1 00:00:00,000 --> 00:00:02,840 Welcome to the Daily AI News Podcast. 2 00:00:02,840 --> 00:00:04,540 We're doing a deep dive today. 3 00:00:04,540 --> 00:00:05,380 Oh, cool. 4 00:00:05,380 --> 00:00:07,440 And do a whole bunch of recent AI developments. 5 00:00:07,440 --> 00:00:08,280 Awesome. 6 00:00:08,280 --> 00:00:12,160 We've got articles, industry trends, expert opinions, 7 00:00:12,160 --> 00:00:15,760 new product releases, and even how AI 8 00:00:15,760 --> 00:00:17,200 is shaping political policy. 9 00:00:17,200 --> 00:00:19,680 Wow, that's a lot. 10 00:00:19,680 --> 00:00:20,520 It is. 11 00:00:20,520 --> 00:00:21,360 Well, that's a lot to cover. 12 00:00:21,360 --> 00:00:23,440 Get ready because things are moving fast. 13 00:00:23,440 --> 00:00:24,280 Yeah. 14 00:00:24,280 --> 00:00:25,600 And you won't want to miss these insights. 15 00:00:25,600 --> 00:00:26,440 Absolutely. 16 00:00:26,440 --> 00:00:28,040 It's a whirlwind of activity. 17 00:00:28,040 --> 00:00:28,880 Yeah. 18 00:00:28,880 --> 00:00:30,600 Let's break it down. 19 00:00:30,600 --> 00:00:32,480 See what's really worth paying attention to. 20 00:00:32,480 --> 00:00:34,600 So let's start with a little reality check. 21 00:00:34,600 --> 00:00:38,120 We keep hearing about AI's like exponential growth. 22 00:00:38,120 --> 00:00:42,280 But Google's CEO, Sundar Pichai, recently 23 00:00:42,280 --> 00:00:46,360 hinted at a possible slowdown at the New York Times 24 00:00:46,360 --> 00:00:47,440 Dealbook Summit. 25 00:00:47,440 --> 00:00:48,160 Interesting. 26 00:00:48,160 --> 00:00:51,600 He suggested that the low hanging fruit might be gone. 27 00:00:51,600 --> 00:00:53,080 So what do you think he means by that? 28 00:00:53,080 --> 00:00:55,560 Well, I think his perspective is that the initial wave 29 00:00:55,560 --> 00:00:59,880 of AI applications, they focused on more readily 30 00:00:59,880 --> 00:01:03,600 solvable problems, like image recognition or basic language 31 00:01:03,600 --> 00:01:04,640 translation. 32 00:01:04,640 --> 00:01:07,920 But now the challenges lie in areas 33 00:01:07,920 --> 00:01:11,840 that require a deeper, more nuanced understanding. 34 00:01:11,840 --> 00:01:13,600 Things like common sense reasoning 35 00:01:13,600 --> 00:01:14,760 or emotional intelligence. 36 00:01:14,760 --> 00:01:15,360 OK. 37 00:01:15,360 --> 00:01:16,480 Yeah, that makes sense. 38 00:01:16,480 --> 00:01:20,200 And this shift demands a different kind of innovation, 39 00:01:20,200 --> 00:01:24,960 one that goes beyond simply scaling up existing models. 40 00:01:24,960 --> 00:01:29,040 So it's not necessarily that progress is halting, 41 00:01:29,040 --> 00:01:32,040 but rather that the nature of the progress is changing. 42 00:01:32,040 --> 00:01:32,960 Exactly. 43 00:01:32,960 --> 00:01:38,920 And we're likely to see a shift from dramatic breakthroughs 44 00:01:38,920 --> 00:01:42,000 to more incremental advancements, 45 00:01:42,000 --> 00:01:43,520 at least for the time being. 46 00:01:43,520 --> 00:01:45,520 And this could have a big impact on the investments 47 00:01:45,520 --> 00:01:46,480 pouring into the field. 48 00:01:46,480 --> 00:01:47,080 Absolutely. 49 00:01:47,080 --> 00:01:49,880 Speaking of investments, Goldman Sachs recently 50 00:01:49,880 --> 00:01:55,760 projected that AI investments could exceed $1 trillion 51 00:01:55,760 --> 00:01:56,760 in the coming years. 52 00:01:56,760 --> 00:01:57,840 That's a lot of money. 53 00:01:57,840 --> 00:01:59,680 With that kind of money at stake. 54 00:01:59,680 --> 00:02:02,400 There's a lot riding on AI's continued progress, right? 55 00:02:02,400 --> 00:02:04,040 Oh, absolutely. 56 00:02:04,040 --> 00:02:06,760 Those investments are going to shape the entire tech 57 00:02:06,760 --> 00:02:10,480 landscape, which ultimately impacts you directly. 58 00:02:10,480 --> 00:02:14,800 Think about the devices you use, the services you rely on, 59 00:02:14,800 --> 00:02:15,760 the way you work. 60 00:02:15,760 --> 00:02:16,760 It's going to change everything. 61 00:02:16,760 --> 00:02:19,240 AI is going to influence all of that. 62 00:02:19,240 --> 00:02:21,320 And that brings up an interesting point. 63 00:02:21,320 --> 00:02:25,320 The impact of AI isn't just about technological advancement. 64 00:02:25,320 --> 00:02:28,480 It's about the societal and ethical implications as well. 65 00:02:28,480 --> 00:02:29,480 Exactly. 66 00:02:29,480 --> 00:02:32,240 And speaking of ethical implications, 67 00:02:32,240 --> 00:02:34,240 some pretty prominent voices have 68 00:02:34,240 --> 00:02:38,120 been raising concerns about the potential dangers 69 00:02:38,120 --> 00:02:40,120 of unchecked AI development. 70 00:02:40,120 --> 00:02:40,840 Interesting. 71 00:02:40,840 --> 00:02:45,720 This year, Nobel Prize winners Jeffrey Hinton and Demis 72 00:02:45,720 --> 00:02:50,080 Hassabis issued a call for strong AI regulation. 73 00:02:50,080 --> 00:02:52,520 So Hinton is known for his work in physics. 74 00:02:52,520 --> 00:02:53,200 Yes. 75 00:02:53,200 --> 00:02:55,000 And Hassabis for chemistry. 76 00:02:55,000 --> 00:02:55,640 Right. 77 00:02:55,640 --> 00:02:57,080 So that's significant coming from that. 78 00:02:57,080 --> 00:02:57,720 It really is. 79 00:02:57,720 --> 00:02:59,640 They highlighted several key concerns. 80 00:02:59,640 --> 00:03:00,200 Well, were they? 81 00:03:00,200 --> 00:03:03,000 Including the potential for an AI arms race. 82 00:03:03,000 --> 00:03:03,560 Oh, wow. 83 00:03:03,560 --> 00:03:05,880 The possibility of existential threats 84 00:03:05,880 --> 00:03:08,880 posed by super intelligent AI. 85 00:03:08,880 --> 00:03:09,920 That sounds scary. 86 00:03:09,920 --> 00:03:11,320 It is a bit unsettling. 87 00:03:11,320 --> 00:03:11,800 Yeah. 88 00:03:11,800 --> 00:03:15,400 And also just the challenges of regulating a field. 89 00:03:15,400 --> 00:03:16,000 Right. 90 00:03:16,000 --> 00:03:17,640 That evolve so rapidly. 91 00:03:17,640 --> 00:03:18,840 You change it so fast. 92 00:03:18,840 --> 00:03:21,200 They're not just talking about some distant future. 93 00:03:21,200 --> 00:03:21,720 OK. 94 00:03:21,720 --> 00:03:25,560 These are imminent concerns that need to be addressed now. 95 00:03:25,560 --> 00:03:29,680 And they emphasize the need for fast and nimble regulations. 96 00:03:29,680 --> 00:03:30,720 Exactly. 97 00:03:30,720 --> 00:03:31,520 Why is that? 98 00:03:31,520 --> 00:03:34,240 Well, traditional regulatory frameworks 99 00:03:34,240 --> 00:03:35,680 can be slow and cumbersome. 100 00:03:35,680 --> 00:03:36,120 Yeah. 101 00:03:36,120 --> 00:03:38,600 And by the time they catch up, the technology 102 00:03:38,600 --> 00:03:40,520 has already moved on. 103 00:03:40,520 --> 00:03:41,200 It's already on. 104 00:03:41,200 --> 00:03:44,600 They argue that we need to learn from existing regulations 105 00:03:44,600 --> 00:03:46,920 in fields like health care and transportation, 106 00:03:46,920 --> 00:03:49,600 adapting them quickly to the specific challenges. 107 00:03:49,600 --> 00:03:50,560 So we need to be flexible. 108 00:03:50,560 --> 00:03:51,040 Exactly. 109 00:03:51,040 --> 00:03:54,320 We need continuous evaluation and adjustment, 110 00:03:54,320 --> 00:03:57,200 a much more dynamic approach to governance 111 00:03:57,200 --> 00:03:58,680 than we've seen in the past. 112 00:03:58,680 --> 00:04:01,160 So it sounds like there's this real tension 113 00:04:01,160 --> 00:04:04,720 between fostering innovation and ensuring safety. 114 00:04:04,720 --> 00:04:05,280 Absolutely. 115 00:04:05,280 --> 00:04:06,640 We want to encourage the development 116 00:04:06,640 --> 00:04:07,960 of these powerful technologies. 117 00:04:07,960 --> 00:04:08,400 Right. 118 00:04:08,400 --> 00:04:10,360 But we need to make sure they're not going to run amok. 119 00:04:10,360 --> 00:04:11,040 Exactly. 120 00:04:11,040 --> 00:04:13,280 And finding that balance is going to be 121 00:04:13,280 --> 00:04:16,400 one of the defining challenges of the AI era. 122 00:04:16,400 --> 00:04:20,400 Now, shifting focus from the broader issues of regulation 123 00:04:20,400 --> 00:04:24,800 and safety, let's dive into a specific problem that's 124 00:04:24,800 --> 00:04:26,680 been plaguing AI development. 125 00:04:26,680 --> 00:04:27,280 What's that? 126 00:04:27,280 --> 00:04:28,240 Reliability. 127 00:04:28,240 --> 00:04:29,520 Oh, yeah. 128 00:04:29,520 --> 00:04:32,760 We've seen incredible advancements in generative AI. 129 00:04:32,760 --> 00:04:33,400 For sure. 130 00:04:33,400 --> 00:04:36,280 But these systems still struggle with hallucinations. 131 00:04:36,280 --> 00:04:36,520 Right. 132 00:04:36,520 --> 00:04:37,920 They essentially make things up. 133 00:04:37,920 --> 00:04:41,720 And often, even their creators don't fully 134 00:04:41,720 --> 00:04:44,480 understand how they arrive at their outputs. 135 00:04:44,480 --> 00:04:46,240 It's a bit of a black box. 136 00:04:46,240 --> 00:04:49,520 This lack of transparency and reliability, 137 00:04:49,520 --> 00:04:51,400 it's a major roadblock. 138 00:04:51,400 --> 00:04:53,360 Definitely, especially when you consider 139 00:04:53,360 --> 00:04:56,440 the potential applications of AI in critical fields, 140 00:04:56,440 --> 00:04:57,800 like health care and finance. 141 00:04:57,800 --> 00:04:58,200 OK. 142 00:04:58,200 --> 00:05:01,040 You can't have an AI system diagnosing patients 143 00:05:01,040 --> 00:05:02,440 or managing investments. 144 00:05:02,440 --> 00:05:05,040 If it's prone to fabricating information, 145 00:05:05,040 --> 00:05:07,240 accuracy is paramount in these areas. 146 00:05:07,240 --> 00:05:09,520 So how do we make AI more reliable? 147 00:05:09,520 --> 00:05:09,800 Right. 148 00:05:09,800 --> 00:05:11,600 Well, there is one approach gaining traction. 149 00:05:11,600 --> 00:05:12,160 OK, what is it? 150 00:05:12,160 --> 00:05:14,320 That's particularly intriguing. 151 00:05:14,320 --> 00:05:16,600 Neurosymbolic AI. 152 00:05:16,600 --> 00:05:18,080 Neurosymbolic AI. 153 00:05:18,080 --> 00:05:18,600 What is that? 154 00:05:18,600 --> 00:05:21,360 It aims to combine the intuitive pattern recognition 155 00:05:21,360 --> 00:05:25,880 of deep learning with the logical reasoning of symbolic AI. 156 00:05:25,880 --> 00:05:29,360 So instead of just crunching data and spitting out results, 157 00:05:29,360 --> 00:05:33,840 Neurosymbolic AI tries to incorporate a more structured, 158 00:05:33,840 --> 00:05:37,280 rule-based approach to decision making. 159 00:05:37,280 --> 00:05:38,400 Precisely. 160 00:05:38,400 --> 00:05:40,600 And this hybrid approach is showing 161 00:05:40,600 --> 00:05:42,040 some promising results. 162 00:05:42,040 --> 00:05:42,880 Like what? 163 00:05:42,880 --> 00:05:46,840 For instance, IBM has been using Neurosymbolic AI 164 00:05:46,840 --> 00:05:50,800 to provide more reasoned answers to image-based queries. 165 00:05:50,800 --> 00:05:51,320 OK. 166 00:05:51,320 --> 00:05:53,520 And Google has developed AI systems 167 00:05:53,520 --> 00:05:55,760 that can solve complex math problems 168 00:05:55,760 --> 00:05:58,320 by combining neural language models 169 00:05:58,320 --> 00:05:59,880 with symbolic deduction engines. 170 00:05:59,880 --> 00:06:00,720 Interesting. 171 00:06:00,720 --> 00:06:03,080 So how does this tie into the issue of reliability? 172 00:06:03,080 --> 00:06:04,480 Yeah, how does it? 173 00:06:04,480 --> 00:06:07,080 Well, by combining these two approaches, 174 00:06:07,080 --> 00:06:11,520 Neurosymbolic AI aims to achieve the best of both worlds, 175 00:06:11,520 --> 00:06:13,640 the learning power of neural networks, 176 00:06:13,640 --> 00:06:17,920 and the explainability and logical reasoning of symbolic AI. 177 00:06:17,920 --> 00:06:18,420 I see. 178 00:06:18,420 --> 00:06:21,680 This could be crucial for building AI systems that 179 00:06:21,680 --> 00:06:25,000 are not only capable but also accountable and transparent. 180 00:06:25,000 --> 00:06:26,960 So it's not just about getting the right answer. 181 00:06:26,960 --> 00:06:31,760 It's about understanding how the AI arrived at that answer. 182 00:06:31,760 --> 00:06:32,320 Exactly. 183 00:06:32,320 --> 00:06:34,960 And being able to trust its reasoning process. 184 00:06:34,960 --> 00:06:38,280 And that's essential if we want to deploy AI in high stakes 185 00:06:38,280 --> 00:06:41,840 fields where reliability is non-negotiable. 186 00:06:41,840 --> 00:06:44,000 Now continuing on this theme of reliability, 187 00:06:44,000 --> 00:06:45,840 let's look at a specific company that's 188 00:06:45,840 --> 00:06:47,480 making strides in this area. 189 00:06:47,480 --> 00:06:48,840 Sounds good. 190 00:06:48,840 --> 00:06:55,120 LG recently released Exxon 3.5, an open-sourced AI model 191 00:06:55,120 --> 00:06:58,360 that takes a unique multi-model approach. 192 00:06:58,360 --> 00:06:59,520 Multi-model approach. 193 00:06:59,520 --> 00:07:00,400 What's interesting about that? 194 00:07:00,400 --> 00:07:02,040 They've developed a range of models 195 00:07:02,040 --> 00:07:05,480 from an ultra-lightweight version designed for use 196 00:07:05,480 --> 00:07:09,520 on devices to a high-performance model for specialized tasks. 197 00:07:09,520 --> 00:07:12,280 So this versatility allows it to be used 198 00:07:12,280 --> 00:07:14,360 across a wide range of applications. 199 00:07:14,360 --> 00:07:14,880 Right. 200 00:07:14,880 --> 00:07:15,600 Interesting. 201 00:07:15,600 --> 00:07:18,080 And they've also implemented some interesting features 202 00:07:18,080 --> 00:07:20,840 to improve the model's reliability. 203 00:07:20,840 --> 00:07:21,520 Like what? 204 00:07:21,520 --> 00:07:24,680 They're utilizing Advanced Retrieval Augmented Generation, 205 00:07:24,680 --> 00:07:26,880 or AGE technology. 206 00:07:26,880 --> 00:07:32,760 This allows Exxon 1.3.5 to access and process information 207 00:07:32,760 --> 00:07:36,120 from real-time web searches and uploaded documents, 208 00:07:36,120 --> 00:07:39,640 ensuring that its responses are grounded in factual data. 209 00:07:39,640 --> 00:07:41,520 So they're trying to prevent those hallucinations 210 00:07:41,520 --> 00:07:42,800 that we talked about earlier. 211 00:07:42,800 --> 00:07:46,000 By giving the AI access to a wider pool of information. 212 00:07:46,000 --> 00:07:46,920 Exactly. 213 00:07:46,920 --> 00:07:48,360 And they've also implemented something 214 00:07:48,360 --> 00:07:50,040 called multi-step reasoning. 215 00:07:50,040 --> 00:07:51,200 Multi-step reasoning. 216 00:07:51,200 --> 00:07:54,560 And this encourages the AI to break down complex questions 217 00:07:54,560 --> 00:07:57,400 into smaller, manageable steps, leading 218 00:07:57,400 --> 00:08:00,600 to more logical and accurate answers. 219 00:08:00,600 --> 00:08:02,360 So it sounds like LG is really committed 220 00:08:02,360 --> 00:08:05,160 to addressing the reliability issue. 221 00:08:05,160 --> 00:08:05,840 Yeah, they are. 222 00:08:05,840 --> 00:08:08,160 And they're not just focusing on research and development. 223 00:08:08,160 --> 00:08:09,480 They're actually putting their AI 224 00:08:09,480 --> 00:08:11,080 to work within their own company. 225 00:08:11,080 --> 00:08:11,440 Yeah. 226 00:08:11,440 --> 00:08:14,920 They developed an enterprise AI agent called Chardex-01. 227 00:08:14,920 --> 00:08:15,640 It's pretty cool. 228 00:08:15,640 --> 00:08:19,640 Which is being rolled out to LG employees 229 00:08:19,640 --> 00:08:22,000 to boost productivity and efficiency. 230 00:08:22,000 --> 00:08:25,000 So think about the implications for your workplace. 231 00:08:25,000 --> 00:08:25,680 Right. 232 00:08:25,680 --> 00:08:29,760 How could AI tools like this change the way you work? 233 00:08:29,760 --> 00:08:31,800 It's like a glimpse into the future of work. 234 00:08:31,800 --> 00:08:32,320 It is. 235 00:08:32,320 --> 00:08:35,320 Where AI seamlessly integrates into our daily routines. 236 00:08:35,320 --> 00:08:35,960 Exactly. 237 00:08:35,960 --> 00:08:39,240 Taking on repetitive tasks and augmenting our capabilities. 238 00:08:39,240 --> 00:08:41,400 LG is really invested in this vision. 239 00:08:41,400 --> 00:08:41,920 They are. 240 00:08:41,920 --> 00:08:44,920 They've been aggressively pursuing AI advancements. 241 00:08:44,920 --> 00:08:48,880 Forming partnerships with industry leaders like AWS, 242 00:08:48,880 --> 00:08:51,840 Dell Technologies, Google Cloud, 243 00:08:51,840 --> 00:08:54,440 and NVIDIA to expand their AI ecosystem. 244 00:08:54,440 --> 00:08:56,040 Sounds like they're getting big on AI. 245 00:08:56,040 --> 00:08:57,000 They are. 246 00:08:57,000 --> 00:08:59,640 Both in terms of internal applications and broader 247 00:08:59,640 --> 00:09:00,840 industry collaboration. 248 00:09:00,840 --> 00:09:01,800 Absolutely. 249 00:09:01,800 --> 00:09:06,400 They see AI as a key driver of future innovation and growth. 250 00:09:06,400 --> 00:09:10,280 LG's President Bae Kyunghoon envisions a future 251 00:09:10,280 --> 00:09:13,000 where we have artificial super intelligence that 252 00:09:13,000 --> 00:09:14,920 can be applied to real world industries. 253 00:09:14,920 --> 00:09:16,120 That's a bold vision. 254 00:09:16,120 --> 00:09:16,840 It is. 255 00:09:16,840 --> 00:09:18,120 It raises some interesting questions 256 00:09:18,120 --> 00:09:19,560 about the long term implications. 257 00:09:19,560 --> 00:09:20,320 For sure. 258 00:09:20,320 --> 00:09:20,960 Of AI. 259 00:09:20,960 --> 00:09:21,720 Yeah. 260 00:09:21,720 --> 00:09:26,760 But for now, let's shift gears to a different sector where AI 261 00:09:26,760 --> 00:09:28,640 is starting to make waves. 262 00:09:28,640 --> 00:09:29,400 Where's that? 263 00:09:29,400 --> 00:09:30,080 Education. 264 00:09:30,080 --> 00:09:31,040 Of course. 265 00:09:31,040 --> 00:09:34,080 A fascinating development is happening at UCLA, 266 00:09:34,080 --> 00:09:37,760 where they're offering a comparative literature course 267 00:09:37,760 --> 00:09:39,200 with a unique twist. 268 00:09:39,200 --> 00:09:40,280 What is it? 269 00:09:40,280 --> 00:09:44,480 The textbook homework assignments and TA resources 270 00:09:44,480 --> 00:09:48,400 are all generated by AI using a platform called Kudu. 271 00:09:48,400 --> 00:09:49,280 Really? 272 00:09:49,280 --> 00:09:54,200 Professor Zarynka Stuhljak, who spearheaded this initiative, 273 00:09:54,200 --> 00:09:58,160 sees it as a way to enhance the learning experience, not 274 00:09:58,160 --> 00:10:02,160 diminish it by leveraging AI to handle the more tedious aspects 275 00:10:02,160 --> 00:10:03,680 of course, preparation. 276 00:10:03,680 --> 00:10:06,440 She aims to free up more time for direct interaction 277 00:10:06,440 --> 00:10:07,320 with students. 278 00:10:07,320 --> 00:10:10,720 Focusing on teaching, mentoring, and engaging 279 00:10:10,720 --> 00:10:12,040 in meaningful discussions. 280 00:10:12,040 --> 00:10:13,920 So it sounds like she's trying to reimagine 281 00:10:13,920 --> 00:10:15,520 the role of the instructor. 282 00:10:15,520 --> 00:10:16,000 Exactly. 283 00:10:16,000 --> 00:10:19,960 Using AI as a tool to facilitate deeper engagement with students. 284 00:10:19,960 --> 00:10:23,560 But this raises questions about the potential impact 285 00:10:23,560 --> 00:10:24,440 on teaching roles. 286 00:10:24,440 --> 00:10:25,400 Of course. 287 00:10:25,400 --> 00:10:28,840 Will AI eventually replace human instructors? 288 00:10:28,840 --> 00:10:30,680 It's a valid concern. 289 00:10:30,680 --> 00:10:33,840 But it's important to remember that technology often 290 00:10:33,840 --> 00:10:37,640 acts as a catalyst for evolution, not eradication. 291 00:10:37,640 --> 00:10:40,360 Just as the printing press revolutionized 292 00:10:40,360 --> 00:10:43,040 the dissemination of knowledge without eliminating 293 00:10:43,040 --> 00:10:45,080 the need for teachers. 294 00:10:45,080 --> 00:10:48,480 Perhaps AI can reshape the educational landscape 295 00:10:48,480 --> 00:10:51,680 in ways that benefit both instructors and students. 296 00:10:51,680 --> 00:10:54,000 So instead of viewing AI as a threat, 297 00:10:54,000 --> 00:10:55,960 we should be thinking about how it 298 00:10:55,960 --> 00:10:59,240 can be used to enhance the educational experience 299 00:10:59,240 --> 00:11:00,080 for everyone involved. 300 00:11:00,080 --> 00:11:00,840 Exactly. 301 00:11:00,840 --> 00:11:03,000 It's about finding the right balance, 302 00:11:03,000 --> 00:11:05,880 using AI to augment human capabilities 303 00:11:05,880 --> 00:11:09,080 and create new possibilities for learning and growth. 304 00:11:09,080 --> 00:11:11,520 Now shifting focus from the classroom 305 00:11:11,520 --> 00:11:13,160 to the political arena. 306 00:11:13,160 --> 00:11:15,960 Donald Trump, the incoming president-elect, 307 00:11:15,960 --> 00:11:20,240 has appointed David Sacks as his crypto-AIsar. 308 00:11:20,240 --> 00:11:20,800 Interesting. 309 00:11:20,800 --> 00:11:22,240 This is a pretty significant role. 310 00:11:22,240 --> 00:11:22,840 It is. 311 00:11:22,840 --> 00:11:27,040 With the potential to shape how these technologies are 312 00:11:27,040 --> 00:11:28,320 regulated in the US. 313 00:11:28,320 --> 00:11:30,920 So what are your thoughts on this appointment? 314 00:11:30,920 --> 00:11:32,920 Definitely something to watch closely, 315 00:11:32,920 --> 00:11:35,600 especially given Sacks's background 316 00:11:35,600 --> 00:11:37,080 and stance on regulation. 317 00:11:37,080 --> 00:11:38,000 What's that? 318 00:11:38,000 --> 00:11:41,640 He's known for his regulatory skepticism, 319 00:11:41,640 --> 00:11:45,760 which could signal a more hands-off approach to AI 320 00:11:45,760 --> 00:11:47,520 governance under the Trump administration. 321 00:11:47,520 --> 00:11:51,080 So less regulation could lead to faster innovation 322 00:11:51,080 --> 00:11:52,080 and development? 323 00:11:52,080 --> 00:11:53,000 Yes. 324 00:11:53,000 --> 00:11:56,240 But it could also raise concerns about ethical considerations 325 00:11:56,240 --> 00:11:57,240 and potential risks. 326 00:11:57,240 --> 00:11:58,360 Exactly. 327 00:11:58,360 --> 00:12:01,760 The tension between fostering innovation 328 00:12:01,760 --> 00:12:05,600 and implementing safeguards is at the heart of this debate. 329 00:12:05,600 --> 00:12:08,080 Sacks' appointment could tilt the scales 330 00:12:08,080 --> 00:12:09,720 towards a lighter regulatory touch. 331 00:12:09,720 --> 00:12:11,520 Which will have a ripple effect. 332 00:12:11,520 --> 00:12:12,760 Throughout the AI industry. 333 00:12:12,760 --> 00:12:14,520 It'll be interesting to see how this plays out. 334 00:12:14,520 --> 00:12:17,920 And what impact it has on the development and deployment 335 00:12:17,920 --> 00:12:19,800 of AI technologies in the US. 336 00:12:19,800 --> 00:12:21,280 Absolutely. 337 00:12:21,280 --> 00:12:25,480 Now for our final topic in this section of our deep dive. 338 00:12:25,480 --> 00:12:28,880 Let's turn to the world of filmmaking, 339 00:12:28,880 --> 00:12:30,360 an industry that's been grappling 340 00:12:30,360 --> 00:12:31,840 with the implications of AI. 341 00:12:31,840 --> 00:12:32,840 Interesting. 342 00:12:32,840 --> 00:12:35,080 The Red Sea International Film Festival 343 00:12:35,080 --> 00:12:37,800 provided some valuable insights. 344 00:12:37,800 --> 00:12:42,400 Emphasizing the role of AI as a co-pilot tool for filmmakers. 345 00:12:42,400 --> 00:12:43,400 Co-pilot tool. 346 00:12:43,400 --> 00:12:44,320 What does that mean? 347 00:12:44,320 --> 00:12:48,600 The emerging consensus is that AI, at least in its current form, 348 00:12:48,600 --> 00:12:52,800 is best suited to enhance creativity, not replace it. 349 00:12:52,800 --> 00:12:54,920 So Chris Jackman from WME. 350 00:12:54,920 --> 00:12:55,640 Yes. 351 00:12:55,640 --> 00:12:59,760 Highlighted how their clients are using AI for tasks 352 00:12:59,760 --> 00:13:02,680 like creating mood boards, generating story outlines, 353 00:13:02,680 --> 00:13:04,560 and even experimenting with deep fakes. 354 00:13:04,560 --> 00:13:06,440 Like what Deep Voodoo did with Sassy Justice. 355 00:13:06,440 --> 00:13:08,280 It's a really interesting example. 356 00:13:08,280 --> 00:13:11,280 So instead of replacing human filmmakers, 357 00:13:11,280 --> 00:13:13,520 AI is being used to streamline certain aspects 358 00:13:13,520 --> 00:13:14,640 of the creative process. 359 00:13:14,640 --> 00:13:15,200 Exactly. 360 00:13:15,200 --> 00:13:18,240 Freeing up time and resources to focus on the core elements 361 00:13:18,240 --> 00:13:19,320 of storytelling. 362 00:13:19,320 --> 00:13:22,640 Of course, the question of job displacement remains a concern. 363 00:13:22,640 --> 00:13:24,800 It is, but the conversation seems 364 00:13:24,800 --> 00:13:28,920 to be shifting from fearing mass unemployment 365 00:13:28,920 --> 00:13:32,080 to anticipating a shift in skill sets and roles. 366 00:13:32,080 --> 00:13:32,920 That makes sense. 367 00:13:32,920 --> 00:13:36,840 Just as the transition from film to digital editing 368 00:13:36,840 --> 00:13:40,440 didn't eliminate editors that transform their work, 369 00:13:40,440 --> 00:13:44,200 AI's integration into filmmaking is likely to create new 370 00:13:44,200 --> 00:13:48,000 opportunities alongside some inevitable disruptions. 371 00:13:48,000 --> 00:13:49,680 So it's not necessarily a question of, 372 00:13:49,680 --> 00:13:53,360 will AI replace human filmmakers, 373 00:13:53,360 --> 00:13:57,320 but rather, how will AI change the nature of filmmaking 374 00:13:57,320 --> 00:13:59,680 and what new skills will be needed to thrive 375 00:13:59,680 --> 00:14:00,760 in this evolving landscape? 376 00:14:00,760 --> 00:14:02,040 Precisely. 377 00:14:02,040 --> 00:14:04,520 And the most successful filmmakers 378 00:14:04,520 --> 00:14:09,200 will likely be those who embrace AI as a creative partner, 379 00:14:09,200 --> 00:14:11,480 learning to leverage its capabilities 380 00:14:11,480 --> 00:14:13,840 to push the boundaries of storytelling. 381 00:14:13,840 --> 00:14:16,520 It sounds like we're entering a new era of filmmaking. 382 00:14:16,520 --> 00:14:17,000 It does. 383 00:14:17,000 --> 00:14:19,000 One where AI plays a significant role 384 00:14:19,000 --> 00:14:20,480 in shaping the creative process. 385 00:14:20,480 --> 00:14:23,040 And as with any technological revolution, 386 00:14:23,040 --> 00:14:25,040 there will be both challenges and opportunities 387 00:14:25,040 --> 00:14:26,160 along the way. 388 00:14:26,160 --> 00:14:29,160 It's a fascinating time to be following the world of AI. 389 00:14:29,160 --> 00:14:31,560 We've seen incredible advancements in recent years, 390 00:14:31,560 --> 00:14:32,960 but we're also starting to grapple 391 00:14:32,960 --> 00:14:35,480 with some of the more complex societal and ethical 392 00:14:35,480 --> 00:14:36,480 implications. 393 00:14:36,480 --> 00:14:38,160 It's like we're on a crossroads trying 394 00:14:38,160 --> 00:14:41,680 to figure out how to harness this powerful technology for good 395 00:14:41,680 --> 00:14:43,760 while mitigating the potential risks. 396 00:14:43,760 --> 00:14:45,640 And speaking of potential risks, let's 397 00:14:45,640 --> 00:14:49,400 circle back to those concerns raised by the Nobel laureates. 398 00:14:49,400 --> 00:14:51,880 The possibility of an AI arms race 399 00:14:51,880 --> 00:14:54,200 is particularly unsettling. 400 00:14:54,200 --> 00:14:55,600 It is a chilling thought. 401 00:14:55,600 --> 00:14:58,520 As AI systems become more sophisticated, 402 00:14:58,520 --> 00:15:00,360 the potential for them to be weaponized 403 00:15:00,360 --> 00:15:02,320 becomes a very real danger. 404 00:15:02,320 --> 00:15:03,840 We've already seen examples of AI 405 00:15:03,840 --> 00:15:06,000 being used in autonomous weapon systems, 406 00:15:06,000 --> 00:15:09,000 which raises serious ethical and humanitarian concerns. 407 00:15:09,000 --> 00:15:11,720 So how do we prevent this from spiraling out of control? 408 00:15:11,720 --> 00:15:14,120 That's where international cooperation and dialogue 409 00:15:14,120 --> 00:15:15,760 become absolutely crucial. 410 00:15:15,760 --> 00:15:17,640 We need global agreements and frameworks 411 00:15:17,640 --> 00:15:21,480 in place to prevent the misuse of AI for military purposes. 412 00:15:21,480 --> 00:15:24,280 The stakes are simply too high to ignore this threat. 413 00:15:24,280 --> 00:15:27,240 It's a daunting task, given the geopolitical complexities 414 00:15:27,240 --> 00:15:29,280 and competing national interests. 415 00:15:29,280 --> 00:15:31,280 But we have to find a way to work together to ensure 416 00:15:31,280 --> 00:15:34,880 that AI is used for peace, not for destruction. 417 00:15:34,880 --> 00:15:35,760 Absolutely. 418 00:15:35,760 --> 00:15:37,320 The future of humanity may very well 419 00:15:37,320 --> 00:15:40,680 depend on our ability to harness AI's potential for good 420 00:15:40,680 --> 00:15:43,080 while preventing its use for harm. 421 00:15:43,080 --> 00:15:44,840 Now shifting gears from the global stage 422 00:15:44,840 --> 00:15:46,840 to the individual level, we talked earlier 423 00:15:46,840 --> 00:15:51,160 about LG's open sourcing of their Excel in 3.5 model. 424 00:15:51,160 --> 00:15:53,560 Can you elaborate on why that's significant? 425 00:15:53,560 --> 00:15:55,480 LG's decision to open source their model 426 00:15:55,480 --> 00:15:58,360 is a notable step toward fostering a more inclusive AI 427 00:15:58,360 --> 00:15:59,440 landscape. 428 00:15:59,440 --> 00:16:01,760 By making their models available for research purposes, 429 00:16:01,760 --> 00:16:03,680 they're contributing to the collective knowledge 430 00:16:03,680 --> 00:16:05,400 and advancement of the field. 431 00:16:05,400 --> 00:16:07,320 It allows researchers and developers worldwide 432 00:16:07,320 --> 00:16:08,960 to build upon each other's work, which 433 00:16:08,960 --> 00:16:11,200 can accelerate progress significantly. 434 00:16:11,200 --> 00:16:13,880 It's a refreshing contrast to the more guarded approach 435 00:16:13,880 --> 00:16:15,800 that some companies take. 436 00:16:15,800 --> 00:16:18,160 Openness and collaboration seem essential if we 437 00:16:18,160 --> 00:16:19,960 want to see AI reach its full potential. 438 00:16:19,960 --> 00:16:21,040 Precisely. 439 00:16:21,040 --> 00:16:24,760 And it aligns with LG's broader vision of democratizing AI, 440 00:16:24,760 --> 00:16:27,040 making it accessible to a wider range of users, 441 00:16:27,040 --> 00:16:29,120 not just those within their own company. 442 00:16:29,120 --> 00:16:30,840 And speaking of their own company, 443 00:16:30,840 --> 00:16:33,000 it's worth noting that LG is also taking steps 444 00:16:33,000 --> 00:16:35,480 to ensure their internal AI tool. 445 00:16:35,480 --> 00:16:39,360 Chattis only prioritizes data security and privacy. 446 00:16:39,360 --> 00:16:41,880 This is especially important when you're talking about deploying 447 00:16:41,880 --> 00:16:43,720 AI within a corporate environment. 448 00:16:43,720 --> 00:16:45,000 Absolutely. 449 00:16:45,000 --> 00:16:47,680 With features like information encryption and privacy 450 00:16:47,680 --> 00:16:50,840 protection technology, they're demonstrating a commitment 451 00:16:50,840 --> 00:16:53,200 to responsible AI development. 452 00:16:53,200 --> 00:16:55,640 Employees need to feel confident that their information is 453 00:16:55,640 --> 00:16:58,760 being handled responsibly when AI tools are integrated 454 00:16:58,760 --> 00:17:00,320 into their workplaces. 455 00:17:00,320 --> 00:17:03,160 It seems like there's a growing awareness across the board 456 00:17:03,160 --> 00:17:06,280 of the need to balance innovation with responsibility. 457 00:17:06,280 --> 00:17:09,080 From Nobel laureates calling for robust regulation 458 00:17:09,080 --> 00:17:12,320 to companies like LG prioritizing data security, 459 00:17:12,320 --> 00:17:14,720 the ethical considerations are coming to the forefront. 460 00:17:14,720 --> 00:17:17,120 It's becoming increasingly clear that AI is not 461 00:17:17,120 --> 00:17:18,520 just a technological challenge. 462 00:17:18,520 --> 00:17:19,800 It's a societal one. 463 00:17:19,800 --> 00:17:22,320 The decisions we make now about its development and deployment 464 00:17:22,320 --> 00:17:24,120 will have far-reaching consequences. 465 00:17:24,120 --> 00:17:26,800 Continuing on this theme of responsible development, 466 00:17:26,800 --> 00:17:28,440 let's talk a bit more about those concerns 467 00:17:28,440 --> 00:17:30,480 regarding algorithmic bias. 468 00:17:30,480 --> 00:17:32,040 There's a risk that AI systems could 469 00:17:32,040 --> 00:17:35,040 perpetuate existing societal inequalities 470 00:17:35,040 --> 00:17:36,680 if they're not designed carefully. 471 00:17:36,680 --> 00:17:37,920 It's a real danger. 472 00:17:37,920 --> 00:17:40,280 AI algorithms are trained on data. 473 00:17:40,280 --> 00:17:42,680 And if that data reflects existing biases, 474 00:17:42,680 --> 00:17:45,680 the resulting AI systems can perpetuate and even 475 00:17:45,680 --> 00:17:47,360 amplify those biases. 476 00:17:47,360 --> 00:17:50,400 This can lead to unfair or discriminatory outcomes 477 00:17:50,400 --> 00:17:54,000 in areas like hiring lending and even criminal justice. 478 00:17:54,000 --> 00:17:55,480 So how do we address this issue? 479 00:17:55,480 --> 00:17:57,560 It requires a multi-pronged approach. 480 00:17:57,560 --> 00:17:59,280 We need diverse teams of developers 481 00:17:59,280 --> 00:18:00,760 who are sensitive to these issues. 482 00:18:00,760 --> 00:18:03,200 We need rigorous testing to identify and mitigate 483 00:18:03,200 --> 00:18:05,000 bias in AI systems. 484 00:18:05,000 --> 00:18:07,120 And we need ongoing monitoring to ensure 485 00:18:07,120 --> 00:18:09,880 that these systems are fair, equitable, and accountable. 486 00:18:09,880 --> 00:18:12,120 It sounds like it's not just about the technology itself, 487 00:18:12,120 --> 00:18:14,400 but also about the people and processes involved 488 00:18:14,400 --> 00:18:15,560 in developing and deploying it. 489 00:18:15,560 --> 00:18:16,280 Exactly. 490 00:18:16,280 --> 00:18:18,000 We need to bake fairness and equity 491 00:18:18,000 --> 00:18:21,200 into the very DNA of AI if we want it to benefit all 492 00:18:21,200 --> 00:18:22,120 of humanity. 493 00:18:22,120 --> 00:18:25,240 Now, shifting focus back to the realm of creative expression, 494 00:18:25,240 --> 00:18:28,080 we discussed AI's impact on filmmaking earlier. 495 00:18:28,080 --> 00:18:31,000 But its influence extends far beyond the silver screen. 496 00:18:31,000 --> 00:18:31,640 That's right. 497 00:18:31,640 --> 00:18:34,600 AI is making its presence felt in music composition, 498 00:18:34,600 --> 00:18:36,960 art generation writing, and even the creation 499 00:18:36,960 --> 00:18:39,080 of entirely new forms of creative expression 500 00:18:39,080 --> 00:18:40,560 that we haven't even imagined yet. 501 00:18:40,560 --> 00:18:43,240 It's blurring the lines between human and machine 502 00:18:43,240 --> 00:18:46,200 creativity, which is both exciting and unsettling. 503 00:18:46,200 --> 00:18:48,360 Some see it as a threat to human artistry, 504 00:18:48,360 --> 00:18:51,360 while others embrace it as an opportunity for collaboration 505 00:18:51,360 --> 00:18:52,320 and exploration. 506 00:18:52,320 --> 00:18:53,760 The key, as we've discussed before, 507 00:18:53,760 --> 00:18:57,480 is to approach AI as a tool for augmentation, not 508 00:18:57,480 --> 00:18:59,240 replacement. 509 00:18:59,240 --> 00:19:03,000 How can we leverage AI to enhance human creativity, 510 00:19:03,000 --> 00:19:05,560 to push the boundaries of artistic expression, 511 00:19:05,560 --> 00:19:08,080 and to create works that would be impossible without this 512 00:19:08,080 --> 00:19:10,040 collaboration between human and machine? 513 00:19:10,040 --> 00:19:11,840 That's the million dollar question. 514 00:19:11,840 --> 00:19:14,360 Artists, musicians, writers, and technologists 515 00:19:14,360 --> 00:19:16,000 are all grappling with these questions 516 00:19:16,000 --> 00:19:18,640 as they navigate this uncharted territory. 517 00:19:18,640 --> 00:19:19,960 And the answers they come up with 518 00:19:19,960 --> 00:19:23,120 are likely to be as diverse and innovative as the creative 519 00:19:23,120 --> 00:19:24,560 expressions themselves. 520 00:19:24,560 --> 00:19:26,680 It's a fascinating time to be witnessing 521 00:19:26,680 --> 00:19:29,640 this fusion of human and machine creativity. 522 00:19:29,640 --> 00:19:32,120 Who knows what incredible new art forms will emerge 523 00:19:32,120 --> 00:19:33,080 from this collaboration? 524 00:19:33,080 --> 00:19:34,960 The possibilities are endless, and that's 525 00:19:34,960 --> 00:19:36,640 what makes this field so exciting. 526 00:19:36,640 --> 00:19:38,480 Now let's turn our attention to a development that 527 00:19:38,480 --> 00:19:42,000 highlights both the potential and the challenges of AI 528 00:19:42,000 --> 00:19:44,280 in education. 529 00:19:44,280 --> 00:19:46,960 We touched on UCLA's AI-generated course earlier, 530 00:19:46,960 --> 00:19:49,560 but there are broader questions about how AI will shape 531 00:19:49,560 --> 00:19:50,800 the future of learning. 532 00:19:50,800 --> 00:19:54,160 It's a topic that's generating a lot of discussion and debate. 533 00:19:54,160 --> 00:19:56,520 Some see AI as a potential game changer, 534 00:19:56,520 --> 00:19:59,280 offering personalized learning experiences, 535 00:19:59,280 --> 00:20:02,160 automating tedious tasks, and providing valuable insights 536 00:20:02,160 --> 00:20:03,920 into student progress. 537 00:20:03,920 --> 00:20:05,840 Others worry about the potential for AI 538 00:20:05,840 --> 00:20:09,080 to dehumanize education to create a one size fits all 539 00:20:09,080 --> 00:20:12,240 approach and to exacerbate existing inequalities. 540 00:20:12,240 --> 00:20:14,880 So how do we navigate this complex landscape? 541 00:20:14,880 --> 00:20:17,320 How do we ensure that AI and education serves 542 00:20:17,320 --> 00:20:19,320 to enhance human learning and development, 543 00:20:19,320 --> 00:20:20,160 not undermine it? 544 00:20:20,160 --> 00:20:21,800 It's a delicate balance. 545 00:20:21,800 --> 00:20:24,320 We need to be mindful of the potential pitfalls while also 546 00:20:24,320 --> 00:20:25,960 embracing the opportunities. 547 00:20:25,960 --> 00:20:28,000 We need to think critically about how AI can be used 548 00:20:28,000 --> 00:20:30,200 to personalize learning to support teachers 549 00:20:30,200 --> 00:20:32,280 and to create more engaging and effective learning 550 00:20:32,280 --> 00:20:33,920 experiences for all students. 551 00:20:33,920 --> 00:20:35,960 It sounds like a collaborative effort is needed involving 552 00:20:35,960 --> 00:20:38,760 educators, technologists, policymakers, and students 553 00:20:38,760 --> 00:20:39,640 themselves. 554 00:20:39,640 --> 00:20:40,760 Absolutely. 555 00:20:40,760 --> 00:20:42,240 We need to work together to ensure 556 00:20:42,240 --> 00:20:45,560 that AI and education is implemented thoughtfully, 557 00:20:45,560 --> 00:20:48,560 ethically, and with a focus on empowering learners not 558 00:20:48,560 --> 00:20:50,120 replacing teachers. 559 00:20:50,120 --> 00:20:53,000 Now shifting gears from the classroom to the boardroom, 560 00:20:53,000 --> 00:20:56,560 let's talk about how AI is transforming the business world. 561 00:20:56,560 --> 00:20:59,560 We've already discussed LG's internal use of AI, 562 00:20:59,560 --> 00:21:02,560 but the impact goes far beyond any one company. 563 00:21:02,560 --> 00:21:05,480 AI is rapidly becoming a core part of how businesses 564 00:21:05,480 --> 00:21:06,960 operate and compete. 565 00:21:06,960 --> 00:21:09,760 From marketing automation and customer service chatbots 566 00:21:09,760 --> 00:21:12,880 to predictive analytics and supply chain optimization, 567 00:21:12,880 --> 00:21:15,960 AI is permeating virtually every aspect of business. 568 00:21:15,960 --> 00:21:18,960 And this trend is only going to accelerate as AI technology 569 00:21:18,960 --> 00:21:20,880 becomes more sophisticated and accessible. 570 00:21:20,880 --> 00:21:21,560 Exactly. 571 00:21:21,560 --> 00:21:24,200 Companies that embrace and effectively integrate AI 572 00:21:24,200 --> 00:21:26,240 are likely to outperform their competitors 573 00:21:26,240 --> 00:21:27,400 in the coming years. 574 00:21:27,400 --> 00:21:30,160 Those that lag behind risk being left in the dust. 575 00:21:30,160 --> 00:21:31,840 It's a digital arms race, in a sense, 576 00:21:31,840 --> 00:21:33,720 with AI as the weapon of choice. 577 00:21:33,720 --> 00:21:36,080 Perhaps not a weapon, but certainly a powerful tool 578 00:21:36,080 --> 00:21:38,360 that's reshaping the battlefield of business. 579 00:21:38,360 --> 00:21:40,000 And as with any powerful tool, there's 580 00:21:40,000 --> 00:21:42,880 a need for responsible use, ethical considerations, 581 00:21:42,880 --> 00:21:45,160 and a focus on long term value creation. 582 00:21:45,160 --> 00:21:45,760 Absolutely. 583 00:21:45,760 --> 00:21:47,520 It's not just about automating tasks 584 00:21:47,520 --> 00:21:48,840 and maximizing efficiency. 585 00:21:48,840 --> 00:21:52,120 It's about leveraging AI to create better products, 586 00:21:52,120 --> 00:21:54,120 deliver better services, and ultimately 587 00:21:54,120 --> 00:21:55,760 made a positive impact on the world. 588 00:21:55,760 --> 00:21:58,600 Now let's take a step back from the specific applications 589 00:21:58,600 --> 00:22:02,160 of AI and consider its broader societal implications. 590 00:22:02,160 --> 00:22:03,520 You're referring to the concerns 591 00:22:03,520 --> 00:22:05,920 about job displacement, the potential for bias 592 00:22:05,920 --> 00:22:08,080 and discrimination, the impact on privacy, 593 00:22:08,080 --> 00:22:11,160 and the ethical considerations surrounding AI decision making. 594 00:22:11,160 --> 00:22:12,120 Precisely. 595 00:22:12,120 --> 00:22:14,680 These are complex and multifaceted issues 596 00:22:14,680 --> 00:22:17,560 that require thoughtful and nuanced discussions. 597 00:22:17,560 --> 00:22:19,760 It's essential that we engage in these conversations 598 00:22:19,760 --> 00:22:22,640 proactively, involving diverse perspectives and voices 599 00:22:22,640 --> 00:22:24,720 to ensure that AI's development and deployment 600 00:22:24,720 --> 00:22:26,720 align with our shared values and goals. 601 00:22:26,720 --> 00:22:28,920 It's about striking a balance between harnessing 602 00:22:28,920 --> 00:22:31,160 the transformative potential of AI 603 00:22:31,160 --> 00:22:33,080 while mitigating its potential risks 604 00:22:33,080 --> 00:22:35,720 and ensuring its benefits are shared widely and equitably. 605 00:22:35,720 --> 00:22:36,480 Indeed. 606 00:22:36,480 --> 00:22:38,320 It's a challenging but crucial task, 607 00:22:38,320 --> 00:22:40,760 one that will require collaboration, innovation, 608 00:22:40,760 --> 00:22:43,360 and a commitment to putting human well-being at the forefront 609 00:22:43,360 --> 00:22:44,960 of our AI endeavors. 610 00:22:44,960 --> 00:22:46,320 That's a great point. 611 00:22:46,320 --> 00:22:49,600 We can't lose sight of the human element in all of this. 612 00:22:49,600 --> 00:22:52,520 AI should be a tool to empower humanity, 613 00:22:52,520 --> 00:22:54,400 not to replace or diminish it. 614 00:22:54,400 --> 00:22:56,280 I think that's the key takeaway from all 615 00:22:56,280 --> 00:22:57,240 of these developments. 616 00:22:57,240 --> 00:22:59,680 How do we ensure AI serves humanity? 617 00:22:59,680 --> 00:23:02,040 It's a question we need to be asking ourselves constantly 618 00:23:02,040 --> 00:23:02,960 as we move forward. 619 00:23:02,960 --> 00:23:03,320 Yeah. 620 00:23:03,320 --> 00:23:04,200 Well said. 621 00:23:04,200 --> 00:23:07,280 It can be easy to get caught up in the hype, the fear, 622 00:23:07,280 --> 00:23:09,880 or even just the sheer complexity of it all. 623 00:23:09,880 --> 00:23:12,120 But ultimately, it's about making choices that 624 00:23:12,120 --> 00:23:13,640 align with our values. 625 00:23:13,640 --> 00:23:16,520 Speaking of choices, let's dive into a specific example 626 00:23:16,520 --> 00:23:19,200 that highlights the complex interplay between AI 627 00:23:19,200 --> 00:23:21,080 and human creativity. 628 00:23:21,080 --> 00:23:24,080 Deep Voodoo, the company founded by the creators South Park, 629 00:23:24,080 --> 00:23:27,000 is doing some fascinating work with deep fake technology. 630 00:23:27,000 --> 00:23:27,600 Oh yeah. 631 00:23:27,600 --> 00:23:30,000 They're YouTube series, Sassy Justice. 632 00:23:30,000 --> 00:23:31,520 It's hilarious. 633 00:23:31,520 --> 00:23:33,400 But beyond the comedy, it also raises 634 00:23:33,400 --> 00:23:36,120 some thought-provoking questions about how AI can blur 635 00:23:36,120 --> 00:23:38,200 the lines between reality and fiction. 636 00:23:38,200 --> 00:23:39,080 Exactly. 637 00:23:39,080 --> 00:23:42,320 They're using AI to create incredibly realistic synthetic 638 00:23:42,320 --> 00:23:42,960 video footage. 639 00:23:42,960 --> 00:23:45,000 And they're doing it in a way that's both entertaining 640 00:23:45,000 --> 00:23:46,120 and thought-provoking. 641 00:23:46,120 --> 00:23:48,080 It makes you question what's real and what's not, 642 00:23:48,080 --> 00:23:50,040 which is a theme that's becoming increasingly 643 00:23:50,040 --> 00:23:51,600 relevant in the digital age. 644 00:23:51,600 --> 00:23:54,960 It definitely makes you think about the potential for misuse. 645 00:23:54,960 --> 00:23:57,920 Deep fakes could be used for all sorts of nefarious purposes, 646 00:23:57,920 --> 00:24:01,920 from spreading misinformation to manipulating public opinion. 647 00:24:01,920 --> 00:24:03,000 No doubt about it. 648 00:24:03,000 --> 00:24:05,960 As deep fake technology becomes more sophisticated 649 00:24:05,960 --> 00:24:09,520 and accessible, the potential for harm increases. 650 00:24:09,520 --> 00:24:11,960 It's a classic double-edged sword scenario, 651 00:24:11,960 --> 00:24:15,520 a powerful tool with the potential for both good and bad. 652 00:24:15,520 --> 00:24:17,080 So how do we navigate this? 653 00:24:17,080 --> 00:24:20,400 How do we foster the positive applications of deep fakes 654 00:24:20,400 --> 00:24:22,720 while safeguarding against the negative ones? 655 00:24:22,720 --> 00:24:25,080 It's a tough question, and there's no easy answer. 656 00:24:25,080 --> 00:24:27,800 It's going to require a multifaceted approach involving 657 00:24:27,800 --> 00:24:31,480 technical safeguards, ethical guidelines, media literacy, 658 00:24:31,480 --> 00:24:33,880 and a healthy dose of skepticism from the public. 659 00:24:33,880 --> 00:24:36,040 It's going to require all of us to be more discerning 660 00:24:36,040 --> 00:24:39,040 about the information we consume and to be more aware of the ways 661 00:24:39,040 --> 00:24:41,120 in which AI can be used to manipulate us. 662 00:24:41,120 --> 00:24:41,840 Absolutely. 663 00:24:41,840 --> 00:24:43,760 We need to develop a kind of AI literacy 664 00:24:43,760 --> 00:24:46,080 so that we can navigate this increasingly complex 665 00:24:46,080 --> 00:24:47,120 digital landscape. 666 00:24:47,120 --> 00:24:48,080 That's a great point. 667 00:24:48,080 --> 00:24:50,440 Now, shifting gears to a different but related topic, 668 00:24:50,440 --> 00:24:53,320 there's been growing concern about the potential for an AI arms 669 00:24:53,320 --> 00:24:53,880 race. 670 00:24:53,880 --> 00:24:56,200 Yes, and rightfully so. 671 00:24:56,200 --> 00:24:58,520 As AI systems become more sophisticated, 672 00:24:58,520 --> 00:25:00,840 there's a real danger that they could 673 00:25:00,840 --> 00:25:03,160 be used to develop autonomous weapons systems that 674 00:25:03,160 --> 00:25:06,000 can make life or death decisions without human intervention. 675 00:25:06,000 --> 00:25:07,720 It's a chilling thought. 676 00:25:07,720 --> 00:25:10,720 The idea of machines deciding who lives and who dies 677 00:25:10,720 --> 00:25:13,440 is straight out of a science fiction dystopia. 678 00:25:13,440 --> 00:25:15,400 And yet, it's a very real possibility 679 00:25:15,400 --> 00:25:16,320 that we need to confront. 680 00:25:16,320 --> 00:25:17,840 The development of autonomous weapons 681 00:25:17,840 --> 00:25:19,680 is already underway in several countries. 682 00:25:19,680 --> 00:25:22,160 And if we don't establish clear guidelines and regulations 683 00:25:22,160 --> 00:25:25,040 soon, it could have devastating consequences. 684 00:25:25,040 --> 00:25:25,960 So what can be done? 685 00:25:25,960 --> 00:25:27,920 International cooperation is key. 686 00:25:27,920 --> 00:25:29,960 We need to bring together governments, researchers, 687 00:25:29,960 --> 00:25:32,400 ethicists, and industry leaders to establish 688 00:25:32,400 --> 00:25:34,800 a global framework for the responsible development 689 00:25:34,800 --> 00:25:36,960 and deployment of AI, particularly when 690 00:25:36,960 --> 00:25:38,680 it comes to military applications. 691 00:25:38,680 --> 00:25:39,960 It's a tall order. 692 00:25:39,960 --> 00:25:42,440 But it's essential if we want to prevent a future where 693 00:25:42,440 --> 00:25:45,280 AI is used to fuel conflict and destruction. 694 00:25:45,280 --> 00:25:49,280 We need to ensure that AI is used for peace, not for war. 695 00:25:49,280 --> 00:25:51,080 And that requires a collective effort, 696 00:25:51,080 --> 00:25:52,720 a shared commitment to harnessing 697 00:25:52,720 --> 00:25:54,720 this powerful technology for good. 698 00:25:54,720 --> 00:25:55,920 Well said. 699 00:25:55,920 --> 00:25:59,360 It's a reminder that AI isn't just about algorithms and data. 700 00:25:59,360 --> 00:26:02,160 It's about choices, values. 701 00:26:02,160 --> 00:26:03,560 And the future we want to create. 702 00:26:03,560 --> 00:26:04,760 Exactly. 703 00:26:04,760 --> 00:26:06,520 And speaking of the future we want to create, 704 00:26:06,520 --> 00:26:09,200 let's shift gears to a more optimistic note. 705 00:26:09,200 --> 00:26:12,040 AI has the potential to revolutionize health care 706 00:26:12,040 --> 00:26:14,800 in countless ways, from improving diagnostics 707 00:26:14,800 --> 00:26:17,880 and drug discovery to personalizing treatment plans 708 00:26:17,880 --> 00:26:20,400 and providing more effective care for the elderly 709 00:26:20,400 --> 00:26:21,480 and disabled. 710 00:26:21,480 --> 00:26:24,000 The possibilities are incredibly exciting. 711 00:26:24,000 --> 00:26:26,840 Imagine a future where AI helps us live longer, healthier 712 00:26:26,840 --> 00:26:30,080 lives, where diseases are detected and treated earlier, 713 00:26:30,080 --> 00:26:32,360 and where health care is more accessible and affordable 714 00:26:32,360 --> 00:26:33,360 for everyone. 715 00:26:33,360 --> 00:26:35,360 It's a vision worth striving for. 716 00:26:35,360 --> 00:26:37,280 And we're already seeing glences of this future 717 00:26:37,280 --> 00:26:39,600 in the research and development that's happening right now. 718 00:26:39,600 --> 00:26:43,040 For example, AI is being used to develop new drugs and therapies 719 00:26:43,040 --> 00:26:45,240 at an unprecedented pace, potentially leading 720 00:26:45,240 --> 00:26:47,000 to breakthroughs in the treatment of cancer 721 00:26:47,000 --> 00:26:49,520 Alzheimer's and other debilitating diseases. 722 00:26:49,520 --> 00:26:50,440 That's amazing. 723 00:26:50,440 --> 00:26:52,520 And it's not just about developing new treatments. 724 00:26:52,520 --> 00:26:54,720 AI can also help us deliver existing treatments 725 00:26:54,720 --> 00:26:55,680 more effectively. 726 00:26:55,680 --> 00:26:56,480 Right. 727 00:26:56,480 --> 00:26:59,120 AI-powered tools can help doctors personalize treatment 728 00:26:59,120 --> 00:27:01,760 plans based on a patient's individual genetic makeup 729 00:27:01,760 --> 00:27:03,680 lifestyle and medical history. 730 00:27:03,680 --> 00:27:06,400 This can lead to better outcomes and fewer side effects. 731 00:27:06,400 --> 00:27:08,520 So instead of a one-size-fits-all approach, 732 00:27:08,520 --> 00:27:11,320 we're moving towards a more tailored, individualized 733 00:27:11,320 --> 00:27:12,320 approach to health care. 734 00:27:12,320 --> 00:27:13,000 Exactly. 735 00:27:13,000 --> 00:27:15,840 And AI is playing a key role in making that possible. 736 00:27:15,840 --> 00:27:17,560 It sounds like AI has the potential 737 00:27:17,560 --> 00:27:20,400 to truly transform health care for the better. 738 00:27:20,400 --> 00:27:22,560 But as with any powerful technology, 739 00:27:22,560 --> 00:27:24,880 there are also potential risks and challenges 740 00:27:24,880 --> 00:27:26,080 that we need to be mindful of. 741 00:27:26,080 --> 00:27:26,840 Absolutely. 742 00:27:26,840 --> 00:27:29,960 We need to be careful about data privacy algorithmic bias 743 00:27:29,960 --> 00:27:33,400 and the potential for over-reliance on AI systems. 744 00:27:33,400 --> 00:27:36,680 It's important that we use AI to augment human expertise, 745 00:27:36,680 --> 00:27:38,400 not replace it entirely. 746 00:27:38,400 --> 00:27:39,280 That's a crucial point. 747 00:27:39,280 --> 00:27:40,960 At the end of the day, health care is about people, 748 00:27:40,960 --> 00:27:42,120 and we can't lose sight of that. 749 00:27:42,120 --> 00:27:42,800 Well said. 750 00:27:42,800 --> 00:27:45,040 Technology should serve to enhance human connection 751 00:27:45,040 --> 00:27:46,920 and compassion, not replace it. 752 00:27:46,920 --> 00:27:50,000 Well, that was quite a deep dive into the world of AI. 753 00:27:50,000 --> 00:27:53,120 We covered a lot of ground today from the potential slowdown 754 00:27:53,120 --> 00:27:56,880 in AI development to the rise of neuro-symbolic AI, 755 00:27:56,880 --> 00:27:59,600 from the ethical implications of deep fakes 756 00:27:59,600 --> 00:28:02,600 to the transformative potential of AI in health care. 757 00:28:02,600 --> 00:28:05,280 It's a field that's constantly evolving, 758 00:28:05,280 --> 00:28:07,920 and it's fascinating to see how it's shaping our world 759 00:28:07,920 --> 00:28:09,560 in so many ways. 760 00:28:09,560 --> 00:28:12,240 What stood out to you the most from our conversation today? 761 00:28:12,240 --> 00:28:13,960 For me, it's the constant tension 762 00:28:13,960 --> 00:28:16,640 between the incredible potential of AI 763 00:28:16,640 --> 00:28:19,880 and the very real risks that we need to be mindful of. 764 00:28:19,880 --> 00:28:21,440 It's a balancing act, and we need 765 00:28:21,440 --> 00:28:24,120 to be thoughtful and deliberate about how we move forward. 766 00:28:24,120 --> 00:28:25,000 I agree. 767 00:28:25,000 --> 00:28:27,320 And it's a conversation that needs to involve everyone, 768 00:28:27,320 --> 00:28:29,160 not just the experts and policymakers. 769 00:28:29,160 --> 00:28:31,440 We all have a role to play in shaping the future of AI. 770 00:28:31,440 --> 00:28:31,920 Absolutely. 771 00:28:31,920 --> 00:28:34,400 We need to be informed, engaged, and willing 772 00:28:34,400 --> 00:28:36,000 to ask tough questions. 773 00:28:36,000 --> 00:28:37,640 The choices we make today will determine 774 00:28:37,640 --> 00:28:40,480 what kind of future we create with this powerful technology. 775 00:28:40,480 --> 00:28:41,440 Well said. 776 00:28:41,440 --> 00:28:44,040 And on that note, we've reached the end of our deep dive. 777 00:28:44,040 --> 00:28:46,640 Thanks for joining us on this exploration of the ever-evolving 778 00:28:46,640 --> 00:28:51,640 world of AI.