1 00:00:00,000 --> 00:00:05,000 All right, so we're driving deep into Microsoft Ignite 2024. 2 00:00:05,380 --> 00:00:07,000 Sokka Nadella's keynote. 3 00:00:07,000 --> 00:00:07,840 Yeah. 4 00:00:07,840 --> 00:00:10,080 It wasn't just about AI, it was about how AI 5 00:00:10,080 --> 00:00:13,840 is gonna rewrite the rules of business 6 00:00:13,840 --> 00:00:15,260 and sooner than you might think. 7 00:00:15,260 --> 00:00:16,100 Yeah. 8 00:00:16,100 --> 00:00:17,960 We've got his keynote transcripts, 9 00:00:17,960 --> 00:00:20,720 some in-depth articles, even some analyst reports. 10 00:00:20,720 --> 00:00:21,560 Nice. 11 00:00:21,560 --> 00:00:22,960 And let me tell you, 12 00:00:22,960 --> 00:00:24,840 things are about to get interesting. 13 00:00:24,840 --> 00:00:28,560 What struck me is how Nadella tackled the elephant 14 00:00:28,560 --> 00:00:30,120 in the room. 15 00:00:30,120 --> 00:00:33,000 He acknowledged that with all the hype around AI, 16 00:00:33,000 --> 00:00:35,840 it's tempting to think, okay, is this another bubble? 17 00:00:35,840 --> 00:00:39,200 But he frames it in a way that really resonated. 18 00:00:39,200 --> 00:00:41,440 He talks about these scaling laws, 19 00:00:41,440 --> 00:00:44,240 almost like Moore's law on steroids. 20 00:00:44,240 --> 00:00:46,600 He's suggesting that AI isn't just getting better, 21 00:00:46,600 --> 00:00:49,240 it's improving at an accelerating rate. 22 00:00:49,240 --> 00:00:50,180 That's a big claim. 23 00:00:50,180 --> 00:00:52,960 Doubling in capability every six months. 24 00:00:52,960 --> 00:00:55,120 I mean, even he admits that this pace 25 00:00:55,120 --> 00:00:56,480 might not be sustainable forever. 26 00:00:56,480 --> 00:00:58,680 Exactly, he encourages skepticism. 27 00:00:58,680 --> 00:01:00,680 He says we should be questioning these assumptions, 28 00:01:00,680 --> 00:01:01,840 pushing the boundaries. 29 00:01:01,840 --> 00:01:02,800 And you know what? 30 00:01:02,800 --> 00:01:04,200 I think that's brilliant. 31 00:01:04,200 --> 00:01:05,040 Yeah. 32 00:01:05,040 --> 00:01:08,600 It creates this atmosphere of grounded excitement. 33 00:01:08,600 --> 00:01:10,240 So amidst all this AI frenzy, 34 00:01:10,240 --> 00:01:12,280 where does Microsoft actually fit in? 35 00:01:12,280 --> 00:01:16,400 Nadella laid out a clear vision with three core platforms, 36 00:01:16,400 --> 00:01:21,400 Co-Pilot, Co-Pilot Devices, and the Azure AI Stack. 37 00:01:21,500 --> 00:01:23,400 It's like they're building a whole ecosystem 38 00:01:23,400 --> 00:01:27,120 designed to bring AI to every corner of the business world. 39 00:01:27,120 --> 00:01:28,280 Let's start with Co-Pilot. 40 00:01:28,280 --> 00:01:29,120 Okay. 41 00:01:29,120 --> 00:01:30,800 Nadella calls it the UI for AI, 42 00:01:30,800 --> 00:01:32,680 which sounds pretty abstract. 43 00:01:32,680 --> 00:01:34,840 What does that even mean in practical terms? 44 00:01:34,840 --> 00:01:36,200 Think about it this way. 45 00:01:36,200 --> 00:01:40,280 We went from typing commands to clicking icons. 46 00:01:40,280 --> 00:01:42,520 And now we're moving toward interacting with technology 47 00:01:42,520 --> 00:01:43,680 using natural language. 48 00:01:43,680 --> 00:01:44,520 Okay. 49 00:01:44,520 --> 00:01:46,560 Co-Pilot is designed to be that bridge, 50 00:01:46,560 --> 00:01:49,880 that intuitive layer that lets us harness the power of AI 51 00:01:49,880 --> 00:01:52,160 without needing to be coding wizards. 52 00:01:52,160 --> 00:01:53,760 So it's like having an AI assistant 53 00:01:53,760 --> 00:01:55,840 that understands what you need and helps you get it done. 54 00:01:55,840 --> 00:01:56,800 Exactly. 55 00:01:56,800 --> 00:01:58,800 And here's where it gets interesting. 56 00:01:58,800 --> 00:02:01,600 He emphasizes that the value of Co-Pilot 57 00:02:01,600 --> 00:02:03,520 isn't just in the technology itself, 58 00:02:03,520 --> 00:02:05,120 it's in how people use it. 59 00:02:05,120 --> 00:02:07,280 The more people adopt Co-Pilot, 60 00:02:07,280 --> 00:02:10,300 the more data it gathers, the smarter it gets. 61 00:02:10,300 --> 00:02:12,180 It's like a network effect for AI. 62 00:02:12,180 --> 00:02:13,020 I see. 63 00:02:13,020 --> 00:02:14,120 So it's not a static tool. 64 00:02:14,120 --> 00:02:14,960 Right. 65 00:02:14,960 --> 00:02:16,560 It's constantly evolving 66 00:02:16,560 --> 00:02:18,120 based on how people interact with it. 67 00:02:18,120 --> 00:02:18,960 Right. 68 00:02:18,960 --> 00:02:20,320 He also highlighted how Co-Pilot 69 00:02:20,320 --> 00:02:22,040 is designed to be extensible. 70 00:02:22,040 --> 00:02:22,880 Okay. 71 00:02:22,880 --> 00:02:23,920 You can build on it, customize it. 72 00:02:23,920 --> 00:02:24,760 Yeah. 73 00:02:24,760 --> 00:02:28,200 Create specialized agents to automate specific tasks. 74 00:02:28,200 --> 00:02:31,120 Think of it like having an army of AI assistants. 75 00:02:31,120 --> 00:02:31,960 Why? 76 00:02:31,960 --> 00:02:34,520 Each with its own like unique skill set working for you. 77 00:02:34,520 --> 00:02:36,240 Yeah, that sounds impressive. 78 00:02:36,240 --> 00:02:37,080 Yeah. 79 00:02:37,080 --> 00:02:38,720 But how do businesses actually measure 80 00:02:38,720 --> 00:02:41,240 the return on investment with all this AI? 81 00:02:41,240 --> 00:02:42,080 Right. 82 00:02:42,080 --> 00:02:43,240 It can't just be about cool features. 83 00:02:43,240 --> 00:02:44,080 Right. 84 00:02:44,080 --> 00:02:45,920 He addressed that head on. 85 00:02:45,920 --> 00:02:48,920 Microsoft is introducing Co-Pilot Analytics. 86 00:02:48,920 --> 00:02:49,760 Okay. 87 00:02:49,760 --> 00:02:51,360 A tool specifically designed to track 88 00:02:51,360 --> 00:02:54,840 how Co-Pilot usage translates into tangible outcomes. 89 00:02:54,840 --> 00:02:55,680 Okay. 90 00:02:55,680 --> 00:02:56,800 They want businesses to be able to see 91 00:02:56,800 --> 00:03:00,040 exactly how this AI is impacting their bottom line. 92 00:03:00,040 --> 00:03:02,080 Okay, so they're not just throwing AI at the wall 93 00:03:02,080 --> 00:03:03,040 and seeing what sticks. 94 00:03:03,040 --> 00:03:03,860 Right. 95 00:03:03,860 --> 00:03:05,480 They're actually thinking about 96 00:03:05,480 --> 00:03:09,160 how to measure its real world impact. 97 00:03:09,160 --> 00:03:10,160 Exactly. 98 00:03:10,160 --> 00:03:11,860 And to drive that point home, 99 00:03:11,860 --> 00:03:13,960 they shared some compelling examples 100 00:03:13,960 --> 00:03:16,080 of companies already using Co-Pilot 101 00:03:16,080 --> 00:03:18,120 to achieve remarkable results. 102 00:03:18,120 --> 00:03:18,960 Like who? 103 00:03:18,960 --> 00:03:19,780 Give me the highlights. 104 00:03:19,780 --> 00:03:21,920 Well, the Bank of Queensland group is a great example. 105 00:03:21,920 --> 00:03:23,680 They were facing this huge challenge 106 00:03:23,680 --> 00:03:26,760 of analyzing thousands of documents for risk assessment. 107 00:03:26,760 --> 00:03:27,580 Okay. 108 00:03:27,580 --> 00:03:29,640 It was a process that used to take weeks. 109 00:03:29,640 --> 00:03:30,480 Yeah. 110 00:03:30,480 --> 00:03:32,620 With Co-Pilot, they've managed to condense that down 111 00:03:32,620 --> 00:03:34,440 to a single day. 112 00:03:34,440 --> 00:03:35,760 Whoa. 113 00:03:35,760 --> 00:03:37,160 That's a massive time saving. 114 00:03:37,160 --> 00:03:39,320 But what about industries beyond finance? 115 00:03:39,320 --> 00:03:41,760 Vodafone is another interesting case. 116 00:03:41,760 --> 00:03:44,240 They're using Co-Pilot and Azure AI 117 00:03:44,240 --> 00:03:47,640 to completely revamp their customer service. 118 00:03:47,640 --> 00:03:50,840 They handle over 45 million conversations every month. 119 00:03:50,840 --> 00:03:51,680 Wow. 120 00:03:51,680 --> 00:03:53,920 Co-Pilot is helping them personalize interactions, 121 00:03:53,920 --> 00:03:55,240 answer common questions, 122 00:03:55,240 --> 00:03:58,720 and even guide customers towards self-service options. 123 00:03:58,720 --> 00:04:00,440 So it's not just about cutting costs. 124 00:04:00,440 --> 00:04:01,280 Right. 125 00:04:01,280 --> 00:04:02,560 It's about improving the customer experience. 126 00:04:02,560 --> 00:04:03,620 Exactly. 127 00:04:03,620 --> 00:04:06,880 They've seen a significant reduction in average hold times, 128 00:04:06,880 --> 00:04:08,880 which makes customers happier. 129 00:04:08,880 --> 00:04:09,720 Yeah. 130 00:04:09,720 --> 00:04:11,160 And it allows their human agents 131 00:04:11,160 --> 00:04:13,320 to focus on the more complex issues. 132 00:04:13,320 --> 00:04:16,320 All right, so Co-Pilot is clearly a big deal, 133 00:04:16,320 --> 00:04:18,120 but how is it actually integrated 134 00:04:18,120 --> 00:04:20,160 into the tools people use every day? 135 00:04:20,160 --> 00:04:21,000 Right. 136 00:04:21,000 --> 00:04:23,500 Nadel talked about Co-Pilot in action, 137 00:04:23,500 --> 00:04:25,880 focusing on the Microsoft 365 suite. 138 00:04:25,880 --> 00:04:26,800 Yeah. 139 00:04:26,800 --> 00:04:28,400 This is where it gets really interesting. 140 00:04:28,400 --> 00:04:31,240 They showed Co-Pilot woven into everything 141 00:04:31,240 --> 00:04:35,240 from Word and Excel to Teams and even PowerPoint. 142 00:04:35,240 --> 00:04:36,080 Okay. 143 00:04:36,080 --> 00:04:37,560 They're not just adding AI features. 144 00:04:37,560 --> 00:04:38,400 Yeah. 145 00:04:38,400 --> 00:04:41,120 They're fundamentally changing how we work with these tools. 146 00:04:41,120 --> 00:04:42,440 Okay, give me some specifics. 147 00:04:42,440 --> 00:04:43,280 Okay. 148 00:04:43,280 --> 00:04:44,200 What stood out to you? 149 00:04:44,200 --> 00:04:47,360 Well, for starters, they unveiled Microsoft Co-Pilot Pages. 150 00:04:47,360 --> 00:04:48,200 Okay. 151 00:04:48,200 --> 00:04:49,020 And let me tell you, 152 00:04:49,020 --> 00:04:51,560 this is where things start to feel a little bit like magic. 153 00:04:51,560 --> 00:04:52,400 Okay. 154 00:04:52,400 --> 00:04:54,080 Imagine a document editor 155 00:04:54,080 --> 00:04:56,240 where you can create dynamic charts, 156 00:04:56,240 --> 00:04:58,640 insert interactive code blocks, 157 00:04:58,640 --> 00:05:01,880 and even pull in information from all sorts of sources. 158 00:05:01,880 --> 00:05:02,720 Wow. 159 00:05:02,720 --> 00:05:05,160 All controlled by natural language prompts. 160 00:05:05,160 --> 00:05:08,360 Nadel himself uses it to prep for meetings. 161 00:05:08,360 --> 00:05:10,320 Wait, so he's not just talking about this stuff. 162 00:05:10,320 --> 00:05:11,160 Yeah. 163 00:05:11,160 --> 00:05:13,080 He's actually using it in his daily workflow. 164 00:05:13,080 --> 00:05:14,720 He showed it live. 165 00:05:14,720 --> 00:05:18,040 He gave Co-Pilot a simple prompt about a client meeting, 166 00:05:18,040 --> 00:05:20,440 and it instantly pulled in relevant details 167 00:05:20,440 --> 00:05:24,520 from the web, LinkedIn, internal documents. 168 00:05:24,520 --> 00:05:25,360 Wow. You name it. 169 00:05:25,360 --> 00:05:27,160 It was like having a research assistant 170 00:05:27,160 --> 00:05:28,240 working at warp speed. 171 00:05:28,240 --> 00:05:30,440 That sounds incredibly powerful. 172 00:05:30,440 --> 00:05:32,140 What about the other Microsoft apps? 173 00:05:32,140 --> 00:05:34,120 Well, Teams got a serious upgrade. 174 00:05:34,120 --> 00:05:34,940 Okay. 175 00:05:34,940 --> 00:05:37,520 Co-Pilot can now analyze past meeting transcripts 176 00:05:37,520 --> 00:05:39,680 and even answer questions about presentations 177 00:05:39,680 --> 00:05:40,920 that are being shared on screen. 178 00:05:40,920 --> 00:05:41,740 Uh-huh. 179 00:05:41,740 --> 00:05:43,160 It's like having an AI teammate 180 00:05:43,160 --> 00:05:45,640 who's always up to speed on your projects. 181 00:05:45,640 --> 00:05:47,720 And then there's Word and PowerPoint. 182 00:05:47,720 --> 00:05:48,560 Yeah. 183 00:05:48,560 --> 00:05:50,640 Co-Pilot can help you generate drafts 184 00:05:50,640 --> 00:05:52,240 based on existing documents. 185 00:05:52,240 --> 00:05:53,080 Okay. 186 00:05:53,080 --> 00:05:55,720 Create presentation outlines from a simple prompt, 187 00:05:55,720 --> 00:05:57,760 no more staring at a blank page. 188 00:05:57,760 --> 00:05:59,800 So it's like having an AI writing partner. 189 00:05:59,800 --> 00:06:01,400 I could definitely see how that would be helpful. 190 00:06:01,400 --> 00:06:03,920 And even Outlook got some love. 191 00:06:03,920 --> 00:06:07,600 Nadel highlighted this prioritize inbox feature. 192 00:06:07,600 --> 00:06:08,440 Oh, nice. 193 00:06:08,440 --> 00:06:10,040 Co-Pilot analyzes your inbox 194 00:06:10,040 --> 00:06:12,720 based on content and sender importance. 195 00:06:12,720 --> 00:06:13,800 So you're always focusing 196 00:06:13,800 --> 00:06:15,600 on the most critical messages first. 197 00:06:15,600 --> 00:06:17,560 It's like having an AI assistant 198 00:06:17,560 --> 00:06:18,840 that filters out the noise 199 00:06:18,840 --> 00:06:21,200 and it helps you manage your time more effectively. 200 00:06:21,200 --> 00:06:23,240 Okay. Color me intrigued. 201 00:06:23,240 --> 00:06:26,660 But for me, the real test is Excel. 202 00:06:26,660 --> 00:06:29,360 I mean, it's the workhorse of the business world. 203 00:06:29,360 --> 00:06:31,400 How are they bringing AI into that? 204 00:06:31,400 --> 00:06:33,200 This is where Nadel really leaned 205 00:06:33,200 --> 00:06:34,840 into the revolutionary language. 206 00:06:34,840 --> 00:06:36,640 And honestly, I think he's right. 207 00:06:36,640 --> 00:06:37,480 Okay. 208 00:06:37,480 --> 00:06:39,720 Imagine being able to give Co-Pilot 209 00:06:39,720 --> 00:06:40,960 a high level prompt, 210 00:06:40,960 --> 00:06:43,000 like how can we improve production rates? 211 00:06:43,000 --> 00:06:43,840 Right. 212 00:06:43,840 --> 00:06:46,600 And having it generate a strategic analysis plan, 213 00:06:46,600 --> 00:06:49,720 execute it and deliver visualizations 214 00:06:49,720 --> 00:06:52,360 and actionable insights in minutes. 215 00:06:52,360 --> 00:06:53,660 Whoa, hold on. 216 00:06:53,660 --> 00:06:55,820 Are you saying that Co-Pilot in Excel 217 00:06:55,820 --> 00:06:58,480 can essentially think like a data analyst? 218 00:06:58,480 --> 00:07:00,080 It's not about replacing analysts. 219 00:07:00,080 --> 00:07:01,840 It's about giving everyone access 220 00:07:01,840 --> 00:07:03,640 to those data-driven insights. 221 00:07:03,640 --> 00:07:05,720 It's like democratizing data analysis, 222 00:07:05,720 --> 00:07:08,360 making it accessible to anyone who can use a spreadsheet. 223 00:07:08,360 --> 00:07:09,360 That's a bold claim. 224 00:07:09,360 --> 00:07:10,200 Yeah. 225 00:07:10,200 --> 00:07:11,040 If they can pull it off, 226 00:07:11,040 --> 00:07:13,480 it could be a game changer for businesses of all sizes. 227 00:07:13,480 --> 00:07:14,880 And Nadel didn't stop there. 228 00:07:14,880 --> 00:07:15,720 Oh no. 229 00:07:15,720 --> 00:07:17,400 He went on to explain how you can actually 230 00:07:17,400 --> 00:07:20,600 extend Co-Pilot with actions and agents, 231 00:07:20,600 --> 00:07:24,520 creating this truly customizable AI ecosystem. 232 00:07:24,520 --> 00:07:25,720 Okay, now you've got my attention. 233 00:07:25,720 --> 00:07:26,840 Tell me more about this. 234 00:07:26,840 --> 00:07:28,120 Think of Co-Pilot actions, 235 00:07:28,120 --> 00:07:30,240 like supercharged outlook rules. 236 00:07:30,240 --> 00:07:31,080 Okay. 237 00:07:31,080 --> 00:07:35,760 They can automate multi-step tasks across Microsoft 365. 238 00:07:35,760 --> 00:07:38,160 You want to automatically save attachments 239 00:07:38,160 --> 00:07:41,320 from certain senders to a specific folder, 240 00:07:41,320 --> 00:07:44,640 and then trigger a notification in Teams. 241 00:07:44,640 --> 00:07:46,920 Co-Pilot actions can handle that. 242 00:07:46,920 --> 00:07:48,080 That's pretty slick. 243 00:07:48,080 --> 00:07:50,120 What about these agents you mentioned? 244 00:07:50,120 --> 00:07:52,960 They're where things get really powerful. 245 00:07:52,960 --> 00:07:55,260 He talked about team-specific agents. 246 00:07:55,260 --> 00:07:58,520 Imagine adding a facilitator agent to your team's meetings 247 00:07:58,520 --> 00:08:00,480 to keep discussions on track, 248 00:08:00,480 --> 00:08:03,320 or a project manager agent and planner 249 00:08:03,320 --> 00:08:05,480 to handle workflow automation. 250 00:08:05,480 --> 00:08:07,960 It's like having a team of AI assistants 251 00:08:07,960 --> 00:08:09,400 working alongside you. 252 00:08:09,400 --> 00:08:11,320 So it's not just about individual productivity, 253 00:08:11,320 --> 00:08:13,360 it's about enhancing team collaboration. 254 00:08:13,360 --> 00:08:14,400 Exactly. 255 00:08:14,400 --> 00:08:16,320 And he didn't forget about SharePoint. 256 00:08:16,320 --> 00:08:19,320 Every SharePoint site will now have a built-in agent 257 00:08:19,320 --> 00:08:21,440 giving you instant access to information 258 00:08:21,440 --> 00:08:22,780 in your knowledge base. 259 00:08:22,780 --> 00:08:25,520 It's like having an AI librarian at your fingertips. 260 00:08:25,520 --> 00:08:27,600 This all sounds incredibly powerful, 261 00:08:27,600 --> 00:08:30,280 but it also seems like it could get pretty complex. 262 00:08:30,280 --> 00:08:32,080 That's where Co-Pilot Studio comes in. 263 00:08:32,080 --> 00:08:32,920 Okay. 264 00:08:32,920 --> 00:08:35,000 Nadella emphasized how simple it is 265 00:08:35,000 --> 00:08:37,640 to create your own Co-Pilot agents. 266 00:08:37,640 --> 00:08:41,080 He even compared it to creating a Word document. 267 00:08:41,080 --> 00:08:43,080 So you're saying that you don't need to be a programmer 268 00:08:43,080 --> 00:08:44,760 to build your own AI agents. 269 00:08:44,760 --> 00:08:46,960 That's the message they were sending loud and clear. 270 00:08:46,960 --> 00:08:47,800 Wow. 271 00:08:47,800 --> 00:08:50,000 And he introduced the concept of autonomous agents, 272 00:08:50,000 --> 00:08:51,800 which are agents that work in the background 273 00:08:51,800 --> 00:08:53,480 proactively handling tasks 274 00:08:53,480 --> 00:08:55,720 without you needing to lift a finger. 275 00:08:55,720 --> 00:08:58,720 He gave the example of a sales qualification agent 276 00:08:58,720 --> 00:09:00,640 that autonomously researches leads 277 00:09:00,640 --> 00:09:02,520 and drafts personalized emails. 278 00:09:02,520 --> 00:09:03,800 Okay, now that's just straight up 279 00:09:03,800 --> 00:09:05,240 science fiction becoming reality. 280 00:09:05,240 --> 00:09:06,240 I know, right? 281 00:09:06,240 --> 00:09:07,080 Yeah. 282 00:09:07,080 --> 00:09:07,920 To top it all off, 283 00:09:07,920 --> 00:09:10,800 Nadella highlighted the growing partner ecosystem. 284 00:09:10,800 --> 00:09:11,640 Okay. 285 00:09:11,640 --> 00:09:14,000 Companies like Adobe, SAP, and ServiceNow 286 00:09:14,000 --> 00:09:16,880 are building their own agents and connectors for Co-Pilot. 287 00:09:16,880 --> 00:09:18,460 So it's not just a Microsoft thing. 288 00:09:18,460 --> 00:09:22,760 It's becoming a platform for AI innovation across industries. 289 00:09:22,760 --> 00:09:23,600 Exactly. 290 00:09:23,600 --> 00:09:25,840 It's becoming this interconnected web 291 00:09:25,840 --> 00:09:28,280 of AI-powered tools and services. 292 00:09:28,280 --> 00:09:30,000 We've covered a lot of grounds with Co-Pilot, 293 00:09:30,000 --> 00:09:33,520 and it's clear that Microsoft is betting big on it. 294 00:09:33,520 --> 00:09:34,920 But what about the hardware side of things? 295 00:09:34,920 --> 00:09:35,760 Right. 296 00:09:35,760 --> 00:09:38,240 Nadella also talked about Co-Pilot devices. 297 00:09:38,240 --> 00:09:39,240 What's the story there? 298 00:09:39,240 --> 00:09:42,600 He shifted the focus to how AI and the cloud 299 00:09:42,600 --> 00:09:45,840 are fundamentally changing the way we think about PCs. 300 00:09:45,840 --> 00:09:48,920 He introduced this concept of Co-Pilot Plus PCs, 301 00:09:48,920 --> 00:09:51,600 which are a new class of Windows devices 302 00:09:51,600 --> 00:09:54,840 specifically designed to leverage the power of the cloud 303 00:09:54,840 --> 00:09:57,320 and edge computing for AI workloads. 304 00:09:57,320 --> 00:09:59,200 Okay, so it's not just about software. 305 00:09:59,200 --> 00:10:00,040 Right. 306 00:10:00,040 --> 00:10:01,920 They're actually building specialized hardware 307 00:10:01,920 --> 00:10:03,840 to run these AI applications. 308 00:10:03,840 --> 00:10:04,660 Right. 309 00:10:04,660 --> 00:10:06,280 They're packed with powerful NPUs, 310 00:10:06,280 --> 00:10:09,080 which are specialized processors designed for AI tasks, 311 00:10:09,080 --> 00:10:11,120 and they're optimized for battery life. 312 00:10:11,120 --> 00:10:11,960 Okay. 313 00:10:11,960 --> 00:10:13,480 So you're not tethered to an outlet. 314 00:10:13,480 --> 00:10:16,200 So they're like AI-powered laptops on steroids. 315 00:10:16,200 --> 00:10:19,360 He also touched on the growing popularity of cloud PCs, 316 00:10:19,360 --> 00:10:21,960 building on the success of Windows 365. 317 00:10:21,960 --> 00:10:22,800 Yeah. 318 00:10:22,800 --> 00:10:24,920 Which lets you stream a personalized Windows desktop 319 00:10:24,920 --> 00:10:26,240 to any device. 320 00:10:26,240 --> 00:10:29,880 He announced this new device called Windows 365 Link. 321 00:10:29,880 --> 00:10:30,720 Okay. 322 00:10:30,720 --> 00:10:32,120 A purpose-built secure device 323 00:10:32,120 --> 00:10:35,200 specifically designed for Windows 365. 324 00:10:35,200 --> 00:10:37,920 It's set to launch in April 2025. 325 00:10:37,920 --> 00:10:39,080 So it's like a thin client 326 00:10:39,080 --> 00:10:40,680 that's optimized for cloud computing. 327 00:10:40,680 --> 00:10:41,520 Exactly. 328 00:10:41,520 --> 00:10:42,920 And of course, Nadella emphasized 329 00:10:42,920 --> 00:10:44,240 the importance of security. 330 00:10:44,240 --> 00:10:45,080 Yeah. 331 00:10:45,080 --> 00:10:47,760 He highlighted the Windows Resiliency Initiative, 332 00:10:47,760 --> 00:10:50,600 which is all about making Windows secure and reliable 333 00:10:50,600 --> 00:10:52,560 for mission-critical workloads. 334 00:10:52,560 --> 00:10:55,400 He specifically mentioned Windows Hotpatch, 335 00:10:55,400 --> 00:10:59,080 which applies security updates without requiring restarts. 336 00:10:59,080 --> 00:11:00,960 That's a huge deal for businesses 337 00:11:00,960 --> 00:11:02,480 that can't afford downtime. 338 00:11:02,480 --> 00:11:04,120 Right, so they're thinking about both the power 339 00:11:04,120 --> 00:11:07,040 and the security of these AI-powered devices. 340 00:11:07,040 --> 00:11:08,480 But what about the developers 341 00:11:08,480 --> 00:11:10,640 who are actually building these applications? 342 00:11:10,640 --> 00:11:11,480 Right. 343 00:11:11,480 --> 00:11:12,320 What's in it for them? 344 00:11:12,320 --> 00:11:14,620 That's where the Azure AI stack comes in. 345 00:11:14,620 --> 00:11:16,960 It's the foundation for AI innovation. 346 00:11:16,960 --> 00:11:17,780 Okay. 347 00:11:17,780 --> 00:11:20,560 Think of it as the platform that provides developers 348 00:11:20,560 --> 00:11:22,840 with the tools and infrastructure they need 349 00:11:22,840 --> 00:11:25,480 to build their own co-pilots and AI agents. 350 00:11:25,480 --> 00:11:28,720 So it's like the engine that powers all this AI magic. 351 00:11:28,720 --> 00:11:29,680 Exactly. 352 00:11:29,680 --> 00:11:31,440 He started by underscoring Azure's 353 00:11:31,440 --> 00:11:33,800 massive global infrastructure. 354 00:11:33,800 --> 00:11:35,960 They've invested heavily in data centers, 355 00:11:35,960 --> 00:11:38,320 sustainable construction practices, 356 00:11:38,320 --> 00:11:40,640 and even advancements in network technology 357 00:11:40,640 --> 00:11:43,640 like Holo Core Fiber for faster connectivity. 358 00:11:43,640 --> 00:11:45,120 Okay, so they're building the foundation 359 00:11:45,120 --> 00:11:47,320 for a future where AI is everywhere. 360 00:11:47,320 --> 00:11:48,680 Sure, what else did he highlight? 361 00:11:48,680 --> 00:11:52,160 He announced Azure Local, which extends Azure services 362 00:11:52,160 --> 00:11:55,400 to hybrid, multi-cloud, and edge locations. 363 00:11:55,400 --> 00:11:56,280 Okay. 364 00:11:56,280 --> 00:11:59,040 This allows businesses to run mission-critical workloads, 365 00:11:59,040 --> 00:12:01,600 including AI workloads wherever they need to. 366 00:12:01,600 --> 00:12:03,760 It's all about flexibility and resilience. 367 00:12:03,760 --> 00:12:05,120 So they're not just building a cloud. 368 00:12:05,120 --> 00:12:08,060 They're building an AI ecosystem that spans from the cloud 369 00:12:08,060 --> 00:12:10,480 to the edge to on-premises. 370 00:12:10,480 --> 00:12:13,200 Right, and then he got into silicon innovation. 371 00:12:13,200 --> 00:12:14,040 Okay. 372 00:12:14,040 --> 00:12:16,280 Nadella revealed that Microsoft is getting serious 373 00:12:16,280 --> 00:12:18,240 about building their own chips. 374 00:12:18,240 --> 00:12:21,500 He introduced their first in-house security chip, 375 00:12:21,500 --> 00:12:24,560 Azure Integrated HSM, which will be included 376 00:12:24,560 --> 00:12:27,280 in all new Azure servers for enhanced security. 377 00:12:27,280 --> 00:12:29,600 So they're not just relying on off-the-shelf components. 378 00:12:29,600 --> 00:12:32,000 They're actually designing their own hardware 379 00:12:32,000 --> 00:12:34,240 to optimize for security and performance. 380 00:12:34,240 --> 00:12:37,040 Yes, and he also announced Azure Boost, 381 00:12:37,040 --> 00:12:39,760 which features their first in-house DPU, 382 00:12:39,760 --> 00:12:41,640 a specialized processor designed 383 00:12:41,640 --> 00:12:44,460 to accelerate data-centric workloads. 384 00:12:44,460 --> 00:12:46,860 They're promising significant performance gains, 385 00:12:46,860 --> 00:12:49,000 which is crucial for AI applications 386 00:12:49,000 --> 00:12:50,760 that demand a lot of processing power. 387 00:12:50,760 --> 00:12:52,520 Okay, so they're building the chips, 388 00:12:52,520 --> 00:12:54,680 the infrastructure, the platforms. 389 00:12:54,680 --> 00:12:56,120 This is a pretty comprehensive approach. 390 00:12:56,120 --> 00:12:56,960 It is. 391 00:12:56,960 --> 00:12:58,160 What about the data itself? 392 00:12:58,160 --> 00:12:59,960 He highlighted Microsoft Fabric 393 00:12:59,960 --> 00:13:02,580 as the core data platform for AI. 394 00:13:02,580 --> 00:13:06,560 It unifies data and analytics into one experience. 395 00:13:06,560 --> 00:13:10,260 He even announced the integration of SQL Server into Fabric, 396 00:13:10,260 --> 00:13:13,080 creating a single platform for both operational 397 00:13:13,080 --> 00:13:15,240 and analytical workloads. 398 00:13:15,240 --> 00:13:17,480 This is huge for data management and analysis. 399 00:13:17,480 --> 00:13:20,000 So they're creating a one-stop shop for all things data. 400 00:13:20,000 --> 00:13:22,920 Exactly, and then he unveiled Azure AI Foundry, 401 00:13:22,920 --> 00:13:25,560 which he positioned as the app server for the AI age. 402 00:13:25,560 --> 00:13:26,400 Okay. 403 00:13:26,400 --> 00:13:28,880 It unifies models, tooling, safety, 404 00:13:28,880 --> 00:13:30,600 and monitoring solutions. 405 00:13:30,600 --> 00:13:35,280 He emphasized model choice, offering over 1,800 models 406 00:13:35,280 --> 00:13:39,160 from providers like OpenAI, Meta, and Cohere. 407 00:13:39,160 --> 00:13:40,000 Wow. 408 00:13:40,000 --> 00:13:42,360 It's like they're creating a marketplace for AI models. 409 00:13:42,360 --> 00:13:43,800 So they're not just building their own models, 410 00:13:43,800 --> 00:13:44,880 they're providing a platform 411 00:13:44,880 --> 00:13:46,640 for others to share and access models. 412 00:13:46,640 --> 00:13:49,080 Yes, it's about creating an ecosystem 413 00:13:49,080 --> 00:13:52,720 where everyone can benefit from the latest AI advancements. 414 00:13:52,720 --> 00:13:54,320 That's pretty impressive. 415 00:13:54,320 --> 00:13:56,840 But he didn't just talk about business applications, did he? 416 00:13:56,840 --> 00:13:57,680 No. 417 00:13:57,680 --> 00:14:00,480 Nadella dedicated a significant chunk of his keynote 418 00:14:00,480 --> 00:14:02,400 to AI for science. 419 00:14:02,400 --> 00:14:06,080 He did, and this is where AI's potential truly shines. 420 00:14:06,080 --> 00:14:10,140 He talked about how AI is transforming scientific research, 421 00:14:10,140 --> 00:14:13,220 moving from static to dynamic prediction. 422 00:14:13,220 --> 00:14:14,800 This means scientists can now understand 423 00:14:14,800 --> 00:14:16,280 not just the shape of molecules, 424 00:14:16,280 --> 00:14:18,000 but their movement and interactions. 425 00:14:18,000 --> 00:14:19,760 Wow, that sounds incredibly complex. 426 00:14:19,760 --> 00:14:22,400 How is AI actually being used in scientific research? 427 00:14:22,400 --> 00:14:24,400 He shared some amazing examples. 428 00:14:24,400 --> 00:14:26,200 Novartis is using generative AI 429 00:14:26,200 --> 00:14:29,800 to design new drug molecules, accelerating drug discovery. 430 00:14:29,800 --> 00:14:30,620 Wow. 431 00:14:30,620 --> 00:14:32,560 Nissan is partnering with Microsoft 432 00:14:32,560 --> 00:14:34,040 to create a model that predicts 433 00:14:34,040 --> 00:14:36,120 EV battery performance over time, 434 00:14:36,120 --> 00:14:39,120 improving accuracy by a staggering 80%. 435 00:14:39,120 --> 00:14:39,960 Wow. 436 00:14:39,960 --> 00:14:42,000 And the Institute for Protein Design 437 00:14:42,000 --> 00:14:45,760 is utilizing Azure to engineer new proteins from scratch 438 00:14:45,760 --> 00:14:48,760 with potential applications in medicine and sustainability. 439 00:14:48,760 --> 00:14:51,680 Whoa, it sounds like AI is already having a major impact 440 00:14:51,680 --> 00:14:53,120 on scientific discovery. 441 00:14:53,120 --> 00:14:54,680 What about quantum computing? 442 00:14:54,680 --> 00:14:57,480 Nadella emphasized the potential of quantum computing 443 00:14:57,480 --> 00:15:00,680 to accelerate scientific discovery even further, 444 00:15:00,680 --> 00:15:02,400 highlighting Microsoft's progress 445 00:15:02,400 --> 00:15:04,520 in developing reliable qubits. 446 00:15:04,520 --> 00:15:07,800 He even announced a partnership with Atom Computing 447 00:15:07,800 --> 00:15:09,520 to create a commercial offering 448 00:15:09,520 --> 00:15:12,240 combining Azure Quantum with Atom's hardware. 449 00:15:12,240 --> 00:15:15,680 So they're not just thinking about today's AI challenges. 450 00:15:15,680 --> 00:15:16,760 They're already looking ahead 451 00:15:16,760 --> 00:15:19,080 to the next generation of computing technologies. 452 00:15:19,080 --> 00:15:19,920 Exactly. 453 00:15:19,920 --> 00:15:21,200 It's incredible how much they covered 454 00:15:21,200 --> 00:15:22,280 in a single keynote. 455 00:15:22,280 --> 00:15:24,000 It was a whirlwind of information, 456 00:15:24,000 --> 00:15:26,080 but Nadella managed to weave it all together 457 00:15:26,080 --> 00:15:28,960 into a compelling narrative about the future of AI 458 00:15:28,960 --> 00:15:32,120 and its potential to transform not just businesses, 459 00:15:32,120 --> 00:15:33,440 but the world. 460 00:15:33,440 --> 00:15:35,320 All right, so we've covered a lot of ground 461 00:15:35,320 --> 00:15:36,320 in this first segment. 462 00:15:36,320 --> 00:15:39,000 We've explored Microsoft's vision for AI 463 00:15:39,000 --> 00:15:43,840 with copilot devices and the Azure AI stack, 464 00:15:43,840 --> 00:15:45,440 but we've only scratched the surface. 465 00:15:45,440 --> 00:15:46,280 Right. 466 00:15:46,280 --> 00:15:47,280 In our next segment, 467 00:15:47,280 --> 00:15:49,520 we'll dive deeper into the practical applications 468 00:15:49,520 --> 00:15:50,480 of copilot. 469 00:15:50,480 --> 00:15:52,800 We'll explore how businesses are actually using it 470 00:15:52,800 --> 00:15:56,000 to streamline operations, enhance customer experiences, 471 00:15:56,000 --> 00:15:58,440 and unlock new levels of efficiency. 472 00:15:58,440 --> 00:16:00,840 It's gonna be fascinating to see how these AI tools 473 00:16:00,840 --> 00:16:02,760 are being used in the real world 474 00:16:02,760 --> 00:16:04,360 to solve real world problems. 475 00:16:04,360 --> 00:16:05,200 It is. 476 00:16:05,200 --> 00:16:06,040 Stay tuned. 477 00:16:06,040 --> 00:16:06,880 Yeah. 478 00:16:06,880 --> 00:16:07,840 All right, let's shift gears from the big picture 479 00:16:07,840 --> 00:16:11,560 and zoom in on how companies are actually using copilot 480 00:16:11,560 --> 00:16:12,720 to get things done. 481 00:16:12,720 --> 00:16:13,560 Yeah. 482 00:16:13,560 --> 00:16:15,960 We were blown away by some of the real world examples 483 00:16:15,960 --> 00:16:18,640 Nadella shared, and we wanna unpack them for you 484 00:16:18,640 --> 00:16:21,160 so you can see how this AI is already making a difference. 485 00:16:21,160 --> 00:16:23,120 What I found most compelling were the stories 486 00:16:23,120 --> 00:16:26,680 from industries that don't always scream cutting edge tech, 487 00:16:26,680 --> 00:16:28,440 like the Bank of Queensland group 488 00:16:28,440 --> 00:16:30,440 who were drowning in paperwork. 489 00:16:30,440 --> 00:16:31,280 Yeah. 490 00:16:31,280 --> 00:16:33,160 Trying to analyze thousands of documents 491 00:16:33,160 --> 00:16:34,560 for risk assessment. 492 00:16:34,560 --> 00:16:37,000 It's the kind of task that used to take weeks 493 00:16:37,000 --> 00:16:39,280 of painstaking manual effort. 494 00:16:39,280 --> 00:16:42,520 I can't even imagine sifting through that much paper. 495 00:16:42,520 --> 00:16:45,160 So how did copilot change the game for them? 496 00:16:45,160 --> 00:16:48,400 They managed to automate a huge chunk of that process. 497 00:16:48,400 --> 00:16:52,000 Tasks that used to take weeks are now done in a single day. 498 00:16:52,000 --> 00:16:54,440 Wow, that's a serious productivity boost. 499 00:16:54,440 --> 00:16:56,080 But it's not just about speed, is it? 500 00:16:56,080 --> 00:16:58,560 No, it's also about accuracy. 501 00:16:58,560 --> 00:17:02,200 Copilot can process and analyze vast amounts of data. 502 00:17:02,200 --> 00:17:03,040 Yeah. 503 00:17:03,040 --> 00:17:05,560 Spotting patterns and identifying potential risks 504 00:17:05,560 --> 00:17:08,240 far more efficiently than a human ever could. 505 00:17:08,240 --> 00:17:09,080 Right. 506 00:17:09,080 --> 00:17:11,840 This gives financial institutions a level of confidence 507 00:17:11,840 --> 00:17:14,080 and insight they simply didn't have before. 508 00:17:14,080 --> 00:17:16,120 So it's like having an AI risk analyst 509 00:17:16,120 --> 00:17:17,320 working alongside your team. 510 00:17:17,320 --> 00:17:18,140 Exactly. 511 00:17:18,140 --> 00:17:20,200 And the potential applications in finance 512 00:17:20,200 --> 00:17:22,680 go far beyond risk assessment. 513 00:17:22,680 --> 00:17:25,800 Think about fraud detection, loan processing, even investment 514 00:17:25,800 --> 00:17:27,040 analysis. 515 00:17:27,040 --> 00:17:29,760 Imagine giving copilot access to market data, 516 00:17:29,760 --> 00:17:32,280 financial reports, economic indicators. 517 00:17:32,280 --> 00:17:32,760 Yeah. 518 00:17:32,760 --> 00:17:34,960 It could potentially uncover opportunities 519 00:17:34,960 --> 00:17:36,280 that humans might miss. 520 00:17:36,280 --> 00:17:39,440 It's almost like giving every financial analyst a superpower. 521 00:17:39,440 --> 00:17:42,440 But let's move beyond the world of numbers. 522 00:17:42,440 --> 00:17:46,160 Nadella also highlighted how copilot is transforming customer 523 00:17:46,160 --> 00:17:49,440 service, an area where the human touch is often 524 00:17:49,440 --> 00:17:51,200 seen as essential. 525 00:17:51,200 --> 00:17:53,120 Tell me about Vodafone's experience. 526 00:17:53,120 --> 00:17:57,320 Vodafone was facing a classic customer service challenge. 527 00:17:57,320 --> 00:18:01,400 They handle over 45 million conversations every month. 528 00:18:01,400 --> 00:18:02,120 Wow. 529 00:18:02,120 --> 00:18:03,520 It's a logistical nightmare. 530 00:18:03,520 --> 00:18:04,040 Yeah. 531 00:18:04,040 --> 00:18:06,440 They were looking for a way to make the experience more 532 00:18:06,440 --> 00:18:08,800 efficient and personalized for customers. 533 00:18:08,800 --> 00:18:11,000 So how did they bring AI into the equation 534 00:18:11,000 --> 00:18:13,360 without losing that human touch? 535 00:18:13,360 --> 00:18:15,260 It's not about replacing humans. 536 00:18:15,260 --> 00:18:17,000 It's about augmenting their abilities. 537 00:18:17,000 --> 00:18:17,520 OK. 538 00:18:17,520 --> 00:18:19,640 Copilot handles the routine tasks, 539 00:18:19,640 --> 00:18:21,800 answering frequently asked questions, 540 00:18:21,800 --> 00:18:24,280 guiding customers through self-service options, 541 00:18:24,280 --> 00:18:27,920 freeing up human agents to focus on the more complex and nuanced 542 00:18:27,920 --> 00:18:28,560 issues. 543 00:18:28,560 --> 00:18:31,320 It's like having an AI-powered triage system, 544 00:18:31,320 --> 00:18:33,520 making sure customers get the right level of support 545 00:18:33,520 --> 00:18:34,840 quickly and efficiently. 546 00:18:34,840 --> 00:18:36,500 And the results speak for themselves. 547 00:18:36,500 --> 00:18:38,160 They've seen a significant decrease 548 00:18:38,160 --> 00:18:41,520 in average hold times, which makes customers happier. 549 00:18:41,520 --> 00:18:44,680 And their agents are less stressed and more empowered 550 00:18:44,680 --> 00:18:46,360 to tackle the tougher problems. 551 00:18:46,360 --> 00:18:47,600 It's a win-win. 552 00:18:47,600 --> 00:18:49,160 I'm starting to see how this AI could 553 00:18:49,160 --> 00:18:51,880 fit into so many different aspects of a business. 554 00:18:51,880 --> 00:18:53,800 But what about industries that are pushing 555 00:18:53,800 --> 00:18:55,880 the boundaries of human knowledge, 556 00:18:55,880 --> 00:18:57,720 like scientific research? 557 00:18:57,720 --> 00:18:59,920 Nadella touched on some fascinating applications 558 00:18:59,920 --> 00:19:00,640 in that area. 559 00:19:00,640 --> 00:19:02,560 This is where it gets really exciting. 560 00:19:02,560 --> 00:19:05,580 Nadella talked about the shift from static to dynamic 561 00:19:05,580 --> 00:19:06,960 prediction. 562 00:19:06,960 --> 00:19:09,720 Imagine being able to not just predict 563 00:19:09,720 --> 00:19:13,160 the shape of molecules, but to actually understand 564 00:19:13,160 --> 00:19:15,720 their movement and interactions. 565 00:19:15,720 --> 00:19:17,680 This has huge implications for fields 566 00:19:17,680 --> 00:19:22,040 like drug discovery, materials science, even renewable energy. 567 00:19:22,040 --> 00:19:24,760 He mentioned Novartis using generative AI 568 00:19:24,760 --> 00:19:27,120 to design new drug molecules. 569 00:19:27,120 --> 00:19:28,120 That sounds incredible. 570 00:19:28,120 --> 00:19:29,840 What does that even look like in practice? 571 00:19:29,840 --> 00:19:33,360 Traditional drug discovery is incredibly slow and expensive. 572 00:19:33,360 --> 00:19:36,920 You're essentially testing thousands, even millions, 573 00:19:36,920 --> 00:19:40,720 of compounds in the lab to see if they have the desired effect. 574 00:19:40,720 --> 00:19:42,760 Generative AI flips the script. 575 00:19:42,760 --> 00:19:44,960 Scientists can now train AI models 576 00:19:44,960 --> 00:19:47,720 on massive data sets of molecular structures 577 00:19:47,720 --> 00:19:49,080 and properties. 578 00:19:49,080 --> 00:19:51,800 The AI can then virtually design and test 579 00:19:51,800 --> 00:19:55,080 new molecules, significantly speeding up the discovery 580 00:19:55,080 --> 00:19:55,920 process. 581 00:19:55,920 --> 00:19:57,160 It's amazing. 582 00:19:57,160 --> 00:19:58,920 It could potentially lead to the development 583 00:19:58,920 --> 00:20:01,360 of new drugs and therapies for diseases 584 00:20:01,360 --> 00:20:02,680 that currently have no cure. 585 00:20:02,680 --> 00:20:03,320 Exactly. 586 00:20:03,320 --> 00:20:04,880 And it's not just limited to medicine. 587 00:20:04,880 --> 00:20:07,420 He also talked about Nissan using AI 588 00:20:07,420 --> 00:20:11,080 to predict the performance of EV batteries over time. 589 00:20:11,080 --> 00:20:13,720 They've seen an 80% improvement in accuracy. 590 00:20:13,720 --> 00:20:14,240 Wow. 591 00:20:14,240 --> 00:20:16,600 This could lead to longer lasting, more efficient 592 00:20:16,600 --> 00:20:18,920 batteries, which is a game changer for the adoption 593 00:20:18,920 --> 00:20:20,040 of electric vehicles. 594 00:20:20,040 --> 00:20:22,320 It's incredible to see how AI is being applied 595 00:20:22,320 --> 00:20:25,600 to these real world problems that affect us all. 596 00:20:25,600 --> 00:20:27,240 What other examples stood out to you? 597 00:20:27,240 --> 00:20:29,840 The work being done by the Institute for Protein Design 598 00:20:29,840 --> 00:20:31,040 is mind blowing. 599 00:20:31,040 --> 00:20:33,320 They're actually using Azure to engineer 600 00:20:33,320 --> 00:20:34,640 new proteins from scratch. 601 00:20:34,640 --> 00:20:35,160 Wow. 602 00:20:35,160 --> 00:20:37,080 Proteins are the building blocks of life. 603 00:20:37,080 --> 00:20:37,600 Yeah. 604 00:20:37,600 --> 00:20:39,600 So being able to design new proteins 605 00:20:39,600 --> 00:20:43,080 with specific functions could revolutionize so many fields. 606 00:20:43,080 --> 00:20:45,160 What kind of applications are we talking about? 607 00:20:45,160 --> 00:20:49,160 Imagine designing proteins that can break down pollutants, 608 00:20:49,160 --> 00:20:53,440 create new materials, or even target specific diseases. 609 00:20:53,440 --> 00:20:57,160 The possibilities are truly endless. 610 00:20:57,160 --> 00:20:59,560 This all seems incredibly futuristic, 611 00:20:59,560 --> 00:21:00,920 yet it's happening right now. 612 00:21:00,920 --> 00:21:01,400 Yeah. 613 00:21:01,400 --> 00:21:03,760 It's amazing to think that this is just the beginning. 614 00:21:03,760 --> 00:21:05,080 Exactly. 615 00:21:05,080 --> 00:21:07,920 As these AI technologies continue to evolve, 616 00:21:07,920 --> 00:21:10,640 we can expect even more groundbreaking applications 617 00:21:10,640 --> 00:21:12,560 to emerge in the years to come. 618 00:21:12,560 --> 00:21:14,800 It's an exciting time to be witnessing 619 00:21:14,800 --> 00:21:17,880 this technological revolution unfold. 620 00:21:17,880 --> 00:21:21,640 It's clear that AI is no longer a distant concept. 621 00:21:21,640 --> 00:21:24,320 It's here, it's evolving rapidly, 622 00:21:24,320 --> 00:21:27,680 and it's already having a profound impact on our world. 623 00:21:27,680 --> 00:21:32,480 OK, so we've seen how Microsoft is building this powerful AI 624 00:21:32,480 --> 00:21:33,640 ecosystem. 625 00:21:33,640 --> 00:21:36,400 And we've explored some pretty incredible real world 626 00:21:36,400 --> 00:21:37,640 applications. 627 00:21:37,640 --> 00:21:40,600 But as with any transformative technology, 628 00:21:40,600 --> 00:21:43,520 there's another side to this story. 629 00:21:43,520 --> 00:21:46,000 Nadella briefly touched on it in his keynote. 630 00:21:46,000 --> 00:21:47,800 And I think it's worth unpacking a little bit. 631 00:21:47,800 --> 00:21:48,520 Yeah, for sure. 632 00:21:48,520 --> 00:21:51,080 You're talking about the potential downsides of AI. 633 00:21:51,080 --> 00:21:53,880 The risks that come with handing over 634 00:21:53,880 --> 00:21:55,600 so much control to algorithms. 635 00:21:55,600 --> 00:21:57,920 It's like we're opening Pandora's box, right? 636 00:21:57,920 --> 00:21:58,440 Exactly. 637 00:21:58,440 --> 00:22:00,120 We need to be sure we're not unleashing 638 00:22:00,120 --> 00:22:01,600 something we can't control. 639 00:22:01,600 --> 00:22:02,880 Yeah. 640 00:22:02,880 --> 00:22:04,080 It's a valid concern. 641 00:22:04,080 --> 00:22:07,480 And to be fair to Nadella, he didn't shy away from it. 642 00:22:07,480 --> 00:22:09,080 He acknowledged that with great power 643 00:22:09,080 --> 00:22:11,320 comes great responsibility. 644 00:22:11,320 --> 00:22:13,200 He talked about the need for guardrails, 645 00:22:13,200 --> 00:22:15,520 for ethical frameworks to guide the development 646 00:22:15,520 --> 00:22:16,960 and deployment of AI. 647 00:22:16,960 --> 00:22:17,920 Yeah, absolutely. 648 00:22:17,920 --> 00:22:19,480 I mean, it's a really important point. 649 00:22:19,480 --> 00:22:22,240 But what does that actually look like in practice? 650 00:22:22,240 --> 00:22:26,160 How do we ensure that AI is used for good and not for harm? 651 00:22:26,160 --> 00:22:28,720 Well, I think it starts with recognizing 652 00:22:28,720 --> 00:22:33,400 that AI systems are only as good as the data they're trained on. 653 00:22:33,400 --> 00:22:36,720 If the data is biased, the AI will be biased. 654 00:22:36,720 --> 00:22:39,080 We need to be incredibly careful about the data sets 655 00:22:39,080 --> 00:22:41,240 we use to train these models, making 656 00:22:41,240 --> 00:22:43,520 sure they're diverse, representative, and free 657 00:22:43,520 --> 00:22:44,960 from harmful prejudices. 658 00:22:44,960 --> 00:22:47,320 So it's not just about the algorithms themselves. 659 00:22:47,320 --> 00:22:49,320 It's about the data that feeds them. 660 00:22:49,320 --> 00:22:49,960 Absolutely. 661 00:22:49,960 --> 00:22:52,040 And it's about transparency. 662 00:22:52,040 --> 00:22:55,560 People need to understand how these AI systems work, 663 00:22:55,560 --> 00:22:56,920 how they make decisions. 664 00:22:56,920 --> 00:22:58,200 It can't be a black docks. 665 00:22:58,200 --> 00:22:58,920 That makes sense. 666 00:22:58,920 --> 00:23:00,640 If we're going to trust these systems, 667 00:23:00,640 --> 00:23:03,080 we need to be able to see under the hood. 668 00:23:03,080 --> 00:23:04,360 Exactly. 669 00:23:04,360 --> 00:23:06,560 And then there's the question of accountability. 670 00:23:06,560 --> 00:23:10,760 Who's responsible if an AI system makes mistake? 671 00:23:10,760 --> 00:23:13,320 Or worse, causes harm. 672 00:23:13,320 --> 00:23:16,160 These are complex collisions that we as a society 673 00:23:16,160 --> 00:23:20,000 need to grapple with as AI becomes more deeply integrated 674 00:23:20,000 --> 00:23:21,200 into our lives. 675 00:23:21,200 --> 00:23:22,600 It's a lot to consider. 676 00:23:22,600 --> 00:23:24,480 But it sounds like there's a growing awareness 677 00:23:24,480 --> 00:23:26,320 of these challenges, which is encouraging. 678 00:23:26,320 --> 00:23:26,960 There is. 679 00:23:26,960 --> 00:23:28,560 And it's not just lip service. 680 00:23:28,560 --> 00:23:32,160 Organizations like Microsoft are actively working on solutions. 681 00:23:32,160 --> 00:23:35,160 They're developing tools to help developers identify and mitigate 682 00:23:35,160 --> 00:23:37,240 bias in their AI models. 683 00:23:37,240 --> 00:23:39,600 They're investing in research to make AI systems more 684 00:23:39,600 --> 00:23:41,440 transparent and explainable. 685 00:23:41,440 --> 00:23:43,520 So it's not just about sounding the alarm. 686 00:23:43,520 --> 00:23:45,520 It's about actually finding solutions. 687 00:23:45,520 --> 00:23:46,800 And it's a collaborative effort. 688 00:23:46,800 --> 00:23:49,680 Governments, industry leaders, researchers, everyone 689 00:23:49,680 --> 00:23:51,440 needs to be part of the conversation. 690 00:23:51,440 --> 00:23:54,320 It's a reminder that technology isn't neutral. 691 00:23:54,320 --> 00:23:56,800 It reflects the values of the people who create it 692 00:23:56,800 --> 00:23:58,600 and the societies in which it's deployed. 693 00:23:58,600 --> 00:23:59,620 Exactly. 694 00:23:59,620 --> 00:24:02,760 And as AI becomes more powerful, the stakes get higher. 695 00:24:02,760 --> 00:24:05,880 We need to be mindful of the potential for AI 696 00:24:05,880 --> 00:24:08,200 to exacerbate existing inequalities, 697 00:24:08,200 --> 00:24:10,680 to create new forms of discrimination. 698 00:24:10,680 --> 00:24:13,080 Yeah, Nadella touched on this briefly in his keynote, 699 00:24:13,080 --> 00:24:13,580 didn't he? 700 00:24:13,580 --> 00:24:16,800 He talked about the need for AI to benefit everyone, 701 00:24:16,800 --> 00:24:18,080 not just a select few. 702 00:24:18,080 --> 00:24:18,600 He did. 703 00:24:18,600 --> 00:24:21,400 And it's not just about access to AI technology. 704 00:24:21,400 --> 00:24:24,160 It's about access to AI education and training. 705 00:24:24,160 --> 00:24:26,600 We need to ensure that everyone has the opportunity 706 00:24:26,600 --> 00:24:29,000 to develop the skills they need to thrive 707 00:24:29,000 --> 00:24:30,440 in an AI-powered world. 708 00:24:30,440 --> 00:24:32,040 So it's not just a technical challenge. 709 00:24:32,040 --> 00:24:33,720 It's a societal challenge. 710 00:24:33,720 --> 00:24:36,600 It's about ensuring that AI serves humanity, not 711 00:24:36,600 --> 00:24:37,640 the other way around. 712 00:24:37,640 --> 00:24:39,180 I think that's a great way to put it. 713 00:24:39,180 --> 00:24:41,360 And that brings us back to you, the listener. 714 00:24:41,360 --> 00:24:42,960 As we've explored in this deep dive, 715 00:24:42,960 --> 00:24:46,280 AI is no longer a futuristic fantasy. 716 00:24:46,280 --> 00:24:46,960 It's here. 717 00:24:46,960 --> 00:24:48,540 It's evolving rapidly. 718 00:24:48,540 --> 00:24:51,800 And it's already having a profound impact on our world. 719 00:24:51,800 --> 00:24:54,560 What struck you the most from Nadella's keynote? 720 00:24:54,560 --> 00:24:56,280 What are you most excited about? 721 00:24:56,280 --> 00:24:57,740 What concerns you? 722 00:24:57,740 --> 00:25:00,240 These are questions worth pondering as we navigate this, 723 00:25:00,240 --> 00:25:02,360 like uncharted territory. 724 00:25:02,360 --> 00:25:05,400 We encourage you to continue exploring these ideas. 725 00:25:05,400 --> 00:25:06,980 Read more about AI ethics. 726 00:25:06,980 --> 00:25:09,440 Engage in conversations about the potential benefits 727 00:25:09,440 --> 00:25:10,500 and risks. 728 00:25:10,500 --> 00:25:14,560 Ask questions about how AI is being developed and deployed 729 00:25:14,560 --> 00:25:17,640 in your industry, in your community. 730 00:25:17,640 --> 00:25:19,320 This is a conversation that needs to happen 731 00:25:19,320 --> 00:25:21,080 at all levels of society. 732 00:25:21,080 --> 00:25:22,800 The choices we make today will determine 733 00:25:22,800 --> 00:25:26,560 the course of the AI revolution and its impact on our future. 734 00:25:26,560 --> 00:25:28,520 We've covered a lot of ground in this deep dive. 735 00:25:28,520 --> 00:25:29,040 We sure have. 736 00:25:29,040 --> 00:25:31,760 From the mind blowing capabilities of co-pilot 737 00:25:31,760 --> 00:25:34,720 to the profound ethical considerations surrounding AI, 738 00:25:34,720 --> 00:25:37,320 it's clear that we're at a pretty pivotal moment 739 00:25:37,320 --> 00:25:38,360 in history. 740 00:25:38,360 --> 00:25:40,880 As always, we encourage you to keep learning, keep exploring, 741 00:25:40,880 --> 00:25:42,440 and keep asking questions. 742 00:25:42,440 --> 00:25:45,880 Because in the age of AI, knowledge is power. 743 00:25:45,880 --> 00:25:48,080 And the more we understand this technology, 744 00:25:48,080 --> 00:25:50,640 the better equipped we'll be to shape its future. 745 00:25:50,640 --> 00:25:52,240 Thanks for joining us on this deep dive. 746 00:25:52,240 --> 00:25:54,680 We'll be back soon with another fascinating exploration 747 00:25:54,680 --> 00:25:59,280 of the latest trends and ideas shaping our world.