using AI in the old you talk about coming back the decision tree model coming back the decision tree model coming back the decision tree model uh via AI as a customer service screen. uh via AI as a customer service screen. uh via AI as a customer service screen. Okay. I see. So yeah. So AI is helping Okay. I see. So yeah. So AI is helping Okay. I see. So yeah. So AI is helping that human find the answer interaction that human find the answer interaction that human find the answer interaction with the right. So you've trained your with the right. So you've trained your with the right. So you've trained your geni chat bots to sound like American geni chat bots to sound like American geni chat bots to sound like American humans is what you're saying. No we I'm humans is what you're saying. No we I'm humans is what you're saying. No we I'm just kidding. I'm just kidding. You're just kidding. I'm just kidding. You're just kidding. I'm just kidding. You're just reading it for yourself. Smart ass. just reading it for yourself. Smart ass. just reading it for yourself. Smart ass. My name is Bob. I'm from Ohio. Can I My name is Bob. I'm from Ohio. Can I My name is Bob. I'm from Ohio. Can I help you today? That's right. But isn't help you today? That's right. But isn't help you today? That's right. But isn't that Isn't that just I'm sleeping in that Isn't that just I'm sleeping in that Isn't that just I'm sleeping in Mumbai, though. Isn't that Isn't that Mumbai, though. Isn't that Isn't that Mumbai, though. Isn't that Isn't that just an instance? I mean, to me, I I just an instance? I mean, to me, I I just an instance? I mean, to me, I I guess to some degree I can I can draw guess to some degree I can I can draw guess to some degree I can I can draw some level of rational correlation to some level of rational correlation to some level of rational correlation to the uh you know, customer service end of the uh you know, customer service end of the uh you know, customer service end of it because they have existing runbooks.

it because they have existing runbooks. it because they have existing runbooks. Yeah. Right. They have scripts and they Yeah. Right. They have scripts and they Yeah. Right. They have scripts and they have Yes. And they have the stats. They have Yes. And they have the stats. They have Yes. And they have the stats. They know what the calls are going to be. I know what the calls are going to be. I know what the calls are going to be. I mean, they just Yeah. Yeah. You know, mean, they just Yeah. Yeah. You know, mean, they just Yeah. Yeah. You know, you know what? Um, you know what? Um, you know what? Um, what what what you know what Gen AI is going to you know what Gen AI is going to you know what Gen AI is going to replace? The job that is going to be replace? The job that is going to be replace? The job that is going to be replaced is that of the FAQ page on your replaced is that of the FAQ page on your replaced is that of the FAQ page on your website. That's freaking perfect. You website. That's freaking perfect. You website. That's freaking perfect. You know, I don't I don't see anything wrong know, I don't I don't see anything wrong know, I don't I don't see anything wrong with that. I mean, you know, one of the with that. I mean, you know, one of the with that. I mean, you know, one of the things I was talking to a lot of folks things I was talking to a lot of folks things I was talking to a lot of folks about lately is, you know, underserved about lately is, you know, underserved about lately is, you know, underserved and unserved aspects of customer and unserved aspects of customer and unserved aspects of customer service, right? Abandoned call rates. service, right? Abandoned call rates. service, right? Abandoned call rates. And how about reducing that? How about, And how about reducing that? How about, And how about reducing that? How about, uh, you know, reducing the time to uh, you know, reducing the time to uh, you know, reducing the time to resolution of all these calls that come resolution of all these calls that come resolution of all these calls that come in that are, you know, don't touch a in that are, you know, don't touch a in that are, you know, don't touch a human, right? and are often times just human, right? and are often times just human, right? and are often times just like simple stuff and like FAQ level like simple stuff and like FAQ level like simple stuff and like FAQ level stuff that can be re um resolved if stuff that can be re um resolved if stuff that can be re um resolved if there's you know simple let's say uh you there's you know simple let's say uh you there's you know simple let's say uh you know uh what do you call it tools as know uh what do you call it tools as know uh what do you call it tools as they call them in the agentic AI world they call them in the agentic AI world they call them in the agentic AI world that can go and resolve those very that can go and resolve those very that can go and resolve those very simple things or retrieve information simple things or retrieve information simple things or retrieve information very simply uh to address that um that very simply uh to address that um that very simply uh to address that um that inquiry or that call right resolve that inquiry or that call right resolve that inquiry or that call right resolve that And there's a point of that though, And there's a point of that though, And there's a point of that though, Leonard. We we we use Service Now and Leonard. We we we use Service Now and Leonard. We we we use Service Now and Zenesk for all of our all of our Zenesk for all of our all of our Zenesk for all of our all of our information on the back end. We have a information on the back end. We have a information on the back end. We have a customer that came to us and said we've

customer that came to us and said we've customer that came to us and said we've reduced their multiple call AI generated reduced their multiple call AI generated reduced their multiple call AI generated FAQ stuff to a one call resolution with FAQ stuff to a one call resolution with FAQ stuff to a one call resolution with a with a human. Awesome. With a human. a with a human. Awesome. With a human. a with a human. Awesome. With a human. So you're sitting there going, "Oh, So you're sitting there going, "Oh, So you're sitting there going, "Oh, really?" Yeah. So think about that. So I really?" Yeah. So think about that. So I really?" Yeah. So think about that. So I go to I go to my FAQ, it's AI generated go to I go to my FAQ, it's AI generated go to I go to my FAQ, it's AI generated and it still is requiring multiple times and it still is requiring multiple times and it still is requiring multiple times to come to the site. to come to the site. to come to the site. Whereas if you picked up the phone and Whereas if you picked up the phone and Whereas if you picked up the phone and called the person and John from Illinois called the person and John from Illinois called the person and John from Illinois picked up the phone and and did a one picked up the phone and and did a one picked up the phone and and did a one call resolution to your rebooting of call resolution to your rebooting of call resolution to your rebooting of your your router or your gateway or your your router or your gateway or your your router or your gateway or anything else or or checking out your anything else or or checking out your anything else or or checking out your multiMZ SIM, can you do that on a multiMZ SIM, can you do that on a multiMZ SIM, can you do that on a chatbot? Can you do that all the time? chatbot? Can you do that all the time? chatbot? Can you do that all the time? You know that a lot of people struggle You know that a lot of people struggle You know that a lot of people struggle with that crap, right? So, well, I mean, with that crap, right? So, well, I mean, with that crap, right? So, well, I mean, it depends. I I know AT&T, it depends. I I know AT&T, it depends. I I know AT&T, you know, has some of that capability. I you know, has some of that capability. I you know, has some of that capability. I don't It's not necessarily generative don't It's not necessarily generative don't It's not necessarily generative AI, but um you Yeah, that's see that's AI, but um you Yeah, that's see that's AI, but um you Yeah, that's see that's the problem. I mean, it is a challenge, the problem. I mean, it is a challenge, the problem. I mean, it is a challenge, but I you know, I'm surprised to hear but I you know, I'm surprised to hear but I you know, I'm surprised to hear sort of hear that and you're not but you sort of hear that and you're not but you sort of hear that and you're not but you know what I'm saying. It's like how do know what I'm saying. It's like how do know what I'm saying. It's like how do you address the underserved and you address the underserved and you address the underserved and unserved? I mean, you're you're people unserved? I mean, you're you're people unserved? I mean, you're you're people who are going off like laying off all of who are going off like laying off all of who are going off like laying off all of their call center people are high on their call center people are high on their call center people are high on crack. It's like, okay, if you want your crack. It's like, okay, if you want your crack. It's like, okay, if you want your churn rate to go even higher, go ahead churn rate to go even higher, go ahead churn rate to go even higher, go ahead and do that. You know, they're already and do that. You know, they're already and do that. You know, they're already unable to service most the, you know,

unable to service most the, you know, unable to service most the, you know, 80% of the the calls that come in, you 80% of the the calls that come in, you 80% of the the calls that come in, you know. Sure. So AI can help you at least know. Sure. So AI can help you at least know. Sure. So AI can help you at least address some of that and that's cool but address some of that and that's cool but address some of that and that's cool but it's going to change the world. Do you it's going to change the world. Do you it's going to change the world. Do you really need AI for that? I mean I mean I really need AI for that? I mean I mean I really need AI for that? I mean I mean I think you can write a set of pandas that think you can write a set of pandas that think you can write a set of pandas that would that's why everyone is now like would that's why everyone is now like would that's why everyone is now like you know all the strategy consulting you know all the strategy consulting you know all the strategy consulting firms are writing about how there's no firms are writing about how there's no firms are writing about how there's no ROI in this stuff. It's like freaking ROI in this stuff. It's like freaking ROI in this stuff. It's like freaking hilarious. hilarious. hilarious. Oh, where's the big revolution that we Oh, where's the big revolution that we Oh, where's the big revolution that we we forecasted? You know, just I mean, we forecasted? You know, just I mean, we forecasted? You know, just I mean, but that's because how much of AI how but that's because how much of AI how but that's because how much of AI how much of AI is predicated on GPU? much of AI is predicated on GPU? much of AI is predicated on GPU? You're never going to get you're never You're never going to get you're never You're never going to get you're never going to get to that point if that's if going to get to that point if that's if going to get to that point if that's if that's the foundation that's that's that's the foundation that's that's that's the foundation that's that's driving it. Dude, what people are are driving it. Dude, what people are are driving it. Dude, what people are are trying to do is how figure out how to trying to do is how figure out how to trying to do is how figure out how to offload and just minimize the cost of offload and just minimize the cost of offload and just minimize the cost of inference. Guess where that's going? is inference. Guess where that's going? is inference. Guess where that's going? is going onto CPU. It my point exactly going onto CPU. It my point exactly going onto CPU. It my point exactly CPU or yeah low low power stuff. I mean CPU or yeah low low power stuff. I mean CPU or yeah low low power stuff. I mean I saw a stat I won't quote my source but I saw a stat I won't quote my source but I saw a stat I won't quote my source but it's like half of all AI workloads are it's like half of all AI workloads are it's like half of all AI workloads are just running on CPUs at this point. Um just running on CPUs at this point. Um just running on CPUs at this point. Um and when you get to the edge it's like and when you get to the edge it's like and when you get to the edge it's like as you know you want to spend the least as you know you want to spend the least as you know you want to spend the least amount of money to get the job done as amount of money to get the job done as amount of money to get the job done as quickly as possible. And that means not quickly as possible. And that means not quickly as possible. And that means not stuffing your equipment filled with stuffing your equipment filled with stuffing your equipment filled with expensive GPUs that are going to sit expensive GPUs that are going to sit expensive GPUs that are going to sit idle. So yeah, it's all going it's all idle. So yeah, it's all going it's all idle. So yeah, it's all going it's all the gravitational pull is all toward the gravitational pull is all toward the gravitational pull is all toward lower power, lower cost. It always is.

lower power, lower cost. It always is. lower power, lower cost. It always is. And and I think we're seeing that with And and I think we're seeing that with And and I think we're seeing that with AI as well. Yeah, latency is everything. AI as well. Yeah, latency is everything. AI as well. Yeah, latency is everything. You're going to use a Zeon 6 with the You're going to use a Zeon 6 with the You're going to use a Zeon 6 with the AMX extensions, folks. AMX extensions, folks. AMX extensions, folks. Microcontroller, oh my god, Microcontroller, oh my god, Microcontroller, oh my god, actually actually actually Pat Gell Singer Pat Gell Singer Pat Gell Singer um almost two years ago when they were um almost two years ago when they were um almost two years ago when they were like bringing what's his name? freaking like bringing what's his name? freaking like bringing what's his name? freaking Sam Alman on stage to talk about the $7 Sam Alman on stage to talk about the $7 Sam Alman on stage to talk about the $7 trillion trillion trillion investment fundraising round fundraising investment fundraising round fundraising investment fundraising round fundraising he was going to do to build I mean think he was going to do to build I mean think he was going to do to build I mean think about how dude talk about the the the about how dude talk about the the the about how dude talk about the the the lineage of stupidity think about that lineage of stupidity think about that lineage of stupidity think about that how everybody was salivating over that how everybody was salivating over that how everybody was salivating over that it was like holy crap you know speaking it was like holy crap you know speaking it was like holy crap you know speaking about our good friend Sam if you were about our good friend Sam if you were about our good friend Sam if you were wondering why recently in all his wondering why recently in all his wondering why recently in all his interviews and he's coming out saying interviews and he's coming out saying interviews and he's coming out saying we've already reached and passed AGI. we've already reached and passed AGI. we've already reached and passed AGI. He's saying it a lot in the last week or He's saying it a lot in the last week or He's saying it a lot in the last week or two in every interview. We've already two in every interview. We've already two in every interview. We've already passed AGI. There's a reason for that passed AGI. There's a reason for that passed AGI. There's a reason for that because part of his contract with because part of his contract with because part of his contract with Microsoft, Microsoft, Microsoft, there was a clause like achieving AGI there was a clause like achieving AGI there was a clause like achieving AGI gets them out of some things, you know, gets them out of some things, you know, gets them out of some things, you know, because right now there's a battle going because right now there's a battle going because right now there's a battle going on right now quietly between him and on right now quietly between him and on right now quietly between him and Satia. But this this is but this is Satia. But this this is but this is Satia. But this this is but this is total BS. You can call any lawyer and total BS. You can call any lawyer and total BS. You can call any lawyer and read what AGI means and they're gonna read what AGI means and they're gonna read what AGI means and they're gonna argue for decades about it. So argue for decades about it. So argue for decades about it. So you make money with AGI in a contract.

you make money with AGI in a contract. you make money with AGI in a contract. This is not of stupidity. That doesn't This is not of stupidity. That doesn't This is not of stupidity. That doesn't that you know that doesn't say much for that you know that doesn't say much for that you know that doesn't say much for Satia, right? And his discernment Satia, right? And his discernment Satia, right? And his discernment I don't know in this matter. I don't I I don't know in this matter. I don't I I don't know in this matter. I don't I mean it's just, you know, it it's just mean it's just, you know, it it's just mean it's just, you know, it it's just he's he's just saying it. It's obviously he's he's just saying it. It's obviously he's he's just saying it. It's obviously it's because it's what he needs and what it's because it's what he needs and what it's because it's what he needs and what he wants to try to get out from he wants to try to get out from he wants to try to get out from underneath. Yeah, they folks their ass. underneath. Yeah, they folks their ass. underneath. Yeah, they folks their ass. They think a lot of these foundation They think a lot of these foundation They think a lot of these foundation model companies, you know, they're model companies, you know, they're model companies, you know, they're struggling right now with struggling right now with struggling right now with commoditization of foundation models and commoditization of foundation models and commoditization of foundation models and um, you know, and I think that's that's um, you know, and I think that's that's um, you know, and I think that's that's causing a lot of uh and and the amount causing a lot of uh and and the amount causing a lot of uh and and the amount invested and bet on these foundation invested and bet on these foundation invested and bet on these foundation models is causing a lot of folks to sort models is causing a lot of folks to sort models is causing a lot of folks to sort of think about their long-term play of think about their long-term play of think about their long-term play here. So, exactly. As soon as I win my here. So, exactly. As soon as I win my here. So, exactly. As soon as I win my 20 trillion copyright infringement 20 trillion copyright infringement 20 trillion copyright infringement lawsuit against all those guys, This lawsuit against all those guys, This lawsuit against all those guys, This whole gang is over for copying my whole gang is over for copying my whole gang is over for copying my children's books. So, watch out. children's books. So, watch out. children's books. So, watch out. I thought you were going to say your I thought you were going to say your I thought you were going to say your submarine book, but yeah. Well, that's submarine book, but yeah. Well, that's submarine book, but yeah. Well, that's one. None of that fair use crap that one. None of that fair use crap that one. None of that fair use crap that they keep trying to say.

Here's a good use is a good use case of Here's a good use is a good use case of agentic saturate the system by having agentic saturate the system by having agentic saturate the system by having all those agent generating lawsuit about all those agent generating lawsuit about all those agent generating lawsuit about copyright infringement. You have the copyright infringement. You have the copyright infringement. You have the framework, Rob. We can just run that. framework, Rob. We can just run that. framework, Rob. We can just run that. There are so many lawsuits right now There are so many lawsuits right now There are so many lawsuits right now against these companies and they're against these companies and they're against these companies and they're going nowhere though it seems. Oh, going nowhere though it seems. Oh, going nowhere though it seems. Oh, because the foundation the the the because the foundation the the the because the foundation the the the foundation is is is not solid enough to foundation is is is not solid enough to foundation is is is not solid enough to assess whether they're right or wrong. assess whether they're right or wrong. assess whether they're right or wrong. So, it's a total new territory. So, it's a total new territory. So, it's a total new territory. We have to redefine. I mean, we we had We have to redefine. I mean, we we had We have to redefine. I mean, we we had conversation on the show before. We have conversation on the show before. We have conversation on the show before. We have to redefine what is knowledge. Am I to redefine what is knowledge. Am I to redefine what is knowledge. Am I going to I mean, should a teacher in, going to I mean, should a teacher in, going to I mean, should a teacher in, you know, a pre-engineer school in you know, a pre-engineer school in you know, a pre-engineer school in France sue me because I've used what he France sue me because I've used what he France sue me because I've used what he taught me to make money? taught me to make money? taught me to make money? Well, hey, let's talk about, you know, Well, hey, let's talk about, you know, Well, hey, let's talk about, you know, stuff that uh Debbie loves to talk stuff that uh Debbie loves to talk stuff that uh Debbie loves to talk about. What do you think about those new about. What do you think about those new about. What do you think about those new uh those new um headlines about that uh those new um headlines about that uh those new um headlines about that ridiculous data breach? ridiculous data breach? ridiculous data breach? Oh my god. I know. I mean, this is just Oh my god. I know. I mean, this is just Oh my god. I know. I mean, this is just in two months, right? Which one is it?

in two months, right? Which one is it? in two months, right? Which one is it? It's like crazy. Which one is this one? It's like crazy. Which one is this one? It's like crazy. Which one is this one? Let her tell you about it. Oh, she comes Let her tell you about it. Oh, she comes Let her tell you about it. Oh, she comes from her. Yeah, it was like this is from her. Yeah, it was like this is from her. Yeah, it was like this is supposed to be the the biggest data supposed to be the the biggest data supposed to be the the biggest data breach of all time now. And they say breach of all time now. And they say breach of all time now. And they say that it's like this is new data, not that it's like this is new data, not that it's like this is new data, not necessarily data that's been scraped necessarily data that's been scraped necessarily data that's been scraped from other breaches and stuff. And so, I from other breaches and stuff. And so, I from other breaches and stuff. And so, I mean, everybody's just exhausted, okay? mean, everybody's just exhausted, okay? mean, everybody's just exhausted, okay? Exhaustion of just looking at all these Exhaustion of just looking at all these Exhaustion of just looking at all these articles. And so people's eyes glaze articles. And so people's eyes glaze articles. And so people's eyes glaze over. So it's like change your over. So it's like change your over. So it's like change your passwords. Part of it is like use passwords. Part of it is like use passwords. Part of it is like use passcodes, change your passwords, use a passcodes, change your passwords, use a passcodes, change your passwords, use a password manager, all that other type of password manager, all that other type of password manager, all that other type of stuff. But it's it just happens so often stuff. But it's it just happens so often stuff. But it's it just happens so often that I think people are just kind of that I think people are just kind of that I think people are just kind of desensitized to it at this point. desensitized to it at this point. desensitized to it at this point. But Debbie, this one was across the But Debbie, this one was across the But Debbie, this one was across the board with a lot of different board with a lot of different board with a lot of different organizations getting involved. I mean, organizations getting involved. I mean, organizations getting involved. I mean, 180 million 180 million 180 million people affected. That sizable number.

people affected. That sizable number. people affected. That sizable number. Oh, 16 billion something like 16 billion Oh, 16 billion something like 16 billion Oh, 16 billion something like 16 billion passwords have been passwords, but 185 passwords have been passwords, but 185 passwords have been passwords, but 185 million people million people million people still catastrophic. Absolutely. But it's still catastrophic. Absolutely. But it's still catastrophic. Absolutely. But it's like I mean the average person, they're like I mean the average person, they're like I mean the average person, they're like, "Well, I thought I was doing the like, "Well, I thought I was doing the like, "Well, I thought I was doing the best that I could." Right? So, it's best that I could." Right? So, it's best that I could." Right? So, it's like, you know, people don't know what like, you know, people don't know what like, you know, people don't know what to do really. 90% of those people are to do really. 90% of those people are to do really. 90% of those people are not even going to do anything because not even going to do anything because not even going to do anything because they don't know. They don't care. no they don't know. They don't care. no they don't know. They don't care. no awareness and then and a lack awareness awareness and then and a lack awareness awareness and then and a lack awareness like I've never received anything from like I've never received anything from like I've never received anything from Last Pass. Yeah. You know, here's the Last Pass. Yeah. You know, here's the Last Pass. Yeah. You know, here's the thing that never sent us an email or a thing that never sent us an email or a thing that never sent us an email or a warning or you need to change your Last warning or you need to change your Last warning or you need to change your Last Pass password. Nothing. Here's the thing Pass password. Nothing. Here's the thing Pass password. Nothing. Here's the thing that's really scary that for some that's really scary that for some that's really scary that for some reason, this is the weird thing, people reason, this is the weird thing, people reason, this is the weird thing, people just don't seem to take this angle on just don't seem to take this angle on just don't seem to take this angle on these incidents is that the institutions these incidents is that the institutions these incidents is that the institutions that you deal with, they don't trust that you deal with, they don't trust that you deal with, they don't trust you. Now, you. Now, you. Now, you know, when we talk about hacks, we you know, when we talk about hacks, we you know, when we talk about hacks, we always talk about, oh, my my uh personal always talk about, oh, my my uh personal always talk about, oh, my my uh personal information got compromised and you information got compromised and you information got compromised and you know, somebody can steal my crap, right?

know, somebody can steal my crap, right? know, somebody can steal my crap, right? And they can impersonate me. Well, yeah. And they can impersonate me. Well, yeah. And they can impersonate me. Well, yeah. And that also means that that And that also means that that And that also means that that institution, whether it's a bank or it's institution, whether it's a bank or it's institution, whether it's a bank or it's a government agency, they can't trust a government agency, they can't trust a government agency, they can't trust your digital identity, right? I prefer your digital identity, right? I prefer your digital identity, right? I prefer that. Huh? I prefer that. that. Huh? I prefer that. that. Huh? I prefer that. Make me prove that I am who I am. That's Make me prove that I am who I am. That's Make me prove that I am who I am. That's the foundation. That's the foundation of the foundation. That's the foundation of the foundation. That's the foundation of trust unraveling underneath us, man. trust unraveling underneath us, man. trust unraveling underneath us, man. That's because the foundation of trust That's because the foundation of trust That's because the foundation of trust has never been established. Correct. has never been established. Correct. has never been established. Correct. This is not about trust. It's about This is not about trust. It's about This is not about trust. It's about authentication. two they're very authentication. two they're very authentication. two they're very different things. No, the foundation of different things. No, the foundation of different things. No, the foundation of trust. If you can't They're tied trust. If you can't They're tied trust. If you can't They're tied together. Yeah. Yeah. They're tied together. Yeah. Yeah. They're tied together. Yeah. Yeah. They're tied together, but they're not one cannot together, but they're not one cannot together, but they're not one cannot replace the other is the point. But if replace the other is the point. But if replace the other is the point. But if you don't trust, you can't do the other you don't trust, you can't do the other you don't trust, you can't do the other end of it. You need the two together. end of it. You need the two together. end of it. You need the two together. Absolutely. I mean, for example, I know some banks I mean, for example, I know some banks had doubled down over the years, which I had doubled down over the years, which I had doubled down over the years, which I thought was laughable on using voice as thought was laughable on using voice as thought was laughable on using voice as a authentication factor. And I'm like, I a authentication factor. And I'm like, I a authentication factor. And I'm like, I know what my voice is my password. My know what my voice is my password. My know what my voice is my password. My voice is my password. That was horrible.

voice is my password. That was horrible. voice is my password. That was horrible. It's terrible. And it I mean, it was It's terrible. And it I mean, it was It's terrible. And it I mean, it was never a good idea. And it's totally not never a good idea. And it's totally not never a good idea. And it's totally not a good idea right now. So, really, a good idea right now. So, really, a good idea right now. So, really, really bad. Give me an example of a good really bad. Give me an example of a good really bad. Give me an example of a good idea from a bank. idea from a bank. idea from a bank. So now they're going to need blood So now they're going to need blood So now they're going to need blood samples. It's going to turn to gatka, samples. It's going to turn to gatka, samples. It's going to turn to gatka, you know. Love that. Yeah, that's not you know. Love that. Yeah, that's not you know. Love that. Yeah, that's not far. Yeah. Are you Are you meaning that Yeah. Are you Are you meaning that selection can replace trust? selection can replace trust? selection can replace trust? What? What? What? Meaning that selection can replace trust Meaning that selection can replace trust Meaning that selection can replace trust when when when No, that's a different problem. Yeah. No No, that's a different problem. Yeah. No No, that's a different problem. Yeah. No one no one's talking about the genetic one no one's talking about the genetic one no one's talking about the genetic engineering that's happening with engineering that's happening with engineering that's happening with crisper and probably how like some of crisper and probably how like some of crisper and probably how like some of these celebrities and really rich people these celebrities and really rich people these celebrities and really rich people are genetically engineering their are genetically engineering their are genetically engineering their progeny to become super humans. That was progeny to become super humans. That was progeny to become super humans. That was the topic. That was that was the topic. the topic. That was that was the topic. the topic. That was that was the topic. That was the topic of Gatka. That's why That was the topic of Gatka. That's why That was the topic of Gatka. That's why it was I know. So what's going to happen it was I know. So what's going to happen it was I know. So what's going to happen based on the Gatka thing is the bank's based on the Gatka thing is the bank's based on the Gatka thing is the bank's going to do the blood sample. They're going to do the blood sample. They're going to do the blood sample. They're going to find out that you've got a going to find out that you've got a going to find out that you've got a disease that's going to hit you like in disease that's going to hit you like in disease that's going to hit you like in 6 months and they're not going to give 6 months and they're not going to give 6 months and they're not going to give you the 30 year mortgage on the house you the 30 year mortgage on the house you the 30 year mortgage on the house that you were trying to get.

that you were trying to get. that you were trying to get. No, no, Rob. That's not farfetch. Oh my No, no, Rob. That's not farfetch. Oh my No, no, Rob. That's not farfetch. Oh my gosh. gosh. gosh. You're totally You are totally wrong, You're totally You are totally wrong, You're totally You are totally wrong, Rob. What the Okay, good. What the banks Rob. What the Okay, good. What the banks Rob. What the Okay, good. What the banks are going to do is to engineer people are going to do is to engineer people are going to do is to engineer people who are more likely to borrow money so who are more likely to borrow money so who are more likely to borrow money so they can make money out of them. This is they can make money out of them. This is they can make money out of them. This is your people. Yes. Wow. You want to do your people. Yes. Wow. You want to do your people. Yes. Wow. You want to do something? Are you talking about like something? Are you talking about like something? Are you talking about like kind of like the engineer in Prometheus? Prometheus. Yeah, there you go. Exactly. Prometheus. Yeah, there you go. Exactly. Like took the pill and he just body Like took the pill and he just body Like took the pill and he just body falls apart into the water system of a falls apart into the water system of a falls apart into the water system of a new planet and it creates a whole new So new planet and it creates a whole new So new planet and it creates a whole new So maybe that's what the banks are going to maybe that's what the banks are going to maybe that's what the banks are going to do is engineer new people who have good do is engineer new people who have good do is engineer new people who have good credit scores and can buy things. All credit scores and can buy things. All credit scores and can buy things. All right, I'm I'm done with that. Yeah, right, I'm I'm done with that. Yeah, right, I'm I'm done with that. Yeah, it's going to happen. No, no, but Rob, it's going to happen. No, no, but Rob, it's going to happen. No, no, but Rob, you don't want good credit score. You you don't want good credit score. You you don't want good credit score. You want bad credit score so you can spend want bad credit score so you can spend want bad credit score so you can spend money with a higher interest rate and money with a higher interest rate and money with a higher interest rate and make more money. You're not you're not make more money. You're not you're not make more money. You're not you're not getting we want the non-banked people. getting we want the non-banked people. getting we want the non-banked people. Yeah. You know you're not getting it. Yeah. You know you're not getting it. Yeah. You know you're not getting it. You want a whole generation of people You want a whole generation of people You want a whole generation of people who borrow a lot at high rates. This is who borrow a lot at high rates. This is who borrow a lot at high rates. This is how you make money. Ah, right. So it's how you make money. Ah, right. So it's how you make money. Ah, right. So it's not necessarily the blood work.

not necessarily the blood work. not necessarily the blood work. It's the clinics that the bad bankked It's the clinics that the bad bankked It's the clinics that the bad bankked people go to that we No, it's actually people go to that we No, it's actually people go to that we No, it's actually it's it's actually the generations. So it's it's actually the generations. So it's it's actually the generations. So Rob, you don't have to worry about it. Rob, you don't have to worry about it. Rob, you don't have to worry about it. You're too old. It's not going to it's You're too old. It's not going to it's You're too old. It's not going to it's not going to hit you. It'll hit it'll not going to hit you. It'll hit it'll not going to hit you. It'll hit it'll hit Gen Z and the alphas and then, you hit Gen Z and the alphas and then, you hit Gen Z and the alphas and then, you know, because they can't get jobs today know, because they can't get jobs today know, because they can't get jobs today coming out of college anyway. So they're coming out of college anyway. So they're coming out of college anyway. So they're going to need to go into debt to even going to need to go into debt to even going to need to go into debt to even more debt to actually survive. Actually, more debt to actually survive. Actually, more debt to actually survive. Actually, you know, Equifax Equifax buys Quest you know, Equifax Equifax buys Quest you know, Equifax Equifax buys Quest Diagnostics for blood work across the Oh Diagnostics for blood work across the Oh Diagnostics for blood work across the Oh my god, we're so bad and yet we're so my god, we're so bad and yet we're so my god, we're so bad and yet we're so prophetic. Yeah, it's a scary thing. We won't be laughing about that. We won't be laughing about that. Quest Diagnostics buys 23 and me at a Quest Diagnostics buys 23 and me at a Quest Diagnostics buys 23 and me at a bargain basement price. So now we just bargain basement price. So now we just bargain basement price. So now we just take your blood, put it into the system, take your blood, put it into the system, take your blood, put it into the system, and they know everything. Exactly. and they know everything. Exactly. and they know everything. Exactly. That's horrible. You know what I That's horrible. You know what I That's horrible. You know what I actually heard recently is somebody actually heard recently is somebody actually heard recently is somebody mentioning plumbers that you should mentioning plumbers that you should mentioning plumbers that you should become a plumber.

become a plumber. become a plumber. because they make a lot of money, bro. because they make a lot of money, bro. because they make a lot of money, bro. No, no, I know that I know it's old news No, no, I know that I know it's old news No, no, I know that I know it's old news for us, but it's funny that now people for us, but it's funny that now people for us, but it's funny that now people are talking about you should become a are talking about you should become a are talking about you should become a plumber or get into a trade. And so, plumber or get into a trade. And so, plumber or get into a trade. And so, everybody's saying it, go to the trades. everybody's saying it, go to the trades. everybody's saying it, go to the trades. Trades are hard. So, you there's a lot Trades are hard. So, you there's a lot Trades are hard. So, you there's a lot of parents these days wondering what of parents these days wondering what of parents these days wondering what what subject that their kids should um what subject that their kids should um what subject that their kids should um major in. And here's the ironic thing. major in. And here's the ironic thing. major in. And here's the ironic thing. Remember we used to make fun of basket Remember we used to make fun of basket Remember we used to make fun of basket weaving, weaving, weaving, right? Underwater basket weaving. Yeah. right? Underwater basket weaving. Yeah. right? Underwater basket weaving. Yeah. Yeah. That might be money island, right? Number one, if you if you YouTube right? Number one, if you if you YouTube it, it's entertaining. And then number it, it's entertaining. And then number it, it's entertaining. And then number two, you're developing a skill which two, you're developing a skill which two, you're developing a skill which might actually have might actually have might actually have humanade. Yeah. Humanade premium, right? humanade. Yeah. Humanade premium, right? humanade. Yeah. Humanade premium, right? Right. And if you're actually good at Right. And if you're actually good at Right. And if you're actually good at it, you can actually sell a lot of crap it, you can actually sell a lot of crap it, you can actually sell a lot of crap u through an AI chatbot. Right. So this u through an AI chatbot. Right. So this u through an AI chatbot. Right. So this is like the new uh entrepreneurial is like the new uh entrepreneurial is like the new uh entrepreneurial framework. Leonard, this is Leonard's framework. Leonard, this is Leonard's framework. Leonard, this is Leonard's career advice. Become a basket weaver.

career advice. Become a basket weaver. career advice. Become a basket weaver. I thought he would say something I thought he would say something I thought he would say something valuable like become a Walmart. You know valuable like become a Walmart. You know valuable like become a Walmart. You know what? Sometimes, okay, to counter what? Sometimes, okay, to counter what? Sometimes, okay, to counter stupidity, you must come up with a stupidity, you must come up with a stupidity, you must come up with a really stupid idea. Got it. Got it. really stupid idea. Got it. Got it. really stupid idea. Got it. Got it. You're you're flipping it. You're You're you're flipping it. You're You're you're flipping it. You're flipping it upside down. So it's like flipping it upside down. So it's like flipping it upside down. So it's like dumb and dumber. Congratulations, dumb and dumber. Congratulations, dumb and dumber. Congratulations, Leonard. You brought the entire hour Leonard. You brought the entire hour Leonard. You brought the entire hour back to back to back to the stupidity level. Yeah. The the the stupidity level. Yeah. The the the stupidity level. Yeah. The the I always remind people as I always I always remind people as I always I always remind people as I always remind people about the trades. remind people about the trades. remind people about the trades. We are looking for 100,000 people to We are looking for 100,000 people to We are looking for 100,000 people to come help build Virginia class and come help build Virginia class and come help build Virginia class and Colombia class submarines. Literally go Colombia class submarines. Literally go Colombia class submarines. Literally go to buildsubmarines.com. They're dying. to buildsubmarines.com. They're dying. to buildsubmarines.com. They're dying. They will train you. They'll pay you to They will train you. They'll pay you to They will train you. They'll pay you to train you. You can be a welder, CNC. train you. You can be a welder, CNC. train you. You can be a welder, CNC. They need people so bad. Yeah. And They need people so bad. Yeah. And They need people so bad. Yeah. And Robin, that's exactly why they did the Robin, that's exactly why they did the Robin, that's exactly why they did the NASCAR uh sponsorship. Yeah. Because NASCAR uh sponsorship. Yeah. Because NASCAR uh sponsorship. Yeah. Because they wanted that kind of class of people they wanted that kind of class of people they wanted that kind of class of people to be able to come back and do that. to be able to come back and do that. to be able to come back and do that. Absolutely. Yeah. Those are those are my Absolutely. Yeah. Those are those are my Absolutely. Yeah. Those are those are my people. I know. That's my class of people. I know. That's my class of people. I know. That's my class of people. I'm tell I'm Mr. Talladega people. I'm tell I'm Mr. Talladega people. I'm tell I'm Mr. Talladega Nights. Ricky Bobby right here.

Nights. Ricky Bobby right here. Nights. Ricky Bobby right here. Bob the welder. Bob the welder. Bob the Bob the welder. Bob the welder. Bob the Bob the welder. Bob the welder. Bob the welder. No, you knew there was a statue welder. No, you knew there was a statue welder. No, you knew there was a statue of baby Jesus in your house somewhere. of baby Jesus in your house somewhere. of baby Jesus in your house somewhere. Baby Jesus. Baby Jesus. Baby Jesus. Little six pound sixb 5 ounce baby Little six pound sixb 5 ounce baby Little six pound sixb 5 ounce baby Jesus. Exactly. In your ghost manger. Oh my god. My god. I love that movie. Oh my god. My god. I love that movie. So funny. Oh my god. There's somebody on So funny. Oh my god. There's somebody on So funny. Oh my god. There's somebody on another planet listening to IoT Coffee another planet listening to IoT Coffee another planet listening to IoT Coffee Talk going, "What the hell is wrong with Talk going, "What the hell is wrong with Talk going, "What the hell is wrong with these people?" Well, I have I have a these people?" Well, I have I have a these people?" Well, I have I have a piece of titanium. So, there you go. piece of titanium. So, there you go. piece of titanium. So, there you go. Yeah. Like cognitive dissonance with Like cognitive dissonance with undertones of conflicting cognition. undertones of conflicting cognition. undertones of conflicting cognition. That's big serious words there. Yeah. I That's big serious words there. Yeah. I That's big serious words there. Yeah. I mean, that sounds like a Whoa. mean, that sounds like a Whoa. mean, that sounds like a Whoa. course college course early for you course college course early for you course college course early for you today.

today. today. I was saying no basket weaving for Bill. I was saying no basket weaving for Bill. I was saying no basket weaving for Bill. Yeah. Well, that that would be cricket Yeah. Well, that that would be cricket Yeah. Well, that that would be cricket and that would be a class right next to and that would be a class right next to and that would be a class right next to basket weaving. Yeah. As a young Obi-Wan basket weaving. Yeah. As a young Obi-Wan basket weaving. Yeah. As a young Obi-Wan would say, Bill, you were the chosen would say, Bill, you were the chosen would say, Bill, you were the chosen one. Yeah. Um Yeah. Um it it is it is it is getting pretty it it is it is it is getting pretty it it is it is it is getting pretty pretty pretty pretty man. Yeah. But no, I you know, I I love man. Yeah. But no, I you know, I I love man. Yeah. But no, I you know, I I love um you know, I came up with this like um you know, I came up with this like um you know, I came up with this like whole keep it real awards thingy. I just whole keep it real awards thingy. I just whole keep it real awards thingy. I just pulled it out of my ass. I mean, pulled it out of my ass. I mean, pulled it out of my ass. I mean, hopefully everyone who was an award hopefully everyone who was an award hopefully everyone who was an award winner realizes that, but it seems like winner realizes that, but it seems like winner realizes that, but it seems like it's getting traction because um you it's getting traction because um you it's getting traction because um you know, some of the the marketing teams of know, some of the the marketing teams of know, some of the the marketing teams of some of the brands who uh you know uh of some of the brands who uh you know uh of some of the brands who uh you know uh of the winners um seem to like it. Um I'm the winners um seem to like it. Um I'm the winners um seem to like it. Um I'm just like trying to be real, right? I just like trying to be real, right? I just like trying to be real, right? I was like, "Hey, these guys were the most was like, "Hey, these guys were the most was like, "Hey, these guys were the most non-bullshitting people that I talked non-bullshitting people that I talked non-bullshitting people that I talked to." Uh, and um, to." Uh, and um, to." Uh, and um, uh, I I I think there's going to be an uh, I I I think there's going to be an uh, I I I think there's going to be an appetite for that because eventually appetite for that because eventually appetite for that because eventually this stuff is going to be so, you know, this stuff is going to be so, you know, this stuff is going to be so, you know, exhausting and the the results are just exhausting and the the results are just exhausting and the the results are just not there. I mean, it's just spectacular not there. I mean, it's just spectacular not there. I mean, it's just spectacular how little ROI there is. And if there is how little ROI there is. And if there is how little ROI there is. And if there is a thesis of return, the return part is a thesis of return, the return part is a thesis of return, the return part is so far off and so disconnected from the so far off and so disconnected from the so far off and so disconnected from the massive amounts of AI infrastructure massive amounts of AI infrastructure massive amounts of AI infrastructure spend that's happening.

spend that's happening. spend that's happening. And keeping in mind that a lot of this And keeping in mind that a lot of this And keeping in mind that a lot of this infrastructure spend is happening in infrastructure spend is happening in infrastructure spend is happening in super computing. It's not even the edge super computing. It's not even the edge super computing. It's not even the edge stuff. There's a mismatch. There's an stuff. There's a mismatch. There's an stuff. There's a mismatch. There's an imbalance, you know, in this narrative. imbalance, you know, in this narrative. imbalance, you know, in this narrative. And I guarantee you the answer that And I guarantee you the answer that And I guarantee you the answer that everyone on the supercomputing side will everyone on the supercomputing side will everyone on the supercomputing side will uh give you when you ask them so you uh give you when you ask them so you uh give you when you ask them so you know okay you're building all this stuff know okay you're building all this stuff know okay you're building all this stuff and to what end this well but we don't and to what end this well but we don't and to what end this well but we don't know or you know how is this AI thing know or you know how is this AI thing know or you know how is this AI thing going to sustain itself and achieve some going to sustain itself and achieve some going to sustain itself and achieve some degree of ROI it's like oh well we don't degree of ROI it's like oh well we don't degree of ROI it's like oh well we don't know they don't know well that's because know they don't know well that's because know they don't know well that's because about a flipping tool Cool. Yeah, you about a flipping tool Cool. Yeah, you about a flipping tool Cool. Yeah, you can do this. Yeah. Yeah. And you know, can do this. Yeah. Yeah. And you know, can do this. Yeah. Yeah. And you know, just to be clear, we, you know, this just to be clear, we, you know, this just to be clear, we, you know, this generative AI la is totally different generative AI la is totally different generative AI la is totally different than the stuff Pete's doing with Edge AI than the stuff Pete's doing with Edge AI than the stuff Pete's doing with Edge AI and machine learning. That is legit. and machine learning. That is legit. and machine learning. That is legit. It is crazy. Every giant corporation It is crazy. Every giant corporation It is crazy. Every giant corporation right now, you're right, cuz we're going right now, you're right, cuz we're going right now, you're right, cuz we're going to their events in Vegas every week and to their events in Vegas every week and to their events in Vegas every week and they're that's all they're talking about they're that's all they're talking about they're that's all they're talking about and how you're going to run your whole and how you're going to run your whole and how you're going to run your whole business on that and everything. And yet business on that and everything. And yet business on that and everything. And yet we're still in the earliest days. And if we're still in the earliest days. And if we're still in the earliest days. And if you open the little readme text file you open the little readme text file you open the little readme text file when you download any of these LLMs and when you download any of these LLMs and when you download any of these LLMs and this technology, they're all really this technology, they're all really this technology, they're all really clear. This is still experimental and it clear. This is still experimental and it clear. This is still experimental and it doesn't really work all the time. Do not doesn't really work all the time. Do not doesn't really work all the time. Do not use it for anything.

use it for anything. use it for anything. There's a million caveats. And so the There's a million caveats. And so the There's a million caveats. And so the fact that people are just like, "Yeah, fact that people are just like, "Yeah, fact that people are just like, "Yeah, I'm blowing past that and we're going to I'm blowing past that and we're going to I'm blowing past that and we're going to bet the far thing." But I mean, but look bet the far thing." But I mean, but look bet the far thing." But I mean, but look at the look at the You want to keep it at the look at the You want to keep it at the look at the You want to keep it real? Look at look at what Edge AI real? Look at look at what Edge AI real? Look at look at what Edge AI Foundation is doing. They're not talking Foundation is doing. They're not talking Foundation is doing. They're not talking about, oh, we're just talking about AI. about, oh, we're just talking about AI. about, oh, we're just talking about AI. We're just They're talking about We're just They're talking about We're just They're talking about solutions. solutions. solutions. Yeah, there you go. Solutions. Yes. Yeah, there you go. Solutions. Yes. Yeah, there you go. Solutions. Yes. Solving real problems in the real world. Solving real problems in the real world. Solving real problems in the real world. That's the That's the thing. And it's That's the That's the thing. And it's That's the That's the thing. And it's happening, too. It's like it's amazing happening, too. It's like it's amazing happening, too. It's like it's amazing to see. It's It's becoming ubiquitous. to see. It's It's becoming ubiquitous. to see. It's It's becoming ubiquitous. And it's kind of a quiet revolution And it's kind of a quiet revolution And it's kind of a quiet revolution that's happening out there, especially that's happening out there, especially that's happening out there, especially as you can run more and more workloads, as you can run more and more workloads, as you can run more and more workloads, you know, closer to where the data is you know, closer to where the data is you know, closer to where the data is created. Yeah, people are finding like I created. Yeah, people are finding like I created. Yeah, people are finding like I can solve this problem. Like I was can solve this problem. Like I was can solve this problem. Like I was saying before, you know, in the real saying before, you know, in the real saying before, you know, in the real world, you want to solve problems as world, you want to solve problems as world, you want to solve problems as fast as you can for the least cost. And fast as you can for the least cost. And fast as you can for the least cost. And um that's just the way gravity works um that's just the way gravity works um that's just the way gravity works with business. I mean, it's just the way with business. I mean, it's just the way with business. I mean, it's just the way it is. So, but when you're doing that, it is. So, but when you're doing that, it is. So, but when you're doing that, you don't have to you don't have to say, you don't have to you don't have to say, you don't have to you don't have to say, well, our AI solution does this. It it's well, our AI solution does this. It it's well, our AI solution does this. It it's here's the problem. Here's the solution.

here's the problem. Here's the solution. here's the problem. Here's the solution. Exactly. Exactly. Yeah. I know it's uh Exactly. Exactly. Yeah. I know it's uh Exactly. Exactly. Yeah. I know it's uh it's it's you know um and and you know it's it's you know um and and you know it's it's you know um and and you know another term that I've been using a lot another term that I've been using a lot another term that I've been using a lot is around sovereignty right so we're is around sovereignty right so we're is around sovereignty right so we're actually about to have this big event in actually about to have this big event in actually about to have this big event in Europe about AI Europe about AI Europe about AI the ability to have sovereignty over the ability to have sovereignty over the ability to have sovereignty over your data your your data sets your your data your your data sets your your data your your data sets your models your your hardware to run AI models your your hardware to run AI models your your hardware to run AI where you need to run it you know where you need to run it you know where you need to run it you know sovereignty is currency and uh and I sovereignty is currency and uh and I sovereignty is currency and uh and I think that that's going to be a big think that that's going to be a big think that that's going to be a big theme for folks is I can't bet the AI theme for folks is I can't bet the AI theme for folks is I can't bet the AI for my business on some other entity for my business on some other entity for my business on some other entity where I need to pay a tax, a cloud tax where I need to pay a tax, a cloud tax where I need to pay a tax, a cloud tax or a hyperscaler tax or end up right or or a hyperscaler tax or end up right or or a hyperscaler tax or end up right or end up in a uh well the big story is end up in a uh well the big story is end up in a uh well the big story is that open AI is in this uh litigation that open AI is in this uh litigation that open AI is in this uh litigation with uh New York Times and the um the with uh New York Times and the um the with uh New York Times and the um the judge in that case said that they have judge in that case said that they have judge in that case said that they have to stop deletion of all of their data to stop deletion of all of their data to stop deletion of all of their data everywhere in the world. And so that's everywhere in the world. And so that's everywhere in the world. And so that's like a disaster. Huge. Yeah. But no, like a disaster. Huge. Yeah. But no, like a disaster. Huge. Yeah. But no, it's really high risk. uh it's only the it's really high risk. uh it's only the it's really high risk. uh it's only the tip of the iceberg because if you you tip of the iceberg because if you you tip of the iceberg because if you you think if you think about it deeply they think if you think about it deeply they think if you think about it deeply they should delete the data and retrain the should delete the data and retrain the should delete the data and retrain the model without the data because the model model without the data because the model model without the data because the model data so data so data so it's an illusion the data is out it's an it's an illusion the data is out it's an it's an illusion the data is out it's an illusion now you know what one of the illusion now you know what one of the illusion now you know what one of the biggest problems the data did they biggest problems the data did they biggest problems the data did they really delete the data really delete the data really delete the data even even even if you do the residual value is in the if you do the residual value is in the if you do the residual value is in the model the pattern has been created in model the pattern has been created in model the pattern has been created in the model so I If you really believe in

the model so I If you really believe in the model so I If you really believe in privacy, you should not say delete my privacy, you should not say delete my privacy, you should not say delete my data. You should say delete my data and data. You should say delete my data and data. You should say delete my data and drain every single model that I was used drain every single model that I was used drain every single model that I was used to train. Otherwise, it's an illusion. to train. Otherwise, it's an illusion. to train. Otherwise, it's an illusion. Especially Especially Especially just remember folks, the files are in just remember folks, the files are in just remember folks, the files are in the computer. the computer. the computer. No, they're No, they're No, they're connected. It's connected. They're in the they're It's connected. They're in the they're in the cloud already. You're done, my in the cloud already. You're done, my in the cloud already. You're done, my friend. You're done. There's no friend. You're done. There's no friend. You're done. There's no deleting. Oh my god, it's everywhere. deleting. Oh my god, it's everywhere. deleting. Oh my god, it's everywhere. You know, I was I was very not unrelated You know, I was I was very not unrelated You know, I was I was very not unrelated but arguing with some people recently but arguing with some people recently but arguing with some people recently about you those those token card about you those those token card about you those those token card security like the RSA token so and they security like the RSA token so and they security like the RSA token so and they were saying oh it's so old now you have were saying oh it's so old now you have were saying oh it's so old now you have the one that you can plug in with USB the one that you can plug in with USB the one that you can plug in with USB you have the UB keys and I'm saying guys you have the UB keys and I'm saying guys you have the UB keys and I'm saying guys if you plug the thing in you're never if you plug the thing in you're never if you plug the thing in you're never sure what's going to happen so a little sure what's going to happen so a little sure what's going to happen so a little device that is that you prove your device that is that you prove your device that is that you prove your process and that you have a secret to process and that you have a secret to process and that you have a secret to unlock yourself is still the most secure unlock yourself is still the most secure unlock yourself is still the most secure way to authenticate way to authenticate way to authenticate not connected most trusted way secure is not connected most trusted way secure is not connected most trusted way secure is secure is different that's see that's secure is different that's see that's secure is different that's see that's the thing the thing the thing it's both it's both it's both I like the idea of draining though I I like the idea of draining though I I like the idea of draining though I like the term draining how do you drain like the term draining how do you drain like the term draining how do you drain data yes I've been advocating that for data yes I've been advocating that for data yes I've been advocating that for years now because when the when the years now because when the when the years now because when the when the Europe came with this GDPR and this Europe came with this GDPR and this Europe came with this GDPR and this right to be forgotten I told oh it's an right to be forgotten I told oh it's an right to be forgotten I told oh it's an illusion you've been giving data for 10 illusion you've been giving data for 10 illusion you've been giving data for 10 years they they train model for 10 years they they train model for 10 years they they train model for 10 years, you're still there. You can

years, you're still there. You can years, you're still there. You can delete whatever you want. You're still delete whatever you want. You're still delete whatever you want. You're still there. So training isn't the the problem there. So training isn't the the problem there. So training isn't the the problem of forgetting. So if we look at these of forgetting. So if we look at these of forgetting. So if we look at these world models, that's that's a big issue, world models, that's that's a big issue, world models, that's that's a big issue, right? And that's why you you continue right? And that's why you you continue right? And that's why you you continue to have like these performance issues to have like these performance issues to have like these performance issues because over time they all decline as because over time they all decline as because over time they all decline as you continue to train them and make them you continue to train them and make them you continue to train them and make them larger. But when you bring them down to larger. But when you bring them down to larger. But when you bring them down to enterprise, you have the same problem. enterprise, you have the same problem. enterprise, you have the same problem. um you know these embeddings don't um you know these embeddings don't um you know these embeddings don't necessarily have a time stamp or any necessarily have a time stamp or any necessarily have a time stamp or any anything that contextualizes their anything that contextualizes their anything that contextualizes their relevance as knowledge right um and so relevance as knowledge right um and so relevance as knowledge right um and so the right the ability for these things the right the ability for these things the right the ability for these things to selectively forget is important but to selectively forget is important but to selectively forget is important but they there's no way of doing that right they there's no way of doing that right they there's no way of doing that right and and so this is this is just the and and so this is this is just the and and so this is this is just the comical stuff right it's called it's comical stuff right it's called it's comical stuff right it's called it's called it's called catastrophic called it's called catastrophic called it's called catastrophic forgetting where it may forget stuff. It forgetting where it may forget stuff. It forgetting where it may forget stuff. It may forget stuff that's good or bad. So may forget stuff that's good or bad. So may forget stuff that's good or bad. So there is there is a way. It's just there is there is a way. It's just there is there is a way. It's just extremely expensive. If you keep the extremely expensive. If you keep the extremely expensive. If you keep the data you use to train your model, you data you use to train your model, you data you use to train your model, you can remove the data and retrain your can remove the data and retrain your can remove the data and retrain your model, but it cost a lot. Exactly. No, model, but it cost a lot. Exactly. No, model, but it cost a lot. Exactly. No, it's not that complicated. Actually, it's not that complicated. Actually, it's not that complicated. Actually, it's very the people say, "Oh, it's too it's very the people say, "Oh, it's too it's very the people say, "Oh, it's too complicated. We can do." Yes, you can complicated. We can do." Yes, you can complicated. We can do." Yes, you can freaking do it because it's expensive.

freaking do it because it's expensive. freaking do it because it's expensive. You should have data lineage. So, you You should have data lineage. So, you You should have data lineage. So, you should know exactly which data was used should know exactly which data was used should know exactly which data was used for that model. It's called for that model. It's called for that model. It's called transparency. And you should be able to transparency. And you should be able to transparency. And you should be able to I but think about how cluji that is that I but think about how cluji that is that I but think about how cluji that is that is so far away from being a learning is so far away from being a learning is so far away from being a learning system. These things don't actually system. These things don't actually system. These things don't actually learn. You train them learning. Right. learn. You train them learning. Right. learn. You train them learning. Right. That's the funny thing. Here is the That's the funny thing. Here is the That's the funny thing. Here is the point. I don't want a learning system. I point. I don't want a learning system. I point. I don't want a learning system. I want a forgetting system. Yeah. Exactly. want a forgetting system. Yeah. Exactly. want a forgetting system. Yeah. Exactly. basically the the thing that you're basically the the thing that you're basically the the thing that you're talking about is what these companies talking about is what these companies talking about is what these companies are spending trillions of dollars and are spending trillions of dollars and are spending trillions of dollars and trying to figure out and that is how can trying to figure out and that is how can trying to figure out and that is how can we we we uh do all do this stuff that we're uh do all do this stuff that we're uh do all do this stuff that we're supposed to do without having to delete supposed to do without having to delete supposed to do without having to delete the model and start again. Yeah. Yeah. the model and start again. Yeah. Yeah. the model and start again. Yeah. Yeah. And that's why why it's so important for And that's why why it's so important for And that's why why it's so important for no one to believe any of this stuff no one to believe any of this stuff no one to believe any of this stuff because we talked about this before. If because we talked about this before. If because we talked about this before. If you trust the outcome, think about it you trust the outcome, think about it you trust the outcome, think about it personally. You know, this thing is personally. You know, this thing is personally. You know, this thing is harvesting information for everywhere harvesting information for everywhere harvesting information for everywhere and then it represents you and then it represents you and then it represents you and then it it becomes the authority on and then it it becomes the authority on and then it it becomes the authority on who you are and it hallucinates and does who you are and it hallucinates and does who you are and it hallucinates and does all this crap. I mean, it's already done all this crap. I mean, it's already done all this crap. I mean, it's already done it to several people that I know. Think it to several people that I know. Think it to several people that I know. Think about how toxic and damaging that is.

about how toxic and damaging that is. about how toxic and damaging that is. It's it's horrific. And then if someone It's it's horrific. And then if someone It's it's horrific. And then if someone can manipulate that, you're can manipulate that, you're can manipulate that, you're Yeah. I mean, how do we know Rob is Yeah. I mean, how do we know Rob is Yeah. I mean, how do we know Rob is really wrong? That's why you can't trust really wrong? That's why you can't trust really wrong? That's why you can't trust any of who wants to know that. any of who wants to know that. any of who wants to know that. Well, I mean, you know, hiring for HR, Well, I mean, you know, hiring for HR, Well, I mean, you know, hiring for HR, trying to get a job, you know. Oh, you trying to get a job, you know. Oh, you trying to get a job, you know. Oh, you see those uh you see those scenarios all see those uh you see those scenarios all see those uh you see those scenarios all the time where people are using LLMs as the time where people are using LLMs as the time where people are using LLMs as they're interviewing online and they're interviewing online and they're interviewing online and answering questions in real time and answering questions in real time and answering questions in real time and you know, is this person a jerk? Oh, you know, is this person a jerk? Oh, you know, is this person a jerk? Oh, it's time to be that woman with the big it's time to be that woman with the big it's time to be that woman with the big hammer spinning around and th smashing hammer spinning around and th smashing hammer spinning around and th smashing into the 1984. 1984. That's what we need into the 1984. 1984. That's what we need into the 1984. 1984. That's what we need right now because, you know, let's just right now because, you know, let's just right now because, you know, let's just end this thing right now cuz you know end this thing right now cuz you know end this thing right now cuz you know what? Nobody can get a job. I feel bad. what? Nobody can get a job. I feel bad. what? Nobody can get a job. I feel bad. All these college kids coming out, not a All these college kids coming out, not a All these college kids coming out, not a single one of them can find a job. single one of them can find a job. single one of them can find a job. There's a reason all this is happening. There's a reason all this is happening. There's a reason all this is happening. Weaving it to ourselves. Plumbing. We're Weaving it to ourselves. Plumbing. We're Weaving it to ourselves. Plumbing. We're doing it to ourselves. Yeah. No. Um, you doing it to ourselves. Yeah. No. Um, you doing it to ourselves. Yeah. No. Um, you know, I think the Amish folks have have know, I think the Amish folks have have know, I think the Amish folks have have it down.

it down. it down. I mean, there's nothing wrong with it. I mean, there's nothing wrong with it. I mean, there's nothing wrong with it. Disconnect Disconnect Disconnect society completely disconnected from society completely disconnected from society completely disconnected from digital. And guess what? You go back. I digital. And guess what? You go back. I digital. And guess what? You go back. I mean, you go back to analog cuz, you mean, you go back to analog cuz, you mean, you go back to analog cuz, you know, we've seen that before where know, we've seen that before where know, we've seen that before where everyone went digital and they said, everyone went digital and they said, everyone went digital and they said, "Screw this crap." Hey, stop for got to "Screw this crap." Hey, stop for got to "Screw this crap." Hey, stop for got to go back. Where do the top tech execs go back. Where do the top tech execs go back. Where do the top tech execs send their kids to school? They send send their kids to school? They send send their kids to school? They send them to the Waldorf school. No tech is them to the Waldorf school. No tech is them to the Waldorf school. No tech is allowed. They all every one of them allowed. They all every one of them allowed. They all every one of them sends them to the Waldor schools in in sends them to the Waldor schools in in sends them to the Waldor schools in in the valley and other places. There's not the valley and other places. There's not the valley and other places. There's not any tech allowed in those places. And so any tech allowed in those places. And so any tech allowed in those places. And so you actually have a real brain. Homage you actually have a real brain. Homage you actually have a real brain. Homage 2.0. There you go. Homage 2.0. 2.0. There you go. Homage 2.0. 2.0. There you go. Homage 2.0. Absolutely. 2.0 is furniture making and Absolutely. 2.0 is furniture making and Absolutely. 2.0 is furniture making and pie making trades making. Love it. pie making trades making. Love it. pie making trades making. Love it. Basket weaving. I mean, you know, as Basket weaving. I mean, you know, as Basket weaving. I mean, you know, as stupid as this sound, it actually ends stupid as this sound, it actually ends stupid as this sound, it actually ends up it will end up being the brilliant up it will end up being the brilliant up it will end up being the brilliant thing. It will be the less stupid of thing. It will be the less stupid of thing. It will be the less stupid of mass stupidity. So I mean mass stupidity. So I mean mass stupidity. So I mean that's true. Analog analog for the win. that's true. Analog analog for the win. that's true. Analog analog for the win. Analog for the win. Well, that's where Analog for the win. Well, that's where Analog for the win. Well, that's where AI is going. You know, if you look at it AI is going. You know, if you look at it AI is going. You know, if you look at it from silicon perspective, neomorphic from silicon perspective, neomorphic from silicon perspective, neomorphic compute, they're looking at analog as compute, they're looking at analog as compute, they're looking at analog as like the next like the next like the next guys to give me your advice on what flip guys to give me your advice on what flip guys to give me your advice on what flip phone I'm going to go to once I retire phone I'm going to go to once I retire phone I'm going to go to once I retire in a year or so. It's a jitter bug. Of in a year or so. It's a jitter bug. Of in a year or so. It's a jitter bug. Of course, you know, Jitterbug.

course, you know, Jitterbug. course, you know, Jitterbug. That's why it's important to worry about That's why it's important to worry about That's why it's important to worry about things like needles and cartridges and things like needles and cartridges and things like needles and cartridges and stuff like that on your turntable. stuff like that on your turntable. stuff like that on your turntable. That's right. Get a fresh cartridge on That's right. Get a fresh cartridge on That's right. Get a fresh cartridge on your turntable. Gold mobile phone. Thank your turntable. Gold mobile phone. Thank your turntable. Gold mobile phone. Thank you very much. Oh, there you go. There's you very much. Oh, there you go. There's you very much. Oh, there you go. There's probably a Trump gold jitterbug out probably a Trump gold jitterbug out probably a Trump gold jitterbug out there somewhere. That's what I'm hoping. there somewhere. That's what I'm hoping. there somewhere. That's what I'm hoping. You think that's probably what he You think that's probably what he You think that's probably what he did? Yeah. Go ahead, Dimmitri. I was did? Yeah. Go ahead, Dimmitri. I was did? Yeah. Go ahead, Dimmitri. I was trying to say to Pete that it depends if trying to say to Pete that it depends if trying to say to Pete that it depends if you have a mobile magnet or mobile coil. you have a mobile magnet or mobile coil. you have a mobile magnet or mobile coil. So that's for for your turn table we're So that's for for your turn table we're So that's for for your turn table we're talking mm or MC. Yes. talking mm or MC. Yes. talking mm or MC. Yes. Well said. All right. Who wants to take Well said. All right. Who wants to take Well said. All right. Who wants to take this out? this out? this out? I'm just going to wrap my neck in I'm just going to wrap my neck in I'm just going to wrap my neck in monster cable right now. My favorite. My favorite. And I'm going to plug it into my tube And I'm going to plug it into my tube And I'm going to plug it into my tube amp and we're going to blast it out to amp and we're going to blast it out to amp and we're going to blast it out to my pumping speakers. And the message is my pumping speakers. And the message is my pumping speakers. And the message is humanity first. Let's shut this stuff humanity first. Let's shut this stuff humanity first. Let's shut this stuff down. It's actually not accurate. Nobody down. It's actually not accurate. Nobody down. It's actually not accurate. Nobody can get a job. We're doing this to can get a job. We're doing this to can get a job. We're doing this to ourselves. So, let's just stop in the ourselves. So, let's just stop in the ourselves. So, let's just stop in the name of love. All right. Thanks for name of love. All right. Thanks for name of love. All right. Thanks for joining us today on IoT Coffee Talk. It joining us today on IoT Coffee Talk. It joining us today on IoT Coffee Talk. It was great. We said the word IoT. It was great. We said the word IoT. It was great. We said the word IoT. It happened. There you go. Our happened. There you go. Our happened. There you go. Our Elevator Kids is needing more help than Elevator Kids is needing more help than Elevator Kids is needing more help than ever because we got unemployed kids all ever because we got unemployed kids all ever because we got unemployed kids all over the place. You know, in fact, I over the place. You know, in fact, I over the place. You know, in fact, I think one of the new things I just think one of the new things I just think one of the new things I just making this up as I go along. Elevator making this up as I go along. Elevator making this up as I go along. Elevator Kids will now be doing trades, training, Kids will now be doing trades, training, Kids will now be doing trades, training, you know, kind of like a community you know, kind of like a community you know, kind of like a community college. We're going to help get

college. We're going to help get college. We're going to help get scholarships for kids to become welders, scholarships for kids to become welders, scholarships for kids to become welders, electricians, plumbers, HVAC, you know, electricians, plumbers, HVAC, you know, electricians, plumbers, HVAC, you know, that kind of stuff. It's important. And that kind of stuff. It's important. And that kind of stuff. It's important. And so, uh, anyway, let's stick with what's so, uh, anyway, let's stick with what's so, uh, anyway, let's stick with what's real, man. Stick with what's real. Stick real, man. Stick with what's real. Stick real, man. Stick with what's real. Stick with what's true. Humanity first. We're with what's true. Humanity first. We're with what's true. Humanity first. We're out. out. out. [Music]