1 00:00:23,080 --> 00:00:24,480 The digital zone 2 00:00:28,410 --> 00:00:32,090 well, hello X, YouTube, LinkedIn, 3 00:00:32,250 --> 00:00:35,450 Twitch, Facebook. And 4 00:00:35,850 --> 00:00:39,610 we're actually streaming this to two YouTube channels at the same 5 00:00:39,610 --> 00:00:43,250 time. The Data Driven channel and I mean sorry, the Frank's World TV 6 00:00:43,250 --> 00:00:47,010 channel and the Impact Quantum YouTube channel. And because this 7 00:00:47,010 --> 00:00:50,330 is kind of a hybrid show, I'm going to post the audio feed for this 8 00:00:50,330 --> 00:00:53,930 on Data Driven and as well as Impact 9 00:00:53,930 --> 00:00:57,290 Quantum, I have with me the most quantum curious person I know, 10 00:00:57,850 --> 00:01:01,610 Candice Gahooly. How's it going, Candace? It's great. I'm really excited to talk 11 00:01:01,610 --> 00:01:05,170 today. I just got all jazzed up by the song. So there you go. That's 12 00:01:05,170 --> 00:01:08,850 why I like that little kind of like early Spice Girls kind of Euro pop 13 00:01:08,850 --> 00:01:12,650 mix, right like that. I actually made that 14 00:01:12,650 --> 00:01:16,130 with AI and that was the prompt like kind of like if you, if you 15 00:01:16,130 --> 00:01:18,730 remember familiar with that era of music. Venga Boys, 16 00:01:20,750 --> 00:01:23,710 the, the tool I use like I'm sorry I can't use that name but I 17 00:01:23,710 --> 00:01:27,070 can substitute like the, the keywords for that. So yeah, 18 00:01:27,390 --> 00:01:31,230 there's actually an extended mix too so. Which I might put on Spotify 19 00:01:31,230 --> 00:01:34,949 one day. I don't know. So yeah. So the big news 20 00:01:34,949 --> 00:01:38,750 and you can tell by my My hat is Nvidia GTC was 21 00:01:38,750 --> 00:01:42,470 this week. I have my, my badge, it's 22 00:01:42,470 --> 00:01:45,550 still going on but the Expo 4 is closed and sadly 23 00:01:46,500 --> 00:01:50,020 I only have an Expo floor pass. 24 00:01:50,740 --> 00:01:54,500 So which, you know, I mean I, I like being on 25 00:01:54,500 --> 00:01:58,180 the Expo floor. I was as someone called, you know, booth 26 00:01:58,180 --> 00:02:01,380 babe, which I suspect is, I think is a compliment. 27 00:02:01,780 --> 00:02:05,540 But you know, I worked a booth 28 00:02:05,540 --> 00:02:07,820 for a lot which was cool because I got to meet a lot of interesting 29 00:02:07,820 --> 00:02:11,580 people, you know, coming to the Red Hat booth and talking about 30 00:02:11,580 --> 00:02:15,270 our solution and product and getting the word out that we're not just a Linux 31 00:02:15,270 --> 00:02:18,790 company. Right. Jensen Huang. And the 32 00:02:18,790 --> 00:02:21,830 keynote, Jensen being the CEO of Nvidia, in case you didn't know, 33 00:02:22,870 --> 00:02:26,590 he and co founder. There's actually a very interesting 34 00:02:26,590 --> 00:02:30,390 book called the Nvidia Way which I highly recommend you 35 00:02:30,390 --> 00:02:33,990 list. I listen to it on Audible. Speaking of which, 36 00:02:35,030 --> 00:02:38,830 Audible is a sponsor of all our shows and if you go to 37 00:02:38,830 --> 00:02:42,380 thedatadrivenbook.com you can get one free book I 38 00:02:42,380 --> 00:02:45,900 recommend it's called the Nvidia Way. I think the guy author's name was Tay Kim. 39 00:02:45,900 --> 00:02:49,740 T, A, E, K, I, M. And you'll get one free book. And 40 00:02:49,740 --> 00:02:53,300 if you decide to get an Audible subscription, which you should, because it's freaking awesome. 41 00:02:53,300 --> 00:02:57,020 I. I live and die by audiobooks mostly because 42 00:02:57,100 --> 00:03:00,860 I'm always. If I'm not traveling for work, I'm driving the 43 00:03:00,860 --> 00:03:04,700 kids around. So it's definitely a safe way to keep 44 00:03:04,700 --> 00:03:07,420 up. I also have wicked cool headphones, 45 00:03:09,170 --> 00:03:12,130 so I can listen to this while I'm walking around and still be involved in 46 00:03:12,130 --> 00:03:15,730 what's going on around me. So, yeah, it was an exciting 47 00:03:15,730 --> 00:03:19,530 week. I think this is the first GTC conference, so I think 48 00:03:19,530 --> 00:03:23,170 it originally stands for Gamers Technology Conference, which really shows kind of 49 00:03:23,170 --> 00:03:26,930 the origin story of Nvidia being primarily a 50 00:03:26,930 --> 00:03:30,650 video card. And what's very interesting 51 00:03:30,650 --> 00:03:33,170 is how that 52 00:03:35,960 --> 00:03:39,600 from. Whoops. There we go. I'm having some equipment 53 00:03:39,600 --> 00:03:43,160 issues, although it is nice to be in the studio because this way, 54 00:03:45,320 --> 00:03:49,040 this way I have full bandwidth and a full screen, so I can have 55 00:03:49,040 --> 00:03:52,800 all the cool bells and whistles and stuff. Yeah, so 56 00:03:52,800 --> 00:03:55,600 I was talking to you, I was texting you, I was messaging you, like, oh, 57 00:03:55,600 --> 00:03:58,400 my God, there's a lot of quantum here, right? So the couple of things really 58 00:03:58,400 --> 00:04:01,640 stood out from, from. From the keynote on day one, and I think really kind 59 00:04:01,640 --> 00:04:05,050 of set the whole tone for it. Obviously, it's in dc, right? So he kind 60 00:04:05,050 --> 00:04:08,770 of talked about the importance of American innovation, the importance of America staying ahead 61 00:04:09,090 --> 00:04:12,810 on AI. He talked about the importance of open source, and he 62 00:04:12,810 --> 00:04:16,410 talked about quantum computing, which I'm like, there you go. I 63 00:04:16,410 --> 00:04:20,210 mean, GTC used to be primarily known as, you 64 00:04:20,210 --> 00:04:23,890 know, the hardware conference. Right now it's about, 65 00:04:23,970 --> 00:04:27,810 you know, AI ecosystems and industrial transformation 66 00:04:27,970 --> 00:04:31,600 and robotics and AI and quantum. Quantum hybrid 67 00:04:31,600 --> 00:04:35,320 computing. I mean, it was. It was. It was cool. 68 00:04:35,320 --> 00:04:38,320 Like, there was something for everyone, right? There was a lot of robots on the 69 00:04:38,320 --> 00:04:42,040 floor. I don't think this one was as kind of crazy manic 70 00:04:42,040 --> 00:04:45,760 as the California one, because as I'm told, the California one, 71 00:04:45,760 --> 00:04:49,200 there's the. You can't walk because it was just so crowded with people. This one 72 00:04:49,200 --> 00:04:52,920 was a little more. I didn't have problems getting places, 73 00:04:52,920 --> 00:04:55,120 although I think some sessions had overflow rooms. 74 00:04:56,790 --> 00:04:59,190 But it was cool. Like, you know, it was nice because it's just that, you 75 00:04:59,190 --> 00:05:02,990 know, it's. It's a relatively short drive for me to go down to 76 00:05:02,990 --> 00:05:05,430 dc, so 77 00:05:06,950 --> 00:05:10,750 it was definitely a lot of fun. You 78 00:05:10,750 --> 00:05:14,230 know, the, the bandwidth situation in the 79 00:05:14,550 --> 00:05:18,190 DC Convention center definitely could have benefited from some of 80 00:05:18,190 --> 00:05:21,950 Nvidia's tech. Well, that's right. Didn't you, you, you, 81 00:05:21,950 --> 00:05:25,270 you, you create a couple shorts, right? I did, I created. So what I ended 82 00:05:25,270 --> 00:05:28,970 up doing, I, I, I, I had a live stream walking, 83 00:05:28,970 --> 00:05:32,690 you know, from. Basically I parked at the Westin and 84 00:05:32,770 --> 00:05:36,450 I walked over to the convention center and I used to work there. Right. So 85 00:05:36,450 --> 00:05:39,130 the Microsoft Office on K Street is like right there. So I kind of know 86 00:05:39,130 --> 00:05:42,970 the area and I kind of. The normal 87 00:05:42,970 --> 00:05:46,210 parking garages I would use back when I worked there were completely full. 88 00:05:46,850 --> 00:05:49,210 So I had to scramble like, oh my God, where am I going to park? 89 00:05:49,210 --> 00:05:52,730 Right. And parking in D.C. is miserable. In fact, the only thing more 90 00:05:52,730 --> 00:05:56,420 miserable than then the parking in D.C. is the 91 00:05:56,420 --> 00:05:58,860 metro in D.C. or for me to Metro in. So 92 00:06:00,460 --> 00:06:02,820 a lot of people like, wait, you drove? And I'm like, yeah, because I can 93 00:06:02,820 --> 00:06:05,860 be, I could be miserable in traffic in my comfort of my own car as 94 00:06:05,860 --> 00:06:09,420 opposed to being miserable like on the train. But 95 00:06:09,660 --> 00:06:13,500 I would choose my car too. I would choose my car. Yeah, you, you and 96 00:06:13,500 --> 00:06:16,100 I, you know, we grew up in New York and like, we did our time 97 00:06:16,100 --> 00:06:18,460 on mass transit. Yeah, I'm done with it. Like, 98 00:06:21,920 --> 00:06:25,200 the only mass transit line I really liked was when I lived in Germany and 99 00:06:25,200 --> 00:06:28,840 then as far as the US Metro north was pretty awesome. Yeah. 100 00:06:28,840 --> 00:06:32,520 Compared to everything else. But like, yeah, Metro north, it's not as good as that. 101 00:06:32,520 --> 00:06:36,360 But I'm also, I also don't live off of 102 00:06:36,360 --> 00:06:39,920 a mark line, which is kind of like the Maryland version of Metro North. Okay. 103 00:06:40,640 --> 00:06:44,400 But, but it was cool. It 104 00:06:44,400 --> 00:06:48,070 was great. So the, the, some of the big announcements. For me, what 105 00:06:48,070 --> 00:06:51,790 really stuck out was kind of the national security angle of it, 106 00:06:52,110 --> 00:06:55,910 right? Yes. And if you look here, I have some pictures that 107 00:06:55,910 --> 00:06:58,990 I took. Like there were sections that were reserved for 108 00:06:59,950 --> 00:07:03,750 congressional staffers. Right. There were a 109 00:07:03,750 --> 00:07:07,590 couple of cases where. Let's see if I can change 110 00:07:07,590 --> 00:07:11,390 up that scene. There we go. Congressional staffers had their 111 00:07:11,390 --> 00:07:15,090 own seats, which I think was very 112 00:07:15,090 --> 00:07:18,770 telling. I think a couple of the panels had elected officials. I think that 113 00:07:18,770 --> 00:07:22,450 senator from Indiana was there. And also Jensen 114 00:07:22,450 --> 00:07:26,210 Wong has kind of figured out kind of the DC kind of 115 00:07:26,210 --> 00:07:28,410 ecosystem pretty well for a tech company. 116 00:07:30,730 --> 00:07:34,490 I mean, he, he basically hit all the right notes. And I've 117 00:07:34,490 --> 00:07:38,290 sat in a lot of these kind of government focused technology conferences. This 118 00:07:38,290 --> 00:07:41,370 was interesting because it was kind of a lot of non government people, a lot 119 00:07:41,370 --> 00:07:45,030 of government people, a lot of armed, a lot of uniformed service walking through. 120 00:07:45,030 --> 00:07:48,830 A lot of people walking through, worked for various departments 121 00:07:48,830 --> 00:07:52,670 of the federal government. And a lot of us were surprised because, you know, they're 122 00:07:52,670 --> 00:07:56,510 all on furlough. So like, what is that? You know, how do you do 123 00:07:56,510 --> 00:07:59,950 that while you're on furlough? And people were like, well, you know, we cannot get 124 00:07:59,950 --> 00:08:03,750 paid and go to the office or not get paid and come here. Right. So 125 00:08:05,910 --> 00:08:09,750 this is way more interesting now. I don't know, I'm not going to 126 00:08:09,750 --> 00:08:13,500 say what, what agency that, that gentleman worked for, but you know, 127 00:08:13,500 --> 00:08:16,100 I thought that was an interesting thing. So there were a lot of feds there. 128 00:08:16,820 --> 00:08:19,620 It was also very interesting from a. 129 00:08:21,460 --> 00:08:25,020 If you haven't watched the keynote, the actual live stream keynote that he gave, it's. 130 00:08:25,020 --> 00:08:28,420 It's very inspiring, right? He kind of puts us in, into perspective. 131 00:08:28,900 --> 00:08:32,660 And the Nvidia creative team really had a good kind of storytelling, 132 00:08:32,660 --> 00:08:36,140 right. Like one of the clip, one of the segments starts from, you know, this 133 00:08:36,140 --> 00:08:39,660 was like, you know, the first video game that shipped that used 134 00:08:40,060 --> 00:08:43,820 an Nvidia accelerator. And then kind of through the years, 135 00:08:43,820 --> 00:08:47,340 like what those video games look like. And also 136 00:08:47,500 --> 00:08:50,140 just a lot of good stuff there. And 137 00:08:51,100 --> 00:08:54,699 they had hardware out on display. If you go here, 138 00:08:54,699 --> 00:08:58,540 this is me on a. Admiring the, 139 00:08:59,580 --> 00:09:03,340 some of the graphics cards. That card there is about, I 140 00:09:03,340 --> 00:09:06,150 think about 300 watts of power on its own. 141 00:09:07,510 --> 00:09:11,270 And the systems that were displayed along next to it all had 142 00:09:11,270 --> 00:09:14,790 like four of them in a row. Right. So these were serious 143 00:09:14,950 --> 00:09:18,670 metal. Right. And I have a lot of YouTube shorts out there and maybe, maybe 144 00:09:18,670 --> 00:09:21,830 I'll show them here. But where I kind of go through all of these things, 145 00:09:23,430 --> 00:09:27,190 there were robots everywhere, Candace. I never seen so many robots 146 00:09:27,190 --> 00:09:29,190 in one place. So, 147 00:09:31,160 --> 00:09:35,000 um, and if you go to Frank's World TV on YouTube, like there's a 148 00:09:35,000 --> 00:09:37,760 lot of shorts I have. So what I ended up doing ultimately was since I 149 00:09:37,760 --> 00:09:41,600 wanted to live stream from the actual convention center, I 150 00:09:41,600 --> 00:09:44,840 couldn't because the band was just miserable. Like you'll see in the live stream, as 151 00:09:44,840 --> 00:09:48,480 soon as I get inside the building, about 50ft inside the building, it just goes 152 00:09:48,480 --> 00:09:52,320 dead. So rather than kind of suffer through that, 153 00:09:52,320 --> 00:09:55,040 I was like, you know what, let me, you know, I'll record some video and 154 00:09:55,040 --> 00:09:58,080 I'll try to upload it. When I tried to do anything kind of like long 155 00:09:58,080 --> 00:10:01,560 form, like horizontally, it took forever to upload. So I'm like, you know what, let 156 00:10:01,560 --> 00:10:04,600 me do just a bunch of shorts. So that's why I got. So whenever I 157 00:10:04,600 --> 00:10:08,120 saw something cool, I capture a couple of like, you know, quick 30 second 158 00:10:08,600 --> 00:10:12,280 minute long video. And this here is 159 00:10:12,360 --> 00:10:13,559 Booze Allen's 160 00:10:16,760 --> 00:10:19,960 platform, I guess, because the robot, everything in green 161 00:10:20,360 --> 00:10:23,720 basically is a bus in robotics. Um, thing. 162 00:10:24,760 --> 00:10:26,760 Everything on top of that is 163 00:10:28,760 --> 00:10:32,440 proprietary thing that Booz Allen big consulting firm here in 164 00:10:32,520 --> 00:10:36,200 the D.C. area, you know, has kind of put on top of 165 00:10:36,200 --> 00:10:39,760 it. So in, in here, which I, I don't know why I'm pointing with my 166 00:10:39,760 --> 00:10:43,160 mouse because you can't see it. But if you look, there's a lidar sensor, 167 00:10:43,160 --> 00:10:46,800 there's a, another thermal 168 00:10:46,800 --> 00:10:50,160 camera. It's a FLIR camera up in the front. The gray thing you see there, 169 00:10:50,960 --> 00:10:54,720 the round thing is the, is the lidar. 170 00:10:54,880 --> 00:10:58,480 And in the back, in that little box right behind 171 00:10:58,480 --> 00:11:02,320 it, the big box in the back is a tactical radio. And 172 00:11:02,400 --> 00:11:06,160 the little thing inside of that tan kind of rectangular 173 00:11:06,160 --> 00:11:08,480 box is a Jetson nano. 174 00:11:11,840 --> 00:11:15,440 Right? So they've taken extra intelligence and put it on top of that. 175 00:11:16,090 --> 00:11:19,450 And there's a lot of, A lot of cool stuff like that. One of the 176 00:11:19,450 --> 00:11:23,250 funniest things to happen is that people are actually cosplaying, walking around 177 00:11:23,250 --> 00:11:25,850 the convention center as Jensen. 178 00:11:27,050 --> 00:11:30,690 Okay. And I got, I gave them. We, you know, at the 179 00:11:30,690 --> 00:11:34,170 booth we had these hats, but we also had red fedoras. So it was giving 180 00:11:34,170 --> 00:11:37,770 that out and we ran. Those were very popular. We ran out of those 181 00:11:37,770 --> 00:11:41,490 within I think the first 45 182 00:11:41,490 --> 00:11:45,100 minutes to an hour. Yeah, that's good swag. That's good swag. We went through 183 00:11:45,100 --> 00:11:48,340 like, like, I think 200 of them. And then we found like an extra 50 184 00:11:48,340 --> 00:11:51,740 on the second day and they were gone in like 10 minutes. So people kept 185 00:11:51,740 --> 00:11:54,300 coming by like, hey, can I get some of that? Can I get one of 186 00:11:54,300 --> 00:11:57,740 those? We're out. And but it's also great 187 00:11:57,740 --> 00:12:01,540 marketing from. Because like, you know, literally the company name 188 00:12:01,540 --> 00:12:05,380 is, you know, the product. Right. So it was pretty cool. And these 189 00:12:05,380 --> 00:12:09,140 guys are funny. I actually did a short video with them and he was 190 00:12:09,140 --> 00:12:12,780 walking around pretending he was Jensen. So the shtick is that the guy on the 191 00:12:12,780 --> 00:12:16,420 right is, you know, they were both his digital 192 00:12:16,420 --> 00:12:20,260 twins. That was basically it. Okay. And they were looking for his third. 193 00:12:20,580 --> 00:12:24,260 So the. What makes us really funny is, is that Jensen is, is as 194 00:12:24,260 --> 00:12:27,860 a, as, as the CEO and co founder of a 5 trillion 195 00:12:27,860 --> 00:12:31,620 dollar company. He's supposedly really down to earth. 196 00:12:31,620 --> 00:12:35,380 I never met him in person, but like, he'll walk around the expo floor 197 00:12:36,100 --> 00:12:39,700 and like introduce himself. And there's always like, he was a few. 198 00:12:40,070 --> 00:12:43,310 He was like, I saw him from about 20ft away and I'm like, please come 199 00:12:43,310 --> 00:12:47,070 here. So we had everything ready, but he didn't. But at 200 00:12:47,070 --> 00:12:49,870 the, at the one in March though, he did come by the red hat Booth. 201 00:12:49,870 --> 00:12:53,670 And he's like, you know, he, he's 202 00:12:53,670 --> 00:12:57,030 like, hey, Red Hat. Like, you know, and one of my team members handed him, 203 00:12:57,030 --> 00:13:00,070 like, we had a scarf and he's like, this is awesome. And he put it 204 00:13:00,070 --> 00:13:03,830 on. He's like, he goes, I remember installing you guys way back in the 205 00:13:03,830 --> 00:13:07,440 day. Like, it was kind of cool. And 206 00:13:08,240 --> 00:13:11,960 so this was pretty funny. But my favorite is the person I met 207 00:13:11,960 --> 00:13:15,800 was. Well, this guy was cool. This 208 00:13:15,800 --> 00:13:19,600 is. He. He lives in Raleigh. This guy. Oops. 209 00:13:20,480 --> 00:13:23,960 And he, he doesn't work for Red Hat, but he does a lot of 210 00:13:23,960 --> 00:13:27,200 videography type stuff. So he had the most impressive rig 211 00:13:28,480 --> 00:13:32,040 and he had what you don't see. You see obviously the big 212 00:13:32,040 --> 00:13:35,690 camera that is a stabilizer. And then below 213 00:13:35,690 --> 00:13:39,370 him he has a 360 camera. So he's able to kind of capture literally everything 214 00:13:40,330 --> 00:13:44,130 from that one rig. So definitely, I 215 00:13:44,130 --> 00:13:46,170 feel like I have to up my equipment game. 216 00:13:47,690 --> 00:13:51,010 Wait, you just got, you just got a new toy? I did just get it, 217 00:13:51,010 --> 00:13:54,610 yeah. My budget is blown for a while. Like, you know, it's the DGX Spark 218 00:13:54,610 --> 00:13:58,050 is what you're referring to. Yes, yes. So they actually had some 219 00:13:58,050 --> 00:14:01,890 giveaways of those and it was definitely like, you know, the hotel thing that people 220 00:14:01,890 --> 00:14:05,610 were excited about. So it did feel kind of good to be one of the 221 00:14:05,610 --> 00:14:09,410 cool kids and be like, I have a DGX bar. Like, you know, and everybody's 222 00:14:09,410 --> 00:14:12,530 like. And the funny thing is a lot of people didn't know you can buy 223 00:14:12,530 --> 00:14:15,690 them at Micro Center. Like, 224 00:14:16,330 --> 00:14:19,170 you know, that's where I got mine. A lot of people were waiting on theirs 225 00:14:19,170 --> 00:14:23,010 to get delivered. Although at the conference, you. They actually had a store 226 00:14:23,010 --> 00:14:26,690 and you could buy them. Wow. Yeah. Though I would imagine with DC 227 00:14:26,690 --> 00:14:28,170 sales tax being what it is, 228 00:14:31,790 --> 00:14:35,310 you know, the sales tax on mine was about 250. I think in D.C. it 229 00:14:35,310 --> 00:14:38,830 would be closer to like 350. Right? But, you know, hey, you know, 230 00:14:39,550 --> 00:14:41,710 you know, you have it right then and there, right? 231 00:14:43,390 --> 00:14:46,990 So this person here, this is Maria Shah. She is a 232 00:14:47,310 --> 00:14:51,030 the YouTuber behind the channel Python 233 00:14:51,030 --> 00:14:53,630 Simplified. And 234 00:14:55,100 --> 00:14:57,500 you know, she goes to a lot of these Nvidia events. So I'm like, you 235 00:14:57,500 --> 00:14:59,660 know, I'm a big fan. So I was like, hey, you know, stop by the 236 00:14:59,660 --> 00:15:03,260 Red Hat booth. And she didn't stop by the Red Hat booth, you know, so 237 00:15:03,260 --> 00:15:05,740 that was cool. Like, it was cool to meet her. She is taller in person 238 00:15:05,740 --> 00:15:09,020 than I thought, which is kind of funny. But 239 00:15:09,260 --> 00:15:12,580 she's super cool and she has like a mini entourage and they were all like 240 00:15:12,580 --> 00:15:16,180 super cool. Like, you know, one guy was like, no, no. Like I pictures 241 00:15:16,180 --> 00:15:19,020 her, picture her wearing this hat and he's like, no, no, you got to get 242 00:15:19,020 --> 00:15:21,340 the right angle. You got to get the right angle. The guy was doing that. 243 00:15:21,340 --> 00:15:23,460 Like I was like one of her people and I was like. And he was 244 00:15:23,460 --> 00:15:26,060 super cool. So 245 00:15:27,580 --> 00:15:31,020 the, yeah, that was, it was a great conference. And 246 00:15:31,340 --> 00:15:35,020 see if I have any other pictures. Oh yeah, there she is. This is the 247 00:15:35,020 --> 00:15:37,420 one that he was like, no, no, you got to get like, you know, with 248 00:15:37,420 --> 00:15:41,100 the branding and stuff like that. So very cool. 249 00:15:41,820 --> 00:15:45,540 But she's really, she's really awesome. And I only recently found out that she 250 00:15:45,540 --> 00:15:49,260 started her career as. And she's relatively young. I didn't 251 00:15:49,260 --> 00:15:52,840 ask her age because that's totally in polite, but she's definitely younger than I 252 00:15:52,840 --> 00:15:56,400 am and she's already changed careers. I think she originally was. 253 00:15:56,480 --> 00:16:00,320 And she only recently shared this. She was originally a graphic designer, 254 00:16:02,240 --> 00:16:06,080 which is interesting. Yeah. And then she's made the switch into. I think originally if 255 00:16:06,080 --> 00:16:09,800 you look through her like her older stuff on YouTube, it was mostly Python 256 00:16:09,800 --> 00:16:12,920 development. Right. Kind of like web development with Python and stuff like that. And then 257 00:16:12,920 --> 00:16:16,680 gradually you've got more as the AI kind 258 00:16:16,680 --> 00:16:19,820 of data thing. So, you know, good on her. You know, like, I think 259 00:16:21,260 --> 00:16:24,540 career changes are going to be kind of the new norm. Right. 260 00:16:24,940 --> 00:16:28,700 Yeah. I mean in every aspect of your life you have to 261 00:16:28,700 --> 00:16:32,340 be adaptable, you have to be flexible. Absolutely. That, 262 00:16:32,340 --> 00:16:36,140 you know, you know, you say that just to, just to handle social interactions. 263 00:16:36,140 --> 00:16:39,820 It has to also do with your profession. You have to, you have to change 264 00:16:40,940 --> 00:16:44,700 and you have to be willing to and, and know that it's scary 265 00:16:45,400 --> 00:16:49,040 and do it anyway. Right, right, right, right. I 266 00:16:49,040 --> 00:16:52,800 mean, I'm actually coming up on the anniversary of when I got 267 00:16:52,800 --> 00:16:56,360 laid off Microsoft. So most people don't know. I did two 268 00:16:56,360 --> 00:16:59,840 stints at Microsoft. One five, five and a half year stint and another like three 269 00:16:59,840 --> 00:17:03,600 and a half year stint. So the first 270 00:17:03,600 --> 00:17:07,080 stint ended because they were like, you got to move to Seattle or else. And 271 00:17:08,760 --> 00:17:12,240 speaking of Microsoft, I saw some folks I used to work with at 272 00:17:12,240 --> 00:17:15,940 Microsoft. So that was cool. They were working the Microsoft booth. Yeah. So we got 273 00:17:15,940 --> 00:17:18,860 to catch up and stuff like that. And 274 00:17:19,980 --> 00:17:23,460 you know, the nice thing about being a red hat is that people really like 275 00:17:23,460 --> 00:17:26,540 red hat because we don't have, you know, 276 00:17:28,060 --> 00:17:31,700 we work with everybody. Right. So like the one, the Microsoft guy was saying 277 00:17:31,700 --> 00:17:35,340 like how crucial red hat is to a lot of his deals. Right. 278 00:17:35,580 --> 00:17:38,140 He makes a lot of money, he's you know, he's a, he's what they call, 279 00:17:38,220 --> 00:17:41,890 they used to call it tsp. And he's like, yeah, like, you know, 280 00:17:42,210 --> 00:17:45,970 Red Hat helps me make my number. Right. AWS people will say that too, 281 00:17:45,970 --> 00:17:49,810 right? It's a very rare kind of company where virtually everybody will work 282 00:17:49,810 --> 00:17:52,050 with us, you know, which is kind of nice. 283 00:17:53,490 --> 00:17:57,330 And so I was faced with that, right. I was a Windows Phone developer, right. 284 00:17:57,490 --> 00:18:01,290 And I made the transition into data science almost 285 00:18:01,290 --> 00:18:05,050 ten years ago now. And yeah, 286 00:18:05,050 --> 00:18:08,760 and I, I wanted, I didn't really want to move to 287 00:18:08,760 --> 00:18:12,520 Seattle, but the real thing that blocked me from like wanting to relocate 288 00:18:12,520 --> 00:18:15,440 was the fact that my family is all on the east Coast. My in laws 289 00:18:16,160 --> 00:18:19,720 were on the east coast. My mom stubbornly stayed in New Jersey way 290 00:18:19,720 --> 00:18:23,520 longer than she needed to after my dad died. And 291 00:18:24,400 --> 00:18:28,240 so I think I made the right decision for my 292 00:18:28,240 --> 00:18:31,680 family. Plus my wife has her own career here in the D.C. metro as a, 293 00:18:32,640 --> 00:18:36,270 as a fed. So it just made a lot of sense. 294 00:18:36,590 --> 00:18:40,190 But we know what's really funny, Candace, is the whole. 295 00:18:40,350 --> 00:18:43,070 Let me share this. This is a little bit of 296 00:18:44,030 --> 00:18:47,750 self promotion, I suppose. This 297 00:18:47,750 --> 00:18:51,510 here is the blog post that Plural site did 298 00:18:51,510 --> 00:18:55,310 on me. Well, that was very cool though. I mean, we can take. It was 299 00:18:55,310 --> 00:18:58,950 cool. Thank you, thank you. It really was cool and you deserve it because like, 300 00:18:58,950 --> 00:19:02,560 it really, it came from your, 301 00:19:02,720 --> 00:19:06,080 your love of lifelong learning and 302 00:19:06,800 --> 00:19:10,280 who can't respect that, you know, that's what's so 303 00:19:10,280 --> 00:19:13,880 fantastic about it. Like, and you could tell we're recording live because you have like 304 00:19:13,880 --> 00:19:14,240 a film. 305 00:19:19,040 --> 00:19:22,320 So they did this really nice story about like, you know, kind of like, you 306 00:19:22,320 --> 00:19:25,960 know, the situation I was in was I really was a Windows Phone 307 00:19:25,960 --> 00:19:28,600 developer and it was just kind of like not, 308 00:19:29,720 --> 00:19:32,600 not a good time to be in Italy. I was the only company that would 309 00:19:32,600 --> 00:19:35,720 had any kind of thing related work to that was Microsoft. 310 00:19:36,200 --> 00:19:39,000 And every single job I applied to that year at Microsoft, they're like, you have 311 00:19:39,000 --> 00:19:42,600 to move to, you have to relocate to Seattle. And I'm like, that's not happening. 312 00:19:43,320 --> 00:19:47,080 So they did a really nice story, kind of like, you know, really 313 00:19:47,080 --> 00:19:50,800 talking about career shifts and changes, you know, although some 314 00:19:50,800 --> 00:19:54,200 people would argue I'm still an engineer, right? So I didn't really change radically. 315 00:19:55,530 --> 00:19:59,010 But you know, even if you're in one field, even a field that's, you know, 316 00:19:59,010 --> 00:20:02,170 quote unquote, a, you know, great career path like 317 00:20:02,890 --> 00:20:06,690 software or development, your career, what, what 318 00:20:06,690 --> 00:20:10,170 it looks like is going to change from the moment you get your degree 319 00:20:10,890 --> 00:20:14,410 or, you know, graduate from a boot camp is Radically going to change. 320 00:20:14,730 --> 00:20:18,170 Right. When I look back in my classes, like, you know, 321 00:20:18,490 --> 00:20:22,050 the one that the. The basically was 322 00:20:22,130 --> 00:20:25,930 Introduction to Relational Databases. Right. SQL and all 323 00:20:25,930 --> 00:20:29,490 that, that's the one that has probably changed the least. 324 00:20:30,370 --> 00:20:34,210 Right. Everything else is kind of like, you know, the language, no one uses Pascal, 325 00:20:34,210 --> 00:20:37,890 no one uses fortran, no one uses prologic. And what was the other one? 326 00:20:39,170 --> 00:20:42,970 There was some AI course I took. I'm blanking on whatever language that was. 327 00:20:42,970 --> 00:20:46,050 But that is completely irrelevant to today's AI. Right. 328 00:20:48,740 --> 00:20:52,580 So it's, I mean, it's just cool. And basically pluralsight has this, you know, 329 00:20:52,980 --> 00:20:56,580 whole thing. And today, candace, is day 1100, if you can believe 330 00:20:56,580 --> 00:20:59,660 that. That's fantastic. I mean, but 331 00:20:59,660 --> 00:21:03,220 legitimately finding how much time a day? 332 00:21:04,340 --> 00:21:08,100 5 minutes, 10 minutes. Today, today I managed to put in like 333 00:21:08,420 --> 00:21:11,860 30 minutes. But just to say I'm going to learn something new. 334 00:21:12,350 --> 00:21:15,870 Right. You know, and you know, that's, I mean, that's really been, 335 00:21:16,110 --> 00:21:19,790 you know, my entire last year, you know, 336 00:21:19,790 --> 00:21:23,630 with, you know, impact quantum and, and data driven. Just 337 00:21:23,790 --> 00:21:27,590 learning something new every day and figuring 338 00:21:27,590 --> 00:21:31,430 out what's useful and what, you know, is 339 00:21:31,430 --> 00:21:34,190 just a lot of hype and I can kind of not really worry about it. 340 00:21:34,190 --> 00:21:37,950 Right. But being willing to learn. Yeah, 341 00:21:38,110 --> 00:21:41,150 I mean, that's, that is going to be the adaptability. And 342 00:21:41,470 --> 00:21:45,190 particularly this is even before kind of people are freaking out about AI taking 343 00:21:45,190 --> 00:21:48,590 away all the jobs. Right. Even before that you really needed to be 344 00:21:48,590 --> 00:21:52,110 adaptable. Right. And I know people that. I mean, 345 00:21:52,110 --> 00:21:55,750 honestly, for me, I wish I could say I started off with that mindset, but 346 00:21:55,750 --> 00:21:57,950 it really took major life crises. 347 00:22:00,110 --> 00:22:02,190 Crazy. What's the plural crisis. 348 00:22:04,810 --> 00:22:08,530 But it took multiple things like whether it was the 349 00:22:08,530 --> 00:22:12,290 dot com bust followed by 911 for me to go from being 350 00:22:12,290 --> 00:22:15,890 a Java developer to a. NET developer and then 351 00:22:15,890 --> 00:22:19,450 going from basically being Windows Stack, Windows 352 00:22:19,530 --> 00:22:23,170 admin developer, engineer to data 353 00:22:23,170 --> 00:22:26,730 science. And AI also took a major 354 00:22:26,730 --> 00:22:30,450 crisis. It's one thing. The previous time I was 355 00:22:30,450 --> 00:22:34,250 laid off, I had no wife, I had no kids, I didn't have a 356 00:22:34,250 --> 00:22:37,970 mortgage. Right. You know, the second time it happened, I did have 357 00:22:37,970 --> 00:22:41,770 all of those. Right. So it was definitely a. You know, 358 00:22:42,170 --> 00:22:45,450 sometimes panic and fear and loathing can lead to 359 00:22:45,450 --> 00:22:49,050 motivation. Look, I mean, my 360 00:22:49,050 --> 00:22:52,770 career started, you know, I was, I was a, I was 361 00:22:52,770 --> 00:22:55,290 an English women's studies communication major. 362 00:22:56,490 --> 00:22:59,960 I graduated from Barnard College of Columbia University, 363 00:23:00,600 --> 00:23:04,360 which is kind of a big deal. I worked very hard. Thank you. 364 00:23:04,760 --> 00:23:08,400 It's legit. Ivy League. Legit. Legit. And I 365 00:23:08,400 --> 00:23:12,240 went into publishing. I just, that's where I landed My first job 366 00:23:12,240 --> 00:23:15,679 and I, I loved being around books. That was pretty 367 00:23:15,679 --> 00:23:19,520 obvious. I remember one of my, one of 368 00:23:19,520 --> 00:23:22,960 my experiences was when Bridget Jones's 369 00:23:22,960 --> 00:23:26,520 Diary came out in, in, in, in 370 00:23:26,520 --> 00:23:30,300 paperback and I was at Penguin Putnam at the time and 371 00:23:30,300 --> 00:23:33,940 you know, just figuring out how to keep all the, all the stores in stock 372 00:23:33,940 --> 00:23:37,740 to keep it, you know, riding that best seller wave. And then finally, 373 00:23:37,740 --> 00:23:41,340 you know, publishing was condensing and then I, and then I, I 374 00:23:41,340 --> 00:23:45,180 immigrated to, to, to Canada and 375 00:23:45,660 --> 00:23:49,500 I knew publishing. But that's when I started in technology 376 00:23:51,260 --> 00:23:54,910 and went into tech publishing. Tech edtech, you know, 377 00:23:54,910 --> 00:23:58,430 pub ed tech. And I was selling, you know, 378 00:23:58,430 --> 00:24:02,230 all kinds of technology to every developer that I could find. 379 00:24:02,470 --> 00:24:06,190 Evolving, just evolving with the market. I think that's where I first 380 00:24:06,190 --> 00:24:09,790 met you. You were like at Silverlight Conference or something like that. At the 381 00:24:09,790 --> 00:24:12,390 Manning booth or was it. Yeah, it was Manning 382 00:24:13,670 --> 00:24:16,390 and that's what it was. I mean I had to, I had to you know, 383 00:24:16,390 --> 00:24:20,230 learn and understand everything. You know, talking about Silverlight to Python 384 00:24:20,390 --> 00:24:24,150 to, you know, and then it became to understanding, you know, machine learning 385 00:24:24,150 --> 00:24:27,510 and TensorFlow and PyTorch and now 386 00:24:27,750 --> 00:24:31,030 you know, just delving into quantum and 387 00:24:31,590 --> 00:24:33,750 being a little bit obsessed with 388 00:24:35,190 --> 00:24:38,950 quantum biology. That's all in quantum chemistry and 389 00:24:38,950 --> 00:24:42,750 quantum consciousness. That's really 390 00:24:42,750 --> 00:24:46,430 tickled, tickled me. Recently we have a great show on in the 391 00:24:46,430 --> 00:24:50,170 queue about quantum where we kind of, we don't go into 392 00:24:50,170 --> 00:24:53,410 it in detail but we do talk about it with, with 393 00:24:53,970 --> 00:24:57,810 a legitimate researcher, right. Who does like, you know, 394 00:24:57,970 --> 00:25:01,490 we get into a good conversation with her about space satellites and stuff like that 395 00:25:01,490 --> 00:25:05,210 and kind of like what's the logistics of that? Like, because like, and I 396 00:25:05,210 --> 00:25:08,770 was, I, I got, I got the answer to my question of like why Laser? 397 00:25:09,490 --> 00:25:13,210 Like, you know what the acronym behind laser means? Like for me I never got 398 00:25:13,210 --> 00:25:16,880 a good answer until that show. So. Right. If you're not already subscribed, do 399 00:25:16,880 --> 00:25:20,680 subscribe. That was a cool conversation and how we're, we're going. You know, you 400 00:25:20,680 --> 00:25:24,280 can connect up in space. It's very different than connecting here down at 401 00:25:24,280 --> 00:25:27,840 Earth, right? Well, yeah. Plus the, the notion of you have like 402 00:25:28,160 --> 00:25:31,880 she didn't give it in freedom units, she gave them in kilometers. But like, you 403 00:25:31,880 --> 00:25:35,480 know, it's actually if you have the 404 00:25:35,480 --> 00:25:38,360 longest subfloor sub ocean floor cable is like 405 00:25:38,360 --> 00:25:41,250 40,000km and 406 00:25:42,370 --> 00:25:46,170 it's actually faster to go up to a satellite and 407 00:25:46,170 --> 00:25:48,210 then back down because that's more of a, 408 00:25:49,890 --> 00:25:53,490 it's, it'll, it'll, it'll end up less than 40,000 kilometers. 409 00:25:55,170 --> 00:25:58,410 Right. Plus there's also. And this is the part I have to listen to it 410 00:25:58,410 --> 00:26:00,690 again because I understood it when she said it 411 00:26:02,690 --> 00:26:06,370 and now I can't describe it. Like. But, but there's a. There's 412 00:26:06,370 --> 00:26:10,160 a. Some quantum phenomena that would get lost through going 413 00:26:10,160 --> 00:26:13,160 through all the repeaters on terrestrial cables. 414 00:26:13,640 --> 00:26:17,240 Whereas if you bounce to the satellite, the satellite is only the only 415 00:26:18,200 --> 00:26:21,920 repeater. So you have one repeater. Right. I remember that. I 416 00:26:21,920 --> 00:26:25,640 remember we were really blown away by that. I don't remember why that mattered. I'll 417 00:26:25,640 --> 00:26:29,320 have to listen to it again. But. But it did matter. It did. Oh, it 418 00:26:29,320 --> 00:26:32,520 absolutely mattered. It had to do, I think with the distance. 419 00:26:34,040 --> 00:26:37,860 I thought it was the repeaters. Well, that they brought 420 00:26:37,860 --> 00:26:41,180 down the distance that it had to. I think it was distance, but it was 421 00:26:41,180 --> 00:26:44,940 also repeaters because you need to repeat. You need to have a repeater, even for 422 00:26:44,940 --> 00:26:48,700 fiber, which I didn't know that. So basically the signal will 423 00:26:48,700 --> 00:26:52,460 lose strength over a certain amount of time. Right. And then you have to 424 00:26:52,460 --> 00:26:56,020 amplify it every time. So because 425 00:26:56,660 --> 00:27:00,460 it's 40,000km and it has to go through a tube, basically 426 00:27:00,460 --> 00:27:04,310 the cable, you need repeaters every so often. 427 00:27:04,310 --> 00:27:06,830 And each one of those repeaters would have to 428 00:27:08,190 --> 00:27:11,230 have special magic hand wavium 429 00:27:12,430 --> 00:27:15,310 to preserve the quantum space. 430 00:27:15,710 --> 00:27:19,510 Quantum. Quantum information input that it gets and then on 431 00:27:19,510 --> 00:27:21,950 the output. And there's a whole lot of 432 00:27:22,910 --> 00:27:26,750 barriers. She explains it really well. I'm not going to, 433 00:27:27,620 --> 00:27:30,700 but there's a whole lot of barriers that, you know, how do you. Preserving that 434 00:27:30,700 --> 00:27:34,500 information is not trivial. So it's just easier to throw something in orbit that can 435 00:27:34,500 --> 00:27:38,260 do it just once and then back down. We. So you also get the distance 436 00:27:38,340 --> 00:27:42,060 benefit too. Right. And that pesky speed of light thing keeps 437 00:27:42,060 --> 00:27:45,620 coming up. So. But this is going to be an upcoming. 438 00:27:45,620 --> 00:27:49,380 This. It's an upcoming show. Yeah, it's very exciting. 439 00:27:49,620 --> 00:27:52,580 I think two shows from now. It's brilliant. Brilliant. 440 00:27:53,220 --> 00:27:56,700 Yeah, she was cool. But yeah, speaking of 441 00:27:56,700 --> 00:28:00,380 quantum, I'm. There was a lot of quantum 442 00:28:00,380 --> 00:28:03,980 companies there, like out on the expo floor. So it was really cool. 443 00:28:03,980 --> 00:28:07,220 So I bumped into and I invited. I gave everyone 444 00:28:07,620 --> 00:28:11,260 like, you know, my contact information. I was like, hey, you know, we got 445 00:28:11,260 --> 00:28:14,980 this and you know, impact Quantum. And so I 446 00:28:14,980 --> 00:28:18,820 bumped into. Not. The display thing is not cooperating with me there it 447 00:28:18,820 --> 00:28:21,450 is. So inflection was there. 448 00:28:22,410 --> 00:28:24,010 Quantum machines was there, 449 00:28:26,650 --> 00:28:30,490 Quero was there, Yuval's 450 00:28:30,490 --> 00:28:34,170 company was there. He wasn't there. But like the people knew him. 451 00:28:34,330 --> 00:28:37,690 So there's a lot. So I introduced myself to everybody there, like hey, you know, 452 00:28:37,690 --> 00:28:41,330 because we're always looking for guests. So that's 453 00:28:41,330 --> 00:28:44,770 a plug for if you're a quantum company. If you're listening, it's 454 00:28:44,770 --> 00:28:48,620 ditto for Data Driven. Right. I mean, it's, it's. What's interesting 455 00:28:48,620 --> 00:28:52,300 is, and I kind of suspected this like a couple years 456 00:28:52,300 --> 00:28:56,060 ago, like, people always like, why are you, why are you interested 457 00:28:56,060 --> 00:28:59,260 in quantum? Right. Because I'm like, there's going to be an overlap of AI and 458 00:28:59,260 --> 00:29:02,859 quantum. Absolutely. And like, and I 459 00:29:02,859 --> 00:29:05,900 also kind of, like, I also kind of like a year ago kind of said, 460 00:29:05,900 --> 00:29:09,500 you know, it's looking like Nvidia one day will be thought of more of as 461 00:29:09,500 --> 00:29:13,240 a defense contractor and critical to national defense. When I said 462 00:29:13,240 --> 00:29:17,040 it, I looked like I was a lunatic. But if you watch the keynote, 463 00:29:17,040 --> 00:29:19,920 I highly recommend you go do that. Like, it's not that hard of a stretch. 464 00:29:19,920 --> 00:29:23,760 He didn't say it in so many words, but it was pretty clear. Like the, 465 00:29:23,760 --> 00:29:27,160 the writings on the wall. Like, this is a national security issue. 466 00:29:27,720 --> 00:29:31,520 Right. And, and, and, and props to Jensen 467 00:29:31,520 --> 00:29:32,200 Huang for 468 00:29:35,320 --> 00:29:38,960 setting the stage for who the adversary is without saying that said 469 00:29:38,960 --> 00:29:42,500 adversary by name. Okay. And since his, I think his 470 00:29:42,500 --> 00:29:46,220 family's from Taiwan, so like, he's probably, it's pretty close 471 00:29:46,220 --> 00:29:49,260 to home in a lot of ways. Right. 472 00:29:50,460 --> 00:29:53,820 And now it's just very impressive. Kind of like 473 00:29:54,060 --> 00:29:57,900 it's these emerging to emerging intersections. Yeah. That 474 00:29:57,900 --> 00:30:01,580 are what's really the most exciting. Like when you, when you think about robotics 475 00:30:01,900 --> 00:30:05,660 and about AI and then you think about quantum 476 00:30:05,660 --> 00:30:08,880 hybrid. Yeah. I mean, these are not 477 00:30:08,880 --> 00:30:12,400 isolated silos of technology. These are very closely 478 00:30:12,400 --> 00:30:15,920 integrated. And you know, my 479 00:30:15,920 --> 00:30:18,560 advice to anyone out there is, you know, get good at one. 480 00:30:19,520 --> 00:30:22,319 Right. Because it's very easy to look at all this, get overwhelmed. Right. But get 481 00:30:22,319 --> 00:30:25,560 good at one silo and then at least have a passing 482 00:30:25,560 --> 00:30:29,360 understanding, conversational understanding of the other ones. Right. Think of it 483 00:30:29,360 --> 00:30:33,020 like human languages. Right. You obviously have your native language and if you can, you 484 00:30:33,020 --> 00:30:36,500 don't have to be totally fluent in a second language. But as long as you 485 00:30:36,500 --> 00:30:40,260 can kind of like have a base understanding and kind of ability to get around, 486 00:30:40,740 --> 00:30:42,900 that is going to open up more doors for you. And I think the same 487 00:30:42,900 --> 00:30:46,180 is true in tech. Right. Like, you know, obviously my home base is 488 00:30:47,380 --> 00:30:51,140 data science and AI, but you 489 00:30:51,140 --> 00:30:54,820 know, soon, maybe one day quantum, Right. I'll be able to explain 490 00:30:55,140 --> 00:30:56,580 why the satellites are better 491 00:30:59,150 --> 00:31:02,350 than, than the landlines. But, you know, 492 00:31:03,550 --> 00:31:07,270 but I think it's also interesting to realize, like, how much 493 00:31:07,270 --> 00:31:10,790 we do know about quantum more than the 494 00:31:10,790 --> 00:31:14,390 average Technologist. Right. Because people are asking me like, why is 495 00:31:14,390 --> 00:31:17,550 quantum a big deal? And I was explaining it and those people like, oh, okay. 496 00:31:17,950 --> 00:31:21,790 You know, and it's like, it's hard. I'm like, yeah, it's very hard. Like, 497 00:31:21,950 --> 00:31:25,510 you know, when I first learned, heard about it, like, I would go 15 498 00:31:25,510 --> 00:31:27,990 minutes, I'd get a migraine, I'd have to stop. Right, 499 00:31:29,190 --> 00:31:32,950 right. Break it down. And you understand that, you know, quantum is 500 00:31:32,950 --> 00:31:36,790 important. It's important for certain businesses, 501 00:31:36,790 --> 00:31:40,390 certain sectors way more than others. It will 502 00:31:40,390 --> 00:31:44,190 affect all sectors, but. And some are more 503 00:31:44,190 --> 00:31:47,590 obvious than others. Right. Like there's going to be some sectors that are going to 504 00:31:48,710 --> 00:31:52,510 immediately be impacted. Right. Security. It. Security being probably 505 00:31:52,510 --> 00:31:56,100 the most obvious. I think health is another, really. Health is another 506 00:31:56,100 --> 00:31:59,580 one. Anything where you have to simulate chemistry. 507 00:31:59,980 --> 00:32:02,780 Yes. Oh my God. I spoke to a 508 00:32:03,100 --> 00:32:06,380 phenomenal woman yesterday. We're gonna have her on the show 509 00:32:06,700 --> 00:32:10,060 and she is this molecular 510 00:32:10,060 --> 00:32:12,780 chemist and she is just 511 00:32:12,780 --> 00:32:16,180 fascinated about the intersection of 512 00:32:16,180 --> 00:32:19,510 chemistry, biology and quantum. And 513 00:32:19,910 --> 00:32:23,670 just, and it's just so important to understand the intersections there. And 514 00:32:23,910 --> 00:32:27,670 that's going to be a great conversation as well. Sorry. No, no, it's a 515 00:32:27,670 --> 00:32:31,190 very exciting time to be like, you know, I mean, honestly, like, if I, 516 00:32:32,390 --> 00:32:35,349 you know, one conference had robots, had AI, had 517 00:32:37,510 --> 00:32:40,950 quantum computing, like all in one place, man, it doesn't get much better than that. 518 00:32:41,590 --> 00:32:45,190 What was really interesting though was a, this was kind of 519 00:32:45,440 --> 00:32:48,600 talk about in the keynote where he talks about, you know, one of the server 520 00:32:48,600 --> 00:32:51,880 racks that they have for their supercomputer is like over 2 million parts. Right. From 521 00:32:51,880 --> 00:32:55,280 like hundreds of different suppliers. So you have to give it 522 00:32:55,520 --> 00:32:58,640 props to Nvidia's like, logistics, plus also 523 00:33:00,160 --> 00:33:03,880 the electrical systems that they need. The cooling system, like they had one, they had 524 00:33:03,880 --> 00:33:07,680 like a couple of exhibits were talking about like different cooling system, liquid cooling, 525 00:33:07,680 --> 00:33:11,360 high efficiency air cooling. There was MCD 526 00:33:11,520 --> 00:33:15,280 and Schneider Electric, a couple of electric companies were there. 527 00:33:16,270 --> 00:33:18,670 Not like electric company kids show when we were kids, but, 528 00:33:20,270 --> 00:33:23,950 but electrical engineering companies were there because it matters. Right? Like all of this 529 00:33:23,950 --> 00:33:27,630 stuff has to happen somewhere in the physical world. And 530 00:33:27,630 --> 00:33:31,350 you know, very often that's in Loudoun County, Virginia. But you know, that's, that's, 531 00:33:31,350 --> 00:33:35,070 that's, that's a topic for another show. But yeah, 532 00:33:35,070 --> 00:33:38,510 so this is some of the swag. So in the keynote room they had T 533 00:33:38,510 --> 00:33:41,880 shirts, so 534 00:33:45,720 --> 00:33:49,000 which was pretty cool. And then we have this bag which 535 00:33:49,240 --> 00:33:51,800 I'm gonna see if I can get my kids to nerd out and trick or 536 00:33:51,800 --> 00:33:52,440 treat with this. 537 00:33:55,400 --> 00:33:58,280 But some of the swag in here was really good. Like, my favorite bit of 538 00:33:58,280 --> 00:34:01,320 swag was this thing. 539 00:34:04,120 --> 00:34:07,400 See if I can see that. It's basically like a. An adapter. 540 00:34:08,800 --> 00:34:11,200 So it also has this. So this is the probably the most useful bit of 541 00:34:11,200 --> 00:34:15,000 swag. There's other cool stuff in here, too. There's what I think 542 00:34:15,000 --> 00:34:18,240 is a luggage tag for F5 Networks. 543 00:34:19,120 --> 00:34:21,760 And this is just the other stuff I collected. 544 00:34:23,040 --> 00:34:26,520 There's. Whose socks are these? AWS 545 00:34:26,520 --> 00:34:29,920 socks. Okay. With the DC 546 00:34:30,320 --> 00:34:31,920 Skyline. That's kind of cool. 547 00:34:35,400 --> 00:34:39,080 Guardians of the AI keychain, or is that a pin 548 00:34:39,080 --> 00:34:42,080 keychain? Hand 549 00:34:42,080 --> 00:34:45,680 sanitizer, but like in a business card type 550 00:34:45,680 --> 00:34:49,000 thing. Okay. But that was pretty cool. And then 551 00:34:49,240 --> 00:34:52,680 I did get quantum machine socks. They're upstairs. 552 00:34:54,200 --> 00:34:57,160 You know, pens, the usual kind of swaggy type stuff. 553 00:34:58,680 --> 00:35:02,370 Google Cloud pen. And so, 554 00:35:02,370 --> 00:35:05,930 yeah, it was. It was definitely a very productive, 555 00:35:06,010 --> 00:35:09,730 you know, couple days. I definitely am 556 00:35:09,730 --> 00:35:13,370 gonna kind of binge watch all the sessions because as far as I know, everything 557 00:35:13,370 --> 00:35:16,410 was recorded. So that'll be kind of nice. 558 00:35:18,730 --> 00:35:22,450 And yeah, it was awesome. And I thought it would be cool 559 00:35:22,450 --> 00:35:25,690 to kind of share this across both shows, right, because these are two very related 560 00:35:25,770 --> 00:35:29,030 fields, right? AI and quantum computing. 561 00:35:30,230 --> 00:35:34,030 Because, you know, whether you're using actual quantum 562 00:35:34,030 --> 00:35:37,790 computers or simulated ones, it's 563 00:35:37,790 --> 00:35:41,590 all going to be some form of linear algebra, which happens to be what 564 00:35:42,950 --> 00:35:46,790 these GPUs are really good at. And the keynote really 565 00:35:46,790 --> 00:35:50,550 did a good job of putting it all into perspective in terms 566 00:35:50,550 --> 00:35:53,760 of, you know, 567 00:35:54,720 --> 00:35:58,160 oh, we, you know, it was a little. Little braggadocious, but, you know, I guess 568 00:35:58,160 --> 00:36:01,880 when you're worth $5 trillion, you know, you can. Yeah, I guess 569 00:36:01,880 --> 00:36:05,120 so. Right? You know, I would. Dear Lord, please give me that problem. 570 00:36:06,400 --> 00:36:09,920 Oh, my God. Honestly, making trouble today. Okay, 571 00:36:10,000 --> 00:36:12,960 now it's Murphy's Law, man. As soon as I crack open a book or start 572 00:36:12,960 --> 00:36:16,240 a call, guaranteed somebody exactly 573 00:36:17,520 --> 00:36:21,120 like. So the. 574 00:36:23,920 --> 00:36:26,080 See, folks, we really do record these live 575 00:36:27,600 --> 00:36:31,440 today, folks. We really do. But these are. These are. 576 00:36:32,320 --> 00:36:35,040 These are interesting times in terms of. 577 00:36:39,840 --> 00:36:43,200 There we go. Cool. Sorry about that, folks. 578 00:36:44,360 --> 00:36:47,960 It really is live. So also, you know, we're streaming this on multiple YouTube channels, 579 00:36:47,960 --> 00:36:51,320 so if you. If you. If you're a lot of channel growth on both channels, 580 00:36:51,480 --> 00:36:55,200 both Frank's World and the Impact Quantum Channel. So wherever platform 581 00:36:55,200 --> 00:36:58,080 you're liking, if you can, like, share and subscribe, that'd be great. Leave a comment 582 00:36:58,080 --> 00:37:01,840 if you have any questions, but there's definitely a lot to digest from 583 00:37:01,840 --> 00:37:05,400 this show in terms of, you know, from robots to 584 00:37:06,120 --> 00:37:09,400 quantum computers. The big thing that they released was The 585 00:37:09,400 --> 00:37:12,950 NVQ link, which is an interesting, 586 00:37:14,150 --> 00:37:16,310 I would say little project, but it's not little. 587 00:37:18,550 --> 00:37:22,070 It is basically like a network bandwidth. I totally want to geek out on this 588 00:37:22,070 --> 00:37:25,150 and I would be lying if I said I knew that much about it, but 589 00:37:25,150 --> 00:37:28,070 everybody was just going crazy over it, 590 00:37:28,710 --> 00:37:32,470 right? Yeah, there's a lot of potential there, 591 00:37:32,470 --> 00:37:35,510 right. I mean, a lot of potential to just kind of 592 00:37:36,890 --> 00:37:40,330 set the pace for quantum networking 100. 593 00:37:40,570 --> 00:37:43,930 Right. And just the high speed bandwidth because hang on a second, 594 00:37:47,690 --> 00:37:51,330 my wireless headset batteries were low when it was beeping at me, so I had 595 00:37:51,330 --> 00:37:54,970 to take those off for a second. But no, like, I mean 596 00:37:54,970 --> 00:37:58,730 just kind of, even if you don't use it, it's basically a 597 00:37:58,730 --> 00:38:01,290 high speed, low latency interconnect 598 00:38:03,060 --> 00:38:06,740 between both quantum processors as well as 599 00:38:06,740 --> 00:38:10,420 GPU based ones. Right. So this is, 600 00:38:10,500 --> 00:38:14,300 I mean the stat was just unbelievable. Like it 601 00:38:14,300 --> 00:38:17,780 could, you know, this thing could house, I mean, terabits of information 602 00:38:17,940 --> 00:38:21,660 could be shared across this. Right. So the whole notion of what it takes to 603 00:38:21,660 --> 00:38:25,500 build a computer bus speeds can 604 00:38:25,500 --> 00:38:29,340 be completely reimagined now because of this. Right? And the idea is that, you 605 00:38:29,340 --> 00:38:32,440 know, when you do have a, you know, you'll see in the picture, right, there's 606 00:38:32,440 --> 00:38:33,240 the chandelier. 607 00:38:36,440 --> 00:38:39,560 Those are going to need some kind of controller system. So you have these hybrid 608 00:38:39,560 --> 00:38:43,040 systems that are both GPU super clusters and an actual quantum 609 00:38:43,040 --> 00:38:46,199 computer. So I think that the. And, and you'll notice that they did a really 610 00:38:46,199 --> 00:38:49,960 good job here of showing now at least three different types. Right? There's this 611 00:38:49,960 --> 00:38:53,720 one, I think that's the Rigetti. 612 00:38:54,120 --> 00:38:56,600 This one, I forget the name of it, but they had these all out on 613 00:38:56,600 --> 00:39:00,170 the floor. Okay. And you'll have to go to watch the 614 00:39:00,170 --> 00:39:03,890 YouTube shorts to kind of see me walk around them and stuff like that. But 615 00:39:03,890 --> 00:39:07,130 I mean it was just, it, you know, and this is just, just so much 616 00:39:07,130 --> 00:39:10,810 going on in so many different directions. One of the 617 00:39:10,810 --> 00:39:13,970 companies there was a robotics company and 618 00:39:14,210 --> 00:39:16,050 they're. I overheard the pitch. 619 00:39:18,450 --> 00:39:22,050 Basically the too long didn't read of the pitch was 620 00:39:22,050 --> 00:39:25,860 you don't buy the robots from them, you pay them $20 an 621 00:39:25,860 --> 00:39:29,700 hour basically per robot. That was basically the 622 00:39:29,700 --> 00:39:33,540 idea. So don't quote me on 623 00:39:33,540 --> 00:39:37,180 that over that. That makes it much more competitive, right? 624 00:39:37,180 --> 00:39:40,700 Yeah. Because I gotta spend how much money to get one 625 00:39:40,700 --> 00:39:43,820 robot. Right. And whatever the, the 626 00:39:43,900 --> 00:39:47,740 accounting magic you need to make that make sense. Right, Right. 627 00:39:47,740 --> 00:39:50,540 You don't. That, that doesn't really apply anymore. Right. It's completely. 628 00:39:52,620 --> 00:39:56,260 Right. I don't even know if that's and. Minimum wage in some 629 00:39:56,260 --> 00:39:59,340 places is 15. Right. So, like, it's not, 630 00:40:00,060 --> 00:40:03,860 you know, and these workers could work 24, 7. They don't get sick. 631 00:40:03,860 --> 00:40:07,700 I mean, they'll break down, but yeah, I mean, the labor market is about to 632 00:40:07,700 --> 00:40:10,940 get seriously disrupted. 633 00:40:11,100 --> 00:40:12,780 Yeah. And, you know, 634 00:40:15,420 --> 00:40:19,080 speak. You know, I think everybody over the 635 00:40:19,080 --> 00:40:22,360 next five, 10 years is going to have to experience some kind of career disruption 636 00:40:22,360 --> 00:40:26,080 and retraining. Right. So if 637 00:40:26,080 --> 00:40:27,120 you don't like learning, 638 00:40:30,000 --> 00:40:33,240 get used to it. You know, Eat your 639 00:40:33,240 --> 00:40:36,600 vegetables. Right? Is kind of like the thing. Learn to like the vegetables. That makes 640 00:40:36,600 --> 00:40:39,600 it a lot easier when you eat them. But it's fun, Right. And I think 641 00:40:40,320 --> 00:40:44,040 I enjoy some of. The stuff that I've learned, like AI tools. I mean, 642 00:40:44,040 --> 00:40:47,040 I. I have. I'm having the best time. I mean, I'm like, is this even. 643 00:40:47,040 --> 00:40:50,070 Am I working right now? I don't even feel like. I feel like I'm enjoying 644 00:40:50,070 --> 00:40:53,510 what I'm creating. I'm enjoying what I'm sharing, 645 00:40:54,070 --> 00:40:57,870 and I'm doing it in a way that's incredibly digestible to 646 00:40:57,870 --> 00:41:01,710 all kinds of folks, and that's what I'm looking to do. And people 647 00:41:01,710 --> 00:41:05,270 need translators, Right. People that can understand 648 00:41:05,430 --> 00:41:08,470 the deep technical side of it and explain it in more human terms. 649 00:41:09,350 --> 00:41:12,870 Right. And, you know, I gave my stump 650 00:41:12,870 --> 00:41:16,420 speech yesterday. Somebody was like, you know, how do I get one of the. There 651 00:41:16,420 --> 00:41:20,140 was a recent graduate. Was there. A lot of university students were there, 652 00:41:20,140 --> 00:41:23,940 too, which I think Nvidia gave them like a sweetheart 653 00:41:23,940 --> 00:41:27,500 deal to attend. Oh, I think it's so important, though. I mean, 654 00:41:27,660 --> 00:41:31,220 it really is. Right. Well, it's smart, too, right? Because one, it's, you know, you 655 00:41:31,220 --> 00:41:34,540 know, eth. You know, it's the right thing to do. Right. But it's also going 656 00:41:34,540 --> 00:41:37,740 to build out their talent pipeline. Right. It's the next generation of talent. 657 00:41:38,460 --> 00:41:41,020 Get them out there, get them all. They're. They're excited. 658 00:41:43,090 --> 00:41:46,770 I met students from Morgan State dmu, 659 00:41:46,930 --> 00:41:50,730 University of Maryland, University of Kentucky. They actually 660 00:41:50,730 --> 00:41:53,890 drove from Cincinnati area to here. 661 00:41:55,250 --> 00:41:58,690 And though, I mean, it was just 662 00:41:58,850 --> 00:42:00,290 a bunch of universities 663 00:42:02,370 --> 00:42:05,850 and Virginia Tech was actually a sponsor of the conference, which I thought was 664 00:42:05,850 --> 00:42:09,690 interesting. Oh, that is interesting. Their logo is up there. And I was 665 00:42:09,690 --> 00:42:13,410 like, oh, that is interesting. And probably a bunch of other universities just didn't notice 666 00:42:13,410 --> 00:42:16,410 it. Their logo is very stands out. Okay, 667 00:42:17,370 --> 00:42:20,730 well, then they did the right way. They did it the right way. Yeah, exactly. 668 00:42:20,730 --> 00:42:24,570 Right. So it was. It 669 00:42:24,570 --> 00:42:28,330 was a very. It was one of the more unique conferences 670 00:42:28,330 --> 00:42:32,130 I've ever been to. Right. Because 671 00:42:32,130 --> 00:42:35,770 it really was at the confluence of national security Fed type 672 00:42:35,770 --> 00:42:39,300 stuff, cutting edge robotics, cutting edge 673 00:42:39,300 --> 00:42:43,100 AI, quantum computers. You had students, you had federal 674 00:42:43,100 --> 00:42:46,620 employees, you had uniform service manager, you had congressional policy 675 00:42:46,620 --> 00:42:50,340 makers pipeline showing up. It was a, it was a unique mix 676 00:42:50,740 --> 00:42:54,260 that you don't see a lot of places. Right, right. 677 00:42:54,580 --> 00:42:58,420 So it was really cool. I'm hoping to go to the one, 678 00:42:58,420 --> 00:43:01,940 the big one in California which is going to be. Suppose somebody told me that 679 00:43:01,940 --> 00:43:05,700 it's wall to wall people and increasingly over the last few years world 680 00:43:05,700 --> 00:43:09,390 of war robots too. So. Right, right. More of that in California. I mean 681 00:43:09,390 --> 00:43:12,990 that's the thing. You wanna this kind of set the stage for you. Yeah, 682 00:43:12,990 --> 00:43:16,710 yeah, expect for the next one. Right? Yeah, exactly. I mean 683 00:43:17,590 --> 00:43:21,230 and, and Nvidia's really got a lot of things figured 684 00:43:21,230 --> 00:43:24,710 out. Right. Like it's not just the hardware, they have the software layer with 685 00:43:24,710 --> 00:43:28,350 Cuda. Jensen does a far better job of explaining it in the first 10 686 00:43:28,350 --> 00:43:31,110 minutes of the keynote. But 687 00:43:31,910 --> 00:43:35,590 I mean no wonder why they're worth 5 trillion. Like it's no 688 00:43:35,590 --> 00:43:36,150 surprise. 689 00:43:40,470 --> 00:43:42,630 It'S always live, it's always. Things are always going on. 690 00:43:45,110 --> 00:43:48,870 Someone came into her, her home office while we were. So 691 00:43:49,030 --> 00:43:50,710 if you're listening, you didn't see it, but. 692 00:43:52,710 --> 00:43:56,550 I found the pod. But so thanks for joining us live. 693 00:43:56,550 --> 00:43:59,920 I don't see any active question questions in the queue but 694 00:44:00,400 --> 00:44:04,000 if I met you at the conference. Very nice to meet you. Definitely 695 00:44:04,800 --> 00:44:08,000 looking forward to getting hands on with the spark 696 00:44:09,600 --> 00:44:12,640 that was also cool. Everybody's like do you have a spark? Do you have a 697 00:44:12,640 --> 00:44:16,480 spark? Well that kind of puts you on different echelon. I know I was like 698 00:44:16,480 --> 00:44:19,720 one of the cool kids. I got a spark that was like. Rolling up the 699 00:44:19,720 --> 00:44:23,160 high school and like you know, a Beamer or my neighborhood is really an 700 00:44:23,160 --> 00:44:24,970 Irocol. But 701 00:44:27,530 --> 00:44:31,330 that date, that, that puts me in a very interesting time and place in 702 00:44:31,330 --> 00:44:35,130 history I suppose. But, but yeah, no it was 703 00:44:35,130 --> 00:44:38,970 really, it was really cool. I think the future looks 704 00:44:38,970 --> 00:44:42,330 amazing and I think there's just so much 705 00:44:42,330 --> 00:44:46,010 opportunity in this space. Oh the one last thing was like there was this. 706 00:44:47,130 --> 00:44:50,810 Nvidia had like a whole startup area. So apparently Nvidia has like a startup program 707 00:44:50,810 --> 00:44:54,090 and stuff like that out. Really cool stuff, a lot of innovative stuff there. 708 00:44:55,130 --> 00:44:58,650 One of the best signs I saw, which was behind the red hat booth, it 709 00:44:58,650 --> 00:45:01,890 was kind of like the next aisle over was they had this huge sign that 710 00:45:01,890 --> 00:45:05,610 said AI took my job right in big text 711 00:45:05,610 --> 00:45:08,810 and the little text to another level. Oh 712 00:45:09,530 --> 00:45:13,090 like that's clever. Right? You know, I mean that's 713 00:45:13,090 --> 00:45:16,650 It's. What did someone say? It's not that AI is going 714 00:45:16,650 --> 00:45:20,160 to take away your job, it's that the person 715 00:45:20,480 --> 00:45:23,840 who knows how to use AI. Is going to take over your job. Is going 716 00:45:23,840 --> 00:45:26,400 to take away. And I'm like, well, I was like, you know, 717 00:45:28,880 --> 00:45:32,600 look at the stuff we do. Right? We're not a big team here. Right? We're 718 00:45:32,600 --> 00:45:34,640 not, you know, 719 00:45:36,480 --> 00:45:40,320 look at what we're able to accomplish. Yeah, absolutely. You 720 00:45:40,320 --> 00:45:43,950 know, and that would not have been, it would have been 721 00:45:43,950 --> 00:45:46,950 doable, it wouldn't have been feasible without AI. Right, 722 00:45:47,510 --> 00:45:49,830 right. Because sadly I do have to sleep sometimes 723 00:45:51,430 --> 00:45:54,950 and. You got three. You got three kids. I got three kids. Yeah. There you 724 00:45:54,950 --> 00:45:58,590 go. Well, I'm really happy that we talked about this because 725 00:45:58,590 --> 00:46:02,270 honestly, the conference looked really exciting. It was awesome. Always nice to 726 00:46:02,270 --> 00:46:05,910 hear from somebody who's there, get them to download, you know, some of that information. 727 00:46:06,470 --> 00:46:10,230 Absolutely, absolutely. Fun fact. We actually re recorded this. 728 00:46:10,230 --> 00:46:13,220 We were, we pre recorded something a day before, before I went and I was 729 00:46:13,220 --> 00:46:16,220 like, no, so much was there that we have to redo it. 730 00:46:16,940 --> 00:46:19,140 So let us know in the comments if you want to hear. Kind of like 731 00:46:19,140 --> 00:46:22,980 the original, It'll be like the original cut of Star wars and kind of 732 00:46:22,980 --> 00:46:24,140 like the remix, you know. 733 00:46:27,020 --> 00:46:30,540 But yeah, I mean I'm, I'm super 734 00:46:30,540 --> 00:46:34,140 excited. It was cool to connect with former people 735 00:46:34,460 --> 00:46:38,260 I work with at Microsoft and these are people that go way back. 736 00:46:38,260 --> 00:46:42,110 Like back to when it was called dpe Developer Platform Evangelism. Like it was 737 00:46:42,110 --> 00:46:45,910 like, you know, he was talking about like, you know, we had some interesting war 738 00:46:45,910 --> 00:46:49,750 stories we could share and stuff like that. Back in 1900 in Hootelie. Hoo. 739 00:46:49,750 --> 00:46:53,110 No, it was 2000 something. But yeah, yeah, I'm right there with you. This was 740 00:46:53,590 --> 00:46:57,230 this, this was when Windows Phone still was a 741 00:46:57,230 --> 00:47:00,710 thing. So way, way back. 742 00:47:01,990 --> 00:47:05,830 But yeah, plus it was really cool to meet like 743 00:47:05,830 --> 00:47:09,520 Maria. Maria Shaw from Python. Simplistic. She's awesome. Shout out to you, Maria. 744 00:47:10,480 --> 00:47:14,040 You know, you know, not only have you also 745 00:47:14,040 --> 00:47:17,800 career transition, you've done it very well. And I think your, your videos are 746 00:47:17,800 --> 00:47:21,440 always positive and helpful to help other people follow that path too. Right. 747 00:47:22,160 --> 00:47:25,920 You know, and that's what we try. To do here, right. Being 748 00:47:25,920 --> 00:47:29,600 quantum curious, we're saying, you know, you don't have to have a PhD. No, 749 00:47:29,680 --> 00:47:32,400 but that doesn't mean that you can't be in the conversation. It doesn't mean you 750 00:47:32,400 --> 00:47:35,760 can't understand. I gave that some speech yesterday. I was like, you know, look, you 751 00:47:35,760 --> 00:47:38,440 don't have to be a PhD in this. So I, you know, they're going to 752 00:47:38,440 --> 00:47:42,200 need, they're going to need customer solution architects. They're going to need. Or Customer success, 753 00:47:42,200 --> 00:47:45,960 whatever they're called now, CSAs. You're going to need people to rack and 754 00:47:45,960 --> 00:47:49,760 stack this stuff. You're going to need people that you know can market 755 00:47:49,760 --> 00:47:53,360 it. You're going to need business development, you need sales leaders. You're going to need 756 00:47:53,360 --> 00:47:57,200 all of that stuff. You are going to need. Yeah. And not 757 00:47:57,200 --> 00:48:00,880 every one of them is going to need a PhD. In fact, 758 00:48:00,880 --> 00:48:04,690 one of the guests said there's already too many PhDs in 759 00:48:04,690 --> 00:48:08,450 this field, which is kind of funny, right? 760 00:48:09,570 --> 00:48:13,170 So actually, speaking of which, Candace, that is an excellent segue. No 761 00:48:13,170 --> 00:48:16,610 wonder why you're a master marketer. So this is our book here 762 00:48:17,650 --> 00:48:21,410 that we wrote and it is. Can I. I think it's up there. 763 00:48:21,570 --> 00:48:25,210 It says Quantum Sales Playbook. There we go. There you go. Quantum 764 00:48:25,210 --> 00:48:28,770 Sales Playbook. And it's basically a sales playbook 765 00:48:29,120 --> 00:48:32,880 that is for startups, for anyone in 766 00:48:32,880 --> 00:48:36,480 really emerging tech fields. Right. Like, you know, I wrote this 767 00:48:36,480 --> 00:48:40,320 around Quantum based on what I experienced with AI, because 768 00:48:40,320 --> 00:48:44,000 I've been doing AI now about 10 years, right. And majority of that 769 00:48:44,000 --> 00:48:47,200 has either been sales or delivering training 770 00:48:47,680 --> 00:48:51,400 about AI, right. So actually I think eight of those 10 771 00:48:51,400 --> 00:48:55,240 years have been selling AI. Two of those have 772 00:48:55,240 --> 00:48:59,060 been training shout out to Wintelect 773 00:48:59,700 --> 00:49:03,220 back in the day. But, but it's also 774 00:49:03,300 --> 00:49:07,020 part of it. Is from, you know, I don't know, maybe 775 00:49:07,020 --> 00:49:10,820 14 or 15 episodes of, of the first part of the season 776 00:49:12,019 --> 00:49:15,700 of us talking to experts and understanding, you know, 777 00:49:15,700 --> 00:49:19,500 right. All of their perspectives be, be them PhDs, be 778 00:49:19,500 --> 00:49:23,180 them industry, be them, you know, trying to go over the bridge from 779 00:49:23,180 --> 00:49:27,010 1 to 1 to the other, you know, hearing what they have to say and 780 00:49:27,010 --> 00:49:30,770 what's real, what's actually happening. One of the guests pointed out, he goes, he, he 781 00:49:30,770 --> 00:49:34,450 does happen to have a PhD, right? And, but he 782 00:49:34,450 --> 00:49:38,050 realized that he, you know, he sold the system to a company in Japan and 783 00:49:38,050 --> 00:49:41,690 like, they had to fly out a lot of 784 00:49:41,690 --> 00:49:45,210 people like customer success, right. To make sure it up and runs and things like 785 00:49:45,210 --> 00:49:48,450 that. And they didn't, you know, I think it was kind of a learning experience. 786 00:49:48,450 --> 00:49:50,850 That's why I'm not saying the name. If you want to listen to it, you 787 00:49:51,080 --> 00:49:53,880 figure out which. Who I'm talking about because that show has been released. 788 00:49:54,840 --> 00:49:58,280 And if you're really clever, you know, that we said the name of said company 789 00:49:58,440 --> 00:50:02,160 already in this episode. But, but, you know, he's like a learning 790 00:50:02,160 --> 00:50:05,400 experience. Like he Realized like, you know, you know, 791 00:50:06,759 --> 00:50:10,240 you're gonna need people to rack and stack him is basically kind of like the 792 00:50:10,240 --> 00:50:14,040 end result. Right. Like when somebody buys a solution and it's has to 793 00:50:14,040 --> 00:50:16,710 be on prem, you have to set it up, configure it. You have to teach 794 00:50:16,710 --> 00:50:19,390 people how to configure it. So you're going to need trainers, you're going to need 795 00:50:19,630 --> 00:50:23,150 marketers, you're going to need all of these roles. You're going to need 796 00:50:23,150 --> 00:50:26,910 them. Right. Do they have to have PhDs in quantum physics? No. 797 00:50:26,910 --> 00:50:30,310 In fact, it's probably a waste of their education and skills because the people with 798 00:50:30,310 --> 00:50:32,990 the PhDs need to be designing the next version of your product. 799 00:50:34,110 --> 00:50:37,710 Right. So you need people who are kind of not 800 00:50:37,710 --> 00:50:41,390 PhDs. You need people from other disciplines to go in and do this. 801 00:50:41,390 --> 00:50:45,040 Right. And that's really kind of the gist of art. This show. 802 00:50:45,040 --> 00:50:48,880 Right. This impact Quantum. And the book is really about, like, if you. This 803 00:50:48,880 --> 00:50:52,600 is really for business developers, startup founders. That's really who this is really meant for 804 00:50:52,600 --> 00:50:56,360 is like, even if you have a PhD, you can't assume 805 00:50:56,360 --> 00:51:00,120 everyone else will understand why qubits are important, why they're 806 00:51:00,120 --> 00:51:03,520 a big deal. Right. And that's the subtitle of the book is Selling Outcomes, not 807 00:51:03,520 --> 00:51:06,760 Qubits. Right. And it's not just, it's not just for 808 00:51:07,160 --> 00:51:10,890 Quantum. No. This could apply to any emerging tech. Exactly. 809 00:51:10,890 --> 00:51:14,410 That's the point. It's for any emerging tech getting kind of beyond what the technology 810 00:51:14,570 --> 00:51:17,130 is into, why the solution is going to work. 811 00:51:18,490 --> 00:51:22,050 That's exactly the more important, you know, aspect of it. So, yeah. 812 00:51:22,050 --> 00:51:25,530 Awesome. And if you run an incubator 813 00:51:25,610 --> 00:51:28,570 or like a research facility at a university, 814 00:51:29,530 --> 00:51:32,410 we'll give you a copy of it for free. Right. We're not doing this for 815 00:51:32,410 --> 00:51:35,870 the money. We're just doing this to, to help nudge along this. Right. Give my, 816 00:51:35,870 --> 00:51:39,710 give my experience in sales, Candace's experience in marketing. Kind of like 817 00:51:39,710 --> 00:51:43,470 translate that into quantum. Right. It's our contribution to this 818 00:51:43,470 --> 00:51:46,830 emerging ecosystem. Exactly, Exactly. 819 00:51:46,830 --> 00:51:50,430 Awesome. And that's all I got. 820 00:51:50,430 --> 00:51:53,590 Anything else pertinent North? 821 00:51:54,150 --> 00:51:57,910 The Great White North? No, honestly, it's raining. It's 822 00:51:57,910 --> 00:52:01,600 raining here today. And that's. So it's not, it's not white yet. 823 00:52:01,600 --> 00:52:05,080 We're gonna need. I mean, and it's. It's been known to snow by 824 00:52:05,080 --> 00:52:08,920 Halloween, but. Yeah, yeah, yeah, I don't think we're. Gonna have that this 825 00:52:08,920 --> 00:52:12,440 year. I think it's. My grandfather grew up in Montreal, so whenever as a kid, 826 00:52:12,440 --> 00:52:16,160 I would complain about being Colder. Like the snow. He would tell 827 00:52:16,160 --> 00:52:19,840 me it was the ultimate uphill, both ways in the 828 00:52:19,840 --> 00:52:23,360 snow, being chased by polar bears. Like, that was the exact 829 00:52:23,600 --> 00:52:27,430 kind of stuff I do to my kids now. Because 830 00:52:27,430 --> 00:52:30,830 it's time. We should be doing it. Time. Yeah, yeah, yeah, yeah. Up a little 831 00:52:30,830 --> 00:52:34,270 bit. There you go. Although one of my Weisenheimer kids is like, you know, growing 832 00:52:34,270 --> 00:52:37,590 up in New York City, he's like, yeah, uphill. Both AOAs in the snow while 833 00:52:37,590 --> 00:52:41,429 getting shot at. Like, oh, okay. Now he's just taking it 834 00:52:41,429 --> 00:52:45,030 to the next level. For his credit was it was 835 00:52:45,190 --> 00:52:48,950 the kids taking it to the next level. So I've 836 00:52:48,950 --> 00:52:52,550 raised snarky kids, which is karma, I suppose, coming back to bite me. 837 00:52:53,270 --> 00:52:56,790 Oh, oh, please. I'm from New York, so my kids have a level of sarcasm. 838 00:52:56,870 --> 00:53:00,190 Oh, yeah. That's unnatural that even though they spent. More years in 839 00:53:00,190 --> 00:53:03,830 Montreal, people are like, you're so New York. And, 840 00:53:03,910 --> 00:53:07,550 like, where are you from? Kind of sticks with 841 00:53:07,550 --> 00:53:10,990 you. Yeah. I mean, I understand why it sticks with me, but it's from them, 842 00:53:10,990 --> 00:53:14,710 and. And they. They left there two and four years old, you know, and 843 00:53:14,710 --> 00:53:18,530 now they're 20 and 18. But it's. It's. It's. It's 844 00:53:18,530 --> 00:53:22,210 in the home, too. Right. It's in the heart. Right. Thankfully for me, like, I'm 845 00:53:22,210 --> 00:53:25,330 still in, like, the east coast corridor. Right. So Baltimore is kind of like, 846 00:53:25,810 --> 00:53:28,730 you know, like a Diet Coke for. I'm gonna get so much hate mail for 847 00:53:28,730 --> 00:53:31,650 that. But it's not. It's culturally similar enough, 848 00:53:32,690 --> 00:53:36,530 you know, Kind of got that east coast vibe. Right. Right. So. 849 00:53:37,330 --> 00:53:40,890 All right. So with that, we'll let our AI who is a British 850 00:53:40,890 --> 00:53:44,730 AI from the other side of the pond, finish the show. And if you're 851 00:53:44,730 --> 00:53:48,370 watching this live on the live stream, you get treated to some 852 00:53:48,370 --> 00:53:52,010 extra fancy graphics. So I have my outro 853 00:53:52,010 --> 00:53:54,490 graphics that I will play now, 854 00:53:55,530 --> 00:53:57,930 assuming I can find it. There it is.