IoT Coffee Talk: Episode 311 - "The Next Generation Turing Test" (When will we reach Physical AI?)

>> Nice little run there. I thought you >> Nice little run there. I thought you were heading down the Jimi Hendrix were heading down the Jimi Hendrix were heading down the Jimi Hendrix pathway for a little bit there for a pathway for a little bit there for a pathway for a little bit there for a moment. That was He was getting there. A moment. That was He was getting there. A moment. That was He was getting there. A little Pacific Northwest uh Ah, speaking little Pacific Northwest uh Ah, speaking little Pacific Northwest uh Ah, speaking of of of >> for the cap. >> for the cap. >> for the cap. I'm making coffee. I was inspired by you I'm making coffee. I was inspired by you I'm making coffee. I was inspired by you guys. That's right. It was a subliminal guys. That's right. It was a subliminal guys. That's right. It was a subliminal subconscious thing you were on. Exactly. subconscious thing you were on. Exactly. subconscious thing you were on. Exactly. Yeah. Jimmy. Jimmy. Do you people know Yeah. Jimmy. Jimmy. Do you people know Yeah. Jimmy. Jimmy. Do you people know that Jimi Hendrix grew up in Seattle? that Jimi Hendrix grew up in Seattle? that Jimi Hendrix grew up in Seattle? >> Seattle. Everyone in Seattle >> Seattle. Everyone in Seattle >> Seattle. Everyone in Seattle >> [laughter] >> [laughter] >> [laughter] >> Yeah, one in Seattle did. >> Yeah, one in Seattle did. >> Yeah, one in Seattle did. Favorite son. Yeah. Actually used to be Favorite son. Yeah. Actually used to be Favorite son. Yeah. Actually used to be uh at the MoPOP uh museum in downtown uh at the MoPOP uh museum in downtown uh at the MoPOP uh museum in downtown Seattle. Used to be a really good I Seattle. Used to be a really good I Seattle. Used to be a really good I don't know if it's still there, but a don't know if it's still there, but a don't know if it's still there, but a really good Hendrix um kind of whole really good Hendrix um kind of whole really good Hendrix um kind of whole exhibit. exhibit. exhibit. >> MoPOP used to be great. I don't know >> MoPOP used to be great. I don't know >> MoPOP used to be great. I don't know what they they turned it into something what they they turned it into something what they they turned it into something else, didn't they? Yeah, I don't know. else, didn't they? Yeah, I don't know. else, didn't they? Yeah, I don't know. Haven't been there in a while, but the Haven't been there in a while, but the Haven't been there in a while, but the Hendrix exhibit used to be that was Hendrix exhibit used to be that was Hendrix exhibit used to be that was classic. By the way, um classic. By the way, um classic. By the way, um we got to jam sometime, P. we got to jam sometime, P. we got to jam sometime, P. I know. Yeah, I was playing yesterday. I I know. Yeah, I was playing yesterday. I I know. Yeah, I was playing yesterday. I got some new gear yesterday. I was like got some new gear yesterday. I was like got some new gear yesterday. I was like >> Yeah. We we should just be the freaking >> Yeah. We we should just be the freaking >> Yeah. We we should just be the freaking entertainment at the next AJ [laughter] entertainment at the next AJ [laughter] entertainment at the next AJ [laughter] Sure. Yeah, THAT'D BE GOOD. WHY NOT, Sure. Yeah, THAT'D BE GOOD. WHY NOT, Sure. Yeah, THAT'D BE GOOD. WHY NOT, RIGHT?

RIGHT? RIGHT? >> YEAH, YEAH. WELL, I'm going to you know, >> YEAH, YEAH. WELL, I'm going to you know, >> YEAH, YEAH. WELL, I'm going to you know, I can join in. I can join in. I can join in. >> [laughter] >> [laughter] >> [laughter] >> There you go. I love that. That's like a >> There you go. I love that. That's like a >> There you go. I love that. That's like a flying Flying V ukulele. There you go. flying Flying V ukulele. There you go. flying Flying V ukulele. There you go. Wow. Classic. It can still be rock and Wow. Classic. It can still be rock and Wow. Classic. It can still be rock and roll on a Flying V ukulele. Sure, why roll on a Flying V ukulele. Sure, why roll on a Flying V ukulele. Sure, why not? not? not? So, hey everyone. Welcome to IoT Coffee So, hey everyone. Welcome to IoT Coffee So, hey everyone. Welcome to IoT Coffee Talk. Remember, don't take us seriously. Talk. Remember, don't take us seriously. Talk. Remember, don't take us seriously. If you do, it's at your own risk, If you do, it's at your own risk, If you do, it's at your own risk, [clears throat] [clears throat] [clears throat] at your own peril. at your own peril. at your own peril. Uh we highly recommend the insurance Uh we highly recommend the insurance Uh we highly recommend the insurance policy that you should take out if you policy that you should take out if you policy that you should take out if you do so do so do so uh because it's not a good idea. uh because it's not a good idea. uh because it's not a good idea. And uh yeah, it's another week and this And uh yeah, it's another week and this And uh yeah, it's another week and this is going to be episode 311. is going to be episode 311. is going to be episode 311. Can you believe that? Can you believe that? Can you believe that? That's pretty freaking ridiculous, That's pretty freaking ridiculous, That's pretty freaking ridiculous, right? right? right? It's piling up. It's like It's piling up. It's like It's piling up. It's like Yeah, and this is how we detox at the Yeah, and this is how we detox at the Yeah, and this is how we detox at the end of the week after end of the week after end of the week after being basically being basically being basically injected injected injected overdose on AI AI AI AI AI AI.

overdose on AI AI AI AI AI AI. overdose on AI AI AI AI AI AI. Jesus. Yeah, I know. And that's how it Jesus. Yeah, I know. And that's how it Jesus. Yeah, I know. And that's how it works. works. works. It's close to you sound like a Mongolian It's close to you sound like a Mongolian It's close to you sound like a Mongolian throat singer. If you do that if you do throat singer. If you do that if you do throat singer. If you do that if you do that fast >> [laughter] >> [laughter] >> You go on LinkedIn these days, it's just >> You go on LinkedIn these days, it's just >> You go on LinkedIn these days, it's just like it's like a tsunami of like it's like a tsunami of like it's like a tsunami of stuff. I mean stuff. I mean stuff. I mean >> AI slop? Well, I don't know if it's >> AI slop? Well, I don't know if it's >> AI slop? Well, I don't know if it's slop, but some of it's slop, but yeah, slop, but some of it's slop, but yeah, slop, but some of it's slop, but yeah, it's just impossible to to keep up with it's just impossible to to keep up with it's just impossible to to keep up with this stuff. I've had a whole I've had a this stuff. I've had a whole I've had a this stuff. I've had a whole I've had a whole quite amusing conversation this whole quite amusing conversation this whole quite amusing conversation this week with a with a clearly AI generated week with a with a clearly AI generated week with a with a clearly AI generated um or AI um um or AI um um or AI um fake recruiter who had been I mean, I've fake recruiter who had been I mean, I've fake recruiter who had been I mean, I've been getting my It was very clear it was been getting my It was very clear it was been getting my It was very clear it was fake to begin with that. fake to begin with that. fake to begin with that. Um it was like $2.2 billion IoT platform Um it was like $2.2 billion IoT platform Um it was like $2.2 billion IoT platform company looking for a new CEO, blah blah company looking for a new CEO, blah blah company looking for a new CEO, blah blah blah. I'm like in the Bay Area. I'm blah. I'm like in the Bay Area. I'm blah. I'm like in the Bay Area. I'm like, I know that there's not a $2.2 like, I know that there's not a $2.2 like, I know that there's not a $2.2 billion revenue billion revenue billion revenue IoT company in the Bay you know, you IoT company in the Bay you know, you IoT company in the Bay you know, you failed at the first gate. But this failed at the first gate. But this failed at the first gate. But this thing's got it's it's probably I'm on thing's got it's it's probably I'm on thing's got it's it's probably I'm on the 15th email back and forth, I think, the 15th email back and forth, I think, the 15th email back and forth, I think, cuz I'm like, let's see how far this cuz I'm like, let's see how far this cuz I'm like, let's see how far this thing can go.

thing can go. thing can go. >> Wild. And it is it's wild, actually. I >> Wild. And it is it's wild, actually. I >> Wild. And it is it's wild, actually. I mean, it's it's Oh, yeah. Yeah. The guy mean, it's it's Oh, yeah. Yeah. The guy mean, it's it's Oh, yeah. Yeah. The guy he it's purporting to be a member of a he it's purporting to be a member of a he it's purporting to be a member of a recruitment firm and I contacted someone recruitment firm and I contacted someone recruitment firm and I contacted someone I know at the recruitment firm said, I know at the recruitment firm said, I know at the recruitment firm said, just so you know, this is kind of like just so you know, this is kind of like just so you know, this is kind of like someone's someone's kind of doing this someone's someone's kind of doing this someone's someone's kind of doing this with your with your name. But um with your with your name. But um with your with your name. But um it's as as an offshoot of what's it's as as an offshoot of what's it's as as an offshoot of what's happening on LinkedIn, P. I mean, on happening on LinkedIn, P. I mean, on happening on LinkedIn, P. I mean, on LinkedIn so much of it Ugh. Yeah. LinkedIn so much of it Ugh. Yeah. LinkedIn so much of it Ugh. Yeah. Wait, what's kind of ironic with all of Wait, what's kind of ironic with all of Wait, what's kind of ironic with all of the keep AI capabilities out there, the keep AI capabilities out there, the keep AI capabilities out there, you're there's more spam and obvious, you're there's more spam and obvious, you're there's more spam and obvious, you know, spam more than ever. And you'd you know, spam more than ever. And you'd you know, spam more than ever. And you'd think so they're using AI for the spam, think so they're using AI for the spam, think so they're using AI for the spam, but they're not using AI to counter the but they're not using AI to counter the but they're not using AI to counter the spam. spam. spam. >> [laughter] >> [laughter] >> [laughter] >> Even though I'm paying LinkedIn like uh >> Even though I'm paying LinkedIn like uh >> Even though I'm paying LinkedIn like uh whatever, the premium thing, you know. whatever, the premium thing, you know. whatever, the premium thing, you know. There's a super premium non-spam There's a super premium non-spam There's a super premium non-spam version. Yeah, that would be great, version. Yeah, that would be great, version. Yeah, that would be great, actually. You know, I would I would pay actually. You know, I would I would pay actually. You know, I would I would pay to filter out all the to filter out all the to filter out all the >> Yeah, I know. I would. I would little >> Yeah, I know. I would. I would little >> Yeah, I know. I would. I would little boost boost boost privacy booster or whatever. Of yeah, if privacy booster or whatever. Of yeah, if privacy booster or whatever. Of yeah, if that's the feature of the subscription, that's the feature of the subscription, that's the feature of the subscription, I would I would pay I mean, you know, I would I would pay I mean, you know, I would I would pay I mean, you know, think about like for instance um on the think about like for instance um on the think about like for instance um on the iPhone, they introduced iPhone, they introduced iPhone, they introduced um the the call Call screener? Yeah, um the the call Call screener? Yeah, um the the call Call screener? Yeah, call screener. Love it. Yeah. And call screener. Love it. Yeah. And call screener. Love it. Yeah. And actually screened out yesterday a call actually screened out yesterday a call actually screened out yesterday a call which was obviously a a spam fishing which was obviously a a spam fishing which was obviously a a spam fishing call Mhm. where somebody was a you know, call Mhm. where somebody was a you know, call Mhm. where somebody was a you know, the bot was impersonating the bot was impersonating the bot was impersonating uh an agent from Amazon and was uh an agent from Amazon and was uh an agent from Amazon and was >> Interesting.

>> Interesting. >> Interesting. >> wanting to talk to me and obviously I >> wanting to talk to me and obviously I >> wanting to talk to me and obviously I think this was a voice it left a voice think this was a voice it left a voice think this was a voice it left a voice message. That was the creepy thing. message. That was the creepy thing. message. That was the creepy thing. Mhm. Right? And Mhm. Right? And Mhm. Right? And um um um was asking me to call them back was asking me to call them back was asking me to call them back uh uh uh to validate that I had and verified that to validate that I had and verified that to validate that I had and verified that I had made an purchase of an iPhone. I had made an purchase of an iPhone. I had made an purchase of an iPhone. And I went to my Amazon account, there's And I went to my Amazon account, there's And I went to my Amazon account, there's nothing there, right? nothing there, right? nothing there, right? >> Right. And >> Right. And >> Right. And >> Chances are though whoever they called >> Chances are though whoever they called >> Chances are though whoever they called did buy an iPhone. did buy an iPhone. did buy an iPhone. >> [laughter] >> [laughter] >> [laughter] >> Uh well, I'm glad these things are are >> Uh well, I'm glad these things are are >> Uh well, I'm glad these things are are filters that take away filters that take away filters that take away all this nonsense, the distractions out all this nonsense, the distractions out all this nonsense, the distractions out of our Yeah. lives. of our Yeah. lives. of our Yeah. lives. And um And um And um you know, there's value in that. My you know, there's value in that. My you know, there's value in that. My favorite spam call I used to get uh favorite spam call I used to get uh favorite spam call I used to get uh you know, you ever get you get the call you know, you ever get you get the call you know, you ever get you get the call from like Microsoft tech support, they from like Microsoft tech support, they from like Microsoft tech support, they call you to help you. So, they called me call you to help you. So, they called me call you to help you. So, they called me once I was at Microsoft. I was in the once I was at Microsoft. I was in the once I was at Microsoft. I was in the building. building. building. And they're calling me and they're like, And they're calling me and they're like, And they're calling me and they're like, I'm calling from Microsoft tech support, I'm calling from Microsoft tech support, I'm calling from Microsoft tech support, whatever. I'm like, oh, cool. What whatever. I'm like, oh, cool. What whatever. I'm like, oh, cool. What building are you in? You know, I always building are you in? You know, I always building are you in? You know, I always say I'm playing along with them. And say I'm playing along with them. And say I'm playing along with them. And we're just going on for like a half we're just going on for like a half we're just going on for like a half hour. I'm like, okay, I'm in 119. So, hour. I'm like, okay, I'm in 119. So, hour. I'm like, okay, I'm in 119. So, where are you? Let me connect you. Are where are you? Let me connect you. Are where are you? Let me connect you. Are you are you You know, I'm like, I'm you are you You know, I'm like, I'm you are you You know, I'm like, I'm trying to talk him through like, can you trying to talk him through like, can you trying to talk him through like, can you go to the the MS web thing and we can go to the the MS web thing and we can go to the the MS web thing and we can connect and where are you in the connect and where are you in the connect and where are you in the directory? And you know, directory? And you know, directory? And you know, So, we we kept going for a while and he So, we we kept going for a while and he So, we we kept going for a while and he hung up. So, but yeah, I would I would hung up. So, but yeah, I would I would hung up. So, but yeah, I would I would get calls inside of Microsoft from the get calls inside of Microsoft from the get calls inside of Microsoft from the Microsoft tech support spam thing. I

Microsoft tech support spam thing. I Microsoft tech support spam thing. I thought that Well, anyone in Microsoft thought that Well, anyone in Microsoft thought that Well, anyone in Microsoft knows that there is no tech support in knows that there is no tech support in knows that there is no tech support in Microsoft. Microsoft. Microsoft. >> Well, yeah. It's it's a it's a >> Well, yeah. It's it's a it's a >> Well, yeah. It's it's a it's a self-evident thing, right? What are you self-evident thing, right? What are you self-evident thing, right? What are you talking about? Microsoft support? It talking about? Microsoft support? It talking about? Microsoft support? It must be an impersonator. must be an impersonator. must be an impersonator. >> [laughter] >> [laughter] >> [laughter] >> Good. I think LinkedIn I mean, I I think >> Good. I think LinkedIn I mean, I I think >> Good. I think LinkedIn I mean, I I think that they're making a trade-off between that they're making a trade-off between that they're making a trade-off between content that generates clicks and content that generates clicks and content that generates clicks and therefore, you know, therefore, you know, therefore, you know, meets what I think is an increasingly meets what I think is an increasingly meets what I think is an increasingly fake measure of engagement and actually fake measure of engagement and actually fake measure of engagement and actually applying the filters that would remove applying the filters that would remove applying the filters that would remove the stuff because ChatGPT one is the stuff because ChatGPT one is the stuff because ChatGPT one is extraordinarily effective at identifying extraordinarily effective at identifying extraordinarily effective at identifying when something's been written with AI. I when something's been written with AI. I when something's been written with AI. I mean, very I'll take emails I get from mean, very I'll take emails I get from mean, very I'll take emails I get from people and stick in ChatGPT and say, people and stick in ChatGPT and say, people and stick in ChatGPT and say, what is was this AI generated? And it what is was this AI generated? And it what is was this AI generated? And it comes back with a broken down analysis comes back with a broken down analysis comes back with a broken down analysis of exactly why and what. Um but I do I of exactly why and what. Um but I do I of exactly why and what. Um but I do I Yeah, I mean, I wouldn't give Microsoft Yeah, I mean, I wouldn't give Microsoft Yeah, I mean, I wouldn't give Microsoft too much credit. I know that they sort too much credit. I know that they sort too much credit. I know that they sort of tried, but you know that in Outlook of tried, but you know that in Outlook of tried, but you know that in Outlook there when you get a fishing an obvious there when you get a fishing an obvious there when you get a fishing an obvious fishing email, especially the ones from fishing email, especially the ones from fishing email, especially the ones from DocuSign that are completely hijack the DocuSign that are completely hijack the DocuSign that are completely hijack the identities and just look really identities and just look really identities and just look really authentic, you know it's fake. You authentic, you know it's fake. You authentic, you know it's fake. You report it as fishing, it comes back and report it as fishing, it comes back and report it as fishing, it comes back and it'll tell you, oh, no, this is legit.

it'll tell you, oh, no, this is legit. it'll tell you, oh, no, this is legit. No problem. No problem. No problem. All the time. All the time. All the time. >> [laughter] >> [laughter] >> [laughter] >> Every single time. It it doesn't >> Every single time. It it doesn't >> Every single time. It it doesn't recognize uh fishing emails. Uh and um I recognize uh fishing emails. Uh and um I recognize uh fishing emails. Uh and um I don't know. don't know. don't know. The I I just feel sorry for the world The I I just feel sorry for the world The I I just feel sorry for the world that doesn't know what's coming that doesn't know what's coming that doesn't know what's coming or is already here. It it it's really or is already here. It it it's really or is already here. It it it's really really bad. And I think people aren't really bad. And I think people aren't really bad. And I think people aren't just they're either ignorant or in just just they're either ignorant or in just just they're either ignorant or in just massive denial about massive denial about massive denial about >> Right. Well, I mean, back in the day >> Right. Well, I mean, back in the day >> Right. Well, I mean, back in the day remember when they were there weren't remember when they were there weren't remember when they were there weren't computer viruses and then they were and computer viruses and then they were and computer viruses and then they were and then there was the whole McAfee Norton then there was the whole McAfee Norton then there was the whole McAfee Norton industry of people that you you paid industry of people that you you paid industry of people that you you paid money to counter the So, we'll have money to counter the So, we'll have money to counter the So, we'll have people paying money for AI screening of people paying money for AI screening of people paying money for AI screening of AI spam, you know, AI spam, you know, AI spam, you know, AI spam. I think there's a whole space AI spam. I think there's a whole space AI spam. I think there's a whole space where AI will continue to try and get where AI will continue to try and get where AI will continue to try and get better at fooling human beings or better at fooling human beings or better at fooling human beings or understanding human beings. Where understanding human beings. Where understanding human beings. Where whereas I think more in the industrial whereas I think more in the industrial whereas I think more in the industrial space as someone said to me last week, space as someone said to me last week, space as someone said to me last week, they said, well, I don't know why people they said, well, I don't know why people they said, well, I don't know why people are spending so much trying time trying are spending so much trying time trying are spending so much trying time trying to figure out how to get robots to to figure out how to get robots to to figure out how to get robots to robots to get along with human beings in robots to get along with human beings in robots to get along with human beings in a factory environment because the a factory environment because the a factory environment because the the aim is to remove the human beings the aim is to remove the human beings the aim is to remove the human beings from that equation. So, you know, and it from that equation. So, you know, and it from that equation. So, you know, and it was a it was a conversation about was a it was a conversation about was a it was a conversation about tactile technology to, you know, help tactile technology to, you know, help tactile technology to, you know, help teach robots to touch, etc. And and it teach robots to touch, etc. And and it teach robots to touch, etc. And and it was like was like was like his view was like, well, the whole goal his view was like, well, the whole goal his view was like, well, the whole goal here is to, you know, for the humans to here is to, you know, for the humans to here is to, you know, for the humans to not be in that environment, to be a not be in that environment, to be a not be in that environment, to be a lights-out factory. So, why are we lights-out factory. So, why are we lights-out factory. So, why are we spending all of this time trying to make spending all of this time trying to make spending all of this time trying to make humanoid robots that are somehow more

humanoid robots that are somehow more humanoid robots that are somehow more acceptable to humans? Who gives a acceptable to humans? Who gives a acceptable to humans? Who gives a Yeah. It's they do, but you know. Yeah, Yeah. It's they do, but you know. Yeah, Yeah. It's they do, but you know. Yeah, but but it's because the machines can't but but it's because the machines can't but but it's because the machines can't do what humans do, right? Um I think do what humans do, right? Um I think do what humans do, right? Um I think that's the big problem. And when you that's the big problem. And when you that's the big problem. And when you talk to folks who have been doing quote talk to folks who have been doing quote talk to folks who have been doing quote unquote physical AI for a long time or unquote physical AI for a long time or unquote physical AI for a long time or even robotics, humanoid robotics, the even robotics, humanoid robotics, the even robotics, humanoid robotics, the biggest problem is the tactile stuff. biggest problem is the tactile stuff. biggest problem is the tactile stuff. Yeah. Um, you know, and I think we Yeah. Um, you know, and I think we Yeah. Um, you know, and I think we mentioned this maybe a couple of mentioned this maybe a couple of mentioned this maybe a couple of episodes ago. But without the tactile it episodes ago. But without the tactile it episodes ago. But without the tactile it vision is limited, right? It's essential vision is limited, right? It's essential vision is limited, right? It's essential or actually maybe it's not even or actually maybe it's not even or actually maybe it's not even essential if you think about it, but the essential if you think about it, but the essential if you think about it, but the tactile part is the toughest part to tactile part is the toughest part to tactile part is the toughest part to get. And then um get. And then um get. And then um you know you know you know the the the these physical models that were were these physical models that were were these physical models that were were that people are building they're based that people are building they're based that people are building they're based on largely vision. on largely vision. on largely vision. Right? Yeah. And so they I mean, you Right? Yeah. And so they I mean, you Right? Yeah. And so they I mean, you know, what about smell?

know, what about smell? know, what about smell? Right? Right? Right? I mean, I mean, I mean, if somebody farts in the room does your if somebody farts in the room does your if somebody farts in the room does your AI AI AI know? know? know? Right? Right? Right? MINE DOES. MINE DOES. MINE DOES. >> [laughter] >> BUT NO, I MEAN, THAT THAT'S LIKE THE >> BUT NO, I MEAN, THAT THAT'S LIKE THE essential question essential question essential question I think in the near future is like if if I think in the near future is like if if I think in the near future is like if if you're if you fart, does your AI know? you're if you fart, does your AI know? you're if you fart, does your AI know? But do you think if you take that video But do you think if you take that video But do you think if you take that video signal is so much easier to ingest and signal is so much easier to ingest and signal is so much easier to ingest and process than tactile signal or scent process than tactile signal or scent process than tactile signal or scent signal or signal or signal or >> True. I think >> True. I think >> True. I think >> But I think Leonard's invented the new >> But I think Leonard's invented the new >> But I think Leonard's invented the new Turing test, which is uh Turing test, which is uh Turing test, which is uh can your AI detect farts? I think that's can your AI detect farts? I think that's can your AI detect farts? I think that's the Yeah. Then we've reached AGI once we the Yeah. Then we've reached AGI once we the Yeah. Then we've reached AGI once we Just doubt into that. They kind of have Just doubt into that. They kind of have Just doubt into that. They kind of have already had that, right? I mean, all already had that, right? I mean, all already had that, right? I mean, all you're doing is introducing methane you're doing is introducing methane you're doing is introducing methane sensing into the AI realm, so That's sensing into the AI realm, so That's sensing into the AI realm, so That's true. I think there was someone who true. I think there was someone who true. I think there was someone who built like an artificial Someone built built like an artificial Someone built built like an artificial Someone built an artificial nose. I think it's out an artificial nose. I think it's out an artificial nose. I think it's out there.

there. there. Yeah, I remember that. That was one of Yeah, I remember that. That was one of Yeah, I remember that. That was one of some one of that was a guy some one of that was a guy some one of that was a guy gosh, he worked on the Microsoft guy. gosh, he worked on the Microsoft guy. gosh, he worked on the Microsoft guy. Yeah, I'll put Yeah, yeah, yeah, the Yeah, I'll put Yeah, yeah, yeah, the Yeah, I'll put Yeah, yeah, yeah, the French guy. I don't remember his name French guy. I don't remember his name French guy. I don't remember his name actually. actually. actually. Um, yes. Bertrand something or other. Um, yes. Bertrand something or other. Um, yes. Bertrand something or other. Prepare up to chat GPT and you're all Prepare up to chat GPT and you're all Prepare up to chat GPT and you're all set. Yeah, I mean, but Bill, I would set. Yeah, I mean, but Bill, I would set. Yeah, I mean, but Bill, I would argue it depends on what you ate, but argue it depends on what you ate, but argue it depends on what you ate, but Yeah, you're right. But it all starts Yeah, you're right. But it all starts Yeah, you're right. But it all starts with sensors. We're going to be at with sensors. We're going to be at with sensors. We're going to be at Sensors Converge, right? Sensors Converge, right? Sensors Converge, right? >> Yeah, good segue. >> Yeah, good segue. >> Yeah, good segue. >> [laughter] >> [laughter] >> [laughter] >> Great segue. Speaking of farts. Speaking >> Great segue. Speaking of farts. Speaking >> Great segue. Speaking of farts. Speaking of of of >> [laughter] >> [laughter] >> [laughter] >> methane sensing. >> methane sensing. >> methane sensing. >> Sensors converge. Speaking of sensors >> Sensors converge. Speaking of sensors >> Sensors converge. Speaking of sensors converging. Yeah, yeah. converging. Yeah, yeah. converging. Yeah, yeah. >> That is that is the ultimate convergence >> That is that is the ultimate convergence >> That is that is the ultimate convergence right there. right there. right there. >> There you go. >> There you go. >> There you go. Now yeah, Sensors Converge is next week, Now yeah, Sensors Converge is next week, Now yeah, Sensors Converge is next week, right? Is that like the 5th through the right? Is that like the 5th through the right? Is that like the 5th through the 7th? 7th? 7th? I think that's it. Where is it? Yeah. I think that's it. Where is it? Yeah. I think that's it. Where is it? Yeah. >> It's in Santa Clara. Santa Clara. Yeah. >> It's in Santa Clara. Santa Clara. Yeah. >> It's in Santa Clara. Santa Clara. Yeah. >> Um, been going on for decades there, >> Um, been going on for decades there, >> Um, been going on for decades there, that show. Yeah, I think that one is that show. Yeah, I think that one is that show. Yeah, I think that one is good. good. good. >> It's going to be a good one. Yeah, and >> It's going to be a good one. Yeah, and >> It's going to be a good one. Yeah, and there it's great. I'm on the board there it's great. I'm on the board there it's great. I'm on the board and it's great to have Edge AI and it's great to have Edge AI and it's great to have Edge AI Foundation as a partner. I know they're Foundation as a partner. I know they're Foundation as a partner. I know they're my favorite. Yeah, and uh my favorite. Yeah, and uh my favorite. Yeah, and uh >> Yeah, we have a big pavilion there and >> Yeah, we have a big pavilion there and >> Yeah, we have a big pavilion there and uh I'm going to do a keynote entitled uh I'm going to do a keynote entitled uh I'm going to do a keynote entitled how Edge AI will save the world, so how Edge AI will save the world, so how Edge AI will save the world, so What? That's the keynote, yeah.

What? That's the keynote, yeah. What? That's the keynote, yeah. >> [laughter] >> [laughter] >> [laughter] >> Are you serious? So you got to tune in >> Are you serious? So you got to tune in >> Are you serious? So you got to tune in for that cuz you want to everyone wants for that cuz you want to everyone wants for that cuz you want to everyone wants to know. Oh yeah, now I really want to to know. Oh yeah, now I really want to to know. Oh yeah, now I really want to know. Why don't you just tell everyone know. Why don't you just tell everyone know. Why don't you just tell everyone now? No, you got to you got to go to the now? No, you got to you got to go to the now? No, you got to you got to go to the show. show. show. >> [laughter] >> [laughter] >> [laughter] >> Oh, no way. >> Oh, no way. >> Oh, no way. You'll have to pay the ticket. You have You'll have to pay the ticket. You have You'll have to pay the ticket. You have to pay the ticket. to pay the ticket. to pay the ticket. That's right. doing that. We're doing That's right. doing that. We're doing That's right. doing that. We're doing doing a fireside chat with ST. We have a doing a fireside chat with ST. We have a doing a fireside chat with ST. We have a panel too on kind of embodied AI. panel too on kind of embodied AI. panel too on kind of embodied AI. Ah. Ah. Ah. So yeah, it should be a lot of fun next So yeah, it should be a lot of fun next So yeah, it should be a lot of fun next week. So a lot of sensor stuff, sensory week. So a lot of sensor stuff, sensory week. So a lot of sensor stuff, sensory sensors. sensors. sensors. Yeah, hey, you know, oh jeez, what's his Yeah, hey, you know, oh jeez, what's his Yeah, hey, you know, oh jeez, what's his name again? name again? name again? The The The the um the um the um the actor on your shirt. the actor on your shirt. the actor on your shirt. Oh, John Woo. Oh, John Woo. Oh, John Woo. That's not John Woo. Well, no, I mean, That's not John Woo. Well, no, I mean, That's not John Woo. Well, no, I mean, you you So you this is So this is from you you So you this is So this is from you you So you this is So this is from the movie The Killer? Yeah, yeah, yeah. the movie The Killer? Yeah, yeah, yeah. the movie The Killer? Yeah, yeah, yeah. Um Um Um >> Yeah. Oh god, what's his name? The guy >> Yeah. Oh god, what's his name? The guy >> Yeah. Oh god, what's his name? The guy on the left.

on the left. on the left. You're right. You're right. You're right. Yeah, yeah, you know, it's like weird Yeah, yeah, you know, it's like weird Yeah, yeah, you know, it's like weird those old Hong Kong movies were really those old Hong Kong movies were really those old Hong Kong movies were really violent, man. violent, man. violent, man. I could do you This is a classic I could do you This is a classic I could do you This is a classic T-shirt. T-shirt. T-shirt. >> Yeah, yeah, yeah. It is. It is. >> Yeah, yeah, yeah. It is. It is. >> Yeah, yeah, yeah. It is. It is. >> It's a it's the John Woo collaboration >> It's a it's the John Woo collaboration >> It's a it's the John Woo collaboration with with with uh The Killer and uh The Killer and uh The Killer and Supreme put it out. Supreme put it out. Supreme put it out. You can probably you can probably pick You can probably you can probably pick You can probably you can probably pick it up for a few hundred bucks. it up for a few hundred bucks. it up for a few hundred bucks. >> [laughter] >> [laughter] >> [laughter] >> Yeah, that's it. He was He was in >> Yeah, that's it. He was He was in >> Yeah, that's it. He was He was in a few hundred bucks. a few hundred bucks. a few hundred bucks. >> [laughter] >> Do you think you could come get one? My >> Do you think you could come get one? My son doesn't have that one, but he has son doesn't have that one, but he has son doesn't have that one, but he has like a wall He has a closet full of like a wall He has a closet full of like a wall He has a closet full of Supreme stuff, which is like Supreme stuff, which is like Supreme stuff, which is like Yeah, the the online kind of gray market Yeah, the the online kind of gray market Yeah, the the online kind of gray market in Supreme is is is stuff with a hook. in Supreme is is is stuff with a hook. in Supreme is is is stuff with a hook. It really is. Yes, 100%. It really is. Yes, 100%. It really is. Yes, 100%. Cool. Cool. Cool. >> Yeah. He was in Crouching Tiger, Hidden >> Yeah. He was in Crouching Tiger, Hidden >> Yeah. He was in Crouching Tiger, Hidden Dragon. Jeez, how can I not remember his Dragon. Jeez, how can I not remember his Dragon. Jeez, how can I not remember his name? I'm getting old.

name? I'm getting old. name? I'm getting old. Um anyway. Um anyway. Um anyway. Yeah. Yeah. Yeah. >> Leave my eye. AI will sort that out. >> Leave my eye. AI will sort that out. >> Leave my eye. AI will sort that out. Yeah, that's right. Rely on AI for your Yeah, that's right. Rely on AI for your Yeah, that's right. Rely on AI for your memory. memory. memory. I'm relying on uh I'm relying on uh I'm relying on uh uh Chow Yun-Fat. uh Chow Yun-Fat. uh Chow Yun-Fat. Chow Yun-Fat. I have to you know, I'm Chow Yun-Fat. I have to you know, I'm Chow Yun-Fat. I have to you know, I'm going to Okay, credit to IMDb. It was a going to Okay, credit to IMDb. It was a going to Okay, credit to IMDb. It was a database. I just did like a simple database. I just did like a simple database. I just did like a simple lookup. lookup. lookup. >> [laughter] >> [laughter] >> [laughter] >> Chow Yun-Fat, yeah. You know how I mean, >> Chow Yun-Fat, yeah. You know how I mean, >> Chow Yun-Fat, yeah. You know how I mean, that guy was huge. that guy was huge. that guy was huge. Uh Uh Uh >> He is. Huge, yeah. I mean, he's freaking >> He is. Huge, yeah. I mean, he's freaking >> He is. Huge, yeah. I mean, he's freaking superstar in Asia. superstar in Asia. superstar in Asia. Yeah. Yeah, it's cool, man. Hm. So Yeah. Yeah, it's cool, man. Hm. So Yeah. Yeah, it's cool, man. Hm. So oh my god, what's up? What's up? So oh my god, what's up? What's up? So oh my god, what's up? What's up? So embodied AI, what the hell is that? I embodied AI, what the hell is that? I embodied AI, what the hell is that? I know. Well, it's another know. Well, it's another know. Well, it's another another term, you know, about AI, you another term, you know, about AI, you another term, you know, about AI, you know, in things. know, in things. know, in things. You know, that it's like, you know You know, that it's like, you know You know, that it's like, you know >> No, I don't know.

>> No, I don't know. >> No, I don't know. >> [laughter] >> [laughter] >> [laughter] >> How did you come up with this term? >> How did you come up with this term? >> How did you come up with this term? This is actually This is actually the This is actually This is actually the This is actually This is actually the first question of the panel. The first first question of the panel. The first first question of the panel. The first question of the panel is what is question of the panel is what is question of the panel is what is embodied AI? Did you Did you do an adult embodied AI? Did you Did you do an adult embodied AI? Did you Did you do an adult warning adult content warning at the warning adult content warning at the warning adult content warning at the beginning of this cuz I fear that that beginning of this cuz I fear that that beginning of this cuz I fear that that we're headed into we're headed into we're headed into >> Oh, I see. >> Oh, I see. >> Oh, I see. Think about that, but you know, that Think about that, but you know, that Think about that, but you know, that could be another angle there. Um, you could be another angle there. Um, you could be another angle there. Um, you know, it's you know, people would think know, it's you know, people would think know, it's you know, people would think about it as like AI that's like infusing about it as like AI that's like infusing about it as like AI that's like infusing capabilities inside of an object. capabilities inside of an object. capabilities inside of an object. Like a robot or things like that. But Like a robot or things like that. But Like a robot or things like that. But it's you know, people use it for like it's you know, people use it for like it's you know, people use it for like smart glasses and stuff. Personally, I'm smart glasses and stuff. Personally, I'm smart glasses and stuff. Personally, I'm not I don't think it's really like that not I don't think it's really like that not I don't think it's really like that great of a term cuz it's really squishy great of a term cuz it's really squishy great of a term cuz it's really squishy and weird. Yeah. and weird. Yeah. and weird. Yeah. But but it's AI in things, but it's you But but it's AI in things, but it's you But but it's AI in things, but it's you know, that's kind of know, that's kind of know, that's kind of >> Does it mean Does it mean we will have >> Does it mean Does it mean we will have >> Does it mean Does it mean we will have to go back and try and stop thinking to go back and try and stop thinking to go back and try and stop thinking about embedding RFID chips in our wrists about embedding RFID chips in our wrists about embedding RFID chips in our wrists cuz a GPU is a lot bigger and I can cuz a GPU is a lot bigger and I can cuz a GPU is a lot bigger and I can imagine that being a Yes. Well, that's imagine that being a Yes. Well, that's imagine that being a Yes. Well, that's Now you're talking about implantables. Now you're talking about implantables. Now you're talking about implantables. So you have you have wearables, So you have you have wearables, So you have you have wearables, hearables, and implantables. So you're hearables, and implantables. So you're hearables, and implantables. So you're talking about implantables.

talking about implantables. talking about implantables. Which would be using like neuromorphic Which would be using like neuromorphic Which would be using like neuromorphic or spiking neural network. You know. or spiking neural network. You know. or spiking neural network. You know. Which is kind of infinite battery life Which is kind of infinite battery life Which is kind of infinite battery life that you'd be inside your body. that you'd be inside your body. that you'd be inside your body. >> that's why in yeah. >> that's why in yeah. >> that's why in yeah. So implantables. Actually, on a more So implantables. Actually, on a more So implantables. Actually, on a more serious note, implantables are being serious note, implantables are being serious note, implantables are being used for like deep brain stimulation and used for like deep brain stimulation and used for like deep brain stimulation and things like for Parkinson's and other things like for Parkinson's and other things like for Parkinson's and other stuff. So you So you'll see actually stuff. So you So you'll see actually stuff. So you So you'll see actually some interesting uh applications of some interesting uh applications of some interesting uh applications of implantables over time that can sort of implantables over time that can sort of implantables over time that can sort of self-tune there. Things cuz right now self-tune there. Things cuz right now self-tune there. Things cuz right now when you do things like that like when you do things like that like when you do things like that like pacemakers and stuff you kind of set it pacemakers and stuff you kind of set it pacemakers and stuff you kind of set it up and you kind of put it in there and up and you kind of put it in there and up and you kind of put it in there and see what happens. But imagine if you see what happens. But imagine if you see what happens. But imagine if you could read the feedback from the body could read the feedback from the body could read the feedback from the body and adjust your electrical output and and adjust your electrical output and and adjust your electrical output and things like that. So it's kind of a things like that. So it's kind of a things like that. So it's kind of a implantables is actually a pretty cool implantables is actually a pretty cool implantables is actually a pretty cool pretty cool area uh if you look at folks pretty cool area uh if you look at folks pretty cool area uh if you look at folks that are doing that. Tough space, that are doing that. Tough space, that are doing that. Tough space, obviously. It's really challenging to do obviously. It's really challenging to do obviously. It's really challenging to do that, but you know you can you can start that, but you know you can you can start that, but you know you can you can start to solve big problems with it, then to solve big problems with it, then to solve big problems with it, then maybe that's it's one of the maybe that's it's one of the maybe that's it's one of the >> Well, you see already see, I mean, it's >> Well, you see already see, I mean, it's >> Well, you see already see, I mean, it's not implantable, but a lot of people not implantable, but a lot of people not implantable, but a lot of people were wearing the stuff on their skin to were wearing the stuff on their skin to were wearing the stuff on their skin to monitor their glucose and whatever, so monitor their glucose and whatever, so monitor their glucose and whatever, so Yeah. You know, there'll be some Yeah. You know, there'll be some Yeah. You know, there'll be some implantable in there that I mean, I implantable in there that I mean, I implantable in there that I mean, I think they have that thing with the CPAP think they have that thing with the CPAP think they have that thing with the CPAP thing. Instead of a CPAP, you can get a thing. Instead of a CPAP, you can get a thing. Instead of a CPAP, you can get a thing in there to thing in there to thing in there to stop your snoring or something.

stop your snoring or something. stop your snoring or something. >> that's where the a lot of the >> that's where the a lot of the >> that's where the a lot of the It's it's so weird. We're using tech to It's it's so weird. We're using tech to It's it's so weird. We're using tech to solve problems that we've created by bad solve problems that we've created by bad solve problems that we've created by bad diets. diets. diets. >> [laughter] >> [laughter] >> [laughter] >> That's true. >> That's true. >> That's true. I know. I know. I know. That's right. I want to keep eating my That's right. I want to keep eating my That's right. I want to keep eating my cotton candy. So how do I do that? Well, cotton candy. So how do I do that? Well, cotton candy. So how do I do that? Well, you know, use this tech to monitor your you know, use this tech to monitor your you know, use this tech to monitor your sugar level. sugar level. sugar level. >> I mean, that's like literally the entire >> I mean, that's like literally the entire >> I mean, that's like literally the entire pharma industry, right? I mean, you pharma industry, right? I mean, you pharma industry, right? I mean, you know, diabetes it's a self-inflicted know, diabetes it's a self-inflicted know, diabetes it's a self-inflicted disease for the most part, right? I mean disease for the most part, right? I mean disease for the most part, right? I mean >> Type two. Type two. Type one is not Type >> Type two. Type two. Type one is not Type >> Type two. Type two. Type one is not Type two. Not two. Not two. Not Okay, thanks. Okay, thanks. Okay, thanks. Type two is Yeah. If you think about it Type two is Yeah. If you think about it Type two is Yeah. If you think about it like for those of us that are Gen X uh like for those of us that are Gen X uh like for those of us that are Gen X uh you know you know you know we were we were advertised a bunch of we were we were advertised a bunch of we were we were advertised a bunch of different things. I mean, right? I mean, different things. I mean, right? I mean, different things. I mean, right? I mean, breakfast in the morning, depending on breakfast in the morning, depending on breakfast in the morning, depending on where you were, it was like Fruit Loops, where you were, it was like Fruit Loops, where you were, it was like Fruit Loops, sugary cereal, and anything like that sugary cereal, and anything like that sugary cereal, and anything like that and Count Chocula. Count Chocula. And and Count Chocula. Count Chocula. And and Count Chocula. Count Chocula. And then you then you then you you crash in class.

you crash in class. you crash in class. >> [laughter] >> [laughter] >> [laughter] >> Lucky Charms. Get your Lucky Charms in >> Lucky Charms. Get your Lucky Charms in >> Lucky Charms. Get your Lucky Charms in there with your marshmallows. You're there with your marshmallows. You're there with your marshmallows. You're right, dude. right, dude. right, dude. >> It's like those of us I mean, I was one >> It's like those of us I mean, I was one >> It's like those of us I mean, I was one of those. It's like give me the Lucky of those. It's like give me the Lucky of those. It's like give me the Lucky Charms. I'm tossing those little grain Charms. I'm tossing those little grain Charms. I'm tossing those little grain things out and I'm keeping the things out and I'm keeping the things out and I'm keeping the marshmallows. marshmallows. marshmallows. >> That's right. You go with the >> That's right. You go with the >> That's right. You go with the marshmallows. Yeah. Yeah, now then you marshmallows. Yeah. Yeah, now then you marshmallows. Yeah. Yeah, now then you hit 10:00 in the morning and you crash. hit 10:00 in the morning and you crash. hit 10:00 in the morning and you crash. Oh my god. So that explains it. I always Oh my god. So that explains it. I always Oh my god. So that explains it. I always wondered why I was so tired wondered why I was so tired wondered why I was so tired by the time you 1:00 rolled around, I by the time you 1:00 rolled around, I by the time you 1:00 rolled around, I was like I needed to have a siesta. was like I needed to have a siesta. was like I needed to have a siesta. There you go. There you go. There you go. Now we're being we're being marketed to Now we're being we're being marketed to Now we're being we're being marketed to about all of these different things and about all of these different things and about all of these different things and then and then and then you you know, then and then and then you you know, then and then and then you you know, these medical things that you I'm like, these medical things that you I'm like, these medical things that you I'm like, we never had commercials that were like we never had commercials that were like we never had commercials that were like health care commercials that hey, go ask health care commercials that hey, go ask health care commercials that hey, go ask your doctor to give you this. Oh yeah. your doctor to give you this. Oh yeah. your doctor to give you this. Oh yeah. By the way, you might have anal itching By the way, you might have anal itching By the way, you might have anal itching and and and colon colon colon deterioration and Oh no, the best is the deterioration and Oh no, the best is the deterioration and Oh no, the best is the warning all the warning labels is like, warning all the warning labels is like, warning all the warning labels is like, don't take this if you're allergic to don't take this if you're allergic to don't take this if you're allergic to it. It may cause may cause death. It may it. It may cause may cause death. It may it. It may cause may cause death. It may cause whatever. And cause whatever. And cause whatever. And you know, so it's like uh Makes no you know, so it's like uh Makes no you know, so it's like uh Makes no sense.

sense. sense. >> It's crazy. The The yeah, these days >> It's crazy. The The yeah, these days >> It's crazy. The The yeah, these days it's you're inundated with Jardiance and it's you're inundated with Jardiance and it's you're inundated with Jardiance and Ardians and all kinds of weird names and Ardians and all kinds of weird names and Ardians and all kinds of weird names and uh uh uh >> Yeah. >> Yeah. >> Yeah. But that's that's the tech. The But that's that's the tech. The But that's that's the tech. The interesting thing is you talk about interesting thing is you talk about interesting thing is you talk about embedded tech and Neuralink and all that embedded tech and Neuralink and all that embedded tech and Neuralink and all that sort of stuff, but the other thing I sort of stuff, but the other thing I sort of stuff, but the other thing I think I was really this week was think I was really this week was think I was really this week was the kind of the ultimate approach is the kind of the ultimate approach is the kind of the ultimate approach is using gene therapy and there's this using gene therapy and there's this using gene therapy and there's this thing called the Yamanaka factors. Um thing called the Yamanaka factors. Um thing called the Yamanaka factors. Um so you can use a specific set of genes so you can use a specific set of genes so you can use a specific set of genes to reprogram cells to reprogram cells to reprogram cells within the body to make them revert to within the body to make them revert to within the body to make them revert to reverse back in time to what being a reverse back in time to what being a reverse back in time to what being a stem cell. And they've been doing stem cell. And they've been doing stem cell. And they've been doing various kind of questionable experiments various kind of questionable experiments various kind of questionable experiments I think on on rats and what have you, I think on on rats and what have you, I think on on rats and what have you, severing rats' optic nerves, exposing severing rats' optic nerves, exposing severing rats' optic nerves, exposing them to these Yamanaka factor factors them to these Yamanaka factor factors them to these Yamanaka factor factors and then the optic nerve regrowing and then the optic nerve regrowing and then the optic nerve regrowing completely and then and the rat then completely and then and the rat then completely and then and the rat then being able to see and similarly reverse being able to see and similarly reverse being able to see and similarly reverse like going from being gray-haired to you like going from being gray-haired to you like going from being gray-haired to you know, young and bouncy. So I think know, young and bouncy. So I think know, young and bouncy. So I think there's there's a there's a kind of race there's there's a there's a kind of race there's there's a there's a kind of race between is this a between is this a between is this a medically driven, genetically driven medically driven, genetically driven medically driven, genetically driven kind of kind of kind of strand of innovation or is it something strand of innovation or is it something strand of innovation or is it something that's facilitated by hardware and that's facilitated by hardware and that's facilitated by hardware and embedded technology? Yeah.

embedded technology? Yeah. embedded technology? Yeah. My money's on the gene therapy side I My money's on the gene therapy side I My money's on the gene therapy side I would I would say, but would I would say, but would I would say, but the cancer uh the cancer uh the cancer uh uh self-evident. If you're telling uh self-evident. If you're telling uh self-evident. If you're telling telling yourselves to do things you telling yourselves to do things you telling yourselves to do things you know, outside of the normal form, then know, outside of the normal form, then know, outside of the normal form, then uh uh uh cancer So, why is it that as you were cancer So, why is it that as you were cancer So, why is it that as you were describing that, I kept thinking of describing that, I kept thinking of describing that, I kept thinking of Aliens, the movie? Aliens, the movie? Aliens, the movie? I don't know why. I don't know why. I don't know why. Super human I have no idea why. Super human I have no idea why. Super human I have no idea why. The xenomorphs you're talking about. The xenomorphs you're talking about. The xenomorphs you're talking about. >> [laughter] >> [laughter] >> [laughter] >> Well, you know, it ends up you know, >> Well, you know, it ends up you know, >> Well, you know, it ends up you know, either we're a product of that already either we're a product of that already either we're a product of that already and alien experiment or we create and alien experiment or we create and alien experiment or we create we create The guy that told me that that we create The guy that told me that that we create The guy that told me that that we didn't know about. research. He was we didn't know about. research. He was we didn't know about. research. He was also the first person to make a human also the first person to make a human also the first person to make a human human ape chimera that they they killed human ape chimera that they they killed human ape chimera that they they killed the embryos at like 20 days. So the guy the embryos at like 20 days. So the guy the embryos at like 20 days. So the guy is kind of out there and is not you is kind of out there and is not you is kind of out there and is not you know, not well respected, but he's he's know, not well respected, but he's he's know, not well respected, but he's he's one of the faces getting vast amounts of one of the faces getting vast amounts of one of the faces getting vast amounts of funding from Bezos and others to go to funding from Bezos and others to go to funding from Bezos and others to go to the Yeah. the Yeah. the Yeah. I mean, there's like things that I mean, there's like things that I mean, there's like things that Yeah, there's things that you simply Yeah, there's things that you simply Yeah, there's things that you simply shouldn't probably shouldn't probably shouldn't probably you shouldn't do. But you get you know, you shouldn't do. But you get you know, you shouldn't do. But you get you know, there you're going to do it anyways.

there you're going to do it anyways. there you're going to do it anyways. Right. There's some It's pronounced Right. There's some It's pronounced Right. There's some It's pronounced Fronkensteen by the way. Fronkensteen, Fronkensteen by the way. Fronkensteen, Fronkensteen by the way. Fronkensteen, not Frankenstein. Yeah. not Frankenstein. Yeah. not Frankenstein. Yeah. Yeah, okay. That's thoroughly Yeah, okay. That's thoroughly Yeah, okay. That's thoroughly depressing. Okay. depressing. Okay. depressing. Okay. Yeah. It's always depressing on a Yeah. It's always depressing on a Yeah. It's always depressing on a Friday. I mean, that's I see that as my Friday. I mean, that's I see that as my Friday. I mean, that's I see that as my role to to come up with depressing Yeah, role to to come up with depressing Yeah, role to to come up with depressing Yeah, thanks, man. thanks, man. thanks, man. Yeah, I didn't think We're all screwed. Yeah, I didn't think We're all screwed. Yeah, I didn't think We're all screwed. We're all screwed. We're all screwed. We're all screwed. >> [laughter] >> [laughter] >> [laughter] >> Started with farts and we ended with >> Started with farts and we ended with >> Started with farts and we ended with xenomorphs. Yeah. xenomorphs. Yeah. xenomorphs. Yeah. Always the way. Always the way. Always the way. Always the way. Always the way. Always the way. >> Yeah, maybe that's what we'll call this >> Yeah, maybe that's what we'll call this >> Yeah, maybe that's what we'll call this episode, the urine test. episode, the urine test. episode, the urine test. >> [laughter] >> Uh but >> Uh but that's the you know, okay, so go going that's the you know, okay, so go going that's the you know, okay, so go going back to neuromorphic though. Yeah. back to neuromorphic though. Yeah. back to neuromorphic though. Yeah. Yeah, you know, medical devices are Yeah, you know, medical devices are Yeah, you know, medical devices are probably where a lot of this is going to probably where a lot of this is going to probably where a lot of this is going to start, you know, solving problems that start, you know, solving problems that start, you know, solving problems that we caused for ourselves with bad diet as we caused for ourselves with bad diet as we caused for ourselves with bad diet as as um as um as um There's no shortage of demand for There's no shortage of demand for There's no shortage of demand for medical solutions these days. medical solutions these days. medical solutions these days. Yeah. The I mean, there's there's Yeah. The I mean, there's there's Yeah. The I mean, there's there's there's the obvious these you know, we there's the obvious these you know, we there's the obvious these you know, we can talk about those Ozempic and all can talk about those Ozempic and all can talk about those Ozempic and all that other stuff, but actually taking that other stuff, but actually taking that other stuff, but actually taking the tech and making it more applicable the tech and making it more applicable the tech and making it more applicable worldwide so that you know, a lot of worldwide so that you know, a lot of worldwide so that you know, a lot of you know, societies that don't have you know, societies that don't have you know, societies that don't have the the richness that we have like in the the richness that we have like in the the richness that we have like in the US that can now get more access to the US that can now get more access to the US that can now get more access to better tech because they're using AI on better tech because they're using AI on better tech because they're using AI on it is going to be interesting. So it is going to be interesting. So it is going to be interesting. So So that's that's going to be pretty So that's that's going to be pretty So that's that's going to be pretty cool. So as the cost cool. So as the cost cool. So as the cost uh of these things comes down, uh I uh of these things comes down, uh I uh of these things comes down, uh I think we'll see you know, more

think we'll see you know, more think we'll see you know, more proliferation of of health care proliferation of of health care proliferation of of health care initiatives and that's for like you initiatives and that's for like you initiatives and that's for like you know, infant mortality and all that know, infant mortality and all that know, infant mortality and all that stuff is much more interesting for me stuff is much more interesting for me stuff is much more interesting for me than than than Ozempic face or whatever that Ozempic face or whatever that Ozempic face or whatever that >> [laughter] >> [laughter] >> [laughter] >> Well, I mean, it seems like basically >> Well, I mean, it seems like basically >> Well, I mean, it seems like basically people chose to carry on doing the people chose to carry on doing the people chose to carry on doing the stupid things that they shouldn't do stupid things that they shouldn't do stupid things that they shouldn't do without any consequence. It takes away without any consequence. It takes away without any consequence. It takes away the consequence of terrible dietary the consequence of terrible dietary the consequence of terrible dietary decisions and and not exercising and all decisions and and not exercising and all decisions and and not exercising and all that. that. that. Yeah. But I don't know it's it that I I Yeah. But I don't know it's it that I I Yeah. But I don't know it's it that I I agree I AI I think that the potential agree I AI I think that the potential agree I AI I think that the potential could kind of democratize access to could kind of democratize access to could kind of democratize access to science I think is incredible. Though science I think is incredible. Though science I think is incredible. Though you know, we talked before about the you know, we talked before about the you know, we talked before about the impact on on both having you know, impact on on both having you know, impact on on both having you know, no junior developers anymore etc. Though no junior developers anymore etc. Though no junior developers anymore etc. Though I did hear someone say this week that I did hear someone say this week that I did hear someone say this week that they were confront they were shocked by they were confront they were shocked by they were confront they were shocked by the fact that a junior developer is the fact that a junior developer is the fact that a junior developer is actually cheaper than the amount of actually cheaper than the amount of actually cheaper than the amount of tokens that they're consuming Mhm. uh tokens that they're consuming Mhm. uh tokens that they're consuming Mhm. uh >> [clears throat] >> [clears throat] >> [clears throat] >> to do all this stuff. Well, that's it. >> to do all this stuff. Well, that's it. >> to do all this stuff. Well, that's it. Yeah, I saw that too. And so it was Yeah, I saw that too. And so it was Yeah, I saw that too. And so it was like, oh we're hiring junior developers like, oh we're hiring junior developers like, oh we're hiring junior developers to save on our token budget. I'm like, to save on our token budget. I'm like, to save on our token budget. I'm like, like wasn't it the opposite last year?

like wasn't it the opposite last year? like wasn't it the opposite last year? It's like we're we're firing people to It's like we're we're firing people to It's like we're we're firing people to use AI. Now you realize the OPEX for AI use AI. Now you realize the OPEX for AI use AI. Now you realize the OPEX for AI Um I was talking to someone the other Um I was talking to someone the other Um I was talking to someone the other day. It's like, oh we want to like you day. It's like, oh we want to like you day. It's like, oh we want to like you know, uh know, uh know, uh you know, analyze all of our YouTube you know, analyze all of our YouTube you know, analyze all of our YouTube videos and come up with all this stuff. videos and come up with all this stuff. videos and come up with all this stuff. We want to turns out like doing this We want to turns out like doing this We want to turns out like doing this stuff is like really expensive. Yeah. Oh stuff is like really expensive. Yeah. Oh stuff is like really expensive. Yeah. Oh yeah, yeah. Uh it's it's just not yeah, yeah. Uh it's it's just not yeah, yeah. Uh it's it's just not feasible. Going back to the LinkedIn feasible. Going back to the LinkedIn feasible. Going back to the LinkedIn discussion, probably one of the reasons discussion, probably one of the reasons discussion, probably one of the reasons LinkedIn doesn't use AI to filter spam LinkedIn doesn't use AI to filter spam LinkedIn doesn't use AI to filter spam is that it would be a lot of operational is that it would be a lot of operational is that it would be a lot of operational costs for them. Even though they do, I costs for them. Even though they do, I costs for them. Even though they do, I know like Google does with YouTube know like Google does with YouTube know like Google does with YouTube because they they go and look for any because they they go and look for any because they they go and look for any kind of mention of election related kind of mention of election related kind of mention of election related stuff they will ban ban that. Yeah. And stuff they will ban ban that. Yeah. And stuff they will ban ban that. Yeah. And they do like copyright checking and all they do like copyright checking and all they do like copyright checking and all that Yeah, yeah. But I think a lot of that Yeah, yeah. But I think a lot of that Yeah, yeah. But I think a lot of that is algorithmic and so this is the that is algorithmic and so this is the that is algorithmic and so this is the problem. A lot of folks think that problem. A lot of folks think that problem. A lot of folks think that everyone's using gen AI and using everyone's using gen AI and using everyone's using gen AI and using NBL 72s of whatever variety to do a lot NBL 72s of whatever variety to do a lot NBL 72s of whatever variety to do a lot of stuff. Actually, a lot of the stuff of stuff. Actually, a lot of the stuff of stuff. Actually, a lot of the stuff is is is as cheap as possible to run as cheap as possible to run as cheap as possible to run um ML, right? Mhm. Uh you know, when I um ML, right? Mhm. Uh you know, when I um ML, right? Mhm. Uh you know, when I was at um was at um was at um NAB Show NAB Show NAB Show ML for the win, you know, hardly anyone ML for the win, you know, hardly anyone ML for the win, you know, hardly anyone is using generative AI except for is using generative AI except for is using generative AI except for just experimental stuff like uh meta just experimental stuff like uh meta just experimental stuff like uh meta tagging, you know, tagging, you know, tagging, you know, using scene detection for meta tagging, using scene detection for meta tagging, using scene detection for meta tagging, but even then but even then but even then um nobody wants to have this um nobody wants to have this um nobody wants to have this uh always-on AI monitoring, right?

uh always-on AI monitoring, right? uh always-on AI monitoring, right? And I don't know where I mentioned this. And I don't know where I mentioned this. And I don't know where I mentioned this. Maybe it was last week. Maybe it was last week. Maybe it was last week. Um but it costs too much. Um but it costs too much. Um but it costs too much. And so what [clears throat] a lot of And so what [clears throat] a lot of And so what [clears throat] a lot of customers are asking for as they see customers are asking for as they see customers are asking for as they see these massive bills is a cheaper way. these massive bills is a cheaper way. these massive bills is a cheaper way. And a lot of that ends up that cheaper And a lot of that ends up that cheaper And a lot of that ends up that cheaper way ends up being more of a reactive way ends up being more of a reactive way ends up being more of a reactive modality rather than a predictive. modality rather than a predictive. modality rather than a predictive. Sound familiar? Mhm. Sound familiar? Mhm. Sound familiar? Mhm. It's about how do we It's about how do we It's about how do we just improve our our ability to detect just improve our our ability to detect just improve our our ability to detect and respond well, more of how do we and respond well, more of how do we and respond well, more of how do we respond quickly and remediate uh when an respond quickly and remediate uh when an respond quickly and remediate uh when an incident does happen. And what they incident does happen. And what they incident does happen. And what they ended up doing is reducing their ended up doing is reducing their ended up doing is reducing their um token consumption by 95% um token consumption by 95% um token consumption by 95% and you know, dropping the cost of the and you know, dropping the cost of the and you know, dropping the cost of the solution by 95% solution by 95% solution by 95% which of course the hyperscale wasn't which of course the hyperscale wasn't which of course the hyperscale wasn't too fond of. too fond of. too fond of. But guess what? That's where practical But guess what? That's where practical But guess what? That's where practical lies. And so lies. And so lies. And so you know, I just really scratch my head you know, I just really scratch my head you know, I just really scratch my head wondering what's going on, you know, we wondering what's going on, you know, we wondering what's going on, you know, we we see like the hyperscalers claim that we see like the hyperscalers claim that we see like the hyperscalers claim that their AI businesses are going up or the their AI businesses are going up or the their AI businesses are going up or the cloud guys new cloud guys. But then you cloud guys new cloud guys. But then you cloud guys new cloud guys. But then you you have to really wonder, okay, how you have to really wonder, okay, how you have to really wonder, okay, how much of that boost did and I posted much of that boost did and I posted much of that boost did and I posted this. How much of that boost boost is this. How much of that boost boost is this. How much of that boost boost is for AI-generated stupid cat videos?

for AI-generated stupid cat videos? for AI-generated stupid cat videos? Right? Um because you know, Nana banana Right? Um because you know, Nana banana Right? Um because you know, Nana banana kind of went bonkers kind of went bonkers kind of went bonkers in the last 3 months, right? in the last 3 months, right? in the last 3 months, right? Uh so how much of that is because of Uh so how much of that is because of Uh so how much of that is because of you know, that kind of use? you know, that kind of use? you know, that kind of use? Right. And how much of it is enterprise Right. And how much of it is enterprise Right. And how much of it is enterprise doing stuff, right? I mean, yeah, a lot doing stuff, right? I mean, yeah, a lot doing stuff, right? I mean, yeah, a lot of that is creation of [clears throat] of that is creation of [clears throat] of that is creation of [clears throat] AI slop for the most part, right? Right. AI slop for the most part, right? Right. AI slop for the most part, right? Right. And um And um And um you know uh Well, it's yeah, this is you know uh Well, it's yeah, this is you know uh Well, it's yeah, this is it's hitting the fan if you look at the it's hitting the fan if you look at the it's hitting the fan if you look at the uh Open AI IPO analysis, you know, the uh Open AI IPO analysis, you know, the uh Open AI IPO analysis, you know, the the one of the interesting metrics I've the one of the interesting metrics I've the one of the interesting metrics I've seen is the seen is the seen is the revenue per gigawatt, right? For data revenue per gigawatt, right? For data revenue per gigawatt, right? For data centers, right? So it's something like centers, right? So it's something like centers, right? So it's something like 10 billion per gigawatt 10 billion per gigawatt 10 billion per gigawatt today today today um and something like that, but the the um and something like that, but the the um and something like that, but the the data center costs about you know, 40 data center costs about you know, 40 data center costs about you know, 40 billion. billion. billion. So you really need to run the data So you really need to run the data So you really need to run the data center for about you know, Yeah. four or center for about you know, Yeah. four or center for about you know, Yeah. four or five years to recoup your investment on five years to recoup your investment on five years to recoup your investment on the data center. So the the revenue per the data center. So the the revenue per the data center. So the the revenue per gigawatt is not not there. This is not gigawatt is not not there. This is not gigawatt is not not there. This is not there.

there. there. Yeah. Yeah. Yeah. Well, and I I think that's exaggerated Well, and I I think that's exaggerated Well, and I I think that's exaggerated too cuz they're just doing simple math. too cuz they're just doing simple math. too cuz they're just doing simple math. The thing is is The thing is is The thing is is um um um you know, SemiAnalysis you know, SemiAnalysis you know, SemiAnalysis came out with I don't know if they even came out with I don't know if they even came out with I don't know if they even coined the term, but it's a concept coined the term, but it's a concept coined the term, but it's a concept we've already talked about on IoT Coffee we've already talked about on IoT Coffee we've already talked about on IoT Coffee Talk. It's about um Talk. It's about um Talk. It's about um uh they call it token efficiency uh they call it token efficiency uh they call it token efficiency but for what you know what we've been but for what you know what we've been but for what you know what we've been referring to it as you know mapping referring to it as you know mapping referring to it as you know mapping actual outcome value to actual outcome value to actual outcome value to the number of tokens actually required the number of tokens actually required the number of tokens actually required to deliver that that to deliver that that to deliver that that value which varies right and so token value which varies right and so token value which varies right and so token efficiency efficiency efficiency actually is the wrong way of looking at actually is the wrong way of looking at actually is the wrong way of looking at it because you have to look at it in it because you have to look at it in it because you have to look at it in terms of the actual consistency terms of the actual consistency terms of the actual consistency of pricing being able to price an of pricing being able to price an of pricing being able to price an outcome and manage outcome and manage outcome and manage make sure that on the back end make sure that on the back end make sure that on the back end you're profitable right because the cost you're profitable right because the cost you're profitable right because the cost can be variable I don't think people see can be variable I don't think people see can be variable I don't think people see that yet in fact I talked to one you that yet in fact I talked to one you that yet in fact I talked to one you know know know that company that you're referring to that company that you're referring to that company that you're referring to about that topic and about that topic and about that topic and it's a big blind spot it's a big blind spot it's a big blind spot and and and and so yeah it's the and so yeah it's the and so yeah it's the the all

the all the all you can't just take prevailing token you can't just take prevailing token you can't just take prevailing token price okay multiply it by price okay multiply it by price okay multiply it by how much your gigawatt of AI compute can how much your gigawatt of AI compute can how much your gigawatt of AI compute can generate and then think that that's generate and then think that that's generate and then think that that's revenue that's that's right at that one revenue that's that's right at that one revenue that's that's right at that one given point in time but what happens as given point in time but what happens as given point in time but what happens as the price of tokens continues to drop the price of tokens continues to drop the price of tokens continues to drop when companies like deep seek and others when companies like deep seek and others when companies like deep seek and others they continue to they continue to they continue to um um um you know force the pricing down right you know force the pricing down right you know force the pricing down right is what they've done right but there's is what they've done right but there's is what they've done right but there's the cost per token but there's also the the cost per token but there's also the the cost per token but there's also the definitely is going down which is great definitely is going down which is great definitely is going down which is great but the inefficiency is the frontier but but the inefficiency is the frontier but but the inefficiency is the frontier but the other question is where's the the other question is where's the the other question is where's the revenue is there enough revenue being revenue is there enough revenue being revenue is there enough revenue being generated for a 40 billion dollar data generated for a 40 billion dollar data generated for a 40 billion dollar data center like basically you need 40 center like basically you need 40 center like basically you need 40 billion in revenue to pay for a 40 billion in revenue to pay for a 40 billion in revenue to pay for a 40 billion dollar data center right I mean billion dollar data center right I mean billion dollar data center right I mean at the end of the day so at the end of the day so at the end of the day so is that being generated is there enough is that being generated is there enough is that being generated is there enough and this is where the open AI IPO I and this is where the open AI IPO I and this is where the open AI IPO I think is going to be is running into think is going to be is running into think is going to be is running into some some some speed bumps right is like they they sort speed bumps right is like they they sort speed bumps right is like they they sort of missed some of the revenue targets of missed some of the revenue targets of missed some of the revenue targets recently and people are questioning you recently and people are questioning you recently and people are questioning you know can you really IPO know can you really IPO know can you really IPO in this environment with open AI and I in this environment with open AI and I in this environment with open AI and I think I'm afraid that if they end up think I'm afraid that if they end up think I'm afraid that if they end up scrapping their IPO could have some scrapping their IPO could have some scrapping their IPO could have some other follow on kind of market other follow on kind of market other follow on kind of market consequences and consequences and consequences and get people skittish on all of their I've get people skittish on all of their I've get people skittish on all of their I've been putting things down at this but been putting things down at this but been putting things down at this but I've not been following the the the the

I've not been following the the the the I've not been following the the the the Musk versus Altman trial Musk versus Altman trial Musk versus Altman trial which is too [clears throat] much this which is too [clears throat] much this which is too [clears throat] much this week but I mean that's that's obviously week but I mean that's that's obviously week but I mean that's that's obviously clearly a potential spanner in the IPO clearly a potential spanner in the IPO clearly a potential spanner in the IPO plan but I wonder if the IPO were to plan but I wonder if the IPO were to plan but I wonder if the IPO were to I kind of think it's unlikely that it I kind of think it's unlikely that it I kind of think it's unlikely that it will but were it to falter you know what will but were it to falter you know what will but were it to falter you know what what impact would that have and it would what impact would that have and it would what impact would that have and it would definitely shake confidence but maybe it definitely shake confidence but maybe it definitely shake confidence but maybe it would also cause people to be a little would also cause people to be a little would also cause people to be a little bit more focused on what's real versus bit more focused on what's real versus bit more focused on what's real versus what's not what's not what's not >> well I mean think about how much >> well I mean think about how much >> well I mean think about how much everyone is you know how much everyone everyone is you know how much everyone everyone is you know how much everyone has loaded up their RPU RPOs on supposed has loaded up their RPU RPOs on supposed has loaded up their RPU RPOs on supposed um um um open AI related contracts open AI related contracts open AI related contracts aren't we aren't we still negating the aren't we aren't we still negating the aren't we aren't we still negating the the real issue right I mean the real issue right I mean the real issue right I mean yeah I'm yeah I'm yeah I'm I'm sorry welcome to welcome to FA and I'm sorry welcome to welcome to FA and I'm sorry welcome to welcome to FA and FO Friday FO Friday FO Friday >> [laughter] >> [laughter] >> [laughter] >> I was about to say that they're all FA >> I was about to say that they're all FA >> I was about to say that they're all FA and and and FOing yeah well yes because I mean we're FOing yeah well yes because I mean we're FOing yeah well yes because I mean we're still skirting the real issue damn grid still skirting the real issue damn grid still skirting the real issue damn grid resilience how are you resilience how are you resilience how are you it it it energy to do all of this right energy to do all of this right energy to do all of this right so now you have to build your own power so now you have to build your own power so now you have to build your own power supply for each data center and not rely supply for each data center and not rely supply for each data center and not rely on the public grid which now boost your on the public grid which now boost your on the public grid which now boost your cost to like the moon basically so cost to like the moon basically so cost to like the moon basically so that's a whole other this is why the that's a whole other this is why the that's a whole other this is why the cost of the data center is even though cost of the data center is even though cost of the data center is even though the cost per token may be going down the the cost per token may be going down the the cost per token may be going down the cost per producing the token cost per cost per producing the token cost per cost per producing the token cost per data center is going up because and if data center is going up because and if data center is going up because and if you can get through the planning process

you can get through the planning process you can get through the planning process >> yeah assuming you can get through the >> yeah assuming you can get through the >> yeah assuming you can get through the not in my backyard protests and not in my backyard protests and not in my backyard protests and everything else going on right it's a everything else going on right it's a everything else going on right it's a it's expensive and it's difficult it's expensive and it's difficult it's expensive and it's difficult >> okay so so you you got to build you got >> okay so so you you got to build you got >> okay so so you you got to build you got to build your own micro grid with some to build your own micro grid with some to build your own micro grid with some level of sustainable energy right so level of sustainable energy right so level of sustainable energy right so you've got some wind you got some solar you've got some wind you got some solar you've got some wind you got some solar make sure the lithium crystals you know make sure the lithium crystals you know make sure the lithium crystals you know you need to cool this so wait a you need to cool this so wait a you need to cool this so wait a minute let's run some water through minute let's run some water through minute let's run some water through there where is that water coming from there where is that water coming from there where is that water coming from the infinite resources of the ground the infinite resources of the ground the infinite resources of the ground that's that's how that's that's how that's that's how >> [laughter] >> [laughter] >> [laughter] >> I mean it it's comical I mean you know >> I mean it it's comical I mean you know >> I mean it it's comical I mean you know from my perspective it's comical for from my perspective it's comical for from my perspective it's comical for those that understand energy delivery to those that understand energy delivery to those that understand energy delivery to solution being provided and what the solution being provided and what the solution being provided and what the dependencies are each step of the way I dependencies are each step of the way I dependencies are each step of the way I saw some some analysis that I think saw some some analysis that I think saw some some analysis that I think someone was trying to justify their someone was trying to justify their someone was trying to justify their the data center and the water uses and the data center and the water uses and the data center and the water uses and they said well you can't use you know a they said well you can't use you know a they said well you can't use you know a million million gallons a day and they million million gallons a day and they million million gallons a day and they said oh don't worry we're going to use said oh don't worry we're going to use said oh don't worry we're going to use the water at night so the water at night so the water at night so >> [laughter] >> it's like that's still a million gallons >> it's like that's still a million gallons a day it's just at night it's you know a day it's just at night it's you know a day it's just at night it's you know well the sad I mean the sad thing is at well the sad I mean the sad thing is at well the sad I mean the sad thing is at the moment when you say renewable energy the moment when you say renewable energy the moment when you say renewable energy that would be a great thing but you know that would be a great thing but you know that would be a great thing but you know what you've seen is is companies that I what you've seen is is companies that I what you've seen is is companies that I shall not name putting shall not name putting shall not name putting diesel generators in containers out the diesel generators in containers out the diesel generators in containers out the back of the data center and back of the data center and back of the data center and then saying that they're not and and you then saying that they're not and and you then saying that they're not and and you know saying that the local the local know saying that the local the local know saying that the local the local community that's that's suddenly community that's that's suddenly community that's that's suddenly pollution oh no that's not that's not pollution oh no that's not that's not pollution oh no that's not that's not happening at all and

happening at all and happening at all and no they're they'll use diesel they use no they're they'll use diesel they use no they're they'll use diesel they use whatever fuel they need but yeah that's whatever fuel they need but yeah that's whatever fuel they need but yeah that's that's a big knot to untie and going that's a big knot to untie and going that's a big knot to untie and going back to the original point if you're not back to the original point if you're not back to the original point if you're not generating 40 40 billion 50 billion per generating 40 40 billion 50 billion per generating 40 40 billion 50 billion per data center over four or five years to data center over four or five years to data center over four or five years to pay it back then you know is it even pay it back then you know is it even pay it back then you know is it even worth it worth it worth it >> and then you know consider that um >> and then you know consider that um >> and then you know consider that um >> [clears throat] >> [clears throat] >> [clears throat] >> yeah yeah it was funny if you listen to >> yeah yeah it was funny if you listen to >> yeah yeah it was funny if you listen to the Microsoft um earnings call the first the Microsoft um earnings call the first the Microsoft um earnings call the first question that was asked by the analysts question that was asked by the analysts question that was asked by the analysts was how is all this going to be paid for was how is all this going to be paid for was how is all this going to be paid for and Amy Hood and I don't think Amy or and Amy Hood and I don't think Amy or and Amy Hood and I don't think Amy or Satya did a really good job of answering Satya did a really good job of answering Satya did a really good job of answering you know you know you know basically basically basically we have no freaking idea and this is we have no freaking idea and this is we have no freaking idea and this is like three and a half years like three and a half years like three and a half years these all these guys are making these these all these guys are making these these all these guys are making these huge huge huge this FOMO bet right this FOMO bet right this FOMO bet right and yeah the math doesn't work out at and yeah the math doesn't work out at and yeah the math doesn't work out at all all all you know even if you assume that you know even if you assume that you know even if you assume that advertising is going to subsidize a lot advertising is going to subsidize a lot advertising is going to subsidize a lot of this stuff right the advertising of this stuff right the advertising of this stuff right the advertising industry in totality is only industry in totality is only industry in totality is only like I think it's around 900 million at like I think it's around 900 million at like I think it's around 900 million at like a like a like a no billion so it's not a trillion but no billion so it's not a trillion but no billion so it's not a trillion but you can't assume that you can't assume that you can't assume that AI quote unquote AI AI quote unquote AI AI quote unquote AI the TAM for AI is that entire the TAM for AI is that entire the TAM for AI is that entire market it's not because the AI is just a market it's not because the AI is just a market it's not because the AI is just a tool right tool right tool right um

um um how are they going to make their money how are they going to make their money how are they going to make their money right unless enterprises are really right unless enterprises are really right unless enterprises are really getting a lot of value out of this stuff getting a lot of value out of this stuff getting a lot of value out of this stuff but but but you know there's conflicting signals you know there's conflicting signals you know there's conflicting signals how much how much how much of the quote unquote demand and there of the quote unquote demand and there of the quote unquote demand and there should be a study on this term demand should be a study on this term demand should be a study on this term demand what the hell does it mean because you what the hell does it mean because you what the hell does it mean because you hear a lot of the Wall Street guys talk hear a lot of the Wall Street guys talk hear a lot of the Wall Street guys talk about well there's so much demand like about well there's so much demand like about well there's so much demand like yeah demand for like the lower level yeah demand for like the lower level yeah demand for like the lower level stuff but what about demand up here what stuff but what about demand up here what stuff but what about demand up here what is it well it's infinite demand well is it well it's infinite demand well is it well it's infinite demand well yeah of course if you give stuff out for yeah of course if you give stuff out for yeah of course if you give stuff out for free if you give cocaine out for free free if you give cocaine out for free free if you give cocaine out for free guess what you might AI is a hell of a guess what you might AI is a hell of a guess what you might AI is a hell of a drug baby drug baby drug baby um of course it's going to look like um of course it's going to look like um of course it's going to look like there's infinite demand but as soon as there's infinite demand but as soon as there's infinite demand but as soon as you start charging a crap ton you know you know if you can price it like cocaine if you can price it like cocaine if you can price it like cocaine then yeah you might you might you might then yeah you might you might you might then yeah you might you might you might make it but if you can't because what make it but if you can't because what make it but if you can't because what you're selling is kind of worthless you're selling is kind of worthless you're selling is kind of worthless well and the numbers we talk saying you well and the numbers we talk saying you well and the numbers we talk saying you know when we talk about kind of the know when we talk about kind of the know when we talk about kind of the investment in data centers and the investment in data centers and the investment in data centers and the investment in electricity I was about investment in electricity I was about investment in electricity I was about the other day the whole global annual the other day the whole global annual the other day the whole global annual investment in generating electricity investment in generating electricity investment in generating electricity fuel operations building new facility fuel operations building new facility fuel operations building new facility tops out around 1.5 trillion and if you tops out around 1.5 trillion and if you tops out around 1.5 trillion and if you look at that against the numbers that look at that against the numbers that look at that against the numbers that Microsoft are quoting the the you know Microsoft are quoting the the you know Microsoft are quoting the the you know that that that open AI are quoting in terms of open AI are quoting in terms of open AI are quoting in terms of infrastructure spend on data center I

infrastructure spend on data center I infrastructure spend on data center I mean it kind of like mean it kind of like mean it kind of like it's a shocking amount of money that it's a shocking amount of money that it's a shocking amount of money that being being budgeted and like I said if being being budgeted and like I said if being being budgeted and like I said if if there isn't a clear if there isn't a if there isn't a clear if there isn't a if there isn't a clear if there isn't a clear path to return on that investment clear path to return on that investment clear path to return on that investment then how long does the patience of how then how long does the patience of how then how long does the patience of how long does people's patience last well long does people's patience last well long does people's patience last well that's the thing is I I think that's the thing is I I think that's the thing is I I think you know people's patience are starting you know people's patience are starting you know people's patience are starting to run short and so now I mean what was to run short and so now I mean what was to run short and so now I mean what was it there's a fortune article that came it there's a fortune article that came it there's a fortune article that came out about Google's earnings recently and out about Google's earnings recently and out about Google's earnings recently and there's like I think about 27 or 37,000 there's like I think about 27 or 37,000 there's like I think about 27 or 37,000 in in in 37 billion in other income and that 37 billion in other income and that 37 billion in other income and that happened to be unrealized happened to be unrealized happened to be unrealized securities gains from their position in securities gains from their position in securities gains from their position in Anthropic Anthropic Anthropic which which which you know the article talks about how you know the article talks about how you know the article talks about how they can throttle that value based on they can throttle that value based on they can throttle that value based on how much they invest so that's cash how much they invest so that's cash how much they invest so that's cash going in that inflates going in that inflates going in that inflates other income other income other income so so so I mean what's I mean what's I mean what's what's going on here do you know what what's going on here do you know what what's going on here do you know what I'm saying it's a high how I'm saying it's a high how I'm saying it's a high how how profitable is the cuz one of the how profitable is the cuz one of the how profitable is the cuz one of the things that you do notice the more things that you do notice the more things that you do notice the more these guys claim that they have an AI these guys claim that they have an AI these guys claim that they have an AI neo cloudish kind of business in their neo cloudish kind of business in their neo cloudish kind of business in their cloud portfolio the faster cloud portfolio the faster cloud portfolio the faster their operating margins go down their operating margins go down their operating margins go down and the faster

and the faster and the faster I assume their gross margin goes down so I assume their gross margin goes down so I assume their gross margin goes down so you know you know you know I've said this I've said this I've said this also on iot coffee talk also on iot coffee talk also on iot coffee talk for actually a couple years now for actually a couple years now for actually a couple years now AI is a bad business for hyperscalers AI is a bad business for hyperscalers AI is a bad business for hyperscalers and they know it they should if they and they know it they should if they and they know it they should if they don't but I have to hats off to Satya don't but I have to hats off to Satya don't but I have to hats off to Satya though because last year though because last year though because last year this is after he got on the this is after he got on the this is after he got on the what is it I think it was Darkash Patel what is it I think it was Darkash Patel what is it I think it was Darkash Patel show he and show he and show he and uh uh uh Dylan Patel they went and did a tour of Dylan Patel they went and did a tour of Dylan Patel they went and did a tour of the the Microsoft data centers and they the the Microsoft data centers and they the the Microsoft data centers and they interviewed Satya one [clears throat] of interviewed Satya one [clears throat] of interviewed Satya one [clears throat] of the things he was very honest about is the things he was very honest about is the things he was very honest about is the depreciation accelerated the depreciation accelerated the depreciation accelerated depreciation and how they have to be depreciation and how they have to be depreciation and how they have to be very measured in how the investment are very measured in how the investment are very measured in how the investment are scheduled over time and you know scheduled over time and you know scheduled over time and you know obviously there's an anxiety for them to obviously there's an anxiety for them to obviously there's an anxiety for them to get as much capacity get as much capacity get as much capacity because of their fomo agenda because of their fomo agenda because of their fomo agenda to secure as much capacity as possible to secure as much capacity as possible to secure as much capacity as possible and deliver that capacity to monetize and deliver that capacity to monetize and deliver that capacity to monetize but you know they none of these guys but you know they none of these guys but you know they none of these guys ever ask themselves it seems the ever ask themselves it seems the ever ask themselves it seems the question of how profitable is that question of how profitable is that question of how profitable is that monetization monetization monetization so you make a trillion dollars so you make a trillion dollars so you make a trillion dollars at a negative profit at a negative profit at a negative profit what is what is that equate to I think I what is what is that equate to I think I what is what is that equate to I think I think it's those similar business it's

think it's those similar business it's think it's those similar business it's similar argument to what you saw in the similar argument to what you saw in the similar argument to what you saw in the cellular industry when the 3G when the cellular industry when the 3G when the cellular industry when the 3G when the first kind of really expensive license first kind of really expensive license first kind of really expensive license set that was released at least in Europe set that was released at least in Europe set that was released at least in Europe was the 3G license set was the 3G license set was the 3G license set and you know I was in in talk I was in and you know I was in in talk I was in and you know I was in in talk I was in in 02 at the time it came down to in 02 at the time it came down to in 02 at the time it came down to it was a cost of doing business that if it was a cost of doing business that if it was a cost of doing business that if you didn't have a 3G license as a telco you didn't have a 3G license as a telco you didn't have a 3G license as a telco clearly you were out of the game clearly you were out of the game clearly you were out of the game and and the math of what they cost and and the math of what they cost and and the math of what they cost versus you know what they would generate versus you know what they would generate versus you know what they would generate we looked at it in 02 from two we looked at it in 02 from two we looked at it in 02 from two perspectives we looked at all the lovely perspectives we looked at all the lovely perspectives we looked at all the lovely revenue we're going to get from content revenue we're going to get from content revenue we're going to get from content and blah blah blah that was one model and blah blah blah that was one model and blah blah blah that was one model and then the other model was value of and then the other model was value of and then the other model was value of the stock price with a 3G license value the stock price with a 3G license value the stock price with a 3G license value of the stock price without a 3G license of the stock price without a 3G license of the stock price without a 3G license and the difference between those two and the difference between those two and the difference between those two numbers was more than the cost of the numbers was more than the cost of the numbers was more than the cost of the licenses and we spent 20 billion 16 licenses and we spent 20 billion 16 licenses and we spent 20 billion 16 billion something crazy on licenses billion something crazy on licenses billion something crazy on licenses across the UK the Europe etc across the UK the Europe etc across the UK the Europe etc I think the same is true now if you I think the same is true now if you I think the same is true now if you don't have a honking great big don't have a honking great big don't have a honking great big investment number in your financials investment number in your financials investment number in your financials that says this is what you're going to that says this is what you're going to that says this is what you're going to spend on AI and you don't have a you spend on AI and you don't have a you spend on AI and you don't have a you know know know a chat GPT or you don't have a dog in a chat GPT or you don't have a dog in a chat GPT or you don't have a dog in the fight then the fight then the fight then are you in the game so it's almost I are you in the game so it's almost I are you in the game so it's almost I don't think it's even a question about don't think it's even a question about don't think it's even a question about profitability it's about buying a chance profitability it's about buying a chance profitability it's about buying a chance to be you know at the table in the next to be you know at the table in the next to be you know at the table in the next in in the next round at least in in the next round at least in in the next round at least >> yeah yeah but you know that >> yeah yeah but you know that >> yeah yeah but you know that that is the but then that's the gamble that is the but then that's the gamble that is the but then that's the gamble right after and sometime the sometime right after and sometime the sometime right after and sometime the sometime the money will come in in the future the money will come in in the future the money will come in in the future like okay when like okay when like okay when it'll be worth it we'll look back and it'll be worth it we'll look back and it'll be worth it we'll look back and it'll all be worth it I

it'll all be worth it I it'll all be worth it I I know well just have to find the right I know well just have to find the right I know well just have to find the right use cases and that's what's still you use cases and that's what's still you use cases and that's what's still you know when you build the general tech know when you build the general tech know when you build the general tech it's like well let's see what we're it's like well let's see what we're it's like well let's see what we're going to use it for I mean obviously going to use it for I mean obviously going to use it for I mean obviously taking meeting minutes you know document taking meeting minutes you know document taking meeting minutes you know document development there's like some use cases development there's like some use cases development there's like some use cases that are really sticking that are really sticking that are really sticking what I like about edge AI just to pivot what I like about edge AI just to pivot what I like about edge AI just to pivot to that for a second is that it to that for a second is that it to that for a second is that it typically starts with a business problem typically starts with a business problem typically starts with a business problem that needs to be solved and then you that needs to be solved and then you that needs to be solved and then you apply the tech to solve the problem so apply the tech to solve the problem so apply the tech to solve the problem so you kind of know you kind of know you kind of know like what you you can spend to solve like what you you can spend to solve like what you you can spend to solve that problem to begin with as opposed to that problem to begin with as opposed to that problem to begin with as opposed to let's build a general purpose chatbot let's build a general purpose chatbot let's build a general purpose chatbot thing and then see what happens so thing and then see what happens so thing and then see what happens so that's why I think on the cloud side that's why I think on the cloud side that's why I think on the cloud side they're struggling with finding they're struggling with finding they're struggling with finding monetizable use cases like is it worth monetizable use cases like is it worth monetizable use cases like is it worth the tokens is it worth the operational the tokens is it worth the operational the tokens is it worth the operational cost to solve the problem in this way cost to solve the problem in this way cost to solve the problem in this way and in some cases it's not yet so and in some cases it's not yet so and in some cases it's not yet so but sorry that's one of the challenges I but sorry that's one of the challenges I but sorry that's one of the challenges I see is that you know look at it from a see is that you know look at it from a see is that you know look at it from a cloud provider's perspective you want cloud provider's perspective you want cloud provider's perspective you want that edge AI components to be that edge AI components to be that edge AI components to be commoditized you want the value to commoditized you want the value to commoditized you want the value to accrue to your you know to the back end accrue to your you know to the back end accrue to your you know to the back end analytics the back end magic and you analytics the back end magic and you analytics the back end magic and you know the guys who are sitting in that know the guys who are sitting in that know the guys who are sitting in that back end have very very deep pockets and back end have very very deep pockets and back end have very very deep pockets and the guys that are sitting at the edge the guys that are sitting at the edge the guys that are sitting at the edge with a few notable exceptions generally with a few notable exceptions generally with a few notable exceptions generally don't and so when it comes down to the don't and so when it comes down to the don't and so when it comes down to the battle of who wins yes I think AI has a battle of who wins yes I think AI has a battle of who wins yes I think AI has a much clearer business case but if you've much clearer business case but if you've much clearer business case but if you've got a bunch of hostile folks over here got a bunch of hostile folks over here got a bunch of hostile folks over here who are trying to gut the price of what who are trying to gut the price of what who are trying to gut the price of what you're providing can you as an AI you're providing can you as an AI you're providing can you as an AI provider be successful or will they kill provider be successful or will they kill provider be successful or will they kill you off regardless of whether or not you off regardless of whether or not you off regardless of whether or not you're generating ROI you're generating ROI you're generating ROI cuz free free is a a big persuader and I

cuz free free is a a big persuader and I cuz free free is a a big persuader and I think a lot a lot of a lot of the the think a lot a lot of a lot of the the think a lot a lot of a lot of the the platform providers are looking at the platform providers are looking at the platform providers are looking at the edge and thinking that stuff needs to be edge and thinking that stuff needs to be edge and thinking that stuff needs to be free you know we need to make it free so free you know we need to make it free so free you know we need to make it free so that the the the generation of data is that the the the generation of data is that the the the generation of data is no longer you know doesn't cost anything no longer you know doesn't cost anything no longer you know doesn't cost anything and we need to and we need to and we need to it's not that difficult to to prove that it's not that difficult to to prove that it's not that difficult to to prove that out right I mean if if we just take out right I mean if if we just take out right I mean if if we just take again and I I I agree 100% with Pete again and I I I agree 100% with Pete again and I I I agree 100% with Pete because he's he's talking very sensical because he's he's talking very sensical because he's he's talking very sensical in terms of edge AI and the business in terms of edge AI and the business in terms of edge AI and the business problem that wants to be solved so we problem that wants to be solved so we problem that wants to be solved so we clearly understand what problem it is clearly understand what problem it is clearly understand what problem it is that we're trying to solve that we're trying to solve that we're trying to solve and and we're applying the tech to it and and we're applying the tech to it and and we're applying the tech to it and you don't have to say oh it's it's and you don't have to say oh it's it's and you don't have to say oh it's it's AI right there you you are solving a AI right there you you are solving a AI right there you you are solving a problem it's not about the tech if we're problem it's not about the tech if we're problem it's not about the tech if we're having the conversation about the tech having the conversation about the tech having the conversation about the tech we're having the wrong conversation we're having the wrong conversation we're having the wrong conversation we're literally saying there's a problem we're literally saying there's a problem we're literally saying there's a problem here and we're going to solve it by here and we're going to solve it by here and we're going to solve it by getting as close to that as possible and getting as close to that as possible and getting as close to that as possible and we're going to do everything there now we're going to do everything there now we're going to do everything there now if you're doing it right you're reducing if you're doing it right you're reducing if you're doing it right you're reducing the amount of data that you're sending the amount of data that you're sending the amount of data that you're sending back to the center cloud and if you're doing that you're pissing and if you're doing that you're pissing off the CSPs because they they're off the CSPs because they they're off the CSPs because they they're they're they're not getting those they're they're not getting those they're they're not getting those workloads and you're pushing those workloads and you're pushing those workloads and you're pushing those workloads out to the edge workloads out to the edge workloads out to the edge >> but that I mean yeah and so >> but that I mean yeah and so >> but that I mean yeah and so the point I was trying to make earlier the point I was trying to make earlier the point I was trying to make earlier before Alister like freaking interrupted before Alister like freaking interrupted before Alister like freaking interrupted me me me >> [laughter] >> just kidding dude

>> just kidding dude not really but not really but not really but was was was you know neuromorphic you know neuromorphic you know neuromorphic um um um a lot of folks that think that's a a a lot of folks that think that's a a a lot of folks that think that's a a cloud thing that oh hey it's going to cloud thing that oh hey it's going to cloud thing that oh hey it's going to replace [clears throat] GPUs blah blah replace [clears throat] GPUs blah blah replace [clears throat] GPUs blah blah blah but it's blah but it's blah but it's it's actually it's actually it's actually solving or has potential to solve solving or has potential to solve solving or has potential to solve constrained problems at the edge so when constrained problems at the edge so when constrained problems at the edge so when you look at medical devices right novel you look at medical devices right novel you look at medical devices right novel medical devices to help solve or remind medical devices to help solve or remind medical devices to help solve or remind or you know wearables glasses right or you know wearables glasses right or you know wearables glasses right right right right >> exactly >> exactly >> exactly um this is where a lot of that next um this is where a lot of that next um this is where a lot of that next generation innovation generation innovation generation innovation and invention is going to come from and invention is going to come from and invention is going to come from right right right and and actually this is kind of what we and and actually this is kind of what we and and actually this is kind of what we saw with saw with saw with AI AI really blew up on the smartphone AI AI really blew up on the smartphone AI AI really blew up on the smartphone not in the data center right data center not in the data center right data center not in the data center right data center was just doing some you know ML training was just doing some you know ML training was just doing some you know ML training blah blah blah but where blah blah blah but where blah blah blah but where value was being exhibited was like in value was being exhibited was like in value was being exhibited was like in freaking compositional photography and freaking compositional photography and freaking compositional photography and like that you know I mean awesome like that you know I mean awesome like that you know I mean awesome value huge differentiation for a lot of value huge differentiation for a lot of value huge differentiation for a lot of the players in the the players in the the players in the space uh and and so I you know space uh and and so I you know space uh and and so I you know the place to look is at the edge in many the place to look is at the edge in many the place to look is at the edge in many instances because some of the you know instances because some of the you know instances because some of the you know everyone thinks that oh yeah you know everyone thinks that oh yeah you know everyone thinks that oh yeah you know you're doing all this innovation is you're doing all this innovation is you're doing all this innovation is coming down to coming down to coming down to the edge actually there's a lot of stuff

the edge actually there's a lot of stuff the edge actually there's a lot of stuff that goes up right socam for instance that goes up right socam for instance that goes up right socam for instance that memory collaboration that memory collaboration that memory collaboration with with with micron between micron and Nvidia a lot micron between micron and Nvidia a lot micron between micron and Nvidia a lot of that is based off of like of that is based off of like of that is based off of like you know mobile memory tech you know mobile memory tech you know mobile memory tech right low power right low power right low power um you know high throughput that kind of um you know high throughput that kind of um you know high throughput that kind of stuff so stuff so stuff so um um um anyway I just wanted to drop that one anyway I just wanted to drop that one anyway I just wanted to drop that one out there um you got and just because I out there um you got and just because I out there um you got and just because I think think think there's this misconception that there's this misconception that there's this misconception that advanced technologies are incubated advanced technologies are incubated advanced technologies are incubated in these large data centers that's not in these large data centers that's not in these large data centers that's not true actually a lot of this happens true actually a lot of this happens true actually a lot of this happens to Bill's point solving really hard to Bill's point solving really hard to Bill's point solving really hard problems problems problems at the edge and then they scale up right at the edge and then they scale up right at the edge and then they scale up right trace their way up trace their way up trace their way up and then you know like so now because and then you know like so now because and then you know like so now because data centers data centers data centers you're sort of past this whole point of you're sort of past this whole point of you're sort of past this whole point of brute force and now you have to figure brute force and now you have to figure brute force and now you have to figure out how to optimize a lot of the out how to optimize a lot of the out how to optimize a lot of the principles of the edge and IoT principles of the edge and IoT principles of the edge and IoT are becoming very important are becoming very important are becoming very important especially for operational data centers especially for operational data centers especially for operational data centers because hoses leak you know because hoses leak you know because hoses leak you know um um um uh you know freaking sockets can uh you know freaking sockets can uh you know freaking sockets can overheat right or so you have to have overheat right or so you have to have overheat right or so you have to have all this physical monitoring of the all this physical monitoring of the all this physical monitoring of the entire infrastructure entire infrastructure entire infrastructure and environment and guess what a lot of

and environment and guess what a lot of and environment and guess what a lot of this technology is coming from this technology is coming from this technology is coming from the edge the edge the edge the you know I know Qualcomm have been the you know I know Qualcomm have been the you know I know Qualcomm have been talking about talking about talking about some kind of interesting new memory some kind of interesting new memory some kind of interesting new memory architectures architectures architectures to solve this issue like in the phone to solve this issue like in the phone to solve this issue like in the phone space you know space you know space you know a lot of you know language models are a lot of you know language models are a lot of you know language models are memory bound more than tops bound and so memory bound more than tops bound and so memory bound more than tops bound and so coming up with better memory coming up with better memory coming up with better memory architectures is really critical and so architectures is really critical and so architectures is really critical and so you you solve that in the phone, then you you solve that in the phone, then you you solve that in the phone, then hey, guess what? Maybe we can solve that hey, guess what? Maybe we can solve that hey, guess what? Maybe we can solve that on the server and then in the data on the server and then in the data on the server and then in the data center. And obviously you can you start center. And obviously you can you start center. And obviously you can you start to get a lot more efficiencies to get a lot more efficiencies to get a lot more efficiencies and get that cost per [clears throat] and get that cost per [clears throat] and get that cost per [clears throat] token down even faster and blah blah token down even faster and blah blah token down even faster and blah blah blah. So yeah, the edge is kind of where blah. So yeah, the edge is kind of where blah. So yeah, the edge is kind of where you know, when things get you know, when things get you know, when things get commercialized, as you know, you first commercialized, as you know, you first commercialized, as you know, you first get them working and then get them working and then get them working and then if you want actually want to if you want actually want to if you want actually want to commercialize it, you have to cost commercialize it, you have to cost commercialize it, you have to cost reduce it so that it actually makes reduce it so that it actually makes reduce it so that it actually makes business sense. Well, you know, and and business sense. Well, you know, and and business sense. Well, you know, and and this whole idea of like unified memory this whole idea of like unified memory this whole idea of like unified memory on SOC, on SOC, on SOC, I mean I mean I mean you basically have memory as close as you basically have memory as close as you basically have memory as close as possible to almost all the different possible to almost all the different possible to almost all the different kind of cores that you would require to kind of cores that you would require to kind of cores that you would require to do AI. Like this heterogeneous compute do AI. Like this heterogeneous compute do AI. Like this heterogeneous compute concept, concept, concept, it's on your smartphone, right? And it's on your smartphone, right? And it's on your smartphone, right? And that's why, like think about it, what that's why, like think about it, what that's why, like think about it, what Apple's done with Apple's done with Apple's done with Apple Silicon, they've taken it Apple Silicon, they've taken it Apple Silicon, they've taken it basically the A you know, the A series basically the A you know, the A series basically the A you know, the A series chip that powered your smartphone and chip that powered your smartphone and chip that powered your smartphone and scaled it up to a scaled it up to a scaled it up to a a desktop, a laptop and you know, sort a desktop, a laptop and you know, sort a desktop, a laptop and you know, sort of a workstation scale.

of a workstation scale. of a workstation scale. And guess what? It's great for it all And guess what? It's great for it all And guess what? It's great for it all kinds of different AI, right? And that's kinds of different AI, right? And that's kinds of different AI, right? And that's why all these people now we're talking why all these people now we're talking why all these people now we're talking about AGI and tech are scrambling to get about AGI and tech are scrambling to get about AGI and tech are scrambling to get one of those freaking Mac minis. Those one of those freaking Mac minis. Those one of those freaking Mac minis. Those things are like you know, according to things are like you know, according to things are like you know, according to the Apple folks on their call, this this the Apple folks on their call, this this the Apple folks on their call, this this things are going to be sold out things are going to be sold out things are going to be sold out they're tapped out for Crazy. as far as they're tapped out for Crazy. as far as they're tapped out for Crazy. as far as I can tell. The I can tell. The I can tell. The >> Finally found their product market fit >> Finally found their product market fit >> Finally found their product market fit >> [laughter] >> [laughter] >> [laughter] >> that thing. >> that thing. >> that thing. Ironically, it's AI and guess what? Ironically, it's AI and guess what? Ironically, it's AI and guess what? They're going to make money off of it. They're going to make money off of it. They're going to make money off of it. >> I know. They're going to make money. You >> I know. They're going to make money. You >> I know. They're going to make money. You know, think of dude, they're their CAPEX know, think of dude, they're their CAPEX know, think of dude, they're their CAPEX went down like 25%. went down like 25%. went down like 25%. >> [laughter] >> [laughter] >> [laughter] >> Crazy. But yet, they are riding an AI >> Crazy. But yet, they are riding an AI >> Crazy. But yet, they are riding an AI um they're riding the AI hype um they're riding the AI hype um they're riding the AI hype trend by selling hardware. Mhm. Yeah. trend by selling hardware. Mhm. Yeah. trend by selling hardware. Mhm. Yeah. Well, I mean but think about it. That Well, I mean but think about it. That Well, I mean but think about it. That that's what that's what the that's what that's what that's what the that's what that's what that's what the that's what it is, right? The whole thing Look at it is, right? The whole thing Look at it is, right? The whole thing Look at the conversation that we're having, CPU the conversation that we're having, CPU the conversation that we're having, CPU versus GPU. Yeah. That's versus GPU. Yeah. That's versus GPU. Yeah. That's everything builds from there.

everything builds from there. everything builds from there. Yeah, yeah, yeah, yeah. Well, yeah, and Yeah, yeah, yeah, yeah. Well, yeah, and Yeah, yeah, yeah, yeah. Well, yeah, and but now there's the new frontier of like but now there's the new frontier of like but now there's the new frontier of like um um um I think the MPU has a lot of potential. I think the MPU has a lot of potential. I think the MPU has a lot of potential. >> MPU, whatever you want to call it. >> MPU, whatever you want to call it. >> MPU, whatever you want to call it. Yeah, yeah. Yeah, yeah. Yeah, yeah. Um but especially the MPU Um but especially the MPU Um but especially the MPU because it can do it can do because it can do it can do because it can do it can do matrix multiply, scalar and vector, matrix multiply, scalar and vector, matrix multiply, scalar and vector, right? So these are all different right? So these are all different right? So these are all different operations. If you look at the diversity operations. If you look at the diversity operations. If you look at the diversity of inference that's coming our way, of inference that's coming our way, of inference that's coming our way, whether it's the vision stuff, the whether it's the vision stuff, the whether it's the vision stuff, the language, whatever, you do kind of want language, whatever, you do kind of want language, whatever, you do kind of want to have a general purpose optimized, to have a general purpose optimized, to have a general purpose optimized, highly optimized um you know, highly optimized um you know, highly optimized um you know, IP IP IP >> [clears throat] >> [clears throat] >> [clears throat] >> that you can run that stuff off of. And >> that you can run that stuff off of. And >> that you can run that stuff off of. And I think the MPU or neural, if you want I think the MPU or neural, if you want I think the MPU or neural, if you want to call it neural processor or whatever, to call it neural processor or whatever, to call it neural processor or whatever, it's going to find its time and it's going to find its time and it's going to find its time and inference might actually be that inference might actually be that inference might actually be that opportunity because you know, like AI PC opportunity because you know, like AI PC opportunity because you know, like AI PC has really struggled. Nobody could has really struggled. Nobody could has really struggled. Nobody could figure out what the hell do we do with figure out what the hell do we do with figure out what the hell do we do with this thing?

this thing? this thing? Well, inference hasn't really you know, Well, inference hasn't really you know, Well, inference hasn't really you know, from the data center hasn't come down from the data center hasn't come down from the data center hasn't come down quite yet. But you know, especially quite yet. But you know, especially quite yet. But you know, especially Qualcomm has been Qualcomm has been Qualcomm has been ever since like chat GPT became a big ever since like chat GPT became a big ever since like chat GPT became a big thing, they've been thing, they've been thing, they've been first to market with a lot of stuff first to market with a lot of stuff first to market with a lot of stuff related to to related to to related to to you know, you know, you know, optimizing small or tiny ML stuff, optimizing small or tiny ML stuff, optimizing small or tiny ML stuff, right? With edge right? With edge right? With edge edge compute. Yeah. I mean they edge compute. Yeah. I mean they edge compute. Yeah. I mean they [clears throat] don't they don't have [clears throat] don't they don't have [clears throat] don't they don't have much of a data center play. So I think much of a data center play. So I think much of a data center play. So I think some of this kind of help helps in some of this kind of help helps in some of this kind of help helps in storage. storage. storage. >> Not not yet, but >> Not not yet, but >> Not not yet, but yeah, we'll see how that that plays out. yeah, we'll see how that that plays out. yeah, we'll see how that that plays out. >> ambitions, yeah, ambitions. >> ambitions, yeah, ambitions. >> ambitions, yeah, ambitions. I would say neo neo data center as I would say neo neo data center as I would say neo neo data center as opposed to data center data center. So opposed to data center data center. So opposed to data center data center. So neo plan. But the fact that they they they aren't But the fact that they they they aren't just necessarily going forward with just necessarily going forward with just necessarily going forward with a GPU, I don't think it's a No. NPUs. I a GPU, I don't think it's a No. NPUs. I a GPU, I don't think it's a No. NPUs. I mean look at what DeepX is doing. They mean look at what DeepX is doing. They mean look at what DeepX is doing. They then these NPUs used to be CNN, RNN then these NPUs used to be CNN, RNN then these NPUs used to be CNN, RNN vision oriented. Now they're more vision oriented. Now they're more vision oriented. Now they're more language accelerated.

language accelerated. language accelerated. are more are more are more language oriented and then we're going language oriented and then we're going language oriented and then we're going to see even more specialized silicon, I to see even more specialized silicon, I to see even more specialized silicon, I think. And that and speaking of memory, think. And that and speaking of memory, think. And that and speaking of memory, you have in memory compute, right? So you have in memory compute, right? So you have in memory compute, right? So you're going to see memory that's you're going to see memory that's you're going to see memory that's actually has AI acceleration actually has AI acceleration actually has AI acceleration capabilities in that. So so I think capabilities in that. So so I think capabilities in that. So so I think we're just at the beginning. We're still we're just at the beginning. We're still we're just at the beginning. We're still in the steam engine era of AI. That's in the steam engine era of AI. That's in the steam engine era of AI. That's that's part of my talk for next week is that's part of my talk for next week is that's part of my talk for next week is it's still the steam engine. We still it's still the steam engine. We still it's still the steam engine. We still have have have the iron horse with the coal and all the iron horse with the coal and all the iron horse with the coal and all that stuff. that stuff. that stuff. We can see it's working, but it's it's We can see it's working, but it's it's We can see it's working, but it's it's super duper inefficient, right? So we super duper inefficient, right? So we super duper inefficient, right? So we this is the frontier. this is the frontier. this is the frontier. Yeah. Yeah, and then maybe one of these Yeah. Yeah, and then maybe one of these Yeah. Yeah, and then maybe one of these days neuromorphic will will uh days neuromorphic will will uh days neuromorphic will will uh >> [clears throat] >> [clears throat] >> [clears throat] >> make its way. It will. It's it'll >> make its way. It will. It's it'll >> make its way. It will. It's it'll inspire some interesting things, but inspire some interesting things, but >> [clears throat] >> Yeah. Yeah. folks in the kind of >> Yeah. Yeah. folks in the kind of >> Yeah. Yeah. folks in the kind of formation stage of what at least the I formation stage of what at least the I formation stage of what at least the I see from in the in this kind of proceed see from in the in this kind of proceed see from in the in this kind of proceed guys. [clears throat] guys. [clears throat] guys. [clears throat] They're in the formation phase of of They're in the formation phase of of They're in the formation phase of of figuring out like how do you actually figuring out like how do you actually figuring out like how do you actually execute this? The the execute this? The the execute this? The the the the the appeal of neuromorphic computing is appeal of neuromorphic computing is appeal of neuromorphic computing is clear. Um and then I'd I'd say there are clear. Um and then I'd I'd say there are clear. Um and then I'd I'd say there are a number of different you know, a number of different you know, a number of different you know, approaches that are being taken, none of approaches that are being taken, none of approaches that are being taken, none of which is really proven yet. But the which is really proven yet. But the which is really proven yet. But the necessity of necessity of necessity of of edge, a super efficient power of edge, a super efficient power of edge, a super efficient power efficient edge based neuromorphic efficient edge based neuromorphic efficient edge based neuromorphic computing computing computing it that's about as clear as it gets.

it that's about as clear as it gets. it that's about as clear as it gets. Um I think Um I think Um I think it is green field. So you know, it it it it is green field. So you know, it it it it is green field. So you know, it it it remains to be seen who actually remains to be seen who actually remains to be seen who actually you know, who actually you know, who actually you know, who actually takes the lead in that space. And there takes the lead in that space. And there takes the lead in that space. And there aren't that many spaces in in you know, aren't that many spaces in in you know, aren't that many spaces in in you know, in in our world that are like that in in our world that are like that in in our world that are like that actually that are kind of you know, this actually that are kind of you know, this actually that are kind of you know, this is kind of green field space. No one's is kind of green field space. No one's is kind of green field space. No one's really figured out how to nail this, but really figured out how to nail this, but really figured out how to nail this, but the demand that it it's latent demand the demand that it it's latent demand the demand that it it's latent demand for that for that type of technology is for that for that type of technology is for that for that type of technology is very very clear. very very clear. very very clear. Oh yeah, yeah. I mean it can definitely Oh yeah, yeah. I mean it can definitely Oh yeah, yeah. I mean it can definitely substitute. And you know, here's the substitute. And you know, here's the substitute. And you know, here's the good news for the neuromorphic guys, at good news for the neuromorphic guys, at good news for the neuromorphic guys, at least you're going to be ahead of the least you're going to be ahead of the least you're going to be ahead of the quantum quantum quantum folks. folks. folks. Well, that's for sure. Well, that's for sure. Well, that's for sure. >> [laughter] >> [laughter] >> [laughter] >> That's a whole other discussion. >> That's a whole other discussion. >> That's a whole other discussion. >> Yeah, and you don't have to dump like >> Yeah, and you don't have to dump like >> Yeah, and you don't have to dump like you know, billions or trillions of you know, billions or trillions of you know, billions or trillions of dollars into supercomputing that dollars into supercomputing that dollars into supercomputing that and and solving problems that are money and and solving problems that are money and and solving problems that are money losers. losers. losers. You know, [snorts] it's cost center You know, [snorts] it's cost center You know, [snorts] it's cost center stuff. People just stuff. People just stuff. People just they still don't understand quantum. they still don't understand quantum. they still don't understand quantum. It's all like traditional solving It's all like traditional solving It's all like traditional solving traditional traditional traditional you know, supercomputing problems. you know, supercomputing problems. you know, supercomputing problems. Weather weather forecasting, basically.

Weather weather forecasting, basically. Weather weather forecasting, basically. Do you think that AI in its current is Do you think that AI in its current is Do you think that AI in its current is has like kind of overtaken some of the has like kind of overtaken some of the has like kind of overtaken some of the need for quantum? So the original goal need for quantum? So the original goal need for quantum? So the original goal of quantum was you can just churn of quantum was you can just churn of quantum was you can just churn through you can do what you do today, through you can do what you do today, through you can do what you do today, but you can do it a thousand times but you can do it a thousand times but you can do it a thousand times faster. Oh, it's faster. Oh, it's faster. Oh, it's you know, the way that it was described you know, the way that it was described you know, the way that it was described to me by a Princeton to me by a Princeton to me by a Princeton professor who's been studying this stuff professor who's been studying this stuff professor who's been studying this stuff for I mean, developing this for I mean, developing this for I mean, developing this stuff for the longest time is think of stuff for the longest time is think of stuff for the longest time is think of it as a calculator, not a computer. it as a calculator, not a computer. it as a calculator, not a computer. Mhm. Mhm. Mhm. But it will solve a really complex But it will solve a really complex But it will solve a really complex problem. It will not [clears throat] problem. It will not [clears throat] problem. It will not [clears throat] you're not going to cracking cracking you're not going to cracking cracking you're not going to cracking cracking the crypto the crypto the crypto encryption. They'll crack encryption. encryption. They'll crack encryption. encryption. They'll crack encryption. >> [laughter] >> [laughter] >> [laughter] >> And and it will not replace traditional >> And and it will not replace traditional >> And and it will not replace traditional compute. In fact, [clears throat] compute. In fact, [clears throat] compute. In fact, [clears throat] traditional computing, bits and bytes traditional computing, bits and bytes traditional computing, bits and bytes are really good at what they do. are really good at what they do. are really good at what they do. >> [laughter] >> [laughter] >> [laughter] >> I mean So Leonard, are you saying that >> I mean So Leonard, are you saying that >> I mean So Leonard, are you saying that Microsoft's not going to introduce the Microsoft's not going to introduce the Microsoft's not going to introduce the quantum PC next year? I heard that quantum PC next year? I heard that quantum PC next year? I heard that that's a that's a that's a >> [laughter] >> [laughter] >> [laughter] >> Yeah, that >> Yeah, that >> Yeah, that that'll come in maybe uh that'll come in maybe uh that'll come in maybe uh Yikes. Like if Rob was here, he would Yikes. Like if Rob was here, he would Yikes. Like if Rob was here, he would say that it would be here in like say that it would be here in like say that it would be here in like whatever, you know, 20 whatever, you know, 20 whatever, you know, 20 >> professional edition.

>> professional edition. >> professional edition. >> [laughter] >> [laughter] >> [laughter] >> Quantum pilot. >> Quantum pilot. >> Quantum pilot. Quantum pilot. Quantum pilot. Quantum pilot. Yeah. Q pilot. Qbert. Yeah. Q pilot. Qbert. Yeah. Q pilot. Qbert. Now. Now. Now. Now. So anyways, Now. So anyways, Now. So anyways, No, it's good stuff, guys. So No, it's good stuff, guys. So No, it's good stuff, guys. So why don't we call it an episode? Sounds why don't we call it an episode? Sounds why don't we call it an episode? Sounds good. Hey everyone, thank you for making good. Hey everyone, thank you for making good. Hey everyone, thank you for making it this far if you did. Holy crap. it this far if you did. Holy crap. it this far if you did. Holy crap. You have more attention than any LLM or You have more attention than any LLM or You have more attention than any LLM or That's right. Yeah, or any That means that you have a context That means that you have a context window of at least 20 billion window of at least 20 billion window of at least 20 billion tokens. So that's pretty good. So tokens. So that's pretty good. So tokens. So that's pretty good. So congratulations. congratulations. congratulations. >> Assuming that people are playing this in >> Assuming that people are playing this in >> Assuming that people are playing this in the background as kind of a sleep aid. the background as kind of a sleep aid. the background as kind of a sleep aid. That's right. That's right. That's right. >> [laughter] >> [laughter] >> [laughter] >> Helping them Yeah, we're subliminally >> Helping them Yeah, we're subliminally >> Helping them Yeah, we're subliminally twisting their minds. Yeah, I twisting their minds. Yeah, I twisting their minds. Yeah, I But no, we really appreciate your But no, we really appreciate your But no, we really appreciate your viewership and your listenership. And viewership and your listenership. And viewership and your listenership. And you know, if you don't you know, if you don't you know, if you don't if you don't tell everybody if you don't tell everybody if you don't tell everybody about IoT Coffee Talk, we'll be quite about IoT Coffee Talk, we'll be quite about IoT Coffee Talk, we'll be quite disappointed. Guys, I don't know where disappointed. Guys, I don't know where disappointed. Guys, I don't know where I'm going with this.

I'm going with this. I'm going with this. >> [laughter] >> [laughter] >> [laughter] >> All right, I will >> All right, I will >> All right, I will I will spam you. See you at Sensors I will spam you. See you at Sensors I will spam you. See you at Sensors Converge next week. Yeah, definitely. Converge next week. Yeah, definitely. Converge next week. Yeah, definitely. Sensors Converge next week because the Sensors Converge next week because the Sensors Converge next week because the IoT starts with sensors. Without IoT starts with sensors. Without IoT starts with sensors. Without sensors, there's no IoT. You cannot sensors, there's no IoT. You cannot sensors, there's no IoT. You cannot sniff farts and your AI will never know sniff farts and your AI will never know sniff farts and your AI will never know if you farted in the room. So remember if you farted in the room. So remember if you farted in the room. So remember that. And also, yeah, that. And also, yeah, that. And also, yeah, um I think we're almost about to go live um I think we're almost about to go live um I think we're almost about to go live with uh with uh with uh Elevate Communities. And check it out. Elevate Communities. And check it out. Elevate Communities. And check it out. It's going to be an effort to bring It's going to be an effort to bring It's going to be an effort to bring you know, technologies, essential you know, technologies, essential you know, technologies, essential technologies to communities so that they technologies to communities so that they technologies to communities so that they can be resilient in light of growing can be resilient in light of growing can be resilient in light of growing environmental threats and environmental threats and environmental threats and you know other challenges that can play you know other challenges that can play you know other challenges that can play and we want to help communities all and we want to help communities all and we want to help communities all around the world if possible to around the world if possible to around the world if possible to quickly leverage quickly leverage quickly leverage emerging technologies as well as emerging technologies as well as emerging technologies as well as established technologies established technologies established technologies for good. So anyways, for good. So anyways, for good. So anyways, we will see you next week and have a we will see you next week and have a we will see you next week and have a great weekend.