1 00:00:00,080 --> 00:00:05,357 the very very best in the world are the brain structure is different and one of 2 00:00:05,440 --> 00:00:08,557 the things that our institutions underestimate 3 00:00:08,640 --> 00:00:11,197 but we're we have an advantage in America because we have this tech scene 4 00:00:11,280 --> 00:00:16,077 is the people think that there's like you know they're with a standard 5 00:00:16,160 --> 00:00:19,997 deviation of the best if you're the second best but it's not it's just a 6 00:00:20,080 --> 00:00:23,357 different universe it's not true and you see this in software and building 7 00:00:23,440 --> 00:00:29,760 software products the very best in the world the people who built PG 8 00:00:29,920 --> 00:00:32,477 uh the the brain structure the way of 9 00:00:32,560 --> 00:00:34,957 solving problems it is not at all 10 00:00:35,040 --> 00:00:39,277 similar to how 11 00:00:39,360 --> 00:00:43,037 uh you know um if you I don't want to 12 00:00:43,120 --> 00:00:48,397 mention their last names because I think one of them is pro happily not famous 13 00:00:48,480 --> 00:00:50,717 but uh >> I think my picture comes out for him 14 00:00:50,800 --> 00:00:52,317 when he search online 15 00:00:52,400 --> 00:00:57,037 >> uh on PG with Bob 16 00:00:57,120 --> 00:01:00,957 they're very few people who could could have pulled that off and I don't and I 17 00:01:01,040 --> 00:01:04,957 think convers and and I would say if you took Ryan and Bob and put them in 18 00:01:05,040 --> 00:01:08,877 academic context I don't think Bob Mcgru minds I'll leave Ryan's last name out 19 00:01:08,960 --> 00:01:11,037 but they would have they would do very very well. 20 00:01:11,120 --> 00:01:12,477 >> Yeah. Well Bob obviously went on to open 21 00:01:12,560 --> 00:01:15,597 AI to do very important work there. It's an interesting point about about talent 22 00:01:15,680 --> 00:01:19,597 that I think you you you you framed in a way was very helpful to think about that 23 00:01:19,680 --> 00:01:22,157 you actually have to be within a couple standard deviations to even appreciate 24 00:01:22,240 --> 00:01:25,277 this. And so I think a big problem with a lot of our institutions for example 25 00:01:25,360 --> 00:01:28,237 around the Pentagon is if you have people who are only you know one 26 00:01:28,320 --> 00:01:31,037 standard deviation above they can't even tell a difference between four and five 27 00:01:31,120 --> 00:01:33,517 they have no idea what's even going on at those levels. So you need people who 28 00:01:33,600 --> 00:01:36,477 are good enough to even appreciate that >> we have a huge advantage and let's just 29 00:01:36,560 --> 00:01:39,117 take US commercial. This is a really 30 00:01:39,200 --> 00:01:42,237 true thing and really not understood. Um 31 00:01:42,320 --> 00:01:46,477 that to appreciate talent you need to be within 32 00:01:46,560 --> 00:01:48,157 standard deviation of that talent. 33 00:01:48,240 --> 00:01:51,517 Unless you have some specialized 34 00:01:51,600 --> 00:01:55,517 weird this is where for whatever reason I think I have some kind of weird 35 00:01:55,600 --> 00:01:59,197 ability where you know I have picked some of the best and managed some of the 36 00:01:59,280 --> 00:02:02,237 best engineers in the world consistently. 37 00:02:02,320 --> 00:02:05,037 larger institutions struggle in some 38 00:02:05,120 --> 00:02:10,397 cases because they think they can't they can't tell the difference between 39 00:02:10,480 --> 00:02:13,517 >> well I I think it's almost like those cultures reject these people who are 40 00:02:13,600 --> 00:02:16,797 extremely good right >> but that's and that's but but but but 41 00:02:16,880 --> 00:02:18,957 again to your American optimism thing 42 00:02:19,040 --> 00:02:21,677 which I share and we have a culture that 43 00:02:21,760 --> 00:02:24,877 nurtures them allows them to be managed 44 00:02:24,960 --> 00:02:28,077 provides capital teaches them like you 45 00:02:28,160 --> 00:02:32,637 know one of the things I think people get wrong is you don't learn to win by 46 00:02:32,720 --> 00:02:36,157 failing. You learn to win by working with people who have ups and downs and 47 00:02:36,240 --> 00:02:37,997 then win. So there's like a deep 48 00:02:38,080 --> 00:02:40,877 understanding whether they work with you 49 00:02:40,960 --> 00:02:44,237 at HVC or they work with others, some of 50 00:02:44,320 --> 00:02:49,117 whom I like and some of whom I don't, but they're they you you do learn what 51 00:02:49,200 --> 00:02:53,197 it means to build business. And in the American commercial context, uh 52 00:02:53,280 --> 00:02:55,357 especially, you have this high turnover. 53 00:02:55,440 --> 00:02:58,317 though it's it's like people really do 54 00:02:58,400 --> 00:02:59,997 the people running these institutions on 55 00:03:00,080 --> 00:03:05,517 the tech side like it 5 years ago CIOS didn't buy our product now they do 56 00:03:05,600 --> 00:03:09,437 because it's like there's this like plasticity of of learning in the US 57 00:03:09,520 --> 00:03:13,757 which is something that I think other countries struggle with that it is true 58 00:03:13,840 --> 00:03:15,677 that 59 00:03:15,760 --> 00:03:18,717 identifying the difference between um 60 00:03:18,800 --> 00:03:23,757 you know Bob and Ryan and any very strong normal engineer is something that 61 00:03:23,840 --> 00:03:27,437 takes specialized quite Frankly, I think it's very similar to music. Very few 62 00:03:27,520 --> 00:03:29,997 people can hear the blue note. Almost no 63 00:03:30,080 --> 00:03:35,037 one can play it. To be what we do in tech is we hear the blue blue note on 64 00:03:35,120 --> 00:03:39,037 the tech talent side >> which very few people it's like you roll 65 00:03:39,120 --> 00:03:43,997 three crazy people into a room >> and a very talented normal person will 66 00:03:44,080 --> 00:03:47,997 pick the one person who's moderately talented. Whereas if you roll those 67 00:03:48,080 --> 00:03:50,637 three people into Palier or to your VC 68 00:03:50,720 --> 00:03:53,757 will be like no we want that one. And 69 00:03:53,840 --> 00:03:57,757 that's crazy. Then you have to be able to manage that person. 70 00:03:57,840 --> 00:04:00,957 >> That's also >> basically that's like my my karma to 71 00:04:01,040 --> 00:04:03,357 have to manage these people now after you had to deal with with us when we 72 00:04:03,440 --> 00:04:06,077 were kids. So [laughter] that's how we're doing it. 73 00:04:06,160 --> 00:04:07,597 >> I have a lot of stories about our times 74 00:04:07,680 --> 00:04:14,120 together, but those our times together are some of the best of my life.