1 00:00:00,080 --> 00:00:02,560 Speaker 1: Over the last few years, Elon Musk has been a 2 00:00:02,680 --> 00:00:06,360 Speaker 1: very busy guy, getting electric cars in the masses, making 3 00:00:06,400 --> 00:00:10,239 Speaker 1: reusable rockets, digging these super high speed transportation tunnels, and 4 00:00:10,880 --> 00:00:14,120 Speaker 1: you know, getting in trouble with government regulators. But he's 5 00:00:14,160 --> 00:00:18,319 Speaker 1: also been funding a very secretive startup called Neuralink, and 6 00:00:18,360 --> 00:00:21,360 Speaker 1: in July he promised to finally unveil what this project 7 00:00:21,440 --> 00:00:25,120 Speaker 1: was up to. So he got on stage in San Francisco. Hello, 8 00:00:25,160 --> 00:00:30,840 Speaker 1: everybody there, must announce that Neuralinks team has been inserting 9 00:00:30,840 --> 00:00:34,000 Speaker 1: these tiny electrodes into the brains of rats to record 10 00:00:34,040 --> 00:00:38,800 Speaker 1: their brain activity. He said, the near term applications are medical. Everyone. 11 00:00:38,920 --> 00:00:42,120 Speaker 1: If they if you survive cancer and hot disease, odds 12 00:00:42,120 --> 00:00:45,560 Speaker 1: are that you will have some brain related disorder, so 13 00:00:45,600 --> 00:00:49,639 Speaker 1: I'll be like Alzheimer's or demand trip. Uh, we can 14 00:00:49,640 --> 00:00:56,600 Speaker 1: solve that with a trip. Musk wasn't shy about what 15 00:00:56,640 --> 00:00:59,959 Speaker 1: he hopes this technology will one day achieve. Yeah, those 16 00:01:00,000 --> 00:01:04,600 Speaker 1: cana sound pretty weird, but um, we can effectively achieve 17 00:01:04,640 --> 00:01:09,080 Speaker 1: a sort of symbiosis with artificial intelligence. So this is 18 00:01:09,080 --> 00:01:11,160 Speaker 1: not a mandatory thing. This is the thing that you 19 00:01:11,160 --> 00:01:13,840 Speaker 1: can choose to have if you want, and we can 20 00:01:13,840 --> 00:01:19,040 Speaker 1: effectively have the option of merging with AI. This is 21 00:01:19,080 --> 00:01:24,120 Speaker 1: extremely important. Ultimately we can do a full brain machine 22 00:01:24,120 --> 00:01:28,840 Speaker 1: interface brain machine interface. This is what people are calling 23 00:01:28,880 --> 00:01:32,080 Speaker 1: this technology away for us to control a computer with 24 00:01:32,120 --> 00:01:36,520 Speaker 1: our thoughts, a form of telepathy that's actually real and 25 00:01:36,600 --> 00:01:39,480 Speaker 1: it sounds crazy, like something straight out of science fiction, 26 00:01:40,080 --> 00:01:43,360 Speaker 1: but it's actually already had real success in medicine in 27 00:01:43,440 --> 00:01:47,680 Speaker 1: real life, even before Elon Musk came around. Today, in 28 00:01:47,720 --> 00:01:50,760 Speaker 1: the show Bloomberg, reporter Sarah McBride takes us through this 29 00:01:50,840 --> 00:01:54,640 Speaker 1: emerging and kind of terrifying field, introducing us to the 30 00:01:54,720 --> 00:01:58,559 Speaker 1: doctors already putting implants into human brains, and a patient 31 00:01:58,680 --> 00:02:02,280 Speaker 1: hoping to cure her seizures with this technology. Well, we 32 00:02:02,360 --> 00:02:05,640 Speaker 1: one day walk around as the cyborgs and Elon Musk's dreams. 33 00:02:06,480 --> 00:02:26,280 Speaker 1: I'm a ito. You're listening to Decrypted stay with us, Hey, Sarah, 34 00:02:26,280 --> 00:02:28,839 Speaker 1: how's it going. I'm good. How are you? I think 35 00:02:28,840 --> 00:02:32,520 Speaker 1: our listeners will recognize you from our episode last season 36 00:02:32,560 --> 00:02:36,040 Speaker 1: about the brains of birds. You've become a resident near 37 00:02:36,120 --> 00:02:41,400 Speaker 1: science expert. Yikes. That was a fun episode. It was 38 00:02:41,480 --> 00:02:44,959 Speaker 1: it was so you. You started digging into this pretty 39 00:02:45,040 --> 00:02:49,160 Speaker 1: much as soon as Elon Musk unveiled the details of Neuralink. 40 00:02:50,040 --> 00:02:52,360 Speaker 1: Do you want to kick us off with a broad 41 00:02:52,639 --> 00:02:57,799 Speaker 1: overview of this field of brain machine interfaces. Yeah, I 42 00:02:57,880 --> 00:03:00,680 Speaker 1: really had no idea how wides that it was. But 43 00:03:00,800 --> 00:03:05,200 Speaker 1: there are lots of companies working on this, lots of academics, 44 00:03:05,919 --> 00:03:09,080 Speaker 1: and I started learning very quickly that perhaps the biggest 45 00:03:09,120 --> 00:03:14,240 Speaker 1: debate in the industry is invasive or non invasive. So 46 00:03:14,880 --> 00:03:18,280 Speaker 1: do you want to put electrodes deep into the brain, 47 00:03:18,360 --> 00:03:21,400 Speaker 1: which involves signing through your skull, or just on the 48 00:03:21,440 --> 00:03:26,160 Speaker 1: outside once I'm more dangerous than the other. Yes. For example, 49 00:03:26,280 --> 00:03:30,640 Speaker 1: Facebook has a big program working on brain machine interfaces, 50 00:03:31,080 --> 00:03:35,000 Speaker 1: and they've picked kind of the safer route just understandably, yes, 51 00:03:35,720 --> 00:03:39,440 Speaker 1: just on the outside of your skull, but not Elon Musk. 52 00:03:41,840 --> 00:03:45,320 Speaker 1: They made a big presentation in July and Elon Musk 53 00:03:45,440 --> 00:03:49,440 Speaker 1: was talking about what they've been able to do, and 54 00:03:49,480 --> 00:03:54,200 Speaker 1: he was talking about how they've implanted electrodes in rodent 55 00:03:54,320 --> 00:03:58,440 Speaker 1: brains and they can read signals from those rodent brains now. 56 00:03:59,120 --> 00:04:03,000 Speaker 1: And then it turns out that neuralink has also been 57 00:04:03,160 --> 00:04:07,040 Speaker 1: working with monkeys, which we weren't supposed to know. That 58 00:04:07,240 --> 00:04:11,200 Speaker 1: Ellen must kind of slipped up a little bit at 59 00:04:11,240 --> 00:04:15,760 Speaker 1: his presentation and as he right, yeah, I mean, but 60 00:04:16,320 --> 00:04:19,920 Speaker 1: we have made you know, monkey has been able to 61 00:04:19,920 --> 00:04:26,640 Speaker 1: control the computer with his brain. Just yeah, why I 62 00:04:26,640 --> 00:04:32,800 Speaker 1: didn't realize running that result today, But there goes the 63 00:04:32,839 --> 00:04:34,280 Speaker 1: lony is going to come out of the bag. So 64 00:04:36,120 --> 00:04:39,160 Speaker 1: I think he just got very excited and wanted people 65 00:04:39,320 --> 00:04:44,160 Speaker 1: to know that. So he even surprised his own CEO 66 00:04:44,360 --> 00:04:47,839 Speaker 1: of Neuralalink, a guy called Max Kodak, by mentioning that 67 00:04:48,480 --> 00:04:52,080 Speaker 1: on stage at his big presentation. So tell me about 68 00:04:52,080 --> 00:04:56,000 Speaker 1: these monkeys. So I hopped on a train to Davis, 69 00:04:56,520 --> 00:05:01,719 Speaker 1: which runs a giant national primate Center. Melissa lets blew In, 70 00:05:01,960 --> 00:05:05,560 Speaker 1: who runs media relations for the university, came and met me, 71 00:05:05,720 --> 00:05:09,039 Speaker 1: drove me out to the primate center, introduced me to 72 00:05:09,240 --> 00:05:13,479 Speaker 1: Jennifer Short, who had colony management for the primate center, 73 00:05:14,240 --> 00:05:16,680 Speaker 1: and the two of them showed me around. We drove 74 00:05:16,720 --> 00:05:19,400 Speaker 1: all over in a golf card. I saw thousands and 75 00:05:19,480 --> 00:05:24,400 Speaker 1: thousands of monkeys. It was really fun. Seem more furious 76 00:05:24,520 --> 00:05:28,839 Speaker 1: than the other one. Sure, So we have corrals for 77 00:05:28,880 --> 00:05:31,680 Speaker 1: the monkeys. They're about half an acre and there are 78 00:05:31,720 --> 00:05:34,440 Speaker 1: twenty four of them that are out here and in 79 00:05:34,560 --> 00:05:38,880 Speaker 1: them we have anywhere from about eight monkeys, and they 80 00:05:38,920 --> 00:05:43,640 Speaker 1: these are breeding groups of monkeys, so they are mating 81 00:05:43,680 --> 00:05:46,359 Speaker 1: and then having babies. So would that be similar to 82 00:05:46,440 --> 00:05:50,320 Speaker 1: families of monkeys. Yes, these are families of monkeys. And 83 00:05:50,440 --> 00:05:56,800 Speaker 1: see the monkey bars, the monkey bars, they're blade um, 84 00:05:57,240 --> 00:05:59,640 Speaker 1: that's so cute. So this is a little baby coming 85 00:05:59,680 --> 00:06:02,440 Speaker 1: to look. Get us through the fence. Now see he 86 00:06:02,800 --> 00:06:05,480 Speaker 1: walked right up and he's like he's standing. Yeah. Yeah, 87 00:06:05,680 --> 00:06:08,680 Speaker 1: So he's drink. He's drinking. He's drinking out of a 88 00:06:08,760 --> 00:06:13,919 Speaker 1: water fountain up an So these are the monkeys that 89 00:06:14,040 --> 00:06:19,960 Speaker 1: Elon Musk is experimenting on. Well not exactly. It turns 90 00:06:19,960 --> 00:06:24,520 Speaker 1: out that the ones that get experimented on by neuralink 91 00:06:24,600 --> 00:06:28,159 Speaker 1: get kind of secreted away into these buildings where nobody 92 00:06:28,279 --> 00:06:30,720 Speaker 1: just driving around and a golf cart can see them. 93 00:06:31,400 --> 00:06:34,720 Speaker 1: So I think it's more accurate to say this is 94 00:06:34,760 --> 00:06:38,560 Speaker 1: the pool of monkeys from which one day a neuralink 95 00:06:38,640 --> 00:06:42,800 Speaker 1: experiment monkey might be selected. The reason I heard about 96 00:06:42,839 --> 00:06:44,599 Speaker 1: the center in the first place is because you work 97 00:06:44,680 --> 00:06:47,200 Speaker 1: with neuralink, So what can you tell me about what 98 00:06:47,240 --> 00:06:50,520 Speaker 1: you're doing with neural link here? Well as with many 99 00:06:50,560 --> 00:06:54,359 Speaker 1: of our ongoing projects, um the research is proprietary and 100 00:06:54,560 --> 00:06:58,479 Speaker 1: ongoing research. We really can't talk about because they're in 101 00:06:58,480 --> 00:07:01,040 Speaker 1: the process of doing the research and it still needs 102 00:07:01,240 --> 00:07:04,200 Speaker 1: to be looked at and to be you know, really 103 00:07:04,279 --> 00:07:08,680 Speaker 1: vigorously reviewed before anybody says anything about the research. So 104 00:07:08,760 --> 00:07:11,680 Speaker 1: this was Melissa again from you See Davis, and I 105 00:07:11,800 --> 00:07:15,240 Speaker 1: tried so hard to get them to say anything about 106 00:07:15,320 --> 00:07:19,120 Speaker 1: what Neuralalink was doing, and the closest I got was 107 00:07:19,200 --> 00:07:22,560 Speaker 1: when I asked, so, are they working on really cool projects? 108 00:07:22,920 --> 00:07:32,000 Speaker 1: And they said yes and left it there. So what 109 00:07:32,040 --> 00:07:34,560 Speaker 1: did you do next? Well, I knew there were some 110 00:07:34,600 --> 00:07:37,200 Speaker 1: people who have left neural Link, and I thought maybe 111 00:07:37,200 --> 00:07:39,600 Speaker 1: I could find out a little bit more about what's 112 00:07:39,640 --> 00:07:44,400 Speaker 1: going on. So I noticed that this guy, Vikash Gilja 113 00:07:44,920 --> 00:07:49,040 Speaker 1: had worked at Neuralink and is now a professor at 114 00:07:49,080 --> 00:07:52,640 Speaker 1: you See San Diego. So I actually went down to 115 00:07:52,880 --> 00:07:57,000 Speaker 1: San Diego. Did you ever meet Elon? Yeah, they met 116 00:07:57,080 --> 00:08:00,560 Speaker 1: him quite a few times, and we'll was that like, 117 00:08:00,800 --> 00:08:05,400 Speaker 1: is he just very interested and everybody sward, Yeah, definitely. 118 00:08:06,000 --> 00:08:09,560 Speaker 1: He signed all kinds of NDA's. He can't talk too 119 00:08:09,600 --> 00:08:13,320 Speaker 1: precisely about what's going on at neural length, but he 120 00:08:13,400 --> 00:08:16,600 Speaker 1: can talk about the state of play in brain machine 121 00:08:16,600 --> 00:08:21,360 Speaker 1: interfaces and what he's doing and what the big breakthroughs 122 00:08:21,360 --> 00:08:23,760 Speaker 1: in the field have been. So what do you tell you? 123 00:08:24,280 --> 00:08:27,560 Speaker 1: So vication I talked a lot about the difference between 124 00:08:27,840 --> 00:08:32,560 Speaker 1: invasive and non invasive technologies, and he came up with 125 00:08:32,600 --> 00:08:35,720 Speaker 1: this great metaphor. He compared it to a cocktail party, 126 00:08:35,800 --> 00:08:39,240 Speaker 1: and he said, non invasive is when you walk into 127 00:08:39,559 --> 00:08:42,400 Speaker 1: a cocktail party and you just kind of put one 128 00:08:42,480 --> 00:08:44,840 Speaker 1: microphone in the door of the room, so you hear 129 00:08:44,880 --> 00:08:47,720 Speaker 1: everything that's going on. You know, everyone's having a great time. 130 00:08:47,840 --> 00:08:52,200 Speaker 1: You hear the glasses clinking and the food being passed around, 131 00:08:52,240 --> 00:08:56,600 Speaker 1: but you really only have those broad strokes, um say, 132 00:08:56,760 --> 00:08:59,640 Speaker 1: if you have a room full of people. It's the 133 00:08:59,679 --> 00:09:04,400 Speaker 1: different between having a few microphones on the ceiling versus 134 00:09:04,520 --> 00:09:09,160 Speaker 1: having um my lapel microphones on on everyone's collars so 135 00:09:09,200 --> 00:09:12,760 Speaker 1: that you can hear each person speaking. The precise level 136 00:09:12,840 --> 00:09:16,840 Speaker 1: of detail you can get with all those different mics 137 00:09:16,880 --> 00:09:20,240 Speaker 1: and different spots of the party is exactly the same 138 00:09:20,280 --> 00:09:23,559 Speaker 1: as different electrodes deep inside different parts of the brain. 139 00:09:23,760 --> 00:09:26,680 Speaker 1: So what neural link is doing is the individual mics 140 00:09:26,760 --> 00:09:35,000 Speaker 1: on every single person's collar. Yes, exactly. And then thanks 141 00:09:35,040 --> 00:09:39,400 Speaker 1: to vikash I met one of the doctors he works with, 142 00:09:39,640 --> 00:09:44,240 Speaker 1: a brain surgeon called Sharona ben Him. She is a 143 00:09:44,360 --> 00:09:50,520 Speaker 1: very impressive woman. She does tons of brain surgeries. She calculated, 144 00:09:50,640 --> 00:09:53,959 Speaker 1: kind of off the cuff, about sixty a year, which 145 00:09:54,040 --> 00:09:57,200 Speaker 1: is more than one a week putting these implants into 146 00:09:57,280 --> 00:10:01,480 Speaker 1: human putting electrodes into people's brains. Yeah, so she got 147 00:10:01,559 --> 00:10:06,600 Speaker 1: really interested in this specialty. In medical school, she has 148 00:10:06,720 --> 00:10:09,560 Speaker 1: this aha moment where she knew she wanted to become 149 00:10:09,600 --> 00:10:13,800 Speaker 1: this type of surgeon. She and her professor were operating 150 00:10:14,280 --> 00:10:18,920 Speaker 1: on a patient with Parkinson's inserting an electrode into his brain, 151 00:10:19,160 --> 00:10:21,720 Speaker 1: and that's when she knew. The patient was awake and 152 00:10:21,760 --> 00:10:25,760 Speaker 1: the tremor was very really profound. Um, and we implanted 153 00:10:25,760 --> 00:10:28,240 Speaker 1: the electrode and this the second we turned it on, 154 00:10:29,559 --> 00:10:34,080 Speaker 1: like magic, the tremor just went away and the patient, 155 00:10:34,240 --> 00:10:36,560 Speaker 1: you know, went from not being able to hold a 156 00:10:36,600 --> 00:10:41,400 Speaker 1: cup to just like very coordinated, streamline fashion moving herd 157 00:10:42,200 --> 00:10:45,480 Speaker 1: And uh, that's what I was sold that. So when 158 00:10:45,520 --> 00:10:47,720 Speaker 1: I thought that that was one of the coolest things 159 00:10:47,760 --> 00:10:50,480 Speaker 1: I've ever seen. That's incredible, that this is what the 160 00:10:50,520 --> 00:10:53,920 Speaker 1: technology can do. Yeah, it really is. But I had 161 00:10:53,960 --> 00:10:57,400 Speaker 1: to keep reminding myself that because she's so matter of 162 00:10:57,480 --> 00:10:59,959 Speaker 1: fact and down to earth, and I had to keep 163 00:11:00,480 --> 00:11:05,480 Speaker 1: telling myself, she's inserting electrodes into patients brains and it's 164 00:11:05,559 --> 00:11:08,200 Speaker 1: actually a real art and we need to get the 165 00:11:08,240 --> 00:11:13,080 Speaker 1: electrode really like perfectly in the right spot, you know, 166 00:11:13,600 --> 00:11:16,200 Speaker 1: in the nucleus and exact right orientation. So it's actually 167 00:11:16,280 --> 00:11:19,600 Speaker 1: quite a surgical challenge. That means she can't be off 168 00:11:19,720 --> 00:11:24,640 Speaker 1: by more than two millimeters. I know, it is crazy. 169 00:11:31,600 --> 00:11:42,480 Speaker 1: We'll be right back. So Dr ben Him was kind 170 00:11:42,600 --> 00:11:46,680 Speaker 1: enough to connect me to a couple of her patients, 171 00:11:47,520 --> 00:11:52,920 Speaker 1: and one of them was this young woman, Lydia. My 172 00:11:53,040 --> 00:11:57,600 Speaker 1: name is Lydia Budney. I have elefsy and it started 173 00:11:57,640 --> 00:12:00,439 Speaker 1: when I was a freshman in high school. So at 174 00:12:00,480 --> 00:12:03,280 Speaker 1: this point it's been about twenty years. She says, she's 175 00:12:03,320 --> 00:12:06,800 Speaker 1: tried so hard to find rhyme or reason to them. 176 00:12:06,840 --> 00:12:09,480 Speaker 1: Does it depend on how much she slapped or what 177 00:12:09,640 --> 00:12:12,640 Speaker 1: she's eaten? And she just can't find a pattern, So 178 00:12:12,720 --> 00:12:17,520 Speaker 1: she just never knows when a seizure might strike. Usually 179 00:12:17,600 --> 00:12:20,920 Speaker 1: when I have them, I'll be going about my normal 180 00:12:20,960 --> 00:12:25,480 Speaker 1: untain doing everything, and then for me, it's I usually 181 00:12:25,480 --> 00:12:28,680 Speaker 1: wake up on the floor, I fall I hit things, 182 00:12:28,840 --> 00:12:31,080 Speaker 1: and it's like all they can do is try and 183 00:12:31,240 --> 00:12:33,800 Speaker 1: keep me in a safe position where I'm not kicking 184 00:12:33,840 --> 00:12:35,520 Speaker 1: a lot of things or hitting a lot of things. 185 00:12:35,600 --> 00:12:38,680 Speaker 1: But it's like they can't do anything to actually keep 186 00:12:38,760 --> 00:12:43,000 Speaker 1: you from having them. She met me just days before 187 00:12:43,000 --> 00:12:48,920 Speaker 1: her thirty four birthday, and she'd already had one surgery 188 00:12:49,200 --> 00:12:55,200 Speaker 1: using electrodes to identify where in the brain her epileptic 189 00:12:55,320 --> 00:12:58,720 Speaker 1: seizures were coming from. And the bad news she got 190 00:12:58,760 --> 00:13:02,760 Speaker 1: after that surgery, which was earlier this year, was everywhere 191 00:13:03,160 --> 00:13:05,520 Speaker 1: there were all different kinds of parts of her brain 192 00:13:06,559 --> 00:13:12,360 Speaker 1: making seizures. Apparently, I am a tricky case because technically 193 00:13:12,440 --> 00:13:15,719 Speaker 1: I have generalized epilepsy because my seizures do not all 194 00:13:15,880 --> 00:13:20,320 Speaker 1: start from the same spot, like the irregular activity happens 195 00:13:20,760 --> 00:13:24,560 Speaker 1: kind of all over. So the irregular activity comes all over, 196 00:13:24,760 --> 00:13:28,040 Speaker 1: but the worst seizures come from just one part of 197 00:13:28,080 --> 00:13:32,000 Speaker 1: her brain. So for her, the best strategy was to 198 00:13:32,120 --> 00:13:37,439 Speaker 1: get permanent electrodes targeting just that one part, and once 199 00:13:37,480 --> 00:13:41,040 Speaker 1: they get inserted into her brain, those electrodes can tell 200 00:13:41,120 --> 00:13:44,720 Speaker 1: when she's about to have a seizure and hopefully zappa 201 00:13:44,800 --> 00:13:47,280 Speaker 1: pulse right into that part of her brain to stop 202 00:13:47,320 --> 00:13:51,959 Speaker 1: the seizure. Wow, that's amazing. What was she scared? I 203 00:13:51,960 --> 00:13:54,160 Speaker 1: didn't even think about it. It was like hands down, like, 204 00:13:54,520 --> 00:13:57,920 Speaker 1: I mean, do what you need to. Um. You know, because, 205 00:13:57,960 --> 00:14:00,040 Speaker 1: like I said, the seizures have become more freak it, 206 00:14:00,800 --> 00:14:07,440 Speaker 1: UM don't seem to be really controllable completely with my medicine. UM. 207 00:14:07,480 --> 00:14:08,840 Speaker 1: It just got to the point where I was like, 208 00:14:09,080 --> 00:14:11,480 Speaker 1: the seizures scared me more than anything that could be 209 00:14:11,520 --> 00:14:14,560 Speaker 1: done in the hospital. She seemed really brave to me, 210 00:14:15,000 --> 00:14:17,840 Speaker 1: but she had this great attitude. I'm going to turn 211 00:14:17,920 --> 00:14:20,640 Speaker 1: thirty four and I already have a computer in my head. 212 00:14:20,720 --> 00:14:24,400 Speaker 1: I'm going to be part robot, you know. It's kind 213 00:14:24,440 --> 00:14:28,600 Speaker 1: of my joke, you know, thirty four root Like, it's 214 00:14:28,600 --> 00:14:38,920 Speaker 1: an awesome time. So, Sarah, I think you said that 215 00:14:38,960 --> 00:14:43,200 Speaker 1: you talked to Lydia just before her second surgery. How's 216 00:14:43,200 --> 00:14:46,480 Speaker 1: she doing now? Well, I've been texting with her and 217 00:14:46,520 --> 00:14:51,800 Speaker 1: it sounds like she's doing great. That second surgery lasted 218 00:14:52,080 --> 00:14:54,840 Speaker 1: just six hours, which would be long for any other 219 00:14:54,920 --> 00:14:58,080 Speaker 1: type of surgery, but for brain surgery, that's a lot 220 00:14:58,200 --> 00:15:01,880 Speaker 1: less than I expected to It went well, Yeah, it 221 00:15:01,920 --> 00:15:06,120 Speaker 1: went really well, and she's already back home. In fact, 222 00:15:06,200 --> 00:15:10,120 Speaker 1: she just went back to work, so she's already a 223 00:15:10,160 --> 00:15:15,360 Speaker 1: bionic woman, as she dreamed. But yeah, so do we 224 00:15:15,440 --> 00:15:18,200 Speaker 1: know if her seizures have already stopped. Well, it's a 225 00:15:18,320 --> 00:15:22,160 Speaker 1: longer process. So they've got all the gear in her 226 00:15:22,160 --> 00:15:25,200 Speaker 1: brain now that can stop the seizures. They just have 227 00:15:25,320 --> 00:15:27,840 Speaker 1: to monitor her for a couple of months and then 228 00:15:27,880 --> 00:15:31,880 Speaker 1: they know exactly how to turn off those seizures. So 229 00:15:31,920 --> 00:15:34,600 Speaker 1: she's in the part of the process which will last 230 00:15:34,680 --> 00:15:38,160 Speaker 1: about two months, where they monitor her brain and then 231 00:15:38,200 --> 00:15:40,760 Speaker 1: they can turn on the part of the technology that 232 00:15:41,080 --> 00:15:44,720 Speaker 1: hopefully will stop the seizures just in time for the holidays. 233 00:15:45,040 --> 00:15:55,680 Speaker 1: It's incredible. If the world of medicine has already come 234 00:15:55,760 --> 00:16:00,080 Speaker 1: this far without Elon Musk, what is Nurling hoping to do. 235 00:16:01,080 --> 00:16:04,800 Speaker 1: They're just hoping to take it much farther, so beyond 236 00:16:04,800 --> 00:16:08,720 Speaker 1: the realm of medicine and into the realm of what 237 00:16:08,880 --> 00:16:14,320 Speaker 1: could be considered by some people cosmetic brain enhancement, So 238 00:16:14,440 --> 00:16:18,320 Speaker 1: things that aren't medically necessary but could enhance your quality 239 00:16:18,360 --> 00:16:23,680 Speaker 1: of life, like having an excellent memory, or being able 240 00:16:23,720 --> 00:16:28,200 Speaker 1: to calculate things very quickly, or being able to download 241 00:16:28,240 --> 00:16:31,600 Speaker 1: a language overnight. Things like that. Did the people you 242 00:16:31,680 --> 00:16:34,440 Speaker 1: talk to have a sense of how soon that was 243 00:16:34,480 --> 00:16:38,440 Speaker 1: going to be ready. Probably fifteen or twenty years. That's 244 00:16:38,440 --> 00:16:46,720 Speaker 1: not that long of a time. Wow, But maybe not 245 00:16:47,160 --> 00:16:50,720 Speaker 1: glitch free, like maybe elements of it, Like take that 246 00:16:50,840 --> 00:16:54,560 Speaker 1: learn a language example. Maybe the first thing would be 247 00:16:54,680 --> 00:16:59,920 Speaker 1: you'd be able to download vocabulary or you'd be able 248 00:17:00,240 --> 00:17:07,760 Speaker 1: to overnight learn some portion of that language. It might 249 00:17:07,760 --> 00:17:11,440 Speaker 1: not be click in fifteen years you can learn French overnight. 250 00:17:11,520 --> 00:17:15,480 Speaker 1: It might be in little stages. You know, the researchers 251 00:17:15,520 --> 00:17:19,000 Speaker 1: you talked to are doing this for a very specific 252 00:17:19,119 --> 00:17:24,320 Speaker 1: purpose of treating people with debilitating illnesses. Do they have 253 00:17:24,359 --> 00:17:30,000 Speaker 1: any concerns about bringing this out to the broader public? Yeah? 254 00:17:30,080 --> 00:17:35,399 Speaker 1: I mean the caution. I had a long conversation about 255 00:17:35,480 --> 00:17:39,840 Speaker 1: ethics and could this worsen inequality? You could see a 256 00:17:39,920 --> 00:17:43,399 Speaker 1: day where rich people can pay for all kinds of 257 00:17:43,520 --> 00:17:47,680 Speaker 1: enhancements that will make it possible to learn things more 258 00:17:47,760 --> 00:17:51,800 Speaker 1: easily and more thoroughly, and poor people won't. So what 259 00:17:51,840 --> 00:17:54,960 Speaker 1: does Sharonna think about all this? Well, she was really 260 00:17:55,240 --> 00:17:59,080 Speaker 1: focused on what is and isn't possible and how many 261 00:17:59,160 --> 00:18:03,040 Speaker 1: misconceptions there are about the brain. Do you think people's 262 00:18:03,080 --> 00:18:06,159 Speaker 1: expectations are getting out of whack with reality. I mean, 263 00:18:06,200 --> 00:18:08,719 Speaker 1: you told me it'll be a long time before we 264 00:18:08,800 --> 00:18:16,600 Speaker 1: have anything. Ellen nice makes things happen, So it's interesting. Um, 265 00:18:16,640 --> 00:18:18,760 Speaker 1: you know, I don't know what people's expectations are. I 266 00:18:18,760 --> 00:18:24,400 Speaker 1: think there's there's expectations and there's fears. Um. But um, 267 00:18:24,720 --> 00:18:28,520 Speaker 1: there's so many interesting unfounded you know, concepts about the 268 00:18:28,560 --> 00:18:32,520 Speaker 1: brain to begin with that, who knows? And she said 269 00:18:32,640 --> 00:18:35,480 Speaker 1: she told me she'd been watching some TV program where 270 00:18:35,520 --> 00:18:40,200 Speaker 1: they talked about how only ten of the brain was used, 271 00:18:40,240 --> 00:18:43,600 Speaker 1: and I told her that before. Is that true? No, 272 00:18:44,040 --> 00:18:45,800 Speaker 1: that's I mean, I don't know what that's based on. 273 00:18:47,520 --> 00:18:50,080 Speaker 1: Ill we use all of our brain? Because I've heard 274 00:18:50,119 --> 00:18:52,320 Speaker 1: we only use a small part of it. I didn't 275 00:18:52,560 --> 00:18:57,000 Speaker 1: know we use all of our brain? Um. But do 276 00:18:57,080 --> 00:19:03,840 Speaker 1: we have rum in our brain to download language? Probably? Really? Yeah? 277 00:19:04,320 --> 00:19:08,320 Speaker 1: If um you could have some kind of cosmetic brain 278 00:19:09,040 --> 00:19:12,360 Speaker 1: something done to augment your brain? What when you pick 279 00:19:14,040 --> 00:19:20,880 Speaker 1: a I don't know, I don't really I don't think 280 00:19:20,880 --> 00:19:24,000 Speaker 1: i'd be really excited about something like that. Really yea 281 00:19:24,280 --> 00:19:29,560 Speaker 1: even memory? Um No, I can't say that I would 282 00:19:29,640 --> 00:19:39,680 Speaker 1: really uh sire any augmentation? Um, guys that Um, I'm 283 00:19:39,720 --> 00:19:43,840 Speaker 1: really happy with the way my brain works. Yeah, I 284 00:19:43,880 --> 00:19:47,800 Speaker 1: mean there's enough noise in all our heads already and 285 00:19:47,920 --> 00:19:50,639 Speaker 1: she didn't want to add to it. Well, she's a 286 00:19:50,680 --> 00:19:54,800 Speaker 1: brilliant neurosurgence. She probably doesn't need it. Would you ever 287 00:19:54,880 --> 00:19:59,240 Speaker 1: want that? I would absolutely? Yeah, if it were safe. Um, 288 00:19:59,280 --> 00:20:01,800 Speaker 1: I would do it a a heartbeat if my wife 289 00:20:01,880 --> 00:20:07,040 Speaker 1: lets me. How about you. I'm super cautious, so when 290 00:20:07,080 --> 00:20:09,760 Speaker 1: I got lazick, I only got it in when eye, 291 00:20:09,840 --> 00:20:13,440 Speaker 1: just in case. So probably no, I don't think I'm 292 00:20:13,480 --> 00:20:19,639 Speaker 1: a good candidate, you know, Sarah. For all of Elon 293 00:20:19,760 --> 00:20:24,960 Speaker 1: Musk's faults, everything he does is just so wildly ambitious. 294 00:20:26,160 --> 00:20:28,320 Speaker 1: And I think the newest thing that he's trying to 295 00:20:28,359 --> 00:20:32,000 Speaker 1: do our brains talking to computers, that's got to be 296 00:20:32,040 --> 00:20:34,480 Speaker 1: the most outlandish one. It has to be the one 297 00:20:34,560 --> 00:20:37,600 Speaker 1: that has the most potential to change the way that 298 00:20:37,640 --> 00:20:41,240 Speaker 1: we live. It kind of changes what it means to 299 00:20:41,280 --> 00:20:46,320 Speaker 1: be human itself. You could say that he talks about 300 00:20:46,560 --> 00:20:52,720 Speaker 1: the philosophy. He says that in the future, when AI 301 00:20:52,760 --> 00:20:57,560 Speaker 1: will be so predominant, we don't have to have this 302 00:20:57,680 --> 00:21:00,119 Speaker 1: kind of enhancement, but things will go much about or 303 00:21:00,240 --> 00:21:02,280 Speaker 1: for us if we do just to live in a 304 00:21:02,359 --> 00:21:06,640 Speaker 1: world with so much AI when the robots takeover. Yeah, 305 00:21:06,800 --> 00:21:11,080 Speaker 1: he's talked in the past about how we need to 306 00:21:11,280 --> 00:21:16,600 Speaker 1: fuse our brains with machines to survive in a world 307 00:21:16,640 --> 00:21:21,720 Speaker 1: like that. He said that potentially we could just be 308 00:21:21,880 --> 00:21:25,800 Speaker 1: housecats to our robot overlords, and the house cat would 309 00:21:25,800 --> 00:21:29,240 Speaker 1: be a good outcome, but the brain implants will help 310 00:21:29,320 --> 00:21:35,119 Speaker 1: us complete help us avoid that house cat fate. Yes, so, 311 00:21:36,760 --> 00:21:41,439 Speaker 1: I don't know. He's not always the most philosophical. He 312 00:21:41,520 --> 00:21:46,600 Speaker 1: asked at that presentation in July, well, what if our 313 00:21:48,000 --> 00:21:51,200 Speaker 1: minds are just brains into vat and then he said, yes, 314 00:21:51,480 --> 00:21:59,520 Speaker 1: that's what they are, brains in that romantic right. And 315 00:22:00,040 --> 00:22:01,960 Speaker 1: what is it to be human? I mean, what is 316 00:22:02,000 --> 00:22:06,520 Speaker 1: it to be anything? Our understanding of everything changes with 317 00:22:07,080 --> 00:22:10,399 Speaker 1: every decade that goes by as we learn more and 318 00:22:10,440 --> 00:22:14,119 Speaker 1: more science. So I'm not sure that we know what 319 00:22:14,200 --> 00:22:16,399 Speaker 1: it is to be human now, and I'm not sure 320 00:22:16,480 --> 00:22:20,880 Speaker 1: that these brain machine interfaces will help us in that regard, 321 00:22:22,760 --> 00:22:40,600 Speaker 1: but they'll still change it whatever it is. Sarah, thanks 322 00:22:40,600 --> 00:22:42,800 Speaker 1: for coming on the show today, Oh thanks for having me. 323 00:22:47,720 --> 00:22:50,760 Speaker 1: Decrypted is hosted by me Akito. Sean Ween is our 324 00:22:50,800 --> 00:22:54,080 Speaker 1: executive producer. So for Foreheads and Ethan Brooks mix the 325 00:22:54,119 --> 00:22:57,639 Speaker 1: show today and Francesca Levy is the head of Bloomberg Podcasts. 326 00:22:57,880 --> 00:23:03,160 Speaker 1: We'll see next week. Put a Council, trans of secuted 327 00:23:03,320 --> 00:23:11,200 Speaker 1: and subtrasted as conclusial councils, Bustin Council, sal coupsal MCLs, BRONC, 328 00:23:11,520 --> 00:23:12,000 Speaker 1: Business