1 00:00:00,000 --> 00:00:01,319 Speaker 1: A bit of a deep dive in the meantime into 2 00:00:01,360 --> 00:00:03,559 Speaker 1: AI for you, is it going to change the world 3 00:00:03,600 --> 00:00:05,640 Speaker 1: or not? Does anyone actually know whether it's going to 4 00:00:05,720 --> 00:00:07,200 Speaker 1: change the world or not? Now? Tom Grub is a 5 00:00:07,240 --> 00:00:10,920 Speaker 1: computer scientist, psychologist co founder of Siri, which is quite 6 00:00:10,920 --> 00:00:13,080 Speaker 1: the claim Sury got sold, of course to Apple. These days, 7 00:00:13,080 --> 00:00:16,000 Speaker 1: he's an entrepreneur and co founder of an adaptive music 8 00:00:16,079 --> 00:00:18,800 Speaker 1: company called Life Score. He's in the country as part 9 00:00:18,840 --> 00:00:21,480 Speaker 1: of Sparks Accelerate, Summits and Tom Grub as we a's 10 00:00:21,520 --> 00:00:22,040 Speaker 1: Tom Nice to. 11 00:00:22,000 --> 00:00:23,759 Speaker 2: Meet, Good morning. 12 00:00:24,160 --> 00:00:27,680 Speaker 1: The window when you come up with something brilliant is 13 00:00:27,800 --> 00:00:30,120 Speaker 1: how big before you know somebody else is going to 14 00:00:30,160 --> 00:00:30,640 Speaker 1: copy it? 15 00:00:32,360 --> 00:00:35,080 Speaker 2: Well, the interesting thing about the brilliant idea of Siri 16 00:00:35,240 --> 00:00:38,960 Speaker 2: was it wasn't ours. That idea of a personal assistant 17 00:00:39,040 --> 00:00:42,279 Speaker 2: had been around since nineteen eighty seven. But what the 18 00:00:42,320 --> 00:00:45,720 Speaker 2: window was for us was taking the time in history 19 00:00:46,080 --> 00:00:48,519 Speaker 2: when a technology was ready, and that's what we did. 20 00:00:48,560 --> 00:00:50,640 Speaker 2: And then we jumped on it. And we had only 21 00:00:50,680 --> 00:00:53,720 Speaker 2: two years to build it before everyone could see it 22 00:00:53,760 --> 00:00:54,760 Speaker 2: in the world and copy it. 23 00:00:55,120 --> 00:00:58,080 Speaker 1: So what was the skill building it or seeing the window? 24 00:00:59,400 --> 00:01:01,800 Speaker 2: Both? Actually it took a team, a small team only 25 00:01:01,800 --> 00:01:05,160 Speaker 2: twenty four people, but we saw the exact time when 26 00:01:05,520 --> 00:01:08,240 Speaker 2: a set of technologies were ready, just barely good enough, 27 00:01:08,760 --> 00:01:11,360 Speaker 2: and we went full speed on building out a thing 28 00:01:11,520 --> 00:01:14,039 Speaker 2: and it worked, and nobody believed it could work, and 29 00:01:14,080 --> 00:01:16,440 Speaker 2: then we showed it could, and then everyone believed they could. 30 00:01:16,680 --> 00:01:17,880 Speaker 1: Did you build it to sell it? 31 00:01:19,200 --> 00:01:21,280 Speaker 2: No? No, we built it to build up a real company. 32 00:01:21,440 --> 00:01:23,760 Speaker 2: We had a really good business in e commerce on 33 00:01:23,920 --> 00:01:26,880 Speaker 2: the phone, and we started working on this when the 34 00:01:26,920 --> 00:01:29,080 Speaker 2: iPhone one came out, so at the very beginning of 35 00:01:29,120 --> 00:01:32,720 Speaker 2: the modern mobile era, and we really thought that's what 36 00:01:32,760 --> 00:01:34,640 Speaker 2: we're going to do. But hey, when Steve Jobs gives 37 00:01:34,720 --> 00:01:36,800 Speaker 2: you a call and says, hey, you want to join 38 00:01:36,840 --> 00:01:38,839 Speaker 2: forces with us, it's hard to turn that down. 39 00:01:39,000 --> 00:01:40,679 Speaker 1: Exactly. Did it change your life? 40 00:01:41,880 --> 00:01:45,120 Speaker 2: Absolutely? I mean my career ambition was to have impact, 41 00:01:45,400 --> 00:01:47,280 Speaker 2: to have a lot of people's lives changed, and it 42 00:01:47,800 --> 00:01:50,640 Speaker 2: became an exponential bend in the curve on impact when 43 00:01:50,880 --> 00:01:52,160 Speaker 2: we joined forces with that one. 44 00:01:52,320 --> 00:01:54,560 Speaker 1: Really interesting that you say that, and I sort of 45 00:01:54,640 --> 00:01:56,320 Speaker 1: knew you would because it rid a bounce you and 46 00:01:56,360 --> 00:01:59,280 Speaker 1: you seem to be looking to use tick for good? 47 00:01:59,440 --> 00:02:00,400 Speaker 1: Is that Fay. 48 00:02:01,640 --> 00:02:04,280 Speaker 2: Definitely on the side of humanity? Yeah, we're trying to 49 00:02:04,520 --> 00:02:07,280 Speaker 2: there's tech for optimization for say, corporate profits, and then 50 00:02:07,440 --> 00:02:09,640 Speaker 2: tech for making people eyes the better. And it's easier 51 00:02:09,639 --> 00:02:09,920 Speaker 2: to do to. 52 00:02:09,919 --> 00:02:12,600 Speaker 1: Look la which is the interface that fascinates me most. So, 53 00:02:12,720 --> 00:02:15,280 Speaker 1: a good guy like you wants to do well by tech. 54 00:02:15,440 --> 00:02:17,679 Speaker 1: But the world is dominated by people who love the 55 00:02:17,680 --> 00:02:20,840 Speaker 1: bottom line more. How do they coexist? 56 00:02:22,040 --> 00:02:25,720 Speaker 2: Well, it's very possible, especially in AI, where there's a 57 00:02:25,760 --> 00:02:28,919 Speaker 2: limited talent pool, you can actually attract the very best 58 00:02:29,000 --> 00:02:32,639 Speaker 2: people by having a higher goal. For example, open ai 59 00:02:32,919 --> 00:02:35,680 Speaker 2: was originally founded as a nonprofit to give the benefits 60 00:02:35,720 --> 00:02:39,160 Speaker 2: of AI to the world, and that's what attracted the 61 00:02:39,280 --> 00:02:42,800 Speaker 2: very best AI scientists, which created the modern aichatbot. 62 00:02:43,520 --> 00:02:46,400 Speaker 1: But I'm sure they said that when the into the 63 00:02:46,440 --> 00:02:49,000 Speaker 1: net as well, didn't they? And yet look what's happened 64 00:02:49,000 --> 00:02:53,840 Speaker 1: to the net, the nest, the net, the Internet, Oh, 65 00:02:53,919 --> 00:02:54,400 Speaker 1: the Internet. 66 00:02:54,720 --> 00:02:57,040 Speaker 2: Well, actually that's very true. That's thirty years ago now, 67 00:02:57,160 --> 00:03:00,000 Speaker 2: and hey, it did do some good things in the world, Cannet, 68 00:03:00,360 --> 00:03:03,200 Speaker 2: it did change our collective mind. Unfortunately, you didn't. You 69 00:03:03,200 --> 00:03:05,440 Speaker 2: didn't anticipate social media and what that would do to 70 00:03:05,480 --> 00:03:08,400 Speaker 2: journalism and we don't would do to our social consciousness. 71 00:03:08,440 --> 00:03:11,880 Speaker 1: Exactly. I'm not a techie like you, but but here's 72 00:03:11,880 --> 00:03:14,560 Speaker 1: my view of AI. AI will ultimately prove to be 73 00:03:14,800 --> 00:03:18,200 Speaker 1: very broadly speaking, about the same as most other really 74 00:03:18,200 --> 00:03:20,400 Speaker 1: big advances in tech. In other words, it won't be 75 00:03:20,560 --> 00:03:23,560 Speaker 1: as transformative as you think, but it won't be as 76 00:03:23,760 --> 00:03:26,040 Speaker 1: non transformative. It'll be somewhere in the middle. Is that 77 00:03:26,080 --> 00:03:28,000 Speaker 1: a reasonable guess at this point in time. 78 00:03:28,720 --> 00:03:30,920 Speaker 2: I would put my ships on the more transformative end 79 00:03:30,960 --> 00:03:35,000 Speaker 2: of that. It's it's different than most technologies, and that 80 00:03:35,160 --> 00:03:38,720 Speaker 2: it is omnipurpose. You can do all kinds of things, 81 00:03:38,800 --> 00:03:41,600 Speaker 2: pretty much anything involving language on the input and language 82 00:03:41,600 --> 00:03:45,440 Speaker 2: on the output with this new technology and that that introduces. 83 00:03:46,000 --> 00:03:49,200 Speaker 2: But it cuts across all vertical industries. But anyone, anybody 84 00:03:49,240 --> 00:03:51,880 Speaker 2: who has knowledge workers in their business, which is everybody, yeah, 85 00:03:52,040 --> 00:03:52,840 Speaker 2: is going to be impacted. 86 00:03:53,720 --> 00:03:58,360 Speaker 1: But for good or bad? And how extreme do you think? 87 00:03:59,080 --> 00:04:01,640 Speaker 2: Well, there's two kinds of I mean, the bad that 88 00:04:01,760 --> 00:04:05,520 Speaker 2: really worries me a lot is the sort of unleashing 89 00:04:05,560 --> 00:04:07,800 Speaker 2: deep fakes that dissolves people ability to know it's true 90 00:04:07,800 --> 00:04:11,840 Speaker 2: and false, or you know, dangerous weaponized bot technologies that 91 00:04:11,920 --> 00:04:14,520 Speaker 2: could break into our security and everything. Those things are 92 00:04:14,520 --> 00:04:17,320 Speaker 2: tough and their system problems, but the other bad that 93 00:04:17,400 --> 00:04:19,680 Speaker 2: maybe we're looking at in Zealand. First, you know, everyone's 94 00:04:19,720 --> 00:04:22,000 Speaker 2: worried about you're done and seeing job loss and so on. 95 00:04:22,400 --> 00:04:24,599 Speaker 2: You know, the business cycle itself is causing that, but 96 00:04:24,640 --> 00:04:27,120 Speaker 2: people are worried that AI will too, and that's the 97 00:04:27,160 --> 00:04:30,760 Speaker 2: keys with the humanistic AI approach says you can invest 98 00:04:30,960 --> 00:04:34,400 Speaker 2: your efforts and attention and money in areas where the 99 00:04:34,440 --> 00:04:40,080 Speaker 2: AI is amplifying and changing existing human labor, rather than it. 100 00:04:40,279 --> 00:04:42,040 Speaker 1: Right explain to me in a way that I can 101 00:04:42,160 --> 00:04:44,760 Speaker 1: understand it might and so you go back to something 102 00:04:44,880 --> 00:04:47,880 Speaker 1: like Siri. These things are only as good as what 103 00:04:47,920 --> 00:04:50,640 Speaker 1: they tappen to. So in other words, when I say, Siri, 104 00:04:50,800 --> 00:04:54,520 Speaker 1: find me a recipe for tomato soup that trolls the net, 105 00:04:54,640 --> 00:04:56,279 Speaker 1: if it's not on the net, it doesn't give you 106 00:04:56,320 --> 00:05:00,640 Speaker 1: a decent answer. Does AI fundamentally and profoundly change that 107 00:05:01,000 --> 00:05:01,240 Speaker 1: or not? 108 00:05:03,279 --> 00:05:05,760 Speaker 2: That kind of thing is essentially going to be the same. 109 00:05:05,800 --> 00:05:10,000 Speaker 2: It's a slightly better interface to information retrieval then say 110 00:05:10,080 --> 00:05:14,120 Speaker 2: just blue links and Google, but it is there's much 111 00:05:14,160 --> 00:05:16,240 Speaker 2: more to it than that, because you can also ask 112 00:05:16,279 --> 00:05:20,480 Speaker 2: the things like help me design an interesting new radio 113 00:05:20,600 --> 00:05:24,400 Speaker 2: show using you know, I don't know, dancing rabbits or something, 114 00:05:24,480 --> 00:05:26,159 Speaker 2: so you can help you can use you can use 115 00:05:26,160 --> 00:05:28,279 Speaker 2: it as an assistant to help you ID eight things 116 00:05:28,520 --> 00:05:30,640 Speaker 2: that are just not out there in the world. You 117 00:05:30,640 --> 00:05:32,280 Speaker 2: can say, play the role of a critic, play the 118 00:05:32,360 --> 00:05:34,839 Speaker 2: role of an employer, play the role of a whoever, 119 00:05:35,320 --> 00:05:39,120 Speaker 2: and it will take that role and you can then practice. 120 00:05:39,320 --> 00:05:42,440 Speaker 2: You can use it as sort of an omnipurpose human assistant. 121 00:05:42,920 --> 00:05:45,560 Speaker 2: All crimes are things for you, but believe that it 122 00:05:45,600 --> 00:05:46,880 Speaker 2: tells you it is true. That's all right? 123 00:05:47,240 --> 00:05:50,520 Speaker 1: Is that retrieving to do that? Is that retrieving stuff 124 00:05:50,520 --> 00:05:53,640 Speaker 1: that's already there and therefore must source that? Or is 125 00:05:53,680 --> 00:05:55,400 Speaker 1: it a a point Will it be at a point 126 00:05:55,440 --> 00:05:57,760 Speaker 1: where literally it may be able to do something we 127 00:05:57,800 --> 00:05:59,719 Speaker 1: haven't even conceived or thought of yet. 128 00:06:00,240 --> 00:06:02,320 Speaker 2: Oh, oh, it doesn't. It doesn't retrieve anything to do. 129 00:06:02,360 --> 00:06:05,400 Speaker 2: Sounds like that it's already baked into its model. Its 130 00:06:05,440 --> 00:06:08,400 Speaker 2: model is essentially a very large compression of everything it's read, 131 00:06:08,480 --> 00:06:12,760 Speaker 2: and it's read a million lifetimes of content, and so 132 00:06:12,839 --> 00:06:15,640 Speaker 2: it's basically just all just smash that down into its model, 133 00:06:15,800 --> 00:06:18,560 Speaker 2: and then it can use that. There's enough patterns of 134 00:06:18,640 --> 00:06:21,040 Speaker 2: human thought that are in that model already. It can 135 00:06:21,120 --> 00:06:23,279 Speaker 2: use that to do new novel things with you. But 136 00:06:23,320 --> 00:06:25,560 Speaker 2: you have to tell it where to go. You can't 137 00:06:25,560 --> 00:06:27,039 Speaker 2: just say, hey, give me a solution to the world. 138 00:06:27,640 --> 00:06:29,599 Speaker 1: So at what point does it take over the world, 139 00:06:29,960 --> 00:06:31,960 Speaker 1: Because if it has to be told what to do, 140 00:06:32,080 --> 00:06:34,320 Speaker 1: it needs to at some point think for itself. When 141 00:06:34,360 --> 00:06:35,040 Speaker 1: does that happen? 142 00:06:36,120 --> 00:06:37,919 Speaker 2: Well, that will probably if that happen, it will probably 143 00:06:37,920 --> 00:06:41,120 Speaker 2: happen because a bad actor tells you that. And that's 144 00:06:41,120 --> 00:06:42,039 Speaker 2: what we're really worried about. 145 00:06:42,400 --> 00:06:46,760 Speaker 1: Here's a taxt, Mike II will be as transformative as electricity. 146 00:06:47,160 --> 00:06:47,919 Speaker 1: Is that fair or not? 147 00:06:48,000 --> 00:06:50,840 Speaker 2: Do you think I actually believe it's true. I think 148 00:06:51,440 --> 00:06:54,000 Speaker 2: some PJ said that the head of Google is sort 149 00:06:54,000 --> 00:06:56,279 Speaker 2: of the company with the biggest investment in AI. I 150 00:06:56,279 --> 00:07:01,120 Speaker 2: think he's right. It is omnipurpose like a electricity. Electricy 151 00:07:01,120 --> 00:07:05,040 Speaker 2: has changed all kinds of businesses and lifestyle lifestyles. Thanks, 152 00:07:05,040 --> 00:07:07,120 Speaker 2: and we'll do that too. It hasn't happened this year. 153 00:07:07,160 --> 00:07:09,520 Speaker 2: It's going to be a little bit of transition exactly. 154 00:07:09,560 --> 00:07:10,840 Speaker 2: That's the main reason, is it. 155 00:07:10,920 --> 00:07:13,160 Speaker 1: How exciting is it to be in this day and 156 00:07:13,280 --> 00:07:16,440 Speaker 1: age doing what people like you do versus being edison 157 00:07:16,560 --> 00:07:18,679 Speaker 1: and discovering stuff that we now take for granted. 158 00:07:19,920 --> 00:07:22,960 Speaker 2: It's amazing to be alive right now to see it happening, 159 00:07:23,040 --> 00:07:24,560 Speaker 2: and we're you know, we're all going to see it happen. 160 00:07:24,640 --> 00:07:27,120 Speaker 2: I saw. I was already a professional when the web happened, 161 00:07:27,120 --> 00:07:29,840 Speaker 2: and seeing that happened was really exciting. It's been thirty 162 00:07:29,920 --> 00:07:31,960 Speaker 2: years now seeing this happened. Now it's going to eclipse 163 00:07:31,960 --> 00:07:34,040 Speaker 2: the Web in terms of the impact. And I think 164 00:07:34,080 --> 00:07:35,640 Speaker 2: we're going to see and all of us in our 165 00:07:35,680 --> 00:07:39,280 Speaker 2: lifetime thing called artificial general intelligence, which is a general 166 00:07:39,320 --> 00:07:41,239 Speaker 2: purpose AI that you can just kind of do whatever 167 00:07:41,280 --> 00:07:43,800 Speaker 2: you want it to. That's going to change everything. And 168 00:07:44,040 --> 00:07:46,120 Speaker 2: the funny thing is we saw that we saw from 169 00:07:46,400 --> 00:07:48,560 Speaker 2: pre cell phone days all the way to that in 170 00:07:48,600 --> 00:07:49,240 Speaker 2: one lifetime. 171 00:07:49,960 --> 00:07:52,360 Speaker 1: Is it going to dumb us down? If something or 172 00:07:52,400 --> 00:07:55,040 Speaker 1: something or somebody can do everything for us, what do 173 00:07:55,120 --> 00:07:55,520 Speaker 1: we do? 174 00:07:56,720 --> 00:07:59,400 Speaker 2: No, absolutely won't run this down. If it's going to 175 00:07:59,480 --> 00:08:02,760 Speaker 2: challenge us to rise in education because sort of mediocre 176 00:08:02,840 --> 00:08:05,440 Speaker 2: writing and reading and mediocre knowledge work is not going 177 00:08:05,520 --> 00:08:08,000 Speaker 2: to be appreciated anymore. People are going to step up 178 00:08:08,400 --> 00:08:11,400 Speaker 2: and use these tools to be better than they are today. 179 00:08:11,440 --> 00:08:13,600 Speaker 2: And those who can learn to do that, are going 180 00:08:13,640 --> 00:08:14,880 Speaker 2: to be the ones who get to hide. 181 00:08:14,680 --> 00:08:19,640 Speaker 1: Meaning jobs life score. It's adept of music, dynamically composed 182 00:08:19,760 --> 00:08:23,880 Speaker 1: and produces as it plays, which allows it to adapt 183 00:08:23,920 --> 00:08:26,400 Speaker 1: to content. What's the purpose of that? Why would you 184 00:08:26,480 --> 00:08:27,320 Speaker 1: want to do that? 185 00:08:28,440 --> 00:08:30,320 Speaker 2: Well, let's say on your morning commute, you're listening to 186 00:08:30,360 --> 00:08:31,680 Speaker 2: the radio and then you want to turn for a 187 00:08:31,720 --> 00:08:34,600 Speaker 2: little bit of music to chill out. Well, it can 188 00:08:34,720 --> 00:08:37,800 Speaker 2: generate a piece of music that is a journey. Is 189 00:08:37,800 --> 00:08:40,320 Speaker 2: that company's your journey? Like a film score for your journey? 190 00:08:40,480 --> 00:08:42,000 Speaker 2: Or let's say're working out in a gym and you 191 00:08:42,000 --> 00:08:44,440 Speaker 2: want to have something just not a playlist, but actually 192 00:08:44,640 --> 00:08:48,560 Speaker 2: adapts while you're working out how it's going. That's you 193 00:08:48,559 --> 00:08:52,280 Speaker 2: can still have human machine human music, but it's remixed 194 00:08:52,280 --> 00:08:52,719 Speaker 2: on the fly. 195 00:08:53,280 --> 00:08:56,000 Speaker 1: Is that being told what to do or is it 196 00:08:56,080 --> 00:08:57,520 Speaker 1: doing it for you? 197 00:08:58,679 --> 00:09:01,880 Speaker 2: It's basically taking eg that was composed by humans and 198 00:09:02,160 --> 00:09:05,800 Speaker 2: recomposing it to in face of the signal. So like 199 00:09:05,840 --> 00:09:08,440 Speaker 2: you're a stoplight, it's sort of playing a nice chill 200 00:09:08,600 --> 00:09:11,200 Speaker 2: like holding beat, and then as you go up and 201 00:09:11,240 --> 00:09:13,720 Speaker 2: accelerate to go to the highway, it ramps it up 202 00:09:13,760 --> 00:09:16,240 Speaker 2: and goes more exciting it's all music that's already been 203 00:09:16,280 --> 00:09:18,760 Speaker 2: composed in a little bit, but then it's making it 204 00:09:18,840 --> 00:09:21,680 Speaker 2: adapt to your life situation at that moment. 205 00:09:21,920 --> 00:09:24,080 Speaker 1: Is it workable? Is it real? Is it happening right now? 206 00:09:25,000 --> 00:09:27,000 Speaker 2: Yeah? It does. It does work, and we have we've 207 00:09:27,000 --> 00:09:29,200 Speaker 2: had working for a couple of years. Now it does 208 00:09:29,200 --> 00:09:31,920 Speaker 2: actually work. It's really fun. In fact, we've also found 209 00:09:31,960 --> 00:09:34,120 Speaker 2: that we can just do it even without the adapt team. 210 00:09:34,200 --> 00:09:36,079 Speaker 2: We could just tell it. Hey, here's a guy who 211 00:09:36,080 --> 00:09:39,400 Speaker 2: had an album that's of great music for relaxing. He said, 212 00:09:39,400 --> 00:09:41,480 Speaker 2: give me an eight hour sleep album. I can't afford 213 00:09:41,480 --> 00:09:43,560 Speaker 2: to write this. Myself and the machine really have an 214 00:09:43,600 --> 00:09:46,160 Speaker 2: eight hour album. But now his fans can go to 215 00:09:46,160 --> 00:09:47,120 Speaker 2: sleep with Wow. 216 00:09:47,600 --> 00:09:50,400 Speaker 1: How's the money side of this? It is raising money. 217 00:09:50,400 --> 00:09:53,480 Speaker 1: It strikes me that if you've got AI in your CV, 218 00:09:53,960 --> 00:09:56,360 Speaker 1: there's there's money to be head out there to, you know, 219 00:09:56,440 --> 00:09:58,600 Speaker 1: trying new ideas and do new research. Is that true? 220 00:10:00,160 --> 00:10:03,240 Speaker 2: There is, Although that sort of an initial hype excitement 221 00:10:03,280 --> 00:10:05,480 Speaker 2: is sort of over now. I think I think now 222 00:10:05,480 --> 00:10:07,640 Speaker 2: we're in the stage where we're looking people are looking 223 00:10:07,640 --> 00:10:10,000 Speaker 2: to spend money on. How do you take existing AI 224 00:10:10,200 --> 00:10:13,080 Speaker 2: ideas and apply thement to a specific industry where you 225 00:10:13,200 --> 00:10:16,319 Speaker 2: know for sure that industry has a problem to solve. 226 00:10:16,720 --> 00:10:18,800 Speaker 1: Fantastic. What do you enjoy your staying in the country, Tom, 227 00:10:18,840 --> 00:10:20,920 Speaker 1: I've appreciated your time very much and good to meet 228 00:10:20,920 --> 00:10:23,360 Speaker 1: and talk with you. Tom Gruber. Once upon a time, 229 00:10:23,400 --> 00:10:26,040 Speaker 1: the inventor of sery bit has gone, as you've just heard, 230 00:10:26,080 --> 00:10:28,559 Speaker 1: onto other big, bright and wonderful things. 231 00:10:28,600 --> 00:10:28,800 Speaker 2: Gee. 232 00:10:28,800 --> 00:10:30,199 Speaker 1: She's an interesting world. 233 00:10:29,960 --> 00:10:30,240 Speaker 2: Isn't it. 234 00:10:30,760 --> 00:10:33,680 Speaker 1: For more from the Mic Asking Breakfast, listen live to 235 00:10:33,800 --> 00:10:36,839 Speaker 1: news talks it'd be from six am weekdays, or follow 236 00:10:36,920 --> 00:10:38,480 Speaker 1: the podcast on iHeartRadio.