1 00:00:02,320 --> 00:00:06,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio. 2 00:00:06,320 --> 00:00:09,399 Speaker 2: News, which is why I'm delighted to speak to Read Hoffman, 3 00:00:09,520 --> 00:00:12,600 Speaker 2: not just LinkedIn co founder and Graylock partner, but a 4 00:00:12,720 --> 00:00:16,560 Speaker 2: serial entrepreneur and somebody who has founded several AI companies 5 00:00:16,560 --> 00:00:19,200 Speaker 2: and will continue to do so. And what I've learned 6 00:00:19,320 --> 00:00:22,280 Speaker 2: is that one hundred million US dollars is the clearing 7 00:00:22,360 --> 00:00:25,800 Speaker 2: price in the market for frontier model AI talent. But 8 00:00:26,520 --> 00:00:29,880 Speaker 2: we're laughing, but actually that's the debate here. Why is 9 00:00:29,880 --> 00:00:32,800 Speaker 2: one hundred million dollars reasonable or unreasonable? 10 00:00:33,320 --> 00:00:36,360 Speaker 1: Well, so, essentially, one of the things that's good about 11 00:00:36,400 --> 00:00:39,159 Speaker 1: having an open marketplace of anything, including labor, is that 12 00:00:39,200 --> 00:00:42,120 Speaker 1: you essentially get multiple bidders. And that's what's that a price. 13 00:00:42,520 --> 00:00:44,479 Speaker 1: And so the fact that someone goes, I'm willing to 14 00:00:44,479 --> 00:00:47,120 Speaker 1: spend one hundred million dollars in order to get this talent, 15 00:00:47,400 --> 00:00:51,239 Speaker 1: you think that's crazy. Why would it possibly higher than 16 00:00:51,479 --> 00:00:54,880 Speaker 1: the vast majority of CEOs of contruc Well, if that one, 17 00:00:55,320 --> 00:00:59,640 Speaker 1: what you're judging is that one talent will potentially create 18 00:01:00,000 --> 00:01:02,520 Speaker 1: millions of dollars of value for you, whether it's in 19 00:01:02,680 --> 00:01:06,000 Speaker 1: a social network, whether it's in you know kind of uh, 20 00:01:06,200 --> 00:01:08,200 Speaker 1: you know, our search engine anything else as a way 21 00:01:08,200 --> 00:01:11,320 Speaker 1: of doing it. And so if you think that, then 22 00:01:11,360 --> 00:01:12,720 Speaker 1: that's just a bold bet. 23 00:01:13,040 --> 00:01:15,480 Speaker 2: What Sam Altman, the CEO of open ai, said was 24 00:01:15,480 --> 00:01:19,000 Speaker 2: that that particular figure which he had accused Meta of 25 00:01:19,000 --> 00:01:21,920 Speaker 2: offering to some open ai staff, what he claimed was 26 00:01:21,959 --> 00:01:24,800 Speaker 2: it was crazy that he sounds like, it's not crazy. 27 00:01:24,840 --> 00:01:27,560 Speaker 1: Really, well, I don't think it's crazy when we know 28 00:01:27,640 --> 00:01:30,679 Speaker 1: that AI is going to transform all businesses in all industry, 29 00:01:30,720 --> 00:01:33,839 Speaker 1: in the entire tech industry. And these are trillion dollar 30 00:01:33,959 --> 00:01:36,400 Speaker 1: companies et cetera at the high end and the whole 31 00:01:36,440 --> 00:01:39,360 Speaker 1: stack all the way through undown in a billion today. 32 00:01:39,400 --> 00:01:40,840 Speaker 2: For a brief moment, one of them was a four 33 00:01:40,880 --> 00:01:43,240 Speaker 2: trillion dollar company exactly please continue. 34 00:01:42,959 --> 00:01:47,080 Speaker 1: Yes in video. And so the uh you know, so 35 00:01:47,720 --> 00:01:51,400 Speaker 1: saying hey, this piece of talent is a risk adjusted 36 00:01:51,440 --> 00:01:55,000 Speaker 1: bet that that makes a difference in that that's just 37 00:01:55,520 --> 00:01:58,600 Speaker 1: a risk bet. You might say it's a dumb risk bet, 38 00:01:59,040 --> 00:02:02,040 Speaker 1: but it's not done to do if those are the 39 00:02:02,040 --> 00:02:02,840 Speaker 1: stakes you're playing for. 40 00:02:03,760 --> 00:02:07,000 Speaker 2: I'm a student of Silicon Valley history. You were there 41 00:02:07,240 --> 00:02:10,200 Speaker 2: with respect, and there was a time where CEOs would 42 00:02:10,200 --> 00:02:13,080 Speaker 2: email each other, you know, and say, don't take my people, Okay, 43 00:02:13,120 --> 00:02:15,200 Speaker 2: I won't if you don't take my people. We had 44 00:02:15,240 --> 00:02:18,239 Speaker 2: this sort of poaching agreements saga in the mid to 45 00:02:18,440 --> 00:02:21,840 Speaker 2: early two thousands. Is this different in this? Is it 46 00:02:21,919 --> 00:02:23,839 Speaker 2: just the reality of a marketplace? 47 00:02:25,320 --> 00:02:27,800 Speaker 1: Well, I think it's much. Look. I think when you 48 00:02:27,880 --> 00:02:30,440 Speaker 1: email and say don't take each other people, that's bad 49 00:02:30,560 --> 00:02:33,839 Speaker 1: for anti trust, that's bad for labor laws, that's bad 50 00:02:33,919 --> 00:02:36,560 Speaker 1: for the right thing to do relative to talented people. 51 00:02:36,560 --> 00:02:40,160 Speaker 1: And obviously, as the founder of LinkedIn, I'm kind of 52 00:02:40,160 --> 00:02:43,480 Speaker 1: in the hey, we should match the talent towards best 53 00:02:43,520 --> 00:02:46,720 Speaker 1: possible outcome. Now, so that was a bad thing to 54 00:02:46,720 --> 00:02:49,000 Speaker 1: be doing. I'm glad we're not doing it now now. 55 00:02:49,160 --> 00:02:51,399 Speaker 1: What we do still, of course want, is we want 56 00:02:51,440 --> 00:02:54,480 Speaker 1: people to engage in serious work at serious companies, as 57 00:02:54,520 --> 00:02:57,120 Speaker 1: opposed to like, hey, I'm being paid this much here 58 00:02:57,200 --> 00:02:59,720 Speaker 1: this month and that much there this month. You've got 59 00:02:59,760 --> 00:03:02,040 Speaker 1: to be like, no, no, let's get the work done. Let's 60 00:03:02,040 --> 00:03:04,480 Speaker 1: build the new future. That's more of my worry on 61 00:03:04,520 --> 00:03:06,679 Speaker 1: the bidding, not whatever prices it gives to. 62 00:03:06,639 --> 00:03:10,440 Speaker 2: You are no longer a board participant of open Ai, 63 00:03:10,520 --> 00:03:12,800 Speaker 2: so I put that out there. But you understand the 64 00:03:12,840 --> 00:03:16,440 Speaker 2: company and you understand its structure. Why is this sort 65 00:03:16,480 --> 00:03:19,120 Speaker 2: of restructure held up, and is that having an impact 66 00:03:19,120 --> 00:03:21,280 Speaker 2: on their ability to hire or retain talent? 67 00:03:21,320 --> 00:03:23,760 Speaker 1: Do you think I haven't heard that it's had an 68 00:03:23,760 --> 00:03:26,160 Speaker 1: impact a negative impact on our ability had because everyone 69 00:03:26,160 --> 00:03:28,679 Speaker 1: knows that Open Air is one of the amazing new 70 00:03:28,760 --> 00:03:32,200 Speaker 1: tech companies of the current badge. I think that the 71 00:03:32,240 --> 00:03:35,440 Speaker 1: restructure is it's a very challenging thing to kind of 72 00:03:36,040 --> 00:03:38,320 Speaker 1: move from where a five oh one C three to 73 00:03:38,360 --> 00:03:42,440 Speaker 1: where a public benefit corp, especially when you have lawsuits 74 00:03:42,680 --> 00:03:46,000 Speaker 1: being filed and refiled and all of the sudden, you know, 75 00:03:46,280 --> 00:03:48,720 Speaker 1: academics saying it's a terrible thing to happen. And so 76 00:03:49,200 --> 00:03:52,200 Speaker 1: I don't know exactly what the impediments are, but it's 77 00:03:52,240 --> 00:03:53,920 Speaker 1: a challenging process. 78 00:03:53,560 --> 00:03:56,160 Speaker 2: If you were to guess. And again, I'm delighted to 79 00:03:56,200 --> 00:03:57,400 Speaker 2: be set with you on a day where there was 80 00:03:57,440 --> 00:04:02,000 Speaker 2: such newsflow Open AI and io Johnny I thing it closed. 81 00:04:02,360 --> 00:04:04,360 Speaker 2: What do you suspect it is that they're building? 82 00:04:04,840 --> 00:04:08,360 Speaker 1: Well, so I don't know, I'm told, but like if 83 00:04:08,360 --> 00:04:09,880 Speaker 1: it were me, I build a phone. 84 00:04:09,800 --> 00:04:12,320 Speaker 2: A phone because the reason I ask you the root 85 00:04:12,320 --> 00:04:14,520 Speaker 2: of it is, every day, how do I interact with 86 00:04:14,560 --> 00:04:16,640 Speaker 2: a generative AI tool, in particular through which is an 87 00:04:16,640 --> 00:04:18,040 Speaker 2: app through my smartphone. 88 00:04:18,279 --> 00:04:21,520 Speaker 1: Yeah, yes, well exactly, No, No, a smartphone. And look, 89 00:04:21,560 --> 00:04:24,480 Speaker 1: I'm you know, I'm a little older. I still use 90 00:04:24,520 --> 00:04:26,080 Speaker 1: a you know, laptop every swapen. 91 00:04:27,279 --> 00:04:29,919 Speaker 2: You have, as I said at the top, been a 92 00:04:29,960 --> 00:04:35,479 Speaker 2: serial entrepreneur. Recently, you've also backed brain implant space. Yes, 93 00:04:35,760 --> 00:04:39,160 Speaker 2: that is a somewhat crowded field. Why did you move 94 00:04:39,200 --> 00:04:39,960 Speaker 2: into that area? 95 00:04:40,040 --> 00:04:42,320 Speaker 1: Read Well, it's a little bit different than brain implant 96 00:04:42,360 --> 00:04:45,520 Speaker 1: It's it's called SAMAI and it's ultrasound. Okay. Now, by 97 00:04:45,520 --> 00:04:48,640 Speaker 1: the way, ultrasound might actually be one of the really 98 00:04:48,680 --> 00:04:50,640 Speaker 1: great things for both reading and writing from the brain, 99 00:04:50,680 --> 00:04:52,799 Speaker 1: because you can read but you don't have to stick 100 00:04:52,880 --> 00:04:55,800 Speaker 1: things in right. And part of the reason I backed 101 00:04:55,800 --> 00:04:57,839 Speaker 1: it is because they're using AI. I'm basically an AI 102 00:04:57,920 --> 00:05:01,960 Speaker 1: investor to get this ultra low frequency much less energy 103 00:05:02,000 --> 00:05:04,960 Speaker 1: than your phone in terms of focusing it on one 104 00:05:05,040 --> 00:05:08,880 Speaker 1: part of the brain. The tool set for creating brain 105 00:05:08,960 --> 00:05:12,040 Speaker 1: therapeutics on all kinds of things, anything from anxiety, this 106 00:05:12,200 --> 00:05:16,880 Speaker 1: serious dementia stuff is it's an amazing possible tool set, 107 00:05:16,920 --> 00:05:18,599 Speaker 1: and that possibility is the thing I invested. 108 00:05:18,720 --> 00:05:20,800 Speaker 2: I found that so interesting that you moved into that field. 109 00:05:20,800 --> 00:05:23,640 Speaker 2: I'm jumping around a bit that across all of this 110 00:05:23,720 --> 00:05:26,960 Speaker 2: is the anxiety of jobs. Many of your peers have 111 00:05:27,040 --> 00:05:30,120 Speaker 2: come out and made bold proclamations of how many jobs 112 00:05:30,160 --> 00:05:33,000 Speaker 2: would be eliminated by AI. I've not had the chance 113 00:05:33,040 --> 00:05:35,240 Speaker 2: yet to ask you for your prediction, and so may I. 114 00:05:35,560 --> 00:05:39,120 Speaker 1: So yes, So look the far future. No one really 115 00:05:39,200 --> 00:05:41,720 Speaker 1: knows anyone who says definitively there's gonna be lots of 116 00:05:41,720 --> 00:05:44,000 Speaker 1: fewer jobs, or definitively if there's gonna be lots more jobs. 117 00:05:44,440 --> 00:05:48,560 Speaker 1: To say that definitively is to undercut the credibility of 118 00:05:48,560 --> 00:05:51,479 Speaker 1: what you're saying. Now, I describe this as the cognitive 119 00:05:51,520 --> 00:05:54,640 Speaker 1: industrial Revolution. I think it has the same impact as 120 00:05:54,640 --> 00:05:58,240 Speaker 1: the industrial revolution, but now in like knowledge work and 121 00:05:58,279 --> 00:06:01,200 Speaker 1: information work and language work and everything, there's both the 122 00:06:01,200 --> 00:06:03,320 Speaker 1: good and the bad of that. The good is none 123 00:06:03,320 --> 00:06:05,600 Speaker 1: of us are of our current modern society works about 124 00:06:05,600 --> 00:06:09,560 Speaker 1: the industrial revolution. That's what creates the economics and prosperity 125 00:06:09,600 --> 00:06:14,320 Speaker 1: for a middle class, for democracies, for Western societies, et cetera. 126 00:06:14,800 --> 00:06:17,000 Speaker 1: On the other hand, the transition is very difficult, right, 127 00:06:17,080 --> 00:06:20,279 Speaker 1: So the transition into the industrial age was challenging. So 128 00:06:20,360 --> 00:06:22,440 Speaker 1: I think we're both going to get the transition, which 129 00:06:22,480 --> 00:06:25,320 Speaker 1: will be a lot of job transformation, initial job loss, 130 00:06:26,000 --> 00:06:30,680 Speaker 1: eventually I think job regaining and transformation and ultimately a 131 00:06:30,680 --> 00:06:31,479 Speaker 1: lot of prosperity. 132 00:06:31,480 --> 00:06:34,479 Speaker 2: But we need to embrace let's titus all together through 133 00:06:34,560 --> 00:06:38,120 Speaker 2: Reed Hoffman the investor. How have you adjusted your financial 134 00:06:38,160 --> 00:06:41,960 Speaker 2: planning and investment strategy based on the talent what we discussed, 135 00:06:41,960 --> 00:06:43,200 Speaker 2: but it also your jobs outlook. 136 00:06:43,600 --> 00:06:47,279 Speaker 1: Well, so I'm still investing a ton in AI companies 137 00:06:47,279 --> 00:06:50,640 Speaker 1: and tech companies, and for example, people forg going to say, well, 138 00:06:50,800 --> 00:06:53,320 Speaker 1: you don't need fewer software engineers. And actually, in fact, 139 00:06:53,640 --> 00:06:55,680 Speaker 1: I think not only are we going to we're not 140 00:06:55,720 --> 00:06:58,320 Speaker 1: going to need fewer. I think we'll still have they 141 00:06:58,400 --> 00:07:01,599 Speaker 1: call it ten million software engineers, developers, you know kind 142 00:07:01,600 --> 00:07:05,200 Speaker 1: of uh, you know across the you know, Western world. 143 00:07:06,120 --> 00:07:08,760 Speaker 1: But I think what's going to happen is actually even 144 00:07:08,880 --> 00:07:11,640 Speaker 1: you are going to start doing software development because everyone's 145 00:07:11,680 --> 00:07:14,680 Speaker 1: going to have a co pilot for doing some of 146 00:07:14,720 --> 00:07:17,720 Speaker 1: their tasks with a software engineer helping them, right, And 147 00:07:17,800 --> 00:07:21,040 Speaker 1: so we're going to have many, many more software engineers. 148 00:07:22,000 --> 00:07:25,640 Speaker 2: Reid Hoffman, Greylock partner, LinkedIn, co founder, serial founder of 149 00:07:25,680 --> 00:07:26,560 Speaker 2: AI companies,