1 00:00:00,000 --> 00:00:02,320 All right, so are you ready to dive into this AI stuff? 2 00:00:02,320 --> 00:00:04,120 There's some crazy predictions in here. 3 00:00:04,120 --> 00:00:05,280 Yeah, it's exciting, isn't it? 4 00:00:05,280 --> 00:00:06,640 Stuff we have to go through today. 5 00:00:06,640 --> 00:00:08,200 I know, I've got all the stuff you sent me, 6 00:00:08,200 --> 00:00:10,160 the video transcript, your notes. 7 00:00:10,160 --> 00:00:12,840 Did you get a chance to skim Altman's blog post too? 8 00:00:12,840 --> 00:00:14,840 Oh yeah, I did, the one from a couple weeks ago, right? 9 00:00:14,840 --> 00:00:16,920 Right, I wanted to get your take on all of this, 10 00:00:16,920 --> 00:00:18,040 you know, with your background. 11 00:00:18,040 --> 00:00:19,960 Oh yeah, well, my background's a little different, 12 00:00:19,960 --> 00:00:21,880 but I think I can keep up. 13 00:00:21,880 --> 00:00:22,720 I think so too, yeah. 14 00:00:22,720 --> 00:00:25,000 Okay, so it seems like the big theme here 15 00:00:25,000 --> 00:00:27,840 is like this intelligence explosion, right, 16 00:00:27,840 --> 00:00:29,360 where AI just kind of takes off. 17 00:00:29,360 --> 00:00:30,600 Right, and it's not just like, 18 00:00:30,600 --> 00:00:32,080 oh, AI is getting a little bit better. 19 00:00:32,080 --> 00:00:34,240 It's like, whoa, it's a million times better. 20 00:00:34,240 --> 00:00:36,160 Like it's gonna blow past us, right? 21 00:00:36,160 --> 00:00:39,120 And this paper, the, what was it called? 22 00:00:39,120 --> 00:00:40,360 The situational awareness one. 23 00:00:40,360 --> 00:00:42,680 Yeah, yeah, that one, it kind of lays out 24 00:00:42,680 --> 00:00:44,520 how this could actually happen. 25 00:00:44,520 --> 00:00:47,040 It's really fascinating, it talks about how, 26 00:00:47,040 --> 00:00:50,040 you know, right now, AI is learning for us, right, 27 00:00:50,040 --> 00:00:51,240 from the data we feed it. 28 00:00:51,240 --> 00:00:52,080 Yeah. 29 00:00:52,080 --> 00:00:54,040 But what happens when it starts learning from itself. 30 00:00:54,040 --> 00:00:54,880 Right. 31 00:00:54,880 --> 00:00:56,040 And generated its own knowledge, 32 00:00:56,040 --> 00:00:57,280 like making its own discoveries. 33 00:00:57,280 --> 00:00:58,600 Yeah, like a snowball effect, 34 00:00:58,600 --> 00:01:00,320 and it just keeps getting smarter and smarter. 35 00:01:00,320 --> 00:01:01,160 Exactly. 36 00:01:01,160 --> 00:01:02,600 And according to Altman, 37 00:01:02,600 --> 00:01:04,560 we might be closer to that than we think. 38 00:01:04,560 --> 00:01:07,760 Yeah, he said something about like two orders of magnitude. 39 00:01:07,760 --> 00:01:10,520 Yeah, so like, you know, GPT-3 to GPT-4, 40 00:01:10,520 --> 00:01:12,120 that was a huge leap, right? 41 00:01:12,120 --> 00:01:12,960 Oh yeah. 42 00:01:12,960 --> 00:01:14,360 Like a hundred times more powerful 43 00:01:14,360 --> 00:01:15,920 as one order of magnitude. 44 00:01:15,920 --> 00:01:17,960 Sink two more leaps like that and boom. 45 00:01:17,960 --> 00:01:18,800 Wow. 46 00:01:18,800 --> 00:01:21,320 And that could happen, what, in a few years? 47 00:01:21,320 --> 00:01:22,440 Potentially, yeah. 48 00:01:22,440 --> 00:01:25,280 I mean, the pace of development is incredible. 49 00:01:25,280 --> 00:01:26,320 I know, it's kind of scary, right? 50 00:01:26,320 --> 00:01:27,800 Like it's exciting, but also, 51 00:01:27,800 --> 00:01:29,320 whoa, are we ready for this? 52 00:01:29,320 --> 00:01:30,440 I think that's the big question. 53 00:01:30,440 --> 00:01:32,440 Are we ready for the intelligence explosion? 54 00:01:32,440 --> 00:01:33,280 Yeah. 55 00:01:33,280 --> 00:01:35,400 And how do we make sure it's a good thing, you know, 56 00:01:35,400 --> 00:01:36,720 that it benefited humanity? 57 00:01:36,720 --> 00:01:38,000 Right, that it doesn't, you know, 58 00:01:38,000 --> 00:01:39,640 decide we're not useful anymore. 59 00:01:39,640 --> 00:01:41,280 Exactly, it's a big responsibility, 60 00:01:41,280 --> 00:01:42,280 figuring all this out. 61 00:01:42,280 --> 00:01:44,520 Okay, so I gotta ask you about this AI coder thing, 62 00:01:44,520 --> 00:01:45,960 because that blew my mind. 63 00:01:45,960 --> 00:01:47,200 Like by the end of the year, 64 00:01:47,200 --> 00:01:49,600 an AI could be the best programmer in the world. 65 00:01:49,600 --> 00:01:50,960 Yeah, that's what Altman is predicting. 66 00:01:50,960 --> 00:01:51,920 It's pretty wild, right? 67 00:01:51,920 --> 00:01:54,040 I mean, I can barely write a line of code, 68 00:01:54,040 --> 00:01:58,120 but the AI will be like churning out perfect code in seconds. 69 00:01:58,120 --> 00:01:59,160 It's gonna change everything. 70 00:01:59,160 --> 00:02:00,560 Think about AlphaGo, remember that? 71 00:02:00,560 --> 00:02:01,600 Yeah, vaguely. 72 00:02:01,600 --> 00:02:04,760 It learned to play go by playing against itself, right? 73 00:02:04,760 --> 00:02:06,920 Oh yeah, and it ended up beating the world champion. 74 00:02:06,920 --> 00:02:09,480 Right, and they're applying a similar approach to coding. 75 00:02:09,480 --> 00:02:13,200 Let the AI learn by doing, by creating and testing code. 76 00:02:13,200 --> 00:02:15,520 So it's not just like copying existing code, 77 00:02:15,520 --> 00:02:17,160 it's actually coming up with new solutions. 78 00:02:17,160 --> 00:02:19,320 Exactly, and the results are already amazing. 79 00:02:19,320 --> 00:02:22,880 OpenAI has an AI that's already in the top 50 80 00:02:22,880 --> 00:02:25,160 among competitive programmers worldwide. 81 00:02:25,160 --> 00:02:27,080 Top 50, that's insane. 82 00:02:27,080 --> 00:02:28,760 So okay, here's the big question. 83 00:02:28,760 --> 00:02:30,680 What happens to all the human programmers? 84 00:02:30,680 --> 00:02:31,960 That's what everyone wants to know, right? 85 00:02:31,960 --> 00:02:33,480 Are the robots coming for our jobs? 86 00:02:33,480 --> 00:02:34,960 Yeah, seriously. 87 00:02:34,960 --> 00:02:35,920 I don't think it's that simple. 88 00:02:35,920 --> 00:02:38,800 I think it's more about augmentation, not replacement. 89 00:02:38,800 --> 00:02:40,480 So like working with the AI? 90 00:02:40,480 --> 00:02:43,560 Exactly, imagine having an AI coding assistant 91 00:02:43,560 --> 00:02:46,240 that's like the best programmer in the world, 92 00:02:46,240 --> 00:02:47,760 right at your fingertips. 93 00:02:47,760 --> 00:02:50,360 So instead of spending hours trying to debug something, 94 00:02:50,360 --> 00:02:52,400 I could just like tell the AI what I want 95 00:02:52,400 --> 00:02:53,320 and it would just do it. 96 00:02:53,320 --> 00:02:54,160 That's the idea. 97 00:02:54,160 --> 00:02:56,000 And it could free up human programmers 98 00:02:56,000 --> 00:02:58,480 to focus on the more creative aspects, 99 00:02:58,480 --> 00:02:59,600 the big picture stuff. 100 00:02:59,600 --> 00:03:01,240 Okay, but still, a lot of people 101 00:03:01,240 --> 00:03:02,720 are gonna be worried about their jobs, right? 102 00:03:02,720 --> 00:03:04,280 For sure, and it's a valid concern. 103 00:03:04,280 --> 00:03:06,120 We need to figure out how to transition 104 00:03:06,120 --> 00:03:08,840 into this new world of work. 105 00:03:08,840 --> 00:03:10,800 How to prepare people for the jobs of the future. 106 00:03:10,800 --> 00:03:12,320 Right, because it's happening fast. 107 00:03:12,320 --> 00:03:13,800 Like even faster than we thought. 108 00:03:13,800 --> 00:03:15,200 Yeah, Moore's law is still relevant, 109 00:03:15,200 --> 00:03:17,280 but AI is advancing even faster than that. 110 00:03:17,280 --> 00:03:18,880 Moore's law, that's the one about computers 111 00:03:18,880 --> 00:03:21,000 getting twice as powerful every, what, 112 00:03:21,000 --> 00:03:22,000 two years or something? 113 00:03:22,000 --> 00:03:23,360 Every 18 months, yeah. 114 00:03:23,360 --> 00:03:26,120 But AI is leveraging something even more powerful, 115 00:03:26,120 --> 00:03:27,240 test time compute. 116 00:03:27,240 --> 00:03:29,520 Test time compute, what is that? 117 00:03:29,520 --> 00:03:30,800 Sounds kind of intimidating. 118 00:03:30,800 --> 00:03:33,760 It's basically the idea that AI can keep getting better 119 00:03:33,760 --> 00:03:35,320 even while it's working on a problem. 120 00:03:35,320 --> 00:03:37,560 It's like it has time to think. 121 00:03:37,560 --> 00:03:39,920 So instead of just giving the first answer it comes up with, 122 00:03:39,920 --> 00:03:43,600 it can analyze different options, optimize its approach. 123 00:03:43,600 --> 00:03:46,200 Exactly, it's like having a super smart assistant 124 00:03:46,200 --> 00:03:48,160 that's constantly learning and improving. 125 00:03:48,160 --> 00:03:50,400 So it's not just about the initial training data, 126 00:03:50,400 --> 00:03:54,080 it's about how much thinking the AI can do in real time. 127 00:03:54,080 --> 00:03:56,160 Right, and this is giving rise to what they call 128 00:03:56,160 --> 00:03:58,120 thinking models AI systems 129 00:03:58,120 --> 00:04:00,000 that are constantly learning and adapting. 130 00:04:00,000 --> 00:04:02,120 Okay, so how much faster is this approach 131 00:04:02,120 --> 00:04:03,960 compared to traditional methods? 132 00:04:03,960 --> 00:04:06,280 Altman suggests the cost of using AI 133 00:04:06,280 --> 00:04:08,160 at any given intelligence level 134 00:04:08,160 --> 00:04:10,400 is falling 10 fold every 12 months. 135 00:04:10,400 --> 00:04:11,520 Wow, that's crazy. 136 00:04:11,520 --> 00:04:13,080 No wonder this feels like such a big deal. 137 00:04:13,080 --> 00:04:15,600 It's a fundamental shift in how we solve problems, 138 00:04:15,600 --> 00:04:18,160 create value, how we interact with the world. 139 00:04:18,160 --> 00:04:20,080 Yeah, like everything is changing around us 140 00:04:20,080 --> 00:04:21,920 and it's all happening so fast. 141 00:04:21,920 --> 00:04:23,160 And that's why it's so important 142 00:04:23,160 --> 00:04:26,560 to understand the potential impacts, both good and bad. 143 00:04:26,560 --> 00:04:28,280 We need to be prepared for what's coming. 144 00:04:28,280 --> 00:04:29,960 Okay, well let's talk about some of those impacts. 145 00:04:29,960 --> 00:04:31,400 We've touched on the AI coders 146 00:04:31,400 --> 00:04:33,320 and this intelligence explosion, 147 00:04:33,320 --> 00:04:36,760 but how is all of this going to affect the future of work? 148 00:04:36,760 --> 00:04:38,520 Like for everyday people? 149 00:04:38,520 --> 00:04:40,160 It's kind of crazy when you think about 150 00:04:40,160 --> 00:04:43,640 how what seemed impossible, like just a few years ago, 151 00:04:43,640 --> 00:04:45,600 is now like totally normal. 152 00:04:45,600 --> 00:04:47,120 Yeah, what do you mean, like flying cars? 153 00:04:47,120 --> 00:04:48,680 I'm still waiting on those. 154 00:04:48,680 --> 00:04:49,760 No, not quite. 155 00:04:49,760 --> 00:04:53,640 But like imagine explaining to someone 30 years ago 156 00:04:53,640 --> 00:04:55,600 that you could have like a tiny computer. 157 00:04:55,600 --> 00:04:56,440 In your pocket. 158 00:04:56,440 --> 00:04:58,000 Yeah, they could access basically 159 00:04:58,000 --> 00:04:59,520 all the information in the world. 160 00:04:59,520 --> 00:05:00,360 Oh yeah, yeah. 161 00:05:00,360 --> 00:05:01,720 They'd probably think you were crazy, 162 00:05:01,720 --> 00:05:03,280 like from Star Trek or something. 163 00:05:03,280 --> 00:05:04,440 Right, but today we're like, 164 00:05:04,440 --> 00:05:06,000 oh yeah, my phone could do that, no big deal. 165 00:05:06,000 --> 00:05:07,880 And my phone probably has more power 166 00:05:07,880 --> 00:05:09,680 than those old computers they used to like 167 00:05:09,680 --> 00:05:10,880 land on the moon, right? 168 00:05:10,880 --> 00:05:13,520 Totally, and Altman talks about this in his blog post too. 169 00:05:13,520 --> 00:05:15,920 He uses the example of transistors. 170 00:05:15,920 --> 00:05:18,320 Transistors, those little things inside computers. 171 00:05:18,320 --> 00:05:20,120 Yeah, they're like the building blocks 172 00:05:20,120 --> 00:05:24,320 of all modern electronics, phones, computers, even cars. 173 00:05:24,320 --> 00:05:25,960 But nobody really thinks about them, right? 174 00:05:25,960 --> 00:05:28,040 They're just kind of there doing their thing. 175 00:05:28,040 --> 00:05:30,680 Exactly, they're essential but invisible. 176 00:05:30,680 --> 00:05:32,920 And Altman thinks AI could be the same way. 177 00:05:32,920 --> 00:05:34,280 Like just woven into our lives 178 00:05:34,280 --> 00:05:35,880 even if we don't always realize it. 179 00:05:35,880 --> 00:05:38,640 Right, but even more transformative. 180 00:05:38,640 --> 00:05:41,880 Because AI isn't just about making things faster or smaller, 181 00:05:41,880 --> 00:05:44,520 it's about changing how we solve problems. 182 00:05:44,520 --> 00:05:45,360 How so? 183 00:05:45,360 --> 00:05:46,280 Well, think about it. 184 00:05:46,280 --> 00:05:50,520 What if AI could help us design like totally new materials 185 00:05:50,520 --> 00:05:53,040 or optimize our cities to be more efficient? 186 00:05:53,040 --> 00:05:55,840 Or even like personalize education for every student. 187 00:05:55,840 --> 00:06:00,480 Exactly, AI could revolutionize every aspect of our lives 188 00:06:00,480 --> 00:06:03,480 and create incredible economic growth in the process. 189 00:06:03,480 --> 00:06:05,040 Because it's not just doing things better, 190 00:06:05,040 --> 00:06:07,080 it's doing things we couldn't even imagine before. 191 00:06:07,080 --> 00:06:07,920 Right, exactly. 192 00:06:07,920 --> 00:06:10,440 It's like opening up a whole new world of possibilities. 193 00:06:10,440 --> 00:06:11,640 Okay, so that's the big picture. 194 00:06:11,640 --> 00:06:12,680 But what about right now? 195 00:06:12,680 --> 00:06:15,920 What are some concrete examples of AI making a difference? 196 00:06:15,920 --> 00:06:17,720 Well, one area where we're already seeing 197 00:06:17,720 --> 00:06:19,920 huge progress is in healthcare. 198 00:06:19,920 --> 00:06:20,760 Really? 199 00:06:20,760 --> 00:06:21,760 Like how? 200 00:06:21,760 --> 00:06:25,040 For example, AI is being used to analyze medical images 201 00:06:25,040 --> 00:06:26,720 like X-rays and MRIs. 202 00:06:26,720 --> 00:06:29,280 So like instead of a doctor having to look at them. 203 00:06:29,280 --> 00:06:30,600 The doctor still looks at them, 204 00:06:30,600 --> 00:06:33,040 but the AI can help them detect things they might miss. 205 00:06:33,040 --> 00:06:35,280 Like a second set of eyes but way more powerful. 206 00:06:35,280 --> 00:06:38,840 Exactly, it can help diagnose diseases like cancer earlier 207 00:06:38,840 --> 00:06:39,880 and more accurately. 208 00:06:39,880 --> 00:06:40,960 Wow, that's amazing. 209 00:06:40,960 --> 00:06:42,600 So it's not replacing doctors, 210 00:06:42,600 --> 00:06:44,600 it's helping them do their jobs better. 211 00:06:44,600 --> 00:06:45,440 Right. 212 00:06:45,440 --> 00:06:48,160 And it can also help personalize treatment plans 213 00:06:48,160 --> 00:06:51,280 based on a patient's individual needs and genetic makeup. 214 00:06:51,280 --> 00:06:54,360 So like medicine tailored just for you, that's incredible. 215 00:06:54,360 --> 00:06:55,360 It's really exciting stuff. 216 00:06:55,360 --> 00:06:56,720 And that's just one example. 217 00:06:56,720 --> 00:06:59,200 AI is also being used to tackle climate change. 218 00:06:59,200 --> 00:07:01,560 Climate change, how can AI help with that? 219 00:07:01,560 --> 00:07:02,400 Well, for one thing, 220 00:07:02,400 --> 00:07:05,280 it can help us analyze the huge amounts of data 221 00:07:05,280 --> 00:07:06,280 we have about the climate. 222 00:07:06,280 --> 00:07:08,080 So we can understand what's happening better. 223 00:07:08,080 --> 00:07:10,680 Right, and make more accurate predictions about the future. 224 00:07:10,680 --> 00:07:12,480 And then hopefully come up with better solutions. 225 00:07:12,480 --> 00:07:13,480 Exactly. 226 00:07:13,480 --> 00:07:16,720 AI can also help us optimize energy consumption, 227 00:07:16,720 --> 00:07:18,640 design more sustainable cities, 228 00:07:18,640 --> 00:07:21,080 even develop new technologies to capture carbon 229 00:07:21,080 --> 00:07:21,960 from the atmosphere. 230 00:07:21,960 --> 00:07:23,720 Okay, so it's not all doom and gloom. 231 00:07:23,720 --> 00:07:26,080 AI can actually help us solve some of the biggest problems 232 00:07:26,080 --> 00:07:26,920 we're facing. 233 00:07:26,920 --> 00:07:27,760 Absolutely. 234 00:07:27,760 --> 00:07:29,200 But of course there are also risks and challenges 235 00:07:29,200 --> 00:07:30,200 we need to be aware of. 236 00:07:30,200 --> 00:07:31,360 Yeah, let's talk about those. 237 00:07:31,360 --> 00:07:33,760 We've all heard about the potential for job losses. 238 00:07:33,760 --> 00:07:34,960 Right, that's a big one. 239 00:07:34,960 --> 00:07:36,880 As AI becomes more capable, 240 00:07:36,880 --> 00:07:38,920 it's likely to automate many jobs 241 00:07:38,920 --> 00:07:40,560 that are currently done by humans. 242 00:07:40,560 --> 00:07:43,840 Especially jobs that are like repetitive or predictable, right? 243 00:07:43,840 --> 00:07:45,000 Exactly. 244 00:07:45,000 --> 00:07:47,280 And this could lead to significant unemployment, 245 00:07:47,280 --> 00:07:50,120 especially in fields like manufacturing and transportation. 246 00:07:50,120 --> 00:07:52,160 Because if a company can use AI 247 00:07:52,160 --> 00:07:54,040 to do the work faster and cheaper, 248 00:07:54,040 --> 00:07:56,160 why would they keep paying human workers? 249 00:07:56,160 --> 00:07:57,280 It's a valid concern. 250 00:07:57,280 --> 00:07:59,480 And it's something we need to start thinking about now. 251 00:07:59,480 --> 00:08:02,040 How do we prepare people for the jobs of the future? 252 00:08:02,040 --> 00:08:04,720 How do we ensure that everyone benefits from AI, 253 00:08:04,720 --> 00:08:05,920 not just a select few? 254 00:08:05,920 --> 00:08:08,280 Yeah, because otherwise we could end up with a society 255 00:08:08,280 --> 00:08:10,080 where the gap between the rich and the poor 256 00:08:10,080 --> 00:08:11,400 just keeps getting wider. 257 00:08:11,400 --> 00:08:13,360 Right, it's not just about the technology itself, 258 00:08:13,360 --> 00:08:14,760 it's about how we use it. 259 00:08:14,760 --> 00:08:16,800 We need to make sure that AI is used 260 00:08:16,800 --> 00:08:19,880 to create a more equitable and just society. 261 00:08:19,880 --> 00:08:22,320 Okay, so job displacement is one big concern. 262 00:08:22,320 --> 00:08:24,800 What other risks should we be thinking about? 263 00:08:24,800 --> 00:08:27,640 Well, there's also the potential for AI to be misused, 264 00:08:27,640 --> 00:08:29,680 you know, for malicious purposes. 265 00:08:29,680 --> 00:08:30,520 Like what? 266 00:08:30,520 --> 00:08:32,480 Well, for example, AI could be used 267 00:08:32,480 --> 00:08:34,520 to develop autonomous weapons systems. 268 00:08:34,520 --> 00:08:36,880 Weapons that can think for themselves. 269 00:08:36,880 --> 00:08:38,160 That's kind of terrifying. 270 00:08:38,160 --> 00:08:39,880 It's definitely a cause for concern. 271 00:08:39,880 --> 00:08:41,400 And it raises a lot of ethical questions 272 00:08:41,400 --> 00:08:43,720 about how we develop and deploy AI. 273 00:08:43,720 --> 00:08:45,800 We need to make sure that we have safeguards in place. 274 00:08:45,800 --> 00:08:48,360 Okay, so we've got killer robots to worry about. 275 00:08:48,360 --> 00:08:49,200 What else? 276 00:08:49,200 --> 00:08:51,240 Well, there's also the question of AI bias. 277 00:08:51,240 --> 00:08:53,800 You know, AI algorithms are trained on data, right? 278 00:08:53,800 --> 00:08:54,640 Yeah. 279 00:08:54,640 --> 00:08:57,080 And if that data is biased, the AI will be biased too. 280 00:08:57,080 --> 00:08:59,320 So like, if the AI is trained on data 281 00:08:59,320 --> 00:09:02,000 that's mostly from men, it might not be very good 282 00:09:02,000 --> 00:09:04,200 at understanding or responding to women. 283 00:09:04,200 --> 00:09:06,560 Exactly, and that could lead to all sorts of problems 284 00:09:06,560 --> 00:09:09,920 from discrimination and hiring to unfair treatment 285 00:09:09,920 --> 00:09:10,920 by law enforcement. 286 00:09:10,920 --> 00:09:14,080 So we need to make sure that the data we use to train AI 287 00:09:14,080 --> 00:09:17,040 is diverse and representative of the real world. 288 00:09:17,040 --> 00:09:20,160 Right, and we need to be constantly monitoring AI systems 289 00:09:20,160 --> 00:09:22,720 for bias and making adjustments as needed. 290 00:09:22,720 --> 00:09:24,160 Okay, all this is a lot to take in. 291 00:09:24,160 --> 00:09:26,200 It seems like there's a lot of potential for good, 292 00:09:26,200 --> 00:09:28,440 but also a lot of potential for harm. 293 00:09:28,440 --> 00:09:30,240 It's a double-edged sword, for sure. 294 00:09:30,240 --> 00:09:33,880 But I think it's important to remember that AI is a tool. 295 00:09:33,880 --> 00:09:36,200 And like any tool, it can be used for good 296 00:09:36,200 --> 00:09:37,040 or for evil. 297 00:09:37,040 --> 00:09:39,040 It all depends on who's wielding it, right? 298 00:09:39,040 --> 00:09:40,640 Exactly, and that's why it's so important 299 00:09:40,640 --> 00:09:42,520 to have these conversations to raise awareness 300 00:09:42,520 --> 00:09:45,200 about the potential risks and benefits of AI 301 00:09:45,200 --> 00:09:46,920 so that we can make informed decisions 302 00:09:46,920 --> 00:09:49,760 about how we develop and deploy this technology. 303 00:09:49,760 --> 00:09:51,320 We've all seen those sci-fi movies 304 00:09:51,320 --> 00:09:53,160 where the AI becomes super intelligent 305 00:09:53,160 --> 00:09:54,360 and takes over the world. 306 00:09:54,360 --> 00:09:56,280 Is that something we should actually be worried about? 307 00:09:56,280 --> 00:09:57,600 Well, it's important to distinguish 308 00:09:57,600 --> 00:10:00,160 between science fiction and reality. 309 00:10:00,160 --> 00:10:02,800 While those scenarios might make for good movies, 310 00:10:02,800 --> 00:10:05,080 most experts agree that we're still a long way 311 00:10:05,080 --> 00:10:07,760 from creating AI that can fully think for itself. 312 00:10:07,760 --> 00:10:09,920 So we're not gonna have a terminator situation 313 00:10:09,920 --> 00:10:10,760 anytime soon? 314 00:10:10,760 --> 00:10:11,960 Probably not. 315 00:10:11,960 --> 00:10:13,920 But that doesn't mean we shouldn't be careful. 316 00:10:13,920 --> 00:10:17,160 Even if AI doesn't become evil in the traditional sense, 317 00:10:17,160 --> 00:10:20,720 there's still the potential for unintended consequences. 318 00:10:20,720 --> 00:10:22,160 Like it could just make a mistake 319 00:10:22,160 --> 00:10:23,560 that has huge repercussions. 320 00:10:23,560 --> 00:10:26,080 Exactly, or it could be used by humans 321 00:10:26,080 --> 00:10:28,640 for purposes that we didn't anticipate or intend. 322 00:10:28,640 --> 00:10:30,400 So it's not just about the AI itself, 323 00:10:30,400 --> 00:10:33,240 it's about the humans who are creating it and using it. 324 00:10:33,240 --> 00:10:34,320 Right, we need to be thinking 325 00:10:34,320 --> 00:10:36,480 about the ethical implications of AI 326 00:10:36,480 --> 00:10:37,840 from the very beginning. 327 00:10:37,840 --> 00:10:39,960 And we need to make sure that we're developing AI 328 00:10:39,960 --> 00:10:44,160 in a way that aligns with our values as a society. 329 00:10:44,160 --> 00:10:45,320 All this is getting pretty deep. 330 00:10:45,320 --> 00:10:47,360 It's easy to feel overwhelmed by all this stuff. 331 00:10:47,360 --> 00:10:48,200 I know, it's a lot. 332 00:10:48,200 --> 00:10:50,320 But I think it's important to have these conversations. 333 00:10:50,320 --> 00:10:52,040 The more we talk about AI, 334 00:10:52,040 --> 00:10:54,760 the better equipped we'll be to make informed decisions 335 00:10:54,760 --> 00:10:55,680 about its future. 336 00:10:55,680 --> 00:10:58,360 And to make sure that it's used for good, not for harm. 337 00:10:58,360 --> 00:11:01,520 Exactly, it's up to us to shape the future of AI. 338 00:11:01,520 --> 00:11:03,960 And to make sure that it benefits all of humanity. 339 00:11:03,960 --> 00:11:06,000 Okay, so we've talked about the practical stuff, 340 00:11:06,000 --> 00:11:08,040 the jobs, the risks, the ethics. 341 00:11:08,040 --> 00:11:10,680 But now I wanna get into the really big questions. 342 00:11:10,680 --> 00:11:11,960 Oh yeah, like what? 343 00:11:11,960 --> 00:11:14,360 Like what does all this mean for humanity? 344 00:11:14,360 --> 00:11:16,600 Are we on the verge of creating something 345 00:11:16,600 --> 00:11:18,320 that's actually smarter than us? 346 00:11:18,320 --> 00:11:19,720 And if so, what does that even mean? 347 00:11:19,720 --> 00:11:21,080 It really makes you think, doesn't it? 348 00:11:21,080 --> 00:11:23,160 Like what does it even mean to be intelligent? 349 00:11:23,160 --> 00:11:25,200 Right, I mean, we've always thought of intelligence 350 00:11:25,200 --> 00:11:26,400 as like a human thing. 351 00:11:26,400 --> 00:11:28,280 Yeah, like we're the smartest ones around. 352 00:11:28,280 --> 00:11:31,880 Exactly, but AI is challenging that assumption. 353 00:11:31,880 --> 00:11:33,520 Because it can do things that we can't, right? 354 00:11:33,520 --> 00:11:36,520 Like process information, add incredible speeds, 355 00:11:36,520 --> 00:11:38,280 make complex calculations. 356 00:11:38,280 --> 00:11:40,520 Right, but is that all there is to intelligence? 357 00:11:40,520 --> 00:11:42,440 Like can a computer really be intelligent 358 00:11:42,440 --> 00:11:45,800 if it doesn't have emotions or consciousness? 359 00:11:45,800 --> 00:11:47,320 Yeah, that's the big question, isn't it? 360 00:11:47,320 --> 00:11:49,080 Like what's the difference between 361 00:11:49,080 --> 00:11:53,200 a really advanced algorithm and actual like awareness? 362 00:11:53,200 --> 00:11:56,440 It's a question philosophers have been debating for centuries. 363 00:11:56,440 --> 00:11:58,520 And that was becoming a practical question too. 364 00:11:58,520 --> 00:12:00,440 Because AI is getting so good 365 00:12:00,440 --> 00:12:02,360 at mimicking human behavior. 366 00:12:02,360 --> 00:12:04,680 Like we've talked about AI writing poetry 367 00:12:04,680 --> 00:12:05,920 and composing music. 368 00:12:05,920 --> 00:12:07,480 Yeah, and creating art, 369 00:12:07,480 --> 00:12:10,560 even having conversations that seem like totally natural. 370 00:12:10,560 --> 00:12:12,080 So if it looks like it's thinking 371 00:12:12,080 --> 00:12:13,200 and acts like it's thinking, 372 00:12:13,200 --> 00:12:14,880 does that mean it actually is thinking? 373 00:12:14,880 --> 00:12:16,560 That's the million dollar question. 374 00:12:16,560 --> 00:12:18,000 And I don't think anyone has the N of yet. 375 00:12:18,000 --> 00:12:18,960 It's kind of freaky, right? 376 00:12:18,960 --> 00:12:19,880 Like we're creating something 377 00:12:19,880 --> 00:12:21,360 that we don't even fully understand. 378 00:12:21,360 --> 00:12:23,320 It's definitely a bit unsettling, 379 00:12:23,320 --> 00:12:26,000 but it's also incredibly exciting. 380 00:12:26,000 --> 00:12:26,840 Exciting? 381 00:12:28,280 --> 00:12:29,200 How so? 382 00:12:29,200 --> 00:12:30,040 Well, think about it. 383 00:12:30,040 --> 00:12:32,320 We're pushing the boundaries of what's possible. 384 00:12:32,320 --> 00:12:34,680 We're exploring the nature of intelligence itself. 385 00:12:34,680 --> 00:12:36,080 Who knows what we might discover? 386 00:12:36,080 --> 00:12:37,080 Okay, I see your point. 387 00:12:37,080 --> 00:12:39,440 It's like the ultimate scientific frontier. 388 00:12:39,440 --> 00:12:40,280 Exactly. 389 00:12:40,280 --> 00:12:41,280 And it's not just about science. 390 00:12:41,280 --> 00:12:43,200 It's about what it means to be human. 391 00:12:43,200 --> 00:12:45,440 Because if we create something that's smarter than us, 392 00:12:45,440 --> 00:12:46,920 does that make us less human? 393 00:12:46,920 --> 00:12:47,760 I don't think so. 394 00:12:47,760 --> 00:12:49,320 I think it actually makes us more human. 395 00:12:49,320 --> 00:12:50,840 More human, how? 396 00:12:50,840 --> 00:12:53,880 Because it forces us to confront our own limitations, 397 00:12:53,880 --> 00:12:56,560 to ask the big questions about what makes us unique. 398 00:12:56,560 --> 00:12:58,080 Like what is it that makes us human 399 00:12:58,080 --> 00:13:01,200 if a machine can do everything we can do but better? 400 00:13:01,200 --> 00:13:02,040 Right. 401 00:13:02,040 --> 00:13:05,280 And I think the answer lies in our capacity for empathy, 402 00:13:05,280 --> 00:13:07,120 for compassion, for love. 403 00:13:07,120 --> 00:13:09,160 Those are the things that make us truly human. 404 00:13:09,160 --> 00:13:11,080 The things that AI can't replicate 405 00:13:11,080 --> 00:13:12,400 no matter how smart it gets. 406 00:13:12,400 --> 00:13:13,240 Exactly. 407 00:13:13,240 --> 00:13:14,640 And I think that's a good thing. 408 00:13:14,640 --> 00:13:16,920 Because it means that we'll always have something to offer. 409 00:13:16,920 --> 00:13:19,200 Even in a world where AI is everywhere, 410 00:13:19,200 --> 00:13:20,480 we'll still be needed. 411 00:13:20,480 --> 00:13:21,320 Absolutely. 412 00:13:21,320 --> 00:13:23,840 And I think the relationship between humans and AI 413 00:13:23,840 --> 00:13:26,840 will be one of partnership, not competition. 414 00:13:26,840 --> 00:13:29,080 Like working together to solve problems, 415 00:13:29,080 --> 00:13:30,120 create new things. 416 00:13:30,120 --> 00:13:33,320 Right, using AI to enhance our abilities, not replace us. 417 00:13:33,320 --> 00:13:37,440 That's a much more hopeful vision than the whole robots 418 00:13:37,440 --> 00:13:39,400 taking over the world scenario. 419 00:13:39,400 --> 00:13:40,760 Yeah, I think so too. 420 00:13:40,760 --> 00:13:43,520 But it's up to us to make that vision a reality. 421 00:13:43,520 --> 00:13:46,960 By making sure AI is developed ethically, responsibly. 422 00:13:46,960 --> 00:13:47,600 Exactly. 423 00:13:47,600 --> 00:13:51,400 We need to be thoughtful, cautious, but also optimistic. 424 00:13:51,400 --> 00:13:52,760 It's a lot to balance, right? 425 00:13:52,760 --> 00:13:54,160 But I think we're up to the challenge. 426 00:13:54,160 --> 00:13:54,920 I think so too. 427 00:13:54,920 --> 00:13:57,320 I mean, we've faced big challenges before. 428 00:13:57,320 --> 00:14:00,600 And we've always found a way to adapt and overcome. 429 00:14:00,600 --> 00:14:03,160 It's kind of like the next chapter in the human story. 430 00:14:03,160 --> 00:14:03,800 Exactly. 431 00:14:03,800 --> 00:14:06,280 And who knows what amazing things we'll create together. 432 00:14:06,280 --> 00:14:08,360 Well, this has been an incredible deep dive. 433 00:14:08,360 --> 00:14:11,040 We've covered so much ground from the technical stuff 434 00:14:11,040 --> 00:14:12,360 to the philosophical stuff. 435 00:14:12,360 --> 00:14:13,440 And everything in between. 436 00:14:13,440 --> 00:14:15,240 It's been mind blowing, to be honest, 437 00:14:15,240 --> 00:14:17,240 and a little bit scary at times. 438 00:14:17,240 --> 00:14:18,040 I know what you mean. 439 00:14:18,040 --> 00:14:19,040 It's a lot to process. 440 00:14:19,040 --> 00:14:21,440 But I think it's important that we have these conversations, 441 00:14:21,440 --> 00:14:23,560 that we start thinking about these issues now. 442 00:14:23,560 --> 00:14:26,400 Because the future is coming, whether we're ready for it or not. 443 00:14:26,400 --> 00:14:27,840 And it's up to us to shape it. 444 00:14:27,840 --> 00:14:28,480 Exactly. 445 00:14:28,480 --> 00:14:31,000 We have the power to create the future we want. 446 00:14:31,000 --> 00:14:33,400 A future where AI is used for good, 447 00:14:33,400 --> 00:14:35,520 to make the world a better place for everyone. 448 00:14:35,520 --> 00:14:36,360 That's the goal, right? 449 00:14:36,360 --> 00:14:39,200 To use our intelligence, both human and artificial, 450 00:14:39,200 --> 00:14:40,560 to build a brighter future. 451 00:14:40,560 --> 00:14:42,960 And on that note, I think it's time to wrap up this deep dive. 452 00:14:42,960 --> 00:14:45,600 Thank you for joining us on this incredible journey 453 00:14:45,600 --> 00:14:47,080 into the world of AI. 454 00:14:47,080 --> 00:14:49,440 We hope you learned something that you're inspired 455 00:14:49,440 --> 00:14:51,240 and maybe even a little bit terrified. 456 00:14:51,240 --> 00:14:51,840 Ha, ha, ha. 457 00:14:51,840 --> 00:14:54,120 Yeah, the healthy dose of fear is always good. 458 00:14:54,120 --> 00:14:55,080 Keeps us on our toes. 459 00:14:55,080 --> 00:14:57,880 But seriously, this is just the beginning of the conversation. 460 00:14:57,880 --> 00:15:00,440 And we encourage you to keep exploring, keep learning, 461 00:15:00,440 --> 00:15:02,200 and keep asking the big questions. 462 00:15:02,200 --> 00:15:05,680 Because the future of AI is the future of humanity. 463 00:15:05,680 --> 00:15:26,440 And it's up to all of us to shape it.