1 00:00:03,680 --> 00:00:09,200 Speaker 1: I'm TT and I'm Zakiyah, and this is Dope Labs. 2 00:00:11,360 --> 00:00:14,560 Speaker 1: Welcome to Dope Labs, a weekly podcast that mixes hardcore 3 00:00:14,680 --> 00:00:17,639 Speaker 1: science with pop culture and a healthy dose of friendship. 4 00:00:22,040 --> 00:00:24,560 Speaker 1: We're back with a follow up on AI. So we 5 00:00:24,760 --> 00:00:29,720 Speaker 1: previously talked about the environmental impact of AI, specifically large 6 00:00:29,800 --> 00:00:33,720 Speaker 1: language models or lms like chat GBT, and the need 7 00:00:33,800 --> 00:00:36,760 Speaker 1: to have a way to measure the resources required to 8 00:00:36,960 --> 00:00:40,040 Speaker 1: execute tasks. Yeah, but this time we're taking a look 9 00:00:40,080 --> 00:00:42,800 Speaker 1: at AI from a different angle and we're diving into 10 00:00:42,800 --> 00:00:46,479 Speaker 1: more of what's possible, the tools that are available, and 11 00:00:46,960 --> 00:00:50,239 Speaker 1: what's needed to leverage them if you choose to use them. 12 00:00:50,520 --> 00:00:53,159 Speaker 1: So let's jump right into the recitation. What do we know. 13 00:00:53,440 --> 00:00:56,240 Speaker 1: There's been a lot in the news on AI and 14 00:00:56,360 --> 00:00:59,840 Speaker 1: social media, and there was an environmental impact that we 15 00:00:59,840 --> 00:01:03,160 Speaker 1: talked about in Lab ninety four. Yeah, there's been discussions 16 00:01:03,160 --> 00:01:06,800 Speaker 1: of AI and education, particularly students' use of it. I've 17 00:01:06,800 --> 00:01:10,480 Speaker 1: seen everybody writing about that and a cheater Yeah. 18 00:01:10,319 --> 00:01:12,800 Speaker 2: Yeah, yeah. 19 00:01:12,920 --> 00:01:18,039 Speaker 1: Trump issued an executive order about early exposure and AI integration, 20 00:01:18,240 --> 00:01:23,520 Speaker 1: plus the opportunities for lifelong learners by creating a task force. Yeah, 21 00:01:23,640 --> 00:01:27,959 Speaker 1: let's move on to what we want to know. Yeah, 22 00:01:28,040 --> 00:01:29,840 Speaker 1: I feel like there's so much on the market for me. 23 00:01:29,959 --> 00:01:32,200 Speaker 1: I'm like, how do we keep up chat GPT? You know, 24 00:01:32,440 --> 00:01:33,679 Speaker 1: there's like this new AI tool. 25 00:01:33,720 --> 00:01:33,800 Speaker 3: Now. 26 00:01:33,840 --> 00:01:35,959 Speaker 1: I'm getting ads on Instagrams where people are like, I 27 00:01:36,000 --> 00:01:39,400 Speaker 1: created this AI tool and it does xyz you can 28 00:01:39,440 --> 00:01:41,360 Speaker 1: take a jpeg and blah blah blah. And I was like, 29 00:01:41,360 --> 00:01:43,039 Speaker 1: what am I clicking on? Did they think this is 30 00:01:43,040 --> 00:01:48,480 Speaker 1: what I want? It's AI overloaded at this point. It's like, oh, 31 00:01:48,520 --> 00:01:51,960 Speaker 1: you can use this AI to brush your teeth. I'm like, whooh, 32 00:01:53,160 --> 00:01:57,920 Speaker 1: okay that I am overwhelmed. And so what I want 33 00:01:57,960 --> 00:02:00,480 Speaker 1: to know is what's the key if you're a opting 34 00:02:00,560 --> 00:02:03,640 Speaker 1: and using AI, Like, how do you sift. 35 00:02:03,360 --> 00:02:06,280 Speaker 2: Through all of those AI tools? 36 00:02:06,400 --> 00:02:09,560 Speaker 1: Yes? And on the I guess the other side of 37 00:02:09,560 --> 00:02:12,239 Speaker 1: that coin, TT is what should you consider if you're 38 00:02:12,320 --> 00:02:15,360 Speaker 1: not using AI, Because just because you're not using it 39 00:02:15,360 --> 00:02:18,160 Speaker 1: doesn't mean you shouldn't know things about it, right, That's right. 40 00:02:18,400 --> 00:02:20,280 Speaker 1: So I think we're ready to jump into the dissection. 41 00:02:20,480 --> 00:02:23,680 Speaker 1: Perfect for this lab, we reached out to a creative 42 00:02:23,880 --> 00:02:27,400 Speaker 1: entrepreneur who is an expert at AI and teaches others 43 00:02:27,400 --> 00:02:29,480 Speaker 1: about it. Lauren is that girl when it comes to 44 00:02:29,520 --> 00:02:34,440 Speaker 1: branding it a designer educator. Yeah, call yourself our AI auntie. 45 00:02:34,480 --> 00:02:38,200 Speaker 4: I'm Lauren de Vane and I branded myself as your 46 00:02:38,240 --> 00:02:41,840 Speaker 4: aiu T on Instagram and on the Internet. I used 47 00:02:41,840 --> 00:02:45,320 Speaker 4: to run social media creative at All to Beauty before 48 00:02:45,360 --> 00:02:48,280 Speaker 4: I started my own things. So I kind of come 49 00:02:48,400 --> 00:02:51,920 Speaker 4: from a creative background. My degree is in graphic design. 50 00:02:52,040 --> 00:02:55,800 Speaker 4: So I'm the creative AI girly that you find helping 51 00:02:56,080 --> 00:03:00,200 Speaker 4: creatives entrepreneurs figure out how to be using ai I 52 00:03:00,520 --> 00:03:02,920 Speaker 4: in their creative workflows but also just like in their 53 00:03:02,960 --> 00:03:05,480 Speaker 4: everyday life and figuring out ways that it can really 54 00:03:05,560 --> 00:03:09,000 Speaker 4: be beneficial to us in all of the things. 55 00:03:09,160 --> 00:03:10,160 Speaker 3: So yeah, that's what I do. 56 00:03:10,400 --> 00:03:11,240 Speaker 2: Oh my goodness. 57 00:03:11,280 --> 00:03:16,200 Speaker 1: So what made you start weaving AI into your workflow? Like, 58 00:03:16,280 --> 00:03:18,560 Speaker 1: what was the thing that popped up where you said, 59 00:03:18,639 --> 00:03:20,640 Speaker 1: uh huh, I've got to tap in. 60 00:03:21,320 --> 00:03:25,000 Speaker 3: So for me, it was discovering mid Journey. 61 00:03:25,280 --> 00:03:30,800 Speaker 4: So chajubt existed before mid Journey, but it was early days, right, 62 00:03:30,840 --> 00:03:33,480 Speaker 4: it was still like twenty twenty two. It couldn't do 63 00:03:33,639 --> 00:03:36,200 Speaker 4: that much yet, And so I tried Chad Jubet, I 64 00:03:36,280 --> 00:03:39,240 Speaker 4: tried Dolly, which is open Ayes image. 65 00:03:38,960 --> 00:03:41,680 Speaker 3: Generation tool, and I was like, this is so bad. 66 00:03:41,840 --> 00:03:44,280 Speaker 4: Fast forward a couple months later, we were like December 67 00:03:44,320 --> 00:03:48,560 Speaker 4: twenty twenty two. I always see these images of just 68 00:03:48,640 --> 00:03:50,960 Speaker 4: such surreal show and I'm like, these aren't photos, Like 69 00:03:50,960 --> 00:03:51,760 Speaker 4: where are these coming from? 70 00:03:51,800 --> 00:03:53,000 Speaker 3: How are people making these? 71 00:03:53,480 --> 00:03:56,160 Speaker 4: And so I found a YouTube that was like mid Journey, 72 00:03:56,200 --> 00:03:58,080 Speaker 4: but it was on Discord at the time, and I 73 00:03:58,120 --> 00:04:02,560 Speaker 4: had no knowledge of Discord, and so I needed to 74 00:04:02,840 --> 00:04:05,400 Speaker 4: find out like how I could be using this tool. 75 00:04:05,600 --> 00:04:08,280 Speaker 4: So I like went into like a forty eight hour 76 00:04:08,680 --> 00:04:10,840 Speaker 4: like I just dove so deep in. It was just 77 00:04:10,880 --> 00:04:12,880 Speaker 4: like making all these images, learning what I could do, 78 00:04:13,400 --> 00:04:15,080 Speaker 4: and it came out of it and just had such 79 00:04:15,120 --> 00:04:18,080 Speaker 4: a different perspective based on what I had done for 80 00:04:18,080 --> 00:04:20,719 Speaker 4: the last ten years working at Walgreens and working at Alta, 81 00:04:20,839 --> 00:04:23,240 Speaker 4: being a designer and a creative and an art director 82 00:04:23,240 --> 00:04:26,080 Speaker 4: and a stylist and photographer, and I just was able 83 00:04:26,120 --> 00:04:29,800 Speaker 4: to see, oh my god, the way that this could 84 00:04:30,680 --> 00:04:35,799 Speaker 4: impact and change the way that creatives are executing photo 85 00:04:35,839 --> 00:04:40,640 Speaker 4: shoots or any like any sort of creative execution. How 86 00:04:40,720 --> 00:04:42,880 Speaker 4: this could change it in terms of speed, intent, in 87 00:04:43,000 --> 00:04:46,159 Speaker 4: terms of cost, in terms of everything, and this just 88 00:04:46,240 --> 00:04:49,240 Speaker 4: kind of it all like crescendoed at the right time, 89 00:04:49,320 --> 00:04:52,520 Speaker 4: and I just started teaching designers how to use AI 90 00:04:52,560 --> 00:04:54,360 Speaker 4: and that just turned into what it is now. 91 00:04:54,680 --> 00:04:55,880 Speaker 2: Amazing, amazing. 92 00:04:56,120 --> 00:04:58,240 Speaker 1: The reason I thought it was so great that we 93 00:04:58,480 --> 00:05:01,520 Speaker 1: had the chance to talk to you is because I 94 00:05:01,600 --> 00:05:04,720 Speaker 1: just saw MIT drop a study that was saying the 95 00:05:04,720 --> 00:05:08,000 Speaker 1: more we rely on AI tools, particularly like chat GPT, 96 00:05:08,560 --> 00:05:11,320 Speaker 1: the less our brains light up, like our neurons are 97 00:05:11,360 --> 00:05:15,760 Speaker 1: just saying I'll pass. And they're calling it cognitive debt. 98 00:05:15,839 --> 00:05:18,920 Speaker 1: So basically they're saying, your creative muscles can get lazy 99 00:05:19,240 --> 00:05:22,160 Speaker 1: when you use these tools to do a lot of 100 00:05:22,200 --> 00:05:25,520 Speaker 1: the thinking. But there's also a twist because there was 101 00:05:25,560 --> 00:05:27,760 Speaker 1: another study and they were saying, if you pause and 102 00:05:27,800 --> 00:05:30,839 Speaker 1: reflect and get kind of meta, which is not just thinking, 103 00:05:30,880 --> 00:05:34,280 Speaker 1: but thinking about how you're thinking, that AI tools can 104 00:05:34,320 --> 00:05:37,600 Speaker 1: actually boost your creativity and originality. And I want to 105 00:05:37,640 --> 00:05:41,400 Speaker 1: know your take, because you've gone from traditional design and 106 00:05:41,520 --> 00:05:45,560 Speaker 1: branding support to AI enhanced work. Do you think the 107 00:05:45,600 --> 00:05:49,040 Speaker 1: AI tools are making a sharper or too comfortable? 108 00:05:49,480 --> 00:05:55,039 Speaker 4: I think the harder thing to grasp is that PREAI, 109 00:05:55,240 --> 00:05:57,960 Speaker 4: when we look at different tools, they generally. 110 00:05:57,720 --> 00:05:59,840 Speaker 3: Are doing like one thing for you. 111 00:06:00,520 --> 00:06:03,120 Speaker 4: Whereas AI it's like I could use it to help 112 00:06:03,160 --> 00:06:05,160 Speaker 4: me learn how to code, where you could use it 113 00:06:05,200 --> 00:06:07,960 Speaker 4: to learn how to come up with an entire strategy 114 00:06:07,960 --> 00:06:09,960 Speaker 4: for your business, while someone else could be using it 115 00:06:10,000 --> 00:06:12,760 Speaker 4: to learn how to like understand what their dietary needs 116 00:06:12,880 --> 00:06:13,719 Speaker 4: or whatever it is. 117 00:06:13,800 --> 00:06:15,719 Speaker 3: Right, So there's so many. 118 00:06:15,640 --> 00:06:19,080 Speaker 4: Use cases for AI that I think when we are like, oh, well, 119 00:06:19,120 --> 00:06:20,960 Speaker 4: it's gonna make you stupid, or it's like but in 120 00:06:21,000 --> 00:06:21,880 Speaker 4: what capacity? 121 00:06:22,000 --> 00:06:22,160 Speaker 3: Right? 122 00:06:22,240 --> 00:06:24,960 Speaker 4: And then I also think that like the other bigger 123 00:06:25,000 --> 00:06:28,359 Speaker 4: piece of that is most people don't know how to 124 00:06:28,480 --> 00:06:29,279 Speaker 4: use it properly. 125 00:06:29,440 --> 00:06:32,760 Speaker 3: And that tends to be the issue because if you're 126 00:06:32,880 --> 00:06:34,359 Speaker 3: using it, and this is one of the biggest thing 127 00:06:34,400 --> 00:06:36,520 Speaker 3: that I teach my students and all my followers is 128 00:06:36,640 --> 00:06:38,040 Speaker 3: process over prompt. 129 00:06:38,200 --> 00:06:41,839 Speaker 4: It's conversation over command. So it's not just like telling 130 00:06:41,839 --> 00:06:42,760 Speaker 4: it to do this one. 131 00:06:42,640 --> 00:06:44,159 Speaker 3: Thing and then like that's it. 132 00:06:44,160 --> 00:06:45,960 Speaker 4: It's like, okay, you ask it to do this thing, 133 00:06:46,000 --> 00:06:48,720 Speaker 4: and then it gives you an output, and then you say, oh, well, 134 00:06:48,760 --> 00:06:51,920 Speaker 4: based on that, can I have three ideas that would 135 00:06:51,960 --> 00:06:54,120 Speaker 4: you know, blow up from here? And then we pick 136 00:06:54,160 --> 00:06:56,360 Speaker 4: one of those and we say, okay, I have this, this. 137 00:06:56,320 --> 00:06:59,000 Speaker 3: And this idea. So it's more about the way that 138 00:06:59,040 --> 00:06:59,680 Speaker 3: you use it. 139 00:06:59,720 --> 00:07:01,880 Speaker 4: I think it probably maybe isn't going to make you 140 00:07:01,920 --> 00:07:03,880 Speaker 4: any smarter if you just take the first output and 141 00:07:03,920 --> 00:07:05,279 Speaker 4: run with it and say that's it. 142 00:07:05,800 --> 00:07:06,320 Speaker 3: But if you. 143 00:07:06,400 --> 00:07:09,560 Speaker 4: Understand how it works and how to actually work with 144 00:07:09,560 --> 00:07:12,920 Speaker 4: it as a collaborator and a partner, and you have 145 00:07:13,400 --> 00:07:17,160 Speaker 4: the domain expertise yourself, and that's another thing that is a. 146 00:07:17,160 --> 00:07:18,440 Speaker 3: Huge piece of it. 147 00:07:18,440 --> 00:07:20,400 Speaker 4: It's like, if you're already good at what you do 148 00:07:20,440 --> 00:07:23,480 Speaker 4: and you understand all that this is really just like 149 00:07:23,640 --> 00:07:26,080 Speaker 4: asking another person to come into the room that's also 150 00:07:26,200 --> 00:07:28,400 Speaker 4: at the same level as you and have a conversation, 151 00:07:28,520 --> 00:07:30,960 Speaker 4: whether it's a person or a group of ten different 152 00:07:30,960 --> 00:07:32,480 Speaker 4: people that you say I want you to come in. 153 00:07:32,480 --> 00:07:34,600 Speaker 4: From this perspective, it's like when you know how to 154 00:07:34,640 --> 00:07:36,480 Speaker 4: prompt it and you know the ways that you can 155 00:07:36,600 --> 00:07:39,640 Speaker 4: use it, I absolutely do not believe that it's making 156 00:07:39,760 --> 00:07:42,600 Speaker 4: us stupider, number or slower. I mean, since I've been 157 00:07:42,680 --> 00:07:45,120 Speaker 4: using it, I feel like my creativity is only exploded 158 00:07:45,480 --> 00:07:48,000 Speaker 4: in the way that I'm able to think about ideas 159 00:07:48,040 --> 00:07:50,760 Speaker 4: and the way that I'm able to quickly iterate on 160 00:07:50,880 --> 00:07:53,560 Speaker 4: ideas and then be like this is the best option, right, 161 00:07:53,600 --> 00:07:56,160 Speaker 4: Like I just think it's all about the way you 162 00:07:56,280 --> 00:07:59,680 Speaker 4: use it and depending on how they ran these tests, right, 163 00:08:00,120 --> 00:08:01,840 Speaker 4: what does that look like. Is it people that are 164 00:08:02,120 --> 00:08:04,080 Speaker 4: that know how to use chad GPT, Is it just 165 00:08:04,120 --> 00:08:06,280 Speaker 4: a bunch of students that have never learned right? 166 00:08:06,400 --> 00:08:09,160 Speaker 3: So I think there's always going to be this side 167 00:08:09,240 --> 00:08:10,920 Speaker 3: or that side of the coin when you look at it. 168 00:08:11,280 --> 00:08:13,200 Speaker 1: The other thing that I always tell folks is that 169 00:08:14,120 --> 00:08:17,440 Speaker 1: the tool is only as good as you are, Like 170 00:08:18,000 --> 00:08:20,360 Speaker 1: the analogy I always use because people are like, oh, no, 171 00:08:21,120 --> 00:08:22,200 Speaker 1: using AI is cheating. 172 00:08:22,320 --> 00:08:24,160 Speaker 2: All these undergrads are cheating. They're cheaters. 173 00:08:24,160 --> 00:08:26,800 Speaker 1: They're cheaters, they don't know anything, they're dumb, all these 174 00:08:26,840 --> 00:08:30,240 Speaker 1: things like that, And I'm like, listen, back when the 175 00:08:30,840 --> 00:08:35,760 Speaker 1: abacusts was made, mathematicians thought using an advocust was cheating. 176 00:08:36,200 --> 00:08:39,760 Speaker 1: When the calculator became a thing, they thought that that 177 00:08:39,960 --> 00:08:43,079 Speaker 1: was cheating. But the thing is is that the calculator 178 00:08:43,200 --> 00:08:45,880 Speaker 1: is only as good as the user. I can give 179 00:08:45,880 --> 00:08:50,320 Speaker 1: you a really advanced calculator and say, calculate the area 180 00:08:50,480 --> 00:08:53,480 Speaker 1: under this curve. If you don't know what to put 181 00:08:53,480 --> 00:08:56,240 Speaker 1: into the calculator, you won't get the right answer. You 182 00:08:56,240 --> 00:08:59,480 Speaker 1: can get an answer, it probably won't be right, and 183 00:08:59,600 --> 00:09:02,640 Speaker 1: so I always say, all of these AI tools are 184 00:09:02,800 --> 00:09:04,960 Speaker 1: only as good as the user. It'll only get you 185 00:09:05,040 --> 00:09:08,280 Speaker 1: but so far, which is the reason why when students 186 00:09:08,320 --> 00:09:11,040 Speaker 1: are using AI, it can only get them to a point, 187 00:09:11,120 --> 00:09:15,120 Speaker 1: and then their professors or teachers or whoever will ask 188 00:09:15,160 --> 00:09:18,160 Speaker 1: them for more, and that's when they have to start 189 00:09:18,360 --> 00:09:23,160 Speaker 1: really thinking critically and using it as an assist rather 190 00:09:23,280 --> 00:09:26,320 Speaker 1: than the only thing that they're using. As the only 191 00:09:26,360 --> 00:09:28,680 Speaker 1: tool that they're using, they have to use their brains. 192 00:09:29,200 --> 00:09:32,920 Speaker 4: Yeah, I totally agree, and I think you know, when 193 00:09:32,960 --> 00:09:35,160 Speaker 4: you look at the whole idea of like students and 194 00:09:35,200 --> 00:09:37,400 Speaker 4: the way that they're using it and whether it's cheating 195 00:09:37,480 --> 00:09:40,160 Speaker 4: or not, I think we also probably need to look 196 00:09:40,200 --> 00:09:43,880 Speaker 4: at like the way that teachers are evaluating students in 197 00:09:43,920 --> 00:09:46,200 Speaker 4: their work. So maybe it's less about what is the 198 00:09:46,200 --> 00:09:48,720 Speaker 4: final output, but like show me how you got to 199 00:09:48,760 --> 00:09:50,960 Speaker 4: this output, Like where what was the thinking? If the 200 00:09:51,000 --> 00:09:54,280 Speaker 4: technology is shifting, I think so needs to. 201 00:09:54,559 --> 00:09:58,000 Speaker 3: The way that we are teaching children how to use it. 202 00:09:57,960 --> 00:10:02,480 Speaker 1: Right, Men should definitely include assessing process, not just output. 203 00:10:04,200 --> 00:10:06,520 Speaker 1: That's what we think about for dope labs. It's like, yes, 204 00:10:06,559 --> 00:10:08,240 Speaker 1: I want you to know these facts, but i'd like 205 00:10:08,280 --> 00:10:10,440 Speaker 1: you to think about the string of questions that got 206 00:10:10,480 --> 00:10:12,240 Speaker 1: us here. We start with what we know, and then 207 00:10:12,280 --> 00:10:14,320 Speaker 1: what we want to know and what questions do we 208 00:10:14,360 --> 00:10:15,800 Speaker 1: ask to get to those answers? 209 00:10:16,240 --> 00:10:18,880 Speaker 3: And I think so many people don't know the questions 210 00:10:18,880 --> 00:10:19,200 Speaker 3: to ask. 211 00:10:19,320 --> 00:10:21,640 Speaker 4: This is what I tell people. Context is key. The 212 00:10:21,640 --> 00:10:24,880 Speaker 4: more context you give it, the better the output's going 213 00:10:24,960 --> 00:10:26,920 Speaker 4: to be because without any knowledge of what it is 214 00:10:26,960 --> 00:10:29,960 Speaker 4: they're actually trying to do or achieve, how is it 215 00:10:30,000 --> 00:10:33,360 Speaker 4: able to like know what you want and then also 216 00:10:33,480 --> 00:10:36,120 Speaker 4: being able to write a prompt that is actually going 217 00:10:36,160 --> 00:10:38,720 Speaker 4: to get you good stuff out of it. So never 218 00:10:38,880 --> 00:10:41,960 Speaker 4: taking something just and running with it on its own, 219 00:10:42,000 --> 00:10:44,560 Speaker 4: but always looking at it and evaluating it and saying, 220 00:10:44,880 --> 00:10:46,479 Speaker 4: is this what I actually. 221 00:10:46,080 --> 00:10:46,640 Speaker 3: Want out of it? 222 00:10:46,880 --> 00:10:49,120 Speaker 4: I think people look at AI and chat Gypts it's 223 00:10:49,120 --> 00:10:51,640 Speaker 4: like the scary techy thing, and it's not. It's all 224 00:10:51,640 --> 00:10:56,280 Speaker 4: about communication. If like, I think teachers and journalists those 225 00:10:56,320 --> 00:10:58,040 Speaker 4: are the people that are going to be using these 226 00:10:58,040 --> 00:11:00,200 Speaker 4: tools the best because they already know how to like 227 00:11:00,640 --> 00:11:03,360 Speaker 4: communicate properly right and ask questions well. 228 00:11:03,400 --> 00:11:05,840 Speaker 3: And I think that's so much about what this is. 229 00:11:05,880 --> 00:11:08,680 Speaker 4: And if you are, like I said, a domain expert 230 00:11:08,760 --> 00:11:11,600 Speaker 4: in what you do. Then you're gonna know those questions 231 00:11:11,600 --> 00:11:11,920 Speaker 4: to ask. 232 00:11:11,960 --> 00:11:12,600 Speaker 3: You're gonna know. 233 00:11:12,559 --> 00:11:14,600 Speaker 4: When something's wrong, and you're gonna be like that sounds 234 00:11:15,120 --> 00:11:16,000 Speaker 4: like a terrible idea. 235 00:11:16,120 --> 00:11:16,840 Speaker 3: Let's not do that. 236 00:11:16,920 --> 00:11:19,760 Speaker 4: Why did you give me that idea? So it is 237 00:11:19,840 --> 00:11:21,760 Speaker 4: all about that, like back and forth with it. 238 00:11:22,040 --> 00:11:40,640 Speaker 1: Yeah, what are your go to AI tools? Folks are 239 00:11:40,720 --> 00:11:43,319 Speaker 1: always talking about Chat GBT, but there's so much more. 240 00:11:43,360 --> 00:11:44,360 Speaker 2: Can you talk about those? 241 00:11:44,559 --> 00:11:48,440 Speaker 3: Yeah? So Chat, I would say, Chat is my like 242 00:11:48,600 --> 00:11:50,040 Speaker 3: go to right now. 243 00:11:50,320 --> 00:11:54,440 Speaker 4: We are in a place where stuff moves so fast, right, yes, 244 00:11:54,520 --> 00:11:58,760 Speaker 4: but right now, Chat has deep research that is so good. 245 00:11:58,880 --> 00:12:01,880 Speaker 4: It has image general that is so good. It has 246 00:12:01,960 --> 00:12:05,560 Speaker 4: these three advanced reasoning models that are like next level. 247 00:12:05,840 --> 00:12:07,959 Speaker 4: I'm not on the free plan. I'm also not on 248 00:12:08,000 --> 00:12:09,920 Speaker 4: the Plus plan. I'm on the Pro plan. I'm paying 249 00:12:09,920 --> 00:12:11,720 Speaker 4: two hundred dollars a month for this thing, which is 250 00:12:11,840 --> 00:12:14,720 Speaker 4: insane to me. I remember saying when I was paying 251 00:12:14,760 --> 00:12:16,160 Speaker 4: the twenty dollars a month that I would pay tw 252 00:12:16,200 --> 00:12:17,760 Speaker 4: hundred dollars a month for this, and I was like, no, 253 00:12:17,840 --> 00:12:20,959 Speaker 4: I wouldn't. But now I'm like, absolutely I would. Because 254 00:12:21,280 --> 00:12:25,480 Speaker 4: with the Pro subscription you're getting almost unlimited messages. On 255 00:12:25,559 --> 00:12:28,839 Speaker 4: all of the models, and these advanced reasoning models are 256 00:12:28,920 --> 00:12:30,480 Speaker 4: like next. 257 00:12:30,280 --> 00:12:31,520 Speaker 3: Level what they can be doing. 258 00:12:31,600 --> 00:12:34,280 Speaker 4: I mean filling in for what you'd be paying five 259 00:12:34,760 --> 00:12:38,040 Speaker 4: ten thousand, fifty thousand dollars to a consultancy to do 260 00:12:38,559 --> 00:12:40,560 Speaker 4: that you can run and do in an hour on 261 00:12:40,600 --> 00:12:43,600 Speaker 4: your own, Like it's it's crazy. So Chat, I do 262 00:12:43,720 --> 00:12:48,000 Speaker 4: think is a really great option. You've obviously got Gemini 263 00:12:48,080 --> 00:12:52,199 Speaker 4: from Google, which I if you follow me on Instagram. 264 00:12:52,200 --> 00:12:53,080 Speaker 3: A while back. 265 00:12:53,240 --> 00:12:57,320 Speaker 4: I used to just I hated Gemini anything for the 266 00:12:57,320 --> 00:12:58,560 Speaker 4: Gemini the time. 267 00:12:58,720 --> 00:13:01,840 Speaker 3: It's just like it's so bad, Like it's so bad. 268 00:13:01,880 --> 00:13:04,320 Speaker 4: And now I'm like, no, dude, it is good, and 269 00:13:04,400 --> 00:13:07,600 Speaker 4: like their video model is so good. I had like 270 00:13:07,679 --> 00:13:10,079 Speaker 4: a moment a couple of weeks ago when it came 271 00:13:10,120 --> 00:13:13,000 Speaker 4: out where I was just like, Okay, maybe I'm a 272 00:13:13,200 --> 00:13:17,160 Speaker 4: little bit nervous about this because it's creating these videos 273 00:13:17,160 --> 00:13:18,760 Speaker 4: that are so lifelike. 274 00:13:18,480 --> 00:13:19,559 Speaker 3: With native sound. 275 00:13:19,720 --> 00:13:23,160 Speaker 4: And that's scary is you've got voice that matches lips 276 00:13:23,160 --> 00:13:26,199 Speaker 4: that matches something that's totally fake and someone can just 277 00:13:26,240 --> 00:13:27,720 Speaker 4: put in any text. 278 00:13:27,440 --> 00:13:28,400 Speaker 3: They want for it to say. 279 00:13:28,480 --> 00:13:31,840 Speaker 4: So like, the video models are getting really really good, 280 00:13:32,160 --> 00:13:36,880 Speaker 4: and then Anthropic has Claude, the brother and sister that 281 00:13:36,920 --> 00:13:41,000 Speaker 4: founded Anthropic, actually started at open Ai with Sam Alman 282 00:13:41,120 --> 00:13:43,600 Speaker 4: with Elon Musk. They left and they were like, we're 283 00:13:43,600 --> 00:13:45,439 Speaker 4: gonna go and create. 284 00:13:45,160 --> 00:13:46,280 Speaker 3: A safer AI. 285 00:13:46,440 --> 00:13:50,280 Speaker 4: So there's a lot more like guardrails around Anthropic and Claude. 286 00:13:50,320 --> 00:13:53,360 Speaker 4: But it's so good at creative writing. It's so good 287 00:13:53,360 --> 00:13:56,600 Speaker 4: at creative writing, so it's real, and it's good at code. 288 00:13:56,400 --> 00:13:58,880 Speaker 3: Right, But the problem there in lies that they all 289 00:13:58,920 --> 00:14:01,280 Speaker 3: freaking leap froggy every week. 290 00:14:01,600 --> 00:14:03,439 Speaker 4: So it's like this is the best one and now 291 00:14:03,520 --> 00:14:05,640 Speaker 4: this is the best one, and it's like I can't 292 00:14:05,720 --> 00:14:09,320 Speaker 4: keep up. But Anthropic, Open Ai and Google are going 293 00:14:09,360 --> 00:14:12,880 Speaker 4: to be remain for like large language models and then imagery. 294 00:14:13,480 --> 00:14:14,360 Speaker 3: I love mid Journey. 295 00:14:14,400 --> 00:14:17,400 Speaker 4: They just came out with video last week and it's 296 00:14:17,559 --> 00:14:18,400 Speaker 4: really really good. 297 00:14:18,440 --> 00:14:20,200 Speaker 3: I was not expecting it to be good. 298 00:14:20,360 --> 00:14:23,520 Speaker 4: They've got a bunch of new stuff with like omni reference, 299 00:14:23,600 --> 00:14:26,680 Speaker 4: so being able to you know, take your company's product, 300 00:14:27,120 --> 00:14:29,880 Speaker 4: take a shot of it on your counter, bring that 301 00:14:30,000 --> 00:14:31,800 Speaker 4: in and have it reference it and be able to 302 00:14:31,800 --> 00:14:35,120 Speaker 4: get it really close and then turn that into video, right, 303 00:14:35,160 --> 00:14:38,600 Speaker 4: And it's just like so like what you can do 304 00:14:38,640 --> 00:14:41,520 Speaker 4: now is so crazy, But those I think would probably 305 00:14:41,600 --> 00:14:47,080 Speaker 4: might be my my, Well, I have one more, okay, okay, 306 00:14:47,440 --> 00:14:51,000 Speaker 4: So and it just opened in beta like recently to everyone. 307 00:14:51,040 --> 00:14:52,880 Speaker 3: I've been using it in alpha for a long time. 308 00:14:52,960 --> 00:14:57,160 Speaker 4: It's called da and it's a browser, so it's from 309 00:14:57,280 --> 00:15:00,760 Speaker 4: the browser company. They have another browser are called Arc, 310 00:15:01,320 --> 00:15:07,160 Speaker 4: but Dia is an AI browser. So basically on any 311 00:15:07,240 --> 00:15:10,840 Speaker 4: website that I'm on, that is the context. So I 312 00:15:10,880 --> 00:15:13,360 Speaker 4: could just open up a chat and be like, hey, 313 00:15:13,400 --> 00:15:15,720 Speaker 4: can you tell me x y z and it'll just 314 00:15:15,840 --> 00:15:18,040 Speaker 4: take everything on there, or a YouTube video you can 315 00:15:18,080 --> 00:15:19,560 Speaker 4: be like, can you summarize. 316 00:15:19,040 --> 00:15:19,840 Speaker 3: This YouTube video? 317 00:15:20,040 --> 00:15:22,080 Speaker 4: So say I'm like planning a trip right and I've 318 00:15:22,080 --> 00:15:25,160 Speaker 4: got like six different Airbnb tabs open. I just tag 319 00:15:25,240 --> 00:15:26,520 Speaker 4: in all of them and say, can you create a 320 00:15:26,520 --> 00:15:29,080 Speaker 4: comparison chart for me for this? Give me the pros 321 00:15:29,120 --> 00:15:30,520 Speaker 4: and cons, like whatever it. 322 00:15:30,520 --> 00:15:34,840 Speaker 3: Is, but no more switching taps. Yes, it is so and. 323 00:15:34,800 --> 00:15:37,760 Speaker 4: It's so good because it's running GBT four point one 324 00:15:37,840 --> 00:15:40,480 Speaker 4: on the back end, so it's it's quick and it 325 00:15:40,640 --> 00:15:43,000 Speaker 4: just came out and beta like a week and a 326 00:15:43,000 --> 00:15:44,240 Speaker 4: half ago, two weeks ago. 327 00:15:44,360 --> 00:15:47,240 Speaker 1: So the way you felt about what was it, The 328 00:15:47,240 --> 00:15:48,920 Speaker 1: way that you didn't like Gemini Ja. The way you 329 00:15:48,960 --> 00:15:51,400 Speaker 1: felt about it is the way I currently feel about Copilot. 330 00:15:52,200 --> 00:15:54,760 Speaker 3: I never even tried. I mean I used Copilot for 331 00:15:54,800 --> 00:15:55,880 Speaker 3: like two days. 332 00:15:55,760 --> 00:15:57,720 Speaker 4: But that was It's I don't know Windows, they don't 333 00:15:57,760 --> 00:15:59,080 Speaker 4: know Microsoft, they don't know any of it. 334 00:15:59,120 --> 00:16:02,760 Speaker 1: I'm like, it's from such a waste of time. Love Claude, though, 335 00:16:03,000 --> 00:16:03,600 Speaker 1: Love Claude. 336 00:16:03,760 --> 00:16:07,680 Speaker 4: Okay, speaking of though, Google, Notebook LM is another. 337 00:16:07,840 --> 00:16:13,280 Speaker 2: Really Notebook LM is good, so good. 338 00:16:13,320 --> 00:16:14,320 Speaker 1: I haven't tell you my. 339 00:16:14,360 --> 00:16:15,640 Speaker 2: Notebook LM story. 340 00:16:16,200 --> 00:16:20,320 Speaker 1: Tell it. At work, my supervisor, we were we were 341 00:16:20,320 --> 00:16:21,800 Speaker 1: doing we had an off site, so were doing all 342 00:16:21,800 --> 00:16:22,240 Speaker 1: this stuff. 343 00:16:22,280 --> 00:16:24,640 Speaker 2: And this is part of my next question. 344 00:16:25,600 --> 00:16:28,560 Speaker 1: A lot of industries are now making it so that 345 00:16:28,640 --> 00:16:30,760 Speaker 1: everybody that works in their company knows how to use 346 00:16:30,800 --> 00:16:32,960 Speaker 1: AI and knows how to use it effectively. So we 347 00:16:32,960 --> 00:16:35,400 Speaker 1: were doing these kind of like experiments where we were 348 00:16:35,480 --> 00:16:39,520 Speaker 1: using AI to build certain things, and we used Notebook 349 00:16:39,640 --> 00:16:42,400 Speaker 1: LM to create a podcast, and do you know, we 350 00:16:42,640 --> 00:16:46,720 Speaker 1: uploaded what the input was a picture of something that 351 00:16:46,760 --> 00:16:50,240 Speaker 1: he drew on this whiteboard in his handwriting. It's like 352 00:16:50,520 --> 00:16:52,880 Speaker 1: chopped up words, and it just like kind of showed 353 00:16:52,920 --> 00:16:56,160 Speaker 1: like the this ecosystem that we were trying to create 354 00:16:56,640 --> 00:17:01,320 Speaker 1: and Notebook LM took it and made like a twenty 355 00:17:01,400 --> 00:17:04,520 Speaker 1: five minute podcast and it was spot on. There were 356 00:17:04,520 --> 00:17:08,800 Speaker 1: two hosts, it was crystal clear, everything made sense. 357 00:17:08,800 --> 00:17:13,000 Speaker 2: I was like, we barely gave it anything. It was amazing. 358 00:17:13,440 --> 00:17:14,200 Speaker 3: It's nuts. 359 00:17:14,320 --> 00:17:18,320 Speaker 4: It's nuts, and what's even crazier now, So like for 360 00:17:18,400 --> 00:17:20,840 Speaker 4: anyone listening, basically what you can do is you can 361 00:17:20,920 --> 00:17:24,240 Speaker 4: give notebook LM, which is a Google product. You can 362 00:17:24,280 --> 00:17:26,119 Speaker 4: give it sources. So I could just like go to 363 00:17:26,200 --> 00:17:28,960 Speaker 4: like five different websites and be like use these as sources. 364 00:17:29,040 --> 00:17:31,720 Speaker 4: Or I could upload a transcript, or I could upload 365 00:17:31,880 --> 00:17:36,000 Speaker 4: I actually had chatgybt do a deep research on myself 366 00:17:36,119 --> 00:17:39,400 Speaker 4: and my brand, fed it that and then it basically 367 00:17:39,560 --> 00:17:42,320 Speaker 4: was a podcast of two people talking about me. And 368 00:17:42,359 --> 00:17:45,480 Speaker 4: I was like, this is so like weird, meta, narcissistic, 369 00:17:45,600 --> 00:17:50,200 Speaker 4: but also like amazing, Like this is so crazy because 370 00:17:51,359 --> 00:17:55,080 Speaker 4: now they've introduced like the like live version, so like 371 00:17:55,160 --> 00:17:58,600 Speaker 4: basically they can be having their conversation and you can 372 00:17:58,640 --> 00:17:59,919 Speaker 4: be like I want to raise my hand and as 373 00:18:00,160 --> 00:18:02,960 Speaker 4: a question and they'll it'll respond to you. 374 00:18:03,119 --> 00:18:04,080 Speaker 2: It's oh my. 375 00:18:03,960 --> 00:18:06,480 Speaker 3: God, it's so crazy. It's so crazy. 376 00:18:06,640 --> 00:18:09,919 Speaker 4: There's so many, so many tools though too that you 377 00:18:09,920 --> 00:18:12,120 Speaker 4: can clone your voice, which is a little bit scary. 378 00:18:12,720 --> 00:18:15,800 Speaker 4: As just like a quick aside. I think everyone and 379 00:18:15,880 --> 00:18:18,520 Speaker 4: your family should have like a safe word now, so 380 00:18:18,520 --> 00:18:20,560 Speaker 4: that like if you're getting phone calls from someone and 381 00:18:20,600 --> 00:18:22,320 Speaker 4: it sounds a little bit weird and you're. 382 00:18:22,160 --> 00:18:23,320 Speaker 3: Like, is this really? 383 00:18:23,320 --> 00:18:25,520 Speaker 4: Then oh, you know, we have this because this is 384 00:18:25,520 --> 00:18:28,440 Speaker 4: what's happening is people are like scammed. And so if 385 00:18:28,480 --> 00:18:30,280 Speaker 4: you have a word that you can say, hey, what's 386 00:18:30,280 --> 00:18:32,560 Speaker 4: the safe word or whatever, and they don't know what 387 00:18:32,640 --> 00:18:35,760 Speaker 4: that word is, then like they're probably not that person, right, 388 00:18:35,840 --> 00:18:39,200 Speaker 4: So just something to think about as a weird world. 389 00:18:39,560 --> 00:18:44,720 Speaker 1: Yeah, thinking about recreating voices, how about recreating your own persona? 390 00:18:45,280 --> 00:18:47,960 Speaker 1: I tried out hey Jin, which is a generative AI 391 00:18:48,080 --> 00:18:51,840 Speaker 1: tool that lets you make avatars of yourself. Now I 392 00:18:51,960 --> 00:18:56,119 Speaker 1: wasn't sold, but I'm curious, Laura, what's your go to 393 00:18:56,359 --> 00:18:58,360 Speaker 1: for this sort of thing? Do you make a videos 394 00:18:58,359 --> 00:18:58,920 Speaker 1: of yourself? 395 00:18:59,359 --> 00:19:02,840 Speaker 4: So I've like messed around with it a little bit, 396 00:19:02,920 --> 00:19:05,680 Speaker 4: Like when it first came out, I made a real 397 00:19:05,840 --> 00:19:09,320 Speaker 4: that wasn't actually me. But I don't do it a 398 00:19:09,320 --> 00:19:11,600 Speaker 4: lot because here's my kind of thought on it. 399 00:19:12,560 --> 00:19:15,880 Speaker 3: In with all of the AI happening. 400 00:19:16,080 --> 00:19:21,120 Speaker 4: People are really looking for personality and want to connect 401 00:19:21,200 --> 00:19:24,800 Speaker 4: with people still, So if the concept that I'm creating 402 00:19:24,840 --> 00:19:28,360 Speaker 4: on my stories is a fake version of me, then 403 00:19:28,400 --> 00:19:31,080 Speaker 4: it's like, well, where do I actually come in there? 404 00:19:31,160 --> 00:19:32,080 Speaker 3: Right, And like, I get it. 405 00:19:32,119 --> 00:19:34,399 Speaker 4: There are plenty of people that want to have this, 406 00:19:34,600 --> 00:19:37,600 Speaker 4: and like I'm all about like creating a custom GBT 407 00:19:37,760 --> 00:19:39,840 Speaker 4: that's maybe trained on your knowledge and trained on your 408 00:19:39,880 --> 00:19:41,960 Speaker 4: IP that people can go and chat with and like 409 00:19:42,000 --> 00:19:45,160 Speaker 4: be able to like learn from. But I just don't 410 00:19:45,200 --> 00:19:48,360 Speaker 4: really see the value in terms of like using it 411 00:19:48,440 --> 00:19:51,119 Speaker 4: to create I mean, there's plenty of creators that are 412 00:19:51,480 --> 00:19:54,239 Speaker 4: doing it and their videos are going viral and like 413 00:19:54,359 --> 00:19:56,840 Speaker 4: it works for them, But for me, it just seems 414 00:19:56,880 --> 00:19:58,919 Speaker 4: like just as much work for me to like go 415 00:19:58,960 --> 00:20:00,880 Speaker 4: and type out what I want to say and then 416 00:20:00,920 --> 00:20:03,760 Speaker 4: go and generate it. Where I'm like, I don't really 417 00:20:03,800 --> 00:20:08,160 Speaker 4: have much of a. 418 00:20:06,320 --> 00:20:08,320 Speaker 3: Strategy when it comes to my social media. 419 00:20:08,440 --> 00:20:10,840 Speaker 4: When I have an idea, I will make the real 420 00:20:11,000 --> 00:20:13,320 Speaker 4: and I will post it right then, and like that's it. 421 00:20:13,520 --> 00:20:15,320 Speaker 3: So for me, I'm happy to just. 422 00:20:15,280 --> 00:20:18,560 Speaker 4: Pull up and start talking and post rather than going 423 00:20:18,600 --> 00:20:21,520 Speaker 4: and having a fake version of myself do that. But 424 00:20:22,160 --> 00:20:24,880 Speaker 4: I don't there are use cases for everything, right, So 425 00:20:25,400 --> 00:20:27,200 Speaker 4: maybe it's on your sales page and you want to 426 00:20:27,240 --> 00:20:30,480 Speaker 4: have like a little version of yourself down there answering questions, 427 00:20:30,520 --> 00:20:33,679 Speaker 4: so whatever. But I would think I think Hagen is 428 00:20:33,720 --> 00:20:40,040 Speaker 4: probably the leading version tool for that. I've used phish 429 00:20:40,200 --> 00:20:44,800 Speaker 4: dot ai for audio cloning just because I had heard 430 00:20:44,800 --> 00:20:47,439 Speaker 4: about it and it was different than eleven Labs. I know, 431 00:20:47,480 --> 00:20:49,600 Speaker 4: eleven Labs just came out with something. But this is 432 00:20:49,600 --> 00:20:53,440 Speaker 4: what's so wild is there are so many tools for everything, 433 00:20:53,560 --> 00:20:55,879 Speaker 4: and it's it's really hard to keep up, especially when 434 00:20:55,920 --> 00:20:57,359 Speaker 4: you have to pay for all of them to like 435 00:20:57,400 --> 00:20:58,240 Speaker 4: even test them. 436 00:20:58,320 --> 00:20:58,560 Speaker 3: Right. 437 00:20:58,680 --> 00:21:03,080 Speaker 4: So yeah, I'm kind I'm entering this like version of 438 00:21:03,119 --> 00:21:04,359 Speaker 4: myself that I'm. 439 00:21:04,200 --> 00:21:06,560 Speaker 3: Like, Okay, Lauren, you need to like just focus because 440 00:21:06,680 --> 00:21:09,400 Speaker 3: if I try and be the A on two to everything, right, 441 00:21:09,480 --> 00:21:10,640 Speaker 3: it's like I. 442 00:21:10,640 --> 00:21:13,160 Speaker 4: Truly like the last two months, I've kind of just 443 00:21:13,200 --> 00:21:16,159 Speaker 4: like taken a step back because it's so much and 444 00:21:16,240 --> 00:21:17,960 Speaker 4: especially with everything going on in the world, it's just 445 00:21:18,000 --> 00:21:19,760 Speaker 4: like to try and keep up with all of it, 446 00:21:20,400 --> 00:21:22,960 Speaker 4: and it's just too hard. So I'm like, I gotta 447 00:21:23,400 --> 00:21:26,120 Speaker 4: I gotta pick like one or two or three and 448 00:21:26,160 --> 00:21:29,400 Speaker 4: focus and like because I am, you know, a creative 449 00:21:29,400 --> 00:21:32,600 Speaker 4: director and a designer, and that's kind of my world. 450 00:21:32,720 --> 00:21:34,679 Speaker 4: I think that's where it's gonna kind of end up 451 00:21:34,760 --> 00:21:37,360 Speaker 4: living and landing. But it's just hard for me because 452 00:21:37,359 --> 00:21:38,960 Speaker 4: I have ADHD and I want to you know, I 453 00:21:39,320 --> 00:21:41,280 Speaker 4: want to help everyone because I see the value and 454 00:21:41,320 --> 00:21:44,080 Speaker 4: what it can do for everyone, and so I'm like, oh. 455 00:21:43,960 --> 00:21:46,320 Speaker 3: But what if, like what about these people, what about. 456 00:21:46,119 --> 00:21:48,440 Speaker 4: The marketers or what about these people? And it's like, yes, 457 00:21:48,960 --> 00:21:51,160 Speaker 4: it can help everyone, but I I gotta like figure 458 00:21:51,200 --> 00:21:52,879 Speaker 4: out how to like keep it on, keep it on 459 00:21:52,920 --> 00:21:54,680 Speaker 4: the tracks, otherwise I'm gonna end. 460 00:21:54,640 --> 00:21:57,439 Speaker 3: Up off the tracks because it's just so crazy. 461 00:21:57,520 --> 00:22:09,760 Speaker 5: Right now. 462 00:22:12,760 --> 00:22:14,800 Speaker 1: You're bringing up so many good points, which is making 463 00:22:14,840 --> 00:22:17,560 Speaker 1: my head like grow bigger and bigger with all these questions. 464 00:22:18,200 --> 00:22:21,240 Speaker 1: Like I mentioned before, it seems like now jobs are 465 00:22:21,240 --> 00:22:23,879 Speaker 1: expecting you to know how to use AI when you 466 00:22:23,920 --> 00:22:27,920 Speaker 1: start the job. So Morgan Debaum, she's the CEO of Blavity, 467 00:22:27,960 --> 00:22:31,240 Speaker 1: and she created her own GPT so that her assistance 468 00:22:31,640 --> 00:22:35,600 Speaker 1: can write emails. They can do a lot of things 469 00:22:35,640 --> 00:22:38,360 Speaker 1: for her because they just prompt her GPT, which has 470 00:22:38,720 --> 00:22:42,320 Speaker 1: basically her brain, and they can do things for her 471 00:22:42,760 --> 00:22:45,920 Speaker 1: and those are the types of skills that folks want 472 00:22:46,000 --> 00:22:49,320 Speaker 1: you to have. But the fear is is that people 473 00:22:49,320 --> 00:22:51,000 Speaker 1: are like, oh, I'm going to lose my job. There's 474 00:22:51,000 --> 00:22:52,479 Speaker 1: not going to be jobs. All the jobs are going 475 00:22:52,520 --> 00:22:55,639 Speaker 1: to be AI. Can you talk about the future and 476 00:22:55,680 --> 00:22:59,680 Speaker 1: what that might look like and like technology that you 477 00:22:59,680 --> 00:23:02,080 Speaker 1: feel like going to change the game and how people 478 00:23:02,160 --> 00:23:06,119 Speaker 1: can navigate these new AI waters for sure? 479 00:23:06,320 --> 00:23:09,760 Speaker 4: And actually, funny story, uh Morgan, I actually did branding 480 00:23:09,800 --> 00:23:10,680 Speaker 4: for her Maacha brand. 481 00:23:10,840 --> 00:23:14,639 Speaker 2: Oh my god, that's amazing. 482 00:23:14,760 --> 00:23:16,760 Speaker 4: A little bit of a full circle there, But no, 483 00:23:17,040 --> 00:23:20,720 Speaker 4: I think that you know, I get it. I understand 484 00:23:20,720 --> 00:23:23,199 Speaker 4: why people are nervous about it, and I understand that 485 00:23:23,240 --> 00:23:25,920 Speaker 4: there is this fear, but I also think that that's 486 00:23:26,000 --> 00:23:29,679 Speaker 4: kind of been what has happened forever. Right, So, like 487 00:23:30,200 --> 00:23:32,879 Speaker 4: you gave the calculator example, but if we look at 488 00:23:32,880 --> 00:23:33,680 Speaker 4: the example of. 489 00:23:33,600 --> 00:23:35,879 Speaker 3: Like in the creative space. 490 00:23:35,960 --> 00:23:39,080 Speaker 4: Okay, so we had people that were like painting portraits, right, 491 00:23:39,160 --> 00:23:41,280 Speaker 4: and then the camera came along and I was. 492 00:23:41,280 --> 00:23:43,680 Speaker 3: Like, well, we don't want to sit for a portrait 493 00:23:43,720 --> 00:23:47,400 Speaker 3: for eight hours. We want the goal of technology generally 494 00:23:47,480 --> 00:23:48,120 Speaker 3: is to get. 495 00:23:47,960 --> 00:23:51,000 Speaker 4: Things done faster whenever. Right, So Okay, now we've got 496 00:23:51,040 --> 00:23:52,960 Speaker 4: film photography. Yeah, you still got to sit there for 497 00:23:52,960 --> 00:23:54,920 Speaker 4: a while when it first came out because it takes 498 00:23:54,960 --> 00:23:56,000 Speaker 4: a while for that to work. 499 00:23:56,280 --> 00:23:57,280 Speaker 3: But then okay, now. 500 00:23:57,119 --> 00:23:59,479 Speaker 4: We're getting into like better cameras and it's quick clicking, 501 00:23:59,520 --> 00:24:01,640 Speaker 4: push and boom and we're done. But now we've got 502 00:24:01,680 --> 00:24:03,760 Speaker 4: digital cameras, right, So what happens to all of those 503 00:24:03,760 --> 00:24:06,080 Speaker 4: people that are working at like the film processing plans 504 00:24:06,480 --> 00:24:08,719 Speaker 4: or building cameras that are not digital? 505 00:24:08,800 --> 00:24:12,040 Speaker 3: Right, those are going to change. And now we've got photoshop. 506 00:24:12,080 --> 00:24:14,840 Speaker 4: But now we have a company like Adobe, right, So 507 00:24:14,920 --> 00:24:16,640 Speaker 4: like where did all those jobs come from? 508 00:24:16,680 --> 00:24:18,639 Speaker 3: So I truly. 509 00:24:18,320 --> 00:24:21,600 Speaker 4: Believe that it's all about like we have to evolve 510 00:24:21,640 --> 00:24:24,439 Speaker 4: and we Yet just because you had one job and 511 00:24:24,480 --> 00:24:27,159 Speaker 4: that's what you learn doesn't mean that that's just that's 512 00:24:27,760 --> 00:24:28,440 Speaker 4: that's life. 513 00:24:28,280 --> 00:24:29,960 Speaker 3: And that's what you get to do forever. And I 514 00:24:30,040 --> 00:24:30,960 Speaker 3: know that maybe. 515 00:24:30,720 --> 00:24:33,199 Speaker 4: Comes across a little bit like privileged. But at the 516 00:24:33,240 --> 00:24:35,600 Speaker 4: same time as if you want to stay ahead, it's 517 00:24:35,760 --> 00:24:37,679 Speaker 4: going to be on you to make sure that you 518 00:24:37,960 --> 00:24:41,480 Speaker 4: are evolving with the technology and changing with the technology 519 00:24:41,920 --> 00:24:45,400 Speaker 4: and shifting how what your role even is. Right now 520 00:24:45,440 --> 00:24:48,159 Speaker 4: you can offer you know, these other things that you 521 00:24:48,200 --> 00:24:50,400 Speaker 4: couldn't offer or now you can say, hey, I can 522 00:24:50,440 --> 00:24:53,320 Speaker 4: give you five different ideas in the same amount of time, 523 00:24:53,920 --> 00:24:56,520 Speaker 4: or I can not give you five ideas, but now 524 00:24:56,560 --> 00:24:59,320 Speaker 4: I can spend more time on your project because I'm 525 00:24:59,320 --> 00:25:01,199 Speaker 4: taking less time I'm on the upfront to come up 526 00:25:01,200 --> 00:25:01,840 Speaker 4: with the ideas. 527 00:25:01,920 --> 00:25:03,520 Speaker 3: Right, So it's all about. 528 00:25:03,280 --> 00:25:08,040 Speaker 4: Kind of shifting how you're bringing AI into your like 529 00:25:08,160 --> 00:25:12,240 Speaker 4: workflows and understanding Okay, because like for me, like I said, 530 00:25:12,280 --> 00:25:14,679 Speaker 4: I have ADHD, so a lot of it's there's a 531 00:25:14,680 --> 00:25:16,640 Speaker 4: lot of people out there that preach, Okay, I'm gonna 532 00:25:16,640 --> 00:25:18,240 Speaker 4: teach you how to use AI to save. 533 00:25:18,160 --> 00:25:20,240 Speaker 3: You, you know, twenty hours a week. 534 00:25:20,480 --> 00:25:22,400 Speaker 4: That is not what I pre I don't tell people 535 00:25:22,400 --> 00:25:25,240 Speaker 4: I'm gonna save them time because for me, just because 536 00:25:25,240 --> 00:25:28,120 Speaker 4: I'm using AI doesn't mean that I'm spending less time 537 00:25:28,160 --> 00:25:31,560 Speaker 4: on something. It just means that I'm spending different time 538 00:25:31,680 --> 00:25:35,720 Speaker 4: on different things, I would say, right, So it's more 539 00:25:35,720 --> 00:25:38,400 Speaker 4: about like I'm using it as like this creative lever, 540 00:25:38,520 --> 00:25:42,160 Speaker 4: whereas other people are using it as this like automation lever, 541 00:25:42,560 --> 00:25:44,560 Speaker 4: and some other people are using it as like a 542 00:25:44,600 --> 00:25:47,160 Speaker 4: time saving lever or all of the things combined. 543 00:25:47,200 --> 00:25:50,760 Speaker 3: But I do, I really do think that it's up 544 00:25:50,800 --> 00:25:51,920 Speaker 3: to everyone. 545 00:25:51,560 --> 00:25:54,760 Speaker 4: To make the determination of like, Okay, I know I 546 00:25:54,840 --> 00:25:56,879 Speaker 4: need to learn how to use AI. I know, like 547 00:25:56,920 --> 00:25:59,080 Speaker 4: and if if they don't want to learn to use AI, 548 00:25:59,200 --> 00:26:02,480 Speaker 4: then that's their decision. But I just I don't see 549 00:26:02,480 --> 00:26:06,359 Speaker 4: the value of ignoring something as large as what we 550 00:26:06,480 --> 00:26:09,680 Speaker 4: have here, Bigger than the Internet, was bigger than all 551 00:26:09,720 --> 00:26:11,600 Speaker 4: of these things that, Like, if you look at somebody 552 00:26:11,680 --> 00:26:13,040 Speaker 4: that said, oh, yeah, I don't you know, I don't 553 00:26:13,080 --> 00:26:15,479 Speaker 4: need a website for my business, and you'd be like, we, well, 554 00:26:15,960 --> 00:26:18,480 Speaker 4: good luck out there, right, And it's like, what do 555 00:26:18,560 --> 00:26:22,120 Speaker 4: you think is gonna happen when all of your competitors 556 00:26:22,200 --> 00:26:28,600 Speaker 4: are adopting AI and can offer your potential clients stuff faster, stuff, cheaper, 557 00:26:28,640 --> 00:26:32,120 Speaker 4: whatever it is because they are using this tools yeah, 558 00:26:32,240 --> 00:26:33,080 Speaker 4: or better. 559 00:26:32,920 --> 00:26:35,600 Speaker 3: Yes, because we have a better idea exactly. 560 00:26:36,080 --> 00:26:38,440 Speaker 4: And if I can go and say, oh, yeah, sure, 561 00:26:38,440 --> 00:26:40,480 Speaker 4: I'm going to run an entire deep dive on your brand, 562 00:26:40,480 --> 00:26:42,359 Speaker 4: I'm gonna be able to tell you exactly. 563 00:26:42,040 --> 00:26:43,000 Speaker 3: Who your audience is. 564 00:26:43,280 --> 00:26:44,920 Speaker 4: If you don't know who your audience is, We're gonna 565 00:26:44,920 --> 00:26:47,760 Speaker 4: figure out who your audience is based on all of this. Like, 566 00:26:48,000 --> 00:26:51,760 Speaker 4: there's just so much more value when you're using it 567 00:26:51,800 --> 00:26:56,000 Speaker 4: properly that you can provide to customers and clients that like, 568 00:26:56,840 --> 00:26:59,720 Speaker 4: you know, I do I It's it makes me nervous 569 00:26:59,720 --> 00:27:02,840 Speaker 4: for peop that don't want to even at least try 570 00:27:02,960 --> 00:27:06,720 Speaker 4: because they think it is cheating, or they think it's stealing, 571 00:27:06,840 --> 00:27:08,840 Speaker 4: or they think it's whatever they think it is. But 572 00:27:09,359 --> 00:27:12,720 Speaker 4: it's almost like somebody, you know, giving a restaurant like 573 00:27:12,760 --> 00:27:14,240 Speaker 4: a one star review and they've never. 574 00:27:14,119 --> 00:27:14,879 Speaker 3: Even been inside. 575 00:27:14,920 --> 00:27:18,520 Speaker 4: It's like, how can you make that determination when you 576 00:27:18,640 --> 00:27:20,639 Speaker 4: really like, maybe you played with it twice and you 577 00:27:20,640 --> 00:27:22,280 Speaker 4: didn't know what you were doing and so it gave 578 00:27:22,280 --> 00:27:24,280 Speaker 4: you a bad answer, and now you've written it off 579 00:27:24,320 --> 00:27:27,560 Speaker 4: and it's like, all right, well okay, I don't know. 580 00:27:27,720 --> 00:27:31,439 Speaker 4: I just I'm so I feel so strongly that it 581 00:27:31,560 --> 00:27:37,160 Speaker 4: is going to change the course of everything that if 582 00:27:37,200 --> 00:27:40,840 Speaker 4: you don't understand it, you are not in a driver's 583 00:27:40,880 --> 00:27:44,200 Speaker 4: seat position anymore. You are following everyone else and you're 584 00:27:44,240 --> 00:27:47,800 Speaker 4: hoping that you can understand what's going on. But so 585 00:27:47,840 --> 00:27:50,320 Speaker 4: it's like, just start learning now so that it can 586 00:27:50,400 --> 00:27:52,400 Speaker 4: get easier, rather than you jump in and you're like. 587 00:27:52,359 --> 00:27:54,040 Speaker 3: What is all this? You know? 588 00:27:54,359 --> 00:27:57,480 Speaker 1: Yeah, I think that's so great. Recently, TC I don't 589 00:27:57,480 --> 00:27:59,040 Speaker 1: know if you know this. My mom has been taking 590 00:27:59,040 --> 00:28:03,480 Speaker 1: an AI class. Okay, they have them for seniors. Because 591 00:28:03,480 --> 00:28:04,680 Speaker 1: I was telling her, I was like, oh this, I'll 592 00:28:04,800 --> 00:28:07,359 Speaker 1: use chat GPT And I think it's so important to 593 00:28:07,440 --> 00:28:09,960 Speaker 1: keep your brain active and to be thinking about what's 594 00:28:10,040 --> 00:28:12,840 Speaker 1: new and understand technology. And it also helps you see 595 00:28:13,160 --> 00:28:15,439 Speaker 1: when you see scamming and phishing attempts, how are they 596 00:28:15,520 --> 00:28:18,040 Speaker 1: using these things to trick me? Right? So I think 597 00:28:18,240 --> 00:28:22,160 Speaker 1: you know, these tools I don't think are inherently nefarious. 598 00:28:22,200 --> 00:28:24,120 Speaker 1: I think it is just like any other tool how 599 00:28:24,160 --> 00:28:27,119 Speaker 1: someone is using it. A kitchen knife can be great 600 00:28:27,200 --> 00:28:29,480 Speaker 1: for chopping onions, or it can be used to commit 601 00:28:29,520 --> 00:28:34,520 Speaker 1: a crime. So I think it's just like, yes, exactly exactly. 602 00:28:33,920 --> 00:28:36,200 Speaker 3: That bad people are going to do bad things. It's 603 00:28:36,240 --> 00:28:38,240 Speaker 3: about like you know what I mean. And it's like the. 604 00:28:38,160 --> 00:28:42,040 Speaker 4: Technology and the tool itself, that is, it's own without 605 00:28:42,520 --> 00:28:44,680 Speaker 4: anyone driving it, it's nothing, it's just sitting there. 606 00:28:44,840 --> 00:28:46,800 Speaker 1: So but you have to know what's possible. So I 607 00:28:46,800 --> 00:28:48,920 Speaker 1: showed her Hegen so she could understand. I said, this 608 00:28:48,960 --> 00:28:50,960 Speaker 1: is making a video of me and if you saw it, 609 00:28:51,080 --> 00:28:52,640 Speaker 1: And I gave her multiple things like what do you 610 00:28:52,680 --> 00:28:54,120 Speaker 1: think is a real video of me versus what do 611 00:28:54,160 --> 00:28:56,480 Speaker 1: you think is generated right to just so she could 612 00:28:56,480 --> 00:28:59,320 Speaker 1: see the limits of like how far it could go 613 00:28:59,360 --> 00:29:01,080 Speaker 1: and how much could look like me. And I think 614 00:29:01,080 --> 00:29:03,320 Speaker 1: that makes a better case for what Lauren just explained 615 00:29:03,320 --> 00:29:05,720 Speaker 1: earlier about having a password, so even if it's not 616 00:29:05,800 --> 00:29:08,120 Speaker 1: something you're gonna adopt, so you can get out the 617 00:29:08,120 --> 00:29:08,880 Speaker 1: way when it's coming. 618 00:29:09,120 --> 00:29:10,640 Speaker 2: And that's the same way I feel about AI. 619 00:29:10,680 --> 00:29:12,120 Speaker 1: If you won't get in the driver's seat, if you 620 00:29:12,120 --> 00:29:13,920 Speaker 1: won't get in the passenger seat, you do need to 621 00:29:14,000 --> 00:29:16,280 Speaker 1: know how fast it goes so you can get out 622 00:29:16,280 --> 00:29:17,600 Speaker 1: the way or see it coming. 623 00:29:18,040 --> 00:29:19,800 Speaker 3: And put your seatbelts on, buckle up. 624 00:29:21,320 --> 00:29:29,760 Speaker 1: Yeah, Lauren TT shared a AI a generated creator and 625 00:29:30,720 --> 00:29:33,400 Speaker 1: they had on like a bonnet. It was a black girl. 626 00:29:33,480 --> 00:29:36,800 Speaker 1: She was talking, she was using black vernacular. Was I 627 00:29:36,920 --> 00:29:40,680 Speaker 1: was like, oh, it was given homegirl, but not connected 628 00:29:40,720 --> 00:29:44,400 Speaker 1: to anything. And you know, I worry about like the 629 00:29:44,480 --> 00:29:49,680 Speaker 1: adoption of different group aesthetics and kind of digital blackface 630 00:29:49,760 --> 00:29:52,920 Speaker 1: in this space and what it means for groups that 631 00:29:53,040 --> 00:29:55,960 Speaker 1: may not kind of know that this is happening. And 632 00:29:56,000 --> 00:29:59,760 Speaker 1: I'm curious, like, have you seen these kind of personas. 633 00:29:59,800 --> 00:30:05,440 Speaker 1: I guess they're not people, and then like as a designer, 634 00:30:05,520 --> 00:30:07,960 Speaker 1: a brand designer, and a person that's teaching other folks 635 00:30:08,040 --> 00:30:10,400 Speaker 1: how to do this type of work, Like, what responsibility 636 00:30:10,400 --> 00:30:13,000 Speaker 1: do you feel like we have when we consider the 637 00:30:13,040 --> 00:30:17,880 Speaker 1: ability of tools to replicate races and cultures and identity 638 00:30:18,440 --> 00:30:22,040 Speaker 1: for whether it's financial gain or just for the aesthetic value. 639 00:30:22,320 --> 00:30:23,160 Speaker 1: Where do you land on that? 640 00:30:23,320 --> 00:30:23,680 Speaker 3: For sure? 641 00:30:24,320 --> 00:30:27,680 Speaker 4: So I will say I'm not really on TikTok because 642 00:30:27,720 --> 00:30:30,520 Speaker 4: I've told myself if I got on TikTok, I would 643 00:30:30,520 --> 00:30:31,240 Speaker 4: never come out of it. 644 00:30:31,400 --> 00:30:33,360 Speaker 3: But I know what I've seen what you're talking about. 645 00:30:33,520 --> 00:30:35,120 Speaker 4: But I don't think there's quite as much like on 646 00:30:35,200 --> 00:30:39,120 Speaker 4: Instagram yet Again, it's all about like the user's responsibility, 647 00:30:39,160 --> 00:30:41,000 Speaker 4: and I think a lot of the people that are 648 00:30:41,040 --> 00:30:45,240 Speaker 4: doing stuff like that are not the most responsible people, right, 649 00:30:45,320 --> 00:30:47,160 Speaker 4: And I think they're just like, oh yeah, sure, and 650 00:30:47,240 --> 00:30:48,800 Speaker 4: I'm gonna throw this up there and like I don't 651 00:30:48,800 --> 00:30:51,160 Speaker 4: care if it's true, I don't care if it's biased. 652 00:30:51,200 --> 00:30:53,280 Speaker 4: I don't care if any of this stuff because they 653 00:30:53,640 --> 00:30:55,360 Speaker 4: they're generally trying to just. 654 00:30:55,280 --> 00:30:56,560 Speaker 3: Like make money and don't pair. 655 00:30:56,800 --> 00:30:59,800 Speaker 4: Especially they can kind of hide behind this like fake 656 00:31:00,040 --> 00:31:02,840 Speaker 4: person now, So there isn't as much accountability as well. 657 00:31:03,280 --> 00:31:06,600 Speaker 4: The other piece of it is like generating like images 658 00:31:07,000 --> 00:31:09,520 Speaker 4: in general, whether it's like a clone of a fake 659 00:31:09,600 --> 00:31:11,880 Speaker 4: person or like just an image, you know. Like I 660 00:31:11,920 --> 00:31:15,280 Speaker 4: worked at ALTA. I would never say like, yeah, let's 661 00:31:15,360 --> 00:31:19,960 Speaker 4: use AI people for our photography, right, I would say, hey, 662 00:31:20,440 --> 00:31:23,120 Speaker 4: let's use AI to help us like cast who do 663 00:31:23,160 --> 00:31:24,960 Speaker 4: we want to cast as models? 664 00:31:25,040 --> 00:31:25,200 Speaker 1: Right? 665 00:31:25,360 --> 00:31:27,320 Speaker 4: Or what is the shots that we want to get 666 00:31:27,400 --> 00:31:29,280 Speaker 4: or what should the makeup look like? But then of 667 00:31:29,320 --> 00:31:31,680 Speaker 4: course we're going to go and hire a real person 668 00:31:32,000 --> 00:31:34,840 Speaker 4: and have that shoot because I just like, again we 669 00:31:34,920 --> 00:31:37,480 Speaker 4: come back to the thing of like people being real 670 00:31:37,720 --> 00:31:40,680 Speaker 4: and authentic, and we have to make sure that like 671 00:31:40,920 --> 00:31:44,800 Speaker 4: we're not misrepresenting and to be fair, so much of 672 00:31:44,840 --> 00:31:48,920 Speaker 4: the data in large language models is biased because everything 673 00:31:48,920 --> 00:31:51,160 Speaker 4: on the Internet is biased, and it's the way that 674 00:31:51,320 --> 00:31:54,000 Speaker 4: we have this information that it's like learning from. 675 00:31:54,080 --> 00:31:55,760 Speaker 3: Right, Jem and I got in trouble. 676 00:31:55,760 --> 00:31:57,640 Speaker 4: They had to shut down their video or their image 677 00:31:57,640 --> 00:32:02,440 Speaker 4: model for a while because it was misrepresent like historical thing. 678 00:32:02,600 --> 00:32:02,760 Speaker 2: You know. 679 00:32:02,800 --> 00:32:04,600 Speaker 4: They would ask for, oh, can we see like this, 680 00:32:04,720 --> 00:32:06,520 Speaker 4: and it was like no, no, that's not what that 681 00:32:06,560 --> 00:32:08,719 Speaker 4: should be. And so they should because I knew it 682 00:32:08,760 --> 00:32:12,000 Speaker 4: wasn't doing it properly. But there's just so much still 683 00:32:12,040 --> 00:32:15,920 Speaker 4: that is like can happen that it's not right and 684 00:32:15,960 --> 00:32:20,719 Speaker 4: it's not appropriate that's going on, Like we're seeing deep fakes, 685 00:32:21,040 --> 00:32:23,760 Speaker 4: like all sorts of stuff. And I think again it 686 00:32:23,800 --> 00:32:27,200 Speaker 4: comes back to like it's about the person using it, 687 00:32:27,400 --> 00:32:30,320 Speaker 4: having the morals and the values of what it is 688 00:32:30,320 --> 00:32:33,440 Speaker 4: that they're creating. But I do think like when we 689 00:32:33,520 --> 00:32:37,720 Speaker 4: talk about, you know, creating people of all different colors 690 00:32:37,720 --> 00:32:40,960 Speaker 4: and races and nationalities and sizes and skin tones and 691 00:32:41,000 --> 00:32:43,680 Speaker 4: hair types and body types, like there's so much and 692 00:32:43,720 --> 00:32:45,840 Speaker 4: I think, you know, as somebody that did work at 693 00:32:45,880 --> 00:32:48,680 Speaker 4: all to where we were trying to cast diverse models, 694 00:32:49,240 --> 00:32:51,800 Speaker 4: you know, or you know, we go and try and 695 00:32:51,840 --> 00:32:54,360 Speaker 4: find stock photography and it's like, okay, well, when you're 696 00:32:54,400 --> 00:32:56,400 Speaker 4: looking for stock for photography, you do have to get 697 00:32:56,400 --> 00:32:59,000 Speaker 4: specific about like okay, yeah, I'm looking for like a 698 00:32:59,040 --> 00:33:02,160 Speaker 4: plus sized black or I'm looking for like a smaller 699 00:33:02,200 --> 00:33:04,240 Speaker 4: Asian WM or whatever it is. You do have to 700 00:33:04,240 --> 00:33:06,680 Speaker 4: be specific. And so I do think people look at 701 00:33:06,720 --> 00:33:08,240 Speaker 4: it and it's like, oh, well, now you're having to 702 00:33:08,320 --> 00:33:10,040 Speaker 4: like say what you want, and it's like, well, you 703 00:33:10,080 --> 00:33:12,440 Speaker 4: still would have needed to do that when you're casting 704 00:33:12,440 --> 00:33:13,120 Speaker 4: a model. 705 00:33:12,920 --> 00:33:13,920 Speaker 3: Or you're casting anyway. 706 00:33:13,960 --> 00:33:16,280 Speaker 4: So yeah, but it's a matter of like, okay, now 707 00:33:16,280 --> 00:33:20,080 Speaker 4: when we see this image, is this realistic to what 708 00:33:20,560 --> 00:33:25,240 Speaker 4: that person would actually look like based on real real shit, 709 00:33:25,400 --> 00:33:27,400 Speaker 4: you know what I mean, rather than like what you 710 00:33:27,560 --> 00:33:31,160 Speaker 4: think what AI thinks it is, because AI imagery is 711 00:33:31,240 --> 00:33:34,160 Speaker 4: the way that it's created through, like diffusion models is all. 712 00:33:34,560 --> 00:33:35,680 Speaker 3: I mean, that's a whole other thing. 713 00:33:35,800 --> 00:33:38,160 Speaker 4: But I think that's the piece too that you have 714 00:33:38,200 --> 00:33:41,080 Speaker 4: to be able to like have again that domain experience 715 00:33:41,080 --> 00:33:42,640 Speaker 4: of like somebody to look at that and be like, 716 00:33:42,640 --> 00:33:45,360 Speaker 4: we're not using that. That doesn't look appropriate, that doesn't 717 00:33:45,360 --> 00:33:47,680 Speaker 4: look like someone from Jamaica, or that doesn't look like 718 00:33:47,720 --> 00:33:52,080 Speaker 4: someone from wherever, right, and we're able to look at 719 00:33:52,080 --> 00:33:55,840 Speaker 4: it and make those determinations for ourselves. 720 00:33:56,200 --> 00:33:57,880 Speaker 3: And I think the other piece of that too is 721 00:33:58,760 --> 00:34:01,120 Speaker 3: when we a lot of people talk about okay, you know, 722 00:34:01,160 --> 00:34:05,240 Speaker 3: when we're putting information in and we're giving information to 723 00:34:05,320 --> 00:34:07,320 Speaker 3: chat gybt like it's learning from us. 724 00:34:07,800 --> 00:34:10,200 Speaker 4: And I do think that like it is a little 725 00:34:10,200 --> 00:34:13,399 Speaker 4: bit of our responsibility to put stuff in there now too, 726 00:34:13,520 --> 00:34:15,880 Speaker 4: that's new to kind of negate a lot of the 727 00:34:15,920 --> 00:34:18,960 Speaker 4: bias information that it has, because if we don't, then 728 00:34:19,000 --> 00:34:21,680 Speaker 4: like how is it gonna ever be able to kind 729 00:34:21,680 --> 00:34:22,400 Speaker 4: of change? 730 00:34:22,400 --> 00:34:24,799 Speaker 3: And I saw something today that was like Elon. 731 00:34:24,600 --> 00:34:26,440 Speaker 4: Musk is going to try and use Grock to like 732 00:34:26,560 --> 00:34:29,840 Speaker 4: rewrite history because he thinks that all of the data 733 00:34:29,880 --> 00:34:31,920 Speaker 4: that we have is like bullshit or something. 734 00:34:32,200 --> 00:34:34,759 Speaker 3: And I'm like, oh, good, good, good good. 735 00:34:34,960 --> 00:34:37,520 Speaker 4: That's who we want to rewriting history. 736 00:34:37,640 --> 00:34:40,600 Speaker 3: So yeah, I don't. I mean, it's all it is 737 00:34:40,680 --> 00:34:41,480 Speaker 3: all very like. 738 00:34:42,920 --> 00:34:43,400 Speaker 5: Scary. 739 00:34:43,600 --> 00:34:46,680 Speaker 4: And that's the thing, right, is like awareness and understanding, 740 00:34:46,719 --> 00:34:49,560 Speaker 4: and like that's what needs to happen is people need 741 00:34:49,600 --> 00:34:53,239 Speaker 4: to understand how these tools work, what's wrong about them, 742 00:34:53,280 --> 00:34:56,239 Speaker 4: what's right about them. Sam Altman, the CEO of Opening Eye, 743 00:34:56,560 --> 00:34:58,040 Speaker 4: just came out and was like, why are you guys 744 00:34:58,040 --> 00:34:58,799 Speaker 4: trusting these things? 745 00:34:58,840 --> 00:35:00,719 Speaker 3: You shouldn't be trusting. This is the one thing you 746 00:35:00,760 --> 00:35:04,120 Speaker 3: shouldn't be trusting. And people are like, what why are 747 00:35:04,120 --> 00:35:06,440 Speaker 3: you saying that. It's like, because he's right, we shouldn't 748 00:35:06,480 --> 00:35:09,600 Speaker 3: just be blindly trusting AI models. That is not what 749 00:35:09,600 --> 00:35:10,360 Speaker 3: should be happening. 750 00:35:10,480 --> 00:35:14,800 Speaker 4: So I think, just generally, I think the main message 751 00:35:14,840 --> 00:35:17,560 Speaker 4: here is like learn what these things can do, learn 752 00:35:17,840 --> 00:35:19,000 Speaker 4: the good they can do. 753 00:35:19,160 --> 00:35:20,160 Speaker 3: Learn the bad they can. 754 00:35:20,120 --> 00:35:22,759 Speaker 4: Do, and really just have a good understanding of what 755 00:35:22,880 --> 00:35:25,120 Speaker 4: it's capable of so that we can understand just like 756 00:35:25,160 --> 00:35:26,640 Speaker 4: your mom, like is that fake? 757 00:35:26,760 --> 00:35:27,320 Speaker 3: Is that real? 758 00:35:27,440 --> 00:35:28,040 Speaker 1: Like? What? Like? 759 00:35:28,320 --> 00:35:31,600 Speaker 4: Awareness is so important right now, just across the board 760 00:35:31,640 --> 00:35:34,080 Speaker 4: to understand, like what's. 761 00:35:33,800 --> 00:35:34,560 Speaker 3: Real and what's not. 762 00:35:35,120 --> 00:35:36,120 Speaker 2: I love this. 763 00:35:36,120 --> 00:35:38,239 Speaker 1: This is the information that people want to hear. I mean, 764 00:35:38,280 --> 00:35:41,480 Speaker 1: you talked about all of the good things with AI 765 00:35:41,560 --> 00:35:44,080 Speaker 1: and then some of the potentially really scary things with AI, 766 00:35:44,520 --> 00:35:46,799 Speaker 1: and like you were saying, it's good to just know, 767 00:35:47,440 --> 00:35:49,239 Speaker 1: Like you might say, oh, I don't really want to 768 00:35:49,280 --> 00:35:52,080 Speaker 1: engage even though people are engaging with AI and they're 769 00:35:52,080 --> 00:35:55,680 Speaker 1: not really realizing it. Understanding and having awareness of what 770 00:35:55,880 --> 00:35:59,160 Speaker 1: is going on, where we're moving to as a world, 771 00:35:59,600 --> 00:36:01,879 Speaker 1: Like what is going to be possible in the next 772 00:36:01,920 --> 00:36:02,560 Speaker 1: six months? 773 00:36:03,000 --> 00:36:04,200 Speaker 2: Is it's wild? 774 00:36:04,280 --> 00:36:07,160 Speaker 1: It's wild, and regulations are trying to keep up and 775 00:36:07,600 --> 00:36:09,839 Speaker 1: it's just a wild landscape, right. 776 00:36:10,320 --> 00:36:14,160 Speaker 2: And I'm excited to try all of these tools. Oh, somebody, 777 00:36:14,200 --> 00:36:15,879 Speaker 2: I have them drop those things. 778 00:36:15,880 --> 00:36:18,440 Speaker 1: I'm gonna drop these in the episode description and you 779 00:36:18,480 --> 00:36:20,480 Speaker 1: can see all of these things because I think that's 780 00:36:20,480 --> 00:36:22,200 Speaker 1: gonna be important for sure. 781 00:36:22,640 --> 00:36:25,279 Speaker 2: Thank you so much, Lauren. You are amazing. 782 00:36:25,600 --> 00:36:29,160 Speaker 1: I am so excited to Zakia introduce me to you, 783 00:36:29,280 --> 00:36:32,560 Speaker 1: and so I'm excited to continue following. I'm gonna be 784 00:36:32,600 --> 00:36:34,880 Speaker 1: diving even more into AI because I was like, I 785 00:36:34,880 --> 00:36:36,560 Speaker 1: feel like I'm an AI expert. 786 00:36:36,320 --> 00:36:38,759 Speaker 2: After listening to you, I'm not. There's still so. 787 00:36:38,840 --> 00:36:40,919 Speaker 1: Much I could be doing, and it it just got 788 00:36:40,920 --> 00:36:42,719 Speaker 1: everything fire my mind. I was like, oh, I could 789 00:36:42,719 --> 00:36:44,360 Speaker 1: be more productive in this way and that way and 790 00:36:44,360 --> 00:36:45,120 Speaker 1: this way and that way. 791 00:36:46,080 --> 00:36:46,839 Speaker 2: Let's get to it. 792 00:36:54,640 --> 00:36:57,520 Speaker 1: You can find us on X and Instagram at Dope 793 00:36:57,600 --> 00:37:00,680 Speaker 1: Labs podcast, tt is on X and it Instagram, at 794 00:37:00,760 --> 00:37:04,080 Speaker 1: d R Underscore, t Sahoe, and you can find Takiya 795 00:37:04,360 --> 00:37:07,239 Speaker 1: at z said So. Dope Labs is a production of 796 00:37:07,320 --> 00:37:12,080 Speaker 1: Lamanada Media. Our senior supervising producer is Kristin Lapour and 797 00:37:12,239 --> 00:37:16,960 Speaker 1: our associate producer is Isara Savez. 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