1 00:00:07,133 --> 00:00:10,453 Speaker 1: You're listening to the Saturday Morning with Jack Tame podcast 2 00:00:10,573 --> 00:00:11,853 Speaker 1: from news talks EDB. 3 00:00:12,733 --> 00:00:15,853 Speaker 2: Twenty two to eleven on news talks EDB. Open Ai 4 00:00:16,013 --> 00:00:18,893 Speaker 2: is the company behind chat GPT and now their top 5 00:00:19,013 --> 00:00:21,373 Speaker 2: talent is being poached by some of the other big 6 00:00:21,413 --> 00:00:25,973 Speaker 2: tech companies four crazy amounts of money. Our textbook paulstine 7 00:00:26,013 --> 00:00:28,933 Speaker 2: House is waiting for his phone to light up. He's 8 00:00:28,973 --> 00:00:32,213 Speaker 2: just got us on Saturday mornings one hundred million bucks. 9 00:00:32,293 --> 00:00:35,213 Speaker 2: Are you serious? This for a scon bonus for a 10 00:00:35,373 --> 00:00:36,253 Speaker 2: computer technician. 11 00:00:37,013 --> 00:00:39,813 Speaker 3: So this is what Sam Oltman, the CEO of open ai, 12 00:00:40,053 --> 00:00:43,053 Speaker 3: has said. People are being poached for right and so 13 00:00:43,293 --> 00:00:45,173 Speaker 3: they must. It must be like employees that are in 14 00:00:45,213 --> 00:00:48,293 Speaker 3: his top ranks have come to and said, buddy, yeah, 15 00:00:48,693 --> 00:00:51,133 Speaker 3: I've got this offer, what can you do for me? 16 00:00:51,293 --> 00:00:53,493 Speaker 3: And I don't know, he's probably just said see ya, 17 00:00:53,733 --> 00:00:55,173 Speaker 3: or he's reluctantly said. 18 00:00:55,413 --> 00:00:58,533 Speaker 2: If you work from home every second Thursday, yeah right, 19 00:00:59,893 --> 00:01:00,733 Speaker 2: right in summer. 20 00:01:01,693 --> 00:01:03,933 Speaker 3: But that's just a staggering number, isn't it. I mean, 21 00:01:03,973 --> 00:01:05,933 Speaker 3: these are the types of numbers you typically here for 22 00:01:06,533 --> 00:01:09,893 Speaker 3: you know, any of our stars or your like big 23 00:01:09,933 --> 00:01:14,093 Speaker 3: Hollywood A listers, and these are like nerdy folks working 24 00:01:14,133 --> 00:01:17,173 Speaker 3: out okay, working out the future of AI. I guess 25 00:01:17,213 --> 00:01:19,013 Speaker 3: so maybe they do need to be paid this sort 26 00:01:19,053 --> 00:01:21,533 Speaker 3: of money like these big like these other big names 27 00:01:21,573 --> 00:01:25,933 Speaker 3: we know about. But it certainly has been ruffling feathers. 28 00:01:26,013 --> 00:01:29,493 Speaker 3: There was every week Meta does a big like all 29 00:01:29,493 --> 00:01:32,573 Speaker 3: hands meeting, and this came up in there all hands meeting, 30 00:01:32,653 --> 00:01:35,773 Speaker 3: and they kind of addressed it and kind of couched it, 31 00:01:35,813 --> 00:01:37,773 Speaker 3: and they were sort of saying, well, it wasn't a 32 00:01:37,813 --> 00:01:41,613 Speaker 3: one hundred million dollars signing bonus. It was structured maybe 33 00:01:41,653 --> 00:01:45,213 Speaker 3: slightly differently. So maybe they're earning one hundred million dollars 34 00:01:45,253 --> 00:01:47,493 Speaker 3: and being paid twenty five million dollars a year. But 35 00:01:47,533 --> 00:01:50,053 Speaker 3: even then I wouldn't say no to that. 36 00:01:50,933 --> 00:01:55,533 Speaker 2: Can I ask this though? So our individuals and the 37 00:01:55,573 --> 00:01:59,413 Speaker 2: expertise that individuals bring, are they so valuable in the space? 38 00:01:59,653 --> 00:02:02,093 Speaker 2: Are there people who are so unique with what they 39 00:02:02,133 --> 00:02:07,013 Speaker 2: bring to AI development that they can possibly justify this underspending? 40 00:02:07,053 --> 00:02:09,613 Speaker 2: You know, like it is one person worth one hundred 41 00:02:09,653 --> 00:02:13,453 Speaker 2: million dollars versus another five people four five million dollars each, 42 00:02:13,453 --> 00:02:14,013 Speaker 2: you know what I mean? 43 00:02:14,613 --> 00:02:19,893 Speaker 3: I would only suggest that quite possibly, I think there's 44 00:02:19,933 --> 00:02:22,133 Speaker 3: a real shortage of people who have experienced in this 45 00:02:22,253 --> 00:02:28,453 Speaker 3: area and what we're seeing probably unlike other technologies that 46 00:02:28,493 --> 00:02:30,853 Speaker 3: have come about, a lot of these AI folks have 47 00:02:30,973 --> 00:02:32,933 Speaker 3: kind of been dabbling with some of the stuff in 48 00:02:33,493 --> 00:02:35,693 Speaker 3: a research capacity. You know, a lot of them have 49 00:02:35,773 --> 00:02:40,613 Speaker 3: probably been around academic or academic adjacent institutions. I mean 50 00:02:40,653 --> 00:02:44,373 Speaker 3: Open AI had a whole nonprofit kind of part to it, 51 00:02:45,053 --> 00:02:47,493 Speaker 3: and then chat GPT's part of their kind of commercial 52 00:02:47,573 --> 00:02:49,853 Speaker 3: arm And so these I think were folks who had 53 00:02:49,893 --> 00:02:55,053 Speaker 3: kind of, yeah, really dedicated themselves to some of this work, 54 00:02:55,213 --> 00:02:57,413 Speaker 3: and now they're obviously seeing the fruits of their labor. 55 00:02:57,413 --> 00:03:00,333 Speaker 3: And I don't think that there are that many who 56 00:03:00,413 --> 00:03:03,573 Speaker 3: would be at that caliber, but certainly those who those 57 00:03:03,613 --> 00:03:05,173 Speaker 3: who are kind of like leading the charge and have 58 00:03:05,213 --> 00:03:09,173 Speaker 3: and writing the papers and being deep into this research. Yeah, 59 00:03:09,333 --> 00:03:12,253 Speaker 3: commanding serious dollars. I mean, this is the I just 60 00:03:12,333 --> 00:03:16,093 Speaker 3: have to remember, this is the hottest technology. And I 61 00:03:16,133 --> 00:03:17,813 Speaker 3: know we talk about a lot of things, and over 62 00:03:17,813 --> 00:03:19,613 Speaker 3: the years, you and I've talked about things, and I've 63 00:03:19,653 --> 00:03:22,613 Speaker 3: seen things come and seen things go. God, look, don't 64 00:03:22,653 --> 00:03:24,933 Speaker 3: even get me started on the three D TVs and 65 00:03:24,973 --> 00:03:28,493 Speaker 3: things like that. But this is actually but this is different, right, 66 00:03:28,573 --> 00:03:31,773 Speaker 3: This feels like a real step change. And these these 67 00:03:31,813 --> 00:03:35,493 Speaker 3: big companies like look at Google, right, their whole livelihood 68 00:03:35,533 --> 00:03:40,453 Speaker 3: has been around data and search and connecting dots, and 69 00:03:41,053 --> 00:03:44,813 Speaker 3: now AIS come in and potentially up ending their entire business. 70 00:03:44,853 --> 00:03:47,053 Speaker 3: So would you take one hundred million dollar bet on 71 00:03:48,053 --> 00:03:52,013 Speaker 3: a guy a girl? Maybe if you. 72 00:03:52,053 --> 00:03:54,693 Speaker 2: Hold your company like Meta, you've gone a hundred million bucks, right, 73 00:03:54,773 --> 00:03:57,253 Speaker 2: Like that's the thing. Everything's relative, like one hundred million 74 00:03:57,293 --> 00:04:01,453 Speaker 2: dollars exactly to another to another company. But it does 75 00:04:01,493 --> 00:04:04,133 Speaker 2: set a very high standard when it comes to when 76 00:04:04,173 --> 00:04:07,213 Speaker 2: it comes to attracting talent. I think though, like the 77 00:04:09,213 --> 00:04:11,853 Speaker 2: if even only a ten percent of the hype for 78 00:04:12,373 --> 00:04:15,653 Speaker 2: AI at least in the next couple of years is warranted, 79 00:04:16,093 --> 00:04:19,653 Speaker 2: it's the kind of technology that has the potential to 80 00:04:19,933 --> 00:04:23,013 Speaker 2: upset the power balance between the big tech companies. 81 00:04:23,093 --> 00:04:23,253 Speaker 3: Right. 82 00:04:23,333 --> 00:04:25,933 Speaker 2: So we've seen the lights of Apple and Google and 83 00:04:26,013 --> 00:04:29,773 Speaker 2: Meta dominate for the last you know, ten or twenty years, 84 00:04:30,133 --> 00:04:31,653 Speaker 2: and all of a sudden that could be about to 85 00:04:31,693 --> 00:04:34,733 Speaker 2: change and change super quickly, which is what's kind of interesting. 86 00:04:35,293 --> 00:04:37,693 Speaker 3: Yeah, unless they do something drastic. 87 00:04:37,613 --> 00:04:40,133 Speaker 2: Unless there's been a million dollars on talent, Yeah, yeah. 88 00:04:39,933 --> 00:04:41,813 Speaker 3: Exactly on the track. I think and I think that 89 00:04:41,933 --> 00:04:44,373 Speaker 3: they're desperate. I think some of these companies, like you know, 90 00:04:44,453 --> 00:04:47,733 Speaker 3: open Aie was a nothing and it's become the company, 91 00:04:47,893 --> 00:04:51,653 Speaker 3: like chet GPT has become the word, has become the 92 00:04:51,773 --> 00:04:54,253 Speaker 3: Google of search. You know what Google is to search, 93 00:04:54,613 --> 00:04:57,973 Speaker 3: they are to AI And would you pay for that? 94 00:04:59,573 --> 00:05:03,053 Speaker 3: Look at your trillion, multi trillion dollar companies and you're like, okay, rounding. 95 00:05:02,813 --> 00:05:05,333 Speaker 2: Area, Yeah maybe maybe we will. Yeah, all right, Paul. Look, 96 00:05:05,333 --> 00:05:07,053 Speaker 2: if you if you need a reference, we certainly don't 97 00:05:07,053 --> 00:05:09,533 Speaker 2: want to lose you on Saturday morning. You need a referee, 98 00:05:09,613 --> 00:05:11,733 Speaker 2: if you're looking for you know, we're always here, So 99 00:05:13,013 --> 00:05:15,773 Speaker 2: I appreciate your time. As always our Textbert Paul Stenhouse. 100 00:05:16,333 --> 00:05:19,413 Speaker 1: For more from Saturday Morning with Jack Tame, listen live 101 00:05:19,533 --> 00:05:22,333 Speaker 1: to News Talks ed B from nine am Saturday, or 102 00:05:22,413 --> 00:05:24,253 Speaker 1: follow the podcast on iHeartRadio