IoT Coffee Talk: Episode 323 - "AI Vibe Disruption!!" (Ride the AI slop wave!)

All right. Hey everybody, welcome to IoT All right. Hey everybody, welcome to IoT Coffee Talk. Got a good crowd this week Coffee Talk. Got a good crowd this week Coffee Talk. Got a good crowd this week [music] on what's going on in the world [music] on what's going on in the world [music] on what's going on in the world of tech and the internet of things and of tech and the internet of things and of tech and the internet of things and connectivity and data centers connectivity and data centers connectivity and data centers >> and I'm I'm I'm echoing echoing. >> and I'm I'm I'm echoing echoing. >> and I'm I'm I'm echoing echoing. >> I can hear myself echoing. >> I can hear myself echoing. >> I can hear myself echoing. >> Echoing is echoing echoing. >> Echoing is echoing echoing. >> Echoing is echoing echoing. That's not good. Am I still echoing? That's not good. Am I still echoing? That's not good. Am I still echoing? >> No, it's >> No, it's >> No, it's >> okay now. >> okay now. >> okay now. >> Oh, [music] it's back. >> Oh, [music] it's back. >> Oh, [music] it's back. >> Is it back? All right, >> Is it back? All right, >> Is it back? All right, somebody else. It's somebody else's somebody else. It's somebody else's somebody else. It's somebody else's head. One, two. Yes, we sound fine. All head. One, two. Yes, we sound fine. All head. One, two. Yes, we sound fine. All right, maybe we're okay. Hello to Pete, right, maybe we're okay. Hello to Pete, right, maybe we're okay. Hello to Pete, Dimmitri, Devin. All right, looks like Dimmitri, Devin. All right, looks like Dimmitri, Devin. All right, looks like we got Alistister coming in here. we got Alistister coming in here. we got Alistister coming in here. Awesome. [cheering] Awesome. [cheering] Awesome. [cheering] Good stuff, Good stuff, Good stuff, Mr. Fulton. Mr. Fulton. Mr. Fulton. [cheering] [cheering] [cheering] So, what's going on with you guys? I So, what's going on with you guys? I So, what's going on with you guys? I don't We don't have many electric don't We don't have many electric don't We don't have many electric guitars to start off with today, unless guitars to start off with today, unless guitars to start off with today, unless Pete pulls out. Pete pulls out. Pete pulls out. >> Would have known. I'm actually not I'm >> Would have known. I'm actually not I'm >> Would have known. I'm actually not I'm not really hooked up for it. Otherwise, not really hooked up for it. Otherwise, not really hooked up for it. Otherwise, I wouldn't.

I wouldn't. I wouldn't. >> You're not hooked up for it? Oh, man. >> You're not hooked up for it? Oh, man. >> You're not hooked up for it? Oh, man. >> You want to do >> You want to do >> You want to do >> Leonard's at uh Yeah. Go ahead, Devin. >> Leonard's at uh Yeah. Go ahead, Devin. >> Leonard's at uh Yeah. Go ahead, Devin. You pull do something. Anything. You pull do something. Anything. You pull do something. Anything. >> You don't You don't want me doing that. >> You don't You don't want me doing that. >> You don't You don't want me doing that. [laughter] [laughter] [laughter] >> Oh my gosh. Yeah. Yeah. Leonard will be >> Oh my gosh. Yeah. Yeah. Leonard will be >> Oh my gosh. Yeah. Yeah. Leonard will be on about 30 minutes. He's at the Intel on about 30 minutes. He's at the Intel on about 30 minutes. He's at the Intel thing. So, thing. So, thing. So, >> I think I [clears throat] think it's the >> I think I [clears throat] think it's the >> I think I [clears throat] think it's the AMD thing, isn't it? AMD thing, isn't it? AMD thing, isn't it? >> Is it the AMD? You know, he was texting >> Is it the AMD? You know, he was texting >> Is it the AMD? You know, he was texting me. He's like, "Oh my gosh, me. He's like, "Oh my gosh, me. He's like, "Oh my gosh, >> x86." you know, >> x86." you know, >> x86." you know, >> x86 >> x86 >> x86 going going going chip thinglets. chip thinglets. chip thinglets. >> Have you guys heard about Nvidia? I >> Have you guys heard about Nvidia? I >> Have you guys heard about Nvidia? I mean, what was Intel and AMD? Have you mean, what was Intel and AMD? Have you mean, what was Intel and AMD? Have you heard about Nvidia? I mean, it's heard about Nvidia? I mean, it's heard about Nvidia? I mean, it's >> I don't know who those guys are. Yeah, I >> I don't know who those guys are. Yeah, I >> I don't know who those guys are. Yeah, I think I think I bought an Nvidia think I think I bought an Nvidia think I think I bought an Nvidia graphics card in the 90s. Is that what graphics card in the 90s. Is that what graphics card in the 90s. Is that what is that who you're talking about? Or >> PCs and I found this. >> PCs and I found this. >> Wow, look at that. >> Wow, look at that. >> Wow, look at that. >> That just got real. I love that. >> That just got real. I love that. >> That just got real. I love that. >> Well, I mean, it's an actually GeForce >> Well, I mean, it's an actually GeForce >> Well, I mean, it's an actually GeForce 9800 GT.

9800 GT. 9800 GT. >> Outstanding. >> Outstanding. >> Outstanding. >> Well, it's an interesting comment >> Well, it's an interesting comment >> Well, it's an interesting comment >> back then. >> back then. >> back then. >> Yeah, >> Yeah, >> Yeah, >> you could have thought that, you know, >> you could have thought that, you know, >> you could have thought that, you know, the gaming industry will die and Nvidia the gaming industry will die and Nvidia the gaming industry will die and Nvidia will die. Then the Bitcoin mining will will die. Then the Bitcoin mining will will die. Then the Bitcoin mining will die and Nvidia will die. Maybe AI will die and Nvidia will die. Maybe AI will die and Nvidia will die. Maybe AI will die and Nvidia will die. [laughter] They die and Nvidia will die. [laughter] They die and Nvidia will die. [laughter] They never know. [snorts] never know. [snorts] never know. [snorts] >> Who knows? It's actually a great >> Who knows? It's actually a great >> Who knows? It's actually a great pivoting strategy, pivoting strategy, pivoting strategy, >> you know, a blast in the past. So, old >> you know, a blast in the past. So, old >> you know, a blast in the past. So, old video cards. Does any remember something video cards. Does any remember something video cards. Does any remember something called Visa Local Bus or Visa Local Bus? called Visa Local Bus or Visa Local Bus? called Visa Local Bus or Visa Local Bus? >> Visa Local Bus. Sure. >> Visa Local Bus. Sure. >> Visa Local Bus. Sure. >> Do you remember that? That was like a >> Do you remember that? That was like a >> Do you remember that? That was like a thing. I remember that. I remember thing. I remember that. I remember thing. I remember that. I remember >> back with uh 3DFX and uh >> back with uh 3DFX and uh >> back with uh 3DFX and uh >> Yeah. All these guys. And then DirectX >> Yeah. All these guys. And then DirectX >> Yeah. All these guys. And then DirectX came on the scene, OpenGL. Like it used came on the scene, OpenGL. Like it used came on the scene, OpenGL. Like it used to be the Wild West. Remember to be the Wild West. Remember to be the Wild West. Remember >> it was the Wild West. games had to be >> it was the Wild West. games had to be >> it was the Wild West. games had to be ported for specific >> you know it took a while for Windows >> you know it took a while for Windows everybody just is you know oh Windows everybody just is you know oh Windows everybody just is you know oh Windows and gaming you know and obviously that's and gaming you know and obviously that's and gaming you know and obviously that's that's helped Windows stay relevant in a that's helped Windows stay relevant in a that's helped Windows stay relevant in a world where more and more people are world where more and more people are world where more and more people are using a Mac but um but if you go further using a Mac but um but if you go further using a Mac but um but if you go further back you know it was not certain that we back you know it was not certain that we back you know it was not certain that we were the DOSs games dominated the world were the DOSs games dominated the world were the DOSs games dominated the world at that time back then and the reason is at that time back then and the reason is at that time back then and the reason is cuz DOSS games can write right to the cuz DOSS games can write right to the cuz DOSS games can write right to the frame buffer and everything like you frame buffer and everything like you frame buffer and everything like you could do anything in DOSs which is weird could do anything in DOSs which is weird could do anything in DOSs which is weird that I'm saying this. Um, and so when that I'm saying this. Um, and so when that I'm saying this. Um, and so when the big change was when Windows 95 the big change was when Windows 95 the big change was when Windows 95 launched and they I remember they gave

launched and they I remember they gave launched and they I remember they gave us a pinball game and people were trying us a pinball game and people were trying us a pinball game and people were trying to build games for it, but but you're to build games for it, but but you're to build games for it, but but you're right Pete, you couldn't get that right Pete, you couldn't get that right Pete, you couldn't get that performance that DOSs performance and performance that DOSs performance and performance that DOSs performance and graphics until we until Direct X had graphics until we until Direct X had graphics until we until Direct X had their own special drivers and then the their own special drivers and then the their own special drivers and then the game developers. It was almost like the game developers. It was almost like the game developers. It was almost like the console wars, right? It was like this console wars, right? It was like this console wars, right? It was like this game's only available on this card, you game's only available on this card, you game's only available on this card, you know? know? know? >> Yeah. Oh, yes. Right. [snorts] >> Yeah. Oh, yes. Right. [snorts] >> Yeah. Oh, yes. Right. [snorts] that that was actually that that was actually that that was actually >> each other >> each other >> each other >> and that was the day where the Watcom C >> and that was the day where the Watcom C >> and that was the day where the Watcom C was very popular because it allow you to was very popular because it allow you to was very popular because it allow you to go very easily lower level in the DOS go very easily lower level in the DOS go very easily lower level in the DOS operating system and and Doom was built operating system and and Doom was built operating system and and Doom was built with Watcom C with Watcom C with Watcom C >> and I know that Watcom was a Canadian >> and I know that Watcom was a Canadian >> and I know that Watcom was a Canadian company out of one of the university in company out of one of the university in company out of one of the university in Waterloo was also Waterloo was also Waterloo was also >> I remember them >> I remember them >> I remember them >> they were also the creator of Watcom SQL >> they were also the creator of Watcom SQL >> they were also the creator of Watcom SQL which which which >> which was uh initially uh uh embedded uh >> which was uh initially uh uh embedded uh >> which was uh initially uh uh embedded uh by powersoft that kind of default by powersoft that kind of default by powersoft that kind of default database for a development tool database for a development tool database for a development tool >> and it became so popular that power >> and it became so popular that power >> and it became so popular that power ended up buying what comes SQL and that ended up buying what comes SQL and that ended up buying what comes SQL and that became the became the became the >> the the SQL technology that then went >> the the SQL technology that then went >> the the SQL technology that then went back into cybase and ended up being the back into cybase and ended up being the back into cybase and ended up being the mobile SQL database. So mobile SQL database. So mobile SQL database. So >> we're very very old here. Well, but also >> we're very very old here. Well, but also >> we're very very old here. Well, but also if you remember an interesting blast if you remember an interesting blast if you remember an interesting blast from the past too is that so that we had from the past too is that so that we had from the past too is that so that we had this chaos where everyone was coming out this chaos where everyone was coming out this chaos where everyone was coming out with new and faster graphics chips for with new and faster graphics chips for with new and faster graphics chips for gaming and convincing game developers to gaming and convincing game developers to gaming and convincing game developers to port to their chips and then OpenGL port to their chips and then OpenGL port to their chips and then OpenGL arrived arrived arrived >> and John Carmarmac who created Doom >> and John Carmarmac who created Doom >> and John Carmarmac who created Doom which was the which was the which was the >> Sinquanon Sinuan

>> Sinquanon Sinuan >> Sinquanon Sinuan >> uh said I'm going to support OpenGL >> uh said I'm going to support OpenGL >> uh said I'm going to support OpenGL supporting open that means Yeah. What is supporting open that means Yeah. What is supporting open that means Yeah. What is that? that? that? >> So, so he uh so he decided I'm going to >> So, so he uh so he decided I'm going to >> So, so he uh so he decided I'm going to put this thing on OpenGL and that was put this thing on OpenGL and that was put this thing on OpenGL and that was the moment when OpenGL became the moment when OpenGL became the moment when OpenGL became >> sort of the new um kind of hardware >> sort of the new um kind of hardware >> sort of the new um kind of hardware acceleration direct hardware access acceleration direct hardware access acceleration direct hardware access standard and one of the first companies standard and one of the first companies standard and one of the first companies to accept to adopt OpenGL was fill in to accept to adopt OpenGL was fill in to accept to adopt OpenGL was fill in the blank Nvidia. the blank Nvidia. the blank Nvidia. >> Nvidia >> Nvidia >> Nvidia >> Nvidia I guess most of >> Nvidia I guess most of >> Nvidia I guess most of >> they kind of leapt to the front because >> they kind of leapt to the front because >> they kind of leapt to the front because they adopted OpenGL with Carmarmac. they adopted OpenGL with Carmarmac. they adopted OpenGL with Carmarmac. >> Yeah. I kind of made that made OpenGL >> Yeah. I kind of made that made OpenGL >> Yeah. I kind of made that made OpenGL what it was. So what it was. So what it was. So >> had Nvidia and what ATI like in the >> had Nvidia and what ATI like in the >> had Nvidia and what ATI like in the graphics card warrants. graphics card warrants. graphics card warrants. >> Um and that's how many of us knew early >> Um and that's how many of us knew early >> Um and that's how many of us knew early on that Dr. Lisa Sue and her gang over on that Dr. Lisa Sue and her gang over on that Dr. Lisa Sue and her gang over at AMD would be a second place at AMD would be a second place at AMD would be a second place contestant in the AI acceleration race. contestant in the AI acceleration race. contestant in the AI acceleration race. And we knew it early on and we predicted And we knew it early on and we predicted And we knew it early on and we predicted it because we knew they acquired ATI a it because we knew they acquired ATI a it because we knew they acquired ATI a long time ago. And so that gave them long time ago. And so that gave them long time ago. And so that gave them that graphics card GPU capability that that graphics card GPU capability that that graphics card GPU capability that all the other players didn't have except all the other players didn't have except all the other players didn't have except for for for >> Speaking of great Canadian companies, >> Speaking of great Canadian companies, >> Speaking of great Canadian companies, ETR, great Canadian company.

ETR, great Canadian company. ETR, great Canadian company. >> There you go. Wow. Wow. >> There you go. Wow. Wow. >> There you go. Wow. Wow. >> So there you go. It all It all circles >> So there you go. It all It all circles >> So there you go. It all It all circles back. back. back. >> It all circles back. >> It all circles back. >> It all circles back. >> Circle of life. >> Circle of life. >> Circle of life. >> All right, Alistister, what's going on >> All right, Alistister, what's going on >> All right, Alistister, what's going on with you? That sounds like you got a new with you? That sounds like you got a new with you? That sounds like you got a new job. job. job. >> Alistar's >> Alistar's >> Alistar's >> He's a new CEO. He's in the CEO club >> He's a new CEO. He's in the CEO club >> He's a new CEO. He's in the CEO club now. now. now. >> Tell us. >> Tell us. >> Tell us. Um really actually really interesting Um really actually really interesting Um really actually really interesting startup. Uh the founder spent some time startup. Uh the founder spent some time startup. Uh the founder spent some time at Microsoft actually. He didn't overlap at Microsoft actually. He didn't overlap at Microsoft actually. He didn't overlap with either of us. We' already left. Um with either of us. We' already left. Um with either of us. We' already left. Um they he was part of an an acquisition of they he was part of an an acquisition of they he was part of an an acquisition of a company called Bonsai. Anyway, he a company called Bonsai. Anyway, he a company called Bonsai. Anyway, he started Mesa about three years ago. Um, started Mesa about three years ago. Um, started Mesa about three years ago. Um, and it's essentially a platform which and it's essentially a platform which and it's essentially a platform which allows you to um, uh, improve your data, allows you to um, uh, improve your data, allows you to um, uh, improve your data, build a full realistic simulated build a full realistic simulated build a full realistic simulated environment, create AI agents in a noode environment, create AI agents in a noode environment, create AI agents in a noode environment, um, train those agents environment, um, train those agents environment, um, train those agents using deep reinforcement learning on using deep reinforcement learning on using deep reinforcement learning on that synthetic data set, um, deploy that synthetic data set, um, deploy that synthetic data set, um, deploy those agents into a live production those agents into a live production those agents into a live production environment, orchestrate teams of environment, orchestrate teams of environment, orchestrate teams of agents, and it's kind of a couple really agents, and it's kind of a couple really agents, and it's kind of a couple really novel ideas. Um, one the kind of syn the novel ideas. Um, one the kind of syn the novel ideas. Um, one the kind of syn the building of a synthetic data set works building of a synthetic data set works building of a synthetic data set works really well in kind of closed loop really well in kind of closed loop really well in kind of closed loop environments. So manufacturing environments. So manufacturing environments. So manufacturing environments where you basically know environments where you basically know environments where you basically know all the variables not out in the real all the variables not out in the real all the variables not out in the real world where you know wind and sun and world where you know wind and sun and world where you know wind and sun and temperature and stuff like that changes temperature and stuff like that changes temperature and stuff like that changes that the method using used to do that is that the method using used to do that is that the method using used to do that is is really interesting and then just the is really interesting and then just the is really interesting and then just the thought process about how you think thought process about how you think thought process about how you think about segmenting tasks to build AI

about segmenting tasks to build AI about segmenting tasks to build AI agents. So super interesting how company agents. So super interesting how company agents. So super interesting how company um small team um early days startup you um small team um early days startup you um small team um early days startup you know um pre- series A so running around know um pre- series A so running around know um pre- series A so running around like crazy with our heads on fire but we like crazy with our heads on fire but we like crazy with our heads on fire but we have customers have customers have customers that you Nestle are we on recording yet? that you Nestle are we on recording yet? that you Nestle are we on recording yet? >> Oh you have customers that's >> Oh you have customers that's >> Oh you have customers that's >> we're recording this. Uh oh I just heard >> we're recording this. Uh oh I just heard >> we're recording this. Uh oh I just heard the nword Nestle. the nword Nestle. the nword Nestle. >> No I didn't. Um >> No I didn't. Um >> No I didn't. Um >> okay we didn't hear that. So some very >> okay we didn't hear that. So some very >> okay we didn't hear that. So some very um some very very uh blue chip um some very very uh blue chip um some very very uh blue chip manufacturing companies with whom we're manufacturing companies with whom we're manufacturing companies with whom we're already working who've already given us already working who've already given us already working who've already given us kind of these core data sets to to to go kind of these core data sets to to to go kind of these core data sets to to to go figure out how to apply AI. It's quite figure out how to apply AI. It's quite figure out how to apply AI. It's quite incredible actually. I'm I'm shocked by incredible actually. I'm I'm shocked by incredible actually. I'm I'm shocked by the range of customers like they gave the range of customers like they gave the range of customers like they gave you one. you one. you one. >> Wow. >> Wow. >> Wow. >> Which speaks to the credibility of the >> Which speaks to the credibility of the >> Which speaks to the credibility of the founder a guy called Kent Anderson. Um, founder a guy called Kent Anderson. Um, founder a guy called Kent Anderson. Um, so yeah, super interesting like back to so yeah, super interesting like back to so yeah, super interesting like back to back to early stage startup craziness. back to early stage startup craziness. back to early stage startup craziness. Um, but but really interesting space and Um, but but really interesting space and Um, but but really interesting space and it's kind of I mean you and I Rob we've it's kind of I mean you and I Rob we've it's kind of I mean you and I Rob we've we've been in and well all of us we've been in and well all of us we've been in and well all of us actually we've been in and around like actually we've been in and around like actually we've been in and around like well first of all what you need to do is well first of all what you need to do is well first of all what you need to do is get more data and then you need a get more data and then you need a get more data and then you need a platform to ingest it and then oh platform to ingest it and then oh platform to ingest it and then oh you need more data still so you need to you need more data still so you need to you need more data still so you need to connect more stuff and you need then you connect more stuff and you need then you connect more stuff and you need then you need some edge intelligence because need some edge intelligence because need some edge intelligence because maybe we can do something like but but maybe we can do something like but but maybe we can do something like but but wrapping all of that together into true wrapping all of that together into true wrapping all of that together into true kind of autonomous industrial kind of autonomous industrial kind of autonomous industrial automation. Wow.

automation. Wow. automation. Wow. >> Is is no one's really figured out how to >> Is is no one's really figured out how to >> Is is no one's really figured out how to do that and and I think these guys have do that and and I think these guys have do that and and I think these guys have got as good a shot as any. So got as good a shot as any. So got as good a shot as any. So >> that's sounds exciting >> that's sounds exciting >> that's sounds exciting >> for us. That's exciting. You know, when >> for us. That's exciting. You know, when >> for us. That's exciting. You know, when you walk through what you're saying that you walk through what you're saying that you walk through what you're saying that the technology does. I think most people the technology does. I think most people the technology does. I think most people assume that you would have to go to one assume that you would have to go to one assume that you would have to go to one of the big tech companies to get that of the big tech companies to get that of the big tech companies to get that kind of stuff. Like people would be kind of stuff. Like people would be kind of stuff. Like people would be surprised and not expect a startup to surprised and not expect a startup to surprised and not expect a startup to Yeah. Yeah, we have this whole Yeah. Yeah, we have this whole Yeah. Yeah, we have this whole environment and to let you build environment and to let you build environment and to let you build autonomous agents and low code and then autonomous agents and low code and then autonomous agents and low code and then train them and then they go off and do train them and then they go off and do train them and then they go off and do you know it's uh you know it's uh you know it's uh >> the customers that we talk the customers >> the customers that we talk the customers >> the customers that we talk the customers we're talking to I think that they're I we're talking to I think that they're I we're talking to I think that they're I think that exact companies are too think that exact companies are too think that exact companies are too focused on trying to sell you what focused on trying to sell you what focused on trying to sell you what they've already got on the wagon um than they've already got on the wagon um than they've already got on the wagon um than they are necessarily trying to think they are necessarily trying to think they are necessarily trying to think about how to solve your problem in about how to solve your problem in about how to solve your problem in >> the innovator's dilemma right they are >> the innovator's dilemma right they are >> the innovator's dilemma right they are uh hesitant to u you know break into new uh hesitant to u you know break into new uh hesitant to u you know break into new areas and cannibal izer existing areas and cannibal izer existing areas and cannibal izer existing >> right so >> right so >> right so >> and this is I think it's part of a kind >> and this is I think it's part of a kind >> and this is I think it's part of a kind of overall the gap in industrial I think of overall the gap in industrial I think of overall the gap in industrial I think one of the many gaps in industrial has one of the many gaps in industrial has one of the many gaps in industrial has always been you know it's people like us always been you know it's people like us always been you know it's people like us building the solutions not um you know building the solutions not um you know building the solutions not um you know the plant operator not the the you know the plant operator not the the you know the plant operator not the the you know the water plant manager not the you know the water plant manager not the you know the water plant manager not the you know and so the solutions that we have ended and so the solutions that we have ended and so the solutions that we have ended up building over the years they don't up building over the years they don't up building over the years they don't they don't meet that person where they they don't meet that person where they they don't meet that person where they are with something that is kind of are with something that is kind of are with something that is kind of intuitive and doesn't require that they intuitive and doesn't require that they intuitive and doesn't require that they learn had to work in Python and doesn't learn had to work in Python and doesn't learn had to work in Python and doesn't you know that just freaking works and you know that just freaking works and you know that just freaking works and and that's where

and that's where and that's where >> the founder is mechanic he's mechanical >> the founder is mechanic he's mechanical >> the founder is mechanic he's mechanical engineer by background so he's he's engineer by background so he's he's engineer by background so he's he's started from well how do you do this at started from well how do you do this at started from well how do you do this at a process level and you know our first a process level and you know our first a process level and you know our first step with customers is is is basically step with customers is is is basically step with customers is is is basically sit down with the team responsible for sit down with the team responsible for sit down with the team responsible for running the process and figure out how running the process and figure out how running the process and figure out how you know how do you actually you know how do you actually you know how do you actually [clears throat] do that how do you make [clears throat] do that how do you make [clears throat] do that how do you make the machine work that way how do you um the machine work that way how do you um the machine work that way how do you um and I think the the pressing priority at and I think the the pressing priority at and I think the the pressing priority at the moment for most of these companies the moment for most of these companies the moment for most of these companies is ton of their seasoned folks who is ton of their seasoned folks who is ton of their seasoned folks who actually know how the plastic extruder actually know how the plastic extruder actually know how the plastic extruder really works are leaving. They're really works are leaving. They're really works are leaving. They're retiring, you know, and so you can give retiring, you know, and so you can give retiring, you know, and so you can give the new employee the manual and say, the new employee the manual and say, the new employee the manual and say, "Here, read this." But it takes 20 years "Here, read this." But it takes 20 years "Here, read this." But it takes 20 years to figure out how to tune the actual to figure out how to tune the actual to figure out how to tune the actual piece of equipment. And so if you can piece of equipment. And so if you can piece of equipment. And so if you can build an AI agent that works alongside build an AI agent that works alongside build an AI agent that works alongside those workers, which is our intent, um, those workers, which is our intent, um, those workers, which is our intent, um, then it helps them get up to speed much then it helps them get up to speed much then it helps them get up to speed much more rapidly and, you know, it gives more rapidly and, you know, it gives more rapidly and, you know, it gives them 20 years experience in a day. Um, them 20 years experience in a day. Um, them 20 years experience in a day. Um, so it really really interesting. There so it really really interesting. There so it really really interesting. There are a bunch of other companies. I'm are a bunch of other companies. I'm are a bunch of other companies. I'm still with Momenta and obviously, you still with Momenta and obviously, you still with Momenta and obviously, you know, there are a whole bunch of other know, there are a whole bunch of other know, there are a whole bunch of other companies in this space kind of going companies in this space kind of going companies in this space kind of going after the problem from slightly after the problem from slightly after the problem from slightly different angles. Um, I don't know that different angles. Um, I don't know that different angles. Um, I don't know that we've necessarily figured it out. I we've necessarily figured it out. I we've necessarily figured it out. I think we we're in the process of, but I think we we're in the process of, but I think we we're in the process of, but I think it's an extraordinarily valuable think it's an extraordinarily valuable think it's an extraordinarily valuable space and it speaks to your book, Bob.

space and it speaks to your book, Bob. space and it speaks to your book, Bob. You know, it this this is the where the You know, it this this is the where the You know, it this this is the where the metal meets, you know, rubber meets the metal meets, you know, rubber meets the metal meets, you know, rubber meets the road kind of thing. Um road kind of thing. Um road kind of thing. Um >> if we can't actually get into these >> if we can't actually get into these >> if we can't actually get into these industrial processes and drive industrial processes and drive industrial processes and drive meaningful improvement then it's you meaningful improvement then it's you meaningful improvement then it's you know it's all for not you know I mean know it's all for not you know I mean know it's all for not you know I mean there's no point any of it because you there's no point any of it because you there's no point any of it because you know all it is is interesting know all it is is interesting know all it is is interesting suggestions um that that stay on a suggestions um that that stay on a suggestions um that that stay on a screen and don't actually live on a screen and don't actually live on a screen and don't actually live on a factory floor. So really interesting factory floor. So really interesting factory floor. So really interesting space. space. space. >> It's actually quite interesting, >> It's actually quite interesting, >> It's actually quite interesting, Alistister, because I think one one Alistister, because I think one one Alistister, because I think one one thing I've learned personally from the thing I've learned personally from the thing I've learned personally from the the the and Rob, you were in this wagon the the and Rob, you were in this wagon the the and Rob, you were in this wagon as a wagon as well. The the the days of as a wagon as well. The the the days of as a wagon as well. The the the days of the IoT platforms, industrial IoT the IoT platforms, industrial IoT the IoT platforms, industrial IoT platform that was supposed to be be this platform that was supposed to be be this platform that was supposed to be be this generic, you know, fantastic things that generic, you know, fantastic things that generic, you know, fantastic things that would improve all processes. What we would improve all processes. What we would improve all processes. What we learned to your point is that all those learned to your point is that all those learned to your point is that all those industrial processes are very much industrial processes are very much industrial processes are very much bespoke custommade system integration bespoke custommade system integration bespoke custommade system integration with a lot of knowledge to implement the with a lot of knowledge to implement the with a lot of knowledge to implement the technology and we could never deliver a technology and we could never deliver a technology and we could never deliver a platform that was flexible enough so platform that was flexible enough so platform that was flexible enough so that it would answer those problem it that it would answer those problem it that it would answer those problem it was too generic and it had too many was too generic and it had too many was too generic and it had too many technology constraints. So if you think technology constraints. So if you think technology constraints. So if you think from that angle the the I would say the from that angle the the I would say the from that angle the the I would say the the the the coding availability the the the coding availability the the the coding availability abilities of those agent can actually abilities of those agent can actually abilities of those agent can actually make this bis bespoke at scale but then make this bis bespoke at scale but then make this bis bespoke at scale but then the platform becomes very different.

the platform becomes very different. the platform becomes very different. It's not just you know the database the It's not just you know the database the It's not just you know the database the data flows and the and the the AI model. data flows and the and the the AI model. data flows and the and the the AI model. It's really oh how do I understand the It's really oh how do I understand the It's really oh how do I understand the business problem? How do I understand business problem? How do I understand business problem? How do I understand the equipment and how do I apply the equipment and how do I apply the equipment and how do I apply intelligence to build at scale bespoke intelligence to build at scale bespoke intelligence to build at scale bespoke solutions. So I think that's and to me solutions. So I think that's and to me solutions. So I think that's and to me that's one of the I make a parallel with that's one of the I make a parallel with that's one of the I make a parallel with that. I I do think that one of the that. I I do think that one of the that. I I do think that one of the biggest category of software that is biggest category of software that is biggest category of software that is going to be challenged by AI is the CRM going to be challenged by AI is the CRM going to be challenged by AI is the CRM system because the CRM system has been system because the CRM system has been system because the CRM system has been you know if you salesforce is an you know if you salesforce is an you know if you salesforce is an extremely complex and and and and extremely complex and and and and extremely complex and and and and expensive system because it's so capable expensive system because it's so capable expensive system because it's so capable that you have to tweak it and use that you have to tweak it and use that you have to tweak it and use services and engineers to customize it services and engineers to customize it services and engineers to customize it for your own business. Now you can just for your own business. Now you can just for your own business. Now you can just describe how your business works and describe how your business works and describe how your business works and generate a custom scene and I see people generate a custom scene and I see people generate a custom scene and I see people doing that over and over again. So we doing that over and over again. So we doing that over and over again. So we might go into a world where you just might go into a world where you just might go into a world where you just describe your business processes. The describe your business processes. The describe your business processes. The thing is coded for you and the business thing is coded for you and the business thing is coded for you and the business process change you regenerate another process change you regenerate another process change you regenerate another CRM. If you have a good data discipline CRM. If you have a good data discipline CRM. If you have a good data discipline with the core fundamental data I think with the core fundamental data I think with the core fundamental data I think this is possible to do. So I can see an this is possible to do. So I can see an this is possible to do. So I can see an interesting parallel here. That's that's interesting parallel here. That's that's interesting parallel here. That's that's pretty pretty pretty >> I mean I think there's there's kind of >> I mean I think there's there's kind of >> I mean I think there's there's kind of what we're doing at AMA which is what we're doing at AMA which is what we're doing at AMA which is requires what we've been doing at requires what we've been doing at requires what we've been doing at Momenta you know there's a couple of Momenta you know there's a couple of Momenta you know there's a couple of folks internally um who've basically folks internally um who've basically folks internally um who've basically rebuilt the firm around AI so things rebuilt the firm around AI so things rebuilt the firm around AI so things like um Salesforce which we don't use like um Salesforce which we don't use like um Salesforce which we don't use but we use HubSpot and I think they've but we use HubSpot and I think they've but we use HubSpot and I think they've just become historians that sit behind just become historians that sit behind just become historians that sit behind an MCP server and we have an AI layer an MCP server and we have an AI layer an MCP server and we have an AI layer that runs across the top that integrates that runs across the top that integrates that runs across the top that integrates everything on SharePoint everything ever everything on SharePoint everything ever everything on SharePoint everything ever said in Teams everything said in email,

said in Teams everything said in email, said in Teams everything said in email, everything in our CRM, everything in our everything in our CRM, everything in our everything in our CRM, everything in our sales process, every everything. It it sales process, every everything. It it sales process, every everything. It it basically has an 360 view of the entire basically has an 360 view of the entire basically has an 360 view of the entire business and you can do things like um business and you can do things like um business and you can do things like um obviously the business of a VC is obviously the business of a VC is obviously the business of a VC is evaluating new investment opportunities. evaluating new investment opportunities. evaluating new investment opportunities. You can use it to evaluate a data room You can use it to evaluate a data room You can use it to evaluate a data room with a thousand items in it and provide with a thousand items in it and provide with a thousand items in it and provide you with a concise report that says you with a concise report that says you with a concise report that says should you invest based upon you as a should you invest based upon you as a should you invest based upon you as a company and your thesis. And one of the company and your thesis. And one of the company and your thesis. And one of the things we've had to do is make it very things we've had to do is make it very things we've had to do is make it very deterministic by give it giving it lots deterministic by give it giving it lots deterministic by give it giving it lots of we want it in this form and this is of we want it in this form and this is of we want it in this form and this is the source station. This is how you the source station. This is how you the source station. This is how you should think about X and so we don't get should think about X and so we don't get should think about X and so we don't get any random out of it. any random out of it. any random out of it. >> But it's nuts. It's nuts. I mean the >> But it's nuts. It's nuts. I mean the >> But it's nuts. It's nuts. I mean the performance improvement I performance improvement I performance improvement I >> well the other thing about CRM that's >> well the other thing about CRM that's >> well the other thing about CRM that's pretty cool we use HubSpot too is in B pretty cool we use HubSpot too is in B pretty cool we use HubSpot too is in B the bane of a lot of you mentioned about the bane of a lot of you mentioned about the bane of a lot of you mentioned about good data and a lot of times the good good data and a lot of times the good good data and a lot of times the good data isn't there but data isn't there but data isn't there but >> things like HubSpot now will do a lot of >> things like HubSpot now will do a lot of >> things like HubSpot now will do a lot of good data enhancement. So all of your good data enhancement. So all of your good data enhancement. So all of your partial records, of which 100% of your partial records, of which 100% of your partial records, of which 100% of your records are partial, it will fill in the records are partial, it will fill in the records are partial, it will fill in the blanks by using the web and LinkedIn and blanks by using the web and LinkedIn and blanks by using the web and LinkedIn and >> I love I love things that fill in the >> I love I love things that fill in the >> I love I love things that fill in the blanks. Kind of like, you know, when we blanks. Kind of like, you know, when we blanks. Kind of like, you know, when we capture the mosquito and amber and we capture the mosquito and amber and we capture the mosquito and amber and we got the DNA sequence for all the got the DNA sequence for all the got the DNA sequence for all the dinosaurs, but there was some blanks dinosaurs, but there was some blanks dinosaurs, but there was some blanks that we had to fill in and so we used that we had to fill in and so we used that we had to fill in and so we used DNA from a frog and we plugged those in DNA from a frog and we plugged those in DNA from a frog and we plugged those in to fill the gaps and you know what could to fill the gaps and you know what could to fill the gaps and you know what could go wrong. So yeah, I love that. Oh my go wrong. So yeah, I love that. Oh my go wrong. So yeah, I love that. Oh my god. Hey Devon, does does your team god. Hey Devon, does does your team god. Hey Devon, does does your team Devon obviously is running a big IoT Devon obviously is running a big IoT Devon obviously is running a big IoT team. Do you find yourself built a lot team. Do you find yourself built a lot team. Do you find yourself built a lot of bespoke stuff? How does how do those

of bespoke stuff? How does how do those of bespoke stuff? How does how do those projects look? projects look? projects look? >> I mean, again, you know what I love >> I mean, again, you know what I love >> I mean, again, you know what I love about all this is you can't take the about all this is you can't take the about all this is you can't take the human out of the whole equation? human out of the whole equation? human out of the whole equation? >> And absolutely, you know, people try to >> And absolutely, you know, people try to >> And absolutely, you know, people try to shoehorn technology and without looking shoehorn technology and without looking shoehorn technology and without looking at the enduser experience, the process. at the enduser experience, the process. at the enduser experience, the process. So not only the process but as you know So not only the process but as you know So not only the process but as you know Alistair when you go in and you talk to Alistair when you go in and you talk to Alistair when you go in and you talk to those operators there's always these those operators there's always these those operators there's always these workarounds that they all have in their workarounds that they all have in their workarounds that they all have in their head. How do you figure that? But the head. How do you figure that? But the head. How do you figure that? But the number one thing is trust and unless number one thing is trust and unless number one thing is trust and unless there's trust in the technology um there's trust in the technology um there's trust in the technology um people are not you know you can make all people are not you know you can make all people are not you know you can make all the AI can make all the recommendations the AI can make all the recommendations the AI can make all the recommendations you want but some human at the end still you want but some human at the end still you want but some human at the end still has to say whether this is not going to has to say whether this is not going to has to say whether this is not going to damage permanently damage my operations damage permanently damage my operations damage permanently damage my operations or my equipment because there's some or my equipment because there's some or my equipment because there's some tribal knowledge in there and human tribal knowledge in there and human tribal knowledge in there and human intuition that you still can't replicate intuition that you still can't replicate intuition that you still can't replicate with AI. But everything you're saying, with AI. But everything you're saying, with AI. But everything you're saying, Alistister, make me go back to that Alistister, make me go back to that Alistister, make me go back to that whole, you know, when we were back in whole, you know, when we were back in whole, you know, when we were back in kindergarten, you got the grade card and kindergarten, you got the grade card and kindergarten, you got the grade card and it says, do you play well with others? it says, do you play well with others? it says, do you play well with others? And we're gonna start thinking now, do And we're gonna start thinking now, do And we're gonna start thinking now, do agents, do robots, do all this agents, do robots, do all this agents, do robots, do all this technology, do they play well with the technology, do they play well with the technology, do they play well with the others? And that's a human being, the others? And that's a human being, the others? And that's a human being, the other agents and things like that. So other agents and things like that. So other agents and things like that. So absolutely, you know, you just don't absolutely, you know, you just don't absolutely, you know, you just don't take it, you know, I always say take it, you know, I always say take it, you know, I always say technology is only 25% of the equation.

technology is only 25% of the equation. technology is only 25% of the equation. you know ROI is a second security you know ROI is a second security you know ROI is a second security regulatory that's a huge part that you regulatory that's a huge part that you regulatory that's a huge part that you know I say that not just make it the know I say that not just make it the know I say that not just make it the four legs of the stool but the people four legs of the stool but the people four legs of the stool but the people you know unless you can get people to you know unless you can get people to you know unless you can get people to change behavior unless you can get change behavior unless you can get change behavior unless you can get people to trust things you're not going people to trust things you're not going people to trust things you're not going to get a lick of ROI and that's why you to get a lick of ROI and that's why you to get a lick of ROI and that's why you have to understand it from a human level have to understand it from a human level have to understand it from a human level and from a process level of how your and from a process level of how your and from a process level of how your technology is going to fit and so I love technology is going to fit and so I love technology is going to fit and so I love everything that you know you're doing everything that you know you're doing everything that you know you're doing with these agents and here comes the with these agents and here comes the with these agents and here comes the winner It's dealing with the winner It's dealing with the winner It's dealing with the unpredictable I think because like even unpredictable I think because like even unpredictable I think because like even in a closed loop environment in a in a closed loop environment in a in a closed loop environment in a factory if you're making I don't know factory if you're making I don't know factory if you're making I don't know making tin cans you know yes you've got making tin cans you know yes you've got making tin cans you know yes you've got visibility thanks to all these visibility thanks to all these visibility thanks to all these wonderfully connected sensors you have wonderfully connected sensors you have wonderfully connected sensors you have now and you've had a data ingestion now and you've had a data ingestion now and you've had a data ingestion you've got the data there's one part you've got the data there's one part you've got the data there's one part which is there's a whole bunch of stuff which is there's a whole bunch of stuff which is there's a whole bunch of stuff that's still going to happen that is that's still going to happen that is that's still going to happen that is unpredictable and that's where the human unpredictable and that's where the human unpredictable and that's where the human comes in because they're able to cope comes in because they're able to cope comes in because they're able to cope with these different varing situations with these different varing situations with these different varing situations you know it's more humid today than it you know it's more humid today than it you know it's more humid today than it was yesterday and that actually affects was yesterday and that actually affects was yesterday and that actually affects the throughput of the machine it doesn't the throughput of the machine it doesn't the throughput of the machine it doesn't say that in the manual there's that say that in the manual there's that say that in the manual there's that aspect But the trust aspect I think is aspect But the trust aspect I think is aspect But the trust aspect I think is being able to create an authentic you being able to create an authentic you being able to create an authentic you know a realistic synthetic environment know a realistic synthetic environment know a realistic synthetic environment that then you can train agents in and that then you can train agents in and that then you can train agents in and then demonstrate those agents. So what then demonstrate those agents. So what then demonstrate those agents. So what AMESA and others doing that well AMEA AMESA and others doing that well AMEA AMESA and others doing that well AMEA for sure we take the company's threshold for sure we take the company's threshold for sure we take the company's threshold you know okay so your output variable is you know okay so your output variable is you know okay so your output variable is number of tin cans you produce an hour number of tin cans you produce an hour number of tin cans you produce an hour and your input variables you know there and your input variables you know there and your input variables you know there are set point variables around the metal are set point variables around the metal are set point variables around the metal variable around blah blah blah you know variable around blah blah blah you know variable around blah blah blah you know this is the best you ever achieved was this is the best you ever achieved was this is the best you ever achieved was 85% we can show you the agent delivering

85% we can show you the agent delivering 85% we can show you the agent delivering 95% and and that kind of because we're a 95% and and that kind of because we're a 95% and and that kind of because we're a small startup and yet large companies small startup and yet large companies small startup and yet large companies are trusting us with data That's why I are trusting us with data That's why I are trusting us with data That's why I think they trust us because we can show think they trust us because we can show think they trust us because we can show them the agent running in a in a them the agent running in a in a them the agent running in a in a realistic environment and say look and realistic environment and say look and realistic environment and say look and and also it's then the visibility of and also it's then the visibility of and also it's then the visibility of caps and governance rules like okay the caps and governance rules like okay the caps and governance rules like okay the agent can't actually I don't know um agent can't actually I don't know um agent can't actually I don't know um switch off all the electricity because switch off all the electricity because switch off all the electricity because it saves money in the you know it can't it saves money in the you know it can't it saves money in the you know it can't do dumb stuff in order to try and win do dumb stuff in order to try and win do dumb stuff in order to try and win the win the reward you know win win win the win the reward you know win win win the win the reward you know win win win the win the game that I think but you the win the game that I think but you the win the game that I think but you have to show people that in action have to show people that in action have to show people that in action before they go huh okay so this isn't before they go huh okay so this isn't before they go huh okay so this isn't this isn't n't going to destroy my this isn't n't going to destroy my this isn't n't going to destroy my factory. This isn't going to, you know, factory. This isn't going to, you know, factory. This isn't going to, you know, I'm not going to I'm not going to harm I'm not going to I'm not going to harm I'm not going to I'm not going to harm myself through taking a risk with this myself through taking a risk with this myself through taking a risk with this new technology, new technology, new technology, >> right? >> right? >> right? >> Hey, >> Hey, >> Hey, >> what's up? >> what's up? >> what's up? >> Is that SFO? >> Is that SFO? >> Is that SFO? >> Yeah. >> Yeah. >> Yeah. >> You know, it's like you in a clear TSA >> You know, it's like you in a clear TSA >> You know, it's like you in a clear TSA pre-check. pre-check. pre-check. >> Yes, I am. I I actually made it through.

>> Yes, I am. I I actually made it through. >> Yes, I am. I I actually made it through. >> That's awesome. >> That's awesome. >> That's awesome. >> Yeah. Little do they know, right? Yeah. >> Yeah. Little do they know, right? Yeah. >> Yeah. Little do they know, right? Yeah. >> Little did they know that you're going >> Little did they know that you're going >> Little did they know that you're going to take down a plane. Yeah, that's real to take down a plane. Yeah, that's real to take down a plane. Yeah, that's real bottom for all those people that you're bottom for all those people that you're bottom for all those people that you're going to be with. going to be with. going to be with. >> What the hell? >> What the hell? >> What the hell? >> Find out >> Find out >> Find out say smuggling wild animals, but you know say smuggling wild animals, but you know say smuggling wild animals, but you know >> JSX JSX. So JSX is [clears throat] a >> JSX JSX. So JSX is [clears throat] a >> JSX JSX. So JSX is [clears throat] a small airline that flies um ember jets small airline that flies um ember jets small airline that flies um ember jets from private hangers on airports to from private hangers on airports to from private hangers on airports to other small airports. And it's cheap and other small airports. And it's cheap and other small airports. And it's cheap and it's cheaper than Southwest. it's cheaper than Southwest. it's cheaper than Southwest. Wow. Wow. Wow. >> Did you say in inbredad lights? >> Did you say in inbredad lights? >> Did you say in inbredad lights? >> Inbred. Yeah. Those little, you know, >> Inbred. Yeah. Those little, you know, >> Inbred. Yeah. Those little, you know, regional jets. So, it has those with regional jets. So, it has those with regional jets. So, it has those with >> like business seats on. And yeah, I'm >> like business seats on. And yeah, I'm >> like business seats on. And yeah, I'm actually fly for the first time next actually fly for the first time next actually fly for the first time next week because I can fly from Burbank to week because I can fly from Burbank to week because I can fly from Burbank to Concord. My office is in Walnut Creek. I Concord. My office is in Walnut Creek. I Concord. My office is in Walnut Creek. I can fly to Concord, which is from Walnut can fly to Concord, which is from Walnut can fly to Concord, which is from Walnut Creek, not where you are, which is where Creek, not where you are, which is where Creek, not where you are, which is where I was last week. SFO. I was last week. SFO. I was last week. SFO. >> Some kind of CEO flight thing that >> Some kind of CEO flight thing that >> Some kind of CEO flight thing that Alison sounds like to me.

Alison sounds like to me. Alison sounds like to me. Southwest. Southwest. Southwest. >> It's cheaper than Southwest. It's like >> It's cheaper than Southwest. It's like >> It's cheaper than Southwest. It's like >> get my head. >> get my head. >> get my head. >> It's the first step to the private jet. >> It's the first step to the private jet. >> It's the first step to the private jet. But But But >> yeah, >> yeah, >> yeah, >> right. >> right. >> right. >> I have a question. I think more >> I have a question. I think more >> I have a question. I think more realistically. realistically. realistically. [clears throat] [clears throat] [clears throat] >> I have a question for Pete. Yeah. So, is >> I have a question for Pete. Yeah. So, is >> I have a question for Pete. Yeah. So, is AMD part of uh AI or Edge AI foundation? AMD part of uh AI or Edge AI foundation? AMD part of uh AI or Edge AI foundation? >> Not yet, actually. Not yet. >> Not yet, actually. Not yet. >> Not yet, actually. Not yet. >> Yeah. I I brought you guys up to >> Yeah. I I brought you guys up to >> Yeah. I I brought you guys up to >> Yes. Actually, I'm going to be at AMD in >> Yes. Actually, I'm going to be at AMD in >> Yes. Actually, I'm going to be at AMD in about a week because we are sponsoring about a week because we are sponsoring about a week because we are sponsoring their their their >> they uh they we are co-sponsoring with >> they uh they we are co-sponsoring with >> they uh they we are co-sponsoring with them the MLS systems rising star them the MLS systems rising star them the MLS systems rising star scholarship program. So, I'm going to scholarship program. So, I'm going to scholarship program. So, I'm going to speak at AMD. But yes, they are on our speak at AMD. But yes, they are on our speak at AMD. But yes, they are on our list to have a chitchat with list to have a chitchat with list to have a chitchat with >> Oh, good chithat. >> Oh, good chithat. >> Oh, good chithat. >> That's where it all starts. >> That's where it all starts. >> That's where it all starts. >> That's where it starts. A chitchat. >> That's where it starts. A chitchat. >> That's where it starts. A chitchat. >> Yeah, >> Yeah, >> Yeah, >> absolutely. So that's part of >> absolutely. So that's part of >> absolutely. So that's part of >> we were just talking about uh before you >> we were just talking about uh before you >> we were just talking about uh before you joined Rob was talking about kind of AMD joined Rob was talking about kind of AMD joined Rob was talking about kind of AMD the acquisition of ATI and kind of the the acquisition of ATI and kind of the the acquisition of ATI and kind of the >> Oh yeah >> Oh yeah >> Oh yeah >> always had some big guns you know.

>> always had some big guns you know. >> always had some big guns you know. >> Yeah. Rock and roll was another one. >> Yeah. Rock and roll was another one. >> Yeah. Rock and roll was another one. >> Yeah. So uh I assume that you had a good >> Yeah. So uh I assume that you had a good >> Yeah. So uh I assume that you had a good >> robust experience there with their AI. >> robust experience there with their AI. >> robust experience there with their AI. >> Yeah. Yeah. It was pretty cool. Yeah. I >> Yeah. Yeah. It was pretty cool. Yeah. I >> Yeah. Yeah. It was pretty cool. Yeah. I was at well they uh they blew me out was at well they uh they blew me out was at well they uh they blew me out here to participate and witness uh here to participate and witness uh here to participate and witness uh advancing AI and uh apparently it's advancing AI and uh apparently it's advancing AI and uh apparently it's gotten a lot bigger which is good news gotten a lot bigger which is good news gotten a lot bigger which is good news for AMD. for AMD. for AMD. >> Cool. And um yeah, they announced the >> Cool. And um yeah, they announced the >> Cool. And um yeah, they announced the their their massive Helios rack. This their their massive Helios rack. This their their massive Helios rack. This >> yeah, double wide massive >> yeah, double wide massive >> yeah, double wide massive beast of a machine that's uh the first beast of a machine that's uh the first beast of a machine that's uh the first rack scale rack scale rack scale >> rack scale solutions >> rack scale solutions >> rack scale solutions >> for AI ridiculous supercomputing. >> for AI ridiculous supercomputing. >> for AI ridiculous supercomputing. >> Yeah. Yeah. Uh but you know, the most >> Yeah. Yeah. Uh but you know, the most >> Yeah. Yeah. Uh but you know, the most interesting thing for me was uh their interesting thing for me was uh their interesting thing for me was uh their freaking rock.ai. freaking rock.ai. freaking rock.ai. Did you guys pick up on that? Did you guys pick up on that? Did you guys pick up on that? >> I saw a little bit about that. >> I saw a little bit about that. >> I saw a little bit about that. >> Do you see my little >> Do you see my little >> Do you see my little >> CUDA competitor, right? Is a CUDA >> CUDA competitor, right? Is a CUDA >> CUDA competitor, right? Is a CUDA competitor.

competitor. competitor. >> Well, no, no, no. Rockcom is the CUDA >> Well, no, no, no. Rockcom is the CUDA >> Well, no, no, no. Rockcom is the CUDA competitor. The rock of AI is a it's competitor. The rock of AI is a it's competitor. The rock of AI is a it's basically a gentic um tool basically a gentic um tool basically a gentic um tool >> and I think that's that I mean and I >> and I think that's that I mean and I >> and I think that's that I mean and I underlying tool that uh allows someone underlying tool that uh allows someone underlying tool that uh allows someone who might be let's say not such a savvy who might be let's say not such a savvy who might be let's say not such a savvy well they might be a a kernel kernel well they might be a a kernel kernel well they might be a a kernel kernel programmer or engineer to basically programmer or engineer to basically programmer or engineer to basically um you know accelerate their work in in um you know accelerate their work in in um you know accelerate their work in in uh optimizing funnels uh optimizing funnels uh optimizing funnels were models on top of AMD hardware. And were models on top of AMD hardware. And were models on top of AMD hardware. And so so so I mean if anything this can drain some I mean if anything this can drain some I mean if anything this can drain some of the the cuda moat but it's one of of the the cuda moat but it's one of of the the cuda moat but it's one of those ironic things right where everyone those ironic things right where everyone those ironic things right where everyone talks about how oh AI is you know like talks about how oh AI is you know like talks about how oh AI is you know like generative AI is so good at coding right generative AI is so good at coding right generative AI is so good at coding right well um what if that well um what if that well um what if that talent can be used to undermine the uh talent can be used to undermine the uh talent can be used to undermine the uh differentiation that has in the market differentiation that has in the market differentiation that has in the market at scale cuz I mean think about it one at scale cuz I mean think about it one at scale cuz I mean think about it one of the problems um one of the problems of the problems um one of the problems of the problems um one of the problems for Nvidia here is that uh the slot for Nvidia here is that uh the slot for Nvidia here is that uh the slot dynamic will basically dynamic will basically dynamic will basically level the playing field right I mean the level the playing field right I mean the level the playing field right I mean the diffusion of capability diffusion of capability diffusion of capability uh you know kernel programming which is uh you know kernel programming which is uh you know kernel programming which is very very difficult very low level stuff very very difficult very low level stuff very very difficult very low level stuff to be able to abstract that up using uh

to be able to abstract that up using uh to be able to abstract that up using uh these types of tools these agentic tools these types of tools these agentic tools these types of tools these agentic tools That's that's a huge potentially That's that's a huge potentially That's that's a huge potentially equalizing equalizing equalizing uh capability that can have that that uh capability that can have that that uh capability that can have that that can ride that slop effect. can ride that slop effect. can ride that slop effect. >> And um I don't know, man. Yeah, it's >> And um I don't know, man. Yeah, it's >> And um I don't know, man. Yeah, it's going to be really interesting to see going to be really interesting to see going to be really interesting to see what happens in the next I think year. what happens in the next I think year. what happens in the next I think year. >> Can you uh can you trade can you >> Can you uh can you trade can you >> Can you uh can you trade can you trademark that phrase slop effect? trademark that phrase slop effect? trademark that phrase slop effect? >> I like that. I like that. >> I like that. I like that. >> I like that. I like that. >> PM PM [laughter] >> PM PM [laughter] >> PM PM [laughter] every time you say it. I think someone I every time you say it. I think someone I every time you say it. I think someone I think someone in Lithuania already think someone in Lithuania already think someone in Lithuania already snagged that one. snagged that one. snagged that one. >> Yeah. Well, you know, people don't >> Yeah. Well, you know, people don't >> Yeah. Well, you know, people don't realize that we innovate on IoT copy realize that we innovate on IoT copy realize that we innovate on IoT copy talk, right? We come up with all kinds talk, right? We come up with all kinds talk, right? We come up with all kinds of ridiculous terms that eventually of ridiculous terms that eventually of ridiculous terms that eventually become main. become main. become main. >> So, do we think that So, AMD, they got >> So, do we think that So, AMD, they got >> So, do we think that So, AMD, they got the new Helas, the whole new rack thing. the new Helas, the whole new rack thing. the new Helas, the whole new rack thing. Is that something that would fit into an Is that something that would fit into an Is that something that would fit into an NT data center? NT data center? NT data center? >> Is did I see Devon on? Is he still on? >> Is did I see Devon on? Is he still on? >> Is did I see Devon on? Is he still on? >> Yeah, he's right here. Yeah, really been >> Yeah, he's right here. Yeah, really been >> Yeah, he's right here. Yeah, really been on the whole time since last week.

on the whole time since last week. on the whole time since last week. >> So, we didn't scare you off. [laughter] >> So, we didn't scare you off. [laughter] >> So, we didn't scare you off. [laughter] >> We have to We have to try harder. We >> We have to We have to try harder. We >> We have to We have to try harder. We have to try harder. have to try harder. have to try harder. >> Yeah, man. I Hey, kudos to you. You have >> Yeah, man. I Hey, kudos to you. You have >> Yeah, man. I Hey, kudos to you. You have some [laughter] >> Oh [clears throat] my god. >> Oh [clears throat] my god. >> Oh, that's awesome. Hey, welcome back, >> Oh, that's awesome. Hey, welcome back, >> Oh, that's awesome. Hey, welcome back, man. It was good to see you on the on man. It was good to see you on the on man. It was good to see you on the on the whatever the Brady Bunch grid. the whatever the Brady Bunch grid. the whatever the Brady Bunch grid. >> How How could I pass up another one? >> How How could I pass up another one? >> How How could I pass up another one? Right. [laughter] Right. [laughter] Right. [laughter] >> This is where it's all happening. >> This is where it's all happening. >> This is where it's all happening. >> It's where it's all happening. >> It's where it's all happening. >> It's where it's all happening. >> Oh, yeah. >> Oh, yeah. >> Oh, yeah. >> You know, Alistair, you said something >> You know, Alistair, you said something >> You know, Alistair, you said something about, "Oh, I'll just rebuild my CRM or about, "Oh, I'll just rebuild my CRM or about, "Oh, I'll just rebuild my CRM or I'll just recreate it." You know, that I'll just recreate it." You know, that I'll just recreate it." You know, that kind of thing. Fast and loose talk kind of thing. Fast and loose talk kind of thing. Fast and loose talk around stuff like that. And yet there's around stuff like that. And yet there's around stuff like that. And yet there's been a lot of talk around obviously AI been a lot of talk around obviously AI been a lot of talk around obviously AI helps us code better and then people are helps us code better and then people are helps us code better and then people are vibe coding and they're using you know vibe coding and they're using you know vibe coding and they're using you know cursor and others and and then so cursor and others and and then so cursor and others and and then so Starbucks kind of made that a little bit Starbucks kind of made that a little bit Starbucks kind of made that a little bit real when they came out and said we're real when they came out and said we're real when they came out and said we're just going to jettison $400 million just going to jettison $400 million just going to jettison $400 million worth of money we have to spend on worth of money we have to spend on worth of money we have to spend on Microsoft and others for our CRM and Microsoft and others for our CRM and Microsoft and others for our CRM and supply chain management. we're just supply chain management. we're just supply chain management. we're just going to build it ourselves like you going to build it ourselves like you going to build it ourselves like you know over the weekend or something like know over the weekend or something like know over the weekend or something like that. There's been a lot of fast and that. There's been a lot of fast and that. There's been a lot of fast and loose talk around Visual Basic. Yeah.

loose talk around Visual Basic. Yeah. loose talk around Visual Basic. Yeah. And so but and it's like well is it is And so but and it's like well is it is And so but and it's like well is it is it real? You know are a lot of is it real? You know are a lot of is it real? You know are a lot of is enterprise software threatened enterprise software threatened enterprise software threatened >> because someone can just crank it out >> because someone can just crank it out >> because someone can just crank it out unless you're nuts you know unless unless you're nuts you know unless unless you're nuts you know unless you're completely insane. you're completely insane. you're completely insane. >> Building it all yourself with an AI >> Building it all yourself with an AI >> Building it all yourself with an AI agent from scratch is going wait until agent from scratch is going wait until agent from scratch is going wait until you find out the first big problem. If you find out the first big problem. If you find out the first big problem. If you're a big company, that big problem you're a big company, that big problem you're a big company, that big problem could cost you millions of dollars. I could cost you millions of dollars. I could cost you millions of dollars. I think what will happen is more think what will happen is more think what will happen is more everybody's producing MCP servers so you everybody's producing MCP servers so you everybody's producing MCP servers so you can access all the data that sits in a can access all the data that sits in a can access all the data that sits in a CRM or a story or whatever. I think what CRM or a story or whatever. I think what CRM or a story or whatever. I think what will happen is that um it's kind of a will happen is that um it's kind of a will happen is that um it's kind of a abstraction layer essentially an AI abstraction layer essentially an AI abstraction layer essentially an AI layer thing across the top all of these layer thing across the top all of these layer thing across the top all of these systems. I think the new feature set the systems. I think the new feature set the systems. I think the new feature set the going forward the future road map is going forward the future road map is going forward the future road map is going to be owned by that abstraction going to be owned by that abstraction going to be owned by that abstraction layer not by the underlying. So I think layer not by the underlying. So I think layer not by the underlying. So I think is is is Microsoft going to go out of is is is Microsoft going to go out of is is is Microsoft going to go out of business tomorrow? Is not you know is business tomorrow? Is not you know is business tomorrow? Is not you know is their CRM product going to go disappear? their CRM product going to go disappear? their CRM product going to go disappear? No. But I think their ability to No. But I think their ability to No. But I think their ability to >> I think there is going to be there'll be >> I think there is going to be there'll be >> I think there is going to be there'll be downward pressure on a lot of these kind downward pressure on a lot of these kind downward pressure on a lot of these kind of legacy expensive legacy kind of of legacy expensive legacy kind of of legacy expensive legacy kind of brittle uh infrastructure companies brittle uh infrastructure companies brittle uh infrastructure companies because of these alternatives. But you because of these alternatives. But you because of these alternatives. But you know as you know if you have something know as you know if you have something know as you know if you have something that's kind of working the last thing that's kind of working the last thing that's kind of working the last thing you want to do is fix it you know. So you want to do is fix it you know. So you want to do is fix it you know. So >> uh I think they'll be I think there's >> uh I think they'll be I think there's >> uh I think they'll be I think there's pressure there, but I'd be surprised if pressure there, but I'd be surprised if pressure there, but I'd be surprised if any serious like enterprise company any serious like enterprise company any serious like enterprise company ditched their their legacy systems ditched their their legacy systems ditched their their legacy systems anytime soon. But anytime soon. But anytime soon. But >> I should agree with Alistar too. It's >> I should agree with Alistar too. It's >> I should agree with Alistar too. It's MCP is the new thing. Like we we on MCP is the new thing. Like we we on MCP is the new thing. Like we we on board all kinds of new board all kinds of new board all kinds of new >> things here and we're a small small

>> things here and we're a small small >> things here and we're a small small business and the first thing I look for business and the first thing I look for business and the first thing I look for is what's the MCP interface because if is what's the MCP interface because if is what's the MCP interface because if there isn't one then I can't really use there isn't one then I can't really use there isn't one then I can't really use it as well. it as well. it as well. >> So you're down with MCP? I'm down. >> So you're down with MCP? I'm down. >> So you're down with MCP? I'm down. [laughter] There's companies that there's MCP There's companies that there's MCP companies. So like not every product has companies. So like not every product has companies. So like not every product has an MCP server interface. So there's an MCP server interface. So there's an MCP server interface. So there's these companies now that that will only these companies now that that will only these companies now that that will only be in business for a short period of be in business for a short period of be in business for a short period of time, but they have MCP connectors to time, but they have MCP connectors to time, but they have MCP connectors to all these other legacy systems, right? all these other legacy systems, right? all these other legacy systems, right? So that's kind of like a an interesting So that's kind of like a an interesting So that's kind of like a an interesting little niche that's popped up on the little niche that's popped up on the little niche that's popped up on the internet. internet. internet. >> Yeah. But the the problem the problem >> Yeah. But the the problem the problem >> Yeah. But the the problem the problem Alistister is that if the if the as you Alistister is that if the if the as you Alistister is that if the if the as you said and I agree with you if the value said and I agree with you if the value said and I agree with you if the value moved at the at the abstraction layer moved at the at the abstraction layer moved at the at the abstraction layer and the orchestration between these MCPS and the orchestration between these MCPS and the orchestration between these MCPS all the big platform vendors will have all the big platform vendors will have all the big platform vendors will have very limited incentive to expose through very limited incentive to expose through very limited incentive to expose through MCPS because they're losing the value MCPS because they're losing the value MCPS because they're losing the value and this is I think the big going to be and this is I think the big going to be and this is I think the big going to be the biggest challenge there and that's the biggest challenge there and that's the biggest challenge there and that's why I I mean I exaggerate when I said 5 why I I mean I exaggerate when I said 5 why I I mean I exaggerate when I said 5 years but I think that there are big years but I think that there are big years but I think that there are big enterprise software categories that will enterprise software categories that will enterprise software categories that will be destroyed or relegated to just be the be destroyed or relegated to just be the be destroyed or relegated to just be the system of record and the abstraction system of record and the abstraction system of record and the abstraction action. On top of that, I give you action. On top of that, I give you action. On top of that, I give you another stupid analogy, but the the way another stupid analogy, but the the way another stupid analogy, but the the way I'm using AI more and more nowadays is I'm using AI more and more nowadays is I'm using AI more and more nowadays is I'm going back to markdown documents I'm going back to markdown documents I'm going back to markdown documents because the problem is that if you're because the problem is that if you're because the problem is that if you're prisoner of the PowerPoint format or the prisoner of the PowerPoint format or the prisoner of the PowerPoint format or the Microsoft format or whatever PDF format, Microsoft format or whatever PDF format, Microsoft format or whatever PDF format, then you spend an enormous amount of then you spend an enormous amount of then you spend an enormous amount of token just normalizing the data so you token just normalizing the data so you token just normalizing the data so you can use it. If I build my knowledge base can use it. If I build my knowledge base can use it. If I build my knowledge base in markdown, then I can port that to any in markdown, then I can port that to any in markdown, then I can port that to any type of AI agent models. So I think type of AI agent models. So I think type of AI agent models. So I think you're going to see more and more you're going to see more and more you're going to see more and more pressure from that hopefully where you pressure from that hopefully where you pressure from that hopefully where you know customers say okay I want my data

know customers say okay I want my data know customers say okay I want my data somewhere but I want to be able to put somewhere but I want to be able to put somewhere but I want to be able to put whatever abstraction layer or AI layer whatever abstraction layer or AI layer whatever abstraction layer or AI layer on top of it which is not what the on top of it which is not what the on top of it which is not what the Microsoft and the others are doing. Microsoft and the others are doing. Microsoft and the others are doing. They're trying to force you in their They're trying to force you in their They're trying to force you in their platform to keep on the lock in. So platform to keep on the lock in. So platform to keep on the lock in. So there's going to be a very interesting there's going to be a very interesting there's going to be a very interesting dynamic to see around that. I think it's dynamic to see around that. I think it's dynamic to see around that. I think it's going to be super difficult for the going to be super difficult for the going to be super difficult for the incumbents because by definition what incumbents because by definition what incumbents because by definition what you want to do is integrate multiple you want to do is integrate multiple you want to do is integrate multiple systems unless you're a sole Microsoft systems unless you're a sole Microsoft systems unless you're a sole Microsoft shop or or you know and I think those shop or or you know and I think those shop or or you know and I think those companies learned the hard way that companies learned the hard way that companies learned the hard way that wasn't a good thing. You've got multiple wasn't a good thing. You've got multiple wasn't a good thing. You've got multiple system vendors in your in your system vendors in your in your system vendors in your in your infrastructure and you know the the infrastructure and you know the the infrastructure and you know the the notion of trusting one of those notion of trusting one of those notion of trusting one of those individual infrastructure vendors to individual infrastructure vendors to individual infrastructure vendors to integrate data across all of the others integrate data across all of the others integrate data across all of the others is is I think something that people is is I think something that people is is I think something that people struggle with. So they're looking for a struggle with. So they're looking for a struggle with. So they're looking for a third party. I think it's a huge third party. I think it's a huge third party. I think it's a huge opportunity for these com for there are opportunity for these com for there are opportunity for these com for there are a bunch of companies offering AI a bunch of companies offering AI a bunch of companies offering AI automation, back office automation, etc. automation, back office automation, etc. automation, back office automation, etc. That's a huge opportunity for those That's a huge opportunity for those That's a huge opportunity for those guys. There's a trust issue because guys. There's a trust issue because guys. There's a trust issue because these are big enterprises and do they these are big enterprises and do they these are big enterprises and do they trust the small startup and trust the small startup and trust the small startup and unfortunately most of those startups are unfortunately most of those startups are unfortunately most of those startups are spending their time marketing to other spending their time marketing to other spending their time marketing to other startups. And I'll say for for me at startups. And I'll say for for me at startups. And I'll say for for me at least, I'm super cheap. I don't want to least, I'm super cheap. I don't want to least, I'm super cheap. I don't want to pay someone else to do something that I pay someone else to do something that I pay someone else to do something that I can figure out how to do myself. And can figure out how to do myself. And can figure out how to do myself. And actually if I can use cursor to produce actually if I can use cursor to produce actually if I can use cursor to produce I won't name any of the companies but if I won't name any of the companies but if I won't name any of the companies but if I can produce this kind of abstraction I can produce this kind of abstraction I can produce this kind of abstraction layer myself with cursor or get even if layer myself with cursor or get even if layer myself with cursor or get even if just a bit of it if I can integrate my just a bit of it if I can integrate my just a bit of it if I can integrate my shareepoint and my email and my you know shareepoint and my email and my you know shareepoint and my email and my you know then I'm going to do that myself. I'm then I'm going to do that myself. I'm then I'm going to do that myself. I'm not going to. So these companies I think not going to. So these companies I think not going to. So these companies I think there's a real opportunity but I think there's a real opportunity but I think there's a real opportunity but I think they're focusing on marketing to other they're focusing on marketing to other they're focusing on marketing to other startups more than than actually

startups more than than actually startups more than than actually focusing on the bigger enterprise. focusing on the bigger enterprise. focusing on the bigger enterprise. >> Yeah, >> Yeah, >> Yeah, >> I would agree with you because you can >> I would agree with you because you can >> I would agree with you because you can actually force a system where the the actually force a system where the the actually force a system where the the existing legacy becames as you were existing legacy becames as you were existing legacy becames as you were saying Pete kind of historian. So they saying Pete kind of historian. So they saying Pete kind of historian. So they have the data the records and the have the data the records and the have the data the records and the knowledge but then the intelligence sits knowledge but then the intelligence sits knowledge but then the intelligence sits on top and because we have the AI agent on top and because we have the AI agent on top and because we have the AI agent and all technology we can actually build and all technology we can actually build and all technology we can actually build that and control that better. So now that and control that better. So now that and control that better. So now obviously this is going to be dramatic obviously this is going to be dramatic obviously this is going to be dramatic for those big platform vendors because for those big platform vendors because for those big platform vendors because they the way they've been doing it with they the way they've been doing it with they the way they've been doing it with CRM that because they have the data then CRM that because they have the data then CRM that because they have the data then you're forced to stay there and you're you're forced to stay there and you're you're forced to stay there and you're forced to you to implement your forced to you to implement your forced to you to implement your processes within themsel but here we say processes within themsel but here we say processes within themsel but here we say no okay yeah you I'm a CRM I'm sales no okay yeah you I'm a CRM I'm sales no okay yeah you I'm a CRM I'm sales force keep the data there but I'm going force keep the data there but I'm going force keep the data there but I'm going to put the intelligence layer outside to put the intelligence layer outside to put the intelligence layer outside and every year I'm going to say I want and every year I'm going to say I want and every year I'm going to say I want to pay less because I'm only using the to pay less because I'm only using the to pay less because I'm only using the data here I want to pay less because I'm data here I want to pay less because I'm data here I want to pay less because I'm using the data here using the data here using the data here >> yes that's what I was thinking you know >> yes that's what I was thinking you know >> yes that's what I was thinking you know Pete talking about the downward pressure Pete talking about the downward pressure Pete talking about the downward pressure so we may not rip and replace so the so we may not rip and replace so the so we may not rip and replace so the that I show up and say, "Look what I that I show up and say, "Look what I that I show up and say, "Look what I built with lovable or cursor or built with lovable or cursor or built with lovable or cursor or whatever." whatever." whatever." >> It may it may not mean that Waldorf >> It may it may not mean that Waldorf >> It may it may not mean that Waldorf Germany is under threat, but it in that Germany is under threat, but it in that Germany is under threat, but it in that sales negotiation, I think people will sales negotiation, I think people will sales negotiation, I think people will play that card.

play that card. play that card. >> Yeah. >> Yeah. >> Yeah. >> Um a little bit to get a better deal. >> Um a little bit to get a better deal. >> Um a little bit to get a better deal. >> This or can you you know, and then I I >> This or can you you know, and then I I >> This or can you you know, and then I I actually talked to a vendor the other actually talked to a vendor the other actually talked to a vendor the other day who said that their MCP connector day who said that their MCP connector day who said that their MCP connector would cost extra and I was like, would cost extra and I was like, would cost extra and I was like, >> "Oh, whatever." >> "Oh, whatever." >> "Oh, whatever." >> Say it. It's >> Say it. It's >> Say it. It's >> like what is it? 1993 or something like >> like what is it? 1993 or something like >> like what is it? 1993 or something like that. that. that. >> Let me charge you for my API. >> Let me charge you for my API. >> Let me charge you for my API. >> Exactly. >> Exactly. >> Exactly. >> Interestingly enough, you know, I I I I >> Interestingly enough, you know, I I I I >> Interestingly enough, you know, I I I I did a little hobby experiment recently did a little hobby experiment recently did a little hobby experiment recently because a friend of mine does a exotic because a friend of mine does a exotic because a friend of mine does a exotic car events and and he uses Squarespace car events and and he uses Squarespace car events and and he uses Squarespace to sell the spot on these events and we to sell the spot on these events and we to sell the spot on these events and we were looking for a long time a way to were looking for a long time a way to were looking for a long time a way to have your QR codes generated and emails have your QR codes generated and emails have your QR codes generated and emails and SMS and obviously you can do that in and SMS and obviously you can do that in and SMS and obviously you can do that in Squarespace, but they charge you a Squarespace, but they charge you a Squarespace, but they charge you a fortune. I coded with CR the whole fortune. I coded with CR the whole fortune. I coded with CR the whole complete system where I just used the complete system where I just used the complete system where I just used the system of record of Squarespace. I system of record of Squarespace. I system of record of Squarespace. I generate the QR code, I send the email, generate the QR code, I send the email, generate the QR code, I send the email, I send the SMS, I manage the list, I I send the SMS, I manage the list, I I send the SMS, I manage the list, I manage the allocation. Took me about 40 manage the allocation. Took me about 40 manage the allocation. Took me about 40 hours, but I have a system I totally hours, but I have a system I totally hours, but I have a system I totally control and I only use that legacy control and I only use that legacy control and I only use that legacy system as the source of record. So I system as the source of record. So I system as the source of record. So I think of course it's a hobbyist little think of course it's a hobbyist little think of course it's a hobbyist little experiment. It's not enterprise grade experiment. It's not enterprise grade experiment. It's not enterprise grade and whatever you want. But I think this and whatever you want. But I think this and whatever you want. But I think this is a direction you can imagine would is a direction you can imagine would is a direction you can imagine would happen because you have so much control happen because you have so much control happen because you have so much control now over wiring the processes on top of now over wiring the processes on top of now over wiring the processes on top of the data that you you want to be able to the data that you you want to be able to the data that you you want to be able to do that on your own and without being do that on your own and without being do that on your own and without being dependent on the platform. Hey, you know dependent on the platform. Hey, you know dependent on the platform. Hey, you know what? Something just landed on my BS BS what? Something just landed on my BS BS what? Something just landed on my BS BS radar. I have a funny feeling some radar. I have a funny feeling some radar. I have a funny feeling some research firm somewhere is going to research firm somewhere is going to research firm somewhere is going to invent the MCP economy.

>> No, I'm not going to do it. [laughter] >> No, I'm not going to do it. [laughter] >> Yeah, >> Yeah, >> Yeah, >> but you know, I started getting worried >> but you know, I started getting worried >> but you know, I started getting worried as soon as somebody's gonna do it. We as soon as somebody's gonna do it. We as soon as somebody's gonna do it. We are now we're now hearing a lot about are now we're now hearing a lot about are now we're now hearing a lot about the AI economy and every time I hear the AI economy and every time I hear the AI economy and every time I hear someone say that I flash back to the someone say that I flash back to the someone say that I flash back to the internet economy internet economy internet economy >> and we've changed the rules and whatever >> and we've changed the rules and whatever >> and we've changed the rules and whatever had before is gone and it's going to be had before is gone and it's going to be had before is gone and it's going to be different. Ah, different. Ah, different. Ah, [laughter] [laughter] [laughter] >> MCP economy. The one company that I >> MCP economy. The one company that I >> MCP economy. The one company that I think is actually doing the one company think is actually doing the one company think is actually doing the one company I think is doing pretty well and and I I think is doing pretty well and and I I think is doing pretty well and and I say this only because at momenta we've say this only because at momenta we've say this only because at momenta we've kind of we've used it we've used kind of we've used it we've used kind of we've used it we've used co-pilot largely to do the integration co-pilot largely to do the integration co-pilot largely to do the integration and automation and it actually and automation and it actually and automation and it actually quite surprisingly does a really good quite surprisingly does a really good quite surprisingly does a really good job at integrating non-Microsoft you job at integrating non-Microsoft you job at integrating non-Microsoft you know systems and it's quite a it's a know systems and it's quite a it's a know systems and it's quite a it's a pretty intuitive system um to to use pretty intuitive system um to to use pretty intuitive system um to to use you know in comparison and it's in It's you know in comparison and it's in It's you know in comparison and it's in It's how to say this. It has I think a it how to say this. It has I think a it how to say this. It has I think a it comes with a depth understanding of how comes with a depth understanding of how comes with a depth understanding of how these systems function in a way that these systems function in a way that these systems function in a way that other LLM based products like chat GPT other LLM based products like chat GPT other LLM based products like chat GPT and other don't you know and so it feels and other don't you know and so it feels and other don't you know and so it feels much more like oh I kind of this thing much more like oh I kind of this thing much more like oh I kind of this thing kind of knows what I'm trying to do here kind of knows what I'm trying to do here kind of knows what I'm trying to do here you know as you go through the process you know as you go through the process you know as you go through the process of of iterating and iterating iterating of of iterating and iterating iterating of of iterating and iterating iterating to create an agent and the agent to create an agent and the agent to create an agent and the agent creation experience is actually really creation experience is actually really creation experience is actually really good as well. Um I did I did you good as well. Um I did I did you good as well. Um I did I did you remember Nicole Hers of it? I did reach remember Nicole Hers of it? I did reach remember Nicole Hers of it? I did reach out to her and say to say actually this out to her and say to say actually this out to her and say to say actually this is pretty freaking good, you know, is pretty freaking good, you know, is pretty freaking good, you know, [laughter] [laughter] [laughter] we talking directly to her team because we talking directly to her team because we talking directly to her team because I think we're doing a bunch of stuff I think we're doing a bunch of stuff I think we're doing a bunch of stuff that's kind of at the at the bleeding

that's kind of at the at the bleeding that's kind of at the at the bleeding edge of um of what they're doing. But is edge of um of what they're doing. But is edge of um of what they're doing. But is I was really really pleasantly surprised I was really really pleasantly surprised I was really really pleasantly surprised you know you know you know >> I would argue it's existential >> I would argue it's existential >> I would argue it's existential existential for them because if they existential for them because if they existential for them because if they don't do that well then the scenario was don't do that well then the scenario was don't do that well then the scenario was highlighting where people going to put highlighting where people going to put highlighting where people going to put the abstraction away somewhere else is the abstraction away somewhere else is the abstraction away somewhere else is going to happen. So yeah, that's smart going to happen. So yeah, that's smart going to happen. So yeah, that's smart on their side. Now I still believe we on their side. Now I still believe we on their side. Now I still believe we should implement that out side. But yes, should implement that out side. But yes, should implement that out side. But yes, agreed. That's that's a great strategy. agreed. That's that's a great strategy. agreed. That's that's a great strategy. That's a great that's a great strategy. That's a great that's a great strategy. That's a great that's a great strategy. No question about it. By the way, your No question about it. By the way, your No question about it. By the way, your your MCP uh your MCP economy is just your MCP uh your MCP economy is just your MCP uh your MCP economy is just data economy 2.0. It just data economy 2.0. It just data economy 2.0. It just >> the semantic web >> the semantic web >> the semantic web >> or 3.0 or whatever. >> or 3.0 or whatever. >> or 3.0 or whatever. >> Oh. Oh. Semantic web. Ouch. >> Oh. Oh. Semantic web. Ouch. >> Oh. Oh. Semantic web. Ouch. Well, I think the other thing all of all Well, I think the other thing all of all Well, I think the other thing all of all of you know of you know of you know pricing model is going to need to look a pricing model is going to need to look a pricing model is going to need to look a lot more like S3 storage, you know, lot more like S3 storage, you know, lot more like S3 storage, you know, going forward because it's essentially a going forward because it's essentially a going forward because it's essentially a data store, you know, all of those fancy data store, you know, all of those fancy data store, you know, all of those fancy add-ons that you SAP like >> wow.

>> wow. We need to we need to solve for the We need to we need to solve for the We need to we need to solve for the identity web first because identity web first because identity web first because >> the identity is still and it's getting >> the identity is still and it's getting >> the identity is still and it's getting worse and worse and worse. introduced to worse and worse and worse. introduced to worse and worse and worse. introduced to the freaking universe. the freaking universe. the freaking universe. >> So, should we talk should we talk about >> So, should we talk should we talk about >> So, should we talk should we talk about that agent that broke out this week? that agent that broke out this week? that agent that broke out this week? That was very pretty. That was very pretty. That was very pretty. >> Did it really? >> Did it really? >> Did it really? >> Well, let's let's find out. >> Well, let's let's find out. >> Well, let's let's find out. >> Yeah, I know. Did it really? >> Yeah, I know. Did it really? >> Yeah, I know. Did it really? >> Is it marketing? I mean, it's like Open >> Is it marketing? I mean, it's like Open >> Is it marketing? I mean, it's like Open AI has done this kind of marketing pitch AI has done this kind of marketing pitch AI has done this kind of marketing pitch of like super scary. Remember this B2 of like super scary. Remember this B2 of like super scary. Remember this B2 model model model says it's too scary you guys going. And says it's too scary you guys going. And says it's too scary you guys going. And I think it built up a level of of I think it built up a level of of I think it built up a level of of interest that interest that interest that >> Yeah. >> Yeah. >> Yeah. I don't know whether that's or not. I don't know whether that's or not. I don't know whether that's or not. >> Yeah, I'm skeptical, too. >> Yeah, I'm skeptical, too. >> Yeah, I'm skeptical, too. >> Well, but all right. So, the story was >> Well, but all right. So, the story was >> Well, but all right. So, the story was an open AI autonomous agent. It's in its an open AI autonomous agent. It's in its an open AI autonomous agent. It's in its containment vessel, you know, surrounded containment vessel, you know, surrounded containment vessel, you know, surrounded by titanium and force force field and by titanium and force force field and by titanium and force force field and stuff like that. And it found a way to stuff like that. And it found a way to stuff like that. And it found a way to hack the system cuz it's smarter than hack the system cuz it's smarter than hack the system cuz it's smarter than all of us and found bunch of zero days all of us and found bunch of zero days all of us and found bunch of zero days and went choo choo choo. Got it. lowered and went choo choo choo. Got it. lowered and went choo choo choo. Got it. lowered the shields, you know, decloaked the the shields, you know, decloaked the the shields, you know, decloaked the Cllingon spaceship, got out onto the Cllingon spaceship, got out onto the Cllingon spaceship, got out onto the open internet where it's flying around open internet where it's flying around open internet where it's flying around like this, and then it made it over to like this, and then it made it over to like this, and then it made it over to hugging face and started doing lots of hugging face and started doing lots of hugging face and started doing lots of crazy stuff over there. But a lot this crazy stuff over there. But a lot this crazy stuff over there. But a lot this is this was the biggest tech thing that is this was the biggest tech thing that is this was the biggest tech thing that happened in the news this week. And happened in the news this week. And happened in the news this week. And people a lot of people are freaked out.

people a lot of people are freaked out. people a lot of people are freaked out. Now you guys say it's marketing and they Now you guys say it's marketing and they Now you guys say it's marketing and they meant to do that. Other people are like, meant to do that. Other people are like, meant to do that. Other people are like, "See, I told you it's [laughter] "See, I told you it's [laughter] "See, I told you it's [laughter] >> But then now the knee-jerk reaction is >> But then now the knee-jerk reaction is >> But then now the knee-jerk reaction is panic and now everything needs a kill panic and now everything needs a kill panic and now everything needs a kill switch." Whether that's realistic or switch." Whether that's realistic or switch." Whether that's realistic or >> Yes, that's the new It's the new word, >> Yes, that's the new It's the new word, >> Yes, that's the new It's the new word, kill switch. kill switch. kill switch. >> Hey, you know, but Devin, that that >> Hey, you know, but Devin, that that >> Hey, you know, but Devin, that that might be the the ploy, right, is to might be the the ploy, right, is to might be the the ploy, right, is to create that fear and then have that kill create that fear and then have that kill create that fear and then have that kill switch conversation to happen. And I switch conversation to happen. And I switch conversation to happen. And I think that might be because of uh the think that might be because of uh the think that might be because of uh the whole gimme thing, right? These Chinese whole gimme thing, right? These Chinese whole gimme thing, right? These Chinese open models uh becoming a real threat to open models uh becoming a real threat to open models uh becoming a real threat to these these uh US AI labs, right? I these these uh US AI labs, right? I these these uh US AI labs, right? I mean, that's that's kind of the way I mean, that's that's kind of the way I mean, that's that's kind of the way I look at it. They're trying to create look at it. They're trying to create look at it. They're trying to create that um air of fear so that they can that um air of fear so that they can that um air of fear so that they can drive some of the direction of where drive some of the direction of where drive some of the direction of where regulation will go around AI in the US regulation will go around AI in the US regulation will go around AI in the US probably more than anything else.

probably more than anything else. probably more than anything else. >> It's not just it's not just tech people >> It's not just it's not just tech people >> It's not just it's not just tech people or random people saying kill switch. the or random people saying kill switch. the or random people saying kill switch. the United States Congress is now actively United States Congress is now actively United States Congress is now actively talking about it because the Congress talking about it because the Congress talking about it because the Congress got freaked out by this thing and so got freaked out by this thing and so got freaked out by this thing and so kill switch is a bit they're all saying kill switch is a bit they're all saying kill switch is a bit they're all saying that that that >> still sounds like something I overheard >> still sounds like something I overheard >> still sounds like something I overheard a guy in the Starbucks in West Hollywood a guy in the Starbucks in West Hollywood a guy in the Starbucks in West Hollywood talking about the other day and it still talking about the other day and it still talking about the other day and it still sounds but but you know when I think sounds but but you know when I think sounds but but you know when I think about kill switch kill switch is the about kill switch kill switch is the about kill switch kill switch is the metaphorical equivalent of melting ane metaphorical equivalent of melting ane metaphorical equivalent of melting ane down in the in the in the smelting bit down in the in the in the smelting bit down in the in the in the smelting bit you know things [laughter] isn't it it's you know things [laughter] isn't it it's you know things [laughter] isn't it it's like oh it's time to melt down like oh it's time to melt down like oh it's time to melt down anecd anyone who wins. anecd anyone who wins. anecd anyone who wins. >> Wow. >> Wow. >> Wow. >> So, Alistister Alistister, when you were >> So, Alistister Alistister, when you were >> So, Alistister Alistister, when you were in West Hollywood, there were you in West Hollywood, there were you in West Hollywood, there were you working on a screenplay with this guy working on a screenplay with this guy working on a screenplay with this guy called called called >> I was I was pitching I was pitching I >> I was I was pitching I was pitching I >> I was I was pitching I was pitching I was pitching brilliant idea for was pitching brilliant idea for was pitching brilliant idea for >> and also and also remember how efficient >> and also and also remember how efficient >> and also and also remember how efficient was the kill switch in Chernobbile. was the kill switch in Chernobbile. was the kill switch in Chernobbile. >> So, [clears throat] >> So, [clears throat] >> So, [clears throat] >> and whatnobel. So if if the if the core design is flow, So if if the if the core design is flow, whatever key switch you have is not whatever key switch you have is not whatever key switch you have is not necessarily going to work. But I think I necessarily going to work. But I think I necessarily going to work. But I think I agree with your theory, Lonard. I think agree with your theory, Lonard. I think agree with your theory, Lonard. I think there is probably a a a kind of there is probably a a a kind of there is probably a a a kind of marketing effort to try to keep on marketing effort to try to keep on marketing effort to try to keep on positioning the US lab as kind of the positioning the US lab as kind of the positioning the US lab as kind of the frontier model and saying, "Oh, they can frontier model and saying, "Oh, they can frontier model and saying, "Oh, they can be rogue and they can be crazy is be rogue and they can be crazy is be rogue and they can be crazy is actuallying that frontier positioning actuallying that frontier positioning actuallying that frontier positioning and and also creating new policies." And and and also creating new policies." And and and also creating new policies." And when we say, "Oh, government is looking when we say, "Oh, government is looking when we say, "Oh, government is looking at it." And I'm not necessarily pointing at it." And I'm not necessarily pointing at it." And I'm not necessarily pointing at the US government. I think all at the US government. I think all at the US government. I think all governments in the world are the same.

governments in the world are the same. governments in the world are the same. But if you expect governments to make But if you expect governments to make But if you expect governments to make the smart decision when it comes for the smart decision when it comes for the smart decision when it comes for technology, this is where you say, "Oh, technology, this is where you say, "Oh, technology, this is where you say, "Oh, shoot." shoot." shoot." >> Well, >> Well, >> Well, it'll have an unintended consequence, it'll have an unintended consequence, it'll have an unintended consequence, you know. I mean, it's uh it's a it'll you know. I mean, it's uh it's a it'll you know. I mean, it's uh it's a it'll drive maybe a a protectionist kind of drive maybe a a protectionist kind of drive maybe a a protectionist kind of policy conversation. that won't policy conversation. that won't policy conversation. that won't translate well into uh into like translate well into uh into like translate well into uh into like sovereign conversations that are sovereign conversations that are sovereign conversations that are happening outside of the US. So, but I happening outside of the US. So, but I happening outside of the US. So, but I mean that's that's the interesting thing mean that's that's the interesting thing mean that's that's the interesting thing that um uh you know uh my reaction to that um uh you know uh my reaction to that um uh you know uh my reaction to Devon's comment who I think was going to Devon's comment who I think was going to Devon's comment who I think was going to say something. Did I hear say something. Did I hear say something. Did I hear >> Were you gonna say something? >> Were you gonna say something? >> Were you gonna say something? >> Finish your thought and then >> Finish your thought and then >> Finish your thought and then >> No, no, no, no. This I want to hear more >> No, no, no, no. This I want to hear more >> No, no, no, no. This I want to hear more from Devin. from Devin. from Devin. >> No, no, no. the topic. >> No, no, no. the topic. >> No, no, no. the topic. >> The first thing that came through my >> The first thing that came through my >> The first thing that came through my mind was well this is the only one that mind was well this is the only one that mind was well this is the only one that was publicly you know brought out was publicly you know brought out was publicly you know brought out [laughter] all the stuff happening that [laughter] all the stuff happening that [laughter] all the stuff happening that we don't know about not only others but we don't know about not only others but we don't know about not only others but now with all knee-jerk reaction is this now with all knee-jerk reaction is this now with all knee-jerk reaction is this a way to gain control because a a way to gain control because a a way to gain control because a competitive advantage if we overregulate competitive advantage if we overregulate competitive advantage if we overregulate ourselves on this while other areas free ourselves on this while other areas free ourselves on this while other areas free to do whatever they want. So yeah, to do whatever they want. So yeah, to do whatever they want. So yeah, >> you know, again, this is what we know >> you know, again, this is what we know >> you know, again, this is what we know of, but there's stuff like this going on of, but there's stuff like this going on of, but there's stuff like this going on all the time.

all the time. all the time. >> Oh, dude. Yeah, totally. And you know >> Oh, dude. Yeah, totally. And you know >> Oh, dude. Yeah, totally. And you know what? To me, this is more of a statement what? To me, this is more of a statement what? To me, this is more of a statement of there's nothing that's I think uh of there's nothing that's I think uh of there's nothing that's I think uh posit, you know, nothing that reflects posit, you know, nothing that reflects posit, you know, nothing that reflects positively on Open AI for this either. positively on Open AI for this either. positively on Open AI for this either. You know, this idea of a um you know, an You know, this idea of a um you know, an You know, this idea of a um you know, an agent escaping its sandbox means that agent escaping its sandbox means that agent escaping its sandbox means that your whatever the hell you were testing, your whatever the hell you were testing, your whatever the hell you were testing, right? Your whole test environment and right? Your whole test environment and right? Your whole test environment and your test uh approach was wrong. your test uh approach was wrong. your test uh approach was wrong. >> Yeah. >> Yeah. >> Yeah. >> Unsafe. It should have never been able >> Unsafe. It should have never been able >> Unsafe. It should have never been able to get out of the sandbox. If anything, to get out of the sandbox. If anything, to get out of the sandbox. If anything, you you would set up your environment to you you would set up your environment to you you would set up your environment to be able to test all the interfaces and be able to test all the interfaces and be able to test all the interfaces and then you know, you know, provide some then you know, you know, provide some then you know, you know, provide some simulation simulation simulation uh for whatever kind of function you're uh for whatever kind of function you're uh for whatever kind of function you're trying to design in within that sandbox. trying to design in within that sandbox. trying to design in within that sandbox. You're not sitting there. I mean, that's You're not sitting there. I mean, that's You're not sitting there. I mean, that's like it completely defeats the you know like it completely defeats the you know like it completely defeats the you know the purpose of having a sandbox or a the purpose of having a sandbox or a the purpose of having a sandbox or a test bed within a sandbox, right? So, test bed within a sandbox, right? So, test bed within a sandbox, right? So, you know, my question is what the hell you know, my question is what the hell you know, my question is what the hell were your developers doing, right?

were your developers doing, right? were your developers doing, right? >> Well, I think it speaks to the need, we >> Well, I think it speaks to the need, we >> Well, I think it speaks to the need, we were talking about this a few weeks ago, were talking about this a few weeks ago, were talking about this a few weeks ago, I think that it speaks to the need for I think that it speaks to the need for I think that it speaks to the need for government, man. government, man. government, man. >> You know, manage what's happening. >> You know, manage what's happening. >> You know, manage what's happening. >> No, I I mean, we shouldn't be there >> No, I I mean, we shouldn't be there >> No, I I mean, we shouldn't be there should be no celebration. There should should be no celebration. There should should be no celebration. There should be no we shouldn't reward their intent be no we shouldn't reward their intent be no we shouldn't reward their intent in any way. uh because it I it's it's in any way. uh because it I it's it's in any way. uh because it I it's it's massively incompetent. You don't you massively incompetent. You don't you massively incompetent. You don't you don't let something like that happen. don't let something like that happen. don't let something like that happen. Period. And we shouldn't accept that as Period. And we shouldn't accept that as Period. And we shouldn't accept that as >> but in the screenplay that Alistister's >> but in the screenplay that Alistister's >> but in the screenplay that Alistister's working on with that guy in Hollywood, working on with that guy in Hollywood, working on with that guy in Hollywood, >> this is like every movie we've seen. We >> this is like every movie we've seen. We >> this is like every movie we've seen. We do have the smartest developers. We did do have the smartest developers. We did do have the smartest developers. We did have the best containment vessel and it have the best containment vessel and it have the best containment vessel and it got smart and it got figured it out and got smart and it got figured it out and got smart and it got figured it out and it probed and found the weaknesses and it probed and found the weaknesses and it probed and found the weaknesses and it's like that's where you're kind of it's like that's where you're kind of it's like that's where you're kind of like we were so wrong, like we were so wrong, like we were so wrong, >> you know, coming. >> you know, coming. >> you know, coming. >> Yeah. The alien impregnated itself and >> Yeah. The alien impregnated itself and >> Yeah. The alien impregnated itself and we got through quarantine back to the we got through quarantine back to the we got through quarantine back to the earth and and that's how it all happens earth and and that's how it all happens earth and and that's how it all happens and this is what's going on right now.

and this is what's going on right now. and this is what's going on right now. >> Yeah. Well, you don't want to get it >> Yeah. Well, you don't want to get it >> Yeah. Well, you don't want to get it right. So the the Annie's inside right. So the the Annie's inside right. So the the Annie's inside Sigourney Weaver. Sigourney Weaver. Sigourney Weaver. >> Yeah. and then pops out and then you >> Yeah. and then pops out and then you >> Yeah. and then pops out and then you chuck him in the smelterion deal. No problem. I love it. Where are deal. No problem. I love it. Where are you going to shoot? Are you going to you going to shoot? Are you going to you going to shoot? Are you going to shoot in at least 20 locations and spend shoot in at least 20 locations and spend shoot in at least 20 locations and spend at least $350 million on at least $350 million on at least $350 million on >> of course >> of course >> of course >> go for it. Absolutely. >> go for it. Absolutely. >> go for it. Absolutely. >> Jesus. The thing about it though is I >> Jesus. The thing about it though is I >> Jesus. The thing about it though is I think it does if it is a marketing think it does if it is a marketing think it does if it is a marketing effect effort is probably going to effect effort is probably going to effect effort is probably going to backfire because if you look at we're backfire because if you look at we're backfire because if you look at we're we're in a more increasingly we're in a more increasingly we're in a more increasingly protectionist world. you know, the role protectionist world. you know, the role protectionist world. you know, the role of the US as the doicile of most of of the US as the doicile of most of of the US as the doicile of most of these big tech companies. If you're an these big tech companies. If you're an these big tech companies. If you're an industrial company sitting in Europe, industrial company sitting in Europe, industrial company sitting in Europe, one of the considerations you already one of the considerations you already one of the considerations you already have is, well, what if if if if the US have is, well, what if if if if the US have is, well, what if if if if the US takes against my country for whatever takes against my country for whatever takes against my country for whatever reason or decides that my company's reason or decides that my company's reason or decides that my company's doing is working with China or blah blah doing is working with China or blah blah doing is working with China or blah blah blah, they're going to blacklist me. So, blah, they're going to blacklist me. So, blah, they're going to blacklist me. So, I'm not even going to have access to any I'm not even going to have access to any I'm not even going to have access to any of these technologies anyway. And on top of these technologies anyway. And on top of these technologies anyway. And on top of that, there's a risk that this of that, there's a risk that this of that, there's a risk that this thing's going to go rogue and eat me thing's going to go rogue and eat me thing's going to go rogue and eat me from the inside out. Maybe I just use from the inside out. Maybe I just use from the inside out. Maybe I just use that open source version from China. I that open source version from China. I that open source version from China. I mean, at least you know, at least I know mean, at least you know, at least I know mean, at least you know, at least I know that I'm I'm I'm it's not going to get that I'm I'm I'm it's not going to get that I'm I'm I'm it's not going to get switched off like, you know, if I get switched off like, you know, if I get switched off like, you know, if I get blacklisted by the US, my email doesn't blacklisted by the US, my email doesn't blacklisted by the US, my email doesn't work anymore. You know, I can't actually work anymore. You know, I can't actually work anymore. You know, I can't actually access Microsoft systems. I can't. So, access Microsoft systems. I can't. So, access Microsoft systems. I can't. So, maybe I'll just take a shot with this maybe I'll just take a shot with this maybe I'll just take a shot with this thing over here. and and thing over here. and and thing over here. and and >> yeah, >> yeah, >> yeah, >> and and a lot of the useful models are >> and and a lot of the useful models are >> and and a lot of the useful models are going to be much, you know, they're going to be much, you know, they're going to be much, you know, they're going to be like distilled from a larger going to be like distilled from a larger going to be like distilled from a larger model and they'll they'll just be a much

model and they'll they'll just be a much model and they'll they'll just be a much smaller footprint, task specific or task smaller footprint, task specific or task smaller footprint, task specific or task optimized, you know, think about what's optimized, you know, think about what's optimized, you know, think about what's happening with Agentic AI and I got an happening with Agentic AI and I got an happening with Agentic AI and I got an earful of that you know, earful of that you know, earful of that you know, [clears throat] this week with AMD and [clears throat] this week with AMD and [clears throat] this week with AMD and everyone else. Um, it's all just turning everyone else. Um, it's all just turning everyone else. Um, it's all just turning into freaking code with select little into freaking code with select little into freaking code with select little aspects of a function or a task uh aspects of a function or a task uh aspects of a function or a task uh having a bit of fuzzy logic provided by having a bit of fuzzy logic provided by having a bit of fuzzy logic provided by a LLM. And now everyone's talking, well, a LLM. And now everyone's talking, well, a LLM. And now everyone's talking, well, you know, the harness is the most you know, the harness is the most you know, the harness is the most important thing. Well, do you realize important thing. Well, do you realize important thing. Well, do you realize what you're saying? You're saying that what you're saying? You're saying that what you're saying? You're saying that the it it's just code. the it it's just code. the it it's just code. What part of that do you not get? So, What part of that do you not get? So, What part of that do you not get? So, what you're saying is the model is not what you're saying is the model is not what you're saying is the model is not as important anymore. It's the harness as important anymore. It's the harness as important anymore. It's the harness that's that's that's That means that the AI is not That means that the AI is not That means that the AI is not that important. That means, you know, that important. That means, you know, that important. That means, you know, you're you're you're you're you're you're you're you're you're creating this really bloated scaffolding creating this really bloated scaffolding creating this really bloated scaffolding to make to make to make an agent or basically AI useful. And I an agent or basically AI useful. And I an agent or basically AI useful. And I mean, you know, [clears throat] I don't mean, you know, [clears throat] I don't mean, you know, [clears throat] I don't think people are listening to think people are listening to think people are listening to themselves. Do you know what I'm saying?

themselves. Do you know what I'm saying? themselves. Do you know what I'm saying? They're really not listening to They're really not listening to They're really not listening to themselves and at some point they will themselves and at some point they will themselves and at some point they will slowly re realize how ridiculous they slowly re realize how ridiculous they slowly re realize how ridiculous they are. And that's really what's happening are. And that's really what's happening are. And that's really what's happening right now with aic AI, you know. And I right now with aic AI, you know. And I right now with aic AI, you know. And I think um um yeah, there's going to be a think um um yeah, there's going to be a think um um yeah, there's going to be a aha moment in probably about I don't aha moment in probably about I don't aha moment in probably about I don't know probably six months from now with know probably six months from now with know probably six months from now with people going, "Oh crap, we need more people going, "Oh crap, we need more people going, "Oh crap, we need more CPUs." CPUs." CPUs." Well, right now we already know that Well, right now we already know that Well, right now we already know that there's everyone CPUs are like this sexy there's everyone CPUs are like this sexy there's everyone CPUs are like this sexy thing now, but most people don't know it thing now, but most people don't know it thing now, but most people don't know it because everyone's still stuck on this because everyone's still stuck on this because everyone's still stuck on this idea that the GPU is what drives AI, idea that the GPU is what drives AI, idea that the GPU is what drives AI, whatever the hell you mean by AI, right? whatever the hell you mean by AI, right? whatever the hell you mean by AI, right? So, it's it's pretty funny stuff So, it's it's pretty funny stuff So, it's it's pretty funny stuff happening right now. Well, I think happening right now. Well, I think happening right now. Well, I think there's there's one virtue in the in the there's there's one virtue in the in the there's there's one virtue in the in the harness approach in the sense that it harness approach in the sense that it harness approach in the sense that it actually explained that you know the the actually explained that you know the the actually explained that you know the the raw LLM is just one component of intent raw LLM is just one component of intent raw LLM is just one component of intent systems and I think I would I'm less systems and I think I would I'm less systems and I think I would I'm less negative than you are in terms of the negative than you are in terms of the negative than you are in terms of the arness I think the concept is actually arness I think the concept is actually arness I think the concept is actually good now the way it's implemented is a good now the way it's implemented is a good now the way it's implemented is a whole other discussion and the magic out whole other discussion and the magic out whole other discussion and the magic out of it is expect because the problem is of it is expect because the problem is of it is expect because the problem is always the same thing people expect always the same thing people expect always the same thing people expect magic so they expect to write two words magic so they expect to write two words magic so they expect to write two words and have the things do something and have the things do something and have the things do something intelligent no it's all about all the intelligent no it's all about all the intelligent no it's all about all the knowledge you put into it and what you knowledge you put into it and what you knowledge you put into it and what you ask him to do and how you basically ask him to do and how you basically ask him to do and how you basically leverage that value and cycle working leverage that value and cycle working leverage that value and cycle working with it. So I I think it's evolving it's with it. So I I think it's evolving it's with it. So I I think it's evolving it's evolving technologically in the right evolving technologically in the right evolving technologically in the right direction. The problem is all the direction. The problem is all the direction. The problem is all the marketing and all the fuzz and marketing and all the fuzz and marketing and all the fuzz and you know I'm the first one and the new you know I'm the first one and the new you know I'm the first one and the new names. That is the the scary thing. So

names. That is the the scary thing. So names. That is the the scary thing. So >> yeah and and that's the thing you know >> yeah and and that's the thing you know >> yeah and and that's the thing you know you you're better off realizing that it you you're better off realizing that it you you're better off realizing that it isn't magic. And and here's the thing. isn't magic. And and here's the thing. isn't magic. And and here's the thing. People who think that it's magic still People who think that it's magic still People who think that it's magic still have to ride the curve of figuring out, have to ride the curve of figuring out, have to ride the curve of figuring out, well, how does it actually work? well, how does it actually work? well, how does it actually work? >> Yeah. >> Yeah. >> Yeah. >> And once you do that, then you can >> And once you do that, then you can >> And once you do that, then you can figure out how can I apply it in a figure out how can I apply it in a figure out how can I apply it in a useful way. People are starting with useful way. People are starting with useful way. People are starting with magic. They didn't they didn't ride the magic. They didn't they didn't ride the magic. They didn't they didn't ride the the learning curve. They freaking just the learning curve. They freaking just the learning curve. They freaking just subscribed for the magic And so subscribed for the magic And so subscribed for the magic And so they're misguided. and and man, I I see they're misguided. and and man, I I see they're misguided. and and man, I I see this this BS playing out very very this this BS playing out very very this this BS playing out very very clearly and it it's it um I don't know clearly and it it's it um I don't know clearly and it it's it um I don't know it's funny because I do laugh about it it's funny because I do laugh about it it's funny because I do laugh about it quite a bit these days but um quite a bit these days but um quite a bit these days but um >> you won't be laughing for very long when >> you won't be laughing for very long when >> you won't be laughing for very long when it comes for you. Oh, or like it came it comes for you. Oh, or like it came it comes for you. Oh, or like it came for Rick Bada apparently, right? for Rick Bada apparently, right? for Rick Bada apparently, right? >> So, are all what did Rick Belotta get >> So, are all what did Rick Belotta get >> So, are all what did Rick Belotta get hacked?

hacked? hacked? >> Something like that. Yeah. >> Something like that. Yeah. >> Something like that. Yeah. >> So, he's like freaking out now that that >> So, he's like freaking out now that that >> So, he's like freaking out now that that um Yeah. All this AI stuff is um Yeah. All this AI stuff is um Yeah. All this AI stuff is >> So, do you think maybe like your this >> So, do you think maybe like your this >> So, do you think maybe like your this containment escape, is it marketing? Do containment escape, is it marketing? Do containment escape, is it marketing? Do they want people to see it? Like there's they want people to see it? Like there's they want people to see it? Like there's another theory here that I'm just making another theory here that I'm just making another theory here that I'm just making up on the fly for a movie. up on the fly for a movie. up on the fly for a movie. >> What if what if these AI companies are >> What if what if these AI companies are >> What if what if these AI companies are kind of dropping breadcrumbs along the kind of dropping breadcrumbs along the kind of dropping breadcrumbs along the way of evidence to remember early on way of evidence to remember early on way of evidence to remember early on they're in they're being pulled in front they're in they're being pulled in front they're in they're being pulled in front of Congress and they're saying please of Congress and they're saying please of Congress and they're saying please regulate us. You need to regulate us. regulate us. You need to regulate us. regulate us. You need to regulate us. This is too much. It's out of control This is too much. It's out of control This is too much. It's out of control and everything because if we if we look and everything because if we if we look and everything because if we if we look ahead 6 months or a few years when the ahead 6 months or a few years when the ahead 6 months or a few years when the biggest lawsuits in the history of the biggest lawsuits in the history of the biggest lawsuits in the history of the world happen bigger than the cigarette world happen bigger than the cigarette world happen bigger than the cigarette things happen. They might, they may not. things happen. They might, they may not. things happen. They might, they may not. >> They'll be able to have a bunch of >> They'll be able to have a bunch of >> They'll be able to have a bunch of things they can point to all along where things they can point to all along where things they can point to all along where they said, "Well, we were telling you they said, "Well, we were telling you they said, "Well, we were telling you this whole time and Congress didn't do this whole time and Congress didn't do this whole time and Congress didn't do anything and we said regulate us and anything and we said regulate us and anything and we said regulate us and look, you know, look, you know, look, you know, >> I don't know. I mean, yeah, I know that >> I don't know. I mean, yeah, I know that >> I don't know. I mean, yeah, I know that Antropic just settled for a billion and Antropic just settled for a billion and Antropic just settled for a billion and a half a half a half >> for ripping off all the novels that I >> for ripping off all the novels that I >> for ripping off all the novels that I wrote and a bunch of other crap.

wrote and a bunch of other crap. wrote and a bunch of other crap. >> Um, but you're rich now. You're rich >> Um, but you're rich now. You're rich >> Um, but you're rich now. You're rich now. Robin, now. Robin, now. Robin, >> I I wonder when my 50 cent check is >> I I wonder when my 50 cent check is >> I I wonder when my 50 cent check is going to come in the mail for the going to come in the mail for the going to come in the mail for the copyright. copyright. copyright. >> You can be a movie producer then and >> You can be a movie producer then and >> You can be a movie producer then and then you can make you can fund the 350 then you can make you can fund the 350 then you can make you can fund the 350 million movie about Arie popping out million movie about Arie popping out million movie about Arie popping out Sigourney Weaver and getting thrown in a Sigourney Weaver and getting thrown in a Sigourney Weaver and getting thrown in a metal spill. I love it. That's metal spill. I love it. That's metal spill. I love it. That's brilliant. brilliant. brilliant. >> Did anybody go see The Odyssey? >> Did anybody go see The Odyssey? >> Did anybody go see The Odyssey? >> No. >> No. >> No. >> No. Yeah, I did. [clears throat] I did. >> No. Yeah, I did. [clears throat] I did. >> No. Yeah, I did. [clears throat] I did. >> Yeah, it was good. It was good. >> Yeah, it was good. It was good. >> Yeah, it was good. It was good. >> Yeah. Still where the money was spent >> Yeah. Still where the money was spent >> Yeah. Still where the money was spent for sure. for sure. for sure. >> It was like It was epic. I think >> It was like It was epic. I think >> It was like It was epic. I think >> it was definitely an epic. Yes. Yeah. >> it was definitely an epic. Yes. Yeah. >> it was definitely an epic. Yes. Yeah. But but you know, going back to the But but you know, going back to the But but you know, going back to the whole uh regulation thing, the thing is whole uh regulation thing, the thing is whole uh regulation thing, the thing is the genie is already out of the bottle. the genie is already out of the bottle. the genie is already out of the bottle. you know, I think and counting on you know, I think and counting on you know, I think and counting on regulation that's going to be effective regulation that's going to be effective regulation that's going to be effective in any way is I think delusional. in any way is I think delusional. in any way is I think delusional. >> Um, number one, no one in the government >> Um, number one, no one in the government >> Um, number one, no one in the government really knows how to regulate this. And really knows how to regulate this. And really knows how to regulate this. And you know, when you talk about you know, when you talk about you know, when you talk about regulation, you have to figure you have regulation, you have to figure you have regulation, you have to figure you have to be put on purpose. Regulate for what to be put on purpose. Regulate for what to be put on purpose. Regulate for what purpose, for what reason? I don't I mean purpose, for what reason? I don't I mean purpose, for what reason? I don't I mean the the level of conflict of interest the the level of conflict of interest the the level of conflict of interest and weirdness uh at the government level and weirdness uh at the government level and weirdness uh at the government level I and you know when you think about all I and you know when you think about all I and you know when you think about all the commercial ties that happen I mean the commercial ties that happen I mean the commercial ties that happen I mean look you know government owns part of look you know government owns part of look you know government owns part of Intel right they own part of like a Intel right they own part of like a Intel right they own part of like a bunch of bunch of bunch of >> u AI related companies well um how h how

>> u AI related companies well um how h how >> u AI related companies well um how h how can you trust government to then can you trust government to then can you trust government to then tailor regulations that are in the tailor regulations that are in the tailor regulations that are in the interest of the public good and what is interest of the public good and what is interest of the public good and what is the public good in this regard and so it the public good in this regard and so it the public good in this regard and so it becomes really becomes really becomes really >> I mean I think the you know the we could >> I mean I think the you know the we could >> I mean I think the you know the we could have a very long discussion about have a very long discussion about have a very long discussion about whether there's a connection between whether there's a connection between whether there's a connection between regulation and purpose and and what regulation and purpose and and what regulation and purpose and and what purpose it serves so yeah could possible purpose it serves so yeah could possible purpose it serves so yeah could possible it is possible I mean you know we had it is possible I mean you know we had it is possible I mean you know we had seat belt regulation that worked I mean seat belt regulation that worked I mean seat belt regulation that worked I mean there's possible to do regulation that there's possible to do regulation that there's possible to do regulation that works so works so works so >> I don't want to throw the baby out of >> I don't want to throw the baby out of >> I don't want to throw the baby out of the the the The other thing is you don't need The other thing is you don't need The other thing is you don't need >> sometimes you only need one entity to >> sometimes you only need one entity to >> sometimes you only need one entity to strategically enforce something strategically enforce something strategically enforce something a norm right that was not my point Pete a norm right that was not my point Pete a norm right that was not my point Pete because yeah they are a good example of because yeah they are a good example of because yeah they are a good example of regulation that work but for in the case regulation that work but for in the case regulation that work but for in the case of seat belt it serve a purpose that of seat belt it serve a purpose that of seat belt it serve a purpose that make total sense but there's a lot of make total sense but there's a lot of make total sense but there's a lot of regulation that have purposes that do regulation that have purposes that do regulation that have purposes that do not make any sense not make any sense not make any sense >> but that doesn't mean you kind of let's >> but that doesn't mean you kind of let's >> but that doesn't mean you kind of let's not regulate because I have examples not regulate because I have examples not regulate because I have examples >> that's not that's not what I saying I >> that's not that's not what I saying I >> that's not that's not what I saying I saying that the the purpose of the saying that the the purpose of the saying that the the purpose of the regulation should be regulation should be regulation should be topic of extremely high importance and topic of extremely high importance and topic of extremely high importance and it is not just the fact that lobby exist it is not just the fact that lobby exist it is not just the fact that lobby exist is is contradiction to that think we can is is contradiction to that think we can is is contradiction to that think we can apply traditional regulation to AI and I apply traditional regulation to AI and I apply traditional regulation to AI and I say that because take that analogy Pete say that because take that analogy Pete say that because take that analogy Pete applying regulation that says wear a applying regulation that says wear a applying regulation that says wear a seat belt is a regul regulation of how seat belt is a regul regulation of how seat belt is a regul regulation of how you do something the way you drive a car you do something the way you drive a car you do something the way you drive a car you have to you should you should use a you have to you should you should use a you have to you should you should use a seat belt whilst you drive a car the seat belt whilst you drive a car the seat belt whilst you drive a car the problem with regulating how AI functions

problem with regulating how AI functions problem with regulating how AI functions is it's changing so quickly and the is it's changing so quickly and the is it's changing so quickly and the government understanding of how these government understanding of how these government understanding of how these systems actually function even if you systems actually function even if you systems actually function even if you even if they're not neural network based even if they're not neural network based even if they're not neural network based and you can actually see what they're and you can actually see what they're and you can actually see what they're doing is so limited that the notion of doing is so limited that the notion of doing is so limited that the notion of regulating how it works. So the only regulating how it works. So the only regulating how it works. So the only thing you can do then is regulate the thing you can do then is regulate the thing you can do then is regulate the outcome. So if it does something bad, outcome. So if it does something bad, outcome. So if it does something bad, we'll come with a big stick and hit you we'll come with a big stick and hit you we'll come with a big stick and hit you over the head. And that works for over the head. And that works for over the head. And that works for companies that have lots of money, companies that have lots of money, companies that have lots of money, >> but it doesn't work for all the startups >> but it doesn't work for all the startups >> but it doesn't work for all the startups in the AI space. in the AI space. in the AI space. >> Because they don't just as an example, >> Because they don't just as an example, >> Because they don't just as an example, I'm not suggesting this is the way to I'm not suggesting this is the way to I'm not suggesting this is the way to go, but from a consumer protection go, but from a consumer protection go, but from a consumer protection perspective, why not have some perspective, why not have some perspective, why not have some regulations around disclosing, you know, regulations around disclosing, you know, regulations around disclosing, you know, AI generated content on social media AI generated content on social media AI generated content on social media platforms? Yeah, they don't even know platforms? Yeah, they don't even know platforms? Yeah, they don't even know just to say hey this is you know this is just to say hey this is you know this is just to say hey this is you know this is AI generated you know this is the topic AI generated you know this is the topic AI generated you know this is the topic for anyone who has a family chat this is for anyone who has a family chat this is for anyone who has a family chat this is like half of our discussion is is that like half of our discussion is is that like half of our discussion is is that AI generated or not I mean just stuff AI generated or not I mean just stuff AI generated or not I mean just stuff like that could be could be helpful to like that could be could be helpful to like that could be could be helpful to restore a little bit of transparency restore a little bit of transparency restore a little bit of transparency >> in AI so >> in AI so >> in AI so >> but transparency should actually be the >> but transparency should actually be the >> but transparency should actually be the regulation it should be a broad category regulation it should be a broad category regulation it should be a broad category whatever artifact is produced there whatever artifact is produced there whatever artifact is produced there should be transparency on this should be transparency on this should be transparency on this production including advertising and production including advertising and production including advertising and everything and all the crap you so the everything and all the crap you so the everything and all the crap you so the the if you trust government to come up the if you trust government to come up the if you trust government to come up with very small I think we use in our with very small I think we use in our with very small I think we use in our foundation of nations France US we have foundation of nations France US we have foundation of nations France US we have some very deep thinking on the structure some very deep thinking on the structure some very deep thinking on the structure of government but we've deviated totally of government but we've deviated totally of government but we've deviated totally away from that few hundred years later I away from that few hundred years later I away from that few hundred years later I don't think there's any government don't think there's any government don't think there's any government regulation that is based on aspirational regulation that is based on aspirational regulation that is based on aspirational leadership big ideas anymore

and the converse of that is regulation and the converse of that is regulation should open up some of the data so you should open up some of the data so you should open up some of the data so you know going back to the MCP you know we know going back to the MCP you know we know going back to the MCP you know we have a lot of proprietary Curry closed have a lot of proprietary Curry closed have a lot of proprietary Curry closed systems especially like these OEM let's systems especially like these OEM let's systems especially like these OEM let's just take IoT OEMs you know they want to just take IoT OEMs you know they want to just take IoT OEMs you know they want to own their data own their data own their data >> you can't stuff with it if you know in >> you can't stuff with it if you know in >> you can't stuff with it if you know in the in our world in the north in North the in our world in the north in North the in our world in the north in North America our regulatory regulators are America our regulatory regulators are America our regulatory regulators are lawyers and politicians in the east lawyers and politicians in the east lawyers and politicians in the east they're all engineers and doctors and they're all engineers and doctors and they're all engineers and doctors and things and understand that so you can things and understand that so you can things and understand that so you can see a lot they're driving a lot more see a lot they're driving a lot more see a lot they're driving a lot more innovation there because they see how innovation there because they see how innovation there because they see how they can open up systems and get access they can open up systems and get access they can open up systems and get access to it if we to it if we to it if we >> you know you put a bunch of lawyers in >> you know you put a bunch of lawyers in >> you know you put a bunch of lawyers in the room and you you don't really get the room and you you don't really get the room and you you don't really get too far and I think we could too far and I think we could too far and I think we could overregulate ourselves to death and this overregulate ourselves to death and this overregulate ourselves to death and this hurts the startups. This hurts the small hurts the startups. This hurts the small hurts the startups. This hurts the small people who can't lobby who can't, you people who can't lobby who can't, you people who can't lobby who can't, you know, have to go through all these steps know, have to go through all these steps know, have to go through all these steps to just even get things certified to to just even get things certified to to just even get things certified to play the game. play the game. play the game. >> Well, you know, that's an interesting >> Well, you know, that's an interesting >> Well, you know, that's an interesting comment there, Devin, because what you comment there, Devin, because what you comment there, Devin, because what you do find in like in particular in Asian do find in like in particular in Asian do find in like in particular in Asian and even more particularly in China is and even more particularly in China is and even more particularly in China is that you have technocrats. And what I that you have technocrats. And what I that you have technocrats. And what I mean by that is they're actually pretty mean by that is they're actually pretty mean by that is they're actually pretty tech-savvy. Um, you know, uh, when you tech-savvy. Um, you know, uh, when you tech-savvy. Um, you know, uh, when you know I would say that a lot of the folks know I would say that a lot of the folks know I would say that a lot of the folks who are policy makers in the in the US who are policy makers in the in the US who are policy makers in the in the US in particular, um, they don't know the in particular, um, they don't know the in particular, um, they don't know the technology that well. I mean, and that's technology that well. I mean, and that's technology that well. I mean, and that's why, you know, when we listen to these why, you know, when we listen to these why, you know, when we listen to these congressional hearings on tech topics, congressional hearings on tech topics, congressional hearings on tech topics, you know, folks who know, I just find it

you know, folks who know, I just find it you know, folks who know, I just find it like the most comical thing to ever like the most comical thing to ever like the most comical thing to ever watch, right? [laughter] >> Talking to you guys, I have a hard stop >> Talking to you guys, I have a hard stop by the retreat. Yeah. No, you're right. the retreat. Yeah. No, you're right. They do sound pretty silly. These They do sound pretty silly. These They do sound pretty silly. These senators asking question and they're senators asking question and they're senators asking question and they're like they're idiots. They don't know like they're idiots. They don't know like they're idiots. They don't know anything. Yeah. anything. Yeah. anything. Yeah. You should have gone to chat GPT and You should have gone to chat GPT and You should have gone to chat GPT and said, "How does this actually work? said, "How does this actually work? said, "How does this actually work? Explain it to me in terms that a layman Explain it to me in terms that a layman Explain it to me in terms that a layman would understand before." Maybe that would understand before." Maybe that would understand before." Maybe that should be the regulation. should be the regulation. should be the regulation. >> Yeah, maybe it should be. Maybe it >> Yeah, maybe it should be. Maybe it >> Yeah, maybe it should be. Maybe it should be should be should be >> understand how it works. Regulations. >> understand how it works. Regulations. >> understand how it works. Regulations. >> It's time for a shameless plug. >> It's time for a shameless plug. >> It's time for a shameless plug. >> Congratulations. >> Congratulations. >> Congratulations. >> Congratulations. >> Congratulations. >> Congratulations. >> Getting blurred out. >> Getting blurred out. >> Getting blurred out. >> Oh my god. [laughter] >> Yeah. So, you're right. The blur thing >> Yeah. So, you're right. The blur thing is is is >> that's weighty. It's a >> that's weighty. It's a >> that's weighty. It's a It's heavy. It's a textbook. It's heavy. It's a textbook. It's heavy. It's a textbook. >> That is a coffee table book. That is >> That is a coffee table book. That is >> That is a coffee table book. That is >> You get paid by the word like they used >> You get paid by the word like they used >> You get paid by the word like they used to. to. to. >> Yeah, I'm getting paid by the word by >> Yeah, I'm getting paid by the word by >> Yeah, I'm getting paid by the word by somebody. I don't know who's going to do somebody. I don't know who's going to do somebody. I don't know who's going to do it. Maybe Sam Alman. I don't know. Wow.

it. Maybe Sam Alman. I don't know. Wow. it. Maybe Sam Alman. I don't know. Wow. You know, it's I was at I was at uh You know, it's I was at I was at uh You know, it's I was at I was at uh Yeah. So, this a hopefully something Yeah. So, this a hopefully something Yeah. So, this a hopefully something positive. There's no AI in here. It uses positive. There's no AI in here. It uses positive. There's no AI in here. It uses simple analytics and IoT and all the simple analytics and IoT and all the simple analytics and IoT and all the stuff we know. And that's what we're all stuff we know. And that's what we're all stuff we know. And that's what we're all supposed to do. There's things that supposed to do. There's things that supposed to do. There's things that we're all good at. And how do you blend we're all good at. And how do you blend we're all good at. And how do you blend that with things that the world needs, that with things that the world needs, that with things that the world needs, right? And so, right? And so, right? And so, >> and not a lot of compute. >> and not a lot of compute. >> and not a lot of compute. >> Yes. Require a lot of comput. This might >> Yes. Require a lot of comput. This might >> Yes. Require a lot of comput. This might let you use little teeny tiny devices, let you use little teeny tiny devices, let you use little teeny tiny devices, right? Um that that Devon knows all too right? Um that that Devon knows all too right? Um that that Devon knows all too well about. So, you know, it's funny. I well about. So, you know, it's funny. I well about. So, you know, it's funny. I was at I was at this little thing I go was at I was at this little thing I go was at I was at this little thing I go to on Friday mornings. It's kind of like to on Friday mornings. It's kind of like to on Friday mornings. It's kind of like a networking thing for tech or whatever. a networking thing for tech or whatever. a networking thing for tech or whatever. And the woman who saw this and she asked And the woman who saw this and she asked And the woman who saw this and she asked me, "Are you a transhumanist?" me, "Are you a transhumanist?" me, "Are you a transhumanist?" And I'm like, I don't even know what And I'm like, I don't even know what And I'm like, I don't even know what that means. that means. that means. But she assumed that based on this cover But she assumed that based on this cover But she assumed that based on this cover that that's what I am. So whatever that that that's what I am. So whatever that that that's what I am. So whatever that is, you should look that up. is, you should look that up. is, you should look that up. >> I'm up. [laughter] >> Is that connecting computers to people? >> Is that connecting computers to people? >> Hey man, >> Hey man, >> Hey man, >> never thought you were a transhumanist, >> never thought you were a transhumanist, >> never thought you were a transhumanist, but maybe but maybe but maybe >> maybe [laughter] >> seriously, lots of people talk about >> seriously, lots of people talk about writing books. Very, very few people writing books. Very, very few people writing books. Very, very few people actually do it.

actually do it. actually do it. >> Credit to you. >> Credit to you. >> Credit to you. >> Yeah. So there you go. >> Yeah. So there you go. >> Yeah. So there you go. Yeah, it took a while for sure. Um, but Yeah, it took a while for sure. Um, but Yeah, it took a while for sure. Um, but yes, it's easy. It's sustainable yes, it's easy. It's sustainable yes, it's easy. It's sustainable development goals, hunger, sustainable development goals, hunger, sustainable development goals, hunger, sustainable cities, climate change, life below cities, climate change, life below cities, climate change, life below water, biodiversity, water, biodiversity, water, biodiversity, so many things. There we go, Devon. Love so many things. There we go, Devon. Love so many things. There we go, Devon. Love it. Love it. Yeah. And so, uh, this is it. Love it. Yeah. And so, uh, this is it. Love it. Yeah. And so, uh, this is design where it could be in classrooms design where it could be in classrooms design where it could be in classrooms in school. Kids could do these projects. in school. Kids could do these projects. in school. Kids could do these projects. It could be in universities or capstone It could be in universities or capstone It could be in universities or capstone project. You know, who knows who's going project. You know, who knows who's going project. You know, who knows who's going to want to take these on, you know? to want to take these on, you know? to want to take these on, you know? >> Where's the signing event? Where's the >> Where's the signing event? Where's the >> Where's the signing event? Where's the signing event? Where are you going to do signing event? Where are you going to do signing event? Where are you going to do that? that? that? >> I don't know. That's a good question. I >> I don't know. That's a good question. I >> I don't know. That's a good question. I need to think about that. need to think about that. need to think about that. >> In can in can be in Amsterdam. be in Amsterdam. >> Yeah, let's do a book signing in >> Yeah, let's do a book signing in >> Yeah, let's do a book signing in Amsterdam. That would [laughter] be Amsterdam. That would [laughter] be Amsterdam. That would [laughter] be >> in Amsterdam. Yes. Yes. That's >> in Amsterdam. Yes. Yes. That's >> in Amsterdam. Yes. Yes. That's >> You had to bring a bunch of books. >> You had to bring a bunch of books. >> You had to bring a bunch of books. That's all. That's all. That's all. >> To bring a Yeah. These are not like my >> To bring a Yeah. These are not like my >> To bring a Yeah. These are not like my normal paperbacks. This would Yeah, this normal paperbacks. This would Yeah, this normal paperbacks. This would Yeah, this is the airlines going to is the airlines going to is the airlines going to >> He shot himself in the foot with that >> He shot himself in the foot with that >> He shot himself in the foot with that one.

one. one. >> Yeah, I really [laughter] did. I really >> Yeah, I really [laughter] did. I really >> Yeah, I really [laughter] did. I really did. Oh, and you know, like lots of TV did. Oh, and you know, like lots of TV did. Oh, and you know, like lots of TV shows, you know, like you see Weekly, shows, you know, like you see Weekly, shows, you know, like you see Weekly, they do an inmemoriam. they do an inmemoriam. they do an inmemoriam. You probably heard that John De'vorak You probably heard that John De'vorak You probably heard that John De'vorak passed away this week. Uh, and I know passed away this week. Uh, and I know passed away this week. Uh, and I know all of you by the weird look on your all of you by the weird look on your all of you by the weird look on your face either don't know who he is or face either don't know who he is or face either don't know who he is or didn't know about it. But anyway, anyone didn't know about it. But anyway, anyone didn't know about it. But anyway, anyone who read PC magazine or Info World for who read PC magazine or Info World for who read PC magazine or Info World for the last several decades the last several decades the last several decades >> or CNET or all that stuff knows who John >> or CNET or all that stuff knows who John >> or CNET or all that stuff knows who John De'vorak, he probably had the longest De'vorak, he probably had the longest De'vorak, he probably had the longest running columns in tech uh going back running columns in tech uh going back running columns in tech uh going back back in the day. He even wrote a book back in the day. He even wrote a book back in the day. He even wrote a book about OS2. about OS2. about OS2. >> Who knew? >> Who knew? >> Who knew? >> Yeah, >> Yeah, >> Yeah, >> he was it he was the center of the >> he was it he was the center of the >> he was it he was the center of the universe for a long time of uh universe for a long time of uh universe for a long time of uh >> computer technology journalists and >> computer technology journalists and >> computer technology journalists and stuff back in the day when there was a stuff back in the day when there was a stuff back in the day when there was a very short list of those folks. very short list of those folks. very short list of those folks. >> Yeah. Yeah. as someone I saw make a >> Yeah. Yeah. as someone I saw make a >> Yeah. Yeah. as someone I saw make a blurb and go, "Oh, back when the tech blurb and go, "Oh, back when the tech blurb and go, "Oh, back when the tech journalists were actually technical." journalists were actually technical." journalists were actually technical." >> Ouch. I don't know. >> Ouch. I don't know. >> Ouch. I don't know. >> I don't know about that. I don't know >> I don't know about that. I don't know >> I don't know about that. I don't know about that. I don't know. I don't know. about that. I don't know. I don't know. about that. I don't know. I don't know. Remember someone came up with a D'vorak Remember someone came up with a D'vorak Remember someone came up with a D'vorak keyboard. Does that ring a bell, Pete?

keyboard. Does that ring a bell, Pete? keyboard. Does that ring a bell, Pete? >> Yeah. >> Yeah. >> Yeah. >> But I think that was unrelated. I think >> But I think that was unrelated. I think >> But I think that was unrelated. I think >> probably unrelated, but I'm going to go >> probably unrelated, but I'm going to go >> probably unrelated, but I'm going to go with it. with it. with it. >> I I got to run, guys. >> I I got to run, guys. >> I I got to run, guys. >> All right. It's good seeing you guys. >> All right. It's good seeing you guys. >> All right. It's good seeing you guys. >> See you. Have a good day. >> See you. Have a good day. >> See you. Have a good day. Thanks for joining us. We'll see you Thanks for joining us. We'll see you Thanks for joining us. We'll see you next week. [music]