All language subtitles for 20260620 ChatGPT + mRNA疫苗幫助治療狗狗癌症|澳洲鏟屎官真實案例 [Yolo 街]

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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:02,800 The well-behaved dog in the frame is named Rosie 2 00:00:03,079 --> 00:00:04,559 An eight-year-old female mud 3 00:00:04,559 --> 00:00:08,039 A few years ago Paul rescued her from an animal shelter in Australia 4 00:00:08,119 --> 00:00:08,800 Since then 5 00:00:08,800 --> 00:00:11,119 Rosie is Paul's best partner 6 00:00:11,119 --> 00:00:12,159 Best Mate 7 00:00:12,280 --> 00:00:12,960 A year ago 8 00:00:14,920 --> 00:00:17,079 Rosie was given a death sentence by the vet 9 00:00:17,079 --> 00:00:18,119 Diagnosed with cancer 10 00:00:18,119 --> 00:00:18,960 Having surgery 11 00:00:18,960 --> 00:00:19,800 Undergoing chemotherapy 12 00:00:19,800 --> 00:00:21,079 Also undergoing immunotherapy 13 00:00:21,320 --> 00:00:23,599 All efforts proved futile 14 00:00:23,639 --> 00:00:24,280 The vet said 15 00:00:24,280 --> 00:00:25,840 Rosie has only a few months left 16 00:00:25,840 --> 00:00:28,840 This Australian dog owner, determined to save Rosie 17 00:00:29,039 --> 00:00:30,920 He came up with a crazy idea 18 00:00:31,079 --> 00:00:32,920 Open ChatGPT 19 00:00:32,920 --> 00:00:34,400 Ask what options there are 20 00:00:35,320 --> 00:00:37,960 This is Rosie after treatment 21 00:00:38,280 --> 00:00:40,840 An Australian dog owner with no medical background 22 00:00:40,840 --> 00:00:42,880 What makes it possible in just a few months 23 00:00:42,880 --> 00:00:46,400 to complete what would normally take ten years of medical research 24 00:00:46,400 --> 00:00:49,400 to design an mRNA cancer vaccine for dogs 25 00:00:50,039 --> 00:00:52,960 What kind of god-tier interaction did he have with AI behind the scenes 26 00:00:53,599 --> 00:00:55,880 this crazy lab-rat plan 27 00:00:55,880 --> 00:00:58,599 Could it unlock another option for humans 28 00:00:58,599 --> 00:01:00,760 a new heavyweight in defeating cancer 29 00:01:02,599 --> 00:01:03,800 Please sit back, everyone 30 00:01:03,800 --> 00:01:06,159 This episode we go straight to real people and true stories 31 00:01:06,719 --> 00:01:08,599 Australian pet owner AI dog-rescue story 32 00:01:09,079 --> 00:01:12,559 A real case that breaks medical norms 33 00:01:12,639 --> 00:01:14,159 While we are at it 34 00:01:14,159 --> 00:01:16,079 When AI becomes a research assistant 35 00:01:16,320 --> 00:01:17,480 Future humans 36 00:01:17,679 --> 00:01:20,480 And is there really a chance to avoid the term terminal illness 37 00:01:20,480 --> 00:01:21,480 Say goodbye 38 00:01:26,199 --> 00:01:27,239 The story's starting point 39 00:01:27,239 --> 00:01:29,679 Starting from a few years ago in Sydney, Australia 40 00:01:29,679 --> 00:01:30,639 About four years ago 41 00:01:30,639 --> 00:01:31,880 Rosie was four years old then 42 00:01:32,000 --> 00:01:34,599 He noticed lumps on both of her hind legs 43 00:01:34,960 --> 00:01:37,159 For a full year 44 00:01:37,159 --> 00:01:39,199 The vets assured him 45 00:01:39,639 --> 00:01:41,400 it is just a common rash 46 00:01:41,400 --> 00:01:42,119 Do not worry 47 00:01:42,599 --> 00:01:44,599 But those tumors kept growing bigger 48 00:01:44,639 --> 00:01:45,800 By the time Rosie was five 49 00:01:46,400 --> 00:01:48,599 A thorough checkup yielded a confirmed diagnosis 50 00:01:49,119 --> 00:01:50,360 Mast Cell Tumor 51 00:01:50,760 --> 00:01:51,599 Mast Cell Tumor 52 00:01:52,039 --> 00:01:53,519 Common in dogs 53 00:01:53,519 --> 00:01:56,119 But also one of the hardest malignant skin cancers to treat 54 00:01:56,599 --> 00:01:57,960 Pet owners watching 55 00:01:58,159 --> 00:01:59,079 You will understand 56 00:02:00,360 --> 00:02:02,639 Pets are family to us 57 00:02:03,119 --> 00:02:07,679 And Rosie is Paul's constant best mate 58 00:02:07,920 --> 00:02:08,440 Best Mate 59 00:02:08,840 --> 00:02:10,639 Paul wouldn't give up 60 00:02:10,679 --> 00:02:14,280 So he set off on a long cancer-fighting journey with Rosie 61 00:02:14,840 --> 00:02:16,519 Conventional cancer treatments 62 00:02:16,679 --> 00:02:18,480 There are only three options 63 00:02:19,119 --> 00:02:20,920 Surgery, chemotherapy, immunotherapy 64 00:02:21,239 --> 00:02:23,519 Paul spent money like water 65 00:02:23,519 --> 00:02:24,280 Tried everything 66 00:02:24,280 --> 00:02:25,360 Countless surgeries 67 00:02:25,360 --> 00:02:27,719 Chemotherapy wore Rosie down 68 00:02:27,880 --> 00:02:29,800 Even immunotherapy 69 00:02:29,800 --> 00:02:30,320 But it all failed 70 00:02:30,880 --> 00:02:33,719 The vet told Paul something no owner wants to hear 71 00:02:33,800 --> 00:02:35,679 Also the hardest thing to hear 72 00:02:36,000 --> 00:02:36,760 Sorry 73 00:02:36,760 --> 00:02:38,440 Its cancer has already spread 74 00:02:38,719 --> 00:02:40,519 Currently in an incurable stage 75 00:02:40,760 --> 00:02:43,000 We can at most give it a few more months of life 76 00:02:43,880 --> 00:02:46,159 Rosie was officially abandoned by conventional medicine 77 00:02:46,719 --> 00:02:48,719 If an ordinary person reached this point 78 00:02:48,960 --> 00:02:50,719 They may have to accept 79 00:02:50,719 --> 00:02:53,960 But in his despair, Paul suddenly hit upon an idea 80 00:02:53,960 --> 00:02:56,280 Since conventional medicine isn\\ 81 00:02:56,280 --> 00:02:57,719 Why not try it 82 00:02:58,400 --> 00:02:59,880 It was 2025 83 00:02:59,880 --> 00:03:01,880 The whole city was talking about how AI could do anything 84 00:03:02,559 --> 00:03:03,880 Paul stared at the computer 85 00:03:03,960 --> 00:03:04,840 He thought If that is the case 86 00:03:04,960 --> 00:03:07,400 Could the AI guru save Rosie\\ 87 00:03:08,039 --> 00:03:09,880 Then he opened ChatGPT 88 00:03:10,199 --> 00:03:12,199 At first he was just like us 89 00:03:12,280 --> 00:03:14,119 to ChatGPT 90 00:03:14,119 --> 00:03:15,800 to understand the complex veterinary information 91 00:03:15,800 --> 00:03:18,039 and explore what other treatment options exist 92 00:03:18,440 --> 00:03:18,880 But 93 00:03:18,880 --> 00:03:19,920 Nobody expected 94 00:03:19,920 --> 00:03:23,079 As Paul dug deeper into the leads ChatGPT gave him 95 00:03:23,679 --> 00:03:26,920 Even started contacting Australia\\ 96 00:03:27,320 --> 00:03:28,400 In his mind 97 00:03:28,400 --> 00:03:33,079 he began to believe he could personally develop a new antidote for Rosie 98 00:03:33,800 --> 00:03:34,639 This move 99 00:03:34,639 --> 00:03:36,639 In the eyes of many doctors at the time 100 00:03:36,639 --> 00:03:38,000 Unthinkable 101 00:03:38,639 --> 00:03:39,679 An amateur 102 00:03:39,679 --> 00:03:45,039 A layperson trying to rely on an online chatbot to save a terminal cancer dog that even top vets say is incurable 103 00:03:45,039 --> 00:03:46,079 In doctors\\ 104 00:03:46,079 --> 00:03:49,360 Isn\\ 105 00:03:50,639 --> 00:03:51,840 Many would even think 106 00:03:51,840 --> 00:03:55,079 Is this owner so desperate they\\ 107 00:03:55,320 --> 00:03:55,820 Crazy, right 108 00:03:56,559 --> 00:03:57,679 But in Paul\\ 109 00:03:57,679 --> 00:03:59,440 He completely ignored what others thought 110 00:03:59,480 --> 00:04:01,000 In his mind at the time 111 00:04:01,000 --> 00:04:03,800 Only one simplest, most direct idea 112 00:04:03,880 --> 00:04:06,159 I don\\ 113 00:04:06,800 --> 00:04:09,360 With this stubborn determination to see it through 114 00:04:09,920 --> 00:04:13,360 The whole thing suddenly took an unbelievable turn 115 00:04:13,760 --> 00:04:16,719 A medical miracle that even OpenAI CEO Sam Altman would post praising 116 00:04:16,719 --> 00:04:20,239 has officially begun 117 00:04:20,639 --> 00:04:22,960 Someone who has never even looked at a DNA sequence 118 00:04:23,559 --> 00:04:26,000 a regular pet owner with no bioinformatics training 119 00:04:26,400 --> 00:04:27,679 Where did the courage come from 120 00:04:27,679 --> 00:04:30,199 That he could help Rosie 121 00:04:30,199 --> 00:04:32,400 to develop a new cancer drug 122 00:04:37,159 --> 00:04:39,199 In fact, the moment Paul opened ChatGPT 123 00:04:39,559 --> 00:04:42,039 He had unknowingly stepped out of 124 00:04:42,039 --> 00:04:42,880 the bounds of traditional medicine 125 00:04:43,360 --> 00:04:46,639 Initially, he just wanted to use AI as a medical dictionary 126 00:04:46,800 --> 00:04:48,079 to help translate terms 127 00:04:49,800 --> 00:04:52,559 Paul at that moment on DNA and RNA 128 00:04:52,800 --> 00:04:55,039 I have no idea what cancer vaccine this is 129 00:04:55,719 --> 00:04:58,119 Who knows ChatGPT in conversation 130 00:04:58,199 --> 00:04:59,920 Paved a way out for Paul 131 00:05:00,280 --> 00:05:03,000 He tells Paul about modern technology 132 00:05:03,159 --> 00:05:05,760 It can truly be tailored for Rosie 133 00:05:05,760 --> 00:05:08,360 Her personalized mRNA cancer vaccine 134 00:05:08,840 --> 00:05:10,280 The premise is actually simple 135 00:05:10,400 --> 00:05:13,920 Paul only needs to fetch Rosie's tumor gene data 136 00:05:13,920 --> 00:05:17,400 ChatGPT as an AI can help decode the vaccine formula 137 00:05:17,960 --> 00:05:20,960 This sounds like a science fiction suggestion 138 00:05:20,960 --> 00:05:23,599 It even woke a father who had hit a dead end 139 00:05:24,039 --> 00:05:26,760 Traditional medical logic is like dining at a tea restaurant 140 00:05:26,960 --> 00:05:28,280 All Meal A, Meal B, and Meal C 141 00:05:28,719 --> 00:05:30,719 Big pharma develops a chemotherapy drug 142 00:05:30,719 --> 00:05:33,000 Used by tens of thousands of cancer patients at once 143 00:05:33,440 --> 00:05:37,079 But cancer cells are the universe's most cunning chameleons 144 00:05:37,559 --> 00:05:40,360 Every tumor mutation in every dog and person 145 00:05:40,360 --> 00:05:42,639 Each one is actually unique 146 00:05:43,320 --> 00:05:44,760 Conventional drugs can't treat Rosie 147 00:05:44,800 --> 00:05:47,159 Because all of Meal A, Meal B, and Meal C 148 00:05:47,239 --> 00:05:48,119 None of them suit it 149 00:05:48,639 --> 00:05:50,519 If that is the case the only way out is 150 00:05:50,519 --> 00:05:52,559 To make Rosie a globally unique one 151 00:05:52,559 --> 00:05:54,639 The one of a kind that belongs to her 152 00:05:54,639 --> 00:05:57,000 a dog's personalized mRNA 153 00:05:57,079 --> 00:05:57,579 cancer vaccine 154 00:05:57,920 --> 00:06:00,280 Neighbors, we've endured COVID-19 155 00:06:00,360 --> 00:06:02,400 Believe in the term mRNA vaccine 156 00:06:02,400 --> 00:06:03,400 won't be unfamiliar anymore 157 00:06:03,400 --> 00:06:04,519 But we are here 158 00:06:04,559 --> 00:06:06,760 Quick recap of what it actually is 159 00:06:07,119 --> 00:06:08,960 How it differs from traditional vaccines 160 00:06:08,960 --> 00:06:11,239 It is not a live attenuated virus 161 00:06:11,239 --> 00:06:11,739 Injected into the body 162 00:06:11,960 --> 00:06:12,840 In essence 163 00:06:12,840 --> 00:06:15,280 It is the feature data of the top fugitive 164 00:06:15,280 --> 00:06:16,800 Sent into your body 165 00:06:16,800 --> 00:06:18,320 Once the vaccine enters the body 166 00:06:18,320 --> 00:06:20,760 Your immune forces will act with precision 167 00:06:20,760 --> 00:06:21,920 Like a wanted notice 168 00:06:21,920 --> 00:06:22,719 Immediately follow 169 00:06:22,719 --> 00:06:24,119 The features on the list 170 00:06:24,280 --> 00:06:25,440 All forces mobilized 171 00:06:25,440 --> 00:06:26,599 Closing in on you completely 172 00:06:26,599 --> 00:06:28,760 The enemy you want to wipe out: COVID-19 173 00:06:28,760 --> 00:06:29,400 Either way 174 00:06:29,400 --> 00:06:30,519 Cancer cells as well 175 00:06:30,519 --> 00:06:32,519 But for this warrant to exist 176 00:06:32,760 --> 00:06:34,400 Clever you should have thought of 177 00:06:35,119 --> 00:06:36,360 Before the warrant is issued 178 00:06:36,360 --> 00:06:38,599 First you need to know what the top fugitive looks like 179 00:06:38,599 --> 00:06:39,559 What it actually looks like 180 00:06:40,199 --> 00:06:40,559 So 181 00:06:40,559 --> 00:06:41,679 Paul without a second thought 182 00:06:41,679 --> 00:06:43,679 follows ChatGPT's instructions 183 00:06:43,920 --> 00:06:46,679 Immediately contact Australia's top research institutions 184 00:06:46,679 --> 00:06:49,079 Genomics Institute at the University of New South Wales 185 00:06:49,719 --> 00:06:51,199 Spending a few thousand AUD 186 00:06:51,559 --> 00:06:52,920 The request is simple 187 00:06:53,440 --> 00:06:55,320 Rose's tumor tissue 188 00:06:55,599 --> 00:06:57,760 Then perform whole genome sequencing 189 00:06:57,920 --> 00:06:58,920 Genome Sequencing 190 00:06:59,159 --> 00:07:02,239 Read every DNA code inside 191 00:07:02,559 --> 00:07:05,199 The associate professor Martin Smith who led the center at that time 192 00:07:05,199 --> 00:07:06,639 When I received Paul's email 193 00:07:06,639 --> 00:07:08,519 At first, my mind was full of questions 194 00:07:08,920 --> 00:07:09,639 The professor wants 195 00:07:09,800 --> 00:07:10,239 Hey 196 00:07:10,239 --> 00:07:11,480 You are a layperson 197 00:07:11,559 --> 00:07:14,400 Do you have any idea how huge the genome data is 198 00:07:14,920 --> 00:07:16,119 Once you have it 199 00:07:16,119 --> 00:07:16,679 how to deal with it 200 00:07:17,440 --> 00:07:19,960 But Paul was sure then and told the professor 201 00:07:20,119 --> 00:07:20,800 Don't worry 202 00:07:20,800 --> 00:07:22,599 data analysis work 203 00:07:22,599 --> 00:07:23,099 I can handle it 204 00:07:23,280 --> 00:07:25,199 The data the research center handed to Paul 205 00:07:25,280 --> 00:07:26,440 Not a miracle drug 206 00:07:26,480 --> 00:07:28,960 But instead several huge digital files 207 00:07:29,360 --> 00:07:31,480 When Paul opened these files 208 00:07:32,639 --> 00:07:34,960 They are strings springing out of ATCG 209 00:07:36,760 --> 00:07:38,320 An endless sea of characters 210 00:07:38,840 --> 00:07:40,599 How many letters are here in total 211 00:07:41,199 --> 00:07:43,920 The answer is about 150 billion 212 00:07:44,559 --> 00:07:45,960 Just how big is 150 billion 213 00:07:46,639 --> 00:07:47,880 If we print it as a book 214 00:07:48,039 --> 00:07:50,039 It could fill the whole university library 215 00:07:50,440 --> 00:07:51,679 Paul faces 216 00:07:51,679 --> 00:07:53,280 these completely irregular ones 217 00:07:53,320 --> 00:07:54,840 a scrambled alphabet salad 218 00:07:55,159 --> 00:07:59,039 to find the one letter copied wrong 219 00:07:59,039 --> 00:08:00,119 causing Rosie to form a tumor 220 00:08:00,519 --> 00:08:02,039 People like us reach this point 221 00:08:02,039 --> 00:08:04,000 Facing this mountain of data 222 00:08:04,039 --> 00:08:06,159 Willpower may be almost gone 223 00:08:06,559 --> 00:08:08,719 But the turning point is 224 00:08:08,719 --> 00:08:10,920 Paul is not just an ordinary IT guy 225 00:08:11,360 --> 00:08:12,480 His real identity 226 00:08:12,480 --> 00:08:15,599 is actually an IT guy who specializes in machine learning 227 00:08:15,719 --> 00:08:17,560 What he is best at 228 00:08:17,560 --> 00:08:19,039 Of course not a surgeon 229 00:08:19,439 --> 00:08:21,920 He deals with data every day 230 00:08:22,399 --> 00:08:23,640 So in his eyes 231 00:08:23,640 --> 00:08:25,760 Big data problems are well within his reach 232 00:08:25,960 --> 00:08:29,119 Since the human eye can't read all 150 billion letters 233 00:08:29,800 --> 00:08:31,960 Then hand it to the fastest AI 234 00:08:32,720 --> 00:08:34,439 Paul enters round-the-clock seclusion 235 00:08:34,640 --> 00:08:36,239 Every day he faces a glowing screen 236 00:08:36,239 --> 00:08:38,439 Treating ChatGPT as his superbrain 237 00:08:38,760 --> 00:08:43,079 Give this data, like a stack of scriptures, to AI for sorting and analysis 238 00:08:43,359 --> 00:08:46,720 AI suddenly becomes Paul's best medical assistant 239 00:08:46,760 --> 00:08:49,720 Help him precisely search through the massive data 240 00:08:50,199 --> 00:08:52,359 Rosy cancer cell neoantigens 241 00:08:52,720 --> 00:08:53,479 Neoantigens 242 00:08:54,079 --> 00:08:55,039 What are neoantigens 243 00:08:55,680 --> 00:08:58,760 Normal cells are ordinary, law-abiding citizens 244 00:08:59,159 --> 00:09:02,960 And cancer cells are fugitives hidden among ordinary citizens 245 00:09:03,479 --> 00:09:05,000 This so-called neoantigen 246 00:09:05,279 --> 00:09:08,399 is actually the fugitive's unique feature 247 00:09:08,760 --> 00:09:12,520 If AI can pinpoint it precisely within 150 billion letters 248 00:09:12,920 --> 00:09:14,920 Find the fugitive features 249 00:09:15,159 --> 00:09:17,800 The vaccine can become a precise arrest warrant 250 00:09:18,000 --> 00:09:21,119 Teach your immune system to use these features to catch them 251 00:09:21,520 --> 00:09:22,279 That is how it works 252 00:09:22,279 --> 00:09:24,199 It would normally take a long time to organize 253 00:09:25,760 --> 00:09:29,359 Through day and night interactions between Paul and ChatGPT 254 00:09:29,359 --> 00:09:31,760 The data mountain starts to be dismantled layer by layer 255 00:09:32,079 --> 00:09:36,239 That 150-billion-letter celestial manuscript begins filtering, slimming down 256 00:09:36,479 --> 00:09:39,880 Finally zeroes in on a specific gene mutation 257 00:09:40,079 --> 00:09:42,199 This gene is called the CKIT gene 258 00:09:42,640 --> 00:09:43,640 That moment 259 00:09:43,640 --> 00:09:45,920 Paul knew the first battle had been won 260 00:09:46,359 --> 00:09:49,039 He finally, in the vast sea of data 261 00:09:49,039 --> 00:09:51,920 He precisely grabbed the tail of this formidable foe, the cancer cell 262 00:09:52,359 --> 00:09:54,720 But the letters of the gene mutation 263 00:09:55,000 --> 00:09:57,399 Only the fugitive's textual description 264 00:09:57,800 --> 00:10:01,039 This is like what is written on the wanted notice 265 00:10:01,039 --> 00:10:01,920 A mole on the suspect's face 266 00:10:02,279 --> 00:10:03,520 But the problem is 267 00:10:03,520 --> 00:10:05,000 Where is the mole located? 268 00:10:05,439 --> 00:10:06,399 Left side, right side 269 00:10:06,399 --> 00:10:07,319 Or is it on the nose? 270 00:10:07,920 --> 00:10:09,600 If there is no 3D location 271 00:10:09,760 --> 00:10:12,720 Rosie's immune system can't make sense of it 272 00:10:12,720 --> 00:10:13,319 nor can they act on it 273 00:10:13,880 --> 00:10:14,359 So 274 00:10:14,359 --> 00:10:16,640 The tricky problem Paul must solve next 275 00:10:16,640 --> 00:10:18,319 is how to turn this string of text into a concise form 276 00:10:18,680 --> 00:10:21,720 a string of text becomes a precise 3D location-based wanted notice 277 00:10:22,199 --> 00:10:24,800 At this point, Google's turn 278 00:10:24,800 --> 00:10:28,880 another AI marvel that turns data into 3D structures 279 00:10:29,479 --> 00:10:31,439 AlphaFold takes the stage 280 00:10:36,279 --> 00:10:37,800 After locking onto the CKIT gene 281 00:10:37,840 --> 00:10:40,720 Paul, though, has the fugitive's flat data 282 00:10:40,840 --> 00:10:44,199 But he knows a string of flat gene letters alone 283 00:10:44,199 --> 00:10:46,840 cannot be directly turned into an injectable drug 284 00:10:46,840 --> 00:10:51,079 Because the next hurdle is predicting the 3D structure of proteins 285 00:10:51,399 --> 00:10:53,199 In the microscopic world 286 00:10:53,199 --> 00:10:54,560 Structure equals function 287 00:10:54,600 --> 00:10:56,359 DNA is only a flat blueprint 288 00:10:56,439 --> 00:10:59,119 The real culprit is the 3D protein 289 00:10:59,680 --> 00:11:01,760 You have to design a bespoke vaccine 290 00:11:01,800 --> 00:11:04,359 With the features of this top fugitive 291 00:11:04,680 --> 00:11:06,920 which is the cancer cell's new antigen 292 00:11:07,119 --> 00:11:09,159 which are a bunch of mutated proteins 293 00:11:09,159 --> 00:11:12,279 Then you must know in 3D space 294 00:11:12,359 --> 00:11:14,680 what these mutated proteins actually look like 295 00:11:14,760 --> 00:11:16,039 In other words 296 00:11:16,039 --> 00:11:19,359 you must precisely pinpoint the spot the cancer cell exposes 297 00:11:20,239 --> 00:11:20,920 where exactly it sits 298 00:11:21,760 --> 00:11:26,520 Pharma companies used to spend years and money researching a protein structure 299 00:11:26,680 --> 00:11:28,079 But Rosie could not wait 300 00:11:28,359 --> 00:11:31,479 So Paul deploys Google's AI marvel AlphaFold 301 00:11:32,880 --> 00:11:34,920 Many people may not have heard of AlphaFold 302 00:11:35,359 --> 00:11:36,239 To put it simply 303 00:11:36,239 --> 00:11:39,279 It is the world's most powerful 3D protein modeling tool 304 00:11:39,800 --> 00:11:41,319 Things that used to take years 305 00:11:41,319 --> 00:11:42,560 Why it can be so fast now 306 00:11:43,199 --> 00:11:44,760 Because Google made a decision 307 00:11:44,760 --> 00:11:48,760 They made AlphaFold freely available to the public 308 00:11:49,000 --> 00:11:52,600 Today, almost all top biology labs worldwide 309 00:11:52,760 --> 00:11:55,079 use this AI tool every day 310 00:11:55,479 --> 00:11:57,840 with this protein 3D modeling tool 311 00:11:57,840 --> 00:12:00,079 The whole process is divided into three parts 312 00:12:00,640 --> 00:12:01,399 Step one 313 00:12:01,399 --> 00:12:05,520 Paul must first navigate the 150-billion-letter data mountain 314 00:12:05,760 --> 00:12:10,840 Precisely filter the seven strongest, easiest-to-recognize new antigens 315 00:12:10,840 --> 00:12:12,760 In the wording of a wanted notice 316 00:12:12,760 --> 00:12:14,640 He successfully locked onto the suspect 317 00:12:15,680 --> 00:12:16,319 Step two 318 00:12:16,319 --> 00:12:20,000 He inputs the 2D data of these seven features into AlphaFold 319 00:12:20,279 --> 00:12:21,560 AI runs a computation 320 00:12:21,560 --> 00:12:25,680 and produced precise 3D models for all seven features 321 00:12:26,279 --> 00:12:26,960 Step three 322 00:12:26,960 --> 00:12:30,760 Paul then has ChatGPT perform cross checks 323 00:12:30,920 --> 00:12:33,720 Cross-check each of the seven 3D models individually 324 00:12:34,079 --> 00:12:35,880 Finally confirm these seven markers 325 00:12:35,880 --> 00:12:39,880 the seven core, inescapable features of this cancer cell 326 00:12:40,600 --> 00:12:42,840 But reality is not that glamorous 327 00:12:42,920 --> 00:12:45,920 Do not think Paul is hiding at home fighting alone 328 00:12:46,439 --> 00:12:49,399 In fact the whole process is a tight cross-disciplinary collaboration 329 00:12:49,760 --> 00:12:52,199 During the months designing the vaccine 330 00:12:52,199 --> 00:12:56,199 Paul has been working with Martin Smith, UNSW gene sequencing expert 331 00:12:56,199 --> 00:12:56,699 Paul has been working with Martin Smith, UNSW gene sequencing expert 332 00:12:56,840 --> 00:13:00,399 and Professor Paul Thorderson, director of the RNA Institute 333 00:13:00,399 --> 00:13:01,840 Maintaining close communication and collaboration 334 00:13:02,399 --> 00:13:06,159 Top scientists, an AI brain, and a father who will not give up 335 00:13:06,680 --> 00:13:10,039 This tailor-made cancer cell that outsiders once fantasized about 336 00:13:11,399 --> 00:13:13,439 Step by step, it becomes reality 337 00:13:13,960 --> 00:13:15,399 After months of effort 338 00:13:15,439 --> 00:13:17,119 Vaccine design finally complete 339 00:13:17,399 --> 00:13:18,640 As soon as the design is finished 340 00:13:18,640 --> 00:13:21,720 he immediately goes to the director of the RNA Institute 341 00:13:21,800 --> 00:13:22,479 Professor Thordarson 342 00:13:23,039 --> 00:13:25,359 Professor Thordarson was initially somewhat skeptical 343 00:13:25,720 --> 00:13:27,840 Because moving from development to production takes time 344 00:13:28,279 --> 00:13:30,239 He worries Rosie will not be able to hold out that long 345 00:13:30,640 --> 00:13:33,439 But after his team 346 00:13:33,439 --> 00:13:36,119 the professor felt this non-scientist-made design 347 00:13:36,279 --> 00:13:37,640 was quite stunning 348 00:13:38,000 --> 00:13:40,640 on top of that, his institute had never worked on a cancer vaccine 349 00:13:41,119 --> 00:13:42,319 so they all clicked right away 350 00:13:43,079 --> 00:13:46,279 but just as Paul thought he had beaten all defenses 351 00:13:46,319 --> 00:13:49,399 as he prepared a decisive shot to save the day 352 00:13:49,520 --> 00:13:51,479 the referee suddenly rushed out to blow the whistle 353 00:13:51,760 --> 00:13:53,479 and intercepted him forcefully 354 00:13:54,039 --> 00:13:55,479 This referee is not from science 355 00:13:55,880 --> 00:13:56,920 nor from AI 356 00:13:57,239 --> 00:13:59,640 but from the oldest invention of our human society 357 00:13:59,640 --> 00:14:01,479 the trickiest invention 358 00:14:01,600 --> 00:14:02,800 bureaucratic admin hell 359 00:14:03,279 --> 00:14:03,960 in Australia 360 00:14:04,039 --> 00:14:06,399 you write a software patch to upgrade the phone 361 00:14:06,399 --> 00:14:07,159 nothing at all 362 00:14:07,359 --> 00:14:12,640 but if you want to inject a string of newly designed chemical molecules into a living dog 363 00:14:13,479 --> 00:14:15,319 the laws and paperwork involved 364 00:14:15,399 --> 00:14:16,319 thicker than a dictionary 365 00:14:16,680 --> 00:14:21,560 Paul must apply to the university and government ethics boards for animal ethics approval 366 00:14:22,000 --> 00:14:26,520 the whole plan becomes a two-front battle against time 367 00:14:26,560 --> 00:14:29,319 on one side, top labs are fully ramped up 368 00:14:29,319 --> 00:14:33,439 This is the precise manufacturing process that turns digital formulas into real weapons 369 00:14:33,479 --> 00:14:34,640 The scientists spent two months 370 00:14:35,119 --> 00:14:38,119 On the other hand, Paul bears the bureaucratic paperwork alone 371 00:14:38,600 --> 00:14:42,239 During these months, this IT guy would come home after work every day 372 00:14:42,239 --> 00:14:43,920 just sitting in front of the computer 373 00:14:43,920 --> 00:14:46,399 filling those endless government filings 374 00:14:46,680 --> 00:14:47,800 He even laughs at himself 375 00:14:47,920 --> 00:14:49,800 to deal with this stack of ethics approvals 376 00:14:49,800 --> 00:14:51,319 He spends several hours a day filling them out 377 00:14:51,359 --> 00:14:53,159 It dragged on for a full three months 378 00:14:53,560 --> 00:14:55,920 The workload was more than the vaccine design itself 379 00:14:56,319 --> 00:14:56,920 In the end 380 00:14:56,920 --> 00:14:58,159 the approvals and the vaccine 381 00:14:59,279 --> 00:15:01,720 But fate played a joke on him again 382 00:15:02,000 --> 00:15:04,079 as Paul held the syringe and medicine 383 00:15:04,079 --> 00:15:06,279 as he was in high spirits preparing to save Rosie 384 00:15:07,000 --> 00:15:10,560 The research center told him, Sorry Sir 385 00:15:10,560 --> 00:15:12,039 We are the research center 386 00:15:12,039 --> 00:15:13,720 Only responsible for R&D and manufacturing 387 00:15:13,720 --> 00:15:15,239 Not authorized to vaccinate your dog 388 00:15:16,079 --> 00:15:16,439 Next 389 00:15:16,439 --> 00:15:19,439 Paul rushed to the regular vet Rosie usually goes to 390 00:15:19,720 --> 00:15:20,640 The vet took one look 391 00:15:20,640 --> 00:15:22,159 and immediately shook his head in alarm 392 00:15:22,159 --> 00:15:25,479 saying this is an untested experimental drug 393 00:15:25,479 --> 00:15:27,159 Who would take responsibility 394 00:15:28,159 --> 00:15:29,880 Months of hard work 395 00:15:29,880 --> 00:15:31,359 The high-tech solution worked 396 00:15:31,359 --> 00:15:32,880 Survived the bureaucratic paperwork 397 00:15:32,920 --> 00:15:33,600 Finally 398 00:15:33,600 --> 00:15:37,159 it was stuck at this spot where no one dares to inject 399 00:15:37,159 --> 00:15:38,039 No way 400 00:15:38,840 --> 00:15:39,399 At this point 401 00:15:39,399 --> 00:15:42,600 Rosie's leg tumor had started to worsen 402 00:15:42,600 --> 00:15:43,720 and it even bleeds 403 00:15:43,720 --> 00:15:45,600 life was clearly counting down to the end 404 00:15:46,039 --> 00:15:52,319 these breakthroughs created by IT guys, AI tools, and a top-tier science team across disciplines 405 00:15:52,920 --> 00:15:56,479 Finally, can they be injected into Rosie's body 406 00:16:01,279 --> 00:16:03,000 Watching anxiously as the vaccine is prepared 407 00:16:03,000 --> 00:16:04,399 But Rosie can't get the shot 408 00:16:04,720 --> 00:16:05,239 Fortunately 409 00:16:05,239 --> 00:16:08,319 Paul via his contact in the U.S. 410 00:16:08,319 --> 00:16:09,760 found The University of Queensland 411 00:16:09,760 --> 00:16:13,479 Professor Rachel Alvina, Vice Dean of the Veterinary Science Institute 412 00:16:13,960 --> 00:16:16,680 Professor Rachel is an expert in animal immunotherapy 413 00:16:16,720 --> 00:16:19,680 She said if Paul can bring Rosie to Brisbane 414 00:16:19,680 --> 00:16:20,800 she can give Rosie the shot 415 00:16:21,159 --> 00:16:21,640 That moment 416 00:16:21,640 --> 00:16:23,720 Rosie's leg tumor had grown very large 417 00:16:23,720 --> 00:16:25,319 Bleeding 418 00:16:25,319 --> 00:16:26,880 The situation was dire 419 00:16:27,159 --> 00:16:28,760 So Paul didn't hesitate 420 00:16:28,760 --> 00:16:32,039 and drove with Rosie all the way from Sydney to Brisbane 421 00:16:32,359 --> 00:16:33,840 And at this moment 422 00:16:33,840 --> 00:16:37,840 Paul also pulled off a bold two-pronged strategy 423 00:16:38,119 --> 00:16:41,000 Apart from his homemade mRNA vaccine 424 00:16:41,159 --> 00:16:43,520 He, through Professor Rachel, 425 00:16:43,520 --> 00:16:48,239 another Nobel Prize–winning immunotherapy drug 426 00:16:48,239 --> 00:16:49,279 immune checkpoint inhibitor 427 00:16:49,279 --> 00:16:51,760 immune checkpoint inhibitor 428 00:16:52,079 --> 00:16:52,800 Ladies and gentlemen 429 00:16:53,319 --> 00:16:55,720 This tactical logic is actually very clever 430 00:16:56,079 --> 00:16:56,920 To understand 431 00:16:56,920 --> 00:16:59,439 cancer cells can run rampant inside our bodies 432 00:16:59,640 --> 00:17:01,880 There are actually two major rogue defenses behind it 433 00:17:02,359 --> 00:17:04,279 The first line of defense is invisibility 434 00:17:04,840 --> 00:17:08,199 Because cancer cells are also our own cells 435 00:17:08,359 --> 00:17:10,880 it can often fool our own immune army 436 00:17:10,880 --> 00:17:12,239 when it is one of us 437 00:17:12,239 --> 00:17:13,039 go straight through 438 00:17:13,520 --> 00:17:15,199 The second line of defense is hypnosis 439 00:17:15,359 --> 00:17:18,119 Even if immune cells approach it they plan to destroy it 440 00:17:18,119 --> 00:17:19,359 they plan to destroy it 441 00:17:20,079 --> 00:17:22,359 cancer cells release hypnotic codes 442 00:17:22,479 --> 00:17:25,399 making cancer cells suddenly unable to see it 443 00:17:25,479 --> 00:17:28,399 That is why conventional treatments often fail 444 00:17:28,800 --> 00:17:30,640 But this time Paul combination therapy 445 00:17:30,640 --> 00:17:34,039 to wipe out both lines of defense in one go 446 00:17:34,199 --> 00:17:36,439 they use immune checkpoint inhibitors 447 00:17:36,680 --> 00:17:38,560 to disrupt the second line of defense 448 00:17:38,560 --> 00:17:39,359 breaks the hypnosis 449 00:17:39,800 --> 00:17:42,359 then follows up with his own AI vaccine 450 00:17:42,479 --> 00:17:44,399 break through the first line of defense 451 00:17:44,640 --> 00:17:48,279 directly insert a warrant listing the 3D features to identify it 452 00:17:50,640 --> 00:17:52,399 one to awaken the army 453 00:17:52,399 --> 00:17:54,520 one to lead the army to find targets 454 00:17:54,960 --> 00:17:56,960 at the University of Queensland Hospital 455 00:17:56,960 --> 00:17:59,960 Professor Rachel Alvina will deploy this perfect combination 456 00:17:59,960 --> 00:18:03,479 injected at multiple sites around Rosie tumor tissue 457 00:18:04,079 --> 00:18:04,880 At this point 458 00:18:04,880 --> 00:18:06,279 Some viewers may recall 459 00:18:06,600 --> 00:18:07,720 Hey Bonnie 460 00:18:07,720 --> 00:18:10,520 In Chapter 1 you said Paul was already with Rosie 461 00:18:10,520 --> 00:18:12,000 Had immunotherapy already? 462 00:18:12,319 --> 00:18:14,000 but there was no result 463 00:18:14,000 --> 00:18:14,479 That is right 464 00:18:14,479 --> 00:18:17,000 The literature does not detail the failure specifics 465 00:18:17,279 --> 00:18:19,439 But based on current medical logic 466 00:18:19,520 --> 00:18:22,159 We can reasonably infer its cause 467 00:18:22,159 --> 00:18:25,039 The standard immunotherapy Paul gave Rosie at the time 468 00:18:25,159 --> 00:18:28,960 likely it was simply using this checkpoint inhibitor 469 00:18:29,279 --> 00:18:32,720 These inhibitors did wake up the immune army 470 00:18:32,880 --> 00:18:35,359 But the problem is there was no warrant on hand 471 00:18:35,520 --> 00:18:37,119 Not knowing what the enemy looks like 472 00:18:37,119 --> 00:18:38,119 rush out 473 00:18:38,119 --> 00:18:38,880 a sea of people 474 00:18:38,880 --> 00:18:42,680 the immune army still cannot tell which cancer cells to target 475 00:18:42,680 --> 00:18:44,720 ultimately they returned empty handed 476 00:18:45,239 --> 00:18:45,600 Okay 477 00:18:45,600 --> 00:18:46,840 Back to Rosie 478 00:18:47,199 --> 00:18:48,239 The first few days after the shot 479 00:18:48,800 --> 00:18:50,359 Rosie more tired than before 480 00:18:50,920 --> 00:18:52,479 One day after returning to Sydney 481 00:18:52,479 --> 00:18:54,560 Paul suddenly finds a lump on Rosie leg 482 00:18:54,560 --> 00:18:56,479 those large tumors suddenly began 483 00:18:56,479 --> 00:18:57,039 to swell violently 484 00:18:57,439 --> 00:18:58,319 This situation 485 00:18:58,319 --> 00:19:00,279 for an ordinary person it might make the legs go weak 486 00:19:00,600 --> 00:19:02,359 But his rational thinking 487 00:19:02,399 --> 00:19:03,840 he feels hopeful 488 00:19:03,880 --> 00:19:06,000 He calmly analyzes that this swelling 489 00:19:06,000 --> 00:19:08,279 may be the immune system got the wake up call 490 00:19:08,640 --> 00:19:10,600 begins a frantic siege on cancer cells 491 00:19:10,600 --> 00:19:12,079 causing local inflammation 492 00:19:12,239 --> 00:19:14,359 This is actually a very good signal 493 00:19:14,359 --> 00:19:14,680 This is actually a very good signal 494 00:19:14,680 --> 00:19:15,319 Sure enough 495 00:19:15,319 --> 00:19:16,199 Not surprisingly 496 00:19:16,359 --> 00:19:17,479 A few days later 497 00:19:17,479 --> 00:19:17,979 A miracle happens 498 00:19:18,239 --> 00:19:19,760 Those swollen tumors 499 00:19:19,840 --> 00:19:21,840 suddenly, like burst balloons 500 00:19:22,479 --> 00:19:23,039 rapidly shrink 501 00:19:23,479 --> 00:19:25,399 Paul describes himself in the interview 502 00:19:25,399 --> 00:19:26,039 he says 503 00:19:26,039 --> 00:19:27,640 In those few short days 504 00:19:27,640 --> 00:19:29,439 I really felt like I was seeing those tumors with my own eyes 505 00:19:29,479 --> 00:19:30,520 as if melting away 506 00:19:30,520 --> 00:19:31,600 watching her feet 507 00:19:31,760 --> 00:19:33,600 I actually started seeing her ankles 508 00:19:33,600 --> 00:19:34,159 I actually started seeing her ankles 509 00:19:34,159 --> 00:19:34,880 Holy crap 510 00:19:34,880 --> 00:19:35,720 it's working 511 00:19:35,880 --> 00:19:37,600 Paul said he was so excited at the time that he shouted 512 00:19:37,960 --> 00:19:38,680 went through so many rounds of chemotherapy 513 00:19:38,680 --> 00:19:40,760 the late-stage malignant tumor stayed stubbornly unchanged despite so many rounds of chemotherapy and surgeries 514 00:19:42,680 --> 00:19:46,880 Under a two-pronged attack of AI vaccines and checkpoint inhibitors 515 00:19:46,880 --> 00:19:49,560 It could be seen with the naked eye as it rapidly shrank away 516 00:19:50,000 --> 00:19:51,439 Even more amazing 517 00:19:51,439 --> 00:19:53,680 Rosie's spirits recovered 518 00:19:53,680 --> 00:19:55,640 Back to the happy dog she used to be 519 00:20:01,319 --> 00:20:03,680 Of course Paul breathed a sigh of relief seeing Rosie 520 00:20:03,680 --> 00:20:06,640 But medicine is always rigorous 521 00:20:06,640 --> 00:20:10,800 Professor Paul Thordarson and Paul later spoke to the public with great candor 522 00:20:10,800 --> 00:20:14,359 While there was improvement, it's not a perfect cure 523 00:20:14,840 --> 00:20:18,520 In medicine this is called a partial response 524 00:20:18,600 --> 00:20:21,800 Most of Rosie's tumors have melted away 525 00:20:21,800 --> 00:20:25,600 But some cancer cells remained resistant to treatment 526 00:20:25,600 --> 00:20:26,680 Even to this day 527 00:20:26,680 --> 00:20:29,039 Paul still uses the data at his disposal 528 00:20:29,039 --> 00:20:32,000 to develop the next generation of booster shots for Rosie 529 00:20:32,119 --> 00:20:32,960 booster shots 530 00:20:33,039 --> 00:20:36,039 to tackle those residual drug-resistant cancer cells 531 00:20:36,600 --> 00:20:39,279 Cancer is a long war 532 00:20:39,279 --> 00:20:40,600 You may not win in a single shot 533 00:20:41,279 --> 00:20:42,960 But at least it shows that 534 00:20:42,960 --> 00:20:46,159 Paul has found a way forward we might not have known before 535 00:20:46,680 --> 00:20:50,840 The battlefield where Silicon Valley and biotech giants are now pouring money is right here 536 00:20:51,159 --> 00:20:53,800 When bioscience becomes information science 537 00:20:53,800 --> 00:20:56,439 Unknown mysteries that would have taken years to solve 538 00:20:56,439 --> 00:20:58,760 compressed by AI into days of data sorting 539 00:20:59,119 --> 00:21:02,760 Many people now worry AI will take away their jobs 540 00:21:02,760 --> 00:21:05,000 But when we look at Paul 541 00:21:05,000 --> 00:21:10,159 Is technology creating new possibilities between doctors and patients? 542 00:21:10,960 --> 00:21:11,520 The future 543 00:21:11,520 --> 00:21:14,800 Will what Paul did become a new kind of job? 544 00:21:15,680 --> 00:21:18,760 The eventual elimination of humans won't come from AI 545 00:21:18,760 --> 00:21:20,199 Weaving miracles 546 00:21:20,199 --> 00:21:21,680 nor is it cold, impersonal technology 547 00:21:21,960 --> 00:21:26,199 But it's those who know how to use AI to protect the ones they love 548 00:21:26,760 --> 00:21:28,680 This episode ends here 549 00:21:28,680 --> 00:21:29,640 Everyone 550 00:21:29,640 --> 00:21:34,720 What new opportunities do you think AI will create in medicine or other fields in the future? 551 00:21:35,199 --> 00:21:37,640 If you like this content remember to support YOLO in your own way 552 00:21:39,520 --> 00:21:40,359 See you next time, bye 41289

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