前 Neuralink 创始人:AI 增强型身体已近在眼前|与 Max Hodak 对谈 | EP #171
Diamandis 将 Science 的近期资产 PRIMA 定位为其更具投机性的脑机接口项目的潜在收入引擎。 Hodak 表示,其光伏视网膜植入物在一项涉及38人的欧洲试验中,让此前失明的患者重新阅读;全球约有50人接受过植入。他强调,该产品目前仍未获批,计划在1个月内向欧盟提交申请,并希望明年年初在欧盟、甚至美国上市。
PRIMA 的经济性可能让可持续的 BCI 开发大幅降低对创投市场周期的依赖。 Hodak 援引的报销先例是美国每位患者约20万美元、欧洲每位患者约15万美元;如果每年服务2,000–3,000名患者,将对应约5亿美元的业务规模;他认为更广泛的机会达到30亿–40亿美元。Diamandis 警告称,“每18个月就得回去取一次水,是巨大的战略劣势”,并认为在一家 BCI 公司年收入达到或超过1亿美元之前,这个领域始终面临再次陷入融资寒冬的风险。
今天的脑机接口距离人类通信带宽仍相去甚远,也无法靠增加更多穿透式导线来安全扩展。 血管电极约为0.5 bit/秒,Neuralink 和 BrainGate 级系统为5–7 bit/秒,语言约为40 bit/秒,注意过程约为10 bit/秒。即便是头发丝般粗细的柔性电极,也会破坏数千个细胞,因为“大脑里没有空间”;这种损伤或许值得用于瘫痪治疗,但不适合连接数百万个神经元。
Science 试图通过一种生物混合器件摆脱这一取舍,让接口实际上长出一条“第13条颅神经”。 水凝胶中的工程化神经元与大脑形成生物连接,而光学刺激和电信号记录留在器件一端;目标架构是10万个电极、100万移植神经元和10亿个突触。小鼠移植物已经会围绕血管生长,并根据活动在4–6周后修剪连接,有望让其接线“由信息定义”。
转化时间表可能正在压缩,部分原因是一项 Hodak 提到但未详细说明的潜在合作。 预计几个月内将进行灵长类动物移植;就在3周前,他还预计首次人体应用需要4年或5年,如今认为可能快得多。最初的应用“几乎肯定”会针对中风,而不是能力增强。
最终论点不止于 AI 增强,还延伸到共享意识和死后的连续性,但 Hodak 仍保留不确定性。 他设想,脑对脑连接最初可以帮助结婚多年的夫妇应对终末期疾病,甚至可能让一方的死亡“基本上变成一次可以康复的中风”,并认为这种连续性或许能在未来10年实现。他也越来越确信,他们将在5年内“做到这一点”。但对于两个意识是否会合而为一,他的回答是:“我不知道那会是什么感觉,但我们会找到答案。”
1. Diamandis 将 PRIMA 定位为潜在融资引擎
Hodak 称 PRIMA 是“全球首个真正有效的视网膜假体”。对于光感受器已经死亡、但视网膜和大脑仍能正常工作的患者,尤其是年龄相关性黄斑变性和视网膜色素变性患者,一枚植入视网膜下方的光伏芯片会接收眼镜投射的激光图像,并刺激残存的视网膜细胞;植入手术约需1小时,几天即可恢复。
一项涉及38名患者的欧洲试验于去年夏天完成,全球约有50人接受过植入。Hodak 表示,据“我们所知”,这是这类失明患者首次重新读出文字;但他同时强调产品尚未获批:计划在1个月内向欧盟提交申请,并希望明年年初在欧盟、以及美国实现商业化。
美国每位患者的报销先例约为20万美元,欧洲约为15万美元;直接符合条件的患者有数万人,更广泛的人群估计接近25万人。若每年达到2,000–3,000名患者,对应的业务规模约为5亿美元;Hodak 将更广泛的机会描述为30亿–40亿美元。Diamandis 警告称,每18个月就必须重新融资是战略劣势,并表示 BCI 需要一家年收入达到或超过1亿美元的公司,才能降低其持续面临的“融资寒冬风险”。
2. 穿透式电极撞上生物学扩展瓶颈
Hodak 的前提是,“BCI 是一个领域,不是一款产品”:EEG、血管支架、穿透式导线、光遗传学和超声波分别服务于不同应用。非侵入式系统存在分辨率和准确性的根本限制,而光学与超声方案通常需要对成年神经元进行不可逆、分布不完善的基因改造。
这条带宽阶梯决定了预期:血管电极约为0.5 bit/秒,Neuralink 或 BrainGate 等穿透式系统达到5–7 bit/秒,语言约为40 bit/秒,注意过程约为10 bit/秒。因此,高带宽可能意味着导出图像或音频,并用知识或记忆丰富认知 token,而不只是让思考速度更快。
导线可以接触单个神经元,但“大脑里没有空间”:即便是微型柔性电极,在湿润且受压缩的组织中也会破坏数千个细胞。Hodak 认为,对于严重脊髓损伤患者,以损失5万个皮层细胞为代价,从500个神经元获得5 bit/秒或许值得;但这种方式无法扩展到数百万个神经元。Diamandis 此前曾否定 Kurzweil 关于2030年代初、约2033年实现高带宽的预测;与 Hodak 交流后,他改变了看法。
3. 生物混合植入物或可让接口自行生长
Science 的替代方案是“长出一条第13条颅神经”。工程化的干细胞衍生神经元被固定在水凝胶中并移植到皮层,电气和机械硬件则留在脑组织之外;光学刺激加上电信号记录,可在没有串扰的情况下实现双向通信。
规模是这场下注的核心:一枚拥有10万个电极的器件可以承载100万神经元并形成10亿个突触,而 BrainGate 只有100个电极,Neuralink 目前也只有1,000个。Hodak 将最终形态比作 Avatar 中延伸到体外的颅神经——“末端接一根 USB 线”——并具备跨越左右半球、类似胼胝体的带宽。
在小鼠体内,移植神经元会广泛建立连接,随后在4–6周后根据活动进行修剪,暗示其接线可能由设备活动“以信息定义”。神经纤维可以向皮层下结构延伸数毫米;与插入式电极不同,它们会围绕血管生长,而毛细血管也会围绕它们重塑。
4. 细胞工程与垂直整合推动时间表前移
让移植物躲过免疫系统,需要对干细胞进行大规模改造,使其具备低免疫原性;为每位患者单独生产将耗时超过1年,成本也高得无法承受。一种由小分子触发的自毁开关,可以让移植物细胞在患者服用某种维生素后死亡;在将它们隐藏于免疫系统之后,这是一项重要的安全保障。Hodak 表示,进入人体时,这些细胞将是“迄今为止改造程度最高的细胞疗法”。
碳化硅等材料,以及“智能手机红利”,补齐了整个技术栈:BCI 可以继承 Apple、Samsung 等公司投入超过1000亿美元支持的技术。Science 还完成了2项收购,其中包括一家位于北卡罗来纳州的自有 MEMS 晶圆厂;公司会主动放弃对价值数百万美元设备的保修,并能在几周内把设计改动推进到手术。
首批灵长类动物移植预计在“几个月内”进行。3周前,Hodak 还认为首次人体应用要等4年或5年,但一项潜在合作可能加快进度;首批患者“几乎肯定”会是中风患者。他的理由是,一只从未拥有过某块皮层区域的猴子,可以模拟一个失去该区域的人类,因此恢复这项能力将有助于技术转化。
5. 脑连接可能重新划定“人”的边界
Hodak 的时间视野落在2030年至2035年之间:AGI 和 ASI “肯定会发生”,但当被问及融合是否是通向未来的唯一道路时,他的回答是“我不知道”。Transformer 或许能够解释皮层,而能动性仍属于人类;参与其中的人可能获得巨大优势,社会必须正视这一点。
他认为,脑对脑连接最可能的首个应用不是 AI 增强,而是帮助一对结婚多年的夫妇应对其中一方的终末期疾病。由于亲密关系本来就会在两个大脑之间分布记忆,只要绑定足够深,就可能让意识与体验在一方死亡后保持连续;他认为,这条工程路径或许能在未来10年内实现。
Hogan 双胞胎是 Hodak 用来说明大脑边界可以重划的自然案例:1个头、4个半球,意识存在共享部分,也能转移任务。“我们知道这一定可能,因为自然已经做到过。”他越来越确信,5年内可以实现这类结果,但对于这种体验本身会是什么样,仍保持不可知论。
I'm super pumped about what you've been building. We're going to talk about 2 things: a product you have today, which is a revenue engine, and the incredible moonshot you're pursuing. I love entrepreneurs who've got something big and bold but also have a real business at the same time on the path there. That's extraordinarily unique and critically important when you're actually building a business, and you've done both. Before we jump into the BCI of it all, would you talk about PRIMA?
First of all, thank you for having me. It's a pleasure—super cool to be here. I don't want to undersell the near-term product, which is still a huge deal.
We have the world's first retinal prosthesis that really works. There are 3 layers of cells in the eye that transmit vision, from light coming in to a signal going into the brain. For patients who have lost the rods and cones in the back of their eyes, their retina is intact and their brain can see, but their eyes no longer light up.
What types of disease are these typically?
This is specifically macular degeneration, especially age-related macular degeneration. Does anybody know anybody with macular degeneration here in the room? A lot, right? It's pretty prevalent. It's also retinitis pigmentosa. My mother's father had retinitis pigmentosa, so I grew up around blindness.
We have a chip that can be implanted in the back of the eye. Each one of these little honeycomb structures is essentially a solar cell. The patient puts on glasses with a laser projector that strikes the implant in the back of the eye to excite the remaining viable cells in the retina and get the visual signal into the optic nerve at the first possible opportunity beyond the dead photoreceptors.
It's a super-simple, 1-hour outpatient procedure. The surgeon makes a little bleb under the retina, places the chip, and then the patient goes home and recovers in a couple of days. They can put on these glasses. We finished a clinical trial last summer with 38 patients in Europe. About 50 people around the world have had it so far. It's the first time in the history of the world, as far as we know, that these blind patients have been able to read again. We're super excited about this.
You know, it's interesting because giving sight to the blind is a very biblical statement.
Literally.
Literally. Yeah. I'm definitely very excited about the BCI technology that we have coming. One of the things I've learned is that the end state is often obvious. Ray Kurzweil was saying in the 1990s, “We would get here.” The end state can be inferred. The question is, how do you get there, and what kinds of investment will it take to make these technologies work? I definitely don't want to undersell the retinal prosthesis.
Let's talk about PRIMA for a second. If you were going to describe the state of the technology in humans—working and ready to sell—where does it stand?
I have to be very careful with what I say on that piece. It's not approved yet, but we're planning to submit for marketing approval in Europe in the next month. We're discussing with the FDA exactly what else they need to see, but we're hoping to have this on the market in the EU, definitely, and hopefully in the U.S. early next year.
Amazing. How big is that potential total market?
There are many billions of dollars a year in potential. There are very strong reimbursement precedents, at a couple hundred thousand dollars—probably around $200,000 per patient. In the U.S., the payer that matters here is Medicare because all these patients are over 65. In Europe, there are reimbursement precedents around $150,000 per patient.
There are tens of thousands of patients for whom this is directly relevant. The whole population is probably about 250,000. If you can reach even 2,000 or 3,000 patients a year, this is a half-a-billion-dollar business and a $3-billion-to-$4-billion opportunity.
I love it when an entrepreneur describes their on-base single as a billion-dollar opportunity. But when you look at AI, the companies that get to invest most sustainably are the profitable tech companies. Having to go back to the well every 18 months is a huge strategic disadvantage. There's been a ton of capital and enthusiasm flowing into BCI, but what this space really needs is a company making $100 million or more a year. Until that happens, there will always be a risk of winter. I think we're incredibly close to super-exciting breakthroughs, but they have to be supported by something that can fund them sustainably.
And you've acquired the manufacturing and built up the manufacturing capacity for this?
Yes. We've done 2 acquisitions, including one as a captive MEMS fab in North Carolina. Vertical integration is essential. I absolutely received the gospel of vertical integration from my former co-founder and prior boss.
We routinely void the warranty on million-dollar fab tools to place atoms exactly where we want them. Being able to do that, and also go from a design change to surgery in a couple of weeks, is absolutely enabling us to innovate.
Hold that in your mind: a company solving something of extraordinary difficulty, with the technology operational, regulatory approvals coming very shortly, and revenues following shortly thereafter. I think that's an extraordinary accomplishment on its own. Now let's move to the grand-slam home-run potential.
I remember when I was talking to Ray Kurzweil about his predictions. If you Google his predictions, he's got an 86% accuracy rate, if you look on Wikipedia. One of his predictions was high-bandwidth BCI by the early 2030s—like 2033. I said, “Ray, this one I don't see happening in that time frame. You're wrong about this one.” Then I met Max, and I thought, “Okay, Ray, you're right again.”
Max, just for a moment—I won't linger on it—but you were the co-founder and president of Neuralink. How long were you there?
About 4 and a half years.
I wouldn't say this—and he won't say this—but, you know, it's actually... I won't even say it. All right. You broke away and founded Science. You had a unique idea, which I think is extraordinary.
Yeah.
Describe the problem with all the current neural implants. You've got external BCI, which is looking at EEGs. You've got something under the skull, above the dura. Then you have wires placed in the upper parts of the neocortex, and you have deep-brain stimulation. Those are all different types, but let's talk about products like Neuralink and others. What's the challenge they have?
There are many different ways to try to record and drive the activity of neurons throughout the brain. Neuroscience as a field has been trying to do this for the last 100—almost 150—years. The first thing I want to say is that BCI is a field, not a product. There are many different products that will use many different modalities for different things.
There do seem to be very serious, fundamental physics limitations to the resolution and accuracy that you can get with purely noninvasive devices. Once you start thinking about putting something below the skull, the main approaches used today involve putting wires into the brain. The idea there is very simple: neurons communicate through electrical fields that they generate, and if you put an electrode in the brain, you can detect this.
There are other groups that are genetically modifying neurons in the brain to make them light-sensitive or make them emit light. There are also groups interested in using ultrasound. The problems with ultrasound and the optical methods of optogenetics are that they really require genetically modifying neurons throughout the brain.
And so doing this in an adult human is really pretty tricky. That seems like a nonstarter for many cases. You’re irreversibly modifying these neurons in the brain of adult humans using these viral vectors, and they don’t get perfectly distributed. Even then, there are still really severe limits to the depth that you can image or the resolution that you can get.
Now, the problem with placing wires into the brain, which allow you to get single neurons, is that we’re used to these cartoons of neurons floating in space, where you can place electrodes safely between them. But the reality is that there’s no space in the brain. The brain is this wet, warm, squished thing.
No matter how small or how flexible your device is, it might look like it’s a tiny fraction of a human hair floating off a finger. Every time you place one of these into the brain, you destroy thousands of cells. That blue line is your typical thickness of an electrode.
If you have a serious spinal cord injury, destroying 50,000 cells in the cortex to get 5 bits per second by recording from 500 neurons might be totally vindicated. But it does mean that you can’t scale up this approach to millions of cells, and that is really what you want in order to get these next-generation applications.
So I think about what an idealized neural interface is. I’ve been thinking about this question really since I was in 5th grade. Can I set a piece of context for folks?
I love that.
In terms of bits per second, in terms of baud rate, how would you describe the human brain interface for communication and speech? Let’s establish how fast our brain is actually inputting and outputting information.
There are 2 ways to answer this question. The figure of merit for any brain-computer interface is bandwidth, in bits per second. This is another way to look at the different approaches.
There are groups that are placing stents with electrodes into blood vessels. There’s something very elegant about getting into the brain through the body’s natural road system, but because of where that limits you and how far you are from the cells, those only get half a bit per second.
Penetrating cortical electrodes, like Neuralink, BrainGate, and others, have been able to get 5 to 7 bits per second. Spoken language is about 40 bits per second.
Okay. Just to hear that, right? Forty bits per second is when you and I are speaking. Neuralink is probably getting how much, you think?
I think what’s been published is about 7 bits per second.
7 bits per second.
Yeah. This is an interesting result, because if you take many different human languages, some are spoken more quickly and convey less information per token, while some are spoken more slowly and convey more information per token. But if you plot these, they all come out to about 40 bits per second.
There’s also a lot of neuroscience evidence that our attention processes the world at about 10 bits per second. The amount of information that you can perceive and remember is limited by this evolved cognitive bottleneck of about 10 bits per second.
When I think about high-bandwidth BCIs, I don’t think in terms of communicating faster. I don’t think you’re going to make it so you can simply convey thoughts more quickly. But it might be possible to get information into the brain. That’s very straightforward and very easy: You can see, you can hear, and you can feel.
These are much, much more than 40 bits per second, but you can’t get these signals out of the brain. For everything that you can perceive, you can imagine, but you can’t get imagery or audio out of the brain. That might be possible.
Or we can think about adding new cortical areas, in the sense that even if you’re still communicating at 40 bits per second in terms of the number of tokens, can you make those tokens much smarter? Can you have skills, knowledge, or memory that allow you to get a Chinese character versus a letter of something?
I just want you to get those numbers, because maybe you think you communicate in megabits or gigabits, like your computer does. We’re at 40 bits.
When I think about what the idealized brain-computer interface is—the one that would really solve a lot of these problems—the thing I think of, if you’ve seen the Avatar movies, is this big externalized cranial nerve.
All of the information that flows in or out of the brain goes through a relatively small number of wires. There are 12 cranial nerves. The optic nerve is nerve II. The vestibular nerve that carries hearing imbalance is nerve eight.
Then you’ve got 31 spinal nerves that connect out to the muscles.
Bringing back memories from medical school.
When we think about our retinal prosthesis, what we really see is a nerve II interface. But the question is: Could you grow a 13th cranial nerve that has interhemispheric bandwidth—the bandwidth that connects the 2 hemispheres through this fiber bundle called the corpus callosum? Could you have a branch of that come out and give you a USB cable at the end?
This was an idea that I had back in college, but it was really beyond the field’s collective ability to build at the time. The idea we had was: What if, instead of placing something into the brain, we load an electronic device with heavily engineered, stem-cell-derived neurons, embed them in a hydrogel so that the cells don’t go anywhere, and then engraft the wet side of this into the brain?
There’s no serious injury to the brain. You don’t place any electrical or mechanical parts. The only thing that penetrates into the brain is the biological processes of these graft cells. But at the far end, you get chemical synapses.
We can activate these cells optically to fire them selectively. They grow both axons and dendrites, so we can get input and output. We can record from them electrically. Optical stimulation and electrical recording allow us to avoid crosstalk.
We can drive all of them at once. This is a cool device, because you can easily make a 100,000-electrode device when you’re much closer to the cells. You can have much tighter electrode pitch, and you can load that with 1 million neurons. When that grows in, you’ll get 1 billion synapses throughout huge areas of the cortex.
Really critically important here: If you look at BrainGate and Neuralink, how many total electrodes are they placing?
BrainGate places 100. Neuralink, so far, has placed 1,000.
We’re talking about 100,000 or millions of these.
The other thing that’s beautiful is that these neural grafts—their axons and dendrites—when they grow into the brain, because they’re native to the brain, they’re not disrupting the tissue. They’re pushing it aside.
If you were to do this for real, you would see an image that looks like this. This is a mouse brain. You can see at the top there’s a bolus of cells where the device was removed for sectioning.
So this is what you did?
Yeah. This is functional in a mouse.
The graft cells that we’ve added are labeled in green. The host neurons of the mouse are in blue. If we look carefully, you can see all these little green dots really throughout it.
What we’ve seen is that when we engraft these devices, they grow in and wire up very promiscuously. They form connections everywhere. Then, after about 4 to 6 weeks, they start undergoing activity-dependent pruning.
The really interesting possibility there is that how they wire up is not necessarily genetically defined. It can be informationally defined based on the types of activity that you’re getting in the device.
In addition to growing down and wiring up through our cortex, the first layer on the surface of the brain, cortical layer 1, is a white matter tract. These are long projections, like a highway between different areas of the brain.
We often see in the devices that we’ll get a fiber bundle that follows that for millimeters. The mouse brain is very small, but we see these things project all the way through to subcortical structures.
Where these neurons and dendrites grow, they wire up and connect, and where they don’t, they die off.
Yeah, they’ll retract. I mean, the cells mostly don’t die, but they’ll retract the axon growth cones and the dendritic arbors.
So this is what we have. This is looking at one of the chips. There are cells loaded in these trenches.
Here, this is a Z-stack. Each frame starts at the surface and looks deeper and deeper into the brain. You can see the circles of the cell bodies on the surface. All of the green that we see is the graft neurons, but you can see the shadows of the blood vessels in these lighter layers.
This is super cool, because when you place an electrode into the brain, you always get bleeding. If you hit a descending blood vessel, you could stroke out a whole mini-column. Here, these grow in around the blood vessels. The capillaries remodel around them.
And so this is a really perfectly biocompatible way to get chemical synapses. We see these things even where it looks like they’ve fallen off. You see the processes of these cells growing in.
The theme of this event, this year’s summit, is convergence. What technologies had to converge here to make this possible?
A lot of this was enabled by recent advances in cell engineering. One of the things that we have to do is hide the graft cells from the immune system. We do a lot of editing to these cells. If we were to do this on a per-patient basis, because the immune system would have to recognize them, this would take over a year and be prohibitively expensive.
There’s been a lot of advancement recently in making what we call hypoimmunogenic stem cells. The whole CRISPR toolbox and a lot of other technologies now include things like small-molecule-triggered kill switches. We can make it so that if you take a vitamin, the graft cells will die. We can keep an eye on them. Once you’ve hidden them from the immune system, you kind of want that built in.
When these go to humans, these will be by far the most heavily edited cell therapy to reach people.
And materials science?
Yeah, it’s materials like silicon carbide. There have been big improvements in the materials. We talk in the BCI field about the smartphone dividend. We rely heavily on the same tech stack that smartphones and wearables build on, but Apple, Samsung, and others have poured over $100 billion into that. Our field is too small to afford that today, but we get to build on it, and that has really enabled us and advanced a lot in the last few years.
All right. Talk to me about where and when this enters primates and potentially humans. When can I get mine?
We currently have some primates getting trained up on behavior.
So you’re training them in advance?
We’re training them in advance. We also need to figure out things like how well they can reason, which actually hasn’t been studied that well. We’re hoping to do the first primate engraftments in a couple of months.
I mean, which is amazing, right?
Once you’re operational in primates, other than regulatory prohibitions, you’re effectively functional. We’ll be able to prove the neuroscience—that is, the big questions for humans and primates. The first humans to get this will almost certainly be for stroke.
If you’d asked me this 3 weeks ago, I would have said I thought it would be 4 or 5 years before the first human got it. I actually think this is now going to be much faster. There might be a collaboration that allows us to go to humans a lot faster than I’d realized. Again, that’ll almost certainly be for stroke.
The primates are actually a pretty good model of human stroke patients, because a human who’s lost a cortical area can be modeled by a monkey that never had it in the first place. If you can restore that capability, then there’s an argument that you’ll be able to do it in humans.
The other thing I’ll say is, beyond stroke rehabilitation or re-adding these capabilities to humans, when we think about scaling this up, I see this as a way to redraw the borders around the brain. Your head has 2 hemispheres. These are connected by a fiber bundle called the corpus callosum that gives you the experience of 1 agent in the head. But really, you’ve got 2 subbrains that are mostly independent.
A long time ago, people used to cut the corpus callosum in epilepsy patients to prevent a seizure from spreading across the hemispheres. If you cut that, you really get something that looks like 2 agents in 1 head. There’s a natural example of going the other way: There’s a pair of twins in Canada, the Hogan twins, who have 1 head with 4 hemispheres, and they can share meaningful elements of their consciousness. There’s an element of task transfer between them.
I think a way to conceptualize this is to imagine if this was a tech product. That might be coming a lot sooner. We know this must be possible because nature has done it, and I’m hoping to have this in humans, hopefully, pretty soon.
Max, I want to dive a little further into what this will mean. So this becomes enabled—other than me being able to think in Google or watch a 4K video with my eyes closed—what does this actually mean in terms of increasing intelligence and connecting to AI? What is a possible future here?
For a lot of my life, I always felt like I could see the future, and I’ve got this event horizon somewhere between 2030 and 2035 now. It’s just impossible to see past. AGI and ASI are definitely happening, and I think that this is—I mean, everybody knows about it now, but there’s basically no way to overrate the impact of that.
Is this the merge, the only way through? I don’t know. That was a conversation we had last year: Do we need to couple?
But if we do merge, you’ve talked about the idea of pretraining, in some ways, these biohybrids. Can you speak to that a little bit?
I think neural interconnects, like brain-to-brain connections, are a really interesting technology for merging with AI. I think transformers are a pretty good explanation for cortex, but to get real agency in a way that is interesting or dangerous, you need something else to add on to that.
People have these loops that are prompted, but that is still coming from the human. It might be that the agency remains with the humans, but these technologies are so powerful and adaptive that people who participate in this have a huge advantage. This is something that societies need to think about.
I also see it as a longevity technology. How do you let someone into your head? That’s a tricky question. I think the first use case for this would probably be things like long-married couples where one has a terminal disease for the last year. You can get a brain-to-brain connection. So rather than merging with AI, it’s merging with your spouse or a close family member.
Talk about a level of intimacy.
Yeah. Can you turn the death experience into basically a stroke that you recover from? Throughout your life, small groups of neurons are constantly dying. There’s a smaller number being generated, but this is turning over.
All communication is about creating correlations between brains. Long relationships already store memories in each other’s brains. Is there a threshold where you can get phenomenal binding across the interface, where you really get 1 agent, and then when you lose some group of neurons, you still get continuity of consciousness and continuity of experience through that transition?
I see that as an alternative path to biological longevity companies, but it feels a lot more like an engineering problem to me. I think it will be possible on the timescale of the next decade. In that view, you can merge with other people, merge with AI, or have these superorganisms that are composites of big groups.
Yeah, I call them a metaintelligence. When we’re able to connect millions of people’s thoughts and feelings at a level of intimacy and connection, I mean, you are a collection of 40 trillion cells that you don’t think of yourself as 40 trillion cells. You think of yourself as you. Imagine if millions or billions are connected through the cloud together, and you become conscious on yet another level.
The really interesting question here, where we’re still missing some physics, is what is the point where you go from having 2 conscious experiences into a single experience, or do you keep multiple attentional windows? I’m increasingly confident we’re going to get this in the next 5 years.
This is tough to talk about without sounding like a lunatic. All I know is that these devices are technically capable of being built, and I have no idea what it will feel like, but we’re going to find out.