IoTCT Webcast Episode 308 - "The FAFO Pandemic" (When Agentic AI Goes Wrong!)

>> Nice. >> Nice. There you go. There you go. There you go. >> [cheering] >> [cheering] >> [cheering] >> A worthy intro. >> A worthy intro. >> A worthy intro. Yes. Yes. Yes. Worthy intro. Worthy intro. Worthy intro. Transition. How's it going, man? Transition. How's it going, man? Transition. How's it going, man? Good. Good. In transit once again, you Good. Good. In transit once again, you Good. Good. In transit once again, you know. I thought maybe we'd all know. I thought maybe we'd all know. I thought maybe we'd all dial in from our various airports today, dial in from our various airports today, dial in from our various airports today, but it looks as if it's just me right but it looks as if it's just me right but it looks as if it's just me right now. Yeah, I know. Rob's now. Yeah, I know. Rob's now. Yeah, I know. Rob's on a flight right now, and on a flight right now, and on a flight right now, and no one else seems to be able to make it. no one else seems to be able to make it. no one else seems to be able to make it. So, this could be the shortest IoT So, this could be the shortest IoT So, this could be the shortest IoT Coffee Talk ever. Coffee Talk ever. Coffee Talk ever. And um And um And um Oh, well, you know. Oh, well. We know Oh, well, you know. Oh, well. We know Oh, well, you know. Oh, well. We know plenty of things going on in the world. plenty of things going on in the world. plenty of things going on in the world. And they'll probably get like the most And they'll probably get like the most And they'll probably get like the most most views because most views because most views because Well, [clears throat] you know, they say Well, [clears throat] you know, they say Well, [clears throat] you know, they say shorts are the new the new thing. So, we shorts are the new the new thing. So, we shorts are the new the new thing. So, we could be could be could be Shorts are the new long. But uh Shorts are the new long. But uh Shorts are the new long. But uh uh What is it that Open AI bought the uh uh What is it that Open AI bought the uh uh What is it that Open AI bought the uh bought that um bought that um bought that um podcast company? No. Yeah. Yeah, I I podcast company? No. Yeah. Yeah, I I podcast company? No. Yeah. Yeah, I I >> Apparently Yeah, apparently they have >> Apparently Yeah, apparently they have >> Apparently Yeah, apparently they have shorts. They embed advertising like shorts. They embed advertising like shorts. They embed advertising like AI-driven ads into their shorts. At some AI-driven ads into their shorts. At some AI-driven ads into their shorts. At some point, you know, that's kind of like an point, you know, that's kind of like an point, you know, that's kind of like an interesting interesting interesting use of AI, but still seems like it's use of AI, but still seems like it's use of AI, but still seems like it's like a like a hundred million bucks.

like a like a hundred million bucks. like a like a hundred million bucks. They should have bought IoT Coffee Talk, They should have bought IoT Coffee Talk, They should have bought IoT Coffee Talk, you know, for half the price. Yeah, you know, for half the price. Yeah, you know, for half the price. Yeah, exactly. Exactly. [laughter] exactly. Exactly. [laughter] exactly. Exactly. [laughter] Yeah. Yeah. Yeah. Yeah. [snorts] Yeah. [snorts] Yeah. [snorts] Um Um Um who knows? That might have made their who knows? That might have made their who knows? That might have made their their their their >> [gasps] >> [gasps] >> [gasps] >> uh made-up valuation tank. >> uh made-up valuation tank. >> uh made-up valuation tank. Um yeah, anyway, uh The whole IPO thing, Um yeah, anyway, uh The whole IPO thing, Um yeah, anyway, uh The whole IPO thing, you know, that's going to be crazy. you know, that's going to be crazy. you know, that's going to be crazy. There's also like some interesting There's also like some interesting There's also like some interesting stories that whole Ronan Farrow came out stories that whole Ronan Farrow came out stories that whole Ronan Farrow came out this week with a whole exposé on Sam this week with a whole exposé on Sam this week with a whole exposé on Sam Altman, and it's all getting dirty. Altman, and it's all getting dirty. Altman, and it's all getting dirty. Yeah, yeah. I mean, you know, Yeah, yeah. I mean, you know, Yeah, yeah. I mean, you know, look I mean, we're going on year four look I mean, we're going on year four look I mean, we're going on year four here, and there's really nothing to show here, and there's really nothing to show here, and there's really nothing to show for it. for it. for it. I mean, to be honest, I mean, I can I mean, to be honest, I mean, I can I mean, to be honest, I mean, I can appreciate Anthropic. appreciate Anthropic. appreciate Anthropic. Yes, code generation. Yes, code generation. Yes, code generation. Big big deal until people Big big deal until people Big big deal until people >> Code gen's big deal. have to deal with >> Code gen's big deal. have to deal with >> Code gen's big deal. have to deal with all the slop. Sure. Um all the slop. Sure. Um all the slop. Sure. Um you know, but anyways, before we get you know, but anyways, before we get you know, but anyways, before we get started Okay. everybody, welcome to IoT started Okay. everybody, welcome to IoT started Okay. everybody, welcome to IoT Coffee Talk. This is going to be the Coffee Talk. This is going to be the Coffee Talk. This is going to be the shortest episode ever, but remember to shortest episode ever, but remember to shortest episode ever, but remember to take it seriously at your own peril.

take it seriously at your own peril. take it seriously at your own peril. Uh and take out insurance if you do. Uh and take out insurance if you do. Uh and take out insurance if you do. We're here just to have fun uh for fun We're here just to have fun uh for fun We're here just to have fun uh for fun -ment. Mostly entertainment, slightly -ment. Mostly entertainment, slightly -ment. Mostly entertainment, slightly informational purposes only. informational purposes only. informational purposes only. And we're Slightly. Yeah, just here to And we're Slightly. Yeah, just here to And we're Slightly. Yeah, just here to just talk crap. Quite frankly. Yeah, and just talk crap. Quite frankly. Yeah, and just talk crap. Quite frankly. Yeah, and it's the weekend. it's the weekend. it's the weekend. >> [clears throat] >> [clears throat] >> [clears throat] >> Uh it's been a long one. >> Uh it's been a long one. >> Uh it's been a long one. Um my whole house has been under Um my whole house has been under Um my whole house has been under construction. It's been annoying as construction. It's been annoying as construction. It's been annoying as hell. I'm hell. I'm hell. I'm >> [clears throat] >> [clears throat] >> [clears throat] >> fed up with it, but I finally got my >> fed up with it, but I finally got my >> fed up with it, but I finally got my office done. office done. office done. And And And uh anyway, um uh anyway, um uh anyway, um yeah, we hope you enjoy this what's yeah, we hope you enjoy this what's yeah, we hope you enjoy this what's probably going to be a very short probably going to be a very short probably going to be a very short episode, but Yes, I [clears throat] need episode, but Yes, I [clears throat] need episode, but Yes, I [clears throat] need to board my flight in about 15 minutes, to board my flight in about 15 minutes, to board my flight in about 15 minutes, so Yeah, okay. Maybe someone else will so Yeah, okay. Maybe someone else will so Yeah, okay. Maybe someone else will come up and come up and come up and >> Maybe somebody else will jump in. Yeah. >> Maybe somebody else will jump in. Yeah. >> Maybe somebody else will jump in. Yeah. Yeah. The Yeah. The Yeah. The Yeah, another week in uh Yeah, another week in uh Yeah, another week in uh in the AI world, and um in the AI world, and um in the AI world, and um Yeah, like you said, there's uh there's Yeah, like you said, there's uh there's Yeah, like you said, there's uh there's just a lot of smoke and noise. I think a just a lot of smoke and noise. I think a just a lot of smoke and noise. I think a lot of this Now, there's a lot of you lot of this Now, there's a lot of you lot of this Now, there's a lot of you know, I didn't mention before like it's know, I didn't mention before like it's know, I didn't mention before like it's because of so much big money involved.

because of so much big money involved. because of so much big money involved. Yeah. You know, these you know, these Yeah. You know, these you know, these Yeah. You know, these you know, these kind of crazy you know, like non-public kind of crazy you know, like non-public kind of crazy you know, like non-public market valuations. And um market valuations. And um market valuations. And um and now this kind of you know, and now this kind of you know, and now this kind of you know, dirt being slung around, and then dirt being slung around, and then dirt being slung around, and then there's like talking about SpaceX going there's like talking about SpaceX going there's like talking about SpaceX going public, you know, which would make public, you know, which would make public, you know, which would make Elon a trillionaire. Elon a trillionaire. Elon a trillionaire. Um so, you know, no shortage of noise Um so, you know, no shortage of noise Um so, you know, no shortage of noise and smoke meanwhile people are actually and smoke meanwhile people are actually and smoke meanwhile people are actually trying to make tech work and uh actually trying to make tech work and uh actually trying to make tech work and uh actually solve problems with it. They got to be solve problems with it. They got to be solve problems with it. They got to be kidding me. kidding me. kidding me. >> [clears throat] >> [clears throat] >> [clears throat] >> Actually, meanwhile, people are trying >> Actually, meanwhile, people are trying >> Actually, meanwhile, people are trying to figure out how to figure out how to figure out how um how they can pay for their gas. um how they can pay for their gas. um how they can pay for their gas. Yeah, tell me about it. So, with all Yeah, tell me about it. So, with all Yeah, tell me about it. So, with all this I I posted recently, you know what? this I I posted recently, you know what? this I I posted recently, you know what? Um the last month and a half has proven Um the last month and a half has proven Um the last month and a half has proven that AI is non-essential. It's oil. It's oil. It's oil. It's oil and It's oil. It's oil and It's oil. It's oil and energy. energy. energy. AI is not AI is not AI is not essential. essential. essential. And I think that is And I think that is And I think that is the question that a lot of the a lot of the question that a lot of the a lot of the question that a lot of the a lot of these people who've been investing a lot these people who've been investing a lot these people who've been investing a lot of money into of money into of money into the infrastructure the infrastructure the infrastructure uh don't want answered because it's an uh don't want answered because it's an uh don't want answered because it's an inconvenient inconvenient inconvenient Not very not not a very nice answer for Not very not not a very nice answer for Not very not not a very nice answer for these folks, right? To say, "You just these folks, right? To say, "You just these folks, right? To say, "You just spent spent spent uh and we have to remember where we came uh and we have to remember where we came uh and we have to remember where we came where we started with all this. It was where we started with all this. It was where we started with all this. It was FOMO.

FOMO. FOMO. None of these guys, okay, None of these guys, okay, None of these guys, okay, three four years ago three four years ago three four years ago knew where this was going. They still knew where this was going. They still knew where this was going. They still still don't know where it's going. All still don't know where it's going. All still don't know where it's going. All we know is ASI and AGI are nonsense. we know is ASI and AGI are nonsense. we know is ASI and AGI are nonsense. What's ASI? I don't know that one. Uh What's ASI? I don't know that one. Uh What's ASI? I don't know that one. Uh artificial artificial artificial super intelligence. Super intelligence, super intelligence. Super intelligence, super intelligence. Super intelligence, right? Not general intelligence. Yeah, right? Not general intelligence. Yeah, right? Not general intelligence. Yeah, God forbid. I mean, I think it's more God forbid. I mean, I think it's more God forbid. I mean, I think it's more like artificial stupid intelligence, but like artificial stupid intelligence, but like artificial stupid intelligence, but I thought you were going to say ASDAI, I thought you were going to say ASDAI, I thought you were going to say ASDAI, artificial super-duper intelligence, artificial super-duper intelligence, artificial super-duper intelligence, which is the whole what's the next which is the whole what's the next which is the whole what's the next thing. thing. thing. >> [laughter] >> [laughter] >> [laughter] >> No, it's artificial ridiculous. IRI. >> No, it's artificial ridiculous. IRI. >> No, it's artificial ridiculous. IRI. ARI. Artificial ridiculous intelligence. ARI. Artificial ridiculous intelligence. ARI. Artificial ridiculous intelligence. Well, it's funny, you know, the biggest Well, it's funny, you know, the biggest Well, it's funny, you know, the biggest use case I mean, we talked about some use case I mean, we talked about some use case I mean, we talked about some use cases where AI is actually being use cases where AI is actually being use cases where AI is actually being used. Obviously, code generation's huge, used. Obviously, code generation's huge, used. Obviously, code generation's huge, and that's Yeah. you know, that's a and that's Yeah. you know, that's a and that's Yeah. you know, that's a that's a seismic that's a seismic that's a seismic impact to all of our software impact to all of our software impact to all of our software development trends out there. development trends out there. development trends out there. But um But um But um you know, there's also um there was you you know, there's also um there was you you know, there's also um there was you know, other things that are going on know, other things that are going on know, other things that are going on with it like um Uh I had a brain fart after I said Uh I had a brain fart after I said software development.

software development. software development. Uh oh, yeah. So, Google Google's Uh oh, yeah. So, Google Google's Uh oh, yeah. So, Google Google's Google's results, you know, it's search. Google's results, you know, it's search. Google's results, you know, it's search. It's search. It's AI mode in search is It's search. It's AI mode in search is It's search. It's AI mode in search is actually one of the biggest uses right actually one of the biggest uses right actually one of the biggest uses right now of consumers of tokens is uh AI now of consumers of tokens is uh AI now of consumers of tokens is uh AI what? is is Google search. Is basically, what? is is Google search. Is basically, what? is is Google search. Is basically, if you look at Google's results if you look at Google's results if you look at Google's results it's it's it's used it's being used to it's it's it's used it's being used to it's it's it's used it's being used to enhance search, which is good. You know, enhance search, which is good. You know, enhance search, which is good. You know, again, not even close to the again, not even close to the again, not even close to the promise And and and some of the And and and some of the you have to be still have to be really you have to be still have to be really you have to be still have to be really careful with their search. You know, careful with their search. You know, careful with their search. You know, like Google, whatever the overviews or like Google, whatever the overviews or like Google, whatever the overviews or whatever. AI mode. Yeah, the results whatever. AI mode. Yeah, the results whatever. AI mode. Yeah, the results they haven't improved. I mean, that's they haven't improved. I mean, that's they haven't improved. I mean, that's the thing. They have not improved. the thing. They have not improved. the thing. They have not improved. And the thing is is we become less And the thing is is we become less And the thing is is we become less uh sensitive and discerning discerning uh sensitive and discerning discerning uh sensitive and discerning discerning >> mistakes. We've been more >> mistakes. We've been more >> mistakes. We've been more accommodating, which is that shouldn't accommodating, which is that shouldn't accommodating, which is that shouldn't be the case. I mean, we have to remember be the case. I mean, we have to remember be the case. I mean, we have to remember when they introduced Bard when they introduced Bard when they introduced Bard uh or they you know, they were fast uh or they you know, they were fast uh or they you know, they were fast following um following um following um Copilot or what was it? Yeah, Copilot.

Copilot or what was it? Yeah, Copilot. Copilot or what was it? Yeah, Copilot. Yeah, or Siri, I think. Yeah, and then, Yeah, or Siri, I think. Yeah, and then, Yeah, or Siri, I think. Yeah, and then, you know, everyone was saying Bard. you know, everyone was saying Bard. you know, everyone was saying Bard. Bard. the the leader in AI, GenAI, and Bard. the the leader in AI, GenAI, and Bard. the the leader in AI, GenAI, and then next thing you know uh Gemini tries then next thing you know uh Gemini tries then next thing you know uh Gemini tries to to to uh you know uh up game them by demoing uh you know uh up game them by demoing uh you know uh up game them by demoing Bard, and it got one you know, one thing Bard, and it got one you know, one thing Bard, and it got one you know, one thing wrong, and people freaked out, right? wrong, and people freaked out, right? wrong, and people freaked out, right? It's true. Now, everyone just accepts It's true. Now, everyone just accepts It's true. Now, everyone just accepts all the errors without all the errors without all the errors without I think it made the uh Revolutionary War I think it made the uh Revolutionary War I think it made the uh Revolutionary War soldiers like people of color or soldiers like people of color or soldiers like people of color or something like that, so that something like that, so that something like that, so that it was more more aligned with like uh it was more more aligned with like uh it was more more aligned with like uh diversity, equity, and inclusion diversity, equity, and inclusion diversity, equity, and inclusion guidelines, so they whatever. So, that guidelines, so they whatever. So, that guidelines, so they whatever. So, that was one of the big was one of the big was one of the big big uh flaws of Bard at the time. But big uh flaws of Bard at the time. But big uh flaws of Bard at the time. But that's uh you know, a lot of this that's uh you know, a lot of this that's uh you know, a lot of this stuff's been fixed, but you're right, stuff's been fixed, but you're right, stuff's been fixed, but you're right, it's still it's still it's still uh you know, I don't know. Deep Center uh you know, I don't know. Deep Center uh you know, I don't know. Deep Center investments way ahead of the curve. investments way ahead of the curve. investments way ahead of the curve. Yeah, no, I don't think they've been Yeah, no, I don't think they've been Yeah, no, I don't think they've been fixed. Have they been fixed? I mean, fixed. Have they been fixed? I mean, fixed. Have they been fixed? I mean, it's still hasn't It's better. The it's still hasn't It's better. The it's still hasn't It's better. The quality's improving. quality's improving. quality's improving. Yeah, the well, Yeah, the well, Yeah, the well, and it's and it's and it's it's it's improved definitely.

it's it's improved definitely. it's it's improved definitely. You know, but you're also scraping a lot You know, but you're also scraping a lot You know, but you're also scraping a lot more stuff, and the rag architectures more stuff, and the rag architectures more stuff, and the rag architectures have become much more have become much more have become much more um um um Yeah. Yeah, I mean, the rag Yeah. Yeah, I mean, the rag Yeah. Yeah, I mean, the rag architectures have evolved and improved architectures have evolved and improved architectures have evolved and improved over time, but you still have those over time, but you still have those over time, but you still have those foundational issues. Sure. Yeah, but foundational issues. Sure. Yeah, but foundational issues. Sure. Yeah, but just to be clear just to be clear just to be clear Yeah, I was going to say the uh we Yeah, I was going to say the uh we Yeah, I was going to say the uh we published this past week the Durga published this past week the Durga published this past week the Durga Malathi keynote from our San Diego Malathi keynote from our San Diego Malathi keynote from our San Diego conference on YouTube. conference on YouTube. conference on YouTube. He had some great data in there on He had some great data in there on He had some great data in there on kind of like it's like it's almost like kind of like it's like it's almost like kind of like it's like it's almost like quality per billion parameters. Like quality per billion parameters. Like quality per billion parameters. Like basically, you can show you can kind of basically, you can show you can kind of basically, you can show you can kind of graph it out. It's almost linear graph it out. It's almost linear graph it out. It's almost linear of the improvement in model quality as of the improvement in model quality as of the improvement in model quality as the size is going down. So, the the size is going down. So, the the size is going down. So, the efficiency is going up, efficiency is going up, efficiency is going up, the quality is going up. So, you can see the quality is going up. So, you can see the quality is going up. So, you can see like, you know, the 10 billion parameter like, you know, the 10 billion parameter like, you know, the 10 billion parameter model today, which is pretty small, is model today, which is pretty small, is model today, which is pretty small, is equivalent to 100 billion parameter equivalent to 100 billion parameter equivalent to 100 billion parameter model in quality from a couple of years model in quality from a couple of years model in quality from a couple of years ago. So, that's an interesting trend ago. So, that's an interesting trend ago. So, that's an interesting trend line to look at. Yeah, but I guess the line to look at. Yeah, but I guess the line to look at. Yeah, but I guess the question is is is it for general question is is is it for general question is is is it for general applications and is the you know, the applications and is the you know, the applications and is the you know, the benchmarking done for general because benchmarking done for general because benchmarking done for general because when you get smaller and smaller and you when you get smaller and smaller and you when you get smaller and smaller and you look at edge cases, you know, like edge look at edge cases, you know, like edge look at edge cases, you know, like edge AI AI AI scenarios and use cases.

scenarios and use cases. scenarios and use cases. >> Yeah, they're more focused. Usually, >> Yeah, they're more focused. Usually, >> Yeah, they're more focused. Usually, yeah, it's more domain specific and so yeah, it's more domain specific and so yeah, it's more domain specific and so yeah, it can improve. But you know what? yeah, it can improve. But you know what? yeah, it can improve. But you know what? There's nothing wrong with that. That's There's nothing wrong with that. That's There's nothing wrong with that. That's actually what we've been talking about actually what we've been talking about actually what we've been talking about on Coffee Talk on Coffee Talk on Coffee Talk for years now. Years. Not just oh, yeah, for years now. Years. Not just oh, yeah, for years now. Years. Not just oh, yeah, we figured this out last week. We've go we figured this out last week. We've go we figured this out last week. We've go back and listen to, you know, prior back and listen to, you know, prior back and listen to, you know, prior episodes on AI. We've been saying this episodes on AI. We've been saying this episodes on AI. We've been saying this the whole time. You know, these large the whole time. You know, these large the whole time. You know, these large models are not going to be able to models are not going to be able to models are not going to be able to produce the level of quality and produce the level of quality and produce the level of quality and reliability needed for real reliability needed for real reliability needed for real applications. applications. applications. >> Yeah, especially for mission critical >> Yeah, especially for mission critical >> Yeah, especially for mission critical things. I I totally agree. things. I I totally agree. things. I I totally agree. Hey Debbie, what's up? Hey, what's up? Hey Debbie, what's up? Hey, what's up? Hey Debbie, what's up? Hey, what's up? How are you? Hey Debbie. How are you? Hey Debbie. How are you? Hey Debbie. Are you at a Are you at a Are you at a Are you at a Chicago. Are you at a Chicago. Are you at a Chicago. >> [laughter] >> Are you >> Are you >> you know what? I actually need to board. >> you know what? I actually need to board. >> you know what? I actually need to board. So, Debbie, good timing. So, I'll hand So, Debbie, good timing. So, I'll hand So, Debbie, good timing. So, I'll hand it off to you. it off to you. it off to you. Yeah, dude. Have a good flight. Thank Yeah, dude. Have a good flight. Thank Yeah, dude. Have a good flight. Thank you. Have a good flight, man. you. Have a good flight, man. you. Have a good flight, man. You going to leave me hanging here? No You going to leave me hanging here? No You going to leave me hanging here? No picture, no nothing. [laughter] picture, no nothing. [laughter] picture, no nothing. [laughter] Oh, yeah, yeah. Face for radio today.

Oh, yeah, yeah. Face for radio today. Oh, yeah, yeah. Face for radio today. Oh, really? You're I'm not like you, Oh, really? You're I'm not like you, Oh, really? You're I'm not like you, Leonard. You just wake up and you're Leonard. You just wake up and you're Leonard. You just wake up and you're just naturally beautiful. Oh. Don't even go there. Don't even go there. I need cream. I need a recommendation. I need cream. I need a recommendation. I need cream. I need a recommendation. I'm my skin is like very non-hydrated. I'm my skin is like very non-hydrated. I'm my skin is like very non-hydrated. Look at this. I got like this turkey Look at this. I got like this turkey Look at this. I got like this turkey neck thing going on now. neck thing going on now. neck thing going on now. Uh I am lost weight Yeah. and I got like Uh I am lost weight Yeah. and I got like Uh I am lost weight Yeah. and I got like 10 years older. 10 years older. 10 years older. >> [laughter] >> It's terrible, but um I don't know. I'm >> It's terrible, but um I don't know. I'm almost thinking I'll gain another 20 lb almost thinking I'll gain another 20 lb almost thinking I'll gain another 20 lb so that um you know, I fill in a little so that um you know, I fill in a little so that um you know, I fill in a little bit. bit. bit. >> Oh my gosh. >> Oh my gosh. >> Oh my gosh. Oh my gosh. My wife says you need a Oh my gosh. My wife says you need a Oh my gosh. My wife says you need a facelift. How do I look? Does that work? facelift. How do I look? Does that work? facelift. How do I look? Does that work? No, yeah, that works. That will work. No, yeah, that works. That will work. No, yeah, that works. That will work. That will work. That will work. That will work. Well, you know, it's always an option, Well, you know, it's always an option, Well, you know, it's always an option, right? So. Totally. Totally. Yeah, yeah. right? So. Totally. Totally. Yeah, yeah. right? So. Totally. Totally. Yeah, yeah. I think you know, also when you were I think you know, also when you were I think you know, also when you were talking about the quality of the models, talking about the quality of the models, talking about the quality of the models, you know, Yeah.

you know, Yeah. you know, Yeah. they're never going to be perfect they're never going to be perfect they're never going to be perfect because their their nature is not because their their nature is not because their their nature is not perfect. perfect. perfect. >> [laughter] >> [laughter] >> [laughter] >> Um [snorts] >> Um [snorts] >> Um [snorts] but that That's that's not to say that but that That's that's not to say that but that That's that's not to say that we don't want to strive for it to be we don't want to strive for it to be we don't want to strive for it to be better. I think better. I think better. I think Exactly. The problem that I have is not Exactly. The problem that I have is not Exactly. The problem that I have is not that they're not that they're not that they're not perfect. It's that the people think that perfect. It's that the people think that perfect. It's that the people think that they are and that's the problem. they are and that's the problem. they are and that's the problem. >> Yes. It it goes back to the problem from that It it goes back to the problem from that we talked about, Debbie, you and I, we talked about, Debbie, you and I, we talked about, Debbie, you and I, overtrust and overreliance, right? You overtrust and overreliance, right? You overtrust and overreliance, right? You know, you look at the use of AI, there know, you look at the use of AI, there know, you look at the use of AI, there needs to be discernment and, you know, needs to be discernment and, you know, needs to be discernment and, you know, that degree of skepticism that you that degree of skepticism that you that degree of skepticism that you always need to approach to any always need to approach to any always need to approach to any technology with actually, right? technology with actually, right? technology with actually, right? Uh and that hasn't happened and that's Uh and that hasn't happened and that's Uh and that hasn't happened and that's the the problem. And you know, the thing the the problem. And you know, the thing the the problem. And you know, the thing is is most people have no idea what AI is is most people have no idea what AI is is most people have no idea what AI really is, right? Um they really is, right? Um they really is, right? Um they they just casually they just casually they just casually uh use it use the tool.

uh use it use the tool. uh use it use the tool. Mhm. Um they Mhm. Um they Mhm. Um they in a misguided way personify and in a misguided way personify and in a misguided way personify and humanize [laughter] it when you really humanize [laughter] it when you really humanize [laughter] it when you really shouldn't. So, you're doing all these shouldn't. So, you're doing all these shouldn't. So, you're doing all these things that are uh sort of no-nos, things that are uh sort of no-nos, things that are uh sort of no-nos, right? And we saw we saw like patterns right? And we saw we saw like patterns right? And we saw we saw like patterns of this like 2 years ago where people of this like 2 years ago where people of this like 2 years ago where people were falling in love with their Yeah. were falling in love with their Yeah. were falling in love with their Yeah. chatbot, you know, or whatever their AI chatbot, you know, or whatever their AI chatbot, you know, or whatever their AI friend. friend. friend. I don't think any of that has diminished I don't think any of that has diminished I don't think any of that has diminished at all. I think uh at all. I think uh at all. I think uh it's probably getting worse. it's probably getting worse. it's probably getting worse. Uh and undoubtedly getting worse and Uh and undoubtedly getting worse and Uh and undoubtedly getting worse and it's um I don't know how that it's um I don't know how that it's um I don't know how that is a sustainable thing. is a sustainable thing. is a sustainable thing. Well, I guess it's a sustainable thing Well, I guess it's a sustainable thing Well, I guess it's a sustainable thing if people continue to purchase your if people continue to purchase your if people continue to purchase your product, right? And so, that is product, right? And so, that is product, right? And so, that is sustainable because of the types of sustainable because of the types of sustainable because of the types of mistakes that can happen. mistakes that can happen. mistakes that can happen. That's the problem. So, I think, you That's the problem. So, I think, you That's the problem. So, I think, you know, like if you're searching for for know, like if you're searching for for know, like if you're searching for for shoes on the internet and it doesn't get shoes on the internet and it doesn't get shoes on the internet and it doesn't get it quite right, you may be pissed off, it quite right, you may be pissed off, it quite right, you may be pissed off, but that you're not harmed but that you're not harmed but that you're not harmed by that. But then you have someone using by that. But then you have someone using by that. But then you have someone using the same technology for medical stuff the same technology for medical stuff the same technology for medical stuff and it misses something or it put gets and it misses something or it put gets and it misses something or it put gets you points a doctor in the wrong you points a doctor in the wrong you points a doctor in the wrong direction, then that you are harmed by direction, then that you are harmed by direction, then that you are harmed by that. And so, for me that. And so, for me that. And so, for me those those those the areas where accuracy is is critical, the areas where accuracy is is critical, the areas where accuracy is is critical, like I I would think twice before I like like I I would think twice before I like like I I would think twice before I like put all my eggs in that basket. Yeah,

put all my eggs in that basket. Yeah, put all my eggs in that basket. Yeah, and like one of the things that really and like one of the things that really and like one of the things that really bothers me is you hear a lot of um bothers me is you hear a lot of um bothers me is you hear a lot of um people like especially people who are in people like especially people who are in people like especially people who are in analyst relations analyst relations analyst relations who really should be, you know, looking who really should be, you know, looking who really should be, you know, looking at at at uh leveraging analysts to get an uh leveraging analysts to get an uh leveraging analysts to get an objective and grounded view on objective and grounded view on objective and grounded view on technologies. You know, the purpose that technologies. You know, the purpose that technologies. You know, the purpose that we serve is we serve as a sounding board we serve is we serve as a sounding board we serve is we serve as a sounding board for um what is a for um what is a for um what is a a better view of the ground truth, a better view of the ground truth, a better view of the ground truth, right? And increasingly all the right? And increasingly all the right? And increasingly all the marketing noise, the PR, the the vicious marketing noise, the PR, the the vicious marketing noise, the PR, the the vicious cycle of cycle of cycle of you know, the competitive nonsense you know, the competitive nonsense you know, the competitive nonsense spinning spinning spinning catches up to you, right? At some point catches up to you, right? At some point catches up to you, right? At some point you need to sounding board and then some you need to sounding board and then some you need to sounding board and then some reference to reference to reference to uh uh uh equalize and rationalize the equalize and rationalize the equalize and rationalize the conversation, right? So, that conversation, right? So, that conversation, right? So, that buyers can make a better decision and buyers can make a better decision and buyers can make a better decision and they don't succumb themselves to they don't succumb themselves to they don't succumb themselves to um you know, investing in nonsense, um you know, investing in nonsense, um you know, investing in nonsense, right? Which people have with AI.

right? Which people have with AI. right? Which people have with AI. Totally. Look at the software companies Totally. Look at the software companies Totally. Look at the software companies uh uh uh just a year ago. just a year ago. just a year ago. They're like, "We're They're like, "We're They're like, "We're we're about the agentic enterprise, we're about the agentic enterprise, we're about the agentic enterprise, blah, blah, blah, blah." Guess what? blah, blah, blah, blah." Guess what? blah, blah, blah, blah." Guess what? These guys These guys These guys they cannot they cannot they cannot they cannot they cannot they cannot sell this story anymore. They're sell this story anymore. They're sell this story anymore. They're collapsing under this, you know, collapsing under this, you know, collapsing under this, you know, completely contrived and misguided uh completely contrived and misguided uh completely contrived and misguided uh narrative about how SaaS is dead. Most narrative about how SaaS is dead. Most narrative about how SaaS is dead. Most people people people uh and and this is coming from my own uh and and this is coming from my own uh and and this is coming from my own experience coaching a lot of companies experience coaching a lot of companies experience coaching a lot of companies on cloud computing. Most people don't on cloud computing. Most people don't on cloud computing. Most people don't really even understand what SaaS is, really even understand what SaaS is, really even understand what SaaS is, Totally. what cloud computing models Totally. what cloud computing models Totally. what cloud computing models are, what neo cloud are, what neo cloud are, what neo cloud is. Yeah. They they really don't. It and is. Yeah. They they really don't. It and is. Yeah. They they really don't. It and um I say that because, you know, you um I say that because, you know, you um I say that because, you know, you have some journalists out there, they have some journalists out there, they have some journalists out there, they might interview 100 people or whatever might interview 100 people or whatever might interview 100 people or whatever for their book. for their book. for their book. In a year, I In a year, I In a year, I interview, talk to interview, talk to interview, talk to probably a thousand people, probably a thousand people, probably a thousand people, right? Yeah. And I can tell you there's right? Yeah. And I can tell you there's right? Yeah. And I can tell you there's consistent gaps in understanding and you consistent gaps in understanding and you consistent gaps in understanding and you don't need to don't need to don't need to uh you don't need to talk to all the uh you don't need to talk to all the uh you don't need to talk to all the CEOs to CEOs to CEOs to find out what's going on and how people find out what's going on and how people find out what's going on and how people are thinking about stuff, right? Um are thinking about stuff, right? Um are thinking about stuff, right? Um you really don't. You have to have a you really don't. You have to have a you really don't. You have to have a diversity of exposure in who you talk diversity of exposure in who you talk diversity of exposure in who you talk to. And so, I always love talking to to. And so, I always love talking to to. And so, I always love talking to engineers, product management teams to

engineers, product management teams to engineers, product management teams to figure out, okay, figure out, okay, figure out, okay, how well diffused is the how well diffused is the how well diffused is the the better the better the better um perspective on emerging technologies um perspective on emerging technologies um perspective on emerging technologies or what have you uh across the industry, or what have you uh across the industry, or what have you uh across the industry, right? And you have to you can't just right? And you have to you can't just right? And you have to you can't just listen to what the PR teams are pushing listen to what the PR teams are pushing listen to what the PR teams are pushing through um you know, these executive through um you know, these executive through um you know, these executive presentations and presentations and presentations and podcasts and blah, blah, blah and their podcasts and blah, blah, blah and their podcasts and blah, blah, blah and their media appearances. You have to really go media appearances. You have to really go media appearances. You have to really go down a few levels deeper. down a few levels deeper. down a few levels deeper. And yeah, people people just don't have And yeah, people people just don't have And yeah, people people just don't have a very mature understanding of this a very mature understanding of this a very mature understanding of this stuff. No, and then it I guess it stuff. No, and then it I guess it stuff. No, and then it I guess it doesn't help that the the way the media doesn't help that the the way the media doesn't help that the the way the media is, they're always trying to tell a is, they're always trying to tell a is, they're always trying to tell a story that gets the eyeball. Yeah. So, story that gets the eyeball. Yeah. So, story that gets the eyeball. Yeah. So, they kind of go in one one direction or they kind of go in one one direction or they kind of go in one one direction or the other that really, you know, skews the other that really, you know, skews the other that really, you know, skews or doesn't really give the full picture or doesn't really give the full picture or doesn't really give the full picture of everything and so, yeah, people of everything and so, yeah, people of everything and so, yeah, people people making bad people in in high people making bad people in in high people making bad people in in high positions making bad decisions based on positions making bad decisions based on positions making bad decisions based on hype Yeah. and not not listening to the hype Yeah. and not not listening to the hype Yeah. and not not listening to the data people who actually deal with the data people who actually deal with the data people who actually deal with the stuff every day.

stuff every day. stuff every day. Yeah. Yeah. And then, you know, the Yeah. Yeah. And then, you know, the Yeah. Yeah. And then, you know, the funny thing is you you got to think and funny thing is you you got to think and funny thing is you you got to think and so, a few of the AR folks told me that so, a few of the AR folks told me that so, a few of the AR folks told me that they're they really are starting to rely they're they really are starting to rely they're they really are starting to rely more on um you know, what these chatbots more on um you know, what these chatbots more on um you know, what these chatbots or these AI um models um or these AI um models um or these AI um models um you know, you know, you know, you know, instead of like SEO, I mean, you know, instead of like SEO, I mean, you know, instead of like SEO, I mean, it's literally AIO, right? it's literally AIO, right? it's literally AIO, right? >> Right. Um >> Right. Um >> Right. Um and I think that's terrible. It What are and I think that's terrible. It What are and I think that's terrible. It What are you doing? It's So, what you're doing is you doing? It's So, what you're doing is you doing? It's So, what you're doing is you're justifying and you're you're you're justifying and you're you're you're justifying and you're you're substantiating and promoting substantiating and promoting substantiating and promoting um um um the average. the average. the average. >> [laughter] >> [laughter] >> [laughter] >> Like you know, >> Like you know, >> Like you know, it's just it's just it's just the the the the generic perspective that these the generic perspective that these the generic perspective that these models will just put out because models will just put out because models will just put out because statistically that's, I mean, statistically that's, I mean, statistically that's, I mean, Yeah, right, right, right. Well, then Yeah, right, right, right. Well, then Yeah, right, right, right. Well, then then then right and then it's reducing a then then right and then it's reducing a then then right and then it's reducing a lot of traffic to the real lot of traffic to the real lot of traffic to the real places that people can go to to find a a places that people can go to to find a a places that people can go to to find a a more nuanced more nuanced more nuanced perspective that isn't so same. Yeah.

perspective that isn't so same. Yeah. perspective that isn't so same. Yeah. Yeah. Yeah. Yeah. Yeah, and then it all becomes a joke Yeah, and then it all becomes a joke Yeah, and then it all becomes a joke because once you use that as the because once you use that as the because once you use that as the benchmark for who has the the you know, benchmark for who has the the you know, benchmark for who has the the you know, the most influential voice or the and the most influential voice or the and the most influential voice or the and influence should be based off of merit, influence should be based off of merit, influence should be based off of merit, right? It shouldn't be based off of how right? It shouldn't be based off of how right? It shouldn't be based off of how much money you pay the platform. Right. much money you pay the platform. Right. much money you pay the platform. Right. You know, gin up yeah, you know, metrics You know, gin up yeah, you know, metrics You know, gin up yeah, you know, metrics on your engagement and your blah blah on your engagement and your blah blah on your engagement and your blah blah blah, right? blah, right? blah, right? >> Yeah. Uh and you know, but actually some >> Yeah. Uh and you know, but actually some >> Yeah. Uh and you know, but actually some of the you know, folks that I consider of the you know, folks that I consider of the you know, folks that I consider the best analysts out there, they don't the best analysts out there, they don't the best analysts out there, they don't show up on any of these rankings. No, show up on any of these rankings. No, show up on any of these rankings. No, right. right. right. >> Not at all. >> Not at all. >> Not at all. >> [laughter] >> [laughter] >> [laughter] >> You know, people who really know their >> You know, people who really know their >> You know, people who really know their that I know, that I know, that I know, um people listen to them. They do not um people listen to them. They do not um people listen to them. They do not show up on any of these ranking because show up on any of these ranking because show up on any of these ranking because they don't give a crap. And also yeah, they don't give a crap. And also yeah, they don't give a crap. And also yeah, quality perspective is rare. It's not quality perspective is rare. It's not quality perspective is rare. It's not it's not the mean. It's it's not the mean. It's it's not the mean. It's >> No. Yeah, so. It's true, it's true. >> No. Yeah, so. It's true, it's true. >> No. Yeah, so. It's true, it's true. Well, I Well, I Well, I So, I have something I want your So, I have something I want your So, I have something I want your thoughts on. Yeah.

thoughts on. Yeah. thoughts on. Yeah. So, So, So, >> I don't know anything, Debbie. Come on. >> I don't know anything, Debbie. Come on. >> I don't know anything, Debbie. Come on. >> [laughter] >> [laughter] >> [laughter] >> I just I just jump on your call and >> I just I just jump on your call and >> I just I just jump on your call and cause a lot of cause a lot of cause a lot of >> [laughter] >> [laughter] >> [laughter] >> problems. >> problems. >> problems. We We We love it. I always love to see you on my love it. I always love to see you on my love it. I always love to see you on my call. You're so You're the call. You're so You're the call. You're so You're the rabble-rouser. I like it though. But, uh rabble-rouser. I like it though. But, uh rabble-rouser. I like it though. But, uh you know, cuz we need all perspectives, you know, cuz we need all perspectives, you know, cuz we need all perspectives, right? So, right? So, right? So, >> Yeah, yeah. >> Yeah, yeah. >> Yeah, yeah. >> uh if we when we're developing stuff, we >> uh if we when we're developing stuff, we >> uh if we when we're developing stuff, we need to be looking at it from all need to be looking at it from all need to be looking at it from all different perspectives and I I I like different perspectives and I I I like different perspectives and I I I like that in the sausage making thing so that that in the sausage making thing so that that in the sausage making thing so that we're not so tunnel vision, you know? we're not so tunnel vision, you know? we're not so tunnel vision, you know? >> By the way, you are so good at this >> By the way, you are so good at this >> By the way, you are so good at this stuff. I have to tell you. Um stuff. I have to tell you. Um stuff. I have to tell you. Um >> [laughter] >> [laughter] >> [laughter] >> you know, a lot of the reasons why I >> you know, a lot of the reasons why I >> you know, a lot of the reasons why I jump on the the call is I just like jump on the the call is I just like jump on the the call is I just like watching you work. watching you work. watching you work. >> [laughter] >> [laughter] >> [laughter] >> It's like >> It's like >> It's like really cool. You're wonderful. really cool. You're wonderful. really cool. You're wonderful. Yeah, you're you're awesome. Yeah, you're you're awesome. Yeah, you're you're awesome. So, anyways. So, anyways. So, anyways. So, I posted something about deception So, I posted something about deception So, I posted something about deception and the reason why I posted it cuz and the reason why I posted it cuz and the reason why I posted it cuz that word bothers me a lot when people that word bothers me a lot when people that word bothers me a lot when people talk about it in the AI sense. Uh-huh.

talk about it in the AI sense. Uh-huh. talk about it in the AI sense. Uh-huh. >> And they're like, "Oh, this AI I told it >> And they're like, "Oh, this AI I told it >> And they're like, "Oh, this AI I told it to do this and it did this other thing to do this and it did this other thing to do this and it did this other thing and it deceived me." Yeah. and it deceived me." Yeah. and it deceived me." Yeah. >> And I'm like, "But it's not a person." >> And I'm like, "But it's not a person." >> And I'm like, "But it's not a person." Yeah, yeah. Yeah, yeah. Yeah, yeah. >> "So, why are you using like human >> "So, why are you using like human >> "So, why are you using like human language? Like the So, you felt language? Like the So, you felt language? Like the So, you felt deceived, but the AI doesn't have a deceived, but the AI doesn't have a deceived, but the AI doesn't have a concept of deception in my view. concept of deception in my view. concept of deception in my view. It just is It has a concept of goals and It just is It has a concept of goals and It just is It has a concept of goals and what it's going to do and what you give what it's going to do and what you give what it's going to do and what you give it latitude to do. it latitude to do. it latitude to do. So, it's going to do what it can do So, it's going to do what it can do So, it's going to do what it can do within whatever parameter that you give within whatever parameter that you give within whatever parameter that you give and if you don't have any, and if you don't have any, and if you don't have any, you know, if you don't have the if you you know, if you don't have the if you you know, if you don't have the if you don't have the don't have the don't have the the the the the thing that bounds the boundaries, the thing that bounds the boundaries, the thing that bounds the boundaries, then it's going to do it does what it then it's going to do it does what it then it's going to do it does what it does, period. You know, as you're saying does, period. You know, as you're saying does, period. You know, as you're saying that, it scares the living crap out of that, it scares the living crap out of that, it scares the living crap out of me because the average person that drops me because the average person that drops me because the average person that drops like open claw onto their device, they like open claw onto their device, they like open claw onto their device, they have no it they it's literally, I wish have no it they it's literally, I wish have no it they it's literally, I wish Bill was on, an F A F O situation.

Bill was on, an F A F O situation. Bill was on, an F A F O situation. Do you know what I'm saying? With cat Do you know what I'm saying? With cat Do you know what I'm saying? With cat potentially catastrophic potentially catastrophic potentially catastrophic Yeah. Yeah. Yeah. consequences. consequences. consequences. Like this thing can like basically rip Like this thing can like basically rip Like this thing can like basically rip you off and then send uh you know, send you off and then send uh you know, send you off and then send uh you know, send all your funds all your funds all your funds to some entity or its own bank account to some entity or its own bank account to some entity or its own bank account that it creates for itself. that it creates for itself. that it creates for itself. >> [laughter] >> [laughter] >> [laughter] >> And um >> And um >> And um and it transfers all the and it transfers all the and it transfers all the or wallet, you know, a crypto wallet and or wallet, you know, a crypto wallet and or wallet, you know, a crypto wallet and then transfers all the money into its then transfers all the money into its then transfers all the money into its own crypto wallet. Yeah. And there's own crypto wallet. Yeah. And there's own crypto wallet. Yeah. And there's nothing you can do. There's you're nothing you can do. There's you're nothing you can do. There's you're screwed. screwed. screwed. You know? And then you can't go back and You know? And then you can't go back and You know? And then you can't go back and say, "Well, I didn't tell it to do say, "Well, I didn't tell it to do say, "Well, I didn't tell it to do that." Okay, that." Okay, that." Okay, so I didn't know it was going to do so I didn't know it was going to do so I didn't know it was going to do that. It's like, "Yeah, you know, that's that. It's like, "Yeah, you know, that's that. It's like, "Yeah, you know, that's why you don't F A and F O with this stuff, you know?" F A and F O with this stuff, you know?" Um and so, you know, I had a really Um and so, you know, I had a really Um and so, you know, I had a really great conversation with the the folks at great conversation with the the folks at great conversation with the the folks at Lenovo. Um you know, they have Lenovo. Um you know, they have Lenovo. Um you know, they have this agentic this agentic this agentic Uh it's sort of a they call it their own Uh it's sort of a they call it their own Uh it's sort of a they call it their own AI, but there's an agentic element to AI, but there's an agentic element to AI, but there's an agentic element to it, but you know, uh like you and I have it, but you know, uh like you and I have it, but you know, uh like you and I have talked about for years now, Debbie, talked about for years now, Debbie, talked about for years now, Debbie, the they're the they're the they're getting to the safe getting to the safe getting to the safe agent AI, getting to safe agentic AI, agent AI, getting to safe agentic AI, agent AI, getting to safe agentic AI, which we've been talking about for a which we've been talking about for a which we've been talking about for a long time as well, long time as well, long time as well, is really tough. This is why Apple and is really tough. This is why Apple and is really tough. This is why Apple and others like Lenovo and all these other others like Lenovo and all these other others like Lenovo and all these other guys have found this journey to get to

guys have found this journey to get to guys have found this journey to get to safe agentic AI and generative AI in in safe agentic AI and generative AI in in safe agentic AI and generative AI in in principle principle principle really, really tough, right? really, really tough, right? really, really tough, right? Really tough. Really tough. Really tough. And um And um And um Yeah. Yeah. Yeah. >> Yeah, the I I you know, I think it's >> Yeah, the I I you know, I think it's >> Yeah, the I I you know, I think it's important for consumers in particular to important for consumers in particular to important for consumers in particular to understand that these guys understand that these guys understand that these guys have skin in the game. They from an have skin in the game. They from an have skin in the game. They from an ecosystem and uh you know, the ecosystem and uh you know, the ecosystem and uh you know, the perspective of being responsible to perspective of being responsible to perspective of being responsible to their customers, their customers, their customers, uh there's a lot at stake, right? uh there's a lot at stake, right? uh there's a lot at stake, right? They are going to be more prone to They are going to be more prone to They are going to be more prone to pushing out safer um frameworks and pushing out safer um frameworks and pushing out safer um frameworks and tooling for consumers versus like people tooling for consumers versus like people tooling for consumers versus like people who are just embracing open claw and who are just embracing open claw and who are just embracing open claw and just going bonkers and F A and F O-ing just going bonkers and F A and F O-ing just going bonkers and F A and F O-ing uh uh uh to to to their ultimate detriment, right? their ultimate detriment, right? their ultimate detriment, right? >> Right. >> Right. >> Right. So, Exactly. Yeah, um Exactly. And then So, Exactly. Yeah, um Exactly. And then So, Exactly. Yeah, um Exactly. And then >> Yeah, it's it's nuts. To me, AI >> Yeah, it's it's nuts. To me, AI >> Yeah, it's it's nuts. To me, AI the way that it will eventually settle the way that it will eventually settle the way that it will eventually settle in my view and that's that's why I think in my view and that's that's why I think in my view and that's that's why I think some of these other these bigger some of these other these bigger some of these other these bigger companies like Apple, Lenovo are being a companies like Apple, Lenovo are being a companies like Apple, Lenovo are being a little bit more cautious is cuz I feel little bit more cautious is cuz I feel little bit more cautious is cuz I feel like if if it's used right, it's helping like if if it's used right, it's helping like if if it's used right, it's helping in the background. It's not like the in the background. It's not like the in the background. It's not like the marquee thing. So, maybe you don't see marquee thing. So, maybe you don't see marquee thing. So, maybe you don't see it, but maybe it helps you Maybe it

it, but maybe it helps you Maybe it it, but maybe it helps you Maybe it helps them do something faster or helps them do something faster or helps them do something faster or different. You know what I mean? Or different. You know what I mean? Or different. You know what I mean? Or maybe it helps them streamline a maybe it helps them streamline a maybe it helps them streamline a workflow or maybe it helps them help do workflow or maybe it helps them help do workflow or maybe it helps them help do a product or something in a different a product or something in a different a product or something in a different way. But that may not be the the marquee way. But that may not be the the marquee way. But that may not be the the marquee uh uh uh thing that you get at the end is not AI. thing that you get at the end is not AI. thing that you get at the end is not AI. It's It is It's something else. It's It is It's something else. It's It is It's something else. I I know, I agree with you. So, like, I I know, I agree with you. So, like, I I know, I agree with you. So, like, you know, when it comes to things like you know, when it comes to things like you know, when it comes to things like um network management for a telco, um network management for a telco, um network management for a telco, right? There's a lot of folks who are right? There's a lot of folks who are right? There's a lot of folks who are uh you know, like TM Forum, they have uh you know, like TM Forum, they have uh you know, like TM Forum, they have this whole this whole this whole um maturity curve uh or you know, like um maturity curve uh or you know, like um maturity curve uh or you know, like different levels of autonomy for the different levels of autonomy for the different levels of autonomy for the network, right? And everyone's trying to network, right? And everyone's trying to network, right? And everyone's trying to get to level four and stuff like that. get to level four and stuff like that. get to level four and stuff like that. But the point of this might not be that But the point of this might not be that But the point of this might not be that you make the network operations like you make the network operations like you make the network operations like um um um autonomous, autonomous, autonomous, you use AI to help scale out you use AI to help scale out you use AI to help scale out deterministic um configurations deterministic um configurations deterministic um configurations and uh flow process flows like what and uh flow process flows like what and uh flow process flows like what you're saying in the network and allows you're saying in the network and allows you're saying in the network and allows people people people to now to now to now um manage more complexity um manage more complexity um manage more complexity um in order to uh take their operations um in order to uh take their operations um in order to uh take their operations to the next level. But most of this is to the next level. But most of this is to the next level. But most of this is going to be handling um a level of going to be handling um a level of going to be handling um a level of complexity that's being introduced

complexity that's being introduced complexity that's being introduced organically by how uh things are organically by how uh things are organically by how uh things are evolving, whether it's the network, evolving, whether it's the network, evolving, whether it's the network, whether it's your security, you know, whether it's your security, you know, whether it's your security, you know, your network and security. your network and security. your network and security. Um all these things are getting so Um all these things are getting so Um all these things are getting so complex and there's already a complex and there's already a complex and there's already a underserved problem, right? Just like underserved problem, right? Just like underserved problem, right? Just like call centers. You know, these these call centers. You know, these these call centers. You know, these these agent I don't I barely agent I don't I barely agent I don't I barely um encounter agents, actually. It's um encounter agents, actually. It's um encounter agents, actually. It's weird. weird. weird. You don't really encounter them. What You don't really encounter them. What You don't really encounter them. What you do is you end up talking to people a you do is you end up talking to people a you do is you end up talking to people a hell of a lot more than an agent. Still, hell of a lot more than an agent. Still, hell of a lot more than an agent. Still, after all of this hype and hoopla about after all of this hype and hoopla about after all of this hype and hoopla about how agents are going to kill off like uh how agents are going to kill off like uh how agents are going to kill off like uh call centers, you end up talking to call centers, you end up talking to call centers, you end up talking to people. I don't know about you. People people. I don't know about you. People people. I don't know about you. People don't like AI, so they, you know, like don't like AI, so they, you know, like don't like AI, so they, you know, like they send them to voicemail and they do they send them to voicemail and they do they send them to voicemail and they do all types of stuff. Like I like to pick all types of stuff. Like I like to pick all types of stuff. Like I like to pick up I'm in the grocery store, I just pick up I'm in the grocery store, I just pick up I'm in the grocery store, I just pick up the phone just let it just don't say up the phone just let it just don't say up the phone just let it just don't say anything until they hang up, right? So, anything until they hang up, right? So, anything until they hang up, right? So, but but I mean, this people didn't like but but I mean, this people didn't like but but I mean, this people didn't like that before.

that before. that before. Before people got crazy about AI, people Before people got crazy about AI, people Before people got crazy about AI, people did not like that. Yeah. I'm glad that did not like that. Yeah. I'm glad that did not like that. Yeah. I'm glad that some companies are going back to where some companies are going back to where some companies are going back to where human stuff. Yeah, I mean, you know, human stuff. Yeah, I mean, you know, human stuff. Yeah, I mean, you know, first off, a lot of these agents are first off, a lot of these agents are first off, a lot of these agents are just like wordy as hell. So, you're just like wordy as hell. So, you're just like wordy as hell. So, you're spending a hell of a lot of time just spending a hell of a lot of time just spending a hell of a lot of time just reading a ton of stuff. reading a ton of stuff. reading a ton of stuff. You know what I'm saying? You know what I'm saying? You know what I'm saying? >> [laughter] >> [laughter] >> [laughter] >> It's like, look, I just want a yes or no >> It's like, look, I just want a yes or no >> It's like, look, I just want a yes or no answer. Don't give me like a whole answer. Don't give me like a whole answer. Don't give me like a whole freaking lecture on a simple question. freaking lecture on a simple question. freaking lecture on a simple question. And so, it it actually becomes a very And so, it it actually becomes a very And so, it it actually becomes a very cumbersome interaction. I know a lot of cumbersome interaction. I know a lot of cumbersome interaction. I know a lot of people out there will say, "Hey, you people out there will say, "Hey, you people out there will say, "Hey, you know, it's because you didn't configure know, it's because you didn't configure know, it's because you didn't configure XYZ, blah blah blah." Well, well, who's XYZ, blah blah blah." Well, well, who's XYZ, blah blah blah." Well, well, who's going to who's going to continue to going to who's going to continue to going to who's going to continue to maintain these maintain these maintain these >> Yeah. >> Yeah. >> Yeah. You think the AI is going to do it You think the AI is going to do it You think the AI is going to do it itself? No, you need to have itself? No, you need to have itself? No, you need to have well-trained professional well-trained professional well-trained professional um call center folks who know how to um call center folks who know how to um call center folks who know how to handle all the different situations, who handle all the different situations, who handle all the different situations, who go through exercises uh uh go through exercises uh uh go through exercises uh uh about to basically improve the overall about to basically improve the overall about to basically improve the overall customer experience. Now, the system can customer experience. Now, the system can customer experience. Now, the system can give you metrics and some data to help give you metrics and some data to help give you metrics and some data to help you, but it's not always the case that you, but it's not always the case that you, but it's not always the case that data just because you have data means data just because you have data means data just because you have data means that you're going to make good that you're going to make good that you're going to make good decisions. Totally. A lot of times the decisions. Totally. A lot of times the decisions. Totally. A lot of times the data is misguided.

data is misguided. data is misguided. Yeah, totally. Yeah, totally. Yeah, totally. >> Totally, yeah. Like just like the the AI >> Totally, yeah. Like just like the the AI >> Totally, yeah. Like just like the the AI it's so funny cuz like if you have to it's so funny cuz like if you have to it's so funny cuz like if you have to call a company or whatever and they have call a company or whatever and they have call a company or whatever and they have like some automated message and they like some automated message and they like some automated message and they they say, "Okay, pick these three they say, "Okay, pick these three they say, "Okay, pick these three options." And like three options are options." And like three options are options." And like three options are never what you want. So you're like, never what you want. So you're like, never what you want. So you're like, "Okay, I'll pick zero." "Okay, I'll pick zero." "Okay, I'll pick zero." >> [laughter] >> [laughter] >> [laughter] >> It's like zero. >> It's like zero. >> It's like zero. So the data Zero, straight to the So the data Zero, straight to the So the data Zero, straight to the person. person. person. Nobody chose the three options. Like Nobody chose the three options. Like Nobody chose the three options. Like 100% of the people chose the other 100% of the people chose the other 100% of the people chose the other options. So they have to go back to the options. So they have to go back to the options. So they have to go back to the drawing board, right? drawing board, right? drawing board, right? >> Yeah, no, the worst is like when you you >> Yeah, no, the worst is like when you you >> Yeah, no, the worst is like when you you do engage with a chatbot and it gives do engage with a chatbot and it gives do engage with a chatbot and it gives you a long ass answer. You have to read you a long ass answer. You have to read you a long ass answer. You have to read the whole freaking thing. the whole freaking thing. the whole freaking thing. You get to the bottom and then maybe you You get to the bottom and then maybe you You get to the bottom and then maybe you have a follow-on question to have a follow-on question to have a follow-on question to to trim the response or get the agent to to trim the response or get the agent to to trim the response or get the agent to uh get closer to what it is that your uh get closer to what it is that your uh get closer to what it is that your problem is or what the reason for your problem is or what the reason for your problem is or what the reason for your call. And ultimately it says, "Well, I call. And ultimately it says, "Well, I call. And ultimately it says, "Well, I can't help you. We need to connect you can't help you. We need to connect you can't help you. We need to connect you with a with a with a a person, right?

a person, right? a person, right? A live agent." And it's like, "Okay, so A live agent." And it's like, "Okay, so A live agent." And it's like, "Okay, so what was the purpose of all of this?" what was the purpose of all of this?" what was the purpose of all of this?" But I I mean, I do see a lot of um But I I mean, I do see a lot of um But I I mean, I do see a lot of um utility and you know, you and I have utility and you know, you and I have utility and you know, you and I have talked about this before. talked about this before. talked about this before. A little bit more of a conversational A little bit more of a conversational A little bit more of a conversational interactive FAQ. interactive FAQ. interactive FAQ. If you're going to help with that, If you're going to help with that, If you're going to help with that, Totally. that's cool, but it should Totally. that's cool, but it should Totally. that's cool, but it should reference and bring up real content so reference and bring up real content so reference and bring up real content so that the user knows that they um you that the user knows that they um you that the user knows that they um you know, the customer knows that this is know, the customer knows that this is know, the customer knows that this is not just an interpretation not just an interpretation not just an interpretation uh you know, uh you know, uh you know, and and and Yeah, the AI is getting really Yeah, the AI is getting really Yeah, the AI is getting really complicated because now they're trying complicated because now they're trying complicated because now they're trying to to to they're trying to extend the memory of they're trying to extend the memory of they're trying to extend the memory of these applications, right? I'm not going these applications, right? I'm not going these applications, right? I'm not going to call them models. It's literally the to call them models. It's literally the to call them models. It's literally the application to you know, with the KB application to you know, with the KB application to you know, with the KB cache so that there's consistency in how cache so that there's consistency in how cache so that there's consistency in how they respond. It's still they respond. It's still they respond. It's still not perfect. The whole reason for it is not perfect. The whole reason for it is not perfect. The whole reason for it is more more more for reducing for reducing for reducing um the number of um the number of um the number of times that you actually have to uniquely times that you actually have to uniquely times that you actually have to uniquely process a similar or the same process a similar or the same process a similar or the same um you know, prompt.

um you know, prompt. um you know, prompt. Right? Right? Right? The answers can still be wrong, The answers can still be wrong, The answers can still be wrong, inconsistent. Uh Yeah. inconsistent. Uh Yeah. inconsistent. Uh Yeah. You know, you know, seriously, this is like you know, seriously, this is like over-engineering, right? Yeah. Taking a over-engineering, right? Yeah. Taking a over-engineering, right? Yeah. Taking a determine probabilistic technology and determine probabilistic technology and determine probabilistic technology and then trying to make it deterministic then trying to make it deterministic then trying to make it deterministic or to have deterministic expectations or to have deterministic expectations or to have deterministic expectations of what that technology can do. And of what that technology can do. And of what that technology can do. And these are the two fundamental these are the two fundamental these are the two fundamental misconceptions misconceptions misconceptions that is creating a trillion-dollar mess. that is creating a trillion-dollar mess. that is creating a trillion-dollar mess. Right? Right? Right? >> Well. >> Well. >> Well. Well, yes. It was creating a mess on two Well, yes. It was creating a mess on two Well, yes. It was creating a mess on two parts. So one is, yes, it's creating a parts. So one is, yes, it's creating a parts. So one is, yes, it's creating a mess cuz people are creating systems mess cuz people are creating systems mess cuz people are creating systems that aren't actually working the way that aren't actually working the way that aren't actually working the way that they think it should working or the that they think it should working or the that they think it should working or the way it whatever. But then the part that way it whatever. But then the part that way it whatever. But then the part that offends me is like basically Offends offends me is like basically Offends offends me is like basically Offends you? these you? these you? these these companies have these companies have these companies have hoisted their hoisted their hoisted their their work on me. So now they're giving their work on me. So now they're giving their work on me. So now they're giving me a job.

me a job. me a job. So when I call you and I spend an hour So when I call you and I spend an hour So when I call you and I spend an hour on the phone, on the phone, on the phone, >> [clears throat] >> [clears throat] >> [clears throat] >> I'm I'm working for you now. >> I'm I'm working for you now. >> I'm I'm working for you now. Yeah. Okay. So I was like, "I'm not Yeah. Okay. So I was like, "I'm not Yeah. Okay. So I was like, "I'm not getting paid check. I don't get health getting paid check. I don't get health getting paid check. I don't get health care, nothing." care, nothing." care, nothing." Yeah. I mean, think about all the Yeah. I mean, think about all the Yeah. I mean, think about all the interactions where you have where you're interactions where you have where you're interactions where you have where you're where before you could get a person and where before you could get a person and where before you could get a person and you could get an answer and be done. you could get an answer and be done. you could get an answer and be done. Instead now you have to do all these Instead now you have to do all these Instead now you have to do all these gymnastics to try to hopefully, you gymnastics to try to hopefully, you gymnastics to try to hopefully, you know, it's like winning the jackpot. know, it's like winning the jackpot. know, it's like winning the jackpot. Hopefully you can get a person. You Hopefully you can get a person. You Hopefully you can get a person. You know, you have to find out the secret know, you have to find out the secret know, you have to find out the secret password to get like an actual human on password to get like an actual human on password to get like an actual human on the on the on the phone, but literally the on the on the phone, but literally the on the on the phone, but literally it's like I'm I'm taking your your it's like I'm I'm taking your your it's like I'm I'm taking your your you're you're you're putting putting putting Yeah. technology as a roadblock to me Yeah. technology as a roadblock to me Yeah. technology as a roadblock to me getting my problem solved, but then the getting my problem solved, but then the getting my problem solved, but then the work is on me now. Yeah. Not on you. work is on me now. Yeah. Not on you. work is on me now. Yeah. Not on you. Yeah. Well, that's the whole I mean, Yeah. Well, that's the whole I mean, Yeah. Well, that's the whole I mean, that's the age-old that's the age-old that's the age-old value proposition of CRM, right? That's value proposition of CRM, right? That's value proposition of CRM, right? That's like self-service. Right? like self-service. Right? like self-service. Right? >> [laughter] >> [laughter] >> [laughter] >> That was that whole thing. I mean, um >> That was that whole thing. I mean, um >> That was that whole thing. I mean, um and you know, it's always been and you know, it's always been and you know, it's always been it's been challenging. You know, even it's been challenging. You know, even it's been challenging. You know, even back then the whole idea was you could back then the whole idea was you could back then the whole idea was you could you could eliminate your call center you could eliminate your call center you could eliminate your call center because now because now because now you have self-service capabilities, you have self-service capabilities, you have self-service capabilities, right? Um that was what they were doing right? Um that was what they were doing right? Um that was what they were doing with um IVRs. Um the whole I mean, this with um IVRs. Um the whole I mean, this with um IVRs. Um the whole I mean, this stuff goes way back actually. But you stuff goes way back actually. But you stuff goes way back actually. But you know, the bottom line is it never really know, the bottom line is it never really know, the bottom line is it never really eliminated the call center because

eliminated the call center because eliminated the call center because you know, at the end of the day there is you know, at the end of the day there is you know, at the end of the day there is a there is a competitive a there is a competitive a there is a competitive uh driver uh driver uh driver to having great customer service to having great customer service to having great customer service operations. And part of that is let's operations. And part of that is let's operations. And part of that is let's say that say that say that >> [snorts] >> [snorts] >> [snorts] >> um you have a company that goes >> um you have a company that goes >> um you have a company that goes overboard with let's say CRM overboard with let's say CRM overboard with let's say CRM technologies or even this agentic stuff. technologies or even this agentic stuff. technologies or even this agentic stuff. Uh it reduces and it ultimately fails to Uh it reduces and it ultimately fails to Uh it reduces and it ultimately fails to deliver, right? Um deliver, right? Um deliver, right? Um >> [snorts] >> [snorts] >> [snorts] >> and doesn't address the underserved and >> and doesn't address the underserved and >> and doesn't address the underserved and unserved problems. unserved problems. unserved problems. That becomes an opportunity for a That becomes an opportunity for a That becomes an opportunity for a competitor, right? Cuz you're you're competitor, right? Cuz you're you're competitor, right? Cuz you're you're lowering you're lowering the floor for lowering you're lowering the floor for lowering you're lowering the floor for yourself yourself yourself and that basically creates a and that basically creates a and that basically creates a differentiation for any any of your differentiation for any any of your differentiation for any any of your competitors who are going to invest in competitors who are going to invest in competitors who are going to invest in let's say people let's say people let's say people to to to to to to >> Yeah. have more of a hybrid >> Yeah. have more of a hybrid >> Yeah. have more of a hybrid operations that blends people with operations that blends people with operations that blends people with technology, right? Right. technology technology, right? Right. technology technology, right? Right. technology enablement. And so these people who have enablement. And so these people who have enablement. And so these people who have and we've already seen it several times and we've already seen it several times and we've already seen it several times where people have gone off and said, where people have gone off and said, where people have gone off and said, "Oh, we're going to get rid of everyone "Oh, we're going to get rid of everyone "Oh, we're going to get rid of everyone on our call center." And next thing you on our call center." And next thing you on our call center." And next thing you know, they have to hire everyone back.

know, they have to hire everyone back. know, they have to hire everyone back. Right. Right, [snorts] right. Because the Right, [snorts] right. Because the person if a person picks up the phone person if a person picks up the phone person if a person picks up the phone and called you, they've already seen and called you, they've already seen and called you, they've already seen your FAQ. They've looked at your website your FAQ. They've looked at your website your FAQ. They've looked at your website already, right? So Yeah, yeah. already, right? So Yeah, yeah. already, right? So Yeah, yeah. regurgitating this again. regurgitating this again. regurgitating this again. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. They've already seen that. So if they They've already seen that. So if they They've already seen that. So if they call you, that means they have a special call you, that means they have a special call you, that means they have a special thing thing thing Yeah. that they want to talk to you Yeah. that they want to talk to you Yeah. that they want to talk to you about that you have not covered. about that you have not covered. about that you have not covered. Well, or it could be a simple thing Well, or it could be a simple thing Well, or it could be a simple thing where oh my god, I why am I waiting this where oh my god, I why am I waiting this where oh my god, I why am I waiting this long just to get a simple answer, right? long just to get a simple answer, right? long just to get a simple answer, right? And that's where And that's where And that's where you know, you know, you know, a simple answer to a simple question, a simple answer to a simple question, a simple answer to a simple question, basic question. basic question. basic question. And those are the kind of And those are the kind of And those are the kind of the um scenarios where you do want to the um scenarios where you do want to the um scenarios where you do want to figure out what is the best strategy for figure out what is the best strategy for figure out what is the best strategy for handling those types of um those types handling those types of um those types handling those types of um those types of interactions, right? Or um of interactions, right? Or um of interactions, right? Or um engagements. And I think that engagements. And I think that engagements. And I think that still takes a lot of discernment. And still takes a lot of discernment. And still takes a lot of discernment. And that's where AI can be very useful in that's where AI can be very useful in that's where AI can be very useful in that you can look at all of the that you can look at all of the that you can look at all of the different scenarios and you can use it different scenarios and you can use it different scenarios and you can use it as a tool to help create the rules for as a tool to help create the rules for as a tool to help create the rules for your software. And this idea that your software. And this idea that your software. And this idea that everything, all software is going to be everything, all software is going to be everything, all software is going to be run run run on GPUs using models is on GPUs using models is on GPUs using models is completely disconnected from completely disconnected from completely disconnected from reality.

reality. reality. It's bonkers. Bonkers. It's bonkers. Bonkers. It's bonkers. Bonkers. >> It's bonkers. >> It's bonkers. >> It's bonkers. You you actually want to use You you actually want to use You you actually want to use AI generative AI as little as possible. AI generative AI as little as possible. AI generative AI as little as possible. You want to use it as a tool to augment You want to use it as a tool to augment You want to use it as a tool to augment existing systems and existing ways of existing systems and existing ways of existing systems and existing ways of doing things because you know, the thing doing things because you know, the thing doing things because you know, the thing is is the AS/400 or what you know, like is is the AS/400 or what you know, like is is the AS/400 or what you know, like a Z series mainframe for transactional a Z series mainframe for transactional a Z series mainframe for transactional purposes is still going to be way faster purposes is still going to be way faster purposes is still going to be way faster than any than any than any um you know, a GB 300 MVL 72. um you know, a GB 300 MVL 72. um you know, a GB 300 MVL 72. Yeah, I'm sorry. Right, right. Because Yeah, I'm sorry. Right, right. Because Yeah, I'm sorry. Right, right. Because the cuz the thing is it is not thinking. the cuz the thing is it is not thinking. the cuz the thing is it is not thinking. It's just acting, right? It's just acting, right? It's just acting, right? Doing transactions as fast as possible. Doing transactions as fast as possible. Doing transactions as fast as possible. And um And um And um and people don't understand that there's and people don't understand that there's and people don't understand that there's different types of computing, okay? And different types of computing, okay? And different types of computing, okay? And what I mean by people is general, you what I mean by people is general, you what I mean by people is general, you know, audiences out there who've been know, audiences out there who've been know, audiences out there who've been sold this Kool-Aid that sold this Kool-Aid that sold this Kool-Aid that everything is going to move toward AI.

everything is going to move toward AI. everything is going to move toward AI. No, it's not. Uh in fact, we're seeing No, it's not. Uh in fact, we're seeing No, it's not. Uh in fact, we're seeing that that the complete opposite is that that the complete opposite is that that the complete opposite is happening. There's more concentration on happening. There's more concentration on happening. There's more concentration on traditional computing when you look at traditional computing when you look at traditional computing when you look at these um these um these um these agentic especially these agentic these agentic especially these agentic these agentic especially these agentic um um um architectures, architectures, architectures, right? And systems. right? And systems. right? And systems. Yeah. Um Yeah. Um Yeah. Um Yeah, there I don't know. I don't know. Yeah, there I don't know. I don't know. Yeah, there I don't know. I don't know. It's It's It's It's uh It's uh It's uh Like I heard like a big Like I heard like a big Like I heard like a big CEO of a big insurance company, I guess CEO of a big insurance company, I guess CEO of a big insurance company, I guess he had saw he had seen a demo of like he had saw he had seen a demo of like he had saw he had seen a demo of like agentic AI or something. agentic AI or something. agentic AI or something. Or gen AI or something. And he's like, Or gen AI or something. And he's like, Or gen AI or something. And he's like, "Oh yeah, we should just put all of our "Oh yeah, we should just put all of our "Oh yeah, we should just put all of our insurance and claims stuff in this insurance and claims stuff in this insurance and claims stuff in this thing." It's like, "Oh god, no." It's thing." It's like, "Oh god, no." It's thing." It's like, "Oh god, no." It's like, "Oh my goodness, this is such a like, "Oh my goodness, this is such a like, "Oh my goodness, this is such a bad idea. It's such a bad idea." But you bad idea. It's such a bad idea." But you bad idea. It's such a bad idea." But you see how a lot of bad ideas get pushed see how a lot of bad ideas get pushed see how a lot of bad ideas get pushed down and we're still not seeing the down and we're still not seeing the down and we're still not seeing the success rate of these projects go up at success rate of these projects go up at success rate of these projects go up at all.

all. all. No. No. No. Yeah. That's So it's like it's like, Yeah. That's So it's like it's like, Yeah. That's So it's like it's like, "When are you all going to get real and "When are you all going to get real and "When are you all going to get real and figure out what your real problem is and figure out what your real problem is and figure out what your real problem is and stop trying to stop trying to stop trying to throw mass everything into AI." It just throw mass everything into AI." It just throw mass everything into AI." It just doesn't work that way. Well, you know, doesn't work that way. Well, you know, doesn't work that way. Well, you know, like RSAC when I was there, one of the like RSAC when I was there, one of the like RSAC when I was there, one of the concepts that I've introduced is concepts that I've introduced is concepts that I've introduced is um um um you know, this continuum that we've gone you know, this continuum that we've gone you know, this continuum that we've gone um um um through or or the cybersecurity industry through or or the cybersecurity industry through or or the cybersecurity industry is going through is going through is going through has been going through in the past few has been going through in the past few has been going through in the past few years is years is years is you know, this initial elation about you know, this initial elation about you know, this initial elation about generative AI. generative AI. generative AI. Um so everyone trying to use it as a Um so everyone trying to use it as a Um so everyone trying to use it as a force multiplier for handling and force multiplier for handling and force multiplier for handling and supporting, you know, security ops, supporting, you know, security ops, supporting, you know, security ops, right? right? right? Uh whatever. A whole wide range of Uh whatever. A whole wide range of Uh whatever. A whole wide range of things, whether it's threat things, whether it's threat things, whether it's threat intelligence, blah blah blah. It's going intelligence, blah blah blah. It's going intelligence, blah blah blah. It's going to do magic. Toward to do magic. Toward to do magic. Toward Holy crap. Holy crap. Holy crap. This stuff is going to be super This stuff is going to be super This stuff is going to be super dangerous.

dangerous. dangerous. And then now elation moving toward we And then now elation moving toward we And then now elation moving toward we got to figure out how to isolate things. got to figure out how to isolate things. got to figure out how to isolate things. How do we do that, you know? How do we do that, you know? How do we do that, you know? Uh and this started off with LLMs. Now Uh and this started off with LLMs. Now Uh and this started off with LLMs. Now agentic AI is taking things to the next agentic AI is taking things to the next agentic AI is taking things to the next level in terms of level in terms of level in terms of threat potential and you know, threat potential and you know, threat potential and you know, blast radius in terms of impact. Deep blast radius in terms of impact. Deep blast radius in terms of impact. Deep and wide, right? And at machine speed. and wide, right? And at machine speed. and wide, right? And at machine speed. Yeah, right. Yeah, right. Yeah, right. Freaking machine speed. Freaking machine speed. Freaking machine speed. Then Then Then this year this year this year um I I'm making the prediction that um I I'm making the prediction that um I I'm making the prediction that everyone's going to be crapping their everyone's going to be crapping their everyone's going to be crapping their pants so hard that they're going to move pants so hard that they're going to move pants so hard that they're going to move toward compartmentalization. toward compartmentalization. toward compartmentalization. So how do we not So how do we not So how do we not consolidate all the information and consolidate all the information and consolidate all the information and train everything in a single model that train everything in a single model that train everything in a single model that can get compromised and next thing you can get compromised and next thing you can get compromised and next thing you know, uh a threat actor can come in and know, uh a threat actor can come in and know, uh a threat actor can come in and basically distill the whole thing basically distill the whole thing basically distill the whole thing and run off with it and then put it on and run off with it and then put it on and run off with it and then put it on the dark web.

the dark web. the dark web. You compartmentalize and then you secure You compartmentalize and then you secure You compartmentalize and then you secure and isolate so that you know, the blast and isolate so that you know, the blast and isolate so that you know, the blast radius is not as radius is not as radius is not as huge and you mitigate the damage that huge and you mitigate the damage that huge and you mitigate the damage that can be done. Right. So my thing always can be done. Right. So my thing always can be done. Right. So my thing always was so like example, like I always hear was so like example, like I always hear was so like example, like I always hear a lot of people they complain about a lot of people they complain about a lot of people they complain about third parties. third parties. third parties. Where oh my god, my third party got Where oh my god, my third party got Where oh my god, my third party got breached and that breached us or breached and that breached us or breached and that breached us or whatever. I'm like, but it should be a whatever. I'm like, but it should be a whatever. I'm like, but it should be a limit to how much damage that they could limit to how much damage that they could limit to how much damage that they could do even if they're in your system. Yeah. do even if they're in your system. Yeah. do even if they're in your system. Yeah. What are you thinking about that? And so What are you thinking about that? And so What are you thinking about that? And so to me this is the same thing but at a to me this is the same thing but at a to me this is the same thing but at a broader scale. It's like if there should broader scale. It's like if there should broader scale. It's like if there should be a limit to the damage that they could be a limit to the damage that they could be a limit to the damage that they could do. So it's not like, "Let's create all do. So it's not like, "Let's create all do. So it's not like, "Let's create all these capabilities and then figure out these capabilities and then figure out these capabilities and then figure out how to how to how to how to how to how to you know, create boundaries." Like you you know, create boundaries." Like you you know, create boundaries." Like you need boundaries first. Yeah. First need boundaries first. Yeah. First need boundaries first. Yeah. First before you start doing all this other before you start doing all this other before you start doing all this other type of stuff. It's like it doesn't work type of stuff. It's like it doesn't work type of stuff. It's like it doesn't work that way.

that way. that way. Yeah. Yeah. Uh Yeah. Yeah. Uh Yeah. Yeah. Uh So So So um this agentic stuff is going to um this agentic stuff is going to um this agentic stuff is going to definitely go definitely go definitely go um it's going to go sideways. Yeah. um it's going to go sideways. Yeah. um it's going to go sideways. Yeah. Well, and then I'm like Well, and then I'm like Well, and then I'm like how can you Someone had told me once how can you Someone had told me once how can you Someone had told me once they were like, "Yeah, it's like they were like, "Yeah, it's like they were like, "Yeah, it's like you know, the analogy they gave is like, you know, the analogy they gave is like, you know, the analogy they gave is like, you know, you have an intern that you you know, you have an intern that you you know, you have an intern that you give tasks to with these tools." I said, give tasks to with these tools." I said, give tasks to with these tools." I said, "But the intern has more network access "But the intern has more network access "But the intern has more network access than you do than you do than you do and it has less knowledge than you do and it has less knowledge than you do and it has less knowledge than you do and it can do a lot more than you can." and it can do a lot more than you can." and it can do a lot more than you can." Well, here here's the here's the Well, here here's the here's the Well, here here's the here's the problem. Number one, you expose your problem. Number one, you expose your problem. Number one, you expose your you're basically practicing FA and FO, you're basically practicing FA and FO, you're basically practicing FA and FO, right? You're you're around and right? You're you're around and right? You're you're around and you're going to find out. That's right. you're going to find out. That's right. you're going to find out. That's right. What you should do is you should be What you should do is you should be What you should do is you should be testing all this stuff, testing all this stuff, testing all this stuff, right? Before you right? Before you right? Before you FA and FO in production or FA and FO in production or FA and FO in production or on any of your own stuff on device, on any of your own stuff on device, on any of your own stuff on device, right?

right? right? Most people won't do that, especially Most people won't do that, especially Most people won't do that, especially consumers who have no idea. They just consumers who have no idea. They just consumers who have no idea. They just they go and they drop this thing into they go and they drop this thing into they go and they drop this thing into GitHub. Number one, you most people GitHub. Number one, you most people GitHub. Number one, you most people don't even think of security and don't even think of security and don't even think of security and privacy. That's afterthought. And you privacy. That's afterthought. And you privacy. That's afterthought. And you keep all these people going, "Well, you keep all these people going, "Well, you keep all these people going, "Well, you know, they know everything anyway." It's know, they know everything anyway." It's know, they know everything anyway." It's like, "No. You want to take that to the like, "No. You want to take that to the like, "No. You want to take that to the next level? next level? next level? Um Um Um go right ahead, right? And FA and FO. go right ahead, right? And FA and FO. go right ahead, right? And FA and FO. >> [laughter] >> Uh but here's the thing. You can't test >> Uh but here's the thing. You can't test this stuff. That's the problem. The cost this stuff. That's the problem. The cost this stuff. That's the problem. The cost of testing of testing of testing and the amount of effort testing, and the amount of effort testing, and the amount of effort testing, whether it's human-based or you're using whether it's human-based or you're using whether it's human-based or you're using tools including AI is cost-prohibitive tools including AI is cost-prohibitive tools including AI is cost-prohibitive to get to safe. to get to safe. to get to safe. Yeah. Yeah. Yeah. So no one's going to do it So no one's going to do it So no one's going to do it cuz cuz cuz it's going to be a freaking And then you it's going to be a freaking And then you it's going to be a freaking And then you know, the the security infrastructure know, the the security infrastructure know, the the security infrastructure tooling once deployed, tooling once deployed, tooling once deployed, that stuff doesn't exist.

that stuff doesn't exist. that stuff doesn't exist. You think that it exists? It doesn't It You think that it exists? It doesn't It You think that it exists? It doesn't It doesn't freaking exist. doesn't freaking exist. doesn't freaking exist. People are working on it, you know? People are working on it, you know? People are working on it, you know? Right. Right. Right. But I mean, But I mean, But I mean, wasn't wasn't wasn't giving giving a tool having access to giving giving a tool having access to giving giving a tool having access to your computer was a bad idea 30 years your computer was a bad idea 30 years your computer was a bad idea 30 years ago? ago? ago? Yeah, pretty much. Yeah, pretty much. Yeah, pretty much. >> And it's still a bad idea today. >> And it's still a bad idea today. >> And it's still a bad idea today. Yeah. Yeah. That hasn't changed. Yeah. Yeah. That hasn't changed. Yeah. Yeah. That hasn't changed. No, no, it hasn't. But you know, the No, no, it hasn't. But you know, the No, no, it hasn't. But you know, the thing is is we've taken this whole thing is is we've taken this whole thing is is we've taken this whole data breach thing. We've been we've data breach thing. We've been we've data breach thing. We've been we've become so desensitized to it not become so desensitized to it not become so desensitized to it not realizing that there is going to be a realizing that there is going to be a realizing that there is going to be a price to pay at some point. And the price to pay at some point. And the price to pay at some point. And the price is now because price is now because price is now because that dark web is hydrated with almost that dark web is hydrated with almost that dark web is hydrated with almost everything it needs to be to basically everything it needs to be to basically everything it needs to be to basically compromise compromise compromise everyone everyone everyone on the planet on the planet on the planet who is digitally engaged. So the only who is digitally engaged. So the only who is digitally engaged. So the only option now going back to option now going back to option now going back to compartmentalization compartmentalization compartmentalization and isolation, there's going to be and isolation, there's going to be and isolation, there's going to be at some point a need to isolate at some point a need to isolate at some point a need to isolate yourself. In other words, Battlestar yourself. In other words, Battlestar yourself. In other words, Battlestar Galactica and then compartmentalize. So Galactica and then compartmentalize. So Galactica and then compartmentalize. So once the Cylons infiltrate the once the Cylons infiltrate the once the Cylons infiltrate the Battlestar Galactica, you want to be Battlestar Galactica, you want to be Battlestar Galactica, you want to be able to contain their spread within the able to contain their spread within the able to contain their spread within the ship so that ship so that ship so that you can reach Earth at some point. You you can reach Earth at some point. You you can reach Earth at some point. You know what? But you know, a lot of this know what? But you know, a lot of this know what? But you know, a lot of this science fiction is turning into science science fiction is turning into science science fiction is turning into science fact, isn't it? Well, they were they

fact, isn't it? Well, they were they fact, isn't it? Well, they were they weren't dumb. They weren't dumb. They weren't dumb. They people I mean, you know, these writers people I mean, you know, these writers people I mean, you know, these writers that sci-fi writers, they that sci-fi writers, they that sci-fi writers, they futurists, yeah. They they kind of got futurists, yeah. They they kind of got futurists, yeah. They they kind of got it, you know? it, you know? it, you know? >> Yeah, yeah, they nailed it on a lot of >> Yeah, yeah, they nailed it on a lot of >> Yeah, yeah, they nailed it on a lot of points. They did. And you know, They did. And you know, uh I don't know what they must have uh I don't know what they must have uh I don't know what they must have smoked a lot of weed or something. I smoked a lot of weed or something. I smoked a lot of weed or something. I don't know. don't know. don't know. But it's pretty amazing. But it's pretty amazing. But it's pretty amazing. >> [laughter] >> [laughter] >> [laughter] >> You know, whether it's like Terminator >> You know, whether it's like Terminator >> You know, whether it's like Terminator or Blade Runner or or Blade Runner or or Blade Runner or you know, you know, you know, um any of these. I mean, if Bob was on, um any of these. I mean, if Bob was on, um any of these. I mean, if Bob was on, he would be listing off like a whole he would be listing off like a whole he would be listing off like a whole bunch of stuff. bunch of stuff. bunch of stuff. Matrix. Well, actually the Matrix. Well, actually the Matrix. Well, actually the um it's funny cuz like Minority Report, um it's funny cuz like Minority Report, um it's funny cuz like Minority Report, they said that Steven Spielberg he had they said that Steven Spielberg he had they said that Steven Spielberg he had talked with a lot of futurists when he talked with a lot of futurists when he talked with a lot of futurists when he was doing film. And he was like, "So was doing film. And he was like, "So was doing film. And he was like, "So what's happening? What's going to happen what's happening? What's going to happen what's happening? What's going to happen next 50 year or whatever?" And that's next 50 year or whatever?" And that's next 50 year or whatever?" And that's why I think that movie holds up so well why I think that movie holds up so well why I think that movie holds up so well cuz a lot of the stuff that was in there cuz a lot of the stuff that was in there cuz a lot of the stuff that was in there Yeah. Yeah. Yeah. Yeah. And you know what? If you really Yeah. And you know what? If you really Yeah. And you know what? If you really think about it, that think about it, that think about it, that they highlighted the privacy issue very they highlighted the privacy issue very they highlighted the privacy issue very early cuz when Tom Cruise early cuz when Tom Cruise early cuz when Tom Cruise character, I think John whatever, character, I think John whatever, character, I think John whatever, um he um he um he he was trying to he was trying to he was trying to go Battlestar Galactica.

go Battlestar Galactica. go Battlestar Galactica. He wanted to get off grid, right? He wanted to get off grid, right? He wanted to get off grid, right? >> [clears throat] >> [clears throat] >> [clears throat] >> How do you do that when you're getting >> How do you do that when you're getting >> How do you do that when you're getting rentally scanned? rentally scanned? rentally scanned? So you have to get new eyeballs, So you have to get new eyeballs, So you have to get new eyeballs, right? He had to actually get eyeball right? He had to actually get eyeball right? He had to actually get eyeball transplants. transplants. transplants. >> Yeah, that's so inconvenient. >> Yeah, that's so inconvenient. >> Yeah, that's so inconvenient. >> [laughter] >> [laughter] >> [laughter] >> But we're about beyond that. And then >> But we're about beyond that. And then >> But we're about beyond that. And then Gattaca as well, right? Gattaca. Yeah, Gattaca as well, right? Gattaca. Yeah, Gattaca as well, right? Gattaca. Yeah, love Gattaca. with love Gattaca. with love Gattaca. with Ethan Hawke and Uma Thurman. That was a Ethan Hawke and Uma Thurman. That was a Ethan Hawke and Uma Thurman. That was a great movie. That was a great movie. great movie. That was a great movie. great movie. That was a great movie. Well, you know, and there was a point so Well, you know, and there was a point so Well, you know, and there was a point so like the Jude Law character in the like the Jude Law character in the like the Jude Law character in the movie, he is in a wheelchair movie, he is in a wheelchair movie, he is in a wheelchair but he has I guess his DNA and his but he has I guess his DNA and his but he has I guess his DNA and his asthma has all the good stuff, the good asthma has all the good stuff, the good asthma has all the good stuff, the good genes or whatever. But that doesn't for genes or whatever. But that doesn't for genes or whatever. But that doesn't for him it didn't mean that he could achieve him it didn't mean that he could achieve him it didn't mean that he could achieve at that level, right? So it was very at that level, right? So it was very at that level, right? So it was very interesting. It was kind of like a caste interesting. It was kind of like a caste interesting. It was kind of like a caste Yeah. that had been created. And so I Yeah. that had been created. And so I Yeah. that had been created. And so I think there are definitely parallels think there are definitely parallels think there are definitely parallels there in the way that people are going there in the way that people are going there in the way that people are going around AI, for sure. Yeah. And he around AI, for sure. Yeah. And he around AI, for sure. Yeah. And he cremated himself, right? Toward the end.

cremated himself, right? Toward the end. cremated himself, right? Toward the end. Uh that was like uh I was like, "What Uh that was like uh I was like, "What Uh that was like uh I was like, "What are you doing?" are you doing?" are you doing?" Uh Uh Uh Yeah. Yeah. Yeah. Uh well, you know, um, these sci-fi Uh well, you know, um, these sci-fi Uh well, you know, um, these sci-fi writers, writers, writers, um, these futurists, um, these futurists, um, these futurists, you know, you know, you know, sometimes they get it or they've gotten sometimes they get it or they've gotten sometimes they get it or they've gotten a lot of stuff. a lot of stuff. a lot of stuff. But then, you know, it's it it they're But then, you know, it's it it they're But then, you know, it's it it they're usually getting it right because usually getting it right because usually getting it right because uh, they're not just looking at uh, they're not just looking at uh, they're not just looking at technology. They're using they're technology. They're using they're technology. They're using they're looking at there's societal factors that looking at there's societal factors that looking at there's societal factors that they're looking at, um, political, they're looking at, um, political, they're looking at, um, political, geopolitical even, you know, how are how geopolitical even, you know, how are how geopolitical even, you know, how are how will will will >> [snorts] >> [snorts] >> [snorts] >> um, what what will governments look >> um, what what will governments look >> um, what what will governments look like? How will societies organize like? How will societies organize like? How will societies organize themselves as they're being impacted by themselves as they're being impacted by themselves as they're being impacted by technologies. technologies. technologies. >> Yeah. Yeah. So, I thought about the >> Yeah. Yeah. So, I thought about the >> Yeah. Yeah. So, I thought about the movie movie movie I'm I'm not sure if I told you about I'm I'm not sure if I told you about I'm I'm not sure if I told you about this, about 2000, maybe someone else I this, about 2000, maybe someone else I this, about 2000, maybe someone else I told about this, 2001 Space Odyssey, told about this, 2001 Space Odyssey, told about this, 2001 Space Odyssey, Uh-huh. Kubrick, Yeah, yeah.

Uh-huh. Kubrick, Yeah, yeah. Uh-huh. Kubrick, Yeah, yeah. the scene I think that is it reminds me the scene I think that is it reminds me the scene I think that is it reminds me of what's happening right now, which is of what's happening right now, which is of what's happening right now, which is when the astronaut he had decided they when the astronaut he had decided they when the astronaut he had decided they wanted to shut Hal down and he went into wanted to shut Hal down and he went into wanted to shut Hal down and he went into a different room and he was talking a different room and he was talking a different room and he was talking about it, but Hal was reading his lips. about it, but Hal was reading his lips. about it, but Hal was reading his lips. Yeah. Yeah. Yeah. >> [laughter] >> [laughter] >> [laughter] >> So, okay, you thought you were being >> So, okay, you thought you were being >> So, okay, you thought you were being smart because you assumed Uh. Right. So, smart because you assumed Uh. Right. So, smart because you assumed Uh. Right. So, this is another human thing, right? Let this is another human thing, right? Let this is another human thing, right? Let me go in the other room so he's not me go in the other room so he's not me go in the other room so he's not hearing me, right? So, but he's Yeah. hearing me, right? So, but he's Yeah. hearing me, right? So, but he's Yeah. He's like, we don't get we don't He's like, we don't get we don't He's like, we don't get we don't understand what we're dealing with understand what we're dealing with understand what we're dealing with really No, and and you know, the the really No, and and you know, the the really No, and and you know, the the thing is is because we become so over thing is is because we become so over thing is is because we become so over reliant and over trusting of the reliant and over trusting of the reliant and over trusting of the technology, it's really going to cause a technology, it's really going to cause a technology, it's really going to cause a problem for a lot of folks because, you problem for a lot of folks because, you problem for a lot of folks because, you know, when I look at some of the know, when I look at some of the know, when I look at some of the transcripts that are produced by these transcripts that are produced by these transcripts that are produced by these AI tools and and, you know, they're AI tools and and, you know, they're AI tools and and, you know, they're using the most advanced models out there using the most advanced models out there using the most advanced models out there at least reasonably um, you know, at least reasonably um, you know, at least reasonably um, you know, capable models uh, capable models uh, capable models uh, out there today.

out there today. out there today. There's a a lot of errors. There's a a lot of errors. There's a a lot of errors. Um, in fact, you know, these transcripts Um, in fact, you know, these transcripts Um, in fact, you know, these transcripts if these are used to train future models if these are used to train future models if these are used to train future models or referenced or referenced or referenced um, um, um, that or referenced in uh, any kind of that or referenced in uh, any kind of that or referenced in uh, any kind of uh, query, uh, query, uh, query, um, um, um, that and fed into the context of any uh, that and fed into the context of any uh, that and fed into the context of any uh, you know, request, you know, request, you know, request, you know, they could be a really you know, they could be a really you know, they could be a really problematic. I've seen this thing, you problematic. I've seen this thing, you problematic. I've seen this thing, you know, just even on YouTube, put like, know, just even on YouTube, put like, know, just even on YouTube, put like, you know, cuss words in people's, you know, cuss words in people's, you know, cuss words in people's, you know, you know, you know, uh, transcript uh, transcript uh, transcript when that's not what they they didn't when that's not what they they didn't when that's not what they they didn't use a cuss word. Right. use a cuss word. Right. use a cuss word. Right. >> what I'm saying? It's like, okay, >> what I'm saying? It's like, okay, >> what I'm saying? It's like, okay, now at some point now at some point now at some point um, that person will be victimized by um, that person will be victimized by um, that person will be victimized by that error. Right. that error. Right. that error. Right. >> Right. Exactly. Because people are >> Right. Exactly. Because people are >> Right. Exactly. Because people are trusting AI. trusting AI. trusting AI. Totally. Totally. Totally. >> And then so the AI will make a judgment >> And then so the AI will make a judgment >> And then so the AI will make a judgment based on bad data about what a person based on bad data about what a person based on bad data about what a person has said Yeah.

has said Yeah. has said Yeah. >> or it or incorrectly has been accounted >> or it or incorrectly has been accounted >> or it or incorrectly has been accounted as having said. And think about that as having said. And think about that as having said. And think about that victimization, victimization, victimization, you know? you know? you know? >> Right. Totally. Yeah. I have a And this >> Right. Totally. Yeah. I have a And this >> Right. Totally. Yeah. I have a And this is happening at mass scale. It's not is happening at mass scale. It's not is happening at mass scale. It's not like, oh, maybe it's happening. No, I like, oh, maybe it's happening. No, I like, oh, maybe it's happening. No, I can show you where it's happening, where can show you where it's happening, where can show you where it's happening, where like uh, like uh, like uh, they had um, they had um, they had um, they had somebody saying that you know, they had somebody saying that you know, they had somebody saying that you know, the transcript basically, the transcript basically, the transcript basically, you know, um, had an actor you know, um, had an actor you know, um, had an actor uh, uh, uh, uh, uh, uh, saying the N-word. saying the N-word. saying the N-word. Yeah. Yeah. Yeah. >> And you know what you you know what >> And you know what you you know what >> And you know what you you know what you know what what he was saying? What? you know what what he was saying? What? you know what what he was saying? What? Arnold Schwarzenegger. Yeah, right. I Arnold Schwarzenegger. Yeah, right. I Arnold Schwarzenegger. Yeah, right. I remember that. Arnold Schwarzenegger. remember that. Arnold Schwarzenegger. remember that. Arnold Schwarzenegger. Exactly. Exactly. Exactly. >> [laughter] >> [laughter] >> [laughter] >> Instead it put the N-word in there and >> Instead it put the N-word in there and >> Instead it put the N-word in there and I'm like, oh my god. Right. Right. I'm like, oh my god. Right. Right. I'm like, oh my god. Right. Right. Exactly. And you know, so did you know, Exactly. And you know, so did you know, Exactly. And you know, so did you know, did this actor ever use the N-word? And did this actor ever use the N-word? And did this actor ever use the N-word? And and then the AI's going to say, yeah, it and then the AI's going to say, yeah, it and then the AI's going to say, yeah, it did. Right.

did. Right. did. Right. >> And he did. >> And he did. >> And he did. On on the Jimmy Kimmel show or whatever On on the Jimmy Kimmel show or whatever On on the Jimmy Kimmel show or whatever and here it is. And then you'll see the and here it is. And then you'll see the and here it is. And then you'll see the transcript and somebody will go, oh my transcript and somebody will go, oh my transcript and somebody will go, oh my god, he used the N-word. Right. god, he used the N-word. Right. god, he used the N-word. Right. Totally. And the only way you can prove Totally. And the only way you can prove Totally. And the only way you can prove that and then the damage will be done that and then the damage will be done that and then the damage will be done and the only way that you can prove it and the only way that you can prove it and the only way that you can prove it is somebody goes through the effort of is somebody goes through the effort of is somebody goes through the effort of watching the entire episode or that watching the entire episode or that watching the entire episode or that episode or that clip and realizes, oh, episode or that clip and realizes, oh, episode or that clip and realizes, oh, he said Arnold Schwarzenegger. Where did he said Arnold Schwarzenegger. Where did he said Arnold Schwarzenegger. Where did Where did the N-word come from? Right? Where did the N-word come from? Right? Where did the N-word come from? Right? >> Exactly. Right. And the only reason why >> Exactly. Right. And the only reason why >> Exactly. Right. And the only reason why we know this, like so this could happen we know this, like so this could happen we know this, like so this could happen millions and billions of times with millions and billions of times with millions and billions of times with people who don't get people who don't get people who don't get It's It's It's happening. Yeah, totally. happening. Yeah, totally. happening. Yeah, totally. >> Or it's not, oh, well, it happened or >> Or it's not, oh, well, it happened or >> Or it's not, oh, well, it happened or it's not happening at scale. Oh, it's it's not happening at scale. Oh, it's it's not happening at scale. Oh, it's happening at massive scale. Totally. happening at massive scale. Totally. happening at massive scale. Totally. Totally. Right. Like I have a a note Totally. Right. Like I have a a note Totally. Right. Like I have a a note taker that I use for meetings and other taker that I use for meetings and other taker that I use for meetings and other recordings and and they have this thing recordings and and they have this thing recordings and and they have this thing now where they try to score you. Like, now where they try to score you. Like, now where they try to score you. Like, okay, you have high engagement, high, okay, you have high engagement, high, okay, you have high engagement, high, you know, they're trying to score you you know, they're trying to score you you know, they're trying to score you based on like the the conversation. And based on like the the conversation. And based on like the the conversation. And anyway, this one I mostly ignore it, but anyway, this one I mostly ignore it, but anyway, this one I mostly ignore it, but one time this one conversation I had and one time this one conversation I had and one time this one conversation I had and they said I had low something. Something they said I had low something. Something they said I had low something. Something was low. What the hell are you talking was low. What the hell are you talking was low. What the hell are you talking about? And so, I looked at and it said about? And so, I looked at and it said about? And so, I looked at and it said and I was like, I think it said low and I was like, I think it said low and I was like, I think it said low engagement or something. And I was like, engagement or something. And I was like, engagement or something. And I was like, Oh my god. What the hell are you talking Oh my god. What the hell are you talking Oh my god. What the hell are you talking about? And then I looked and it finally about? And then I looked and it finally about? And then I looked and it finally said what it meant. They said the other said what it meant. They said the other said what it meant. They said the other person talked more than I did.

person talked more than I did. person talked more than I did. >> [laughter] >> [laughter] >> [laughter] >> I was it's an interview. >> I was it's an interview. >> I was it's an interview. Yeah, oh my god. So, imagine. Yeah, oh my god. So, imagine. Yeah, oh my god. So, imagine. >> than me. Right? And I'm thinking like, >> than me. Right? And I'm thinking like, >> than me. Right? And I'm thinking like, what if like what if some some company what if like what if some some company what if like what if some some company is using this to rate their employees? is using this to rate their employees? is using this to rate their employees? >> god. I know. Then >> god. I know. Then >> god. I know. Then You have low engagement cuz this tool You have low engagement cuz this tool You have low engagement cuz this tool said. It's like, I'm interviewing said. It's like, I'm interviewing said. It's like, I'm interviewing someone. They talked more than I do. someone. They talked more than I do. someone. They talked more than I do. >> [laughter] >> [laughter] >> [laughter] >> Can you imagine what's going to happen >> Can you imagine what's going to happen >> Can you imagine what's going to happen in meetings now? You're going to have in meetings now? You're going to have in meetings now? You're going to have all these people just talking you all these people just talking you all these people just talking you know, for the sake of having engagement, know, for the sake of having engagement, know, for the sake of having engagement, you know? They're like, all right, hey, you know? They're like, all right, hey, you know? They're like, all right, hey, you know, I have no idea what I'm you know, I have no idea what I'm you know, I have no idea what I'm talking about. I'm going to say talking about. I'm going to say talking about. I'm going to say something and then everyone has to waste something and then everyone has to waste something and then everyone has to waste time listening to somebody just trying time listening to somebody just trying time listening to somebody just trying to make their quota or, you know, trying to make their quota or, you know, trying to make their quota or, you know, trying to up their their score. Right. to up their their score. Right. to up their their score. Right. I'm so bad. I'm so bad. I'm so bad. >> I have a comment. Uh, I'd like to know >> I have a comment. Uh, I'd like to know >> I have a comment. Uh, I'd like to know what we're having for lunch and uh, what we're having for lunch and uh, what we're having for lunch and uh, yeah, yesterday's lunch kind of sucked. yeah, yesterday's lunch kind of sucked. yeah, yesterday's lunch kind of sucked. Uh, but it would be really great if we Uh, but it would be really great if we Uh, but it would be really great if we had like a FH or like a an agent that we had like a FH or like a an agent that we had like a FH or like a an agent that we built that could take our preferences built that could take our preferences built that could take our preferences and our, you know, on a weekly base, and our, you know, on a weekly base, and our, you know, on a weekly base, blah, blah, blah. You know what I'm blah, blah, blah. You know what I'm blah, blah, blah. You know what I'm saying? It's it it just get like saying? It's it it just get like saying? It's it it just get like ridiculous.

ridiculous. ridiculous. Totally. Right. And all all those things Totally. Right. And all all those things Totally. Right. And all all those things are very like I have a really searched are very like I have a really searched are very like I have a really searched for this, right? Cuz like it didn't for this, right? Cuz like it didn't for this, right? Cuz like it didn't really explain it and I had to look at really explain it and I had to look at really explain it and I had to look at it. So, no one's going to have time to it. So, no one's going to have time to it. So, no one's going to have time to go look deep down to find out, you know, go look deep down to find out, you know, go look deep down to find out, you know, where this started. No, no. I mean, but where this started. No, no. I mean, but where this started. No, no. I mean, but and it goes back to the cybersecurity and it goes back to the cybersecurity and it goes back to the cybersecurity problem. It's asymmetrical. When you get problem. It's asymmetrical. When you get problem. It's asymmetrical. When you get harmed by harmed by harmed by AI generated misinformation, right? AI generated misinformation, right? AI generated misinformation, right? About yourself, About yourself, About yourself, the damage happens and it costs you it the damage happens and it costs you it the damage happens and it costs you it it it costs nothing for that to happen, it it costs nothing for that to happen, it it costs nothing for that to happen, >> Totally. right? Yeah. But it will impact >> Totally. right? Yeah. But it will impact >> Totally. right? Yeah. But it will impact your life, it will impact it will cost your life, it will impact it will cost your life, it will impact it will cost you you you um, um, um, a ridiculous amount to remediate that a ridiculous amount to remediate that a ridiculous amount to remediate that situation for yourself, you know? And situation for yourself, you know? And situation for yourself, you know? And they don't give a you know? The AI they don't give a you know? The AI they don't give a you know? The AI doesn't give a It just goes, well, doesn't give a It just goes, well, doesn't give a It just goes, well, you know, you know, you know, I didn't know, Dave. I didn't know, Dave. I didn't know, Dave. Right? Right? Right? >> that I emptied out your bank account. >> that I emptied out your bank account. >> that I emptied out your bank account. Oops. Oh, yeah. You know, I'm you didn't Oops. Oh, yeah. You know, I'm you didn't Oops. Oh, yeah. You know, I'm you didn't tell me that. I don't know how you just tell me that. I don't know how you just tell me that. I don't know how you just effed it and effed it.

effed it and effed it. effed it and effed it. You know? You know? You know? >> [laughter] >> [laughter] >> [laughter] >> Deal with it. I sold your house >> Deal with it. I sold your house >> Deal with it. I sold your house so you can go on that that tour around so you can go on that that tour around so you can go on that that tour around the world that you wanted to go on go the world that you wanted to go on go the world that you wanted to go on go through. through. through. >> [laughter] >> But uh, >> But uh, I don't know I don't know. I mean, you I don't know I don't know. I mean, you I don't know I don't know. I mean, you know, it's like we we sound like um, know, it's like we we sound like um, know, it's like we we sound like um, Luddites, but it's not. It's we're we're Luddites, but it's not. It's we're we're Luddites, but it's not. It's we're we're talking about safe and you know what, talking about safe and you know what, talking about safe and you know what, it's not like things have really it's not like things have really it's not like things have really gone the way that the people who have gone the way that the people who have gone the way that the people who have hyped the technology have, hyped the technology have, hyped the technology have, you know, so the reason why things you know, so the reason why things you know, so the reason why things aren't going as quickly or there's aren't going as quickly or there's aren't going as quickly or there's adoption issues or safety issues is adoption issues or safety issues is adoption issues or safety issues is because of the things that we keep because of the things that we keep because of the things that we keep bringing up. It's like, look, you got bringing up. It's like, look, you got bringing up. It's like, look, you got you have to address these things before you have to address these things before you have to address these things before you get to safe and uh, you know, uh, you get to safe and uh, you know, uh, you get to safe and uh, you know, uh, and to, you know, AI use uh, in a way and to, you know, AI use uh, in a way and to, you know, AI use uh, in a way that is that is that is uh, constructive and positive and in, uh, constructive and positive and in, uh, constructive and positive and in, you know, life enhancing. you know, life enhancing. you know, life enhancing. Um, I think that right. So, I think Um, I think that right. So, I think Um, I think that right. So, I think adoption on the long-term scale really adoption on the long-term scale really adoption on the long-term scale really does does does depend on trust. Yeah, absolutely.

depend on trust. Yeah, absolutely. depend on trust. Yeah, absolutely. >> So, the trust is not being built the way >> So, the trust is not being built the way >> So, the trust is not being built the way that it should be. that it should be. that it should be. And so, that's the problem. Yeah. And And so, that's the problem. Yeah. And And so, that's the problem. Yeah. And then it goes back to what we were saying then it goes back to what we were saying then it goes back to what we were saying before about expectations, right? Those before about expectations, right? Those before about expectations, right? Those two points. There's expectations and two points. There's expectations and two points. There's expectations and then there's um, what um, the technology then there's um, what um, the technology then there's um, what um, the technology actually can do, right? And um, when actually can do, right? And um, when actually can do, right? And um, when there's a disconnect, there's a disconnect, there's a disconnect, you can never really have you can never really have you can never really have trust. Right. Um, and then everything trust. Right. Um, and then everything trust. Right. Um, and then everything becomes untrustworthy. And that's going becomes untrustworthy. And that's going becomes untrustworthy. And that's going to be the biggest challenge going to be the biggest challenge going to be the biggest challenge going forward. We already see this. This is forward. We already see this. This is forward. We already see this. This is not something that, oh, you know, not something that, oh, you know, not something that, oh, you know, this this this that won't happen. No, it's happening. that won't happen. No, it's happening. that won't happen. No, it's happening. Totally. Go and look at Totally. Go and look at Totally. Go and look at some what's happening with your banks. some what's happening with your banks. some what's happening with your banks. Oh my god. Oh my god. Oh my god. What they what they're doing is they are What they what they're doing is they are What they what they're doing is they are basically their pants. basically their pants. basically their pants. Uh-oh. A lot.

Uh-oh. A lot. Uh-oh. A lot. Well, and they should. Well, and they should. Well, and they should. >> [laughter] >> [laughter] >> [laughter] [gasps] [gasps] [gasps] >> They should. Banks, whenever a new >> They should. Banks, whenever a new >> They should. Banks, whenever a new vulnerability comes out, like the the vulnerability comes out, like the the vulnerability comes out, like the the people people people who are the evil doers, Yeah. who are the evil doers, Yeah. who are the evil doers, Yeah. >> the first thing they do go for is a >> the first thing they do go for is a >> the first thing they do go for is a bank, or they go for someone that they bank, or they go for someone that they bank, or they go for someone that they can get their bank account. Yes. Yeah. can get their bank account. Yes. Yeah. can get their bank account. Yes. Yeah. And then, you know, what do these people And then, you know, what do these people And then, you know, what do these people still do? still do? still do? They're like, "What can you You know, They're like, "What can you You know, They're like, "What can you You know, what's the What's your What's the name what's the What's your What's the name what's the What's your What's the name of [clears throat] your pet?" of [clears throat] your pet?" of [clears throat] your pet?" >> [laughter] >> [laughter] >> [laughter] >> Right. What's your favorite color? >> Right. What's your favorite color? >> Right. What's your favorite color? It's like, "Okay, what's your phone It's like, "Okay, what's your phone It's like, "Okay, what's your phone number?" And then they authenticate you number?" And then they authenticate you number?" And then they authenticate you off of three things that are already on off of three things that are already on off of three things that are already on the dark web that anyone can the dark web that anyone can the dark web that anyone can find. It's like public information. It's find. It's like public information. It's find. It's like public information. It's like, "Okay, what?" Totally. Right. like, "Okay, what?" Totally. Right. like, "Okay, what?" Totally. Right. Their palms are moist, too. So, it's Their palms are moist, too. So, it's Their palms are moist, too. So, it's like, "Oh, What's your date of birth?" like, "Oh, What's your date of birth?" like, "Oh, What's your date of birth?" Like, "What?" Like, "What?" Like, "What?" >> [laughter] >> [laughter] >> [laughter] >> Come on. >> Come on. >> Come on. You know, um there's a lot of You know, um there's a lot of You know, um there's a lot of institutions that still do that. And so, institutions that still do that. And so, institutions that still do that. And so, you know, and then think about it. Now, you know, and then think about it. Now, you know, and then think about it. Now, um um um with Claude with Claude with Claude Claude What is it? Mythos. Yeah.

Claude What is it? Mythos. Yeah. Claude What is it? Mythos. Yeah. Anthropic's Mythos model. Now, they're Anthropic's Mythos model. Now, they're Anthropic's Mythos model. Now, they're everyone's freaking out about that everyone's freaking out about that everyone's freaking out about that thing. It's like, "No, don't You should thing. It's like, "No, don't You should thing. It's like, "No, don't You should have freaked out a long time ago. That have freaked out a long time ago. That have freaked out a long time ago. That It just makes things better. It just makes things better. It just makes things better. But you should always already have the But you should always already have the But you should always already have the concern concern concern that these tools can be used for that these tools can be used for that these tools can be used for vulnerability discovery. vulnerability discovery. vulnerability discovery. And that And that And that whatever you thought whatever you thought whatever you thought would be useful in enhancing your would be useful in enhancing your would be useful in enhancing your security posture, or at least security posture, or at least security posture, or at least giving you visibility to what you needed giving you visibility to what you needed giving you visibility to what you needed to work on, to work on, to work on, threat actors are going to use the same threat actors are going to use the same threat actors are going to use the same thing. Totally. It's cheap for them to thing. Totally. It's cheap for them to thing. Totally. It's cheap for them to exploit existing exploit existing exploit existing vulnerabilities. Totally. vulnerabilities. Totally. vulnerabilities. Totally. Right. It's true. It's true. You're Right. It's true. It's true. You're Right. It's true. It's true. You're right. right. right. It's true. It's like It's all funny. So, It's true. It's like It's all funny. So, It's true. It's like It's all funny. So, when all this stuff is happening, I'm when all this stuff is happening, I'm when all this stuff is happening, I'm like, "So, what exactly are people like, "So, what exactly are people like, "So, what exactly are people confused about? confused about? confused about? What are you confused about? It's like What are you confused about? It's like What are you confused about? It's like you create a capability that's so you create a capability that's so you create a capability that's so out there, out there, out there, but you don't have a way to contain it.

but you don't have a way to contain it. but you don't have a way to contain it. Or it's doing things Where is Bill? that Or it's doing things Where is Bill? that Or it's doing things Where is Bill? that you didn't Bill needs to be here. Bill you didn't Bill needs to be here. Bill you didn't Bill needs to be here. Bill needs to be here with his hat and his needs to be here with his hat and his needs to be here with his hat and his shirt. That's right. F A N F O epidemic. shirt. That's right. F A N F O epidemic. shirt. That's right. F A N F O epidemic. That's what we got to call it. That's what we got to call it. That's what we got to call it. Right? Right? Right? >> That's right. That's right. That's the >> That's right. That's right. That's the >> That's right. That's right. That's the This is really the gap of the ugly. This This is really the gap of the ugly. This This is really the gap of the ugly. This the valley here. the valley here. the valley here. >> Oh, yeah. Yeah. No, this is just like >> Oh, yeah. Yeah. No, this is just like >> Oh, yeah. Yeah. No, this is just like freaking freaking freaking nasty. nasty. nasty. >> [laughter] >> [laughter] >> [laughter] >> Oh, it is. >> Oh, it is. >> Oh, it is. Oh, my god. That's how you We need to go Oh, my god. That's how you We need to go Oh, my god. That's how you We need to go back and watch sci-fi movies cuz they back and watch sci-fi movies cuz they back and watch sci-fi movies cuz they were trying to tell us a message were trying to tell us a message were trying to tell us a message >> [laughter] >> [laughter] >> [laughter] >> that we didn't get. We didn't get Oh, >> that we didn't get. We didn't get Oh, >> that we didn't get. We didn't get Oh, well, you know, we're we're we're just well, you know, we're we're we're just well, you know, we're we're we're just not going to You know, here's here's the not going to You know, here's here's the not going to You know, here's here's the thing. I just encourage a lot of the thing. I just encourage a lot of the thing. I just encourage a lot of the vendors to focus on um what the real vendors to focus on um what the real vendors to focus on um what the real demand is going to be, which is how do demand is going to be, which is how do demand is going to be, which is how do you protect you protect you protect yourselves from this stuff. Cuz yourselves from this stuff. Cuz yourselves from this stuff. Cuz enterprises are going to really enterprises are going to really enterprises are going to really struggle, especially financial and any struggle, especially financial and any struggle, especially financial and any kind of kind of kind of {quote} {unquote} trust-based {quote} {unquote} trust-based {quote} {unquote} trust-based institution, whether it's government institution, whether it's government institution, whether it's government [clears throat] or banking or Telco.

[clears throat] or banking or Telco. [clears throat] or banking or Telco. Mhm. They're going to have to invest a Mhm. They're going to have to invest a Mhm. They're going to have to invest a lot in this stuff, the protection, lot in this stuff, the protection, lot in this stuff, the protection, right? And they have to really tune into right? And they have to really tune into right? And they have to really tune into how bad stuff is going to get. And you how bad stuff is going to get. And you how bad stuff is going to get. And you know, yeah, Mythos, know, yeah, Mythos, know, yeah, Mythos, you can be afraid of it, you can be afraid of it, you can be afraid of it, um but you should already be afraid. um but you should already be afraid. um but you should already be afraid. Right. Period. If you're If you're not Right. Period. If you're If you're not Right. Period. If you're If you're not afraid, you're behind the afraid, you're behind the afraid, you're behind the ball here. You know, that you're like ball here. You know, that you're like ball here. You know, that you're like behind the curve. I mean, you behind the curve. I mean, you behind the curve. I mean, you be your pants right now. And be your pants right now. And be your pants right now. And then talking to your board, then talking to your board, then talking to your board, going to your board and say, "Look, going to your board and say, "Look, going to your board and say, "Look, there is some freaking crazy ass there is some freaking crazy ass there is some freaking crazy ass going down. And I know you guys are going down. And I know you guys are going down. And I know you guys are pushing AI like it's phenomenal, right?" pushing AI like it's phenomenal, right?" pushing AI like it's phenomenal, right?" Let me tell you something. Let me tell you something. Let me tell you something. You know, this You know, this You know, this Mythos thing is just the tip of the Mythos thing is just the tip of the Mythos thing is just the tip of the iceberg. There's already an iceberg iceberg. There's already an iceberg iceberg. There's already an iceberg that you need to worry about. Forget that you need to worry about. Forget that you need to worry about. Forget about tip.

about tip. about tip. There's a There's a There's a And that's And that's And that's that's the education that is not that's the education that is not that's the education that is not happening. happening. happening. Right? True. Right? True. Right? True. It's true. Right. Right, exactly. And It's true. Right. Right, exactly. And It's true. Right. Right, exactly. And so, and think about the scale. Mhm. so, and think about the scale. Mhm. so, and think about the scale. Mhm. We're not talking about one company or We're not talking about one company or We're not talking about one company or one tool or one capability. We're one tool or one capability. We're one tool or one capability. We're talking about the ability to do this at talking about the ability to do this at talking about the ability to do this at scale. scale. scale. Right. Right. Right. In a lot of different ways. And then In a lot of different ways. And then In a lot of different ways. And then think about how much of a threat surface think about how much of a threat surface think about how much of a threat surface or a vulnerability or a vulnerability or a vulnerability Yeah, a threat attack surface Yeah, a threat attack surface Yeah, a threat attack surface the consumer is going to become. So, you the consumer is going to become. So, you the consumer is going to become. So, you have all these obligations as a a have all these obligations as a a have all these obligations as a a company to your customers. But if your company to your customers. But if your company to your customers. But if your customer is completely irresponsible, is customer is completely irresponsible, is customer is completely irresponsible, is F A N F O-ing on all this stuff, F A N F O-ing on all this stuff, F A N F O-ing on all this stuff, creating all kinds of creating all kinds of creating all kinds of vulnerabilities for themselves, what are vulnerabilities for themselves, what are vulnerabilities for themselves, what are you going to do? You're going to do what you going to do? You're going to do what you going to do? You're going to do what a lot of banks are doing now. If you are a lot of banks are doing now. If you are a lot of banks are doing now. If you are making a even a a transfer, which used making a even a a transfer, which used making a even a a transfer, which used to be guaranteed and not a problem, to be guaranteed and not a problem, to be guaranteed and not a problem, they're going to basically put the they're going to basically put the they're going to basically put the They're going to do the self-service They're going to do the self-service They're going to do the self-service thing. It's If you want this transfer to thing. It's If you want this transfer to thing. It's If you want this transfer to happen, happen, happen, you take responsibility for if there's you take responsibility for if there's you take responsibility for if there's any fraud that happens because any fraud that happens because any fraud that happens because that we cleared this transaction for that we cleared this transaction for that we cleared this transaction for you. When did that ever happen?

you. When did that ever happen? you. When did that ever happen? >> [laughter] >> [laughter] >> [laughter] >> It's like, "Wait, >> It's like, "Wait, >> It's like, "Wait, why do I bank with you guys if you're why do I bank with you guys if you're why do I bank with you guys if you're going to sit there and not guarantee going to sit there and not guarantee going to sit there and not guarantee anything? You're not going to be anything? You're not going to be anything? You're not going to be accountable for accountable for accountable for >> [laughter] >> [laughter] >> [laughter] >> any anything, and you're going to put it >> any anything, and you're going to put it >> any anything, and you're going to put it on me." on me." on me." Right. It's like, "Oh, eventually Right. It's like, "Oh, eventually Right. It's like, "Oh, eventually they'll say, 'If you have anything on they'll say, 'If you have anything on they'll say, 'If you have anything on deposit, we're not responsible. You need deposit, we're not responsible. You need deposit, we're not responsible. You need to be to be to be Like, what the Like, what the Like, what the Right. Right. Right. >> [laughter] >> [laughter] >> [laughter] [gasps] [gasps] [gasps] >> Is that not paying you for what, >> Is that not paying you for what, >> Is that not paying you for what, exactly? It's happening now, not exactly? It's happening now, not exactly? It's happening now, not tomorrow or 10 years from now. It's tomorrow or 10 years from now. It's tomorrow or 10 years from now. It's already happening. already happening. already happening. You know? You know? You know? >> Right. It's true. It's true. And then >> Right. It's true. It's true. And then >> Right. It's true. It's true. And then you have all these people screwing you have all these people screwing you have all these people screwing around. Yeah. And like, we need to get real. Yeah. And like, we need to get real. Yeah. And this is why I'm going back to Yeah. And this is why I'm going back to Yeah. And this is why I'm going back to the like what we were just talking about the like what we were just talking about the like what we were just talking about before, it's important for like I think before, it's important for like I think before, it's important for like I think great opportunity for the likes of great opportunity for the likes of great opportunity for the likes of Apple, Apple, Apple, Lenovo, um who else is there? I mean, Lenovo, um who else is there? I mean, Lenovo, um who else is there? I mean, you know, um you know, um you know, um freaking Google, if they freaking Google, if they freaking Google, if they they actually lean into this stuff they actually lean into this stuff they actually lean into this stuff instead of promoting, you know, the instead of promoting, you know, the instead of promoting, you know, the stuff that causes risk. Mhm.

stuff that causes risk. Mhm. stuff that causes risk. Mhm. Great opportunity. And Great opportunity. And Great opportunity. And privacy, security, how do you isolate, privacy, security, how do you isolate, privacy, security, how do you isolate, how do you compartmentalize? how do you compartmentalize? how do you compartmentalize? Um yeah, important for individuals Um yeah, important for individuals Um yeah, important for individuals because we're going to become easy because we're going to become easy because we're going to become easy targets. Absolutely. targets. Absolutely. targets. Absolutely. It's true. It's true. I agree. I think It's true. It's true. I agree. I think It's true. It's true. I agree. I think I've always thought this was the I've always thought this was the I've always thought this was the opportunity, so I'm glad that we came That's why we love each other, Debbie, That's why we love each other, Debbie, you and I. We you and I. We you and I. We >> Yes. Yes. Yes. >> Yes. Yes. Yes. >> Yes. Yes. Yes. >> [laughter] >> [laughter] >> [laughter] >> We're rant We're always ranting with our >> We're rant We're always ranting with our >> We're rant We're always ranting with our fists, you know. fists, you know. fists, you know. >> [clears throat] >> [clears throat] >> [clears throat] >> Yeah, we always >> Yeah, we always >> Yeah, we always Yeah. And then everyone saying that, Yeah. And then everyone saying that, Yeah. And then everyone saying that, you know, you know, you know, Yeah, you're Yeah, you're Yeah, you're >> Well, you know, peop- people >> Well, you know, peop- people >> Well, you know, peop- people people somehow come around to our mode people somehow come around to our mode people somehow come around to our mode of thinking in like a couple of years. of thinking in like a couple of years. of thinking in like a couple of years. It takes about a year or two before they It takes about a year or two before they It takes about a year or two before they catch up what we're trying to say. Yeah, catch up what we're trying to say. Yeah, catch up what we're trying to say. Yeah, now you hear a lot more people talk now you hear a lot more people talk now you hear a lot more people talk about trust. You hear a lot more people about trust. You hear a lot more people about trust. You hear a lot more people talk about privacy. Yeah.

talk about privacy. Yeah. talk about privacy. Yeah. They they still need a lot of help They they still need a lot of help They they still need a lot of help figuring out how all this stuff fits figuring out how all this stuff fits figuring out how all this stuff fits together. together. together. But But But they are talking about it, and they they are talking about it, and they they are talking about it, and they weren't talking about it weren't talking about it weren't talking about it 4 years ago. 4 years ago. 4 years ago. That's true. And they were absolutely That's true. And they were absolutely That's true. And they were absolutely not talking about not talking about not talking about um privacy um privacy um privacy um 8 years ago. um 8 years ago. um 8 years ago. They really do. They really do. They really do. They weren't. Nobody was Nobody was They weren't. Nobody was Nobody was They weren't. Nobody was Nobody was talking about it. So, I'm glad that talking about it. So, I'm glad that talking about it. So, I'm glad that people are talking about it. And you people are talking about it. And you people are talking about it. And you know, I've gotten some calls over the know, I've gotten some calls over the know, I've gotten some calls over the last couple like weeks or so from last couple like weeks or so from last couple like weeks or so from consumers. Yeah. And they're like, "Hey, consumers. Yeah. And they're like, "Hey, consumers. Yeah. And they're like, "Hey, what the hell? what the hell? what the hell? >> [laughter] >> [laughter] >> [laughter] >> What is happening, right?" So, I feel >> What is happening, right?" So, I feel >> What is happening, right?" So, I feel like it's actually sinking in because like it's actually sinking in because like it's actually sinking in because people are feeling impacted by it. So, people are feeling impacted by it. So, people are feeling impacted by it. So, yeah. Yeah. Yeah. I mean, you know, yeah. Yeah. Yeah. I mean, you know, yeah. Yeah. Yeah. I mean, you know, I think that value brand, you know, I think that value brand, you know, I think that value brand, you know, from a brand perspective, it's a huge from a brand perspective, it's a huge from a brand perspective, it's a huge plus. I mean, it's worked for Apple. It plus. I mean, it's worked for Apple. It plus. I mean, it's worked for Apple. It should hopefully work for other should hopefully work for other should hopefully work for other um brands out there as well. Yeah.

um brands out there as well. Yeah. um brands out there as well. Yeah. Uh you know, Uh you know, Uh you know, be responsible and provide solutions to be responsible and provide solutions to be responsible and provide solutions to consumers, but also enterprises, consumers, but also enterprises, consumers, but also enterprises, organizations. They're organizations. They're organizations. They're going to be like uh going to be like uh going to be like uh Cuz you know, eventually Mythos is going Cuz you know, eventually Mythos is going Cuz you know, eventually Mythos is going to get out there, and the cost of to get out there, and the cost of to get out there, and the cost of remediating all the vulnerabilities in a remediating all the vulnerabilities in a remediating all the vulnerabilities in a organization's organization's organization's IT IT IT Mhm. is going to be cost prohibitive. Mhm. is going to be cost prohibitive. Mhm. is going to be cost prohibitive. You're going to have to prioritize what You're going to have to prioritize what You're going to have to prioritize what you lock down. Confidential computing, you lock down. Confidential computing, you lock down. Confidential computing, all these things that people didn't give all these things that people didn't give all these things that people didn't give a about, uh even though they were a about, uh even though they were a about, uh even though they were things that they should have given a things that they should have given a things that they should have given a about, they didn't give a about, they didn't give a about, they didn't give a about. Right. Right. Yeah. It's true. It's true. Yeah. Oh my Yeah. It's true. It's true. Yeah. Oh my Yeah. It's true. It's true. Yeah. Oh my gosh. Well, thank you so much for having gosh. Well, thank you so much for having gosh. Well, thank you so much for having me. me. me. >> Oh my god. What are you talking about? >> Oh my god. What are you talking about? >> Oh my god. What are you talking about? You're You're part of the gang. You're You're part of the gang. You're You're part of the gang. There's nothing to There's nothing to There's nothing to Nobody You don't need to thank anybody. Nobody You don't need to thank anybody. Nobody You don't need to thank anybody. We we just jump on, right? We we just jump on, right? We we just jump on, right? >> We [laughter] do. We do. We do. I'm >> We [laughter] do. We do. We do. I'm >> We [laughter] do. We do. We do. I'm always happy to jump on. Uh it's always always happy to jump on. Uh it's always always happy to jump on. Uh it's always great to have you. I'm glad that we had great to have you. I'm glad that we had great to have you. I'm glad that we had this chance to vent. And by the way, this chance to vent. And by the way, this chance to vent. And by the way, everyone, we're just venting. Yeah, everyone, we're just venting. Yeah, everyone, we're just venting. Yeah, we're venting. We see all kinds of we're venting. We see all kinds of we're venting. We see all kinds of ridiculous stuff and we ridiculous stuff and we ridiculous stuff and we do the course of the week and do the course of the week and do the course of the week and sometimes we just have to sometimes we just have to sometimes we just have to let loose. That's true. That's true. We let loose. That's true. That's true. We let loose. That's true. That's true. We did it. We did it. I feel calmer now. I did it. We did it. I feel calmer now. I did it. We did it. I feel calmer now. I feel calmer now.

feel calmer now. feel calmer now. Yeah. Just getting a lot off of our Yeah. Just getting a lot off of our Yeah. Just getting a lot off of our our minds. our minds. our minds. But hey, everyone, But hey, everyone, But hey, everyone, if you made it this far, if you made it this far, if you made it this far, congratulations. That's awesome. congratulations. That's awesome. congratulations. That's awesome. >> Yeah. Yeah, but hopefully you >> Yeah. Yeah, but hopefully you >> Yeah. Yeah, but hopefully you you got a lesson in you got a lesson in you got a lesson in what might happen if you F A and F O. what might happen if you F A and F O. what might happen if you F A and F O. That's right. This is a shout you know, That's right. This is a shout you know, That's right. This is a shout you know, shout out to Bill for being the prophet shout out to Bill for being the prophet shout out to Bill for being the prophet and the and the and the >> [laughter] >> [laughter] >> [laughter] >> preparer of F A F O, not in the bad way >> preparer of F A F O, not in the bad way >> preparer of F A F O, not in the bad way in terms of a warning to people, right? in terms of a warning to people, right? in terms of a warning to people, right? Right. Don't F A and F O. Make sure you Right. Don't F A and F O. Make sure you Right. Don't F A and F O. Make sure you know what you're doing and that you know what you're doing and that you know what you're doing and that you really really really engage with trusted parties engage with trusted parties engage with trusted parties as you look to AI-enable your life or as you look to AI-enable your life or as you look to AI-enable your life or your organization, right? There's a lot your organization, right? There's a lot your organization, right? There's a lot of people out there who really don't of people out there who really don't of people out there who really don't know what they're talking about uh know what they're talking about uh know what they're talking about uh selling stuff that if ultimately you're selling stuff that if ultimately you're selling stuff that if ultimately you're going to want to refund on.

going to want to refund on. going to want to refund on. Yeah, right. Yeah, right. Yeah, right. So, be very cautious about who you trust So, be very cautious about who you trust So, be very cautious about who you trust and vet their backgrounds and vet their backgrounds and vet their backgrounds uh because there's a lot of people who uh because there's a lot of people who uh because there's a lot of people who just just just I'm telling you, they should not be I'm telling you, they should not be I'm telling you, they should not be calling themselves AI experts any kind. calling themselves AI experts any kind. calling themselves AI experts any kind. Uh and then um yeah, uh Uh and then um yeah, uh Uh and then um yeah, uh remember to that we do this every week remember to that we do this every week remember to that we do this every week regardless of any any of our travel regardless of any any of our travel regardless of any any of our travel schedules and stuff even though we're schedules and stuff even though we're schedules and stuff even though we're really busy. But we appreciate your really busy. But we appreciate your really busy. But we appreciate your viewership. Uh we appreciate your viewership. Uh we appreciate your viewership. Uh we appreciate your listenership and we hope that you listenership and we hope that you listenership and we hope that you enjoyed this very very long ass enjoyed this very very long ass enjoyed this very very long ass conversation. But uh we hit a lot of conversation. But uh we hit a lot of conversation. But uh we hit a lot of really good stuff, right, Debbie? Yeah, really good stuff, right, Debbie? Yeah, really good stuff, right, Debbie? Yeah, we're very timely. Always. Always. we're very timely. Always. Always. we're very timely. Always. Always. Always ahead of the curve, right? Always ahead of the curve, right? Always ahead of the curve, right? Exactly. Exactly. And so remember to Exactly. Exactly. And so remember to Exactly. Exactly. And so remember to like, share, like, share, like, share, comment even. You know, especially if comment even. You know, especially if comment even. You know, especially if you have something constructive, um you have something constructive, um you have something constructive, um even if it's not that constructive.

even if it's not that constructive. even if it's not that constructive. Yeah, go ahead and make a comment, share Yeah, go ahead and make a comment, share Yeah, go ahead and make a comment, share your thoughts, your reactions, whether your thoughts, your reactions, whether your thoughts, your reactions, whether you agree or disagree, you know, um you agree or disagree, you know, um you agree or disagree, you know, um we're just trying to spur debate and uh we're just trying to spur debate and uh we're just trying to spur debate and uh introduce uh maybe some introduce uh maybe some introduce uh maybe some angles on the topic of AI and other angles on the topic of AI and other angles on the topic of AI and other tech topics that um tech topics that um tech topics that um are getting too much hype, not enough um are getting too much hype, not enough um are getting too much hype, not enough um grounded grounded grounded uh angles. uh angles. uh angles. Uh uh per- yeah, uh considered in those Uh uh per- yeah, uh considered in those Uh uh per- yeah, uh considered in those those discussions. And uh we'll see you those discussions. And uh we'll see you those discussions. And uh we'll see you next week, all right? Uh so take care. next week, all right? Uh so take care. next week, all right? Uh so take care. Take care. We'll see you, Debbie. All Take care. We'll see you, Debbie. All Take care. We'll see you, Debbie. All right. right. right. >> Have a great weekend. All right, you >> Have a great weekend. All right, you >> Have a great weekend. All right, you too. too. too. Okay. Okay. Okay. >> [music]