1 00:00:00,000 --> 00:00:02,080 All right, everyone ready to dive in. 2 00:00:02,080 --> 00:00:05,480 Today we're going deep on organoid intelligence. 3 00:00:05,480 --> 00:00:06,320 Oh, yeah. 4 00:00:06,320 --> 00:00:07,160 Play, OI. 5 00:00:07,160 --> 00:00:10,520 Yeah, where brain cells meet computer chips. 6 00:00:10,520 --> 00:00:12,160 It's like something out of sci-fi, isn't it? 7 00:00:12,160 --> 00:00:14,600 It really is, but it's actually happening right now. 8 00:00:14,600 --> 00:00:15,880 We're talking about real science. 9 00:00:15,880 --> 00:00:17,200 Real science. 10 00:00:17,200 --> 00:00:21,400 And to guide us today, we have an interview with Brett Kagan, 11 00:00:21,400 --> 00:00:24,840 a neuroscientist who's at the forefront of this OI research. 12 00:00:24,840 --> 00:00:27,360 And he is just brilliant. 13 00:00:27,360 --> 00:00:30,160 You can tell he's really excited about the potential of OI. 14 00:00:30,160 --> 00:00:30,660 Absolutely. 15 00:00:30,660 --> 00:00:33,360 And I think what struck me was not only the potential, 16 00:00:33,360 --> 00:00:38,120 but also his awareness of the challenges and the complexity 17 00:00:38,120 --> 00:00:41,040 of it all, replicating even the most basic brain function. 18 00:00:41,040 --> 00:00:42,520 It's a huge undertaking. 19 00:00:42,520 --> 00:00:44,360 Yeah, so think of this as like a crash course 20 00:00:44,360 --> 00:00:45,600 in organoid intelligence. 21 00:00:45,600 --> 00:00:46,080 Exactly. 22 00:00:46,080 --> 00:00:48,320 We're going to break down what it is, how it works, 23 00:00:48,320 --> 00:00:50,480 and why it could actually revolutionize the world 24 00:00:50,480 --> 00:00:51,560 as we know it. 25 00:00:51,560 --> 00:00:52,920 By the end of this deep dive, you'll 26 00:00:52,920 --> 00:00:55,560 know what OI is, what it can do, and what some of the hurdles 27 00:00:55,560 --> 00:00:56,760 are that researchers are facing. 28 00:00:56,760 --> 00:00:58,520 OK, so let's start with the basics. 29 00:00:58,520 --> 00:01:01,000 What exactly is organoid intelligence? 30 00:01:01,000 --> 00:01:04,080 So imagine scientists growing these tiny 3D clusters 31 00:01:04,080 --> 00:01:07,040 of brain cells called organoids in a dish. 32 00:01:07,040 --> 00:01:07,920 Like mini brains. 33 00:01:07,920 --> 00:01:09,200 Mini brains, exactly. 34 00:01:09,200 --> 00:01:10,560 And these organoids, they actually 35 00:01:10,560 --> 00:01:12,920 have some of the functional properties of a real brain. 36 00:01:12,920 --> 00:01:13,400 Wow. 37 00:01:13,400 --> 00:01:14,920 They can learn and adapt. 38 00:01:14,920 --> 00:01:16,000 Seriously. 39 00:01:16,000 --> 00:01:17,320 And researchers like Kagan, they're 40 00:01:17,320 --> 00:01:20,720 connecting these mini brains to electronic circuits, 41 00:01:20,720 --> 00:01:23,480 basically creating this hybrid bio computer. 42 00:01:23,480 --> 00:01:26,320 OK, so we've got these mini brains on a chip. 43 00:01:26,320 --> 00:01:28,480 What can they actually do? 44 00:01:28,480 --> 00:01:31,200 Well, one of the most amazing demonstrations of OI 45 00:01:31,200 --> 00:01:34,240 was an experiment where they taught a network of these brain 46 00:01:34,240 --> 00:01:35,440 cells to play pong. 47 00:01:35,440 --> 00:01:37,520 Hold on, brain cells playing video games. 48 00:01:37,520 --> 00:01:38,680 How is that even possible? 49 00:01:38,680 --> 00:01:39,600 Sounds wild. 50 00:01:39,600 --> 00:01:42,040 I know, but get these neurons learned to play 51 00:01:42,040 --> 00:01:43,960 pong in just five minutes. 52 00:01:43,960 --> 00:01:44,680 Five minutes. 53 00:01:44,680 --> 00:01:45,200 Five minutes. 54 00:01:45,200 --> 00:01:47,840 It shows you how incredible the brain's natural learning 55 00:01:47,840 --> 00:01:48,640 ability is. 56 00:01:48,640 --> 00:01:49,920 That's crazy fast. 57 00:01:49,920 --> 00:01:52,320 Especially when you compare it to traditional AI. 58 00:01:52,320 --> 00:01:55,360 Yeah, traditional AI takes like hours or even days 59 00:01:55,360 --> 00:01:56,440 to learn something like that. 60 00:01:56,440 --> 00:01:57,280 Absolutely. 61 00:01:57,280 --> 00:01:59,240 This difference in learning speed 62 00:01:59,240 --> 00:02:01,560 is one of the things that has researchers so excited 63 00:02:01,560 --> 00:02:03,160 about the potential of OI. 64 00:02:03,160 --> 00:02:05,600 So why even bother with growing brain cells 65 00:02:05,600 --> 00:02:07,240 when we already have AI? 66 00:02:07,240 --> 00:02:10,280 I mean, what's the big advantage of OI? 67 00:02:10,280 --> 00:02:11,200 That's a great question. 68 00:02:11,200 --> 00:02:12,960 And Kagan addresses that directly. 69 00:02:12,960 --> 00:02:16,240 He says that brain cells are way more energy efficient 70 00:02:16,240 --> 00:02:17,720 than our current AI systems. 71 00:02:17,720 --> 00:02:19,400 So it's all about efficiency. 72 00:02:19,400 --> 00:02:19,920 Think about it. 73 00:02:19,920 --> 00:02:23,560 The human brain runs on roughly 20 watts of power. 74 00:02:23,560 --> 00:02:24,240 That's it? 75 00:02:24,240 --> 00:02:24,680 That's it. 76 00:02:24,680 --> 00:02:27,240 Now, compare that to the huge amount of energy 77 00:02:27,240 --> 00:02:30,640 used by data centers powering today's AI models. 78 00:02:30,640 --> 00:02:33,400 And you start to see the sustainability advantage of OI. 79 00:02:33,400 --> 00:02:34,360 OK, that makes sense. 80 00:02:34,360 --> 00:02:36,040 Less energy faster. 81 00:02:36,040 --> 00:02:37,960 Learning OI is sounding pretty impressive. 82 00:02:37,960 --> 00:02:39,400 It definitely has potential. 83 00:02:39,400 --> 00:02:42,720 Another area Kagan highlights is this idea of embodiment, 84 00:02:42,720 --> 00:02:46,520 which could be key to unlocking even more of OI's capabilities. 85 00:02:46,520 --> 00:02:47,200 Embodiment. 86 00:02:47,200 --> 00:02:49,160 What does that even mean when we're talking about brain cells 87 00:02:49,160 --> 00:02:49,960 in a dish? 88 00:02:49,960 --> 00:02:52,640 Imagine giving these brain cells a virtual body 89 00:02:52,640 --> 00:02:54,160 in a simulated environment. 90 00:02:54,160 --> 00:02:54,640 OK. 91 00:02:54,640 --> 00:02:56,120 So they can interact with objects, 92 00:02:56,120 --> 00:02:59,040 experience consequences, and learn through that interaction. 93 00:02:59,040 --> 00:03:02,240 So it's not just input and output, like with regular AI? 94 00:03:02,240 --> 00:03:02,760 Exactly. 95 00:03:02,760 --> 00:03:04,760 It's about allowing these neuron networks 96 00:03:04,760 --> 00:03:07,640 to really understand their world, you know, 97 00:03:07,640 --> 00:03:10,000 making their learning more meaningful, more like how 98 00:03:10,000 --> 00:03:11,280 we learn in the real world. 99 00:03:11,280 --> 00:03:11,760 Wow. 100 00:03:11,760 --> 00:03:15,080 OK, so we've got these organoids learning super fast, 101 00:03:15,080 --> 00:03:17,760 potentially using way less energy. 102 00:03:17,760 --> 00:03:21,720 And now they have virtual bodies to experience their environment. 103 00:03:21,720 --> 00:03:22,920 It's pretty mind blowing. 104 00:03:22,920 --> 00:03:24,880 What's next for OI? 105 00:03:24,880 --> 00:03:27,120 What are researchers focused on now? 106 00:03:27,120 --> 00:03:30,000 Well, one of the big things is developing hardware and software, 107 00:03:30,000 --> 00:03:32,160 specifically designed for OI. 108 00:03:32,160 --> 00:03:34,720 Right, because right now they're using what's already out there. 109 00:03:34,720 --> 00:03:35,280 Exactly. 110 00:03:35,280 --> 00:03:37,160 They're having to kind of hack things together 111 00:03:37,160 --> 00:03:40,120 to make even basic experiments like the Pong game work. 112 00:03:40,120 --> 00:03:42,320 So imagine what they could do with the right tools. 113 00:03:42,320 --> 00:03:43,040 Exactly. 114 00:03:43,040 --> 00:03:45,280 That's where a lot of the research is focused right now, 115 00:03:45,280 --> 00:03:47,920 developing those tools and platforms that could really 116 00:03:47,920 --> 00:03:49,400 take OI to the next level. 117 00:03:49,400 --> 00:03:51,000 What about scaling this up? 118 00:03:51,000 --> 00:03:56,400 Can we make these organoid brains bigger, more complex, 119 00:03:56,400 --> 00:03:59,160 you know, handle tasks beyond playing Pong? 120 00:03:59,160 --> 00:04:00,560 That is the million dollar question. 121 00:04:00,560 --> 00:04:01,960 And it's one of the biggest challenges 122 00:04:01,960 --> 00:04:03,320 that researchers are facing right now. 123 00:04:03,320 --> 00:04:03,800 Yeah. 124 00:04:03,800 --> 00:04:07,040 Can we create OI systems that are intelligent, 125 00:04:07,040 --> 00:04:09,720 but also robust, reliable, and able to tackle 126 00:04:09,720 --> 00:04:10,840 more complex problems? 127 00:04:10,840 --> 00:04:12,160 It's still an open question. 128 00:04:12,160 --> 00:04:14,800 So it seems like we're still in the early stages of figuring out 129 00:04:14,800 --> 00:04:16,240 what OI can really do. 130 00:04:16,240 --> 00:04:19,960 We are, but that's also what makes this field so exciting. 131 00:04:19,960 --> 00:04:23,960 We're on the cusp of a potential revolution in computing. 132 00:04:23,960 --> 00:04:26,960 With any new technology, there are definitely hurdles 133 00:04:26,960 --> 00:04:29,560 to overcome, and a lot we still don't know. 134 00:04:29,560 --> 00:04:30,440 Absolutely. 135 00:04:30,440 --> 00:04:32,320 But I think it's safe to say the future of OI 136 00:04:32,320 --> 00:04:35,600 is incredibly promising, and we're just scratching the surface. 137 00:04:35,600 --> 00:04:38,800 We've covered the basics of what OI is and how it works, 138 00:04:38,800 --> 00:04:40,960 but what can we actually deal with it? 139 00:04:40,960 --> 00:04:42,680 Where can we apply this technology? 140 00:04:42,680 --> 00:04:43,600 Well, that's exactly what we're going 141 00:04:43,600 --> 00:04:45,800 to be talking about in part two of this deep dive. 142 00:04:45,800 --> 00:04:47,160 Tattoo, and we'll be right back. 143 00:04:47,160 --> 00:04:50,240 We'll delve into the potential applications of OI, 144 00:04:50,240 --> 00:04:53,720 from revolutionizing medicine to changing the way we think 145 00:04:53,720 --> 00:04:55,080 about computing itself. 146 00:04:55,080 --> 00:04:56,040 Welcome back, everyone. 147 00:04:56,040 --> 00:04:58,320 So we're continuing our exploration of organoid 148 00:04:58,320 --> 00:04:59,640 intelligence, and this time we're 149 00:04:59,640 --> 00:05:01,400 looking at its potential applications. 150 00:05:01,400 --> 00:05:03,720 Like, where could OI make a real difference? 151 00:05:03,720 --> 00:05:05,000 The potential is huge. 152 00:05:05,000 --> 00:05:08,480 It really spans fields like medicine computing, 153 00:05:08,480 --> 00:05:11,680 even how we understand consciousness itself. 154 00:05:11,680 --> 00:05:13,240 So let's start with medicine. 155 00:05:13,240 --> 00:05:16,880 Kagan talked about drug discovery and disease modeling. 156 00:05:16,880 --> 00:05:19,160 How could OI have an impact there? 157 00:05:19,160 --> 00:05:22,760 Well, imagine testing new drugs on actual human brain cells, 158 00:05:22,760 --> 00:05:26,280 but without the ethical concerns of human trials. 159 00:05:26,280 --> 00:05:29,680 OI could revolutionize drug development. 160 00:05:29,680 --> 00:05:31,720 It could give us a faster and more efficient way 161 00:05:31,720 --> 00:05:32,920 to find new treatments. 162 00:05:32,920 --> 00:05:34,920 So speed things up and make it more effective. 163 00:05:34,920 --> 00:05:37,920 Exactly, and because these organoids come from human cells, 164 00:05:37,920 --> 00:05:40,680 they could also provide a much more accurate model 165 00:05:40,680 --> 00:05:44,280 for studying diseases like Alzheimer's or Parkinson's. 166 00:05:44,280 --> 00:05:47,200 So we could actually understand these diseases better. 167 00:05:47,200 --> 00:05:49,600 Yes, potentially leading to new therapies. 168 00:05:49,600 --> 00:05:50,400 That's incredible. 169 00:05:50,400 --> 00:05:52,360 It's like having a personalized testing ground 170 00:05:52,360 --> 00:05:53,320 for each patient. 171 00:05:53,320 --> 00:05:55,200 Yeah, that's the ultimate goal. 172 00:05:55,200 --> 00:05:58,160 Personalized medicine tailored to an individual's genes, 173 00:05:58,160 --> 00:06:00,400 and OI could play a big role in making that happen. 174 00:06:00,400 --> 00:06:02,960 So are we talking about curing diseases that 175 00:06:02,960 --> 00:06:04,600 are currently incurable? 176 00:06:04,600 --> 00:06:07,360 It's possible, although OI is still in its early stages. 177 00:06:07,360 --> 00:06:09,520 A lot of research needs to be done before we 178 00:06:09,520 --> 00:06:10,760 see those kinds of breakthroughs. 179 00:06:10,760 --> 00:06:11,920 But the potential is there. 180 00:06:11,920 --> 00:06:14,360 What about applications beyond medicine? 181 00:06:14,360 --> 00:06:16,880 Kagan mentioned OI-powered prosthetics. 182 00:06:16,880 --> 00:06:18,840 Now that's one of the most fascinating applications, 183 00:06:18,840 --> 00:06:19,760 I think. 184 00:06:19,760 --> 00:06:23,560 Imagine a prosthetic arm controlled not by motors, 185 00:06:23,560 --> 00:06:26,240 but by your thoughts seamlessly integrated 186 00:06:26,240 --> 00:06:27,280 with your nervous system. 187 00:06:27,280 --> 00:06:29,240 That sounds straight out of science fiction. 188 00:06:29,240 --> 00:06:30,040 It does, doesn't it? 189 00:06:30,040 --> 00:06:30,540 Yeah. 190 00:06:30,540 --> 00:06:32,240 But that's the potential of OI. 191 00:06:32,240 --> 00:06:33,600 How would that even work? 192 00:06:33,600 --> 00:06:36,040 It's all about creating a direct connection 193 00:06:36,040 --> 00:06:39,400 between the organoid and the nervous system. 194 00:06:39,400 --> 00:06:42,600 The organoid could learn to interpret brain signals 195 00:06:42,600 --> 00:06:45,600 and translate them into commands for the prosthetic limb. 196 00:06:45,600 --> 00:06:48,680 So the organoid would be like a translator between your brain 197 00:06:48,680 --> 00:06:49,800 and the prosthetic. 198 00:06:49,800 --> 00:06:50,880 That's a great way to put it. 199 00:06:50,880 --> 00:06:52,960 It's still experimental, but researchers 200 00:06:52,960 --> 00:06:55,120 are making progress in connecting organoids 201 00:06:55,120 --> 00:06:56,720 to peripheral nerves. 202 00:06:56,720 --> 00:06:58,800 Wow, the possibilities are amazing. 203 00:06:58,800 --> 00:07:00,120 What about computing itself? 204 00:07:00,120 --> 00:07:02,920 Could OI change the way we think about computers? 205 00:07:02,920 --> 00:07:04,920 That's what a lot of researchers are exploring. 206 00:07:04,920 --> 00:07:06,840 Kagan talked about heterogeneous compute 207 00:07:06,840 --> 00:07:09,000 combining different types of processing units. 208 00:07:09,000 --> 00:07:11,160 So instead of just CPUs and GPUs, 209 00:07:11,160 --> 00:07:13,440 you'd have these biological processing units, too, 210 00:07:13,440 --> 00:07:14,240 the organoids. 211 00:07:14,240 --> 00:07:14,960 Exactly. 212 00:07:14,960 --> 00:07:18,800 Each type of unit has its own strengths and weaknesses. 213 00:07:18,800 --> 00:07:21,480 By combining them, you create a system that's 214 00:07:21,480 --> 00:07:23,520 more powerful than the sum of its parts. 215 00:07:23,520 --> 00:07:25,040 So it's not about replacing our computers, 216 00:07:25,040 --> 00:07:27,560 but making them better with this new kind 217 00:07:27,560 --> 00:07:29,160 of biological intelligence. 218 00:07:29,160 --> 00:07:30,160 That's the idea. 219 00:07:30,160 --> 00:07:32,840 We need to think of OI as complementary to what we already 220 00:07:32,840 --> 00:07:33,480 have. 221 00:07:33,480 --> 00:07:35,720 It's about expanding what computers can do. 222 00:07:35,720 --> 00:07:37,920 Kagan also mentioned learning from OI 223 00:07:37,920 --> 00:07:41,040 to improve our understanding of how humans learn. 224 00:07:41,040 --> 00:07:41,540 Right. 225 00:07:41,540 --> 00:07:43,560 By studying how organoids learn, we 226 00:07:43,560 --> 00:07:46,160 could gain insights into the basic principles of learning 227 00:07:46,160 --> 00:07:49,000 and intelligence that could then be applied to how we learn. 228 00:07:49,000 --> 00:07:50,520 So we're not just building better computers, 229 00:07:50,520 --> 00:07:52,120 but understanding ourselves better. 230 00:07:52,120 --> 00:07:52,640 Exactly. 231 00:07:52,640 --> 00:07:54,600 OI could revolutionize technology, 232 00:07:54,600 --> 00:07:57,040 but it could also deepen our understanding of who we are 233 00:07:57,040 --> 00:07:58,400 and how we think. 234 00:07:58,400 --> 00:07:58,880 OK. 235 00:07:58,880 --> 00:08:00,560 So we've talked about all these applications, 236 00:08:00,560 --> 00:08:02,400 but what are some of the challenges that 237 00:08:02,400 --> 00:08:05,800 stand in the way of OI becoming a reality? 238 00:08:05,800 --> 00:08:07,520 One of the biggest is scalability. 239 00:08:07,520 --> 00:08:09,720 Can we actually grow these organoids 240 00:08:09,720 --> 00:08:11,920 to be big enough and complex enough 241 00:08:11,920 --> 00:08:13,520 to handle real-world tasks? 242 00:08:13,520 --> 00:08:14,020 Right. 243 00:08:14,020 --> 00:08:16,520 Playing pong is one thing, but controlling a prosthetic 244 00:08:16,520 --> 00:08:18,680 or designing a new drug is a whole other level. 245 00:08:18,680 --> 00:08:19,200 Exactly. 246 00:08:19,200 --> 00:08:22,360 Another challenge is robustness and reliability. 247 00:08:22,360 --> 00:08:25,280 Can we create OI systems that are stable 248 00:08:25,280 --> 00:08:27,080 and work consistently over time? 249 00:08:27,080 --> 00:08:29,000 Remember, these are biological systems. 250 00:08:29,000 --> 00:08:30,280 They can be quite fragile. 251 00:08:30,280 --> 00:08:31,000 That makes sense. 252 00:08:31,000 --> 00:08:32,720 And what about the hardware and software? 253 00:08:32,720 --> 00:08:35,760 We talked about the limitations of existing technology. 254 00:08:35,760 --> 00:08:37,560 How are researchers dealing with that? 255 00:08:37,560 --> 00:08:39,400 Well, there's a lot of work going on 256 00:08:39,400 --> 00:08:42,080 to develop specialized hardware and software that's 257 00:08:42,080 --> 00:08:43,960 designed specifically for OI. 258 00:08:43,960 --> 00:08:44,560 OK. 259 00:08:44,560 --> 00:08:47,680 For example, new types of biocompatible electrodes 260 00:08:47,680 --> 00:08:50,720 and sensors that can interface with the organoids 261 00:08:50,720 --> 00:08:51,560 more effectively. 262 00:08:51,560 --> 00:08:53,200 So it's about building an environment 263 00:08:53,200 --> 00:08:55,520 where these organoids can thrive and connect 264 00:08:55,520 --> 00:08:56,680 with our technology. 265 00:08:56,680 --> 00:08:57,200 Exactly. 266 00:08:57,200 --> 00:08:59,960 Bridging the gap between the biological and the digital. 267 00:08:59,960 --> 00:09:02,120 And that requires some really innovative engineering 268 00:09:02,120 --> 00:09:04,240 and a deep understanding of both biology and computer 269 00:09:04,240 --> 00:09:04,720 science. 270 00:09:04,720 --> 00:09:06,600 It sounds like there's so much exciting research 271 00:09:06,600 --> 00:09:08,320 happening in the field of OI. 272 00:09:08,320 --> 00:09:09,080 There is. 273 00:09:09,080 --> 00:09:11,360 And while there are definitely challenges, 274 00:09:11,360 --> 00:09:13,280 the potential is enormous. 275 00:09:13,280 --> 00:09:16,360 This technology could transform medicine, reshape computing, 276 00:09:16,360 --> 00:09:18,680 and even change how we understand ourselves. 277 00:09:18,680 --> 00:09:19,000 OK. 278 00:09:19,000 --> 00:09:22,040 So we're back for the final part of our deep dive 279 00:09:22,040 --> 00:09:23,800 into organoid intelligence. 280 00:09:23,800 --> 00:09:24,800 The home stretch. 281 00:09:24,800 --> 00:09:28,920 We've covered the basics, the potential applications, 282 00:09:28,920 --> 00:09:31,680 and now it's time to talk about something really important, 283 00:09:31,680 --> 00:09:33,640 the future implications of this technology. 284 00:09:33,640 --> 00:09:33,840 Yeah. 285 00:09:33,840 --> 00:09:35,640 Things get a little more philosophical here. 286 00:09:35,640 --> 00:09:36,040 It does. 287 00:09:36,040 --> 00:09:38,240 It's one thing to talk about brain cells playing pong. 288 00:09:38,240 --> 00:09:41,280 But when we start talking about creating systems 289 00:09:41,280 --> 00:09:43,760 with real biological intelligence, 290 00:09:43,760 --> 00:09:47,160 it brings up some big questions about the future 291 00:09:47,160 --> 00:09:48,760 for humanity and technology. 292 00:09:48,760 --> 00:09:49,320 Absolutely. 293 00:09:49,320 --> 00:09:51,400 I mean, we're essentially talking about creating 294 00:09:51,400 --> 00:09:53,160 a new form of intelligence. 295 00:09:53,160 --> 00:09:56,280 One that's based on biology, not just silicon and code. 296 00:09:56,280 --> 00:09:56,880 Right. 297 00:09:56,880 --> 00:09:58,160 And that changes everything. 298 00:09:58,160 --> 00:09:59,120 It really does. 299 00:09:59,120 --> 00:10:00,680 It changes how we design computers, 300 00:10:00,680 --> 00:10:04,440 how we understand intelligence, even consciousness itself. 301 00:10:04,440 --> 00:10:05,000 Exactly. 302 00:10:05,000 --> 00:10:06,520 It challenges our whole definition of what 303 00:10:06,520 --> 00:10:08,800 it means to be intelligent, to be sentient. 304 00:10:08,800 --> 00:10:09,040 Right. 305 00:10:09,040 --> 00:10:12,160 If we can create systems that think like humans, 306 00:10:12,160 --> 00:10:15,360 at least in some ways, how do we define their rights? 307 00:10:15,360 --> 00:10:18,800 Do they deserve the same moral consideration 308 00:10:18,800 --> 00:10:20,240 as any other living being? 309 00:10:20,240 --> 00:10:21,720 These are questions that philosophers 310 00:10:21,720 --> 00:10:23,200 have been debating forever. 311 00:10:23,200 --> 00:10:23,640 Yeah. 312 00:10:23,640 --> 00:10:25,960 But OI brings a whole new dimension to the debate, 313 00:10:25,960 --> 00:10:28,760 because we're not just theorizing about AI anymore. 314 00:10:28,760 --> 00:10:30,480 We're actually building it cell by cell. 315 00:10:30,480 --> 00:10:31,640 And it's happening so fast. 316 00:10:31,640 --> 00:10:34,160 The advancements in OI research are incredible. 317 00:10:34,160 --> 00:10:36,920 It feels like every few months there's a new breakthrough. 318 00:10:36,920 --> 00:10:39,680 Which is why it's so important to have these conversations. 319 00:10:39,680 --> 00:10:42,160 Now, while the technology is still young, 320 00:10:42,160 --> 00:10:44,960 we have a chance to shape how OI develops. 321 00:10:44,960 --> 00:10:46,600 Make sure it's used ethically. 322 00:10:46,600 --> 00:10:48,560 Kagan himself talked about that a lot. 323 00:10:48,560 --> 00:10:50,880 The need for responsible development 324 00:10:50,880 --> 00:10:54,440 and open discussion between scientists, ethicists, 325 00:10:54,440 --> 00:10:58,960 and the public, he seems very aware of the potential risks 326 00:10:58,960 --> 00:11:01,640 and is pushing for a cautious approach. 327 00:11:01,640 --> 00:11:02,680 I think that's crucial. 328 00:11:02,680 --> 00:11:05,880 We can't get so caught up in the excitement of new technology 329 00:11:05,880 --> 00:11:08,240 that we forget about the ethical implications. 330 00:11:08,240 --> 00:11:09,880 It's like a tightrope walk. 331 00:11:09,880 --> 00:11:10,240 It is. 332 00:11:10,240 --> 00:11:12,080 It's a balancing act, but an essential one. 333 00:11:12,080 --> 00:11:14,280 So what does responsible development actually 334 00:11:14,280 --> 00:11:15,400 look like in this case? 335 00:11:15,400 --> 00:11:17,320 What are the key things to consider? 336 00:11:17,320 --> 00:11:20,960 Well, for one, transparency being open about the research, 337 00:11:20,960 --> 00:11:23,520 the methods, and the potential risks and benefits. 338 00:11:23,520 --> 00:11:23,880 Yes. 339 00:11:23,880 --> 00:11:25,320 Everyone knows what's going on. 340 00:11:25,320 --> 00:11:25,960 Exactly. 341 00:11:25,960 --> 00:11:28,760 And ensuring that the research is done ethically. 342 00:11:28,760 --> 00:11:31,840 Prioritizing the well-being of both the organoids 343 00:11:31,840 --> 00:11:33,920 and the people who might use this technology. 344 00:11:33,920 --> 00:11:34,440 That makes sense. 345 00:11:34,440 --> 00:11:36,040 And having these discussions publicly, 346 00:11:36,040 --> 00:11:39,040 not just among scientists, but with policymakers, 347 00:11:39,040 --> 00:11:40,840 ethicists, and the general public. 348 00:11:40,840 --> 00:11:43,200 Everyone has a stake in this OI. 349 00:11:43,200 --> 00:11:46,880 Has the potential to affect all of us in profound ways. 350 00:11:46,880 --> 00:11:49,960 So we need to approach it with a sense of shared responsibility. 351 00:11:49,960 --> 00:11:52,600 It's a societal issue, not just a scientific one. 352 00:11:52,600 --> 00:11:53,520 Right. 353 00:11:53,520 --> 00:11:56,120 And we need to be asking some tough questions. 354 00:11:56,120 --> 00:11:59,360 What are the potential unintended consequences 355 00:11:59,360 --> 00:12:02,840 of creating systems with biological intelligence? 356 00:12:02,840 --> 00:12:04,920 How do we make sure this technology doesn't make 357 00:12:04,920 --> 00:12:08,040 existing inequalities worse or end up in the wrong hands? 358 00:12:08,040 --> 00:12:09,880 There are no easy answers to these questions. 359 00:12:09,880 --> 00:12:10,200 No. 360 00:12:10,200 --> 00:12:11,480 But at least we're acknowledging them 361 00:12:11,480 --> 00:12:12,680 and starting the conversation. 362 00:12:12,680 --> 00:12:14,600 And it's not just about avoiding the risks. 363 00:12:14,600 --> 00:12:17,200 It's also about using OI for good. 364 00:12:17,200 --> 00:12:19,720 How can we use this technology to improve lives 365 00:12:19,720 --> 00:12:22,000 to solve some of the world's biggest problems? 366 00:12:22,000 --> 00:12:23,800 That's where things get really exciting. 367 00:12:23,800 --> 00:12:24,960 Oh. 368 00:12:24,960 --> 00:12:26,280 I mean, think about it. 369 00:12:26,280 --> 00:12:29,720 OI could be used to develop new clean energy sources 370 00:12:29,720 --> 00:12:33,720 to create sustainable materials to enhance our cognitive abilities. 371 00:12:33,720 --> 00:12:35,080 The possibilities are endless. 372 00:12:35,080 --> 00:12:37,920 It's about creating a better future, not just with technology, 373 00:12:37,920 --> 00:12:42,560 but also in terms of what it means to be human in a world 374 00:12:42,560 --> 00:12:45,880 where biological and artificial intelligence coexist. 375 00:12:45,880 --> 00:12:47,520 That's a future I'm really looking forward to. 376 00:12:47,520 --> 00:12:51,320 It'll have challenges, of course, but also incredible possibilities. 377 00:12:51,320 --> 00:12:53,400 And it's a future that we get to shape together. 378 00:12:53,400 --> 00:12:57,040 So as we wrap up this deep dive into organoid intelligence, 379 00:12:57,040 --> 00:13:01,400 I'm left with a feeling of awe and a sense of cautious optimism. 380 00:13:01,400 --> 00:13:04,200 This technology has the power to change everything. 381 00:13:04,200 --> 00:13:05,000 It really does. 382 00:13:05,000 --> 00:13:08,080 It's up to all of us to make sure it changes things for the better 383 00:13:08,080 --> 00:13:11,160 by asking the hard questions, having open conversations, 384 00:13:11,160 --> 00:13:14,040 and approaching this new frontier with a sense of responsibility 385 00:13:14,040 --> 00:13:14,760 and wonder. 386 00:13:14,760 --> 00:13:16,240 I couldn't have said it better myself. 387 00:13:16,240 --> 00:13:19,400 Thanks for joining us on this deep dive into organoid intelligence. 388 00:13:19,400 --> 00:13:21,280 It's a topic that's sure to keep evolving, 389 00:13:21,280 --> 00:13:22,960 so keep those questions coming. 390 00:13:22,960 --> 00:13:25,920 And let's continue exploring this incredible new frontier together.