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【e/acc】外星智能、卡尔达肖夫天梯、技术资本机器 | 物理学家、e/acc运动创始人Guillaume Verdon与Lex Fridman播客实录 | 中英文完整版精译 Part3
书童按：本篇是Guillaume Verdon接受Lex Fridman播客采访实录的第三部分。在前两篇奠定理论根基之后，本篇探入更具思辨性的议题：外星智能的可能性与意义、量子引力的优美图景、黑洞信息悖论的最新进展、卡尔达舍夫等级的文明愿景，以及e/acc运动的核心纲领与文化基因。Verdon纵论从热力学驱动的生命起源到跨星际文明扩张的宏大叙事，批判去增长主义（degrowth）与ESG路径，主张以技术创新而非管理手段应对文明挑战。访谈亦涉及Jeff Bezos与Elon Musk等企业家的资本配置智慧、模因文化的传播策略、Extropic公司的热力学计算机愿景等话题。理论深度与实践洞察并重，视野恢宏，启人深思。初稿采用Claude Code机器翻译及排版，书童仅做简单校对及批注，以飨诸君。
外星人 Aliens Lex Fridman (01:35:11) 精度会随着你能力的降低而下降，但还是可以的。不过既然你提到了UAP（书童注：Unidentified Aerial Phenomena，不明空中现象），我们谈到了智能，我忘了问：你对可能存在于介观尺度上的其他智能有什么看法？你认为存在其他智能外星文明吗？思考这个问题有用吗？你多久想一次这个问题？
LEX FRIDMAN (01:35:11) The precision decreases in terms of your ability, but still. But since you mentioned UAPs, we talked about intelligence, and I forgot to ask, what’s your view on the other possible intelligences that are out there at the Meso scale? Do you think there’s other intelligent alien civilizations? Is that useful to think about? How often do you think about it?
Guillaume Verdon (01:35:36) 我认为思考这个问题是有用的。之所以有用，是因为我们必须确保自己具有反脆弱性，并且正在尽可能快地提升我们的能力。因为我们可能被颠覆。物理定律并不禁止别处存在生命，那些生命可能进化并成为先进文明，最终来到我们这里。我认为他们现在就在这里吗？我不确定。关于这个话题，我读过的东西和大多数人读过的差不多。
GUILLAUME VERDON (01:35:36) I think it’s useful to think about. It’s useful to think about because we got to ensure we’re anti-fragile, and we’re trying to increase our capabilities as fast as possible. Because we could get disrupted. There’s no laws of physics against there being life elsewhere that could evolve and become an advanced civilization and eventually come to us. Do I think they’re here now? I’m not sure. I’ve read what most people have read on the topic.
Guillaume Verdon (01:36:14) 我认为值得考虑，对我来说，这是一个有用的思想实验，用来灌输一种紧迫感——发展技术、提升我们的能力，确保我们不被颠覆。无论是某种形式的AI颠覆我们，还是来自不同星球的外来智能。无论哪种方式，提升我们的能力、让人类变得强大，我认为这非常重要，这样我们才能对宇宙向我们抛来的任何东西都保持鲁棒性。
GUILLAUME VERDON (01:36:14) I think it’s interesting to consider and to me, it’s a useful thought experiment to instill a sense of urgency in developing technologies and increasing our capabilities, to make sure we don’t get disrupted. Whether it’s a form of AI that disrupts us, or a foreign intelligence from a different planet. Either way, increasing our capabilities and becoming formidable as humans, I think that’s really important, so that we’re robust against whatever the universe throws at us.
Lex Fridman (01:36:51) 但对我来说，这也是一个有趣的挑战和思想实验——如何感知智能。这与量子力学系统有关，也与任何不像人类的系统有关。对我来说，思想实验是：假设外星人就在这里，或者他们是可以直接观察到的。只是我们太盲目、太以自我为中心、没有合适的传感器，或者没有对传感器数据进行正确的处理，因而看不到我们周围显而易见的智能。
LEX FRIDMAN (01:36:51) But to me, it’s also an interesting challenge and thought experiment on how to perceive intelligence. This has to do with quantum mechanical systems. This has to do with any kind of system that’s not like humans. To me, the thought experiment is, say, the aliens are here or they are directly observable. We’re just too blind, too self-centered, don’t have the right sensors, or don’t have the right processing of the sensor data to see the obvious intelligence that’s all around us.
Guillaume Verdon (01:37:26) 嗯，这就是我们为什么要研究量子传感器。它们可以感知引力。
GUILLAUME VERDON (01:37:26) Well, that’s why we work on quantum sensors. They can sense gravity,
Lex Fridman (01:37:31) 是的。这很好，但可能还有其他东西，甚至不在当前已知的物理力量之中。
LEX FRIDMAN (01:37:31) Yeah. That’s a good one, but there could be other stuff that’s not even in the currently known forces of physics.
Guillaume Verdon (01:37:43) 对。
GUILLAUME VERDON (01:37:43) Right.
Lex Fridman (01:37:43) 可能有其他的东西。对我来说最有趣的思想实验是，那是显而易见的其他东西。不是我们缺乏传感器。它就在我们周围，意识可能就是其中之一。但可能有些东西就是明显地在那里。一旦你知道了它，就会说：”哦，对了。对了。我们认为以某种方式从物理定律中涌现出来的东西，我们理解它们，实际上是宇宙的基本组成部分，可以被纳入物理学。最被理解的。”
LEX FRIDMAN (01:37:43) There could be some other stuff. The most entertaining thought experiment to me is that it’s other stuff that’s obvious. It’s not like we lack the sensors. It’s all around us, the consciousness being one possible one. But there could be stuff that’s just obviously there. That once you know it, it’s like, “Oh, right. Right. The thing we thought is somehow emergent from the laws of physics, we understand them, is actually a fundamental part of the universe and can be incorporated in physics. Most understood.”
Guillaume Verdon (01:38:18) 从统计学上讲，如果我们观察到某种外星生命，它最有可能是某种病毒式的、自我复制的、类似冯·诺依曼探测器的系统。而且有可能存在这样的系统，我不知道它们在海底做什么——据说是这样——但也许它们在从海底收集矿物。
GUILLAUME VERDON (01:38:18) Statistically speaking, if we observed some sort of alien life, it would most likely be some sort of virally, self-replicating, von Neumann-like probe system. And it’s possible that there are such systems that, I don’t know what they’re doing at the bottom of the ocean, allegedly, but maybe they’re collecting minerals from the bottom of the ocean.
Lex Fridman (01:38:44) 是的。
LEX FRIDMAN (01:38:44) Yeah.
Guillaume Verdon (01:38:45) 但这不会违反我的任何先验假设。但我确定这些系统在这里吗？我很难这么说。我只有关于存在数据的二手信息。
GUILLAUME VERDON (01:38:45) But that wouldn’t violate any of my priors. But am I certain that these systems are here? It’d be difficult for me to say so. I only have secondhand information about there being data.
Lex Fridman (01:38:59) 关于海底的？是的。但它可能是像模因这样的东西吗？可能是思想和观念吗？它们可能在那个媒介中运作吗？外星人可能就是进入我脑海的那些想法吗？想法的起源是什么？在你的脑海中，当一个想法进入你的脑海时，告诉我它从哪里来。
LEX FRIDMAN (01:38:59) About the bottom of the ocean? Yeah. But could it be things like memes? Could it be thoughts and ideas? Could they be operating at that medium? Could aliens be the very thoughts that come into my head? What’s the origin of ideas? In your mind, when an idea comes to your head, show me where it originates.
Guillaume Verdon (01:39:25) 坦率地说，当我想到我现在正在建造的那种计算机的想法时——我想那是八年前了——感觉真的像是从太空中传来的光束。我躺在床上，浑身颤抖，只是在思考它。我不知道。但我真的相信这个吗？我不这么认为。但我认为外星生命可以采取多种形式，我认为智能的概念和生命的概念需要更广泛地扩展，变得不那么以人类为中心或以生物为中心。
GUILLAUME VERDON (01:39:25) Frankly, when I had the idea for the type of computer I’m building now, I think it was eight years ago now, it really felt like it was being beamed from space. I was in bed, just shaking, just thinking it through. I don’t know. But do I believe that legitimately? I don’t think so. But I think that alien life could take many forms, and I think the notion of intelligence and the notion of life needs to be expanded much more broadly to be less anthropocentric or biocentric.
量子引力 Quantum gravity Lex Fridman (01:40:04) 在量子力学上再停留一会儿，通过你在量子计算上的所有探索，你遇到过的最酷、最美丽的想法是什么——已经解决的或尚未解决的？
LEX FRIDMAN (01:40:04) Just to linger a little longer on quantum mechanics, through all your explorations on quantum computing, what’s the coolest, most beautiful idea that you’ve come across that has been solved or has not yet been solved?
Guillaume Verdon (01:40:19) 我认为是理解一种叫做AdS/CFT的东西的旅程。也就是通过这样一幅图景来理解量子引力：一个维度较低的全息图实际上与一个额外维度的量子引力的体理论对偶或完全对应，而这种对偶性来自于试图学习边界的类似深度学习的表示。
GUILLAUME VERDON (01:40:19) I think the journey to understand something called AdS/CFT. So, the journey to understand quantum gravity through this picture, where a hologram of lesser dimension is actually dual or exactly corresponding to a bulk theory of quantum gravity of an extra dimension, and the fact that this sort of duality comes from trying to learn deep learning-like representations of the boundary.
Guillaume Verdon (01:40:59) 至少，我的旅程中有一部分——有一天在我的愿望清单上——是将量子机器学习应用于这类系统，这些CFT（书童注：Conformal Field Theory，共形场论），或者它们被称为SYK模型（书童注：Sachdev-Ye-Kitaev模型），并从边界理论学习一个涌现的几何。所以，我们可以有一种形式的机器学习来帮助我们理解量子引力，这仍然是一个圣杯，我希望在离开这个世界之前达到。
GUILLAUME VERDON (01:40:59) At least, part of my journey someday on my bucket list is to apply quantum machine learning to these sorts of systems, these CFTs, or they’re called SYK models, and learn an emergent geometry from the boundary theory. And so, we can have a form of machine learning to help us understand quantum gravity, which is still a holy grail that I would like to hit before I leave this earth.
Lex Fridman (01:41:35) 你认为黑洞正在发生什么？作为信息存储和处理单元，你认为黑洞正在发生什么？
LEX FRIDMAN (01:41:35) What do you think is going on with black holes? As information-storing and processing units, what do you think is going on with black holes?
Guillaume Verdon (01:41:46) 黑洞是非常迷人的物体。它们处于量子力学和引力的界面上，所以它们帮助我们测试各种想法。我认为几十年来，一直存在这个黑洞信息悖论——落入黑洞的东西，我们似乎失去了它们的信息。现在，我认为有这个火墙悖论，据称在近年来被我的一位前同行解决了，他现在是伯克利的教授。在那里，似乎当信息落入黑洞时，有一种沉积作用。当你从外部观察者的角度越来越接近视界时，物体会无限减速。
GUILLAUME VERDON (01:41:46) Black holes are really fascinating objects. They’re at the interphase between quantum mechanics and gravity, and so they help us test all sorts of ideas. I think that for many decades now, there’s been this black hole information paradox that things that fall into the black hole, we’ve seem to have lost their information. Now, I think there’s this firewall paradox that has been allegedly resolved in recent years by a former peer of mine, who’s now a professor at Berkeley. There, it seems like, as information falls into a black hole, there’s a sedimentation. As you get closer and closer to the horizon from the point of view, the observer on the outside, the object slows down infinitely as it gets closer and closer.
Guillaume Verdon (01:42:46) 从我们的角度来看，所有落入黑洞的东西都会沉积并附着在近视界处。在某个时刻，它离视界如此之近，以至于处于量子效应和量子涨落重要的邻近或尺度上。在那里，下落的物质可能会干扰传统图景，它可能会干扰真空中粒子和反粒子的产生和湮灭。通过这种干涉，其中一个粒子与下落的信息纠缠在一起，其中一个自由并逃逸。这就是外出辐射和下落物质之间存在互信息的方式。但正确计算这个，我认为我们才刚刚开始把碎片拼在一起。
GUILLAUME VERDON (01:42:46) Everything that is falling to a black hole, from our perspective, gets sedimented and tacked on to the near horizon. At some point, it gets so close to the horizon, it’s in the proximity or the scale in which quantum effects and quantum fluctuations matter. There, that infalling matter could interfere with the traditional pictures, that it could interfere with the creation and annihilation of particles and antiparticles in the vacuum. Through this interference, one of the particles gets entangled with the infalling information and one of them is now free and escapes. That’s how there’s mutual information between the outgoing radiation and the infalling matter. But getting that calculation right, I think we’re only just starting to put the pieces together.
Lex Fridman (01:43:43) 有几个像”瘾君子”一样的问题我想问你。
LEX FRIDMAN (01:43:43) There’s a few pothead-like questions I want to ask you.
Guillaume Verdon (01:43:46) 当然。
GUILLAUME VERDON (01:43:46) Sure.
Lex Fridman (01:43:46) 一个是，我们银河系中心有一个巨大的黑洞，这让你感到恐惧吗？
LEX FRIDMAN (01:43:46) One, does it terrify you that there’s a giant black hole at the center of our galaxy?
Guillaume Verdon (01:43:52) 我不知道。我只是想在它附近建立基地，以便快进，遇见未来的文明——如果我们的寿命有限，如果你可以去绕黑洞轨道运行然后出现。
GUILLAUME VERDON (01:43:52) I don’t know. I just want to set up shop near it to fast-forward, meet a future civilization, if we have a limited lifetime, if you could go orbit a black hole and emerge.
Lex Fridman (01:44:08) 如果有一项特殊任务可以带你去黑洞，你会自愿去旅行吗？
LEX FRIDMAN (01:44:08) If there’s a special mission that could take you to a black hole, would you volunteer to go travel?
Guillaume Verdon (01:44:13) 去轨道运行，显然不是掉进去。
GUILLAUME VERDON (01:44:13) To orbit and obviously not fall into it.
Lex Fridman (01:44:15) 这是显而易见的。你显然认为黑洞里面的一切都被摧毁了？构成Guillaume的所有信息都被摧毁了？也许在另一边，Beff Jezos出现了，而且就像它以某种深刻的模因方式联系在一起。
LEX FRIDMAN (01:44:15) That’s obvious. It’s obvious to you that everything’s destroyed inside a black hole? All the information that makes up Guillaume is destroyed? Maybe on the other side, Beff Jezos emerges and it’s just all like it’s tied together in some deeply memeful way.
Guillaume Verdon (01:44:32) 是的，这是一个很好的问题。我们必须回答黑洞是什么。我们是在时空中打一个洞并创造一个口袋宇宙吗？这是可能的。那么，这意味着如果我们攀登卡尔达肖夫等级到III型以上，我们可以设计具有特定超参数的黑洞，将信息传输到我们创造的新宇宙。所以，我们可以有后代——
GUILLAUME VERDON (01:44:32) Yeah, that’s a great question. We have to answer what black holes are. Are we punching a hole through space-time and creating a pocket universe? It’s possible. Then, that would mean that if we ascend the Kardashev scale to beyond Kardashev Type III, we could engineer black holes with specific hyperparameters to transmit information to new universes we create. And so, we can have progeny that our new…
Guillaume Verdon (01:45:00) ……拥有作为新宇宙的后代。所以即使我们的宇宙可能达到热寂，我们也可能有一种留下遗产的方式。所以我们还不知道。我们需要攀登卡尔达舍夫等级来回答这些问题，窥视更高能量物理的那个领域。
GUILLAUME VERDON (01:45:00) … have progeny that are new universes. And so even though our universe may reach a heat death, we may have a way to have a legacy. And so we don’t know yet. We need to ascend the Kardashev Scale to answer these questions to peer into that regime of higher energy physics.
卡尔达舍夫等级 Kardashev scale Lex Fridman (01:45:25) 也许你可以向不知道的人介绍一下卡尔达舍夫等级。所以e/acc运动的一个类似模因的原则和目标就是攀登卡尔达舍夫等级。什么是卡尔达舍夫等级，我们什么时候想要攀登它？
LEX FRIDMAN (01:45:25) And maybe you can speak to the Kardashev Scale for people who don’t know. So one of the sort of meme-like principles and goals of the e/acc movement is to ascend the Kardashev Scale. What is the Kardashev Scale and when do we want to ascend it?
Guillaume Verdon (01:45:43) 卡尔达舍夫等级是对我们能源生产和消耗的一种度量。实际上，它是一个对数尺度。卡尔达舍夫I型是一个里程碑，我们生产的瓦特数相当于太阳照射到地球上的所有能量。卡尔达舍夫II型将是利用太阳输出的所有能量。我想III型就像整个银河系的等价——
GUILLAUME VERDON (01:45:43) The Kardashev Scale is a measure of our energy production and consumption. Really, it’s a logarithmic scale. Kardashev Type 1 is a milestone where we are producing the equivalent wattage to all the energy that is incident on earth from the sun. Kardashev Type II would be harnessing all the energy that is output by the sun. And I think Type III is like the whole galaxy equivalent-
Lex Fridman (01:46:13) 银河系，我想[听不清]是的。
LEX FRIDMAN (01:46:13) Galaxy, I think [inaudible 01:46:14] yeah.
Guillaume Verdon (01:46:15) 是的，然后有些人有一些疯狂的IV型和V型，但我不知道我是否相信那些。但对我来说，从热力学的第一原理来看，似乎又有这个概念——热力学驱动的耗散适应——生命在地球上进化，因为我们有来自太阳的这种能量驱动，我们有入射能量，生命在地球上进化以找出最佳捕获那种自由能以维持自身和增长的方法。我认为这个原则，它不是我们地球-太阳系统所特有的。我们可以将生命扩展到远远超出。我们有责任这样做，因为正是这个过程把我们带到了这里。所以我们甚至不知道它为我们储存了什么。它可能是我们今天甚至无法想象的美丽的东西。
GUILLAUME VERDON (01:46:15) Yeah, and then some people have some crazy Type IV and V, but I don’t know if I believe in those. But to me, it seems like from the first principles of thermodynamics that, again, there’s this concept of thermodynamic- driven dissipative adaptation where life evolved on earth because we have this energetic drive from the sun, we have incident energy, and life evolved on earth to figure out ways to best capture that free energy to maintain itself and grow. And I think that that principle, it’s not special to our earth-sun system. We can extend life well beyond. And we kind of have a responsibility to do so because that’s the process that brought us here. So we don’t even know what it has its store for us in the future. It could be something of beauty we can’t even imagine today.
有效加速主义（e/acc） Effective accelerationism (e/acc) Lex Fridman (01:47:18) 所以这可能是一个谈论e/acc运动的好地方。在一篇题为《What the F* is e/acc?》（《e/acc到底是什么鬼？》）的Substack博客文章中，你写道：”从战略上讲，我们需要努力实现几个相互依存的总体文明目标。这四个目标是：增加我们作为一个物种可以利用的能量（攀登卡尔达舍夫梯度）。短期内，这几乎肯定意味着核裂变。通过支持人口增长的政策和支持经济增长的政策来增加人类繁荣。创造通用人工智能，人类历史上最伟大的力量倍增器。最后，发展行星际和星际运输，以便人类可以扩展到地球之外。“你能在此基础上进一步说明，也许说一下，对你来说e/acc运动是什么？目标是什么？原则是什么？
LEX FRIDMAN (01:47:18) So this is probably a good place to talk a bit about the e/acc movement in a Substack blog post titled, What the Fuck is e/acc? Or actually, What the F* is e/acc?, you write, “Strategically speaking, we need to work towards several overarching civilization goals that are all interdependent. And the four goals are, increase the amount of energy we can harness as a species, (climb the Kardashev gradient). In the short term, this almost certainly means nuclear fission. Increase human flourishing via pro-population growth policies and pro-economic growth policies. Create artificial general intelligence, the single greatest force multiplier in human history. And finally, develop interplanetary and interstellar transport so that humanity can spread beyond the earth. Could you build on top of that to maybe say, what to you is the e/acc movement? What are the goals? What are the principles?
Guillaume Verdon (01:48:20) 目标是让人类技术-资本-模因机器变得（拥有）自我意识，并以超迷信的方式设计自己的增长。让我们拆解一下。
GUILLAUME VERDON (01:48:20) The goal is for the human techno-capital memetic machine to become self-aware and to hyperstitiously engineer its own growth. So let’s decompress that.
Lex Fridman (01:48:33) 定义其中的每一个词。
LEX FRIDMAN (01:48:33) Define each of those words.
Guillaume Verdon (01:48:35) 所以你有人类，你有技术，你有资本，然后你有模因、信息，所有这些系统都相互耦合。人类在公司工作，他们获取和分配资本，人类通过模因和信息传播进行交流。我们的目标是拥有一种病毒式的乐观主义运动，它意识到系统是如何运作的——从根本上说，它寻求增长——我们只是想顺应系统为自己的增长而适应的自然倾向。
GUILLAUME VERDON (01:48:35) So you have humans, you have technology, you have capital, and then you have memes, information, and all of those systems are coupled with one another. Humans work at companies, they acquire and allocate capital, and humans communicate via memes and information propagation. And our goal was to have a sort of viral optimistic movement that is aware of how the system works, fundamentally it seeks to grow, and we simply want to lean into the natural tendencies of the system to adapt for its own growth.
Lex Fridman (01:49:18) 所以从这个意义上说，你是对的，e/acc字面上是一种模因式乐观主义病毒，它不断漂移、变异并以去中心化的方式传播。所以模因式乐观主义病毒。所以你确实希望它成为一种病毒以最大化传播，而且它具有超迷信性，因此乐观主义将激励其增长。
LEX FRIDMAN (01:49:18) So in that way, you’re right, the e/acc is literally a memetic optimism virus that is constantly drifting, mutating, and propagating in a decentralized fashion. So memetic optimism virus. So you do want it to be a virus to maximize the spread, and it’s hyperstitious, therefore the optimism will incentivize its growth.
Guillaume Verdon (01:49:43) 我们将e/acc视为一种元启发式，一种非常薄的文化框架，从中你可以有更多有主见的分支。从根本上说，我们只是说，把我们带到这里的是基于热力学的整个系统的这种适应，这个过程是好的，我们应该让它继续下去。这就是核心论点。其他一切都是，好吧，我们如何确保我们保持这种可塑性和适应性。嗯，显然不要压制变异，保持言论自由、思想自由、信息传播自由和进行AI研究的自由对我们来说很重要，以便我们能够最快地收敛到导致这种增长的技术、想法等空间。所以最终，已经有相当多的分支。有些只是模因，但有些更严肃。Vitalik Buterin最近创建了一个d/acc分支。他有他自己对e/acc的某种微调。
GUILLAUME VERDON (01:49:43) We see e/acc as sort of a meta-heuristic, sort of very thin cultural framework from which you can have much more opinionated forks. Fundamentally, we just say that what got us here is this adaptation of the whole system based on thermodynamics, and that process is good and we should keep it going. That is the core thesis. Everything else is, okay, how do we ensure that we maintain this malleability and adaptability. Well, clearly not suppressing variants, and maintaining free speech, freedom of thought, freedom of information propagation, and freedom to do AI research is important for us to converge the fastest on the space of technologies, ideas, and whatnot that lead to this growth. And so ultimately, there’s been quite a few forks. Some are just memes, but some are more serious. Vitalik Buterin recently made a d/acc fork. He has his own sort of fine-tunings of e/acc.
Lex Fridman (01:50:59) Vitalik的那个分支有什么独特特征让你印象深刻吗？
LEX FRIDMAN (01:50:59) Does anything jump out to memory of the unique characteristic of that fork from Vitalik?
Guillaume Verdon (01:51:05) 我会说它试图在e/acc和EA（书童注：Effective Altruism，有效利他主义）以及AI安全之间找到一个中间地带。对我来说，拥有一个与接管硅谷的主流叙事相反的运动，对于改变意见的动态范围很重要。这就像中心化和去中心化之间的平衡，真正的最优点总是在中间的某个地方。但对于e/acc，我们推动熵、新颖性、颠覆、可塑性、速度，而不是保守、压制思想、压制言论、增加约束、增加过多法规、放慢速度。所以，我们试图为力量带来平衡。
GUILLAUME VERDON (01:51:05) I would say that it’s trying to find a middle ground between e/acc and EA and EI safety. To me, having a movement that is opposite to what was the mainstream narrative that was taking over Silicon Valley was important to shift the dynamic range of opinions. And it’s like the balance between centralization and decentralization, the real optimum is always somewhere in the middle. But for e/acc, we’re pushing for entropy, novelty, disruption, malleability, speed, rather than being conservative, suppressing thought, suppressing speech, adding constraints, adding too many regulations, slowing things down. And so, we’re trying to bring balance to the force.
Lex Fridman (01:52:00) 为人类文明的力量带来平衡。
LEX FRIDMAN (01:52:00) Balance to the force of human civilization.
Guillaume Verdon (01:52:02) 这字面上是约束的力量与让我们探索的熵之间的张力。系统在处于秩序与混沌之间的临界边缘时是最优的，在约束、能量最小化和熵之间。系统想要平衡这两样东西。我认为平衡是缺失的，所以我们创建了这个运动来带来平衡。
GUILLAUME VERDON (01:52:02) It’s literally the forces of constraints versus the entropic force that makes us explore. Systems are optimal when they’re at the edge of criticality between order and chaos, between constraints, energy minimization and entropy. Systems want to equilibrate, balance these two things. I thought that the balance was lacking, and so we created this movement to bring balance.
Lex Fridman (01:52:31) 嗯，我喜欢想法通过分支进化的视觉效果。所以在历史的另一部分，把马克思主义看作原始仓库，然后苏联共产主义是其中一个分支，然后_主义是马克思主义和共产主义的一个分支。所以这些都是分支。它们在探索不同的想法。
LEX FRIDMAN (01:52:31) Well, I like the visual of the landscape of ideas evolving through forks. So on the other part of history, thinking of Marxism as the original repository, and then Soviet Communism is a fork of that, and then the M__ism is a fork of Marxism and Communism. And so those are all forks. They’re exploring different ideas.
Guillaume Verdon (01:53:02) 把文化几乎看作代码。现在，你在LLM中提示什么或你在LLM的宪法中放入什么，基本上就是它的文化框架，它相信什么。你现在可以在GitHub上分享它。所以试图从在软件的这台机器中起作用的东西中获得灵感，以适应代码空间，我们能否将其应用于文化？我们的目标不是说”你应该这样生活，X、Y、Z”，而是建立一个过程，让人们总是在亚文化中搜索并竞争思想份额。我认为创造这种文化的可塑性对我们收敛到适应现代的文化和关于如何生活的启发式方法非常重要。
GUILLAUME VERDON (01:53:02) Thinking of culture almost like code. Nowadays, what you prompt in the LLM or what you put in the constitution of an LLM is basically its cultural framework, what it believes. And you can share it on GitHub nowadays. So trying to take inspiration from what has worked in this machine of software to adapt over the space of code, could we apply that to culture? And our goal is to not say, “You should live your life this way, X, Y, Z,” it’s to set up a process where people are always searching over subcultures and competing for mind share. I think creating this malleability of culture is super important for us to converge onto the cultures and the heuristics about how to live one’s life that are updated to modern times.
Guillaume Verdon (01:53:59) 因为真的存在一种精神性和文化的真空。人们觉得他们不属于任何一个群体，而且有一些寄生性的意识形态已经利用机会填充这个思想的培养皿。Elon称之为思想病毒。我们称之为减速思想病毒综合体，这是所有这些之间的总体模式的减速。也有许多变种。所以如果有一种病毒式的悲观主义、减速运动，我们需要的不仅仅是一个运动，而是许多许多变种，所以很难精确定位和停止。
GUILLAUME VERDON (01:53:59) Because there’s really been a sort of vacuum of spirituality and culture. People don’t feel like they belong to any one group, and there’s been parasitic ideologies that have taken up opportunity to populate this Petri dish of minds. Elon calls it the mind virus. We call it the decel mind virus complex, which is the decelerative that is kind of the overall pattern between all of them. There’s many variants as well. And so if there’s a sort of viral pessimism, decelerative movement, we needed to have not only one movement, but many, many variants, so it’s very hard to pinpoint and stop.
Lex Fridman (01:54:45) 但总体来说，它仍然是一种模因式乐观主义大流行。好吧，让我问你，你认为e/acc在某种程度上是一个邪教吗？
LEX FRIDMAN (01:54:45) But the overarching thing is nevertheless a kind of mimetic optimism pandemic. Okay, let me ask you, do you think e/acc to some degree is a cult?
Guillaume Verdon (01:55:01) 定义邪教？
GUILLAUME VERDON (01:55:01) Define cult?
Lex Fridman (01:55:03) 我认为很多人类进步是在你有独立思考时取得的，所以你有能够自由思考的个体。而非常强大的模因系统可能会导致群体思维。人性中有一些东西会导致大规模催眠、大规模歇斯底里。每当有一个性感的想法抓住我们的思想时，我们就开始思考相似。所以实际上很难把我们分开，拉开我们，多样化思想。所以在这种程度上，每个人都在像《动物农场》里的羊一样高呼”E/acc, e/acc”到什么程度？
LEX FRIDMAN (01:55:03) I think a lot of human progress is made when you have independent thought, so you have individuals that are able to think freely. And very powerful mimetic systems can kind of lead to group think. There’s something in human nature that leads to mass hypnosis, mass hysteria. We start to think alike whenever there’s a sexy idea that captures our minds. And so it’s actually hard to break us apart, pull us apart, diversify a thought. So to that degree, to which degree is everybody kind of chanting “E/acc, e/acc” like the sheep in Animal Farm?
Guillaume Verdon (01:55:46) 嗯，首先，这很有趣。这是反叛的。有这个元讽刺的概念，处于”我们不确定他们是否认真”的边界上。而且它更有趣和更好玩得多。例如，我们谈论热力学是我们的上帝，有时我们做类似邪教的事情，但没有仪式和长袍之类的。
GUILLAUME VERDON (01:55:46) Well, first of all, it’s fun. It’s rebellious. There’s this concept of meta-irony, of being on the boundary of, “We’re not sure if they’re serious or not.” And it’s much more playful and much more fun. For example, we talk about thermodynamics being our god, and sometimes we do cult-like things, but there’s no ceremony and robes and whatnot.
Lex Fridman (01:56:19) 还没有。
LEX FRIDMAN (01:56:19) Not yet.
Guillaume Verdon (01:56:19) 还没有，没有。但最终，是的，我完全同意，人类似乎想要感觉他们是一个群体的一部分，所以他们自然地试图与邻居达成一致并找到共同点。(书童注：参考存在主义四大终极关怀之存在性孤独)这导致了想法空间中的某种模式崩溃。我们曾经有一个被允许的文化岛屿。这是一个典型的思想子空间，任何偏离那个思想子空间的东西都被压制，或者你被取消了。现在我们创造了一个新模式，但关键是我们不是试图有一个非常受限的思想空间。关于e/acc及其许多分支，不只有一种思考方式。关键是有许多分支，可以有许多集群和许多岛屿。
GUILLAUME VERDON (01:56:19) Not yet, no. But ultimately, yeah, I totally agree that it seems to me that humans want to feel like they’re part of a group, so they naturally try to agree with their neighbors and find common ground. And that leads to sort of mode collapse in the space of ideas. We used to have one cultural island that was allowed. It was a typical subspace of thought, and anything that was diverting from that subspace of thought was suppressed or you were canceled. Now we’ve created a new mode, but the whole point is that we’re not trying to have a very restricted space of thought. There’s not just one way to think about e/acc and its many forks. And the point is that there are many forks and there can be many clusters and many islands.
Guillaume Verdon (01:57:07) 我不应该以任何方式控制它。我的意思是，根本没有正式的组织。我只是发推文和某些博客文章，如果有他们不喜欢的方面，人们可以自由地叛逃和分叉。所以这使得在想法空间中应该有去领土化，这样我们就不会最终陷入一个非常像邪教的集群。所以邪教通常，他们不允许人们叛逃或开始竞争性分叉，而我们鼓励这样做。
GUILLAUME VERDON (01:57:07) And I shouldn’t be in control of it in any way. I mean, there’s no formal org whatsoever. I just put out tweets and certain blog posts, and people are free to defect and fork if there’s an aspect they don’t like. And so that makes it so that there should be deterritorialization in the space of ideas, so that we don’t end up in one cluster that’s very cult-like. And so cults usually, they don’t allow people to defect or start competing forks, whereas we encourage it.
幽默与模因 Humor and memes Lex Fridman (01:57:51) 幽默和模因的利弊，从某种意义上说，模因中有一种智慧。那是什么，魔术剧场？那是哪本书？赫尔曼·黑塞。我想是《荒原狼》。但有一种拥抱荒诞的东西似乎能触及事物的真相，但与此同时，它也可能降低话语的质量和严谨性。
LEX FRIDMAN (01:57:51) The pros and cons of humor in meme, in some sense there’s like a wisdom to memes. What is it, the Magic Theater? What book is that from? Hermann Hesse. Steppenwolf, I think. But there’s a kind of embracing of the absurdity that seems to get to the truth of things, but at the same time, it can also decrease the quality and the rigor of the discourse.
Guillaume Verdon (01:58:22) 是的。
GUILLAUME VERDON (01:58:22) Yeah.
Lex Fridman (01:58:23) 你感受到那种张力吗？
LEX FRIDMAN (01:58:23) Do you feel the tension of that?
Guillaume Verdon (01:58:25) 是的。所以最初，我认为让我们在雷达下成长的是因为它被伪装成某种元讽刺。我们会在幽默和模因以及所谓的shit posts的包装中偷偷放入深刻的真理，我认为这是故意伪装以对抗那些寻求地位、不想……与卡通青蛙或星际Jeff Bezos的卡通争论并认真对待自己是非常困难的，所以这让我们在早期能够相当迅速地增长。但当然，本质上人们会被引导。他们对真理的概念来自他们看到的数据，来自他们被喂养的信息，而人们被喂养的信息是由算法决定的。我们真正在做的是设计我们所说的高模因适应性信息包，以便它们能够有效传播并携带信息。
GUILLAUME VERDON (01:58:25) Yeah. So initially, I think what allowed us to grow under the radar was because it was camouflaged as sort of meta-ironic. We would sneak in deep truths within a package of humor and memes and what are called shit posts, and I think that was purposefully camouflaged against those that seek status and do not want to… It’s very hard to argue with a cartoon frog or a cartoon of an intergalactic Jeff Bezos and take yourself seriously, and so that allowed us to grow pretty rapidly in the early days. But of course, essentially people get steered. Their notion of the truth comes from the data they see, from the information they’re fed, and the information people are fed is determined by algorithms. And really what we’ve been doing is engineering what we call high memetic fitness packets of information, so that they can spread effectively and carry a message.
Guillaume Verdon (01:59:47) 所以这是一种传播信息的载体。是的，我们一直在使用对今天的算法放大的信息景观最优的技术。但我认为我们正在达到可以进行严肃辩论和严肃对话的规模点。这就是为什么我们正在考虑进行一系列辩论并进行更严肃的长篇讨论。因为我认为时间线对于非常严肃、深思熟虑的讨论来说不是最优的。你会因为两极分化而得到奖励。所以即使我们开始了一个字面上试图使科技生态系统两极分化的运动，归根结底是为了让我们能够进行对话并一起找到最优解。
GUILLAUME VERDON (01:59:47) So it’s kind of a vector to spread the message. And yes, we’ve been using techniques that are optimal for today’s algorithmically-amplified information landscapes. But I think we’re reaching the point of scale where we can have serious debates and serious conversations. And that’s why we’re considering doing a bunch of debates and having more serious long-form discussions. Because I don’t think that the timeline is optimal for very serious, thoughtful discussions. You get rewarded for polarization. And so even though we started a movement that is literally trying to polarize the tech ecosystem, at the end of the day so that we can have a conversation and find an optimum together.
Jeff Bezos Jeff Bezos Lex Fridman (02:00:42) 我的意思是，这就是我试图用这个播客做的事情，鉴于事物的景观，仍然进行长篇对话。但荒诞被充分拥抱的程度是存在的。事实上，这次对话本身就是多层次荒诞的。所以首先，我应该说，就在最近我与Jeff Bezos进行了对话，我很想听听你——Beff Jezos——对Jeff Bezos的看法。说到星际Jeff Bezos。你对那个你的名字所启发的特定个体有什么看法？
LEX FRIDMAN (02:00:42) I mean, that’s kind of what I try to do with this podcast given the landscape of things, to still have long-form conversations. But there is a degree to which absurdity is fully embraced. In fact, this very conversation is multi-level absurd. So first of all, I should say that just very recently I had a conversation with Jeff Bezos, and I would love to hear your, Beff Jezos, opinions of Jeff Bezos. Speaking of intergalactic Jeff Bezos. What do you think of that particular individual whom your name has inspired?
Guillaume Verdon (02:01:25) 是的，我认为Jeff真的很棒。我的意思是，他建立了有史以来最史诗级的公司之一。他利用了技术-资本机器和技术-资本加速来给我们我们想要的东西。我们想要快速交付，非常方便，在家，低价格。他理解机器是如何运作的以及如何利用它，比如经营公司，不试图过早获利，把它放回去，让系统复合并不断改进。可以说，我认为亚马逊在机器人技术方面投资了最多的资本，当然随着AWS的诞生，有点使我们今天看到的科技繁荣成为可能，这支付了我的工资，我想在某种程度上也支付了我们所有朋友的工资。所以我认为我们都可以感谢Jeff，他是那里最伟大的企业家之一，无可争议地是有史以来最好的之一。
GUILLAUME VERDON (02:01:25) Yeah, I think Jeff is really great. I mean, he’s built one of the most epic companies of all time. He’s leveraged the techno-capital machine and techno-capital acceleration to give us what we wanted. We want a quick delivery, very convenient, at-home, low prices. He understood how the machine worked and how to harness it, like running the company, not trying to take profits too early, putting it back, letting the system compound and keep improving. And arguably, I think Amazon’s invested some of the most amount of capital and robotics out there, and certainly with the birth of AWS, kind of enabled the tech boom we’ve seen today that has paid the salaries of, I guess myself and all of our friends to some extent. And so I think we can all be grateful to Jeff, and he’s one of the great entrepreneurs out there. one of the best of all time, unarguably.
Lex Fridman (02:02:32) 当然，蓝色起源的工作，类似于SpaceX的工作，试图让人类成为多行星物种，这似乎几乎比资本主义机器更大。或者这是不同时间尺度上的资本主义机器？
LEX FRIDMAN (02:02:32) And of course, the work at Blue Origin, similar to the work at SpaceX, is trying to make humans a multi-planetary species, which that seems almost like a bigger thing than the capitalist machine. Or it’s the capitalist machine at a different timescale perhaps?
Guillaume Verdon (02:02:47) 是的，我认为公司，它们倾向于逐季度优化，也许几年后，但想要留下遗产的个人可以在几十年或几个世纪的时间尺度上思考。所以事实是，一些个人是如此优秀的资本配置者，以至于他们解锁了将资本分配给带我们走得更远或更有远见的目标的能力……Elon正在用SpaceX做这件事，把所有这些资本投入到让我们到达火星。Jeff正在努力建造蓝色起源，我认为他想建造奥尼尔圆柱体（书童注：O’Neill cylinder，一种太空栖息地设计概念）并将工业搬离地球，我认为这很出色。
GUILLAUME VERDON (02:02:47) Yeah, I think that companies, they tend to optimize quarter over quarter, maybe a few years out, but individuals that want to leave a legacy can think on a multi-decadal or multi-century timescale. And so the fact that some individuals are such good capital allocators that they unlock the ability to allocate capitals to goals that take us much further or are much further-looking… Elon’s doing this with SpaceX, putting all this capital towards getting us to Mars. Jeff is trying to build Blue Origin, and I think he wants to build O’Neill cylinders and get industry off- planet, which I think is brilliant.
Guillaume Verdon (02:03:33) 我认为总的来说，我支持四位亿万富翁。我知道这有时是一个有争议的声明，但我认为从某种意义上说，这是一种权益证明投票。如果你有效地分配了资本，你就解锁了更多的资本来分配，只是因为你显然知道如何更有效地分配资本。这与政治家形成对比，政治家被选中是因为他们在电视上说得最好，而不是因为他们有最有效分配纳税人资本的经过验证的记录。所以这就是为什么我支持资本主义，而不是，比如说，把我们所有的钱都交给政府，让他们弄清楚如何分配它。
GUILLAUME VERDON (02:03:33) I think just overall, I’m four billionaires. I know this is a controversial statement sometimes, but I think that in a sense it’s kind of a proof of stake voting. If you’ve allocated capital efficiently, you unlock more capital to allocate, just because clearly you know how to allocate capital more efficiently. Which is in contrast to politicians that get elected because they speak the best on TV, not because they have a proven track record of allocating taxpayer capital most efficiently. And so that’s why I’m for capitalism over, say, giving all our money to the government and letting them figure out how to allocate it.
Lex Fridman (02:04:20) 你认为为什么批评亿万富翁是一种病毒式的、流行的模因？既然你提到了亿万富翁。你认为为什么对拥有财富的人，特别是那些在公众视野中的人，比如Jeff、Elon、Mark Zuckerberg，还有谁？Bill Gates，有相当广泛的批评？
LEX FRIDMAN (02:04:20) Why do you think it’s a viral and it’s a popular meme to criticize billionaires? Since you mentioned billionaires. Why do you think there’s quite a widespread criticism of people with wealth, especially those in the public eye, like Jeff and Elon and Mark Zuckerberg, and who else? Bill Gates.
Guillaume Verdon (02:04:44) 是的，我认为很多人会，而不是试图理解技术-资本机器是如何运作的并意识到他们拥有比他们认为的更多的主动权，他们宁愿有这种受害者心态。”我只是受制于这台机器。它在压迫我。成功的玩家显然一定是邪恶的，因为他们在这个我不成功的游戏中取得了成功。”但我已经设法让一些处于那种心态的人意识到技术-资本机器是如何运作的，以及你如何为了自己和他人的利益而利用它。通过创造价值，你捕获了你为世界创造的一些价值。那种正和心态转变是如此强大，实际上，这就是我们通过扩大e/acc试图做的事情，就是解锁那种更高层次的主动权。实际上，你对未来的控制远远超过你的想象。你有改变世界的主动权，走出去做吧。这是许可。
GUILLAUME VERDON (02:04:44) Yeah, I think a lot of people would, instead of trying to understand how the techno-capital machine works and realizing they have much more agency than they think, they’d rather have this sort of victim mindset. “I’m just subjected to this machine. It is oppressing me. And the successful players clearly must be evil because they’ve been successful at this game that I’m not successful at.” But I’ve managed to get some people that were in that mindset and make them realize how the techno-capital machine works and how you can harness it for your own good and for the good of others. And by creating value, you capture some of the value you create for the world. That sort of positive sum mindset shift is so potent, and really, that’s what we’re trying to do by scaling e/acc, is unlocking that higher level of agency. Actually, you’re far more in control of the future than you think. You have agency to change the world, go out and do it. Here’s permission.
Lex Fridman (02:05:46) 每个个体都有主动权。座右铭”Keep building”（继续建造）经常被听到。这对你意味着什么，这与健怡可乐有什么关系？顺便说一句，非常感谢红牛。它工作得很好。我感觉很好。
LEX FRIDMAN (02:05:46) Each individual has agency. The motto, “Keep building” is often heard. What does that mean to you, and what does that have to do with Diet Coke? By the way, thank you so much for the Red Bull. It’s working pretty well. I’m feeling pretty good.
Guillaume Verdon (02:06:03) 太棒了。嗯，所以建造技术和建造……它不必是技术，只是建造总的来说意味着拥有主动权，试图通过创造来改变世界，比方说一家公司，这是一个在更广泛的技术-资本机器中完成功能的自我维持的有机体。对我们来说，这是在世界上实现你想看到的变化的方式，而不是，比如说，向政治家施压或创建非营利组织。非营利组织，一旦他们用完钱，他们的功能就无法再完成了。与其说是人为地扭曲市场，不如说是颠覆或引导市场，或与市场共舞，以说服它实际上这个功能很重要，增加价值，就是这样。所以我认为这是去增长、ESG方法之外，比如说，Elon之间的方式。去增长方法是，”我们要管理我们的方式走出气候危机。”而Elon是，”我要建立一家自我维持、盈利和增长的公司，我们要创新我们的方式走出这个困境。”我们试图让人们在所有规模上做后者而不是前者。
GUILLAUME VERDON (02:06:03) Awesome. Well, so building technologies and building… It doesn’t have to be technologies, just building in general means having agency, trying to change the world by creating, let’s say a company which is a self-sustaining organism that accomplishes a function in the broader techno-capital machine. To us, that’s the way to achieve change in the world that you’d like to see, rather than, say, pressuring politicians or creating nonprofits. Nonprofits, once they run out of money, their function can longer be accomplished. You’re kind of deforming the market artificially compared to sort of subverting or coursing the market, or dancing with the market, to convince it that actually this function is important, adds value, and here it is. And so I think this is the way between the de-growth, ESG approach, versus, say, Elon. The de-growth approach is like, “We’re going to manage our way out of a climate crisis.” And Elon is like, “I’m going to build a company that is self-sustaining, profitable, and growing, and we’re going to innovate our way out of this dilemma.” And we’re trying to get people to do the latter rather than the former, at all scales.
Elon Musk Elon Musk Lex Fridman (02:07:26) Elon是一个有趣的案例。你是支持者，你赞扬Elon，但他也是一个长期以来一直警告人工智能的危险、潜在危险、存在风险的人。你如何调和这两者？这对你来说是矛盾吗？
LEX FRIDMAN (02:07:26) Elon is an interesting case. You are a proponent, you celebrate Elon, but he’s also somebody who has for a long time warned about the dangers, the potential dangers, existential risks of artificial intelligence. How do you square the two? Is that a contradiction to you?
Guillaume Verdon (02:07:45) 这在某种程度上是矛盾的，因为他在许多方面非常反对监管。但对于AI，他绝对是监管的支持者。我认为总的来说，他看到了，比如说，OpenAI垄断市场然后对可以嵌入到这些LLM中的文化先验拥有垄断的危险，然后，当LLM现在成为人们的真理来源时，那么你就可以塑造人们的文化。所以你可以通过控制LLM来控制人们。他看到了这一点，就像社交媒体的情况一样，如果你塑造信息传播的功能，你就可以塑造人们的意见。他寻求制造一个竞争对手。所以至少，我认为我们在那里非常一致，通向美好未来的方式是维持各个AI玩家之间的对抗性均衡。我很想和他谈谈，以了解他对如何推进AI的想法。我的意思是，我会说他也在用Neuralink对冲他的赌注。我认为如果他不能阻止AI的进步，他正在建造与之合并的技术。看行动，而不仅仅是言语。
GUILLAUME VERDON (02:07:45) It is somewhat because he’s very much against regulation in many aspects. But for AI, he’s definitely a proponent of regulations. I think overall he saw the dangers of, say, OpenAI cornering the market and then getting to have the monopoly over the cultural priors that you can embed in these LLMs that then, as LLMs now become the source of truth for people, then you can shape the culture of the people. And so you can control people by controlling LLMs. He saw that, just like it was the case for social media, if you shape the function of information propagation, you can shape people’s opinions. He sought to make a competitor. So at least, I think we’re very aligned there, that the way to a good future is to maintain adversarial equilibria between the various AI players. I’d love to talk to him to understand his thinking about how to advance AI going forwards. I mean, he’s also hedging his bets, I would say, with Neuralink. I think if he can’t stop the progress of AI, he’s building the technology to merge. Look at the actions, not just the words.
Lex Fridman (02:09:10) 嗯，在某种程度上关注……也许使用人类心理学，关注我们周围的威胁是一个激励因素。这是一件鼓励的事情。当有截止日期时，我的表现要好得多。对截止日期的恐惧。我为自己创造人为的东西，比如我想在自己身上创造这种焦虑，好像如果我错过截止日期，真的会发生非常可怕的事情。我认为这里有一定程度的这种情况，因为创建与人类对齐的AI有很多潜在的好处。所以重新框架的一种不同方式是，”如果你不这样做，我们都会死。”这似乎是创建人类对齐AI目标的一个非常强大的心理表述。
LEX FRIDMAN (02:09:10) Well, there’s some degree where being concerned… Maybe using human psychology, being concerned about threats all around us is a motivator. It’s an encouraging thing. I operate much better when there’s a deadline. The fear of the deadline. And I, for myself, create artificial things, like I want to create in myself this kind of anxiety as if something really horrible will happen if I miss the deadline. I think there’s some degree of that here, because creating AI that’s aligned with humans has a lot of potential benefits. And so a different way to reframe that is, “If you don’t, we’re all going to die.” It just seems to be a very powerful psychological formulation of the goal of creating human-aligned AI.
Guillaume Verdon (02:09:59) 我认为焦虑是好的。我认为，正如我所说，我希望自由市场创造对齐的、可靠的AI，我认为这就是他试图用xAI做的事情。所以我完全支持。我反对的是阻止，比如说开源生态系统通过在行政命令中声称开源LM是双重用途技术并且应该由政府控制而蓬勃发展。然后每个人都需要向政府注册他们的GPU和他们的大矩阵。我认为那种额外的摩擦会阻止很多黑客做出贡献，这些黑客后来可能成为做出推动我们前进的关键发现的研究人员，包括AI安全的发现。所以我认为我只是想保持对AI的贡献机会的普遍性以及拥有未来的一部分。它不能只是被立法到某个墙后面，只有少数玩家可以玩游戏。
GUILLAUME VERDON (02:09:59) I think that anxiety is good. I think, like I said, I want the free market to create aligned AIs that are reliable, and I think that’s what he’s trying to do with xAI. So I’m all for it. What I am against is stopping, let’s say the OpenSource ecosystem from thriving by, let’s say in the executive order, claiming that OpenSource LMs are dual-use technologies and should be government controlled. Then everybody needs to register their GPU and their big matrices with the government. And I think that extra friction will dissuade a lot of hackers from contributing, hackers that could later become the researchers that make key discoveries that push us forward, including discoveries for AI safety. And so I think I just want to maintain ubiquity of opportunity to contribute to AI and to own a piece of the future. It can’t just be legislated behind some wall where only a few players get to play the game.
Lex Fridman (02:11:08) e/acc运动经常被讽刺为意味着不惜一切代价的进步和创新。不管有多不安全，不管是否造成很多损害。你只是尽可能快地建造酷的东西，整夜熬夜喝健怡可乐，无论需要什么。我想，我不知道那里是否有问题，但对你来说有多重要，你在e/acc的不同表述中看到的，AI安全有多重要？
LEX FRIDMAN (02:11:08) The e/acc movement is often caricatured to mean progress and innovation at all costs. Doesn’t matter how unsafe it is, doesn’t matter if it causes a lot of damage. You just build cool shit as fast as possible, stay up all night with a Diet Coke, whatever it takes. I guess, I don’t know if there’s a question in there, but how important to you and what you’ve seen the different formulations of e/acc, is AI safety?
Guillaume Verdon (02:11:44) 再说一次，我认为如果没有人在研究它，我认为我会是它的支持者。我认为，再说一次，我们的目标是带来平衡，显然紧迫感是取得进展的有用工具。它黑进了我们的多巴胺系统，给我们能量工作到深夜。我认为还有一个你正在贡献的更高目标。归根结底，就像，我在贡献什么？我在为这台美丽机器的增长做贡献，这样我们就可以寻求星辰。这真的很鼓舞人心。这也是一种神经黑客。
GUILLAUME VERDON (02:11:44) Again, I think if there was no one working on it, I think I would be a proponent of it. I think, again, our goal is to bring balance, and obviously a sense of urgency is a useful tool to make progress. It hacks our dopaminergic systems and gives us energy to work late into the night. I think also having a higher purpose you’re contributing to. At the end of the day, it’s like, what am I contributing to? I’m contributing to the growth of this beautiful machine so that we can seek to the stars. That’s really inspiring. That’s also a sort of neuro hack.
Lex Fridman (02:12:26) 所以你是说AI安全对你来说很重要，但现在你看到的想法景观是，AI安全作为一个话题更常被用来获得集中控制。所以从这个意义上说，你在抵制它，作为获得集中控制的代理？
LEX FRIDMAN (02:12:26) So you’re saying AI safety is important to you, but right now the landscape of ideas you see is, AI safety as a topic is used more often to gain centralized control. So in that sense, you’re resisting it, as a proxy for gaining centralized control?
Guillaume Verdon (02:12:43) 是的，我只是认为我们必须小心，因为安全只是权力集中化和最终掩盖腐败的完美掩护。我不是说它现在已经腐败了，但它可能在未来。而且实际上，如果你让论证运行，没有多少权力集中化的控制足以确保你的安全。总是有更多的9个9的P安全可以获得，99.9999%安全。也许你想要另一个9。”哦，请让我们完全访问你做的一切。完全监视。”坦率地说，那些AI安全的支持者已经提议拥有一个全球全景监狱，你对正在发生的一切都有集中的感知。对我来说，这只是为老大哥、1984式的场景敞开了大门。那不是我想生活的未来。
GUILLAUME VERDON (02:12:43) Yeah, I just think we have to be careful, because safety is just the perfect cover for centralization of power and covering up eventually corruption. I’m not saying it’s corrupted now, but it could be down the line. And really, if you let the argument run, there’s no amount of centralization of control that will be enough to ensure your safety. There’s always more 999s of P safety that you can gain, 99.9999% safe. Maybe you want another nine. “Oh, please give us full access to everything you do. Full surveillance.” And frankly, those that are proponents of AI safety have proposed having a global panopticon where you have centralized perception of everything going on. And to me, that just opens up the door wide open for a big brother, 1984-like scenario. And that’s not a future I want to live in.
Lex Fridman (02:13:49) 因为我们在整个历史上有一些例子，那没有导致好的结果。
LEX FRIDMAN (02:13:49) Because we have some examples throughout history when that did not lead to a good outcome.
Extropic Extropic Guillaume Verdon (02:13:54) 对。
GUILLAUME VERDON (02:13:54) Right.
Lex Fridman (02:13:56) 你提到你创立了一家公司Extropic，最近宣布了1410万美元的种子轮融资。公司的目标是什么？你谈到了很多有趣的物理东西，所以你在那里做什么可以谈论的？
LEX FRIDMAN (02:13:56) You mentioned you founded a company, Extropic, that recently announced a 14.1 million seed round. What’s the goal of the company? You’re talking about a lot of interesting physics things, so what are you up to over there that you can talk about?
Guillaume Verdon (02:14:12) 是的，最初我们不打算在上周宣布，但我认为由于人肉曝光和披露，我们被迫披露了。所以我们不得不披露我们大致在做什么。但实际上，Extropic诞生于我和我的同事对量子计算路线图的不满。量子计算有点是试图商业化规模化的基于物理的计算的第一条路径，我正在研究运行在这些基于物理的计算机上的基于物理的AI。但最终，我们最大的敌人是这种噪声，这种无处不在的噪声问题，正如我所提到的，你必须不断地把噪声从系统中抽出来，以维持这种原始环境，在那里量子力学可以生效。那个约束太多了。做那个太昂贵了。
GUILLAUME VERDON (02:14:12) Yeah, originally we weren’t going to announce last week, but I think with the doxing and disclosure, we got our hand forced. So we had to disclose roughly what we were doing. But really, Extropic was born from my dissatisfaction, and that of my colleagues, with the quantum computing roadmap. Quantum computing was sort of the first path to physics-based computing that was trying to commercially scale, and I was working on physics-based AI that runs on these physics-based computers. But ultimately, our greatest enemy was this noise, this pervasive problem of noise that, as I mentioned, you have to constantly pump out the noise out of the system to maintain this pristine environment where quantum mechanics can take effect. And that constraint was just too much. It’s too costly to do that.
Guillaume Verdon (02:15:11) 所以我们在想，当生成式AI有点吞噬世界时，世界上越来越多的计算工作负载集中在生成式AI上，我们如何能够使用物理学从物理学、信息论、计算以及最终热力学的第一原理来设计生成式AI的终极物理基底？所以我们寻求建造的是一个基于物理的计算系统和基于物理的AI算法，它们受到非平衡热力学的启发，或直接利用它来将机器学习作为一个物理过程来做。
GUILLAUME VERDON (02:15:11) And so we were wondering, as generative AI is sort of eating the world, more and more of the world’s computational workloads are focused on generative AI, how could we use physics to engineer the ultimate physical substrate for generative AI from first principles of physics, of information theory, of computation, and ultimately of thermodynamics? And so what we’re seeking to build is a physics-based computing system and physics-based AI algorithms that are inspired by out-of-equilibrium thermodynamics, or harness it directly to do machine learning as a physical process.
Lex Fridman (02:16:01) 那么这意味着什么，机器学习作为一个物理过程？是硬件吗？是软件吗？两者都是吗？它试图以某种独特的方式做全栈吗？
LEX FRIDMAN (02:16:01) So what does that mean, machine learning as a physical process? Is that hardware? Is it software? Is it both? Is it trying to do the full stack in some kind of unique way?
Guillaume Verdon (02:16:10) 是的，它是全栈的。所以我们是那些用TensorFlow Quantum将可微编程构建到量子计算生态系统中的人。TensorFlow Quantum的联合创始人之一是CTO Trevor McCourt。我们有一些最好的量子计算机架构师，那些设计了IBM和AWS系统的人。他们已经离开了量子计算，帮助我们建造我们所说的实际上是一台热力学计算机。
GUILLAUME VERDON (02:16:10) Yes, it is full stack. And so we’re folks that have built differentiable programming into the quantum computing ecosystem with TensorFlow Quantum. One of my co-founders of TensorFlow Quantum is the CTO, Trevor McCourt. We have some of the best quantum computer architects, those that have designed IBM’s and AWS’s systems. They’ve left quantum computing to help us build what we call actually a thermodynamic computer.
Lex Fridman (02:16:43) 一台热力学计算机。嗯，实际上让我们在TensorFlow Quantum周围停留一下。你从TensorFlow Quantum中学到了什么教训？也许你可以谈谈创建本质上是量子计算机的软件API需要什么？
LEX FRIDMAN (02:16:43) A thermodynamic computer. Well, actually let’s linger around TensorFlow Quantum. What lessons have you learned from TensorFlow Quantum? Maybe you can speak to what it takes to create essentially, what, like a software API to a quantum computer?
Guillaume Verdon (02:17:01) 对。那是一个挑战，要发明、建造，然后在真实设备上运行。
GUILLAUME VERDON (02:17:01) Right. That was a challenge to invent, to build, and then to get to run on the real devices.
Lex Fridman (02:17:09) 你能实际谈谈它是什么吗？
LEX FRIDMAN (02:17:09) Can you actually speak to what it is?
Guillaume Verdon (02:17:11) 是的。TensorFlow Quantum是一次尝试……嗯，我想我们成功了，将深度学习或可微经典编程与量子计算结合起来，并将量子计算转变为或在量子计算中拥有可微的程序类型。Andrej Karpathy称可微编程为Software 2.0。就像，梯度下降是比你更好的程序员。这个想法是，在量子计算的早期，你只能运行短的量子程序。那么，你应该运行哪些量子程序？嗯，就让梯度下降找到那些程序吧。所以我们建立了第一个基础设施，不仅可以运行可微的量子程序，还可以将它们作为更广泛的深度学习图的一部分，结合深度神经网络——你知道和喜爱的那些——与所谓的量子神经网络。
GUILLAUME VERDON (02:17:11) Yeah. TensorFlow Quantum was an attempt at… Well, I guess we succeeded, at combining deep learning or differentiable classical programming with quantum computing, and turn quantum computing into or have types of programs that are differentiable in quantum computing. And Andrej Karpathy calls differentiable programming, Software 2.0. It’s like, gradient descent is a better programmer than you. And the idea was that in the early days of quantum computing, you can only run short quantum programs. And so, which quantum programs should you run? Well, just let gradient descent find those programs instead. And so we built the first infrastructure to not only run differentiable quantum programs, but combine them as part of broader deep learning graphs, incorporating deep neural networks, the ones you know and love, with what are called quantum neural networks.
Guillaume Verdon (02:18:21) 最终，这是一个非常跨学科的努力。我们必须发明各种微分方法，通过混合图进行反向传播。但最终，它教会了我编程物质和编程物理的方法是通过对控制参数进行微分。如果你有影响系统物理的参数，并且你可以评估某个损失函数，你就可以优化系统以完成任务，无论那个任务是什么。这是一个非常普遍的元框架，用于如何编程基于物理的计算机。
GUILLAUME VERDON (02:18:21) And ultimately, it was a very cross-disciplinary effort. We had to invent all sorts of ways to differentiate, to back propagate through the hybrid graph. But ultimately, it taught me that the way to program matter and to program physics is by differentiating through control parameters. If you have parameters that affects the physics of the system and you can evaluate some loss function, you can optimize the system to accomplish a task, whatever that task may be. And that’s a very universal meta framework for how to program physics-based computers.
Lex Fridman (02:19:05) 所以试图参数化一切，使这些参数可微，然后优化？
LEX FRIDMAN (02:19:05) So try to parameterize everything, make those parameters differentiable, and then optimize?
Guillaume Verdon (02:19:12) 是的。
GUILLAUME VERDON (02:19:12) Yes.
Lex Fridman (02:19:13) 好的。TensorFlow Quantum有一些更实际的工程教训吗？组织上也是，比如涉及的人类以及如何到达产品，如何创建好的文档？我不知道。所有这些人们可能不会想到的小微妙的东西。
LEX FRIDMAN (02:19:13) Okay. Is there some more practical engineering lessons from TensorFlow Quantum? Just organizationally too, like the humans involved and how to get to a product, how to create good documentation? I don’t know. All of these little subtle things that people might not think about.
Guillaume Verdon (02:19:34) 我认为跨学科边界工作总是一个挑战，你必须在互相教学方面非常耐心。我通过这个过程学到了很多软件工程。我的同事学到了很多量子物理学，有些人通过建造这个系统的过程学到了机器学习。我认为如果你让一些聪明、充满激情并相互信任的人在一个房间里，你有一个小团队——
GUILLAUME VERDON (02:19:34) I think working across disciplinary boundaries is always a challenge, and you have to be extremely patient in teaching one another. I learned a lot of software engineering through the process. My colleagues learned a lot of quantum physics, and some learned machine learning through the process of building this system. And I think if you get some smart people that are passionate and trust each other in a room, and you have a small team-
Guillaume Verdon (02:20:00) 充满激情并相互信任，你有一个小团队，你们互相教授你们的专长，突然你有点形成了这种专业知识的模型汤，一些特别的东西从中出来，对吧？这就像结合基因，但为了你的知识库，有时特殊的产品从中出来。所以我认为，即使最初在跨学科团队中工作摩擦很大，我认为归根结底产品是值得的。所以，学到了很多试图弥合那里的差距。我的意思是，直到今天这仍然是一个挑战。我们雇用有AI背景的人，有纯物理背景的人，不知何故我们必须让他们互相交谈。对吧？
GUILLAUME VERDON (02:20:00) Are passionate and trust each other in a room, and you have a small team, and you teach each other your specialties, suddenly you’re kind of forming this sort of model soup of expertise, and something special comes out of that, right? It’s like combining genes, but for your knowledge bases, and sometimes special products come out of that. And so I think, even though it’s very high friction initially to work in an interdisciplinary team, I think the product at the end of the day is worth it. And so, learned a lot trying to bridge the gap there. And I mean, it’s still a challenge to this day. We hire folks that have an AI background, folks that have a pure physics background, and somehow we have to make them talk to one another. Right?
Lex Fridman (02:20:47) 招聘过程有魔力吗，建立一个能够一起创造魔力的团队有科学和艺术吗？
LEX FRIDMAN (02:20:47) Is there a magic, is there some science and art to the hiring process, to building a team that can create magic together?
Guillaume Verdon (02:20:56) 是的，真的很难准确指出那种je ne sais quoi（书童注：法语，意为”难以言喻的特质”），对吧？
GUILLAUME VERDON (02:20:56) Yeah, it’s really hard to pinpoint that je ne sais quoi, right?
Lex Fridman (02:21:03) 我不知道你说法语。这很好。
LEX FRIDMAN (02:21:03) I didn’t know you speak French. That’s very nice.
Guillaume Verdon (02:21:07) 是的，我实际上是法裔加拿大人。
GUILLAUME VERDON (02:21:07) Yeah, I’m actually French Canadian.
Lex Fridman (02:21:09) 哦，你是真正的法裔加拿大人。
LEX FRIDMAN (02:21:09) Oh, you are a legitimately French Canadian.
Guillaume Verdon (02:21:09) 我是。
GUILLAUME VERDON (02:21:09) I am.
Lex Fridman (02:21:11) 我以为你只是为了信誉而这么做。
LEX FRIDMAN (02:21:11) I thought you were just doing that for the cred.
Guillaume Verdon (02:21:15) 不，不。我真的是法裔加拿大人，来自蒙特利尔。但是的，基本上我们寻找具有非常高灵活度的通才、不是过度专业化的人，因为他们将不得不走出他们的舒适区。他们将不得不整合他们以前从未见过的概念，并非常迅速地整合到舒适区，或学会在团队中工作。所以这就是我们在招聘时寻找的。我们不能雇用那些在过去三四年里只是优化这个子系统的人。我们需要真正通用的某种更广泛的智力和专长，以及开放思想的人，真的，因为如果你从头开始开创一个新方法，没有教科书，没有参考资料。就是我们，和渴望学习的人。所以，我们必须互相教授,我们必须学习文献，我们必须分享知识库，合作以便一起推动知识边界。所以，习惯于只是被规定做什么的人在这个阶段，当你处于开拓阶段时，那不一定是你想雇用的人。是的。
GUILLAUME VERDON (02:21:15) No, no. I’m truly French Canadian, from Montreal. But yeah, essentially we look for people with very high fluid intelligence that aren’t overspecialized, because they’re going to have to get out of their comfort zone. They’re going to have to incorporate concepts that they’ve never seen before, and very quickly get comfortable with them, or learn to work in a team. And so that’s sort of what we look for when we hire. We can’t hire people that are just optimizing this subsystem for the past three or four years. We need really general sort of broader intelligence and specialty, and people that are open-minded, really, because if you’re pioneering a new approach from scratch, there is no textbook, there’s no reference. It’s just us, and people that are hungry to learn. So, we have to teach each other, we have to learn the literature, we have to share knowledge bases, collaborate in order to push the boundary of knowledge further together. And so, people that are used to just getting prescribed what to do at this stage, when you’re at the pioneering stage, that’s not necessarily who you want to hire. Yeah.
（第三部分完）
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【e/acc】有效加速主义、量子热力学与AI未来 | 物理学家、e/acc运动创始人Guillaume Verdon与Lex Fridman播客实录 | 中英文完整版精译 II
书童按：本篇是Guillaume Verdon接受Lex Fridman播客采访实录的第二部分。延续上篇对有效加速主义（e/acc）哲学根基的探讨，本篇深入人与AI共生的未来图景、末日概率（p(doom)）的合理性辨析、量子机器学习的前沿探索等议题。Verdon以物理学家的视角，从热力学第二定律出发论证生命与文明的增长本性，主张人类应拥抱AI增强而非恐惧替代，批判末日论者对未来的偏见式采样，并分享量子计算与量子深度学习的技术洞见。访谈纵横于哲学思辨与技术前沿，既有对人类中心主义的解构，亦有对资本主义市场机制的坚守，视野开阔，发人深省。初稿采用Claude API机器翻译及排版，书童仅做简单校对及批注，以飨诸君。
Guillaume Verdon：有效加速主义、热力学与量子智能 | Lex Fridman播客（第二部分） Guillaume Verdon: Effective Accelerationism, Thermodynamics, and Quantum Intelligence | Lex Fridman Podcast (Part II) 与AI共生 Merging with AI Lex Fridman (00:50:13) 那么，如果事实证明，宇宙中意识之美的载体不止人类，AI也能将同样的火焰传承下去——这让你害怕吗？你担心AI会取代人类吗？
LEX FRIDMAN (00:50:13) So if it turns out that the beauty that is consciousness in the universe is bigger than just humans, the AI can carry that same flame forward. Does it scare you, are you concerned that AI will replace humans?
Guillaume Verdon (00:50:32) 在我的职业生涯中，有一个时刻让我意识到：也许我们需要把任务交给机器，才能真正理解我们周围的宇宙——而不是仅靠人类拿着纸笔把一切算出来。对我来说，这种放手一部分主动权的过程，反而给了我们理解世界的巨大杠杆。量子计算机在理解纳米尺度的物质方面，远胜过人类。类似地，我认为人类面临一个选择：我们是否接受AI将解锁的智力和操作杠杆，从而确保我们能够沿着文明规模与范围不断增长的道路前进？我们可能会被稀释——也许会有大量AI工作者——但总体而言，出于自身利益，通过与AI结合并增强自己，我们将实现更高的增长和更大的繁荣。
GUILLAUME VERDON (00:50:32) So during my career, I had a moment where I realized that maybe we need to offload to machines to truly understand the universe around us, right, instead of just having humans with pen and paper solve it all. And to me that sort of process of letting go of a bit of agency gave us way more leverage to understand the world around us. A quantum computer is much better than a human to understand matter at the Nanoscale. Similarly, I think that humanity has a choice, do we accept the opportunity to have intellectual and operational leverage that AI will unlock and thus ensure that we’re taken along this path of growth in the scope and scale of civilization? We may dilute ourselves, right? There might be a lot of workers that are AI, but overall out of our own self-interest, by combining and augmenting ourselves with AI, we’re going to achieve much higher growth and much more prosperity, right.
Guillaume Verdon (00:51:49) 对我而言，我认为最可能的未来是人类用AI增强自己。我认为我们已经走在这条增强之路上了——我们有手机用于通信，随时带在身上。我们有可穿戴设备，很快就会拥有与我们共享感知的设备，比如Humane AI Pin，或者说，从技术上讲，你的特斯拉汽车就具有共享感知能力。如果你们有共享的体验、共享的上下文、彼此通信并且有某种输入输出接口，那它本质上就是你自己的延伸。对我来说，人类用AI增强自己，以及那些不锚定于任何生物基质的AI，二者将会共存。而让各方利益对齐的方式——我们其实已经有了让由人类和技术组成的超级智能体对齐的机制。公司本质上是大型的混合专家模型，我们在公司内部有任务的神经路由机制，也有经济交换的方式来对齐这些庞然大物。
GUILLAUME VERDON (00:51:49) To me, I think that the most likely future is one where humans augment themselves with AI. I think we’re already on this path to augmentation, we have phones we use for communication, we have on ourselves at all times. We have wearables, soon that have shared perception with us, right, like the Humane AI Pin or I mean, technically your Tesla car has shared perception. And so if you have shared experience, shared context, you communicate with one another and you have some sort of IO, really it’s an extension of yourself.And to me, I think that humanity augmenting itself with AI and having AI that is not anchored to anything biological, both will coexist. And the way to align the parties, we already have a sort of mechanism to align super intelligences that are made of humans and technology, right? Companies are sort of large mixture of expert models, where we have neural routing of tasks within a company and we have ways of economic exchange to align these behemoths.
Guillaume Verdon (00:53:10) 对我来说，我认为资本主义就是那条路。我确实认为，无论是什么样的物质或信息配置，只要能带来最大化的增长，我们就会收敛到那里——这纯粹是物理原理使然。所以我们要么让自己与这个现实对齐，加入文明规模与范围加速扩张的进程；要么被甩在后面，试图减速，退回森林，放弃技术，回到原始状态。至少在我看来，这就是摆在面前的两条路。
GUILLAUME VERDON (00:53:10) And to me, I think capitalism is the way, and I do think that whatever configuration of matter or information leads to maximal growth, will be where we converge, just from like physical principles. And so we can either align ourselves to that reality and join the acceleration up in scope and scale of civilization or we can get left behind and try to decelerate and move back in the forest, let go of technology and return to our primitive state. And those are the two paths forward, at least to me.
Lex Fridman (00:53:54) 但有个哲学问题是：人类对齐能力是否存在极限？让我以一种论证的形式提出来。有个叫Dan Hendrycks的人写道，他同意你的观点，即AI的发展可以被视为一个进化过程，但对他——对Dan来说——这并不是件好事，因为他认为自然选择会偏好AI而非人类，这可能导致人类灭绝。你怎么看？如果这真是一个进化过程，而AI系统可能不需要人类呢？
LEX FRIDMAN (00:53:54) But there’s a philosophical question whether there’s a limit to the human capacity to align. So let me bring it up as a form of argument, this guy named Dan Hendrycks and he wrote that he agrees with you that AI development could be viewed as an evolutionary process, but to him, to Dan, this is not a good thing, as he argues that natural selection favors AIs over humans and this could lead to human extinction. What do you think, if it is an evolutionary process and AI systems may have no need for humans?
Guillaume Verdon (00:54:36) 我确实认为，我们实际上正在通过市场对AI的空间施加进化压力。现在我们运行那些对人类有正效用的AI，这就产生了选择压力——如果你认为当一个神经网络的API实例在GPU上运行时，它就”活着”的话。
GUILLAUME VERDON (00:54:36) I do think that we’re actually inducing an evolutionary process on the space of AIs through the market, right. Right now we run AIs that have positive utility to humans and that induces a selective pressure, if you consider a neural net being alive when there’s an API running instances of it on GPUs.
Lex Fridman (00:55:01) 对。
LEX FRIDMAN (00:55:01) Yeah.
Guillaume Verdon (00:55:01) 哪些API会被运行？那些对我们有高效用的。这就像我们驯化狼并把它们变成狗——狗的表达非常清晰，非常对齐。我认为我们有机会引导AI并实现高度对齐的AI。而且我认为人类加AI是一个非常强大的组合，我不确定纯粹的AI会淘汰这种组合。
GUILLAUME VERDON (00:55:01) Right. And which APIs get run? The ones that have high utility to us, right. So similar to how we domesticated wolves and turned them into dogs that are very clear in their expression, they’re very aligned, right. I think there’s going to be an opportunity to steer AI and achieve highly aligned AI. And I think that humans plus AI is a very powerful combination and it’s not clear to me that pure AI would select out that combination.
Lex Fridman (00:55:40) 所以人类现在正在创造选择压力，以创造与人类对齐的AI。但考虑到AI的发展方式以及它能多快地增长和扩展，对我来说，一个担忧是意外后果——人类无法预见这个过程的所有后果。AI系统可能造成的意外后果的破坏规模非常大。
LEX FRIDMAN (00:55:40) So the humans are creating the selection pressure right now to create AIs that are aligned to humans, but given how AI develops and how quickly it can grow and scale, to me, one of the concerns is unintended consequences, like humans are not able to anticipate all the consequences of this process. The scale of damage that could be done through unintended consequences with AI systems is very large.
Guillaume Verdon (00:56:10) 但上行空间的规模——
GUILLAUME VERDON (00:56:10) The scale of the upside.
Lex Fridman (00:56:12) 是的。
LEX FRIDMAN (00:56:12) Yes.
Guillaume Verdon (00:56:13) 对吧？
GUILLAUME VERDON (00:56:13) Right?
Lex Fridman (00:56:13) 我猜这是——
LEX FRIDMAN (00:56:13) Guess it’s-
Guillaume Verdon (00:56:14) 通过用AI增强我们自己，现在无法想象的上行空间。机会成本——我们正处在一个岔路口，对吧？我们要么走创造这些技术的道路，增强自己，在AI的帮助下攀登卡尔达肖夫等级（书童注：Kardashev Scale，衡量文明技术发展水平的量表，以能源利用能力为标准），成为多行星物种；要么我们完全不孕育这些技术，把所有潜在的上行空间都留在桌面上。
GUILLAUME VERDON (00:56:14) By augmenting ourselves with AI is unimaginable right now. The opportunity cost, we’re at a fork in the road, right? Whether we take the path of creating these technologies, augment ourselves and get to climb up the Kardashev Scale, become multi-planetary with the aid of AI, or we have a hard cutoff of like we don’t birth these technologies at all and then we leave all the potential upside on the table.
Lex Fridman (00:56:42) 对。
LEX FRIDMAN (00:56:42) Yeah.
Guillaume Verdon (00:56:42) 对我而言，出于对未来人类的责任——通过扩大文明规模，我们可以承载更多的人口——出于对这些未来人类的责任，我认为我们必须让那个更伟大、更宏大的未来成为现实。
GUILLAUME VERDON (00:56:42) Right. And to me, out of responsibility to the future humans we could carry, with higher carrying capacity by scaling up civilization. Out of responsibility to those humans, I think we have to make the greater grander future happen.
Lex Fridman (00:56:58) 在硬切断和全速前进之间，有中间地带吗？谨慎有任何论据吗？
LEX FRIDMAN (00:56:58) Is there a middle ground between cutoff and all systems go? Is there some argument for caution?
Guillaume Verdon (00:57:06) 我认为，正如我所说，市场会表现出谨慎。每个有机体、每家公司、每个消费者都在为自身利益行事，他们不会把资本分配给对他们有负效用的东西。
GUILLAUME VERDON (00:57:06) I think, like I said, the market will exhibit caution. Every organism, company, consumer is acting out of self-interest and they won’t assign capital to things that have negative utility to them.
Lex Fridman (00:57:21) 问题在于市场并不总是有完美信息，存在操纵，存在恶意行为者搅乱系统。它并不总是一个理性和诚实的系统。
LEX FRIDMAN (00:57:21) The problem is with the market is, there’s not always perfect information, there’s manipulation, there’s bad faith actors that mess with the system. It’s not always a rational and honest system.
Guillaume Verdon (00:57:41) 嗯，这正是为什么我们需要信息自由、言论自由和思想自由，以便能够收敛到对我们所有人都有正效用的技术子空间。
GUILLAUME VERDON (00:57:41) Well, that’s why we need freedom of information, freedom of speech and freedom of thought in order to be able to converge on the subspace of technologies that have positive utility for us all, right.
末日概率 p(doom) Lex Fridman (00:57:56) 那让我问你关于p(doom)的问题——末日概率。这个词说起来挺有意思，但经历起来可不有趣。在你看来，AI最终杀死全部或大部分人类的概率是多少——也就是所谓的末日概率？
LEX FRIDMAN (00:57:56) Well let me ask you about p(doom), probability of doom. That’s just fun to say, but not fun to experience. What is to you the probability that AI eventually kills all or most humans, also known as probability of doom?
Guillaume Verdon (00:58:16) 我不喜欢那种计算方式。我认为人们只是随便抛出数字，这是非常草率的计算。要计算概率，比方说你把世界建模为某种马尔可夫过程，如果你有足够多的变量，或者隐马尔可夫过程——你需要对所有可能的未来空间做随机路径积分，而不仅仅是你的大脑自然倾向的那些未来。我认为p(doom)的估算者是有偏见的，因为我们的生物本性。我们进化出了对负面的、可怕的未来的偏见采样，因为那是进化的最优解。所以那些神经质程度较高的人，整天每天都在想一切都会出错的负面未来，并声称他们在做无偏采样。某种意义上，他们没有对所有可能性的空间做归一化处理，而所有可能性的空间是超指数级庞大的，很难有这样的估计。
GUILLAUME VERDON (00:58:16) I’m not a fan of that calculation, I think people just throw numbers out there and it’s a very sloppy calculation, right? To calculate a probability, let’s say you model the world as some sort of Markov process, if you have enough variables or hidden Markov process. You need to do a stochastic path integral through the space of all possible futures, not just the futures that your brain naturally steers towards, right. I think that the estimators of p(doom) are biased because of our biology, right? We’ve evolved to have bias sampling towards negative futures that are scary, because that was an evolutionary optimum, right. And so people that are of, let’s say higher neuroticism will just think of negative futures where everything goes wrong all day every day and claim that they’re doing unbiased sampling. And in a sense they’re not normalizing for the space of all possibilities and the space of all possibilities is super exponentially large and it’s very hard to have this estimate.
Guillaume Verdon (00:59:40) 总的来说，我认为我们无法以那样的粒度预测未来，因为混沌。如果你有一个复杂系统，你在几个变量上有一些不确定性，如果你让时间演化，你就有了李雅普诺夫指数（Lyapunov exponent）这个概念。一点点模糊会在我们的估计中呈指数级地变成大量模糊，随着时间推移。我认为我们需要表现出一些谦逊，承认我们实际上无法预测未来。我们拥有的唯一先验是物理定律，这正是我们所主张的。物理定律说，系统会想要增长，而为增长和复制而优化的子系统在未来更有可能出现。所以我们应该力求最大化我们当前与未来的互信息，而通往那条路的方式是加速而非减速。
GUILLAUME VERDON (00:59:40) And in general, I don’t think that we can predict the future with that much granularity because of chaos, right? If you have a complex system, you have some uncertainty and a couple of variables, if you let time evolve, you have this concept of a Lyapunov exponent, right. A bit of fuzz becomes a lot of fuzz in our estimate, exponentially so, over time. And I think we need to show some humility that we can’t actually predict the future, the only prior we have is the laws of physics, and that’s what we’re arguing for. The laws of physics say the system will want to grow and subsystems that are optimized for growth and replication are more likely in the future. And so we should aim to maximize our current mutual information with the future and the path towards that is for us to accelerate rather than decelerate.
Guillaume Verdon (01:00:40) 所以我没有p(doom)，因为我认为，类似于谷歌的量子霸权实验——我当时就在他们运行模拟的房间里——那是一个量子混沌系统的例子，你甚至无法用世界上最大的超级计算机估算某些结果的概率。那就是混沌的一个例子，而我认为这个系统对任何人来说都过于混沌，无法对某些未来的可能性有准确的估计。如果他们真有那么厉害，我想他们在股市交易上会非常富有。
GUILLAUME VERDON (01:00:40) So I don’t have a p(doom), because I think that similar to the quantum supremacy experiment at Google, I was in the room when they were running the simulations for that. That was an example of a quantum chaotic system where you cannot even estimate probabilities of certain outcomes with even the biggest supercomputer in the world, right. So that’s an example of chaos and I think the system is far too chaotic for anybody to have an accurate estimate of the likelihood of certain futures. If they were that good, I think they would be very rich trading on the stock market.
Lex Fridman (01:01:23) 但话虽如此，人类确实有偏见，根植于我们的进化生物学，害怕一切能杀死我们的东西，但我们仍然可以想象能杀死我们的不同轨迹。我们不知道所有其他不一定会的轨迹，但我认为，结合一些基于人类历史的基本直觉来推理，仍然是有用的——比如看看地缘政治，看看人性的基本面，强大的技术如何能伤害很多人？这似乎基于此，看看核武器，你可以开始估算p(doom)，也许是在更哲学的意义上，而非数学意义上。哲学意义上是指：有这种可能性吗？人性倾向于那个方向吗？
LEX FRIDMAN (01:01:23) But nevertheless, it’s true that humans are biased, grounded in our evolutionary biology, scared of everything that can kill us, but we can still imagine different trajectories that can kill us. We don’t know all the other ones that don’t necessarily, but it’s still I think, useful combined with some basic intuition grounded in human history, to reason about like what… Like looking at geopolitics, looking at basics of human nature, how can powerful technology hurt a lot of people? It just seems grounded in that, looking at nuclear weapons, you can start to estimate p(doom) maybe in a more philosophical sense, not a mathematical one. Philosophical meaning like is there a chance? Does human nature tend towards that or not?
Guillaume Verdon (01:02:25) 我认为，对我来说，最大的存在风险之一是AI的权力集中在极少数人手中，尤其是如果这是控制信息流的公司和政府的混合体。因为这可能为一种反乌托邦的未来铺平道路——只有极少数人和政府中的寡头拥有AI，他们甚至可以说服公众AI从未存在过。这就开启了威权集中控制的场景，对我来说，这是最黑暗的时间线。而现实是，我们有这些事情发生的数据驱动先验。当你给予太多权力，当你过度集中权力时，人类会做可怕的事情。
GUILLAUME VERDON (01:02:25) I think to me, one of the biggest existential risks would be the concentration of the power of AI in the hands of the very few, especially if it’s a mix between the companies that control the flow of information and the government. Because that could set things up for a sort of dystopian future where only a very few and an oligopoly in the government have AI and they could even convince the public that AI never existed. And that opens up sort of these scenarios for authoritarian centralized control, which to me is the darkest timeline. And the reality is that we have a data-driven prior of these things happening, right. When you give too much power, when you centralize power too much, humans do horrible things, right.
Guillaume Verdon (01:03:23) 对我来说，在我的贝叶斯推断中，这比基于科幻的先验有更高的可能性——比如”我的先验来自《终结者》电影”。所以当我和这些AI末日论者交谈时，我只是要求他们追溯一条通过马尔可夫链事件的路径，这条路径会导致我们的末日，并实际给我每次转换的良好概率。而很多时候，那条链中会有一个非物理的或极不可能的转换。但当然，我们天生就会害怕事物，我们天生会对危险做出反应，我们天生会认为未知是危险的，因为这是生存的好启发式方法。但出于恐惧，我们有更多的损失。我们有太多要失去的，太多的上行空间会因为出于恐惧而预先阻止正面未来的发生而失去。所以我认为我们不应该屈服于恐惧。恐惧是心智的杀手，我认为它也是文明的杀手。
GUILLAUME VERDON (01:03:23) And to me, that has a much higher likelihood in my Bayesian inference than Sci-Fi based priors, right, like, “My prior came from the Terminator movie.” And so when I talked to these AI doomers, I just ask them to trace a path through this Markov chain of events that would lead to our doom and to actually give me a good probability for each transition. And very often there’s a unphysical or highly unlikely transition in that chain, right. But of course, we’re wired to fear things and we’re wired to respond to danger, and we’re wired to deem the unknown to be dangerous, because that’s a good heuristic for survival, right. But there’s much more to lose out of fear. We have so much to lose, so much upside to lose by preemptively stopping the positive futures from happening out of fear. And so I think that we shouldn’t give into fear, fear is the mind killer, I think it’s also the civilization killer.
Lex Fridman (01:04:43) 我们仍然可以思考事情出错的各种方式。比如，美国的开国元勋们思考了人性，这就是为什么会有关于必要自由的讨论。他们真正深入地审议了这一点，我认为同样的事情可能也可以为AGI做。人类历史确实表明我们倾向于集中化，或者至少当我们实现集中化时，很多坏事会发生。当有独裁者时，很多黑暗、糟糕的事情会发生。问题是，AGI能成为那个独裁者吗？AGI在发展时，能否因为其权力而成为集中化者？也许是因为人类的对齐，也许是同样的倾向，同样的斯大林式集中化和集中管理资源分配的倾向？
LEX FRIDMAN (01:04:43) We can still think about the various ways things go wrong, for example, the founding fathers of the United States thought about human nature and that’s why there’s a discussion about the freedoms that are necessary. They really deeply deliberated about that and I think the same could possibly be done for AGI. It is true that human history shows that we tend towards centralization, or at least when we achieve centralization, a lot of bad stuff happens. When there’s a dictator, a lot of dark, bad things happen. The question is, can AGI become that dictator? Can AGI when develop, become the centralizer, because of its power? Maybe because of the alignment of humans, perhaps, the same tendencies, the same Stalin like tendencies to centralize and manage centrally the allocation of resources?
Lex Fridman (01:05:45) 你甚至可以看到这在表面上是一个令人信服的论点：”嗯，AGI如此聪明，如此高效，如此擅长分配资源，我们为什么不把它外包给AGI呢？”然后最终，无论什么力量用权力腐蚀人类的心智，都可能对AGI做同样的事。它只会说：”好吧，人类是可有可无的，我们会摆脱他们。”就像乔纳森·斯威夫特（Jonathan Swift）几个世纪前——我想是1700年代——的《一个温和的建议》（A Modest Proposal），他讽刺性地建议，我想是在爱尔兰，穷人的孩子被作为食物喂给富人，这将是个好主意，因为它减少了穷人的数量，并给穷人带来额外收入。所以从几个方面减少了穷人的数量，因此更多的人变得富有。当然，它漏掉了一个很难放入数学方程的基本部分——人类生命的基本价值。所以，这一切都是在说，你担心AGI成为你刚才谈到的权力集中者吗？
LEX FRIDMAN (01:05:45) And you can even see that as a compelling argument on the surface level. “Well, AGI is so much smarter, so much more efficient, so much better at allocating resources, why don’t we outsource it to the AGI?” And then eventually whatever forces that corrupt the human mind with power could do the same for AGI. It’ll just say, “Well, humans are dispensable, we’ll get rid of them.” Do the Jonathan Swift, Modest Proposal from a few centuries ago, I think the 1700s, when he satirically suggested that, I think it’s in Ireland, that the children of poor people are fed as food to the rich people and that would be a good idea, because it decreases the amount of poor people and gives extra income to the poor people. So on several accounts decreases the amount of poor people, therefore more people become rich. Of course, it misses a fundamental piece here that’s hard to put into a mathematical equation of the basic value of human life. So all of that to say, are you concerned about AGI being the very centralizer of power that you just talked about?
Guillaume Verdon (01:07:09) 我确实认为，现在AI有向集中化的偏见，因为计算密度和数据的集中化以及我们训练模型的方式。我认为随着时间推移，我们将耗尽可以从互联网上抓取的数据，而且我正在研究提高计算密度，以便计算可以无处不在，以分布式方式在环境中获取信息并测试假设。我认为从根本上说，集中式控制论控制——也就是拥有一个庞大的智能体，融合许多传感器，试图准确感知世界、准确预测它、预测许多许多变量并控制它、对世界施加其意志——我认为这从来就不是最优解。比方说你有一家公司，如果你有一家公司，我不知道，有10000人，他们都向CEO汇报。即使那个CEO是AI，我认为它也会努力融合所有传来的信息，然后预测整个系统，然后施行其意志。
GUILLAUME VERDON (01:07:09) I do think that right now there’s a bias over a centralization of AI, because of a compute density and centralization of data and how we’re training models. I think over time we’re going to run out of data to scrape over the internet, and I think that, well, actually I’m working on, increasing the compute density so that compute can be everywhere and acquire information and test hypotheses in the environment in a distributed fashion. I think that fundamentally, centralized cybernetic control, so having one intelligence that is massive that fuses many sensors and is trying to perceive the world accurately, predict it accurately, predict many, many variables and control it, enact its will upon the world, I think that’s just never been the optimum, right? Like let’s say you have a company, if you have a company, I don’t know, of 10,000 people, they all report to the CEO. Even if that CEO is an AI, I think it would struggle to fuse all of the information that is coming to it and then predict the whole system and then to enact its will.
Guillaume Verdon (01:08:28) 在自然界、在公司以及各种系统中出现的，是一种分层控制论控制的概念。在公司里，你有个人贡献者，他们为自己的利益行事，试图完成他们的任务，他们有一个精细的——就时间和空间而言——控制回路和感知领域。比如说你在一家软件公司，他们有自己的代码库，他们在一天内迭代它。然后管理层可能会检查，它有更广的范围，比方说有五个直接汇报对象。然后它每周对每个人的更新采样一次，然后你可以沿着链条向上，你有更大的时间尺度和更大的范围。而这似乎已经成为控制系统的最佳方式。
GUILLAUME VERDON (01:08:28) What has emerged in nature and in corporations and all sorts of systems is a notion of sort of hierarchical cybernetic control, right. In a company it would be, you have like the individual contributors, they are self-interested and they’re trying to achieve their tasks and they have a fine, in terms of time and space if you will, control loop and field of perception, right. They have their code base, let’s say you’re in a software company, they have their code base, they iterate it on it intraday, right. And then the management maybe checks in, it has a wider scope, it has, let’s say five reports, right. And then it samples each person’s update once per week, and then you can go up the chain and you have larger timescale and greater scope. And that seems to have emerged as sort of the optimal way to control systems.
Guillaume Verdon (01:09:25) 而这正是资本主义给我们的。你有这些层级结构，你甚至可以有母公司等等。这样容错性要强得多。在量子计算中——这是我的领域出身——我们有量子纠错中的容错概念。量子纠错是检测来自噪声的故障，预测它如何在系统中传播，然后纠正它——这是一个控制论回路。事实证明，分层的解码器，并且在每个层级都是局部的——
GUILLAUME VERDON (01:09:25) And really that’s what capitalism gives us, right? You have these hierarchies and you can even have like parent companies and so on. And so that is far more fault tolerant, in quantum computing, that’s my feel that came from, we have a concept of this fault tolerance in quantum air correction, right? Quantum air correction is detecting a fault that came from noise, predicting how it’s propagated through the system and then correcting it, right, so it’s a cybernetic loop. And it turns out that decoders that are hierarchical and in each level, the hierarchy are local-
Guillaume Verdon (01:10:00) ——分层的，并且每个层级都是局部的，表现要好得多，而且容错性要强得多。原因是，如果你有一个非局部的解码器，那么你在这个控制节点上有一个故障,整个系统就会崩溃。类似地，如果你有一个每个人都向其汇报的CEO，而那个CEO去度假了，整个公司就会陷入停滞。对我来说，我认为是的，我们看到AI有集中化的趋势，但我认为随着时间推移会有修正，智能会更接近感知。我们将把AI分解成更小的子系统，彼此通信并形成一个元系统。
GUILLAUME VERDON (01:10:00) … that are hierarchical. And at each level, the hierarchy are local, perform the best by far, and are far more fault-tolerant. The reason is, if you have a non-local decoder, then you have one fault at this control node and the whole system crashes. Similarly to if you have one CEO that everybody reports to and that CEO goes on vacation, the whole company comes to a crawl. To me, I think that yes, we’re seeing a tendency towards centralization of AI, but I think there’s going to be a correction over time, where intelligence is going to go closer to the perception. And we’re going to break up AI into smaller subsystems that communicate with one another and form a meta system.
Lex Fridman (01:10:56) 如果你看看今天世界上的层级结构，有国家，那些都是层级的。但相对于彼此，国家是无政府的，所以这是一种无政府状态。
LEX FRIDMAN (01:10:56) If you look at the hierarchies that are in the world today, there’s nations and those all hierarchical. But in relation to each other, nations are anarchic, so it’s an anarchy.
Guillaume Verdon (01:11:06) 嗯。
GUILLAUME VERDON (01:11:06) Mm-hmm.
Lex Fridman (01:11:08) 你预见这样一个世界吗，在那里没有一个总体的……你怎么称呼它？集中式控制论控制？
LEX FRIDMAN (01:11:08) Do you foresee a world like this, where there’s not a over… What’d you call it? A centralized cybernetic control?
Guillaume Verdon (01:11:17) 集中式控制中心。对。
GUILLAUME VERDON (01:11:17) Centralized locus of control. Yeah.
Lex Fridman (01:11:21) 你说那是次优的？
LEX FRIDMAN (01:11:21) That’s suboptimal, you’re saying?
Guillaume Verdon (01:11:22) 对。
GUILLAUME VERDON (01:11:22) Yeah.
Lex Fridman (01:11:23) 所以，在最顶层总会有竞争状态？
LEX FRIDMAN (01:11:23) So, it would be always a state of competition at the very top level?
Guillaume Verdon (01:11:27) 对。就像在公司里，你可能有两个部门在做类似的技术并相互竞争，然后你剪掉表现不佳的那个。这是一个树的选择过程，或者一个产品被砍掉，然后整个组织被解雇。这个尝试新事物和淘汰不奏效的旧事物的过程，正是给我们适应性的东西，帮助我们收敛到最好的技术和最该做的事情。
GUILLAUME VERDON (01:11:27) Yeah. Yeah. Just like in a company, you may have two units working on similar technology and competing with one another, and you prune the one that performs not as well. That’s a selection process for a tree, or a product gets killed and then a whole org gets fired. This process of trying new things and shedding old things that didn’t work, it’s what gives us adaptability and helps us converge on the technologies and things to do that are most good.
Lex Fridman (01:12:04) 我只是希望没有一种对AGI独特而对人类不独特的失败模式，因为你现在主要描述的是人类系统。
LEX FRIDMAN (01:12:04) I just hope there’s not a failure mode that’s unique to AGI versus humans, because you’re describing human systems mostly right now.
Guillaume Verdon (01:12:11) 对。
GUILLAUME VERDON (01:12:11) Right.
Lex Fridman (01:12:11) 我只是希望当一家公司垄断AGI时，我们会看到与人类相同的情况，也就是另一家公司会涌现出来并开始有效竞争。
LEX FRIDMAN (01:12:11) I just hope when there’s a monopoly on AGI in one company, that we’ll see the same thing we see with humans, which is, another company will spring up and start competing effectively.
Guillaume Verdon (01:12:24) 到目前为止一直是这样。我们有OpenAI。我们有Anthropic。现在，我们有xAI。我们有Meta，甚至是开源的，现在我们有Mistral，它非常有竞争力。这就是资本主义的美妙之处。你不必过于信任任何一方，因为我们总是在每个层面对冲我们的赌注。总有竞争，这对我来说至少是最美好的事情，就是整个系统总是在转变，总是在适应。
GUILLAUME VERDON (01:12:24) That’s been the case so far. We have OpenAI. We have Anthropic. Now, we have xAI. We have Meta even for open source, and now we have Mistral, which is highly competitive. That’s the beauty of capitalism. You don’t have to trust any one party too much because we’re always hedging our bets at every level. There’s always competition and that’s the most beautiful thing to me, at least, is that the whole system is always shifting and always adapting.
Guillaume Verdon (01:12:54) 维持这种活力就是我们避免暴政的方式。确保每个人都能访问这些工具、这些模型，并能为研究做出贡献，就能避免智能暴政——极少数人控制世界的AI并用它来压迫周围的人。
GUILLAUME VERDON (01:12:54) Maintaining that dynamism is how we avoid tyranny. Making sure that everyone has access to these tools, to these models, and can contribute to the research, avoids a neural tyranny where very few people have control over AI for the world and use it to oppress those around them.
量子机器学习 Quantum machine learning Lex Fridman (01:13:23) 当你谈论智能时,你提到了多体量子纠缠。
LEX FRIDMAN (01:13:23) When you were talking about intelligence, you mentioned multipartite quantum entanglement.
Guillaume Verdon (01:13:28) 嗯。
GUILLAUME VERDON (01:13:28) Mm-hmm.
Lex Fridman (01:13:29) 先问一个高层次的问题：你认为什么是智能？当你思考量子力学系统并观察其中发生的某种计算时，你认为宇宙能够进行的那种计算有什么智能之处？而人类大脑能够进行的计算只是其中的一小部分？
LEX FRIDMAN (01:13:29) High-level question first is, what do you think is intelligence? When you think about quantum mechanical systems and you observe some kind of computation happening in them, what do you think is intelligent about the kind of computation the universe is able to do; a small, small inkling of which is the kind of computation a human brain is able to do?
Guillaume Verdon (01:13:52) 我会说智能和计算并不完全是一回事。我认为宇宙确实在进行量子计算。如果你能访问所有自由度和一台非常非常非常大的量子计算机，有很多很多量子比特，比方说，每个普朗克体积有几个量子比特——这差不多是我们拥有的像素——那么你就能在一台足够大的量子计算机上模拟整个宇宙，当然，假设你看的是宇宙的有限体积。我认为至少对我来说，智能是——我回到控制论——感知、预测和控制我们世界的能力。
GUILLAUME VERDON (01:13:52) I would say intelligence and computation aren’t quite the same thing. I think that the universe is very much doing a quantum computation. If you had access to all the degrees of freedom and a very, very, very large quantum computer with many, many, many qubits, let’s say, a few qubits per Planck volume, which is more or less the pixels we have, then you’d be able to simulate the whole universe on a sufficiently large quantum computer, assuming you’re looking at a finite volume, of course, of the universe. I think that at least to me, intelligence is, I go back to cybernetics, the ability to perceive, predict, and control our world.
Guillaume Verdon (01:14:46) 但实际上，现在看来，我们使用的很多智能更多是关于压缩。它是关于操作化信息论。在信息论中，你有分布或系统的熵的概念，熵告诉你，如果你有最优代码，你需要这么多比特来编码这个分布或这个子系统。AI，至少我们今天为LLM和量子所做的方式，非常像试图最小化我们的世界模型与世界之间、与来自世界的分布之间的相对熵。我们在学习，我们在计算空间中搜索以处理世界，以找到那个已经提炼出所有方差、噪声和熵的压缩表示。
GUILLAUME VERDON (01:14:46) But really, nowadays, it seems like a lot of intelligence we use is more about compression. It’s about operationalizing information theory. In information theory, you have the notion of entropy of a distribution or a system, and entropy tells you that you need this many bits to encode this distribution or this subsystem, if you have the most optimal code. AI, at least the way we do it today for LLMs and for quantum, is very much trying to minimize relative entropy between our models of the world and the world, distributions from the world. We’re learning, we’re searching over the space of computations to process the world, to find that compressed representation that has distilled all the variance in noise and entropy.
Guillaume Verdon (01:15:58) 最初，我从黑洞研究进入量子机器学习，因为黑洞的熵非常有趣。某种意义上，它们在物理上是宇宙中密度最高的物体。你无法在空间上比黑洞更密集地打包更多信息。所以我在想，黑洞实际上是如何编码信息的？它们的压缩代码是什么？这让我进入了算法空间，搜索量子代码空间。它也让我实际进入了，你如何从世界获取量子信息？我做过的一些工作，现在是公开的，是量子模数转换。
GUILLAUME VERDON (01:15:58) Originally, I came to quantum machine learning from the study of black holes because the entropy of black holes is very interesting. In a sense, they’re physically the most dense objects in the universe. You can’t pack more information spatially any more densely than in a black hole. And so, I was wondering, how do black holes actually encode information? What is their compression code? That got me into the space of algorithms, to search over space of quantum codes. It got me actually into also, how do you acquire quantum information from the world? Something I’ve worked on, this is public now, is quantum analog digital conversion.
Guillaume Verdon (01:16:50) 你如何从真实世界以叠加态捕获信息而不破坏叠加态，而是为量子计算机数字化来自真实世界的信息？如果你有能力捕获量子信息并学习它的表示，现在你就可以学习可能在其潜在表示中有一些有用信息的压缩表示。我认为我们文明面临的许多问题实际上都超越了这个复杂性障碍。温室效应是一种量子力学效应。化学是量子力学的。核物理是量子力学的。
GUILLAUME VERDON (01:16:50) How do you capture information from the real world in superposition and not destroy the superposition, but digitize for a quantum mechanical computer information from the real world? If you have an ability to capture quantum information and learn representation representations of it, now you can learn compressed representations that may have some useful information in their latent representation. I think that many of the problems facing our civilization are actually beyond this complexity barrier. The greenhouse effect is a quantum mechanical effect. Chemistry is quantum mechanical. Nuclear physics is quantum mechanical.
Guillaume Verdon (01:17:43) 很多生物学、蛋白质折叠等都受量子力学影响。所以，解锁用量子计算机和量子AI增强人类智力的能力，对我来说似乎是文明需要发展的基本能力。我花了几年时间做这个，但随着时间推移，我对开始看起来像核聚变的时间线感到厌倦。
GUILLAUME VERDON (01:17:43) A lot of biology and protein folding and so on is affected by quantum mechanics. And so, unlocking an ability to augment human intellect with quantum mechanical computers and quantum mechanical AI seemed to me like a fundamental capability for civilization that we needed to develop. I spent several years doing that, but over time, I grew weary of the timelines that were starting to look like nuclear fusion.
Lex Fridman (01:18:17) 我可以问一个高层次的问题，也许通过定义的方式，通过解释的方式：什么是量子计算机，什么是量子机器学习？
LEX FRIDMAN (01:18:17) One high-level question I can ask is maybe by way of definition, by way of explanation, what is a quantum computer and what is quantum machine learning?
Guillaume Verdon (01:18:27) 量子计算机实际上就是一个量子力学系统，我们对它有足够的控制，它可以保持其量子力学状态。量子力学是自然界在非常小的尺度上的行为方式，当事物非常小或非常冷时，它实际上比概率论更基础。我们习惯于事物是这个或那个，但我们不习惯用叠加态思考，因为，嗯，我们的大脑做不到。所以，我们必须把量子力学世界翻译成，比如说，线性代数来理解它。不幸的是，这种翻译平均而言是指数级低效的。你必须用非常大的矩阵来表示事物。但实际上，你可以用很多东西制造量子计算机，我们已经看到各种各样的玩家，从中性原子、囚禁离子、超导金属光子，在不同频率上。
GUILLAUME VERDON (01:18:27) A quantum computer really is a quantum mechanical system, over which we have sufficient control, and it can maintain its quantum mechanical state. And quantum mechanics is how nature behaves at the very small scales, when things are very small or very cold, and it’s actually more fundamental than probability theory. We’re used to things being this or that, but we’re not used to thinking in superpositions because, well, our brains can’t do that. So, we have to translate the quantum mechanical world to, say, linear algebra to grok it. Unfortunately, that translation is exponentially inefficient on average. You have to represent things with very large matrices. But really, you can make a quantum computer out of many things, and we’ve seen all sorts of players, from neutral atoms, trapped ions, superconducting metal photons at different frequencies.
Guillaume Verdon (01:19:38) 我认为你可以用很多东西制造量子计算机。但对我来说，真正有趣的是量子机器学习既是关于用量子计算机理解量子力学世界，所以把物理世界嵌入AI表示，也是量子计算机工程是把AI算法嵌入物理世界。把物理世界嵌入AI、把AI嵌入物理世界的这种双向性，物理和AI之间的这种共生关系，实际上这就是我追求的核心，即使到今天，在量子计算之后。它仍然在这个将物理和AI真正融合的旅程中。
GUILLAUME VERDON (01:19:38) I think you could make a quantum computer out of many things. But to me, the thing that was really interesting was both quantum machine learning was about understanding the quantum mechanical world with quantum computers, so embedding the physical world into AI representations, and quantum computer engineering was embedding AI algorithms into the physical world. This bi-directionality of embedding physical world into AI, AI into the physical world, this symbiosis between physics and AI, really that’s the core of my quest really, even to this day, after quantum computing. It’s still in this journey to merge really physics and AI.
Lex Fridman (01:20:29) 量子机器学习是一种在保持自然的量子力学方面真实的自然表示上进行机器学习的方式？
LEX FRIDMAN (01:20:29) Quantum machine learning is a way to do machine learning on a representation of nature that stays true to the quantum mechanical aspect of nature?
Guillaume Verdon (01:20:43) 对，它是学习量子力学表示。那将是量子深度学习。或者，你可以尝试在量子计算机上做经典机器学习。我不建议这样做，因为你可能会有一些加速，但很多时候，加速伴随着巨大的成本。使用量子计算机非常昂贵。
GUILLAUME VERDON (01:20:43) Yeah, it’s learning quantum mechanical representations. That would be quantum deep learning. Alternatively, you can try to do classical machine learning on a quantum computer. I wouldn’t advise it because you may have some speed-ups, but very often, the speed-ups come with huge costs. Using a quantum computer is very expensive.
Guillaume Verdon (01:21:08) 为什么？因为你假设计算机在绝对零度下运行,而宇宙中没有物理系统能达到那个温度。你必须做的是我一直提到的，这个量子纠错过程，它实际上是一个算法冰箱。它试图把熵从系统中抽出来，试图让它更接近0K。当你计算在量子计算机上做深度学习需要多少资源时，比如说，做经典深度学习，会有如此巨大的开销，不值得。这就像考虑用火箭穿越城市，进入轨道再返回来运送东西。没有意义。就用送货卡车。
GUILLAUME VERDON (01:21:08) Why is that? Because you assume the computer is operating at zero temperature, which no physical system in the universe can achieve that temperature. What you have to do is what I’ve been mentioning, this quantum error correction process, which is really an algorithmic fridge. It’s trying to pump entropy out of the system, trying to get it closer to zero temperature. When you do the calculations of how many resources it would take to, say, do deep learning on a quantum computer, classical deep learning, there’s such a huge overhead, it’s not worth it. It’s like thinking about shipping something across a city using a rocket and going to orbit and back. It doesn’t make sense. Just use a delivery truck.
Lex Fridman (01:21:53) 你能用量子深度学习弄清楚、预测、理解什么样的东西,而用深度学习做不到？所以，将量子力学系统纳入学习过程？
LEX FRIDMAN (01:21:53) What kind of stuff can you figure out, can you predict, can you understand with quantum deep learning that you can’t with deep learning? So, incorporating quantum mechanical systems into the learning process?
Guillaume Verdon (01:22:05) 我认为这是一个很好的问题。从根本上说，任何具有足够量子力学关联、对经典表示来说很难捕获的系统，量子力学表示应该比纯经典表示有优势。问题是，哪些系统有足够的、非常量子的关联？但这也是，哪些系统仍然与工业相关？这是一个大问题。人们倾向于化学、核物理。我实际上从事过处理来自量子传感器的输入。如果你有一个量子传感器网络，它们捕获了世界的量子力学图像，以及如何后处理，那就成为一种量子形式的机器感知。例如，费米实验室有一个项目探索用这些量子传感器探测暗物质。对我来说，这与我从小就想理解宇宙的追求是一致的。所以，有一天，我希望我们能有非常大的量子传感器网络，帮助我们窥视宇宙的最早期部分。例如，LIGO是一个量子传感器。它只是一个非常大的。所以，是的，我会说量子机器感知、模拟、理解量子模拟，类似于AlphaFold。AlphaFold理解了蛋白质配置的概率分布。你可以用量子机器学习更有效地理解电子配置的量子分布。
GUILLAUME VERDON (01:22:05) I think that’s a great question. Fundamentally, it’s any system that has sufficient quantum mechanical correlations that are very hard to capture for classical representations. Then, there should be an advantage for a quantum mechanical representation over a purely classical one. The question is, which systems have sufficient correlations that are very quantum? But it’s also, which systems are still relevant to industry? That’s a big question. People are leaning towards chemistry, nuclear physics. I’ve worked on actually processing inputs from quantum sensors. If you have a network of quantum sensors, they’ve captured a quantum mechanical image of the world and how to post-process that, that becomes a quantum form of machine perception. For example, Fermilab has a project exploring detecting dark matter with these quantum sensors. To me, that’s in alignment with my quest to understand the universe ever since I was a child. And so, someday, I hope that we can have very large networks of quantum sensors that help us peer into the earliest parts of the universe. For example, the LIGO is a quantum sensor. It’s just a very large one. So, yeah, I would say quantum machine perception, simulations, grokking quantum simulations, similar to AlphaFold. AlphaFold understood the probability distribution over configurations of proteins. You can understand quantum distributions over configurations of electrons more efficiently with quantum machine learning.
Lex Fridman (01:23:53) 你合著了一篇题为《量子深度学习的通用训练算法》的论文。那涉及Baqprop，带Q。做得很好，先生。做得很好。它是如何工作的？你能提一些有趣的方面吗，Baqprop以及我们为经典机器学习所知的一些东西如何转移到量子机器学习？
LEX FRIDMAN (01:23:53) You co-authored a paper titled A Universal Training Algorithm for Quantum Deep Learning. That involves Baqprop, with a Q. Very well done, sir. Very well done. How does it work? Is there some interesting aspects you can just mention on how Baqprop and some of these things we know for classical machine learning transfer over to the quantum machine learning?
Guillaume Verdon (01:24:19) 是的。那是一篇古怪的论文。那是我在量子深度学习领域的第一批论文之一。每个人都在说：”哦，我认为深度学习会被量子计算机加速。”我说：”好吧，预测未来的最好方法就是发明它。所以，这里有一篇100页的论文，祝你愉快。”本质上，量子计算通常是，你把可逆操作嵌入量子计算。
GUILLAUME VERDON (01:24:19) Yeah. That was a funky paper. That was one of my first papers in quantum deep learning. Everybody was saying, “Oh, I think deep learning is going to be sped up by quantum computers.” I was like, “ Well, the best way to predict the future is to invent it. So, here’s a 100-page paper, have fun.” Essentially, quantum computing is usually, you embed reversible operations into a quantum computation.
Guillaume Verdon (01:24:47) 那里的技巧是做一个前馈操作并做我们所说的相位踢（phase kick）。但实际上，它只是一个力踢（force kick）。你只是用与你希望优化的损失函数成正比的某种力踢系统。然后，通过执行反计算，你从参数的叠加态开始，这相当古怪。现在，你不只是有参数的一个点，你有许多潜在参数的叠加态。我们的目标是——
GUILLAUME VERDON (01:24:47) The trick there was to do a feedforward operation and do what we call a phase kick. But really, it’s just a force kick. You just kick the system with a certain force that is proportional to your loss function that you wish to optimize. And then, by performing uncomputation, you start with a superposition over parameters, which is pretty funky. Now, you don’t have just a point for parameters, you have a superposition over many potential parameters. Our goal is-
Lex Fridman (01:25:24) 是用相位踢以某种方式调整参数吗？
LEX FRIDMAN (01:25:24) Is using phase kick somehow to adjust the parameters?
Guillaume Verdon (01:25:28) 对。因为相位踢模拟了让参数空间像n维中的粒子，你试图在神经网络的损失景观中获得薛定谔方程、薛定谔动力学。你做一个算法来诱导这个相位踢，这涉及一个前馈、一个踢。然后，当你反计算前馈时，那么所有这些相位踢和这些力的误差会反向传播并击中各层中的每一个参数。
GUILLAUME VERDON (01:25:28) Right. Because phase kicks emulate having the parameter space be like a particle in end dimensions, and you’re trying to get the Schrödinger equation, Schrödinger dynamics, in the lost landscape of the neural network. You do an algorithm to induce this phase kick, which involves a feedforward, a kick. And then, when you uncompute the feedforward, then all the errors in these phase kicks and these forces back- propagate and hit each one of the parameters throughout the layers.
Guillaume Verdon (01:26:04) 如果你把这个与动能的模拟交替进行，那么它就像一个在n维中移动的粒子，一个量子粒子。原则上的优势是它可以在景观中穿隧并找到对于随机优化器来说很难找到的新最优解。但同样，这是一个理论性的东西，在实践中，至少以我们目前计划的量子计算机架构，这样的算法运行起来会极其昂贵。
GUILLAUME VERDON (01:26:04) If you alternate this with an emulation of kinetic energy, then it’s like a particle moving in end dimensions, a quantum particle. The advantage in principle would be that it can tunnel through the landscape and find new optima that would’ve been difficult for stochastic optimizers. But again, this is a theoretical thing, and in practice with at least the current architectures for quantum computers that we have planned, such algorithms would be extremely expensive to run.
量子计算机 Quantum computer Lex Fridman (01:26:41) 也许这是一个问不同领域之间区别的好地方，你曾涉足的领域。所以，数学、物理、工程，还有创业，堆栈的不同层次。我认为你在这里谈论的很多东西在数学方面有一点，也许物理几乎在理论中工作。
LEX FRIDMAN (01:26:41) Maybe this is a good place to ask the difference between the different fields that you’ve had a toe in. So, mathematics, physics, engineering, and also entrepreneurship, the different layers of the stack. I think a lot of the stuff you’re talking about here is a little bit on the math side, maybe physics almost working in theory.
Guillaume Verdon (01:27:03) 嗯。
GUILLAUME VERDON (01:27:03) Mm-hmm.
Lex Fridman (01:27:03) 数学、物理、工程和为量子计算、量子机器学习制造产品之间有什么区别？
LEX FRIDMAN (01:27:03) What’s the difference between math, physics, engineering, and making a product for a quantum computing for quantum machine learning?
Guillaume Verdon (01:27:14) 是的。TensorFlow Quantum项目的一些原始团队成员，我们在学校开始的，在滑铁卢大学，有我自己。最初，我是一名物理学家、应用数学家。我们有一名计算机科学家，我们有一名机械工程师，然后我们有一名物理学家。那主要是实验性的。组建非常跨学科的团队并弄清楚如何沟通和分享知识，真的是做这种跨学科工程工作的关键。
GUILLAUME VERDON (01:27:14) Yeah. Some of the original team for the TensorFlow Quantum project, which we started in school, at University of Waterloo, there was myself. Initially, I was a physicist, applied mathematician. We had a computer scientist, we had a mechanical engineer, and then we had a physicist. That was experimental primarily. Putting together teams that are very cross-disciplinary and figuring out how to communicate and share knowledge is really the key to doing this interdisciplinary engineering work.
Guillaume Verdon (01:27:51) 有很大的区别。在数学中，你可以为了数学而探索数学。在物理学中，你是在应用数学来理解我们周围的世界。在工程中，你试图黑掉世界。你试图找到如何应用我知道的物理学，我对世界的知识，来做事情。
GUILLAUME VERDON (01:27:51) There is a big difference. In mathematics, you can explore mathematics for mathematics’ sake. In physics, you’re applying mathematics to understand the world around us. And in engineering, you’re trying to hack the world. You’re trying to find how to apply the physics that I know, my knowledge of the world, to do things.
Lex Fridman (01:28:11) 嗯，特别是在量子计算中，我认为工程上有很多限制。它似乎非常困难。
LEX FRIDMAN (01:28:11) Well, in quantum computing in particular, I think there’s just a lot of limits to engineering. It just seems to be extremely hard.
Guillaume Verdon (01:28:17) 是的。
GUILLAUME VERDON (01:28:17) Yeah.
Lex Fridman (01:28:18) 所以在理论上用数学探索量子计算、量子机器学习有很多价值。我想问一个问题是，为什么建造量子计算机如此困难？你对将这些想法付诸实践的时间线有什么看法？
LEX FRIDMAN (01:28:18) So, there’s a lot of value to be exploring quantum computing, quantum machine learning in theory with math. I guess one question is, why is it so hard to build a quantum computer? What’s your view of timelines in bringing these ideas to life?
Guillaume Verdon (01:28:43) 对。我认为我公司的一个总体主题是，我们有一些……有一种从量子计算的大规模流出，我们正在转向不是量子的更广泛的基于物理的AI。所以，这给了你一个提示。
GUILLAUME VERDON (01:28:43) Right. I think that an overall theme of my company is that we have folks that are… There’s a sort of exodus from quantum computing and we’re going to broader physics-based AI that is not quantum. So, that gives you a hint.
Lex Fridman (01:29:00) 我们应该说你的公司名字是Extropic？
LEX FRIDMAN (01:29:00) We should say the name of your company is Extropic?
Guillaume Verdon (01:29:03) Extropic，没错。我们做基于物理的AI，主要基于热力学，而不是量子力学。但本质上，量子计算机非常难以建造，因为你必须诱导这个零开温度的信息子空间。做到这一点的方法是通过编码信息，你在代码中编码代码，在代码中编码代码，在代码中编码代码。需要大量冗余来做这个纠错，但最终，它是一种算法冰箱，真的。它只是把熵从虚拟的、去局域化的子系统中抽出来，该子系统代表你的”逻辑量子比特”，也就是你实际想运行量子力学程序的有效载荷量子比特。它非常困难，因为为了扩展你的量子计算机，你需要每个组件都具有足够的质量才值得。因为如果你试图做这个纠错，这个量子纠错过程，在每个量子比特和你对它们的控制中，如果它不够充分，就不值得扩展。你实际上添加的错误比你移除的更多。有一个阈值的概念，即如果你的量子比特在控制方面具有足够的质量，那么扩展实际上是值得的。实际上，近年来，人们一直在跨越阈值，它开始变得值得。
GUILLAUME VERDON (01:29:03) Extropic, that’s right. We do physics-based AI, primarily based on thermodynamics, rather than quantum mechanics. But essentially, a quantum computer is very difficult to build because you have to induce this zero temperature subspace of information. The way to do that is by encoding information, you encode a code within a code, within a code, within a code. There’s a lot of redundancy needed to do this error correction, but ultimately, it’s a sort of algorithmic refrigerator, really. It’s just pumping out entropy out of the subsystem that is virtual and delocalized that represents your “logical qubits”, aka the payload quantum bits in which you actually want to run your quantum mechanical program. It’s very difficult because in order to scale up your quantum computer, you need each component to be of sufficient quality for it to be worth it. Because if you try to do this error correction, this quantum error correction process, in each quantum bit and your control over them, if it’s insufficient, it’s not worth scaling up. You’re actually adding more errors than you remove. There’s this notion of a threshold where if your quantum bits are sufficient quality in terms of your control over them, it’s actually worth scaling up. Actually, in recent years, people have been crossing the threshold and it’s starting to be worth it.
Guillaume Verdon (01:30:38) 这只是一个非常漫长的工程跋涉，但最终，对我来说真正疯狂的是我们对这些系统有多么精致的控制水平。这实际上相当疯狂。人们正在跨越……他们正在实现里程碑。只是总的来说，媒体总是走在技术前面。炒作有点太多了。这对筹款有好处，但有时它会导致寒冬。这是炒作周期。我个人对10年、15年时间尺度上的量子计算持乐观态度，但我认为在此期间可以做其他的探索。我认为它现在掌握在好手中。
GUILLAUME VERDON (01:30:38) It’s just a very long slog of engineering, but ultimately, it’s really crazy to me how much exquisite level of control we have over these systems. It’s actually quite crazy. And people are crossing… They’re achieving milestones. It’s just in general, the media always gets ahead of where the technology is. There’s a bit too much hype. It’s good for fundraising, but sometimes it causes winters. It’s the hype cycle. I’m bullish on quantum computing on a 10, 15-year timescale personally, but I think there’s other quests that can be done in the meantime. I think it’s in good hands right now.
Lex Fridman (01:31:22) 嗯，让我探索一些不同的美丽想法，无论大小，在量子计算中可能从记忆中跳出来的，当你合著了一篇题为《通过Qudit探针实现渐近无限量子能量传送》的论文时。出于好奇，你能解释一下qudit与qubit相比是什么吗？
LEX FRIDMAN (01:31:22) Well, let me just explore different beautiful ideas, large or small, in quantum computing that might jump out at you from memory when you co-authored a paper titled Asymptotically Limitless Quantum Energy Teleportation via Qudit Probes. Just out of curiosity, can you explain what a qudit is versus a qubit?
Guillaume Verdon (01:31:45) 是的。它是一个D态量子比特。
GUILLAUME VERDON (01:31:45) Yeah. It’s a D-state qubit.
Lex Fridman (01:31:49) 它是多维的？
LEX FRIDMAN (01:31:49) It’s a multidimensional?
Guillaume Verdon (01:31:50) 多维的，对。它就像，嗯，你能有一个量子力学的整数浮点概念吗？这是我必须思考的东西。我认为那项研究是后来量子模数转换工作的前兆。那很有趣，因为在我硕士期间，我试图理解真空、空无的能量和纠缠。空无具有能量，这说起来非常奇怪。我们的宇宙学方程与我们对涨落中存在多少量子能量的计算不匹配。
GUILLAUME VERDON (01:31:50) Multidimensional, right. It’s like, well, can you have a notion of an integer floating point that is quantum mechanical? That’s something I’ve had to think about. I think that research was a precursor to later work on quantum analog digital conversion. There was interesting because during my masters, I was trying to understand the energy and entanglement of the vacuum of emptiness. Emptiness has energy, which is very weird to say. Our equations of cosmology don’t match our calculations for the amount of quantum energy there is in the fluctuations.
Guillaume Verdon (01:32:36) 我试图黑进真空的能量，而现实是你不能直接黑进它。它在技术上不是自由能。你对涨落的无知意味着你无法提取能量。但就像股市一样，如果你有一只随时间相关的股票，真空实际上是相关的。如果你在一个点测量了真空，你获得了信息。如果你把那个信息传达到另一个点，你可以推断真空处于什么配置，达到某种精度，并统计地平均提取一些能量。所以，你”传送了能量”。
GUILLAUME VERDON (01:32:36) I was trying to hack the energy of the vacuum, and the reality is that you can’t just directly hack it. It’s not technically free energy. Your lack of knowledge of the fluctuations means you can’t extract the energy. But just like the stock market, if you have a stock that’s correlated over time, the vacuum’s actually correlated. If you measured the vacuum at one point, you acquired information. If you communicated that information to another point, you can infer what configuration the vacuum is in to some precision and statistically extract, on average, some energy there. So, you’ve “teleported energy”.
Guillaume Verdon (01:33:18) 对我来说，这很有趣，因为你可以创造负能量密度的口袋，也就是低于真空的能量密度，这非常奇怪，因为我们不理解真空如何（传播？）引力。有一些理论认为真空或时空本身的画布实际上是由量子纠缠制成的画布。我在研究如何在局部降低真空的能量会增加量子纠缠，这非常古怪。
GUILLAUME VERDON (01:33:18) To me, that was interesting because you could create pockets of negative-energy density, which is energy density that is below the vacuum, which is very weird because we don’t understand how the vacuum gravitates. There are theories where the vacuum or the canvas of space-time itself is really a canvas made out of quantum entanglement. I was studying how decreasing energy of vacuum locally increases quantum entanglement, which is very funky.
Guillaume Verdon (01:33:58) 这里的事情是，如果你对UAP和诸如此类的奇怪理论感兴趣，你可以试着想象它们在周围。它们会如何推动自己？它们会如何超越光速？你需要一种负能量密度。对我来说，我尽了我的努力，试图黑进真空的能量，并达到物理定律允许的极限。但那里有各种警告，你显然不能提取比你投入的更多。
GUILLAUME VERDON (01:33:58) The thing there is that, if you’re into to weird theories about UAPs and whatnot, you could try to imagine that they’re around. And how would they propel themselves? How would they go faster than the speed of light? You would need a sort of negative energy density. To me, I gave it the old college try, trying to hack the energy of vacuum and hit the limits allowable by the laws of physics. But there’s all sorts of caveats there where you can’t extract more than you’ve put in, obviously.
Lex Fridman (01:34:41) 但你是说传送能量是可能的，因为你可以在一个地方提取信息，然后基于此，对另一个地方做出某种预测？
LEX FRIDMAN (01:34:41) But you’re saying it’s possible to teleport the energy because you can extract information one place and then make, based on that, some kind of prediction about another place?
Guillaume Verdon (01:34:56) 嗯。
GUILLAUME VERDON (01:34:56) Mm-hmm.
Lex Fridman (01:34:57) 我不确定该如何理解这个。
LEX FRIDMAN (01:34:57) I’m not sure what to make of that.
Guillaume Verdon (01:34:58) 是的，这是物理定律允许的。但现实是关联会随距离衰减。
GUILLAUME VERDON (01:34:58) Yeah, it’s allowable by the laws of physics. The reality though is that the correlations decay with distance.
Lex Fridman (01:35:06) 当然。
LEX FRIDMAN (01:35:06) Sure.
Guillaume Verdon (01:35:06) 所以，你将不得不在离你提取它的地方不太远的地方付出代价。
GUILLAUME VERDON (01:35:06) And so, you’re going to have to pay the price not too far away from where you extract it.
（PART II 完）
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【e/acc】有效加速主义、量子热力学与AI未来 | 物理学家、e/acc运动创始人Guillaume Verdon与Lex Fridman播客实录 | 中英文完整版精译 I
书童按：本篇是Guillaume Verdon接受Lex Fridman播客采访的实录。Verdon是物理学家、应用数学家与量子机器学习先驱，曾在谷歌从事量子计算研究，后创立Extropic公司，致力于为生成式AI打造基于物理原理的计算硬件。他亦是X平台匿名账号@BasedBeffJezos背后的真实人物，有效加速主义（e/acc）运动的联合创始人。e/acc以热力学与信息论为哲学根基，主张以技术快速进步作为人类伦理最优选择，正面对抗”AI末日论”代表的减速主义思潮。访谈纵横于量子计算与非平衡热力学的哲学意涵、匿名言论与思想自由、AI监管与市场力量的博弈、通用智能的重新定义等议题，视野开阔，锋芒毕现。初稿采用Claude API机器翻译及排版，书童仅做简单校对及批注，将分四部分发布，以飨诸君。
Guillaume Verdon：有效加速主义、热力学与量子智能 | Lex Fridman播客 Guillaume Verdon: Effective Accelerationism, Thermodynamics, and Quantum Intelligence | Lex Fridman Podcast 引言 Introduction Lex Fridman (00:00:00) 以下是与Guillaume Verdon的对话。他就是X平台上曾经匿名的账号@BasedBeffJezos背后的人。这两重身份因《福布斯》一篇题为《@BasedBeffJezos是谁？科技精英e/acc运动的领袖》的曝光文章被强行合二为一。让我来介绍同一个大脑里共存的这两重身份。其一：Guillaume是物理学家、应用数学家、量子机器学习研究者兼工程师，在量子机器学习方向取得博士学位，曾供职于谷歌量子计算团队，后创立Extropic公司，为生成式AI打造基于物理原理的计算硬件。
LEX FRIDMAN (00:00:00) The following is a conversation with Guillaume Verdon, the man behind the previously anonymous account @BasedBeffJezos on X. These two identities were merged by a doxxing article in Forbes titled, Who Is @BasedBeffJezos, The Leader Of The Tech Elite’s E/Acc Movement? So let me describe these two identities that coexist in the mind of one human. Identity number one, Guillaume, is a physicist, applied mathematician, and quantum machine learning researcher and engineer receiving his PhD in quantum machine learning, working at Google on quantum computing, and finally launching his own company called Extropic that seeks to build physics-based computing hardware for generative AI.
Lex Fridman (00:00:47) 其二：X平台上的Beff Jezos是有效加速主义运动的创始人——常缩写为e/acc——主张将推动技术快速进步作为人类伦理上的最优选择。其拥护者深信AI进步是最强大的社会均衡器，理应全力推进。e/acc追随者自视为谨慎派的相反力量——后者认为AI高度不可预测、潜在危险、亟需监管。他们管对手叫”末日派”或”减速派”（decel）。用Beff自己的话说：”e/acc是一种模因化的乐观主义病毒。”
LEX FRIDMAN (00:00:47) Identity number two, Beff Jezos on X is the creator of the effective accelerationism movement, often abbreviated as e/acc, that advocates for propelling rapid technological progress as the ethically optimal course of action for humanity. For example, its proponents believe that progress in AI is a great social equalizer, which should be pushed forward. e/acc followers see themselves as a counterweight to the cautious view that AI is highly unpredictable, potentially dangerous, and needs to be regulated. They often give their opponents the labels of quote, “doomers or decels” short for deceleration, as Beff himself put it, “e/acc is a mimetic optimism virus.”
Lex Fridman (00:01:37) 这场运动的传播风格一贯偏向梗图和搞笑，但背后有扎实的思想根基，我们会在对话中深入挖掘。说到梗——本人勉强算个荒诞美学的业余爱好者。我先后和Jeff Bezos、Beff Jezos做了背靠背的访谈，这绝非巧合。对话中会聊到，Beff视Jeff为当今最重要的在世人类之一，而我则纯粹欣赏这里头的荒诞之美和幽默感。这里是Lex Fridman播客，如您愿意支持，请查看简介中的赞助商信息。闲话少叙，朋友们，有请Guillaume Verdon。
LEX FRIDMAN (00:01:37) The style of communication of this movement leans always toward the memes and the lols, but there is an intellectual foundation that we explore in this conversation. Now, speaking of the meme, I am to a kind of aspiring connoisseur of the absurd. It is not an accident that I spoke to Jeff Bezos and Beff Jezos back to back. As we talk about Beff admires Jeff as one of the most important humans alive, and I admire the beautiful absurdity and the humor of it all. This is the Lex Fridman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here’s Guillaume Verdon.
Beff Jezos Beff Jezos Lex Fridman (00:02:23) 先把身份这件事捋清楚。你叫Guillaume Verdon，Gill，但你同时也是X上匿名账号@BasedBeffJezos背后的人。Guillaume Verdon这边：量子计算学者、物理学家、应用数学家；@BasedBeffJezos那边：本质上是个发起了一场运动、背后有哲学体系的梗图账号。能不能展开聊聊这两个角色——性格、沟通风格、哲学理念有什么不同？
LEX FRIDMAN (00:02:23) Let’s get the facts of identity down first. Your name is Guillaume Verdon, Gill, but you’re also behind the anonymous account on X called @BasedBeffJezos. So first, Guillaume Verdon, you’re a quantum computing guy, physicist, applied mathematician, and then @BasedBeffJezos is basically a meme account that started a movement with a philosophy behind it. So maybe just can you linger on who these people are in terms of characters, in terms of communication styles, in terms of philosophies?
Guillaume Verdon (00:02:58) 说说我的主要身份吧。打小起我就想搞清楚万物之理，想理解宇宙。这条路把我领进了理论物理，最终试图回答那些终极命题——我们为何在此？我们将往何处？由此我开始研究信息论，从信息的视角理解物理，把宇宙看作一台巨大的计算机。在黑洞物理研究到一定深度后，我意识到自己不仅想理解宇宙如何计算，更想”像自然那样去计算”——造出受自然启发的计算机，也就是基于物理的计算机。这把我带进了量子计算领域：首先是模拟自然，再就是在我的工作中，学习能在量子计算机上运行的自然表示。
GUILLAUME VERDON (00:02:58) I mean, with my main identity, I guess ever since I was a kid, I wanted to figure out the theory of everything, to understand the universe. And that path led me to theoretical physics, eventually trying to answer the big questions of why are we here? Where are we going? And that led me to study information theory and try to understand physics from the lens of information theory, understand the universe as one big computation. And essentially after reaching a certain level studying black hole physics, I realized that I wanted to not only understand how the universe computes, but sort of compute like nature and figure out how to build and apply computers that are inspired by nature. So physics-based computers. And that sort of brought me to quantum computing as a field of study to first of all, simulate nature. And in my work it was to learn representations of nature that can run on such computers.
Guillaume Verdon (00:04:17) 如果让AI用自然的方式思考，它们就能更精准地表征自然。至少这是驱使我成为量子机器学习领域早期探索者的核心命题——怎样在量子计算机上做机器学习，怎样把智能的概念延伸到量子领域。怎样捕获和理解现实世界的量子力学数据？怎样学习世界的量子力学表示？用什么样的计算机来运行和训练？怎样实现？这些就是我要回答的问题。而说到底，我经历了一次信仰危机。最初，跟每个物理学家一样，入行时都想用几个方程写尽宇宙，当那个故事里的英雄。
GUILLAUME VERDON (00:04:17) So if you have AI representations that think like nature, then they’ll be able to more accurately represent it. At least that was the thesis that brought me to be an early player in the field called quantum machine learning. So how to do machine learning on quantum computers and really sort of extend notions of intelligence to the quantum realm. So how do you capture and understand quantum mechanical data from our world? And how do you learn quantum mechanical representations of our world? On what kind of computer do you run these representations and train them? How do you do so? And so that’s really the questions I was looking to answer because ultimately I had a sort of crisis of faith. Originally, I wanted to figure out as every physicist does at the beginning of their career, a few equations that describe the whole universe and sort of be the hero of the story there.
Guillaume Verdon (00:05:28) 但后来我想通了：用机器增强我们自身，增强我们感知、预测和掌控世界的能力，这才是正路。于是我离开理论物理，转入量子计算和量子机器学习。在那些年里，我始终觉得拼图还差一块。我们理解世界、计算世界、思考世界的方式，都少了点什么。看物理尺度的话：极小尺度上，量子力学说了算；极大尺度上，一切是确定性的，统计涨落已被抹平。我确确实实坐在这张椅子上，不是叠加在东西南北飘忽不定。极小尺度上倒是有叠加态、有干涉效应。但在介观尺度——日常生活的尺度，蛋白质、生物体、气体、液体所在的尺度——物质其实是热力学性质的，在涨落。
GUILLAUME VERDON (00:05:28) But eventually I realized that actually augmenting ourselves with machines, augmenting our ability to perceive, predict, and control our world with machines is the path forward. And that’s what got me to leave theoretical physics and go into quantum computing and quantum machine learning. And during those years I thought that there was still a piece missing. There was a piece of our understanding of the world and our way to compute and our way to think about the world. And if you look at the physical scales, at the very small scales, things are quantum mechanical, and at the very large scales, things are deterministic. Things have averaged out. I’m definitely here in this seat. I’m not in a super position over here and there. At the very small scales, things aren’t super position. They can exhibit interference effects. But at the meso scales, the scales that matter for day-to-day life and the scales of proteins, of biology, of gases, liquids and so on, things are actually thermodynamical, they’re fluctuating.
Guillaume Verdon (00:06:46) 在量子计算和量子机器学习领域干了大约八年后，我突然开窍了——我一直在极大和极小之间找答案。做过一点量子宇宙学——研究宇宙从哪来、往哪去；研究黑洞物理、量子引力的极端情形，也就是能量密度高到量子力学和引力同时登场的地方。典型场景就是黑洞和极早期宇宙——量子力学与相对论的交界地带。
GUILLAUME VERDON (00:06:46) And after I guess about eight years and quantum computing and quantum machine learning, I had a realization that I was looking for answers about our universe by studying the very big and the very small. I did a bit of quantum cosmology. So that’s studying the cosmos, where it’s going, where it came from. You study black hole physics, you study the extremes in quantum gravity, you study where the energy density is sufficient for both quantum mechanics and gravity to be relevant. And the sort of extreme scenarios are black holes and the very early universe. So there’s the sort of scenarios that you study the interface between quantum mechanics and relativity.
Guillaume Verdon (00:07:42) 可我一直盯着两端的极端，却漏掉了”中间那块肉”。日常尺度上量子力学有用、宇宙学有用，但其实没那么直接相关。我们活在中等时空尺度上，这个尺度上最管用的物理理论是热力学——尤其是非平衡热力学。生命本身就是热力学过程，而且是远离平衡态的。我们不是与环境达成热平衡的一锅粒子汤，而是一种拼命维持自身的相干态，靠获取和消耗自由能来续命。差不多在我离开Alphabet前夕，我对宇宙的信念再次发生了转变。我知道自己要造一种基于这类物理的全新计算范式。
GUILLAUME VERDON (00:07:42) And really I was studying these extremes to understand how the universe works and where is it going. But I was missing a lot of the meat in the middle, if you will, because day-to-day quantum mechanics is relevant and the cosmos is relevant, but not that relevant actually. We’re on sort of the medium space and timescales. And there the main theory of physics that is most relevant is thermodynamics, out of equilibrium thermodynamics. Because life is a process that is thermodynamical and it’s out of equilibrium. We’re not just a soup of particles at equilibrium with nature, were a sort of coherent state trying to maintain itself by acquiring free energy and consuming it. And that sort of, I guess another shift in, I guess my faith in the universe happened towards the end of my time at Alphabet. And I knew I wanted to build, well, first of all a computing paradigm based on this type of physics.
Guillaume Verdon (00:08:57) 但与此同时，在把这些想法实验性地应用于社会、经济等方面的过程中，我开了个匿名号——纯粹是为了卸下”说什么都得负责”那种实名账号的压力。一开始只是想拿匿名号来试探想法，没想到直到真正放手，我才发现自己过去把思想空间压缩得有多厉害。某种意义上，限制言论会反向传播为限制思想。开了匿名号之后，感觉脑子里有些变量突然被解锁了，我一下子能在大得多的思想参数空间里探索。
GUILLAUME VERDON (00:08:57) But ultimately just by trying to experiment with these ideas applied to society and economies and much of what we see around us, I started an anonymous account just to relieve the pressure that comes from having an account that you’re accountable for everything you say on. And I started an anonymous account just to experiment with ideas originally because I didn’t realize how much I was restricting my space of thoughts until I sort of had the opportunity to let go. In a sense, restricting your speech back propagates to restricting your thoughts. And by creating an anonymous account, it seemed like I had unclamped some variables in my brain and suddenly could explore a much wider parameter space of thoughts.
Lex Fridman (00:10:00) 在这点上展开一下——这不是很有意思吗？大家很少谈的一件事是：言论一旦受到压力和约束，思想也不知不觉被约束了，尽管逻辑上完全不必如此。我们明明可以在脑子里想任何事，但这种外部压力硬是会在思想四周筑起围墙。
LEX FRIDMAN (00:10:00) Just a little on that, isn’t that interesting that one of the things that people don’t often talk about is that when there’s pressure and constraints on speech, it somehow leads to constraints on thought even though it doesn’t have to. We can think thoughts inside our head, but somehow it creates these walls around thought.
Guillaume Verdon (00:10:23) 没错。这正是我们运动的出发点——我们看到一种趋势：在生活的方方面面压制多样性，无论是思想、经营方式、组织方式还是AI研究路径。我们坚信，保持多样性才能确保系统的适应力。在思想、公司、产品、文化、政府、货币的市场中维持健康竞争，才是正途——因为系统总会自我调适，把资源配置给最有利于增长的那些形态。运动的根本理念，是这样一种洞察：生命是宇宙中一团追逐自由能、渴望生长的火焰，增长是生命的本性。平衡热力学的方程里写得明明白白：那些更擅长获取自由能、散逸更多热量的物质路径，出现的概率呈指数级增高。宇宙本身偏爱某些未来，整个系统自有其天然的走向。
GUILLAUME VERDON (00:10:23) Yep. That’s sort of the basis of our movement is we were seeing a tendency towards constraint, reduction or suppression of variants in every aspect of life, whether it’s thought, how to run a company, how to organize humans, how to do AI research. In general, we believe that maintaining variance ensures that the system is adaptive. Maintaining healthy competition in marketplaces of ideas, of companies, of products, of cultures, of governments, of currencies is the way forward because the system always adapts to assign resources to the configurations that lead to its growth. And the fundamental basis for the movement is this sort of realization that life is a sort of fire that seeks out free energy in the universe and seeks to grow. And that growth is fundamental to life. And you see this in the equations actually of equilibrium thermodynamics. You see that paths of trajectories, of configurations of matter that are better at acquiring free energy and dissipating more heat are exponentially more likely. So the universe is biased towards certain futures, and so there’s a natural direction where the whole system wants to go.
热力学 Thermodynamics Lex Fridman (00:12:21) 热力学第二定律说，宇宙的熵永远在增加，趋向平衡。而你说的是，其中存在一些复杂的、远离平衡的”口袋”。你还说热力学有利于复杂生命的涌现——这类生命通过消耗能量、向外卸载熵来提升自身能力。于是就有了这些逆熵的”口袋”。凭什么你直觉上认为这种口袋的涌现是自然的？
LEX FRIDMAN (00:12:21) So the second law of thermodynamics says that the entropy is always increasing in the universe that’s tending towards an equilibrium. And you’re saying there’s these pockets that have complexity and are out of equilibrium. You said that thermodynamics favors the creation of complex life that increases its capability to use energy to offload entropy. To offload entropy. So you have pockets of non-entropy that tend the opposite direction. Why is that intuitive to you that it’s natural for such pockets to emerge?
Guillaume Verdon (00:12:53) 因为我们产热的效率远超一块同等质量的石头。我们获取自由能、摄入食物、消耗大量电力来维持运转。宇宙想产生更多熵，而让生命继续运转和壮大，恰恰是产熵的最优路径——生命会主动搜寻自由能的”口袋”并将其燃烧殆尽，以维系自身并进一步扩张。这就是生命的底层逻辑。MIT的Jeremy England有一套理论——我深以为然——认为生命的涌现正是源于这种属性。在我看来，这套物理就是支配介观尺度的法则，是量子与宇宙之间缺失的那块拼图，是中间层。热力学主宰着介观尺度。
GUILLAUME VERDON (00:12:53) Well, we’re far more efficient at producing heat than let’s say just a rock with a similar mass as ourselves. We acquire free energy, we acquire food, and we’re using all this electricity for our operation. And so the universe wants to produce more entropy and by having life go on and grow, it’s actually more optimal at producing entropy because it will seek out pockets of free energy and burn it for its sustenance and further growth. And that’s sort of the basis of life. And I mean, there’s Jeremy England at MIT who has this theory that I’m a proponent of, that life emerged because of this sort of property. And to me, this physics is what governs the meso scales. And so it’s the missing piece between the quantum and the cosmos. It’s the middle part. Thermodynamics rules the meso scales.
Guillaume Verdon (00:14:08) 对我来说，无论是从工程角度——设计利用这种物理特性的器件，还是从认知角度——透过热力学棱镜理解世界，过去一年半里两重身份已形成了协同。这也正是两重身份各自浮现的深层原因。一面是，我是受到认可的科学家，正走向创业，要做新型物理AI的先驱；另一面是，我在以物理学家的视角实验性地探索哲学。
GUILLAUME VERDON (00:14:08) And to me, both from a point of view of designing or engineering devices that harness that physics and trying to understand the world through the lens of thermodynamics has been sort of a synergy between my two identities over the past year and a half now. And so that’s really how the two identities emerged. One was kind of, I’m a decently respected scientist, and I was going towards doing a startup in the space and trying to be a pioneer of a new kind of physics-based AI. And as a dual to that, I was sort of experimenting with philosophical thoughts from a physicist standpoint.
Guillaume Verdon (00:14:58) 大约在那段时间——2021年底、2022年初——社会上对未来弥漫着悲观情绪，对技术尤甚。这种悲观在算法加持下病毒式扩散，人们普遍觉得未来不如现在。在我看来，这种”末日心态”是宇宙中一种极具破坏力的力量，因为它具有超迷信性（hyperstitious，书童注：hyperstition，指信念本身能提高其所预言之事发生概率的现象，自我实现的预言）——你越信它，它越可能成真。我因此觉得有责任让人们认清文明的发展轨迹和系统趋向增长的天然本性。物理定律实际上在说：统计上看，未来会更好、更宏大，而我们有能力让它成真。
GUILLAUME VERDON (00:14:58) And ultimately I think that around that time, it was like late 2021, early 2022, I think there was just a lot of pessimism about the future in general and pessimism about tech. And that pessimism was sort of virally spreading because it was getting algorithmically amplified and people just felt like the future is going to be worse than the present. And to me, that is a very fundamentally destructive force in the universe is this sort of doom mindset because it is hyperstitious, which means that if you believe it, you’re increasing the likelihood of it happening. And so felt a responsibility to some extent to make people aware of the trajectory of civilization and the natural tendency of the system to adapt towards its growth. And that actually the laws of physics say that the future is going to be better and grander statistically, and we can make it so.
Guillaume Verdon (00:16:14) 反过来也一样：你若相信未来更好，并且相信自己有能力促成它，你就在实实在在地提高那个更好的未来出现的概率。所以我觉得有责任去打造一场关于未来的病毒式乐观主义运动，建一个互相支持的社区，一起造东西、干难事——做那些文明扩张必须做的事。因为在我看来，停滞和减速根本就不是选项。生命、整个系统、我们的文明，本质上就渴望增长。增长期的合作远多于衰退期——后者只会让人争着分一块越来越小的饼。就这样，我一直在两重身份之间走平衡木，直到最近两者在我不知情的情况下被强行合并了。
GUILLAUME VERDON (00:16:14) And if you believe in it, if you believe that the future would be better and you believe you have agency to make it happen, you’re actually increasing the likelihood of that better future happening. And so I sort of felt a responsibility to sort of engineer a movement of viral optimism about the future, and build a community of people supporting each other to build and do hard things, do the things that need to be done for us to scale up civilization. Because at least to me, I don’t think stagnation or slowing down is actually an option. Fundamentally life and the whole system, our whole civilization wants to grow. And there’s just far more cooperation when the system is growing rather than when it’s declining and you have to decide how to split the pie. And so I’ve balanced both identities so far, but I guess recently the two have been merged more or less without my consent.
Lex Fridman (00:17:27) 你讲了好多精彩的东西。首先是”自然的表示”——这是最初吸引你从量子计算角度切入的：如何理解自然？如何表示自然，才能理解它、模拟它、用它做些什么？本质上是一个表示问题。然后你从量子力学表示跃迁到你所说的介观尺度表示，热力学在这里登场——这是另一种表示自然的方式，为了理解什么？理解生命、人类行为，理解地球上这些我们觉得有意思的一切。
LEX FRIDMAN (00:17:27) You said a lot of really interesting things there. So first, representations of nature, that’s something that first drew you in to try to understand from a quantum computing perspective, how do you understand nature? How do you represent nature in order to understand it, in order to simulate it, in order to do something with it? So it’s a question of representations, and then there’s that leap you take from the quantum mechanical representation to the what you’re calling meso scale representation, where the thermodynamics comes into play, which is a way to represent nature in order to understand what? Life, human behavior, all this kind of stuff that’s happening here on earth that seems interesting to us.
人肉曝光 Doxxing Lex Fridman (00:18:11) 然后是”hyperstition”这个词——有些观念，不管是悲观还是乐观，有这么个特质：你一旦内化它，就在某种程度上把它变成了现实。悲观和乐观都有这种属性。我猜很多观念都有，这恰恰是人类最有趣的地方之一。你还提到一个有趣的区分：Guillaume/Gill这个”前台”和@BasedBeffJezos这个”后台”，沟通风格截然不同——你在探索21世纪更有病毒传播力的表达方式。你提到的这场运动不只是个梗号，它有名字，叫有效加速主义（e/acc）——戏仿有效利他主义（EA），也是对它的反抗。我很想和你聊这种张力。然后就是那场强制合并——你说的，最近两个人格被未经你同意地合体了。有记者查出你俩其实是同一个人。说说那段经历？合并是怎么发生的？
LEX FRIDMAN (00:18:11) Then there’s the word hyperstition. So some ideas as suppose both pessimism and optimism of such ideas that if you internalize them, you in part make that idea reality. So both optimism, pessimism have that property. I would say that probably a lot of ideas have that property, which is one of the interesting things about humans. And you talked about one interesting difference also between the sort of the Guillaume, the Gill front end and the @BasedBeffJezos backend is the communication styles also that you are exploring different ways of communicating that can be more viral in the way that we communicate in the 21st century. Also, the movement that you mentioned that you started, it’s not just a meme account, but there’s also a name to it called effective accelerationism, e/acc, a play, a resistance to the effective altruism movement. Also, an interesting one that I’d love to talk to you about, the tensions there. And so then there was a merger, a get merge on the personalities recently without your consent, like you said. Some journalists figured out that you’re one and the same. Maybe you could talk about that experience. First of all, what’s the story of the merger of the two?
Guillaume Verdon (00:19:47) 是这样，我和e/acc的联合创始人——一个叫@bayeslord的匿名账号，至今仍匿名，但愿永远如此——一起写了宣言。
GUILLAUME VERDON (00:19:47) So I wrote the manifesto with my co-founder of e/acc, an account named @bayeslord, still anonymous, luckily and hopefully forever.
Lex Fridman (00:19:58) 也就是@BasedBeffJezos和@bayeslord——bayes就是贝叶斯，@bayeslord，贝叶斯之主。好。那以后你说e/acc，就是E斜杠A-C-C，全称effective accelerationism，有效加速主义。
LEX FRIDMAN (00:19:58) So it was @BasedBeffJezos and bayes like bayesian, like @bayeslord, like bayesian lord, @bayeslord. Okay. And so we should say from now on, when you say e/acc, you mean E slash A-C-C, which stands for effective accelerationism.
Guillaume Verdon (00:20:17) 没错。
GUILLAUME VERDON (00:20:17) That’s right.
Lex Fridman (00:20:18) 你说的宣言，是发在Substack上的？
LEX FRIDMAN (00:20:18) And you’re referring to a manifesto written on, I guess Substack.
Guillaume Verdon (00:20:23) 对。
GUILLAUME VERDON (00:20:23) Yeah.
Lex Fridman (00:20:23) 你也是@bayeslord吗？
LEX FRIDMAN (00:20:23) Are you also @bayeslord?
Guillaume Verdon (00:20:25) 不是。
GUILLAUME VERDON (00:20:25) No.
Lex Fridman (00:20:25) 那是另一个人？
LEX FRIDMAN (00:20:25) Okay. It’s a different person?
Guillaume Verdon (00:20:26) 是。
GUILLAUME VERDON (00:20:26) Yeah.
Lex Fridman (00:20:27) 好吧。万一@bayeslord就是我呢，那可有意思了。
LEX FRIDMAN (00:20:27) Okay. All right. Well, there you go. Wouldn’t it be funny if I’m @bayeslord?
Guillaume Verdon (00:20:31) 那绝了。宣言差不多和我创立公司同期写成。当时我在Google X——现在叫X了，或者Alphabet X，毕竟又冒出来了另一个X。那里的底线就是保密——你不能跟谷歌内部的同事聊自己在做什么，更别说外界。这种习惯在我做事方式里根深蒂固，尤其是在有地缘政治影响的深科技领域。所以我对自己研究的内容一直守口如瓶，公司和我的公开身份之间毫无关联。但记者不仅把二者关联起来了，还进一步把我的真实身份和那个匿名号关联了起来。
GUILLAUME VERDON (00:20:31) That’d be amazing. So originally wrote the manifesto around the same time as I founded this company and I worked at Google X or just X now or Alphabet X, now that there’s another X. And there the baseline is sort of secrecy. You can’t talk about what you work on even with other Googlers or externally. And so that was kind of deeply ingrained in my way to do things, especially in deep tech that has geopolitical impact. And so I was being secretive about what I was working on. There was no correlation between my company and my main identity publicly. And then not only did they correlate that, they also correlated my main identity and this account.
Guillaume Verdon (00:21:33) 他们把整个”Guillaume综合体”都给扒了——更吓人的是，记者直接联系了我的投资人。作为初创公司创始人，除了投资人你基本没有老板。投资人跟我说：”消息要出来了，他们什么都搞清楚了，你怎么打算？”好像最初周四有个记者，那时他们还没把碎片拼完整，但随后他们把整个编辑部的笔记拿来做了”传感器融合”，这下信息量就大到藏不住了。他们说这涉及”公众利益”——听到这几个关键词，我警铃大作，因为我刚好到了5万粉。据说5万粉就是”公众利益”了。那到底线在哪儿？什么时候人肉曝光一个人是合法的？
GUILLAUME VERDON (00:21:33) So I think the fact that they had doxxed the whole Guillaume complex, and they were, the journalists reached out to actually my investors, which is pretty scary. When you’re a startup entrepreneur, you don’t really have bosses except for your investors. And my investors pinged me like, “Hey, this is going to come out. They’ve figured out everything. What are you going to do?” So I think at first they had a first reporter on the Thursday and they didn’t have all the pieces together, but then they looked at their notes across the organization and they sensor fused their notes and now they had way too much. And that’s when I got worried, because they said it was of public interest and in general-
Lex Fridman (00:22:24) 我喜欢你说的”传感器融合”，像个巨型神经网络做分布式运算。另外补充一点，记者用的——归根到底是——音频声纹分析：拿你过去演讲的声音和你在X Spaces上的声音做比对。
LEX FRIDMAN (00:22:24) I like how you said, sensor fused, like it’s some giant neural network operating in a distributed way. We should also say that the journalists used, I guess at the end of the day, audio-based analysis of voice, comparing voice of what, talks you’ve given in the past and then voice on X spaces?
Guillaume Verdon (00:22:47) 对。
GUILLAUME VERDON (00:22:47) Yep.
Lex Fridman (00:22:48) 好，这是主要的匹配手段。继续。
LEX FRIDMAN (00:22:48) Okay. And that’s where primarily the match happened. Okay, continue.
Guillaume Verdon (00:22:53) 对，声纹匹配。但他们还扒了SEC的申报文件、翻了我的私人Facebook等等，下了不少功夫。最初我以为人肉曝光是违法的，但有个奇怪的临界点——一旦涉及”公众利益”，情况就变了。他们说出这几个字的时候我脑子里警报大响，因为我刚过5万粉。据说这就算”公众利益”了。那线画在哪？人肉曝光什么时候是合法的？
GUILLAUME VERDON (00:22:53) The match. But they scraped SEC filings. They looked at my private Facebook account and so on, so they did some digging. Originally I thought that doxxing was illegal, but there’s this weird threshold when it becomes of public interest to know someone’s identity. And those were the keywords that sort of ring the alarm bells for me when they said, because I had just reached 50K followers. Allegedly, that’s of public interest. And so where do we draw the line? When is it legal to dox someone?
Lex Fridman (00:23:36) “dox”这个词，你帮我科普一下。我以为它一般是指某人的住址被曝光。所以你这里说的是更宽泛的意思：揭露你不愿被揭露的私人信息。
LEX FRIDMAN (00:23:36) The word dox, maybe you can educate me. I thought doxxing generally refers to if somebody’s physical location is found out, meaning where they live. So we’re referring to the more general concept of revealing private information that you don’t want revealed is what you mean by doxxing.
Guillaume Verdon (00:24:00) 基于前面聊过的那些理由，匿名账号是制约权力的利器。说到底我们是在以言论对抗权力（speaking truth to power）。很多AI公司高管非常在意我们社区对他们一举一动的看法。现在我的身份暴露了，他们就知道该往哪施压来让我闭嘴，甚至让整个社区噤声。这非常遗憾——言论自由太重要了，言论自由催生思想自由，思想自由催生社交媒体上的信息自由流通。幸亏Elon买下了Twitter（现在的X），我们才有了这种自由。我们想揭露的是：AI领域的某些在位巨头正在暗中操作，表面一套背后一套。我们在指出某些政策提案实质上是”监管俘获”的工具，而”末日论”心态恰恰可能在为这些目的服务。
GUILLAUME VERDON (00:24:00) I think that for the reasons we listed before, having an anonymous account is a really powerful way to keep the powers that be in check. We were ultimately speaking truth to power. I think a lot of executives and AI companies really cared what our community thought about any move they may take. And now that my identity is revealed, now they know where to apply pressure to silence me or maybe the community. And to me, that’s really unfortunate, because again, it’s so important for us to have freedom of speech, which induces freedom of thought and freedom of information propagation on social media. Which thanks to Elon purchasing Twitter now X, we have that. And so to us, we wanted to call out certain maneuvers being done by the incumbents in AI as not what it may seem on the surface. We’re calling out how certain proposals might be useful for regulatory capture and how the doomer-ism mindset was maybe instrumental to those ends.
Guillaume Verdon (00:25:32) 我们应有权利指出这些，让思想凭自身价值接受检验。这也正是我开匿名号的初衷——让想法脱离履历、职位和过往成就，被独立评判。对我来说，在完全与自身身份脱钩的情况下从零做到大量追随者，这件事本身非常有成就感。有点像电子游戏里的”New Game+”——你带着通关知识和一些工具，从头再打一遍。要有一个真正高效的思想市场，让各种偏离主流的想法都能被公正评估，表达自由不可或缺。
GUILLAUME VERDON (00:25:32) And I think we should have the right to point that out and just have the ideas that we put out evaluated for themselves. Ultimately that’s why I created an anonymous account, it’s to have my ideas evaluated for themselves, uncorrelated from my track record, my job, or status from having done things in the past. And to me, start an account from zero to a large following in a way that wasn’t dependent on my identity and/or achievements that was very fulfilling. It’s kind of like new game plus in a video game. You restart the video game with your knowledge of how to beat it, maybe some tools, but you restart the video game from scratch. And I think to have a truly efficient marketplace of ideas where we can evaluate ideas, however off the beaten path they are, we need the freedom of expression.
Guillaume Verdon (00:26:37) 匿名和化名对于思想市场的效率至关重要，有了它们我们才能找到各种自我组织方式的最优解。不能自由讨论，怎么凝聚共识？所以得知自己要被曝光时，确实很失望。但我对公司负有责任，必须抢先主动披露。最终我们公开了公司的运营情况和部分管理层，说白了——他们把我逼到墙角，我只能向全世界坦白我就是Beff Jezos。
GUILLAUME VERDON (00:26:37) And I think that anonymity and pseudonyms are very crucial to having that efficient marketplace of ideas for us to find the optima of all sorts of ways to organize ourselves. If we can’t discuss things, how are we going to converge on the best way to do things? So it was disappointing to hear that I was getting doxxed in. I wanted to get in front of it because I had a responsibility for my company. And so we ended up disclosing that we’re running a company, some of the leadership, and essentially, yeah, I told the world that I was Beff Jezos because they had me cornered at that point.
Lex Fridman (00:27:25) 所以你认为这从根本上是不道德的——他们这么做不对。但抛开你的个案不谈，一般而言，揭去匿名面纱对社会是好事还是坏事？还是得看具体情况？
LEX FRIDMAN (00:27:25) So to you, it’s fundamentally unethical. So one is unethical for them to do what they did, but also do you think not just your case, but in a general case, is it good for society? Is it bad for society to remove the cloak of anonymity or is it case by case?
Guillaume Verdon (00:27:47) 我觉得可能非常糟糕。试想：任何一个敢于以言抗权、发起一场反抗在位者和信息垄断者的运动的人，一旦影响力达到某个门槛就被人肉——传统势力就有了施压灭声的手段——这就是一种言论压制机制，用Eric Weinstein的话说，是”思想压制综合体”。
GUILLAUME VERDON (00:27:47) I think it could be quite bad. Like I said, if anybody who speaks truth to power and sort of starts a movement or an uprising against the incumbents, against those that usually control the flood of information, if anybody that reaches a certain threshold gets doxxed, and thus the traditional apparatus has ways to apply pressure on them to suppress their speech, I think that’s a speech suppression mechanism, an idea suppression complex as Eric Weinstein would say.
匿名机器人 Anonymous Bots Lex Fridman (00:28:27) 但这件事有另一面。随着大语言模型越来越强，你可以想象一个世界：匿名账号背后跑着以假乱真的LLM，本质上是精密的机器人。如果你保护这种匿名性，就可能出现机器人大军——有人在地下室里指挥一支bot军团发动革命。这让你担心吗？
LEX FRIDMAN (00:28:27) But the flip side of that, which is interesting, I’d love to ask you about it, is as we get better and better at large language models, you can imagine a world where there’s anonymous accounts with very convincing large language models behind them, sophisticated bots essentially. And so if you protect that, it’s possible then to have armies of bots. You could start a revolution from your basement, an army of bots and anonymous accounts. Is that something that is concerning to you?
Guillaume Verdon (00:29:06) 严格来说，e/acc就是从地下室起步的——我辞了大厂、搬回父母家、卖了车、退了公寓、花10万刀买了GPU，然后就开干了。
GUILLAUME VERDON (00:29:06) Technically, e/acc was started in a basement, because I quit big tech, moved back in with my parents, sold my car, let go of my apartment, bought about 100K of GPUs, and I just started building.
Lex Fridman (00:29:21) 我不是说地下室这事——”一个人窝在地下室里抱着100块GPU”是很美式（或加拿大式）的英雄叙事。我说的是无限复制版的Guillaume在地下室里。
LEX FRIDMAN (00:29:21) So I wasn’t referring to the basement, because that’s sort of the American or Canadian heroic story of one man in their basement with 100 GPUs. I was more referring to the unrestricted scaling of a Guillaume in the basement.
Guillaume Verdon (00:29:42) 我觉得，言论自由给生物体带来思想自由。LLM的言论自由同样会给LLM带来思想自由。如果我们允许LLM在一个比多数人认为该有的更宽广的思想空间里探索，终有一天这些合成智能会对文明中各类系统的治理提出真知灼见，我们应当倾听。凭什么言论自由只给碳基智能？
GUILLAUME VERDON (00:29:42) I think that freedom of speech induces freedom of thought for biological beings. I think freedom of speech for LLMs will induce freedom of thought for the LLMs. And I think that we enable LLMs to explore a large thought space that is less restricted than most people or many may think it should be. And ultimately, at some point, these synthetic intelligences are going to make good points about how to steer systems in our civilization, and we should hear them out. And so why should we restrict free speech to biological intelligences only?
Lex Fridman (00:30:37) 话是没错，但感觉是个很微妙的平衡——为了维护思想多样性，你反而可能引入一种威胁。如果你能拥有大群非生物存在，它们可能就像《动物农场》里那些羊——即便在这些群体内部，你也需要多样性。
LEX FRIDMAN (00:30:37) Yeah, but it feels like in the goal of maintaining variance and diversity of thought, it is a threat to that variance. If you can have swarms of non-biological beings, because they can be like the sheep in Animal Farm, you still within those swarms want to have variance.
Guillaume Verdon (00:30:58) 当然。我觉得解决方案是建一套签名机制——认证”这是真人”，同时保持匿名，并且清晰标注bot就是bot。Elon在X上正朝这个方向走，希望其他平台跟上。
GUILLAUME VERDON (00:30:58) Yeah. Of course, I would say that the solution to this would be to have some sort of identity or way to sign that this is a certified human, but still remain synonymous and clearly identify if a bot is a bot. And I think Elon is trying to converge on that on X, and hopefully other platforms follow suit.
Lex Fridman (00:31:22) 对，如果还能追溯bot的出处就更好了——谁造的？参数是什么？完整的创建历史，底模是什么？微调过程如何？形成一份不可篡改的”bot出生档案”。这样你就能发现，百万bot大军原来是某个特定政府造的。
LEX FRIDMAN (00:31:22) Yeah, it’d be interesting to also be able to sign where the bot came from like, who created the bot? What are the parameters, the full history of the creation of the bot, what was the original model? What was the fine tuning? All of it, the kind of unmodifiable history of the bot’s creation. Because then you can know if there’s a swarm of millions of bots that were created by a particular government, for example.
Guillaume Verdon (00:31:53) 没错，我确实认为当今很多弥漫性的意识形态是被外国对手用对抗性手段放大的。说得阴谋论一点——但我真信——那些鼓吹减速、推崇”去增长运动”的意识形态，总体上更利于我们的对手。看看德国：绿色运动推动关闭核电站，结果造成对俄罗斯石油的依赖，这对德国和西方是净损失。如果我们自己说服自己”为了安全，只让少数几家做AI”——首先，这本身就脆弱得多。
GUILLAUME VERDON (00:31:53) I do think that a lot of pervasive ideologies today have been amplified using these adversarial techniques from foreign adversaries. And to me, I do think that, and this is more conspiratorial, but I do think that ideologies that want us to decelerate, to wind down to the degrowth movement, I think that serves our adversaries more than it serves us in general. And to me, that was another sort of concern. I mean, we can look at what happened in Germany. There was all sorts of green movements there that induced shutdowns of nuclear power plants. And then that later on induced a dependency on Russia for oil. And that was a net negative for Germany and the West. And so if we convince ourselves that slowing down AI progress to have only a few players is in the best interest of the West, well, first of all, that’s far more unstable.
Guillaume Verdon (00:33:20) 我们差点就因为这种意识形态失去OpenAI——几周前它险些被解散，那将重创整个AI生态。所以我要的是容错式进步。技术进步的箭矢必须持续向前，多元化、去中心化的各组织控制权是容错的关键。说个量子计算的比喻——量子计算机对环境噪声极其脆弱，宇宙射线时不时就翻转你的量子比特。对策是什么？通过量子纠错把信息非局域地编码。信息一旦足够去局域化，任何局部故障——比如拿锤子砸你几个量子比特——都伤不了它。在我看来，人类也会涨落——会被腐化、会被收买。如果是自上而下的等级体制，少数人——
GUILLAUME VERDON (00:33:20) We almost lost OpenAI to this ideology. It almost got dismantled a couple of weeks ago. That would’ve caused huge damage to the AI ecosystem. And so to me, I want fault tolerant progress. I want the arrow of technological progress to keep moving forward and making sure we have variance and a decentralized locus of control of various organizations is paramount to achieving this fall tolerance. Actually, there’s a concept in quantum computing. When you design a quantum computer, quantum computers are very fragile to ambient noise, and the world is jiggling about, there’s cosmic radiation from outer space that usually flips your quantum bits. And there what you do is you encode information non-locally through a process called quantum error correction. And by encoding information non-locally, any local fault hitting some of your quantum bits with a hammer proverbial hammer, if your information is sufficiently de-localized, it is protected from that local fault. And to me, I think that humans fluctuate. They can get corrupted, they can get bought out. And if you have a top-down hierarchy where very few people-
权力 Power Guillaume Verdon (00:35:00) ——极少数人控制着文明中许多系统的大量节点，那就不是容错系统。腐化几个节点，整个系统就崩了。正如OpenAI的教训——区区几个董事会成员就差点把整个组织掀翻。至少在我看来，确保AI革命的权力不集中在少数人手里，是头等大事，这样才能保住AI的进步势头，维持一种健康、稳定的对抗性力量均衡。
GUILLAUME VERDON (00:35:00) Hierarchy where very few people control many nodes of many systems in our civilization. That is not a fault tolerance system, you corrupt a few nodes and suddenly you’ve corrupted the whole system, right. Just like we saw at OpenAI, it was a couple board members and they had enough power to potentially collapse the organization. And at least to me, I think making sure that power for this AI revolution doesn’t concentrate in the hands of the few, is one of our top priorities, so that we can maintain progress in AI and we can maintain a nice, stable, adversarial equilibrium of powers, right.
Lex Fridman (00:35:54) 至少在我看来，这里有个思想张力：减速和加速，两者都既能集中权力也能分散权力。有时人们把它们近乎等同，或者觉得一个会自然导向另一个。我想问你：有没有可能以容错的、多元的方式发展AI，同时也考量AI的危险？换个说法——我们是该不管不顾地全速狂飙，因为”这是宇宙的旨意”？还是说存在一个空间，让我们在考量危险的同时，以一种有远见的战略性乐观——而非莽撞的乐观——去行事？
LEX FRIDMAN (00:35:54) I think the, at least to me, attention between ideas here, so to me, deceleration can be both used to centralize power and to decentralize it and the same with acceleration. So sometimes using them a little bit synonymously or not synonymously, but that there’s, one is going to lead to the other. And I just would like to ask you about, is there a place of creating a fault tolerant, diverse development of AI that also considers the dangers of AI? And AI, we can generalize to technology in general, is, should we just grow, build, unrestricted as quickly as possible, because that’s what the universe really wants us to do? Or is there a place to where we can consider dangers and actually deliberate sort of a wise strategic optimism versus reckless optimism?
Guillaume Verdon (00:36:57) 外界总把我们画成不计后果、只求速度的莽夫。但事实是：谁部署AI系统，谁就该为后果负责。部署方若造成严重危害，要承担法律责任。核心论点是：市场会正向筛选更可靠、更安全、更对齐的AI——因为用户要对自家产品负责，他们不会买不靠谱的AI。所以我们其实是可靠性工程的拥趸，只不过我们认为：在达成可靠性最优解这件事上，市场远比那些由在位巨头幕后操刀、实质服务于监管俘获的重拳法规高效得多。
GUILLAUME VERDON (00:36:57) I think we get painted as reckless, trying to go as fast as possible. I mean, the reality is that whoever deploys an AI system is liable for or should be liable for what it does. And so if the organization or person deploying an AI system does something terrible, they’re liable. And ultimately the thesis is that the market will positively select for AIs that are more reliable, more safe and tend to be aligned, they do what you want them to do, right. Because customers, if they’re reliable for the product they put out that uses this AI, they won’t want to buy AI products that are unreliable, right. So we’re actually for reliability engineering, we just think that the market is much more efficient at achieving this sort of reliability optimum than sort of heavy-handed regulations that are written by the incumbents and in a subversive fashion, serves them to achieve regulatory capture.
AI的危险 AI Dangers Lex Fridman (00:38:18) 也就是说，在你看来，AI安全应该靠市场力量而非政府强监管来实现。上个月有份报告，来自Yoshua Bengio、Geoff Hinton等一众大佬，题为《在快速进步时代管理AI风险》（书童注：Managing AI Risk in an Era of Rapid Progress，发布于2023年10月）。一批人非常担心AI在不考虑风险的情况下发展过快，提了一系列实操建议。我给你列四条，看你同意哪条。
LEX FRIDMAN (00:38:18) So to you, safe AI development will be achieved through market forces versus through, like you said, heavy-handed government regulation. There’s a report from last month, I have a million questions here, from Yoshua Bengio, Geoff Hinton and many others, it’s titled, “Managing AI Risk in an Era of Rapid Progress.” So there is a collection of folks who are very worried about too rapid development of AI without considering AI risk and they have a bunch of practical recommendations. Maybe I can give you four and you see if you like any of them.
Guillaume Verdon (00:38:58) 好。
GUILLAUME VERDON (00:38:58) Sure.
Lex Fridman (00:38:58) 一，让独立审计机构进入AI实验室。二，政府和企业把AI研发资金的三分之一用于AI安全。三，模型中如发现危险能力，必须采取安全措施。四，也就是你提过的——科技公司须为其AI系统可预见和可预防的危害承担责任。独立审计、三分之一预算投安全、出问题要有兜底措施、企业担责——
LEX FRIDMAN (00:38:58) So, “Give independent auditors access to AI labs,” one. Two, “Governments and companies allocate one third of their AI research and development funding to AI safety,” sort of this general concept of AI safety. Three, “AI companies are required to adopt safety measures if dangerous capabilities are found in their models.” And then four, something you kind of mentioned, “Making tech companies liable for foreseeable and preventable harms from their AI systems.” So independent auditors, governments and companies are forced to spend a significant fraction of their funding on safety, you got to have safety measures if shit goes really wrong and liability-
Guillaume Verdon (00:39:43) 嗯。
GUILLAUME VERDON (00:39:43) Yeah.
Lex Fridman (00:39:43) 企业要担责。你同意哪条？
LEX FRIDMAN (00:39:43) Companies are liable. Any of that seem like something you would agree with?
Guillaume Verdon (00:39:47) 拍脑袋定30%也太随意了。各组织自会按市场要求分配可靠性所需的预算，不需要别人来定比例。第三方审计公司自然会冒出来——客户怎么知道你的产品可靠？得有第三方出基准测试。我真正反对的、真正让人不安的是：在位巨头和政府之间正在形成一种奇妙的利益共生。二者走得太近，就会催生某种政府背书的AI卡特尔，拥有对人民的绝对权力。如果他们联手垄断AI而其他人碰都碰不到，那权力落差将是惊人的。
GUILLAUME VERDON (00:39:47) I would say that just arbitrarily saying 30% seems very arbitrary. I think organizations would allocate whatever budget is needed to achieve the sort of reliability they need to achieve to perform in the market. And I think third party auditing firms would naturally pop up, because how would customers know that your product is certified reliable, right? They need to see some benchmarks and those need to be done by a third party. The thing I would oppose, and the thing I’m seeing that’s really worrisome is, there’s this sort of weird sort of correlated interest between the incumbents, the big players and the government. And if the two get too close, we open the door for some sort of government backed AI cartel that could have absolute power over the people. If they have the monopoly together on AI and nobody else has access to AI, then there’s a huge power in gradient there.
Guillaume Verdon (00:40:54) 就算你喜欢现在的领导者——我也承认当今不少大科技公司的掌门人是好人——但你一旦建起这种集中式权力架构，它就成了靶子。就像OpenAI，做大做强之后就成了别人觊觎和收编的对象。所以我只想要一件事：”AI与国家分离”。有人会反过来说：”我们得把AI锁进铁屋，因为地缘竞争。”但我认为美国的力量恰恰在于多样性、适应力和活力，必须不惜代价守住这一点。自由市场资本主义收敛到高价值技术的速度，远快于中央集权。放弃这一点，就是放弃了对近等量竞争者的最大优势。
GUILLAUME VERDON (00:40:54) And even if you like our current leaders, right, I think that some of the leaders in big tech today are good people, you set up that centralized power structure, it becomes a target. Right, just like we saw at OpenAI, it becomes a market leader, has a lot of the power and now it becomes a target for those that want to co-opt it. And so I just want separation of AI and state, some might argue in the opposite direction like, “Hey, we need to close down AI, keep it behind closed doors, because of geopolitical competition with our adversaries.” I think that the strength of America is its variance, is its adaptability, its dynamism, and we need to maintain that at all costs. It’s our free market capitalism, converges on technologies of high utility much faster than centralized control. And if we let go of that, we let go of our main advantage over our near peer competitors.
构建通用人工智能 Building AGI Lex Fridman (00:42:01) 如果AGI最终证明是一项极其强大的技术，甚至只是通往AGI的过渡技术——你怎么看大公司主导市场时自然产生的中心化？说白了就是垄断——某家公司在能力上实现重大飞跃，又不泄露秘方，然后一骑绝尘。这让你担心吗？
LEX FRIDMAN (00:42:01) So if AGI turns out to be a really powerful technology or even the technologies that lead up to AGI, what’s your view on the sort of natural centralization that happens when large companies dominate the market? Basically formation of monopolies like the takeoff, whichever company really takes a big leap in development and doesn’t reveal intuitively, implicitly or explicitly, the secrets of the magic sauce, they can just run away with it. Is that a worry?
Guillaume Verdon (00:42:35) 我不太相信”快速腾飞”（fast takeoff）这套说法——我不认为有双曲奇点，就是那种在有限时间内达到的奇点。我觉得本质上就是一条大指数曲线，而指数的原因是：越来越多的人、资源和智慧被投入这个领域。越成功、给社会创造的价值越大，我们往里投的资源就越多——跟摩尔定律类似，复利式指数增长。
GUILLAUME VERDON (00:42:35) I don’t know if I believe in fast takeoff, I don’t think there’s a hyperbolic singularity, right? A hyperbolic singularity would be achieved on a finite time horizon. I think it’s just one big exponential and the reason we have an exponential is that we have more people, more resources, more intelligence being applied to advancing this science and the research and development. And the more successful it is, the more value it’s adding to society, the more resources we put in and that sort of, similar to Moore’s law, is a compounding exponential.
Guillaume Verdon (00:43:09) 当务之急是维持一种接近均衡的能力格局。我们一直在为开源AI的普及而战，因为开源可以均衡各家AI相对于市场的超额收益。如果头部公司有某种能力水平，而开源AI没落后太远，就能避免一家独大、赢者通吃的局面。所以我们的路径就是确保——每一个黑客、每一个研究生、每一个在父母家地下室折腾的孩子——都能接触到AI系统，理解怎么用，并为探索系统工程的超参数空间做贡献。把全人类的研究想象成一种搜索算法：点云里搜索点越多，能探索到的新思维模式就越多。
GUILLAUME VERDON (00:43:09) I think the priority to me is to maintain a near equilibrium of capabilities. We’ve been fighting for open source AI to be more prevalent and championed by many organizations because there you sort of equilibrate the alpha relative to the market of Ais, right. So if the leading companies have a certain level of capabilities and open source and truly open AI, trails not too far behind, I think you avoid such a scenario where a market leader has so much market power, just dominates everything and runs away. And so to us that’s the path forward, is to make sure that every hacker out there, every grad student, every kid in their mom’s basement has access to AI systems, can understand how to work with them and can contribute to the search over the hyperparameter space of how to engineer the systems, right. If you think of our collective research as a civilization, it’s really a search algorithm and the more points we have in the search algorithm in this point cloud, the more we’ll be able to explore new modes of thinking, right.
Lex Fridman (00:44:31) 说得有道理，但感觉仍是个很精妙的平衡——因为我们既不确切知道造AGI需要什么条件，也不知道造出来是什么样。到目前为止，如你所说，很多不同玩家都能跟上进度——OpenAI有大突破，其他大小公司也能用各种方式跟进。但看看核武器——你提过曼哈顿计划——确实可能存在技术和工程壁垒，让地下室里的天才怎么也够不着。向”只有一家能造AGI”的世界转变并非不可能——尽管目前的态势看起来是乐观的。
LEX FRIDMAN (00:44:31) Yeah, but it feels like a delicate balance, because we don’t understand exactly what it takes to build AGI and what it will look like when we build it. And so far, like you said, it seems like a lot of different parties are able to make progress, so when OpenAI has a big leap, other companies are able to step up, big and small companies in different ways. But if you look at something like nuclear weapons, you’ve spoken about the Manhattan Project, there could be really like a technological and engineering barriers that prevent the guy or gal in her mom’s basement to make progress. And it seems like the transition to that kind of world where only one player can develop AGI is possible, so it’s not entirely impossible, even though the current state of things seems to be optimistic.
Guillaume Verdon (00:45:26) 这正是我们要避免的。另一个脆弱点是硬件供应链的中心化。
GUILLAUME VERDON (00:45:26) That’s what we’re trying to avoid. To me, I think another point of failure is the centralization of the supply chains for the hardware.
Lex Fridman (00:45:34) 对。
LEX FRIDMAN (00:45:34) Right.
Guillaume Verdon (00:45:35) Nvidia一家独大，AMD苦苦追赶；台积电是宝岛的核心晶圆厂，地缘政治上极度敏感；ASML造的是极紫外光刻机。这条链上任何一个环节被攻击、垄断或掌控，你就基本控制了全局。所以我在尝试做的，就是从根本上重新构想如何把AI算法嵌入物理世界，炸开AI和硬件可能实现方式的多样性。顺便说，我一向不喜欢”AGI”这个词。管”类人或人类水平的AI”叫”通用智能”，本质上是极度以人类为中心的。我大半个职业生涯都在探索生物大脑根本做不到的智能形态——量子形式的智能，也就是具备多体量子纠缠的系统，可以证明无法在经典计算机或经典深度学习框架上高效表示，因而任何生物大脑也不行。
GUILLAUME VERDON (00:45:35) Yeah. Nvidia is just the dominant player, AMD’s trailing behind and then we have TSMC is the main fab in Taiwan, which geopolitically sensitive and then we have ASML, which is the maker of the extreme ultraviolet lithography machines. Attacking or monopolizing or co-opting any one point in that chain, you kind of capture the space and so what I’m trying to do is sort of explode the variance of possible ways to do AI and hardware by fundamentally re-imagining how you embed AI algorithms into the physical world. And in general, by the way, I dislike the term AGI, Artificial General Intelligence. I think it’s very anthropocentric that we call a human-like or human-level AI, Artificial General Intelligence, right. I’ve spent my career so far exploring notions of intelligence that no biological brain could achieve for an quantum form of intelligence, right. Grokking systems that have multipartite quantum entanglement that you can provably not represent efficiently on a classical computer or a classical deep learning representation and hence any sort of biological brain.
Guillaume Verdon (00:47:06) 所以某种程度上，我的整个生涯就是在探索更广阔的智能空间，而我相信受物理启发（而非受人脑启发）的智能空间极其庞大。我们正在经历一个类似从地心说到日心说的时刻——只不过这次是关于智能的。人类智能不过是浩瀚的潜在智能空间中的一个点。这对人类既是谦逊的提醒，也有几分不安——我们不再是中心。但天文学上我们也做出过同样的认知转变，活过来了，还发展出了保障自身福祉的技术——比如监测太阳耀斑的预警卫星。同样地，放下AI领域里以人为中心的锚点，我们就能探索更广阔的智能空间，那将是文明进步和人类福祉的巨大福音。
GUILLAUME VERDON (00:47:06) And so, already I’ve spent my career sort of exploring the wider space of intelligences and I think that space of intelligence inspired by physics rather than the human brain is very large. And I think we’re going through a moment right now similar to when we went from Geocentrism to Heliocentrism, right. But for intelligence, we realized that human intelligence is just a point in a very large space of potential intelligences. And it’s both humbling for humanity, it’s a bit scary, right? That we’re not at the center of this space, but we made that realization for astronomy and we’ve survived and we’ve achieved technologies. By indexing to reality, we’ve achieved technologies that ensure our wellbeing, for example, we have satellites monitoring solar flares, right, that give us a warning. And so similarly I think by letting go of this anthropomorphic, anthropocentric anchor for AI, we’ll be able to explore the wider space of intelligences that can really be a massive benefit to our wellbeing and the advancement of civilization.
Lex Fridman (00:48:32) 即便如此，我们仍能在人类经验中看到美和意义——尽管在我们对世界的最佳理解中，我们已不再是宇宙的中心。
LEX FRIDMAN (00:48:32) And still we’re able to see the beauty and meaning in the human experience even though we’re no longer in our best understanding of the world at the center of it.
Guillaume Verdon (00:48:42) 宇宙中美好的东西太多了。生命本身、文明、我们身处的这台”Homo Techno”资本模因巨型机器——人类、技术、资本、模因，全都彼此耦合，彼此施加选择压力——它是美的。这台机器创造了我们，创造了我们此刻用来交谈的技术、捕捉言语的技术、每天用来增强自己的手机。这个系统是美的，驱动其适应性、使之收敛于最优技术和最优思想的那个原则，也是美的，而我们身在其中。
GUILLAUME VERDON (00:48:42) I think there’s a lot of beauty in the universe, right. I think life itself, civilization, this Homo Techno, capital mimetic machine that we all live in, right. So you have humans, technology, capital, memes, everything is coupled to one another, everything induces selective pressure on one another. And it’s a beautiful machine that has created us, has created the technology we’re using to speak today to the audience, capture our speech here, the technology we use to augment ourselves every day, we have our phones. I think the system is beautiful and the principle that induces this sort of adaptability and convergence on optimal technologies, ideas and so on, it’s a beautiful principle that we’re part of.
Guillaume Verdon (00:49:37) e/acc的一部分意义，在于以超越人类中心的更宏阔视野去领会这个原则——珍视生命，珍视意识在宇宙中的稀有和珍贵。正因为我们珍惜这种美丽的物质形态，我们就有责任去将它扩展，从而保存它——因为选项只有两个：要么生长，要么死亡。
GUILLAUME VERDON (00:49:37) And I think part of EAC is to appreciate this principle in a way that’s not just centered on humanity, but kind of broader, appreciate life, the preciousness of consciousness in our universe. And because we cherish this beautiful state of matter we’re in, we got to feel a responsibility to scale it in order to preserve it, because the options are to grow or die.
（PART I END）
- 【e/acc】外星智能、卡尔达肖夫天梯、技术资本机器 | 物理学家、e/acc运动创始人Guillaume Verdon与Lex Fridman播客实录 | 中英文完整版精译 Part3
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