1 00:00:00,000 --> 00:00:03,260 Welcome to the Daily AI News Podcast. 2 00:00:03,260 --> 00:00:05,040 Today we're diving deep 3 00:00:05,040 --> 00:00:07,640 into a whole bunch of recent news articles, 4 00:00:07,640 --> 00:00:09,080 all about AI. 5 00:00:09,080 --> 00:00:11,040 Are you ready for some fascinating stories? 6 00:00:11,040 --> 00:00:12,240 I am, let's do it. 7 00:00:12,240 --> 00:00:14,360 Okay, first up we got OpenAI. 8 00:00:14,360 --> 00:00:15,200 All right. 9 00:00:15,200 --> 00:00:16,440 They just hired Gabor Kassell. 10 00:00:16,440 --> 00:00:17,280 Oh wow. 11 00:00:17,280 --> 00:00:18,440 Yeah, you know him right. 12 00:00:18,440 --> 00:00:19,520 Co-founder of Pebble. 13 00:00:19,520 --> 00:00:20,840 Yeah, the Twitter competitor. 14 00:00:20,840 --> 00:00:21,680 Exactly. 15 00:00:21,680 --> 00:00:22,520 It's a delicious thing. 16 00:00:22,520 --> 00:00:23,340 So what do you think this means? 17 00:00:23,340 --> 00:00:26,040 I mean, he's got this history of successful startups. 18 00:00:26,040 --> 00:00:28,560 Yeah, and that deep experience with social media 19 00:00:28,560 --> 00:00:31,560 makes you think maybe OpenAI is looking to expand 20 00:00:31,560 --> 00:00:36,080 into like AI-powered communication platforms, 21 00:00:36,080 --> 00:00:39,640 or even integrate AI into existing social experiences. 22 00:00:39,640 --> 00:00:40,880 Yeah, you think they might be developing 23 00:00:40,880 --> 00:00:42,120 their own platform. 24 00:00:42,120 --> 00:00:43,600 To rival Twitter. 25 00:00:43,600 --> 00:00:45,400 I mean, it's definitely possible, right? 26 00:00:45,400 --> 00:00:46,240 Yeah. 27 00:00:46,240 --> 00:00:47,080 Could be a big move. 28 00:00:47,080 --> 00:00:48,240 Huge, totally shake things up. 29 00:00:48,240 --> 00:00:49,080 For sure. 30 00:00:49,080 --> 00:00:50,560 And speaking of big moves, 31 00:00:50,560 --> 00:00:53,920 anthropic, they've recruited Alex Rodriguez. 32 00:00:53,920 --> 00:00:55,600 Oh wow, from Mark? 33 00:00:55,600 --> 00:00:57,120 The self-driving truck company. 34 00:00:57,120 --> 00:00:58,160 Yeah, I know them. 35 00:00:58,160 --> 00:01:01,360 Yeah, so he's focusing on AI safety research. 36 00:01:01,360 --> 00:01:02,920 That's right, at Anthropic. 37 00:01:02,920 --> 00:01:03,760 Interesting. 38 00:01:03,760 --> 00:01:05,520 So this seems like a pretty smart move. 39 00:01:05,520 --> 00:01:07,640 Oh, absolutely, especially with all the attention 40 00:01:07,640 --> 00:01:09,880 on responsible AI development. 41 00:01:09,880 --> 00:01:11,760 Right, AI is getting more powerful every day. 42 00:01:11,760 --> 00:01:12,600 It really is. 43 00:01:12,600 --> 00:01:15,120 So making sure it's used safely and ethically 44 00:01:15,120 --> 00:01:16,280 is super important. 45 00:01:16,280 --> 00:01:17,520 It is, and this guy, Rod Reg, 46 00:01:17,520 --> 00:01:20,040 is his background is in a field 47 00:01:20,040 --> 00:01:22,200 where safety is like paramount. 48 00:01:22,200 --> 00:01:23,600 Yeah, autonomous driving. 49 00:01:23,600 --> 00:01:24,440 Exactly. 50 00:01:24,440 --> 00:01:25,280 Makes sense. 51 00:01:25,280 --> 00:01:26,520 They want to build AI that's beneficial 52 00:01:26,520 --> 00:01:27,880 and safe for everyone. 53 00:01:27,880 --> 00:01:28,720 Totally. 54 00:01:28,720 --> 00:01:31,360 So continuing on with AI development, 55 00:01:31,360 --> 00:01:34,280 let's talk hardware, specifically NVIDIA. 56 00:01:34,280 --> 00:01:35,880 Ah, the big dogs. 57 00:01:35,880 --> 00:01:37,880 You know, there's CEO Jensen Wong. 58 00:01:37,880 --> 00:01:40,600 He asked SK Hynex to speed up delivery 59 00:01:40,600 --> 00:01:43,720 of their next gen HBM4 memory chips. 60 00:01:43,720 --> 00:01:44,560 Really? 61 00:01:44,560 --> 00:01:45,480 By how much? 62 00:01:45,480 --> 00:01:46,640 Six months. 63 00:01:46,640 --> 00:01:48,720 Wow, that's a huge ask. 64 00:01:48,720 --> 00:01:51,000 It is, it really shows how intense 65 00:01:51,000 --> 00:01:52,760 the demand for AI chips is. 66 00:01:52,760 --> 00:01:54,400 Yeah, I mean, for those who don't know, 67 00:01:54,400 --> 00:01:56,520 these HBM4 chips, they're designed 68 00:01:56,520 --> 00:01:59,400 for high performance computing, including AI. 69 00:01:59,400 --> 00:02:01,400 Right, NVIDIA, they want to get their hands on these chips. 70 00:02:01,400 --> 00:02:02,240 A-shape. 71 00:02:02,240 --> 00:02:03,060 Makes sense. 72 00:02:03,060 --> 00:02:05,040 They need them to power all those advanced AI systems. 73 00:02:05,040 --> 00:02:05,880 Exactly. 74 00:02:05,880 --> 00:02:07,480 So I think it's safe to say the race is on. 75 00:02:07,480 --> 00:02:11,040 Oh yeah, between SK Hynex, Samsung, Micron. 76 00:02:11,040 --> 00:02:11,920 All of them. 77 00:02:11,920 --> 00:02:13,480 They want to provide these chips 78 00:02:13,480 --> 00:02:15,560 that are essential for AI processing. 79 00:02:15,560 --> 00:02:16,400 Absolutely. 80 00:02:16,400 --> 00:02:18,640 They're all vying for dominance in this market. 81 00:02:18,640 --> 00:02:19,560 And we're seeing that play out 82 00:02:19,560 --> 00:02:20,880 in the financial markets too. 83 00:02:20,880 --> 00:02:21,720 How so? 84 00:02:21,720 --> 00:02:24,720 Well, NVIDIA, they just replaced Intel 85 00:02:24,720 --> 00:02:25,560 Oh wow. 86 00:02:25,560 --> 00:02:26,920 with what's called the Jones Industrial Average. 87 00:02:26,920 --> 00:02:29,360 That's a pretty symbolic shift. 88 00:02:29,360 --> 00:02:30,200 It is. 89 00:02:30,200 --> 00:02:32,000 It really highlights how the semiconductor industry 90 00:02:32,000 --> 00:02:35,800 is changing, driven by this whole AI revolution. 91 00:02:35,800 --> 00:02:37,820 So where do you think that leaves Intel? 92 00:02:37,820 --> 00:02:40,120 Well, they've been struggling a bit. 93 00:02:40,120 --> 00:02:40,960 Yeah. 94 00:02:40,960 --> 00:02:43,720 While NVIDIA's stock is skyrocketing. 95 00:02:43,720 --> 00:02:45,560 It's a reminder that even the biggest companies 96 00:02:45,560 --> 00:02:46,500 need to adapt. 97 00:02:46,500 --> 00:02:48,800 Yeah, they gotta innovate to stay relevant. 98 00:02:48,800 --> 00:02:50,380 For sure, especially in the face 99 00:02:50,380 --> 00:02:51,720 of technological disruption. 100 00:02:51,720 --> 00:02:52,880 Exactly. 101 00:02:52,880 --> 00:02:54,160 So let's shift gears a bit. 102 00:02:54,160 --> 00:02:55,000 Okay. 103 00:02:55,000 --> 00:02:57,320 Let's talk about what's happening over in the UAE. 104 00:02:57,320 --> 00:02:58,160 All right. 105 00:02:58,160 --> 00:03:00,120 Their national oil company, ADNOC. 106 00:03:00,120 --> 00:03:03,560 They're partnering with G42, Microsoft, 107 00:03:03,560 --> 00:03:05,000 and AIQ. 108 00:03:05,000 --> 00:03:05,840 Interesting. 109 00:03:05,840 --> 00:03:08,000 To implement something called agentic AI 110 00:03:08,000 --> 00:03:09,240 in the energy sector. 111 00:03:09,240 --> 00:03:11,320 Agentic AI, huh? 112 00:03:11,320 --> 00:03:12,160 That's new to me. 113 00:03:12,160 --> 00:03:14,720 So basically, these are AI systems 114 00:03:14,720 --> 00:03:17,560 that can operate really autonomously, 115 00:03:17,560 --> 00:03:20,160 making decisions and taking actions on their own. 116 00:03:20,160 --> 00:03:21,600 Based on real time data. 117 00:03:21,600 --> 00:03:22,440 Exactly. 118 00:03:22,440 --> 00:03:23,760 And predefined objectives. 119 00:03:23,760 --> 00:03:25,240 All right, so you can imagine these systems 120 00:03:25,240 --> 00:03:27,520 managing complex operations. 121 00:03:27,520 --> 00:03:28,360 Wow. 122 00:03:28,360 --> 00:03:29,320 Like in oil production. 123 00:03:29,320 --> 00:03:30,160 Yeah. 124 00:03:30,160 --> 00:03:31,640 Optimizing resource allocation. 125 00:03:31,640 --> 00:03:35,040 Maybe even predicting problems before they happen. 126 00:03:35,040 --> 00:03:36,040 That's pretty amazing. 127 00:03:36,040 --> 00:03:39,280 It's like having a super intelligent virtual manager. 128 00:03:39,280 --> 00:03:40,120 I know, right. 129 00:03:40,120 --> 00:03:42,240 Overseeing the entire operation. 130 00:03:42,240 --> 00:03:44,760 And this aligns perfectly with the UAE's 131 00:03:44,760 --> 00:03:46,400 larger push into AI. 132 00:03:46,400 --> 00:03:47,960 Oh yeah, they're investing a ton 133 00:03:47,960 --> 00:03:49,800 in AI research and development. 134 00:03:49,800 --> 00:03:51,520 Right, they're even creating Arabic 135 00:03:51,520 --> 00:03:53,520 and Hindi language chatbots. 136 00:03:53,520 --> 00:03:55,160 They're really going all in on this. 137 00:03:55,160 --> 00:03:56,000 They are. 138 00:03:56,000 --> 00:03:56,960 It's like they're setting themselves up 139 00:03:56,960 --> 00:03:59,160 to be a leader in the AI landscape. 140 00:03:59,160 --> 00:04:00,440 It's a smart move. 141 00:04:00,440 --> 00:04:01,280 It is. 142 00:04:01,280 --> 00:04:02,200 AI is not just a technology, 143 00:04:02,200 --> 00:04:04,720 it's a tool for economic transformation. 144 00:04:04,720 --> 00:04:05,680 Yeah, they see that. 145 00:04:05,680 --> 00:04:07,440 They're looking beyond oil 146 00:04:07,440 --> 00:04:10,400 and seeing AI as the key to their future. 147 00:04:10,400 --> 00:04:12,320 Okay, ready for a surprising connection? 148 00:04:12,320 --> 00:04:13,160 Always. 149 00:04:13,160 --> 00:04:17,680 Denmark just unveiled this new AI supercomputer. 150 00:04:17,680 --> 00:04:18,520 Okay. 151 00:04:18,520 --> 00:04:19,360 It's called Gefian. 152 00:04:19,360 --> 00:04:20,440 Gefian, huh? 153 00:04:20,440 --> 00:04:22,280 Yeah, it's a $100 million project 154 00:04:22,280 --> 00:04:23,680 packed with NVIDIA chips. 155 00:04:23,680 --> 00:04:24,520 Of course. 156 00:04:24,520 --> 00:04:26,240 And it's gonna empower Danish businesses 157 00:04:26,240 --> 00:04:28,600 and researchers in all kinds of fields. 158 00:04:28,600 --> 00:04:30,320 Like healthcare, biotech. 159 00:04:30,320 --> 00:04:31,960 Exactly, but here's the thing. 160 00:04:31,960 --> 00:04:32,800 What's that? 161 00:04:32,800 --> 00:04:37,600 It was partially funded by the Novo Nordisk Foundation. 162 00:04:37,600 --> 00:04:39,320 Wait, the one's behind a Zimpik? 163 00:04:39,320 --> 00:04:40,560 Yep, the weight loss drug. 164 00:04:40,560 --> 00:04:41,760 That's wild. 165 00:04:41,760 --> 00:04:43,200 I know, right? 166 00:04:43,200 --> 00:04:45,000 Talk about an unexpected connection. 167 00:04:45,000 --> 00:04:46,680 It never would have put those two together. 168 00:04:46,680 --> 00:04:49,200 It shows how advancements in one area 169 00:04:49,200 --> 00:04:51,040 can have these ripple effects in others. 170 00:04:51,040 --> 00:04:51,880 It really does. 171 00:04:51,880 --> 00:04:54,560 So the success of this pharmaceutical product 172 00:04:54,560 --> 00:04:56,800 has basically enabled Denmark 173 00:04:56,800 --> 00:04:59,960 to build this cutting edge AI infrastructure. 174 00:04:59,960 --> 00:05:01,720 It's amazing, and it's not just 175 00:05:01,720 --> 00:05:03,600 about the technology itself. 176 00:05:03,600 --> 00:05:06,440 It shows that governments and private organizations 177 00:05:06,440 --> 00:05:09,200 are recognizing the importance of AI. 178 00:05:09,200 --> 00:05:11,960 Yeah, they're investing in this kind of infrastructure 179 00:05:11,960 --> 00:05:14,440 to drive innovation and economic growth. 180 00:05:14,440 --> 00:05:16,800 And Denmark's approach with Gefian, 181 00:05:16,800 --> 00:05:19,320 it could be a model for other countries 182 00:05:19,320 --> 00:05:21,680 that wanna boost their own AI capabilities. 183 00:05:21,680 --> 00:05:24,360 Okay, so bringing it back to AI talent. 184 00:05:24,360 --> 00:05:25,200 All right. 185 00:05:25,200 --> 00:05:26,280 We talked about those big hires. 186 00:05:26,280 --> 00:05:28,280 Yeah, open AI and Anthropic. 187 00:05:28,280 --> 00:05:30,120 It really highlights the importance 188 00:05:30,120 --> 00:05:32,440 of leadership and AI adoption. 189 00:05:32,440 --> 00:05:33,400 Oh, absolutely. 190 00:05:33,400 --> 00:05:36,000 I was talking to our AI expert, Kurt Kendall, 191 00:05:36,000 --> 00:05:41,000 and he emphasized that we need bold leaders. 192 00:05:41,640 --> 00:05:42,480 Makes sense. 193 00:05:42,480 --> 00:05:45,920 And clear business use cases for AI. 194 00:05:45,920 --> 00:05:47,640 Yeah, too many companies are just jumping 195 00:05:47,640 --> 00:05:49,000 on the AI bandwagon. 196 00:05:49,000 --> 00:05:50,240 Right, without a real strategy. 197 00:05:50,240 --> 00:05:51,640 It's all hype, no substance. 198 00:05:51,640 --> 00:05:53,240 Exactly, he called it AI washing. 199 00:05:53,240 --> 00:05:54,080 Catchy. 200 00:05:54,080 --> 00:05:55,920 So Kendall's point is we need leaders 201 00:05:55,920 --> 00:05:59,040 who can see how AI can actually solve problems. 202 00:05:59,040 --> 00:06:00,800 Yeah, create value, drive growth. 203 00:06:00,800 --> 00:06:03,280 Right, it's not just about implementing the latest tech. 204 00:06:03,280 --> 00:06:05,040 It's about understanding its potential 205 00:06:05,040 --> 00:06:06,440 and using it strategically. 206 00:06:06,440 --> 00:06:07,280 Exactly. 207 00:06:07,280 --> 00:06:09,600 So now let's look at how AI is impacting healthcare. 208 00:06:09,600 --> 00:06:10,520 Okay. 209 00:06:10,520 --> 00:06:11,440 There's this partnership 210 00:06:11,440 --> 00:06:14,040 between Oxford Canabinoid Technologies. 211 00:06:14,040 --> 00:06:14,880 Oh, see you. 212 00:06:14,880 --> 00:06:16,080 Yeah, and Hypatia AI. 213 00:06:16,080 --> 00:06:17,000 I've heard of them. 214 00:06:17,000 --> 00:06:19,480 They were founded by an ex-Google engineer. 215 00:06:19,480 --> 00:06:21,040 You got it, David Gordon. 216 00:06:21,040 --> 00:06:21,880 Cool. 217 00:06:21,880 --> 00:06:24,960 So they're creating this AI-powered research assistant. 218 00:06:24,960 --> 00:06:26,400 Oh wow, what will it do? 219 00:06:26,400 --> 00:06:30,000 It can analyze massive amounts of scientific literature. 220 00:06:30,000 --> 00:06:32,960 That's incredible, especially for a company like OCT. 221 00:06:32,960 --> 00:06:35,040 Right, they have this huge library 222 00:06:35,040 --> 00:06:38,080 of over 500 cannabinoid derivatives. 223 00:06:38,080 --> 00:06:40,680 Yeah, this AI tool could help them uncover 224 00:06:40,680 --> 00:06:42,840 all sorts of potential within that library. 225 00:06:42,840 --> 00:06:44,480 Exactly, and their big goal 226 00:06:44,480 --> 00:06:47,040 is to develop non-addictive pain meds. 227 00:06:47,040 --> 00:06:49,240 Wow, that would be huge. 228 00:06:49,240 --> 00:06:51,800 It would, think about the impact on the opioid crisis. 229 00:06:51,800 --> 00:06:54,120 I know, it would be a game changer for so many people. 230 00:06:54,120 --> 00:06:55,920 Totally, this is a prime example 231 00:06:55,920 --> 00:06:57,800 of how AI can be used to address 232 00:06:57,800 --> 00:07:00,320 these really pressing societal challenges. 233 00:07:00,320 --> 00:07:02,320 Yeah, it's not just about creating new technologies, 234 00:07:02,320 --> 00:07:04,840 it's about using them to make a real difference. 235 00:07:04,840 --> 00:07:06,200 Absolutely, so we've talked a lot 236 00:07:06,200 --> 00:07:07,800 about the demand for AI chips. 237 00:07:07,800 --> 00:07:10,000 Right, and NVIDIA's kind of dominating the market. 238 00:07:10,000 --> 00:07:10,840 Well, get this, 239 00:07:10,840 --> 00:07:13,360 they're not just supplying chips for supercomputers. 240 00:07:13,360 --> 00:07:15,400 Hmm, what else are they up to? 241 00:07:15,400 --> 00:07:18,640 They're also a major player in drug discovery. 242 00:07:18,640 --> 00:07:19,480 Really? 243 00:07:19,480 --> 00:07:21,600 Yeah, they've partnered with recursion pharmaceuticals. 244 00:07:21,600 --> 00:07:22,440 Okay. 245 00:07:22,440 --> 00:07:25,520 And this company, they're using AI 246 00:07:25,520 --> 00:07:27,720 to identify potential drug candidates. 247 00:07:27,720 --> 00:07:29,640 For like a whole range of diseases. 248 00:07:29,640 --> 00:07:31,680 Yeah, they've built this massive biological 249 00:07:31,680 --> 00:07:32,800 and chemical data set. 250 00:07:32,800 --> 00:07:33,640 Wow. 251 00:07:33,640 --> 00:07:36,440 And they're using NVIDIA's AI platforms to analyze it all. 252 00:07:36,440 --> 00:07:39,600 So NVIDIA's not just providing the hardware, 253 00:07:39,600 --> 00:07:42,760 they're actively involved in the drug discovery process. 254 00:07:42,760 --> 00:07:43,600 Exactly. 255 00:07:43,600 --> 00:07:44,800 That's really smart. 256 00:07:44,800 --> 00:07:48,320 It is, it's a perfect example of how AI and big data 257 00:07:48,320 --> 00:07:50,040 are revolutionizing drug discovery. 258 00:07:50,040 --> 00:07:53,360 Yeah, it's making the whole process faster, more efficient. 259 00:07:53,360 --> 00:07:54,800 And hopefully more successful. 260 00:07:54,800 --> 00:07:55,640 Definitely. 261 00:07:55,640 --> 00:07:58,480 This is just another way NVIDIA is solidifying their position 262 00:07:58,480 --> 00:08:00,720 as a leader in the AI ecosystem. 263 00:08:00,720 --> 00:08:01,960 They're not just selling chips, 264 00:08:01,960 --> 00:08:04,120 they're enabling all these advancements 265 00:08:04,120 --> 00:08:05,720 across all these different sectors. 266 00:08:05,720 --> 00:08:07,600 They're providing the tools and expertise. 267 00:08:07,600 --> 00:08:10,560 Yeah, to help companies harness the power of AI. 268 00:08:10,560 --> 00:08:13,520 Okay, that's it for part one of our deep dive. 269 00:08:13,520 --> 00:08:14,360 Alrighty. 270 00:08:14,360 --> 00:08:15,480 We've covered a lot of ground, 271 00:08:15,480 --> 00:08:18,880 from talent and chips to the global impact of AI. 272 00:08:18,880 --> 00:08:21,440 It's incredible how fast this field is moving. 273 00:08:21,440 --> 00:08:22,560 It really is. 274 00:08:22,560 --> 00:08:23,400 But we're not done yet. 275 00:08:23,400 --> 00:08:24,240 Oh, good. 276 00:08:24,240 --> 00:08:25,760 In part two, we'll keep exploring 277 00:08:25,760 --> 00:08:27,520 how AI is shaping industries. 278 00:08:27,520 --> 00:08:28,520 Can't wait. 279 00:08:28,520 --> 00:08:31,600 With a closer look at energy, finance, and more. 280 00:08:31,600 --> 00:08:32,840 Sounds good. 281 00:08:32,840 --> 00:08:34,720 So we were talking about the UAE 282 00:08:34,720 --> 00:08:37,600 and their plans for agentic AI. 283 00:08:37,600 --> 00:08:39,560 Right, using it in oil production. 284 00:08:39,560 --> 00:08:41,440 It's a pretty cool example of how AI 285 00:08:41,440 --> 00:08:44,160 is like changing these old industries, you know? 286 00:08:44,160 --> 00:08:47,520 Yeah, imagine AI managing all these complex operations. 287 00:08:47,520 --> 00:08:48,360 Right. 288 00:08:48,360 --> 00:08:50,320 Making things more efficient, maybe even greener. 289 00:08:50,320 --> 00:08:51,160 Yeah, exactly. 290 00:08:51,160 --> 00:08:52,720 And it's not just oil production either. 291 00:08:52,720 --> 00:08:53,560 Oh, really? 292 00:08:53,560 --> 00:08:56,200 Yeah, AI is being used in renewable energy. 293 00:08:56,200 --> 00:08:57,040 Okay. 294 00:08:57,040 --> 00:08:59,680 Smart grids, even predicting energy consumption. 295 00:08:59,680 --> 00:09:02,120 So making the whole energy system smarter. 296 00:09:02,120 --> 00:09:03,440 Basically, yeah. 297 00:09:03,440 --> 00:09:04,280 That's pretty wild. 298 00:09:04,280 --> 00:09:06,840 All this focus on AI is really pushing things forward 299 00:09:06,840 --> 00:09:08,440 on the hardware side too. 300 00:09:08,440 --> 00:09:10,880 Absolutely, and we've talked about it before. 301 00:09:10,880 --> 00:09:14,080 That demand for AI chips is intense. 302 00:09:14,080 --> 00:09:15,680 It is, and in video. 303 00:09:15,680 --> 00:09:17,000 They're leading the pack, for sure. 304 00:09:17,000 --> 00:09:18,200 It's not just supercomputers either. 305 00:09:18,200 --> 00:09:19,040 Right. 306 00:09:19,040 --> 00:09:20,880 Like we said, they're also involved in drug discovery. 307 00:09:20,880 --> 00:09:22,920 With recursion pharmaceuticals. 308 00:09:22,920 --> 00:09:23,760 Exactly. 309 00:09:23,760 --> 00:09:25,560 It's amazing how their technology is being used 310 00:09:25,560 --> 00:09:26,720 in so many different areas. 311 00:09:26,720 --> 00:09:27,560 It really is. 312 00:09:27,560 --> 00:09:28,480 They're not just selling chips. 313 00:09:28,480 --> 00:09:30,120 They're actually driving these advancements 314 00:09:30,120 --> 00:09:31,360 across industries. 315 00:09:31,360 --> 00:09:32,840 Okay, so let's move on to finance. 316 00:09:32,840 --> 00:09:33,680 All right. 317 00:09:33,680 --> 00:09:34,720 AI is making a big impact there too. 318 00:09:34,720 --> 00:09:37,640 Oh yeah, we're seeing AI-powered trading platforms. 319 00:09:37,640 --> 00:09:38,640 Robo-advisors. 320 00:09:38,640 --> 00:09:40,320 Fraud detection systems. 321 00:09:40,320 --> 00:09:41,160 Oh, much potential. 322 00:09:41,160 --> 00:09:44,040 Well, the financial industry has always been about data. 323 00:09:44,040 --> 00:09:44,880 Right? 324 00:09:44,880 --> 00:09:45,700 Yeah, true. 325 00:09:45,700 --> 00:09:47,400 So it makes sense that they'd embrace AI. 326 00:09:47,400 --> 00:09:48,240 Yeah. 327 00:09:48,240 --> 00:09:51,000 These algorithms can analyze tons of data in real time. 328 00:09:51,000 --> 00:09:52,720 Way faster than any human could. 329 00:09:52,720 --> 00:09:54,840 So like an AI trading platform could make these 330 00:09:54,840 --> 00:09:56,960 split second decisions based on the market. 331 00:09:56,960 --> 00:09:59,480 Exactly, maximizing profits for investors. 332 00:09:59,480 --> 00:10:01,040 And then you have Robo-advisors. 333 00:10:01,040 --> 00:10:03,440 Right, giving personalized investment advice. 334 00:10:03,440 --> 00:10:05,760 Based on your goals and risk tolerance. 335 00:10:05,760 --> 00:10:08,360 Makes financial planning way more accessible. 336 00:10:08,360 --> 00:10:11,680 It does, but are there any downsides to all this? 337 00:10:11,680 --> 00:10:13,120 Well, there are some concerns, yeah. 338 00:10:13,120 --> 00:10:13,960 Like what? 339 00:10:13,960 --> 00:10:15,760 There are potential biases in the algorithms. 340 00:10:15,760 --> 00:10:16,600 Okay. 341 00:10:16,600 --> 00:10:18,920 The risk of relying too much on automated systems. 342 00:10:18,920 --> 00:10:21,440 And we definitely need strong regulations 343 00:10:21,440 --> 00:10:23,600 to make sure things are fair and transparent. 344 00:10:23,600 --> 00:10:25,120 Right, it's a powerful technology. 345 00:10:25,120 --> 00:10:26,960 It is, so we gotta be careful with it. 346 00:10:26,960 --> 00:10:28,640 Okay, let's talk about manufacturing. 347 00:10:28,640 --> 00:10:29,480 Right. 348 00:10:29,480 --> 00:10:30,920 AI is changing that industry too. 349 00:10:30,920 --> 00:10:31,760 Big time. 350 00:10:31,760 --> 00:10:35,240 We're talking about optimizing production processes. 351 00:10:35,240 --> 00:10:36,720 Improving quality control. 352 00:10:36,720 --> 00:10:39,120 Even creating brand new materials. 353 00:10:39,120 --> 00:10:41,000 That's like those smart factories you hear about. 354 00:10:41,000 --> 00:10:41,840 Exactly. 355 00:10:41,840 --> 00:10:44,400 Where robots and AI are working side by side. 356 00:10:44,400 --> 00:10:47,920 Yeah, these AI systems can monitor the whole production line. 357 00:10:47,920 --> 00:10:49,160 See if there are any problems. 358 00:10:49,160 --> 00:10:50,680 Make adjustments in real time. 359 00:10:50,680 --> 00:10:52,200 So it's all about efficiency. 360 00:10:52,200 --> 00:10:53,360 And quality. 361 00:10:53,360 --> 00:10:56,640 It's pretty crazy how AI is shifting manufacturing 362 00:10:56,640 --> 00:10:59,280 from this labor intensive industry 363 00:10:59,280 --> 00:11:02,040 to something that's totally technology driven. 364 00:11:02,040 --> 00:11:03,120 It is a big shift. 365 00:11:03,120 --> 00:11:05,640 And that means changes for the workforce too. 366 00:11:05,640 --> 00:11:07,320 That's true, some jobs might be lost. 367 00:11:07,320 --> 00:11:10,200 But new ones will be created too in areas like data science 368 00:11:10,200 --> 00:11:11,360 and AI engineering. 369 00:11:11,360 --> 00:11:12,680 So it's this whole transition. 370 00:11:12,680 --> 00:11:15,480 And we need to make sure it's a just transition. 371 00:11:15,480 --> 00:11:16,560 Meaning what? 372 00:11:16,560 --> 00:11:19,280 Well, we need to support workers who might be displaced. 373 00:11:19,280 --> 00:11:21,160 Through things like retraining programs 374 00:11:21,160 --> 00:11:23,320 and job placement services. 375 00:11:23,320 --> 00:11:25,240 So everyone benefits from these advancements. 376 00:11:25,240 --> 00:11:26,080 Exactly. 377 00:11:26,080 --> 00:11:27,440 Okay, let's talk about customer service. 378 00:11:27,440 --> 00:11:28,280 Sure. 379 00:11:28,280 --> 00:11:30,000 I feel like I'm seeing more and more chatbots 380 00:11:30,000 --> 00:11:31,120 popping up everywhere. 381 00:11:31,120 --> 00:11:33,840 You are, they're handling a lot of customer interactions now. 382 00:11:33,840 --> 00:11:35,080 Yeah, like answering questions. 383 00:11:35,080 --> 00:11:36,160 Resolving issues. 384 00:11:36,160 --> 00:11:38,240 It's kind of changing the face of customer service. 385 00:11:38,240 --> 00:11:40,400 It is, and it can be really efficient. 386 00:11:40,400 --> 00:11:41,240 Yeah. 387 00:11:41,240 --> 00:11:43,760 24 seven availability, quick responses. 388 00:11:43,760 --> 00:11:46,840 Even personalized interactions based on your data. 389 00:11:46,840 --> 00:11:50,600 But can they really understand complex customer needs? 390 00:11:50,600 --> 00:11:51,440 That's a good question. 391 00:11:51,440 --> 00:11:52,680 And there's always that concern 392 00:11:52,680 --> 00:11:54,120 about losing the human touch. 393 00:11:54,120 --> 00:11:54,960 Right. 394 00:11:54,960 --> 00:11:56,360 It can't all be about efficiency. 395 00:11:56,360 --> 00:11:57,200 Absolutely. 396 00:11:57,200 --> 00:12:00,640 So remember earlier we talked about open AI and go borse cell. 397 00:12:00,640 --> 00:12:02,080 Yeah, the social media guy. 398 00:12:02,080 --> 00:12:02,920 Right. 399 00:12:02,920 --> 00:12:04,840 It makes you think about the role of AI in online spaces. 400 00:12:04,840 --> 00:12:05,680 Definitely. 401 00:12:05,680 --> 00:12:07,920 AI algorithms are already doing a lot. 402 00:12:07,920 --> 00:12:08,760 Yeah. 403 00:12:08,760 --> 00:12:11,000 Like recommending content, filtering spam. 404 00:12:11,000 --> 00:12:13,280 Even detecting hate speech. 405 00:12:13,280 --> 00:12:16,200 But as AI gets more advanced. 406 00:12:16,200 --> 00:12:18,280 It could amplify biases. 407 00:12:18,280 --> 00:12:19,320 That's bread misinformation. 408 00:12:19,320 --> 00:12:21,200 Even manipulate users. 409 00:12:21,200 --> 00:12:22,880 It's a little scary if you think about it. 410 00:12:22,880 --> 00:12:23,720 It is. 411 00:12:23,720 --> 00:12:26,840 We need to be really careful about how we integrate AI 412 00:12:26,840 --> 00:12:28,320 into these platforms. 413 00:12:28,320 --> 00:12:29,480 Make sure it's used ethically. 414 00:12:29,480 --> 00:12:30,320 Exactly. 415 00:12:30,320 --> 00:12:31,800 Okay, switching gears completely. 416 00:12:31,800 --> 00:12:33,320 Let's talk about education. 417 00:12:33,320 --> 00:12:34,240 Interesting. 418 00:12:34,240 --> 00:12:37,520 Have you heard about AI being used to personalize learning? 419 00:12:37,520 --> 00:12:41,080 Yeah, like AI tutors and adaptive learning platform. 420 00:12:41,080 --> 00:12:41,920 Right. 421 00:12:41,920 --> 00:12:43,160 It could revolutionize how we learn. 422 00:12:43,160 --> 00:12:44,000 Absolutely. 423 00:12:44,000 --> 00:12:48,360 Imagine a system that can analyze your strengths and weaknesses. 424 00:12:48,360 --> 00:12:50,560 Tailor the material to your needs. 425 00:12:50,560 --> 00:12:53,480 Give you personalized feedback. 426 00:12:53,480 --> 00:12:56,240 It would be amazing, but there are some challenges too. 427 00:12:56,240 --> 00:12:58,680 Of course, like making sure everyone has access 428 00:12:58,680 --> 00:13:00,080 to these resources. 429 00:13:00,080 --> 00:13:00,920 Right. 430 00:13:00,920 --> 00:13:02,480 And we need to think about data privacy. 431 00:13:02,480 --> 00:13:04,160 Yeah, and the role of human teachers. 432 00:13:04,160 --> 00:13:05,240 Can't forget about them. 433 00:13:05,240 --> 00:13:06,800 Okay, one last area to cover. 434 00:13:06,800 --> 00:13:07,480 Okay. 435 00:13:07,480 --> 00:13:09,040 What's AI in the legal profession? 436 00:13:09,040 --> 00:13:12,080 Now, that's something I haven't thought much about. 437 00:13:12,080 --> 00:13:13,080 It's pretty fascinating. 438 00:13:13,080 --> 00:13:15,000 AI can be used for legal research. 439 00:13:15,000 --> 00:13:15,600 Uh-huh. 440 00:13:15,600 --> 00:13:17,000 Analyzing contracts. 441 00:13:17,000 --> 00:13:19,640 Even predicting case outcomes. 442 00:13:19,640 --> 00:13:20,240 Yep. 443 00:13:20,240 --> 00:13:23,840 Imagine an AI that can go through tons of documents in seconds. 444 00:13:23,840 --> 00:13:25,520 Find the relevant information. 445 00:13:25,520 --> 00:13:26,160 Exactly. 446 00:13:26,160 --> 00:13:28,640 And these algorithms can analyze past cases. 447 00:13:28,640 --> 00:13:31,360 To see what might happen in similar situations. 448 00:13:31,360 --> 00:13:34,120 It could really improve efficiency in the legal field. 449 00:13:34,120 --> 00:13:37,880 Could, but there are ethical concerns too. 450 00:13:37,880 --> 00:13:38,400 Like what? 451 00:13:38,400 --> 00:13:41,600 How do we make sure these AI systems are fair? 452 00:13:41,600 --> 00:13:42,760 Prevent bias. 453 00:13:42,760 --> 00:13:45,560 And how do we balance the benefits of efficiency 454 00:13:45,560 --> 00:13:48,560 with the need for human oversight? 455 00:13:48,560 --> 00:13:49,360 Good point. 456 00:13:49,360 --> 00:13:50,760 It's not something we can just hand over 457 00:13:50,760 --> 00:13:51,840 to machines completely. 458 00:13:51,840 --> 00:13:52,600 Exactly. 459 00:13:52,600 --> 00:13:55,240 So as AI becomes more integrated into our lives. 460 00:13:55,240 --> 00:13:58,320 It's crucial to have these discussions about its impact. 461 00:13:58,320 --> 00:13:59,240 Address the risks. 462 00:13:59,240 --> 00:14:01,240 Make sure we're using it responsibly. 463 00:14:01,240 --> 00:14:02,400 The powerful tool. 464 00:14:02,400 --> 00:14:05,760 And it's up to us to use it wisely. 465 00:14:05,760 --> 00:14:08,200 OK, so we've seen how AI is changing 466 00:14:08,200 --> 00:14:09,360 all these different industries. 467 00:14:09,360 --> 00:14:09,600 Right. 468 00:14:09,600 --> 00:14:10,920 But what about the bigger picture? 469 00:14:10,920 --> 00:14:11,200 Yeah. 470 00:14:11,200 --> 00:14:13,360 What does it all mean for the workforce? 471 00:14:13,360 --> 00:14:14,240 The economy. 472 00:14:14,240 --> 00:14:15,440 Society as a whole. 473 00:14:15,440 --> 00:14:16,440 Those are big questions. 474 00:14:16,440 --> 00:14:16,920 They are. 475 00:14:16,920 --> 00:14:18,640 A lot of experts are trying to figure it out. 476 00:14:18,640 --> 00:14:18,840 Yeah. 477 00:14:18,840 --> 00:14:21,200 On one hand, AI could create all these new jobs. 478 00:14:21,200 --> 00:14:22,200 What was productivity? 479 00:14:22,200 --> 00:14:23,200 But on the other hand. 480 00:14:23,200 --> 00:14:25,360 There's that fear of job displacement. 481 00:14:25,360 --> 00:14:27,720 People losing their jobs to machines. 482 00:14:27,720 --> 00:14:29,240 It's definitely a concern. 483 00:14:29,240 --> 00:14:31,400 And workers will need to adapt. 484 00:14:31,400 --> 00:14:32,560 Learn new skills. 485 00:14:32,560 --> 00:14:33,080 Yeah. 486 00:14:33,080 --> 00:14:34,080 It's not going to be easy. 487 00:14:34,080 --> 00:14:36,200 So some studies say AI will actually 488 00:14:36,200 --> 00:14:38,440 create more jobs than it destroys. 489 00:14:38,440 --> 00:14:41,200 Especially in fields like data science. 490 00:14:41,200 --> 00:14:42,120 AI development. 491 00:14:42,120 --> 00:14:44,240 But other studies say some sectors 492 00:14:44,240 --> 00:14:46,920 could see massive job losses. 493 00:14:46,920 --> 00:14:47,880 Like manufacturing. 494 00:14:47,880 --> 00:14:48,920 Transportation. 495 00:14:48,920 --> 00:14:50,920 It's tough to predict exactly what will happen. 496 00:14:50,920 --> 00:14:51,400 It is. 497 00:14:51,400 --> 00:14:53,160 But we need to be prepared. 498 00:14:53,160 --> 00:14:56,200 So investing in education and training is crucial. 499 00:14:56,200 --> 00:14:56,800 Absolutely. 500 00:14:56,800 --> 00:14:59,480 We need to equip people with the skills they need. 501 00:14:59,480 --> 00:15:02,240 To thrive in this new AI powered world. 502 00:15:02,240 --> 00:15:03,000 Exactly. 503 00:15:03,000 --> 00:15:04,120 And those skills. 504 00:15:04,120 --> 00:15:04,840 What are they? 505 00:15:04,840 --> 00:15:07,200 Well, think about the things machines aren't good at yet. 506 00:15:07,200 --> 00:15:07,520 OK. 507 00:15:07,520 --> 00:15:08,360 Creativity. 508 00:15:08,360 --> 00:15:09,360 Critical thinking. 509 00:15:09,360 --> 00:15:10,280 Problem solving. 510 00:15:10,280 --> 00:15:11,400 Emotional intelligence. 511 00:15:11,400 --> 00:15:13,320 Those are going to be essential in the future. 512 00:15:13,320 --> 00:15:15,600 And it's not just on individuals to adapt, right? 513 00:15:15,600 --> 00:15:16,160 Right. 514 00:15:16,160 --> 00:15:18,280 Businesses and governments need to step up too. 515 00:15:18,280 --> 00:15:19,320 So what does that look like? 516 00:15:19,320 --> 00:15:21,760 Well, we need policies that encourage innovation. 517 00:15:21,760 --> 00:15:22,200 Yeah. 518 00:15:22,200 --> 00:15:26,480 But also provide safety nets for workers who might be displaced. 519 00:15:26,480 --> 00:15:26,760 OK. 520 00:15:26,760 --> 00:15:28,760 So things like retraining programs. 521 00:15:28,760 --> 00:15:30,600 It's exactly job placement services. 522 00:15:30,600 --> 00:15:32,640 Maybe even universal basic income. 523 00:15:32,640 --> 00:15:34,080 Some people are talking about that. 524 00:15:34,080 --> 00:15:36,800 It's all about creating a system that supports people 525 00:15:36,800 --> 00:15:38,120 through these changes. 526 00:15:38,120 --> 00:15:38,680 Makes sense. 527 00:15:38,680 --> 00:15:41,720 And make sure the benefits of AI are shared by everyone. 528 00:15:41,720 --> 00:15:42,000 Right. 529 00:15:42,000 --> 00:15:43,360 Not just a select few. 530 00:15:43,360 --> 00:15:44,680 Exactly. 531 00:15:44,680 --> 00:15:47,120 So let's talk about the economic impact of AI. 532 00:15:47,120 --> 00:15:47,640 OK. 533 00:15:47,640 --> 00:15:50,280 I mean, we've seen how it can boost efficiency in businesses. 534 00:15:50,280 --> 00:15:50,720 Yeah. 535 00:15:50,720 --> 00:15:51,880 Drive innovation. 536 00:15:51,880 --> 00:15:55,200 But how will this affect economic growth on a larger scale? 537 00:15:55,200 --> 00:15:57,440 Well, a lot of experts think AI could 538 00:15:57,440 --> 00:15:59,960 lead to significant economic growth. 539 00:15:59,960 --> 00:16:00,720 How so? 540 00:16:00,720 --> 00:16:04,040 Well, by automating tasks, optimizing processes, 541 00:16:04,040 --> 00:16:05,480 creating new products and services. 542 00:16:05,480 --> 00:16:05,880 Right. 543 00:16:05,880 --> 00:16:07,920 All of that can increase productivity 544 00:16:07,920 --> 00:16:09,840 and lead to higher GDP growth. 545 00:16:09,840 --> 00:16:13,240 But there's also the potential for AI to make inequality worse. 546 00:16:13,240 --> 00:16:16,280 That's a real concern if only a small group of people 547 00:16:16,280 --> 00:16:18,600 benefit from AI, like tech companies, 548 00:16:18,600 --> 00:16:19,920 or highly skilled workers. 549 00:16:19,920 --> 00:16:22,720 Then the gap between the rich and the poor could get even bigger. 550 00:16:22,720 --> 00:16:23,360 Exactly. 551 00:16:23,360 --> 00:16:25,480 So policymakers need to address that. 552 00:16:25,480 --> 00:16:28,400 Make sure the benefits of AI are distributed fairly. 553 00:16:28,400 --> 00:16:30,600 So everyone has a chance to succeed. 554 00:16:30,600 --> 00:16:33,000 That means investing in education. 555 00:16:33,000 --> 00:16:34,360 Promoting entrepreneurship. 556 00:16:34,360 --> 00:16:37,880 Creating policies that support a more inclusive economy. 557 00:16:37,880 --> 00:16:38,640 Exactly. 558 00:16:38,640 --> 00:16:41,080 It seems like AI is this double-edged sword. 559 00:16:41,080 --> 00:16:41,680 It is. 560 00:16:41,680 --> 00:16:43,200 It's a powerful tool. 561 00:16:43,200 --> 00:16:45,320 With the potential to improve our lives. 562 00:16:45,320 --> 00:16:47,840 But we need to be mindful of the risks. 563 00:16:47,840 --> 00:16:49,160 The potential downsides. 564 00:16:49,160 --> 00:16:50,840 And make sure we're using it ethically. 565 00:16:50,840 --> 00:16:52,720 So we've covered a lot in this deep dive. 566 00:16:52,720 --> 00:16:55,560 We have from specific applications 567 00:16:55,560 --> 00:16:57,840 to the broader societal implications. 568 00:16:57,840 --> 00:16:58,760 It's been fascinating. 569 00:16:58,760 --> 00:16:59,400 It has. 570 00:16:59,400 --> 00:17:01,920 AI is changing the world in so many ways. 571 00:17:01,920 --> 00:17:03,120 And we're just at the beginning. 572 00:17:03,120 --> 00:17:03,760 Exactly. 573 00:17:03,760 --> 00:17:05,840 Who knows what the future holds? 574 00:17:05,840 --> 00:17:08,480 Thanks for listening to the Daily AI News Podcast. 575 00:17:08,480 --> 00:17:24,520 And we'll see you next time.