书童按：本篇是Guillaume Verdon接受Lex Fridman播客采访实录的第四部分，亦是完结篇。在前三篇建立理论根基、探讨运动理念之后，本篇回归技术前沿与人生哲思：AGI的本质与物理基底AI的互补、奇点概念的批判性审视、有效利他主义（EA）与有效加速主义（e/acc）的哲学分歧、Guillaume个人的极致生产力日常、身份认同的流变、给年轻人的建议、以及对死亡与生命意义的终极思考。Verdon主张以物理能量而非主观感受作为文明进步的客观度量，批判EA的hedons（享乐单位）损失函数易陷入局部最优（如虾类养殖场痛苦最小化或”线头享乐主义”），强调死亡作为系统耗散适应的必要环节。访谈以爱因斯坦名言收尾：”若一个想法起初听来不荒诞，那它便毫无希望。”全程思想密度极高，哲学深度与工程实践并重，既有热力学定律的冷峻，亦有模因文化的狂欢。初稿采用Claude Code机器翻译及排版，书童仅做简单校对及批注，至此四部曲完结，以飨诸君。
Lex Fridman (02:22:31) 你提到Extropic正在尝试构建生成式AI的物理基底。那这和AGI本身有什么区别？换句话说，AGI有可能在你们公司里被创造出来吗？还是说AGI只是把你们的技术当作底层基底来使用？
LEX FRIDMAN (02:22:31) So you mentioned with Extropic you’re trying to build the physical substrate for generative AI. What’s the difference between that and the AGI AI itself? So, is it possible that in the halls of your company, AGI will be created? Or will AGI just be using this as a substrate?
Guillaume Verdon (02:22:51) 我认为我们的目标是既能运行类人AI——也就是拟人AI——
GUILLAUME VERDON (02:22:51) I think our goal is to both run human like AI, or anthropomorphic AI.
Lex Fridman (02:22:58) 抱歉用了AGI这个词，我知道它会让你不太舒服。
LEX FRIDMAN (02:22:58) Sorry for use of the term AGI. I know it’s triggering for you.
Guillaume Verdon (02:23:02) 我们认为未来真正的方向是基于物理的AI与拟人AI的结合。你可以这样想象：我有一种基于物理的AI驱动的世界建模引擎。基于物理的AI更擅长在所有尺度上表征世界，因为它可以是量子力学的、热力学的、确定性的、混合型的世界表征——就像我们的世界在不同尺度上遵循不同的物理规律。如果你从中汲取灵感，以自然本身的方式去学习表征，你就能获得对自然远为精确的描述。这样你就能在所有尺度上拥有非常精确的世界模型。一端是世界建模引擎，另一端是类人的拟人AI。于是你既有了科学——验证想法的试验场，也有了合成科学家。在我们看来，这种基于物理的AI与拟人AI的联合系统，是最接近真正完全通用的人工智能系统的东西。
GUILLAUME VERDON (02:23:02) We think that the future is actually physics-based AI combined with anthropomorphic AI. So, you can imagine, I have a sort of world modeling engine through physics-based AI. Physics-based AI is better at representing the world at all scales, because it can be quantum mechanical, thermodynamic, deterministic, hybrid representations of the world, just like our world at different scales has different regimes of physics. If you inspire yourself from that in the ways you learn representations of nature, you can have much more accurate representations of nature. So, you can have very accurate world models at all scales. And so, you have the world modeling engine, and then you have the anthropomorphic AI that is human-like. So you can have the science, the playground to test your ideas, and you can have the synthetic scientist. And to us, that joint system of a physics-based and an anthropomorphic AI is the closest thing to a fully general, artificially intelligent system.
Lex Fridman (02:24:07) 也就是说，你可以通过将AI锚定于物理来更接近真理，同时仍然保留一个拟人化的接口，方便我们这些喜欢与人类或类人系统对话的人使用。那么在这个话题上，我猜这正是当前大语言模型在你看来的一大局限——它们是出色的”一本正经胡说八道”专家，未必真正锚定于真理。这么说公平吗？
LEX FRIDMAN (02:24:07) So you can get closer to truth by grounding of the AI to physics, but you can also still have a anthropomorphic interface to us humans that like to talk to other humans, or human-like systems. So, on that topic, I suppose that is one of the big limitations of current large language models to you, is that they’re good bullshitters, they’re not really grounded to truth necessarily. Would that be fair to say?
Guillaume Verdon (02:24:40) 没错，你不会试图用一个在互联网文本上训练出来的语言模型去预测股市走向，它不可能是一个很准确的模型。它无法精确地建模自身的先验知识或对世界的不确定性。所以，你需要一种不同类型的AI来弥补这种文本外推式AI的不足。确实如此。
GUILLAUME VERDON (02:24:40) Yeah, no, you wouldn’t try to extrapolate the stock market with an LM trained on text from the internet. It’s not going to be a very accurate model. It’s not going to model its priors or its uncertainties about the world very accurately. So, you need a different type of AI to compliment this text extrapolation AI. Yeah.
Lex Fridman (02:25:05) 你之前提到了奇点。我们离奇点还有多远？
LEX FRIDMAN (02:25:05) You mentioned singularity earlier. How far away are we from a singularity?
Guillaume Verdon (02:25:09) 我不确定自己是否相信那种作为单一时间点的有限时间奇点。我认为它更可能是渐近式的，沿某种对角线趋近的渐近线。我们有光锥的限制，有物理定律在约束我们的增长能力，所以显然不可能在有限时间内完全发散。我的先验判断是，对面阵营的很多人认为，一旦我们达到人类水平的AI，就会出现一个拐点，然后突然间[听不清]，AI就会顿悟如何在纳米尺度上操纵物质、组装纳米机器人。但在利用AI改造物质这个方向上干了将近十年之后，我可以告诉你，这比他们想象的要难得多。现实是，你需要大量来自高精度但昂贵的自然模拟、或者自然本身的样本数据，这就制约了你控制周围世界的能力。在计算层面和热力学层面，获取关于世界的信息以便预测和控制它，存在一个不可逾越的最低成本。正是这个成本让一切保持在可控范围内。
GUILLAUME VERDON (02:25:09) I don’t know if I believe in a finite time singularity as a single point in time. I think it’s going to be asymptotic, and sort of a diagonal sort of asymptote. We have the light cone, we have the limits of physics restricting our ability to grow. So, obviously can’t fully diverge on a finite time. I think my priors are that I think a lot of people on the other side of the aisle think that once we reach human level AI, there’s going to be an inflection point, and a sudden [inaudible 02:25:48], suddenly AI is going to grok how to manipulate matter at the nano scale, and assemble nanobots. And having worked for nearly a decade in applying AI to engineer matter, it’s much harder than they think. And in reality, you need a lot of samples from either a simulation of nature that’s very accurate and costly, or nature itself, and that keeps your ability to control the world around us in check. There’s a sort of minimal cost computationally, and thermodynamically, to acquiring information about the world in order to be able to predict and control it. And that keeps things in check.
Lex Fridman (02:26:27) 有意思，你提到了”对面阵营”。说到这个，我昨天发了一个关于p(doom)的投票——也就是末日概率。结果显示，认为末日极有可能和极不可能的人之间泾渭分明。我在想，未来是不是真的会出现类似共和党对民主党、红蓝对立那样的阵营划分？AI末日论者对阵e/acc支持者？[听不清]
LEX FRIDMAN (02:26:27) It’s funny you mentioned the other side of the aisle. So, in the poll I posted about p(doom) yesterday, what’s the probability of doom? There seems to be a nice division between people think it’s very likely, and very unlikely. I wonder if in the future there’ll be the actual Republicans versus Democrats division, blue versus red? Is the AI doomers versus the e/accers, EAC? [inaudible 02:26:53].
Guillaume Verdon (02:26:53) 是的。不过这个运动从根本上说不是左右之争，它更像是向上还是向下的问题，就文明的规模而言——
GUILLAUME VERDON (02:26:53) Yeah. So, this movement is not right wing or left wing fundamentally, it’s more like up versus down, in terms of the scale of-
Lex Fridman (02:27:01) 哪边算”上”？好的。
LEX FRIDMAN (02:27:01) Which one is the up? Okay.
Guillaume Verdon (02:27:02) ……文明的规模，对吧？
GUILLAUME VERDON (02:27:02) … Civilization, right?
Lex Fridman (02:27:03) 好的。
LEX FRIDMAN (02:27:03) All right.
Guillaume Verdon (02:27:05) 不过，现有政党似乎确实存在某种站队现象：那些主张更多权力集中化、更多管控和监管的人正在向末日论者靠拢，因为在民众中制造恐惧是让人们心甘情愿交出更多控制权、赋予政府更大权力的绝佳手段。但从本质上说，我们不是左对右。我们做过关于e/acc内部成员政治立场的调查，结果相当均衡。所以，这是我们这个时代一个全新的根本性议题。它不仅仅是中心化对去中心化的问题，它更像是……科技进步主义对科技保守主义的对决，对吧？
GUILLAUME VERDON (02:27:05) But, it seems to be like there is sort of case of alignment of the existing political parties, where those that are for more centralization of power, control, and more regulations are aligning themselves with the doomers, because that sort of instilling fear in people is a great way for them to give up more control, and give the government more power. But fundamentally, we’re not left versus right. I think we’ve done polls of people’s alignment within EAC. I think it’s pretty balanced. So, it’s a new fundamental issue of our time. It’s not just centralization versus decentralization. It’s kind of do we go… It’s like tech progressivism, versus techno conservatism. Right?
Lex Fridman (02:27:54) e/acc作为一个运动，经常被拿来与EA——有效利他主义——做对比。你认为有效利他主义有哪些优点和缺点？在你看来，它有什么有见地的地方，又有什么不足？
LEX FRIDMAN (02:27:54) So e/acc as a movement is often formulated in contrast to EA, effective altruism. What do you think are the pros and cons of effective altruism? What’s interesting, insightful to you about them, and what is negative?
Guillaume Verdon (02:28:15) 嗯，我认为人们试图从第一性原理出发去做好事，这本身是好的。
GUILLAUME VERDON (02:28:15) Right. I think people trying to do good from first principles is good.
Lex Fridman (02:28:23) 其实我们应该先说明一下，抱歉打断你——如果我说错了你可以纠正——有效利他主义是一种试图以最优方式行善的运动，其中”善”大概是用世界上的痛苦总量来衡量的，目标是将其最小化。但正如任何优化问题一样，它可能会走偏。所以，探讨它可能如何走偏是很有意思的。
LEX FRIDMAN (02:28:23) We should actually say, and sorry to interrupt, we should probably say that, and you can correct me if I’m wrong, but effective altruism is the kind of movement that’s trying to do good optimally, where good is probably measured something like the amount of suffering in the world. You want to minimize it. And there’s ways that that can go wrong, as any optimization can. And so, it’s interesting to explore how things can go wrong.
Guillaume Verdon (02:28:55) 我们双方都在试图做好事，分歧在于应该用什么损失函数，对吧？
GUILLAUME VERDON (02:28:55) We’re both trying to do good to some extent, and we’re arguing for which loss function we should use, right?
Lex Fridman (02:29:03) 是的。
LEX FRIDMAN (02:29:03) Yes.
Guillaume Verdon (02:29:04) 他们的损失函数是某种hedons（书童注：享乐单位，用于量化快乐程度的假设单位），即享乐主义的度量单位——你感觉有多好，持续多久？痛苦就是负的hedons，他们试图将其最小化。但在我们看来，这个损失函数存在某种虚假的局部最小值。比如你可能会去最小化虾类养殖场的痛苦，这在我看来并不怎么有建设性。又或者你可能陷入”线头享乐主义”（书童注：wireheading，指通过直接刺激大脑奖励中心获得快感而忽视其他目标的状态）——装一个脑机接口，或者永远刷TikTok，短期内因为神经化学反应而感觉良好，但从长期来看，它导向衰败与死亡，因为你什么也没有创造。
GUILLAUME VERDON (02:29:04) Their loss function is sort of hedons, units of hedonism. How good do you feel, and for how much time? And so, suffering would be negative hedons, and they’re trying to minimize that. But to us that seems like that loss function has sort of spurious minima, you can start minimizing shrimp farm pain, which seems not that productive to me. Or you can end up with wire heading, where you just either install a neural link, or you scroll TikTok forever, and you feel good on the short-term timescale because of your neurochemistry, but on a long-term timescale, it causes decay and death, because you’re not being productive.
Guillaume Verdon (02:29:54) 而e/acc的做法则是用一个客观的度量来衡量文明进步——不是享乐主义这种主观的损失函数，而是物理能量这一客观量，它无法被操纵，极其客观，没有多少空子可钻。如果用GDP或货币来衡量，那是锚定在某个浮动价值上的，不是衡量进步的好方法。但归根结底，我们双方都在试图推动进步、确保人类繁荣发展，只是选择了不同的损失函数和不同的路径。
GUILLAUME VERDON (02:29:54) Whereas sort of EAC, measuring progress of civilization, not in terms of a subjective loss function like hedonism, but rather an objective measure, quantity that cannot be gamed that is physical energy, it’s very objective, and there’s not many ways to game it. If you did it in terms of GDP, or a currency, that’s pinned to certain value that’s moving. And so, that’s not a good way to measure our progress. But the thing is we’re both trying to make progress, and ensure humanity flourishes, and gets to grow. We just have different loss functions, and different ways of going about doing it.
Lex Fridman (02:30:42) 也许你可以指点我、纠正我——每当有人试图把整个人类文明、人类体验简化为一个方程式时，我总会有些警惕。我们是否应该对方程式的暴政、对优化损失函数的执念保持怀疑？是否需要对”优化损失函数”这件事本身抱有一种认知上的谦逊？
LEX FRIDMAN (02:30:42) Is there a degree, maybe you can educate me, correct me, I get a little bit skeptical when there’s an equation involved trying to reduce all of the human civilization, human experience to an equation. Is there a degree that we should be skeptical of the tyranny of an equation of a loss function over wish to optimize? Like having a kind of intellectual humility about optimizing over loss functions?
Guillaume Verdon (02:31:12) 是的。这个特定的损失函数并不是刚性的，它更像是平均值的平均值——未来状态的分布本身服从某种分布。所以它不是确定性的，我们并没有被锁死在某条固定轨道上，这只是关于未来的一个统计性陈述。但说到底，你可以选择信不信引力，但不服从它可不是一个选项——有些人试过了，下场不太好。同理，热力学就在那里，不以我们的好恶为转移。我们只是在试图指出”什么是”，然后据此找准自己的方位，规划前行的路径。
GUILLAUME VERDON (02:31:12) Yeah. So, this particular loss function, it’s not stiff. It’s kind of an average of averages. It’s like distributions of states in the future are going to follow a certain distribution. So it’s not deterministic, it’s not like… We’re not on stiff rails. It’s just a statistical statement about the future. But at the end of the day, you can believe in gravity or not, but it’s not necessarily an option to obey it. And some people try to test that, and that goes not so well. So, similarly, I think thermodynamics is there whether we like it or not, and we’re just trying to point out what is, and try to orient ourselves, and chart a path forward given this fundamental truth.
Lex Fridman (02:32:04) 但终究还是存在不确定性，存在信息的缺口，而人类天生倾向于用叙事来填补这些缺口。对物理学的解读……当涉及不确定性时，即使物理学也可以被各种诠释。人类总善于利用这种模糊性来为自身目的服务。所以每当一个方程式出现，在我们真正完美理解宇宙之前，人类总会做人类擅长的事——借”行善”之名蒙蔽大众，行不善之实。我想这是我们对所有运动都应保持警惕的地方。
LEX FRIDMAN (02:32:04) But there’s still some uncertainty, there’s still a lack of information, and humans tend to fill the gap of the lack of information with narratives. And so, how they interpret… Even physics is up to interpretation when there’s uncertainty involved. And humans tend to use that to further their own means. So, it’s always, whenever there’s an equation, it just seems like until we have really perfect understanding of the universe, humans will do what humans do, and they try to use the narrative of doing good to fool the populace into doing bad. I guess that this is something that we should be skeptical about in all movements.
Guillaume Verdon (02:32:57) 没错，所以我们欢迎质疑，对吧？
GUILLAUME VERDON (02:32:57) That’s right? So we invite skepticism. Right?
Lex Fridman (02:33:02) 你觉得有效利他主义到底哪里出了问题？这些问题是否也可能出现在有效加速主义身上？
LEX FRIDMAN (02:33:02) Do you have an understanding of what might, to a degree that went wrong, what do you think may have gone wrong with effective altruism that might also go wrong with effective accelerationism?
Guillaume Verdon (02:33:15) 嗯，我觉得它早期确实为工程师、知识分子和理性主义者提供了一种社群归属感，那时社群看起来非常健康。但后来他们组建了各种机构，开始调配资本，掌握了实际权力。他们拥有真实的权力——他们影响政府，如今影响着大多数AI组织。他们实质上控制着OpenAI的董事会，再看看Anthropic，我想他们在那里也有相当的影响力。而e/acc的预设更像是资本主义的逻辑：每个个体、每个组织和元组织都会为自身利益行事，我们应该在所有时间、所有尺度上保持某种对抗性均衡或竞争博弈，以相互制约。我认为，说到底，”行善”的旗号为他们积累巨量权力和资本提供了完美的掩护，而不幸的是，权力往往会随时间腐蚀人心。
GUILLAUME VERDON (02:33:15) Yeah, I mean I think it provided initially a sense of community for engineers, and intellectuals, and rationalists in the early days, and it seems like the community was very healthy, but then they formed all sorts of organizations, and started routing capital, and having actual power. They have real power. They influence the government, they influence most AI orgs now. I mean, they’re literally controlling the board of OpenAI, and look over to Anthropic. I think they’ll have some control over that too. And so, I think the assumption of e/acc is more like capitalism, is that every agent organism and meta organism is going to act in its own interest, and we should maintain sort of adversarial equilibrium, or adversarial competition to keep each other in check at all times, at all scales. I think that yeah, ultimately, it was the perfect cover to acquire tons of power, and capital, and unfortunately sometimes that corrupts people over time.
Lex Fridman (02:34:23) 既然你说建造很重要，那Guillaume Verdon的完美高效一天是什么样的？你每天摄入多少咖啡因？完美的一天长什么样？
LEX FRIDMAN (02:34:23) What does a perfectly productive day, since building is important, what is a perfectly productive day in the life of Guillaume Verdon look like? How much caffeine do you consume? What’s a perfect day?
Guillaume Verdon (02:34:39) 好的，我有一套特定的作息。我最理想的工作日是中午12点到凌晨4点。下午早些时候处理会议，通常是外部会议，也有一些内部会议。因为我是CEO，必须和外界打交道——客户、投资者、面试候选人。这段时间我通常会摄入外源性酮体。
GUILLAUME VERDON (02:34:39) Okay, so I have a particular regimen. I would say my favorite days are 12:00 PM to 4:00 AM, and I would have meetings in the early afternoon, usually external meetings, some internal meetings. Because I’m CEO, I have to interface with the outside world, whether it’s customers, or investors, or interviewing potential candidates. And usually I’ll have ketones, exogenous ketones.
Lex Fridman (02:35:12) 所以你在遵循生酮饮食，还是——
LEX FRIDMAN (02:35:12) So, are you on a keto diet, or is this-
Guillaume Verdon (02:35:16) 我以前为了打橄榄球做过生酮饮食之类的，但现在我喜欢把一天的一部分工作做完之后再吃饭，这样就能保持极致的专注力。
GUILLAUME VERDON (02:35:16) I’ve done keto before for football, and whatnot, but I like to have a meal after part of my day is done, and so I can just have extreme focus.
Lex Fridman (02:35:31) 你在上半天空腹处理社交事务。
LEX FRIDMAN (02:35:31) You do the social interactions earlier in the day without food.
Guillaume Verdon (02:35:35) 把社交前置，对。就像我现在就靠酮体和红牛撑着，它给你的思维清晰度真的是另一个层次。因为一旦你吃了东西，本来可以供给神经活动的能量就要分配给消化系统了。吃完饭后我大概休息一个小时到一个半小时。理想状态是一天只吃一顿——牛排、鸡蛋加蔬菜，以动物性食物为主，水果和肉。然后进入第二轮高峰期，那通常是深度工作时间。虽然我是CEO，但我依然保持技术参与，大多数专利都有我的贡献。那个时段我就熬到深夜，和工程师们一起攻克高度技术性的问题。
GUILLAUME VERDON (02:35:35) Front load them, yeah. Yeah. Like right now I’m on ketones, and a Red Bull, and it just gives you a clarity of thought that is really next level. Because then when you eat, you’re actually allocating some of your energy that could be going to neural energy to your digestion. After I eat, maybe I take a break, an hour or so, an hour and a half, and then usually it’s like ideally one meal a day, like steak and eggs, and vegetables, animal-based primarily. So, fruit and meat. And then I do a second wind, usually that’s deep work, because I am A CEO, but I’m still technical. I’m contributing to most patents. And there, I’ll just stay up late into the night, and work with engineers on very technical problems.
Lex Fridman (02:36:25) 也就是大概晚上9点到凌晨4点那个时段。
LEX FRIDMAN (02:36:25) So it’s like the 9:00 PM to 4:00 AM, whatever though, that range of time.
Guillaume Verdon (02:36:30) 对，那是完美的时段。邮件不再涌来，各种紧急事务也消停了，你终于可以专注。然后你迎来第二波高峰。据我所知，Demis Hassabis（书童注：DeepMind创始人）的工作节奏也差不多，这确实启发了我的作息安排。我在谷歌时就开始这么做了——白天管产品、开会，晚上做技术工作。
GUILLAUME VERDON (02:36:30) Yeah, yeah. That’s the perfect time. The emails, the things that are on fire stop trickling in, you can focus. And then you have your second wind. And I think Demis Hassabis has a similar workday to some extent. So, I think that’s definitely inspired my workday. But yeah, I started this workday when I was at Google, and had to manage a bit of the product during the day, and have meetings, and then do technical work at night.
Lex Fridman (02:37:00) 那锻炼、睡眠这些呢？你提到了橄榄球，你以前打橄榄球？
LEX FRIDMAN (02:37:00) Exercise, sleep, those kinds of things. You said football, you used to play football?
Guillaume Verdon (02:37:06) 对，我以前打美式橄榄球，从小各种运动都练过。后来有段时间痴迷撸铁。读研学数学那会儿，我的一天就是：做数学、举铁、摄入咖啡因，仅此而已。极其纯粹，最纯粹的僧侣模式。但撸铁有一点特别有意思：你通过特定的驱动信号来诱发神经适应，通过各种补剂来增强神经可塑性，举重时大脑会分泌各种脑源性神经营养因子。
GUILLAUME VERDON (02:37:06) Yeah, I used to play American football. I’ve done all sorts of sports growing up. And then I was into powerlifting for a while. So, when I was studying mathematics in grad school, I would just do math, and lift, take caffeine, and that was my day. It was very pure, the purest of monk modes. But it’s really interesting, how in powerlifting you’re trying to cause neural adaptation by having certain driving signals, and you’re trying to engineer a neuroplasticity through all sorts of supplements, and you have all sorts of brain derived neurotrophic factors that get secreted when you lift.
Guillaume Verdon (02:37:44) 所以对我来说很有意思的是，我当时一边学数学，一边试图在整个神经系统——不仅仅是大脑——层面上去设计神经适应。我觉得如果你真正在乎所学的东西，学习速度会快得多。如果你能说服自己对正在学的东西极度在乎，再加上某种辅助——比如咖啡因，或某种胆碱能补剂来增强神经可塑性——效果会更显著。这个我应该找Andrew Huberman聊聊，他才是专家。但至少在我的经验里，你可以试着给大脑灌入更多的token，可以试着调高学习率，这样就能在更短的时间内学得更快。
GUILLAUME VERDON (02:37:44) So, it’s funny to me how I was trying to engineer a neural adaptation in my nervous system more broadly, not just my brain while learning mathematics. I think you can learn much faster if you really care. If you convince yourself to care a lot about what you’re learning, and you have some sort of assistance, let’s say caffeine, or some cholinergic supplement to increase neuroplasticity. I should chat with Andrew Huberman at some point. He’s the expert. But yeah, at least to me it’s like you can try to input more tokens into your brain, if you will, and you can try to increase the learning rate, so that you can learn much faster on a shorter timescale.
Guillaume Verdon (02:38:30) 我就是这样学了很多东西——追随好奇心。如果你对正在做的事情充满热情，你就会学得更快，变聪明的速度也更快。如果你追随好奇心，你就永远不会觉得无聊。所以我建议大家追随自己的好奇心，不要被学科的边界或工作中被分配的赛道所束缚。走出去探索，跟着直觉走，尽可能多地获取信息、将其压缩进你的大脑——任何你觉得有趣的东西都行。
GUILLAUME VERDON (02:38:30) So, I’ve learned a lot of things. I’ve followed my curiosity. You’re naturally… If you’re passionate about what you’re doing, you’re going to learn faster, you’re going to become smarter faster. And if you follow your curiosity, you’re always going to be interested. And so, I advise people to follow their curiosity and don’t respect the boundaries of certain fields, or what you’ve been allocated in terms of lane of what you’re working on. Just go out and explore, and follow your nose, and try to acquire, and compress as much information as you can into your brain. Anything that you find interesting.
Lex Fridman (02:39:05) 还有就是在乎一件事。就像你说的，这一点很有意思，对我也非常管用——就是”骗”自己去在乎一件事。
LEX FRIDMAN (02:39:05) And caring about a thing. Like you said, which is interesting, it works for me really well, is tricking yourself that you care about a thing.
Guillaume Verdon (02:39:12) 是的。
GUILLAUME VERDON (02:39:12) Yes.
Lex Fridman (02:39:13) 然后你就真的开始在乎了。
LEX FRIDMAN (02:39:13) And then you start to really care about it.
Guillaume Verdon (02:39:15) 没错。
GUILLAUME VERDON (02:39:15) Yep.
Lex Fridman (02:39:15) 所以有意思的是，热情是学习的绝佳催化剂。
LEX FRIDMAN (02:39:15) So, it’s funny, the motivation is a really good catalyst for learning.
Guillaume Verdon (02:39:22) 没错。所以我扮演Beff Jezos这个角色，至少有一部分就是这种……
GUILLAUME VERDON (02:39:22) Right. And so, at least part of my character, as Beff Jezos is kind of like…
Lex Fridman (02:39:29) 对，自我激励大师。
LEX FRIDMAN (02:39:29) Yeah, hype man.
Guillaume Verdon (02:39:30) 对，但其实我是在给自己打鸡血，然后顺便发条推文而已。当我试图让自己进入一种极度亢奋的状态——一种改变了的意识状态，极度专注、进入心流、全身通电、试图发明从未存在过的东西——我需要达到一种不可思议的兴奋程度。而大脑确实有这些隐藏的认知层级，可以通过更高水平的肾上腺素等来解锁。我从撸铁中学到了这一点：你可以训练出一个心理开关来增强你的力量。如果你能设计出这样一个开关——也许是某首歌、某段音乐作为触发信号——突然间你就完全进入状态，达到最大力量输出。我通过多年的举铁训练出了这个开关。当你要扛起500磅的杠铃、它随时可能压碎你的时候，如果你没有把那个开关打开，你可能会死。这种求生本能会瞬间唤醒你的全部潜能。我把这项技能迁移到了研究工作中——每到关键时刻、赌注极高的时候，我就能进入另一个层次的神经表现状态。
GUILLAUME VERDON (02:39:30) Yeah, but I’m hyping myself up, but then I just tweet about it, and it’s just when I’m trying to get really hyped up, and an altered state of consciousness where I’m ultra focused, in the flow, wired, trying to invent something that’s never existed, I need to get to unreal levels of excitement. But your brain has these levels of cognition that you can unlock with higher levels of adrenaline, and whatnot. And I mean, I’ve learned that in powerlifting, that actually you can engineer a mental switch to increase your strength. If you can engineer a switch, maybe you have a prompt, like a certain song or some music where suddenly you’re fully primed, then you’re at max, maximum strength. And I’ve engineered that switch through years of lifting. If you’re going to get under 500 pounds and it could crush you, if you don’t have that switch to be wired in, you might die. So, that’ll wake you right up. That sort of skill I’ve carried over to research, when it’s go time, when the stakes are high, somehow I just reach another level of neural performance.
Lex Fridman (02:40:40) 所以Beff Jezos就是你的智识版浩克，你的生产力浩克——把开关一拧就行了。
LEX FRIDMAN (02:40:40) So Beff Jezos is your sort of embodiment representation of your intellectual Hulk. It’s your productivity Hulk that you just turn on.
Guillaume Verdon (02:40:50) 是的。
GUILLAUME VERDON (02:40:50) Yeah.
Lex Fridman (02:40:50) 拥有这两个身份，你从中对身份的本质有了什么领悟？我觉得有意思的是，一个人能如此明确地在两顶帽子之间切换。
LEX FRIDMAN (02:40:50) What have you learned about the nature of identity from having these two identities? I think it’s interesting for people, to be able to put on those two hats so explicitly.
Guillaume Verdon (02:41:01) 早期很有意思。那时候我觉得两个身份是完全隔开的——”哦，这不过是个角色，我是Guillaume，Beff只是一个人设。”我把自己的想法拿过来，再推到更极端一点。但随着时间推移，两个身份在心理上开始融合。有人会对我说：”不，我见过你本人，你就是Beff，你不仅仅是Guillaume。”我当时愣了一下：”等等，我是吗？”现在两者已经完全合一了。但其实在身份被曝光之前，这种融合在心理层面就已经开始了——我就是这个角色，它是我的一部分。
GUILLAUME VERDON (02:41:01) I think it was interesting in the early days, I think in the early days, I thought it was truly compartmentalized. Like, “Oh yeah, this is a character. I’m Guillaume. Beff is just the character.” I take my thoughts, and then I extrapolate them to a bit more extreme. But over time, it’s kind of like both identities were starting to merge mentally, and people were like, “No, I met you. You are Beff. You are not just Guillaume.” And I was like, “Wait, am I?” And now it’s fully merged. But it was already, before the docs, it was already starting mentally that I am this character. It’s part of me.
Lex Fridman (02:41:39) 你会推荐别人也搞一个小号吗？
LEX FRIDMAN (02:41:39) Would you recommend people have an alt?
Guillaume Verdon (02:41:42) 绝对推荐。
GUILLAUME VERDON (02:41:42) Absolutely.
Lex Fridman (02:41:43) 比如年轻人，你会建议他们通过小号来探索不同的身份吗？匿名账号？
LEX FRIDMAN (02:41:43) Like young people. Would you recommend them to explore different identities by having alts? Alt accounts?
Guillaume Verdon (02:41:49) 这很有趣。就像写一篇辩论文章并选择一个立场，对吧？辩论赛里你就是这么做的。关键是你可以有实验性的想法——因为赌注极低，你只是一个匿名账号，可能才20个粉丝，你可以在一个低风险的环境里试验你的想法。我觉得在这个一切都绑定真名、一切都可追溯到你本人的时代，我们失去了这种可能性。人们害怕开口，害怕探索那些尚未成形的想法，我觉得我们在这里失去了一些珍贵的东西。所以我希望X等平台能真正支持用户保持匿名，因为让人们自由分享尚未成熟的想法、逐步逼近那些隐藏的真理至关重要——仅靠实名的公开讨论，很难抵达那些真理。
GUILLAUME VERDON (02:41:49) It’s fun. It’s like writing an essay, and taking a position, right? It’s like you do this in debate. It’s like you can have experimental thoughts, and by the stakes being so low, because you’re an anon account with, I don’t know, 20 followers or something, you can experiment with your thoughts in a low stakes environment. And I feel like we’ve lost that in the era of everything being under your main name, everything being attributable to you. People just are afraid to speak, explore ideas that aren’t fully formed, and I feel like we’ve lost something there. So, I hope platforms like X and others really help support people trying to stay synonymous, or anonymous, because it’s really important for people to share thoughts that aren’t fully formed, and converge onto maybe hidden truths that were hard to converge upon if it was just through open conversation with real names.
Lex Fridman (02:42:46) 是的。我真心信奉一种——不是激进的，而是严谨的共情。就是认真去想象：持有某种观点的人，他的世界是什么样的？然后把这个思想实验一步步推向更深处。小号就是实现这一点的一种方式。它提供了一种有趣的途径，让你真正去体验”作为一个持有某套信念的人”是什么感觉，并且在几天、几周、几个月的跨度里持续扮演。当然，始终存在一个危险：你可能真的变成那个人。这就是尼采说的——”当你长久凝视深渊时，深渊也在凝视你。”得小心。
LEX FRIDMAN (02:42:46) Yeah. I really believe in not radical, but rigorous empathy. It’s like really considering what it’s like to be a person of a certain viewpoint, and taking that, as a thought experiment, farther and farther and farther. And one way of doing that as an alt account. That’s a fun, interesting way to really explore what it’s like to be a person that believes a set of beliefs, and taking that across the span of several days, weeks, months. Of course there’s always the danger of becoming that. That’s the Nietzche, “Gaze long into the abyss, the abyss gazes into you.” You have to be careful.
Guillaume Verdon (02:42:46) Breaking Beff（书童注：戏仿美剧《绝命毒师》Breaking Bad）。
GUILLAUME VERDON (02:42:46) Breaking Beff.
Lex Fridman (02:43:31) 对，Breaking Beff。哪天你醒来发现自己剃了光头：”我是谁？我变成了什么？”好了，你已经给出了不少建议，但你会给年轻人什么忠告？在我们所处的这个风云变幻的世界里，如何去经营一份事业，过一种自己可以引以为豪的人生？
LEX FRIDMAN (02:43:31) Yeah, right. Breaking Beff. Yeah. You wake up with a shaved head one day, just like, “Who am I? What have I become?” So, you’ve mentioned quite a bit of advice already, but what advice would you give to young people of, in this interesting world we’re in, how to have a career and how to have a life they can be proud of?
Guillaume Verdon (02:43:58) 对我来说，当初选择理论物理的原因是：我想学习技术栈的最底层——那些无论技术如何迭代都不会过时的东西。那是我的根基，后来我在此基础上一层层搭建起工程技能和其他能力。物理定律不会变。当下的技术版图看起来变化飞快，让人晕头转向，但有些东西——基础数学和物理——是永恒的。如果你掌握了这些知识，再加上对复杂系统和适应性系统的理解，我认为你会走得非常远。不是每个人都必须学数学，但我认为学习数学、物理和工程，真的是一次巨大的认知解锁。
GUILLAUME VERDON (02:43:58) I think to me, the reason I went to theoretical physics was that I had to learn the base of the stack that was going to stick around no matter how the technology changes. And to me, that was the foundation upon which then I later built engineering skills, and other skills. And to me, the laws of physics, it may seem like the landscape right now is changing so fast, it’s disorienting. But certain things like fundamental mathematics and physics aren’t going to change. And if you have that knowledge, and knowledge about complex systems, and adaptive systems, I think that’s going to carry you very far. And so, not everybody has to study mathematics, but I think it’s really a huge cognitive unlock to learn math, and some physics, and engineering.
Lex Fridman (02:44:48) 尽可能深入到技术栈的最底层。
LEX FRIDMAN (02:44:48) Get as close to the base of the stack as possible.
Guillaume Verdon (02:44:51) 对，没错。因为技术栈的底层是不变的。其他一切……你的知识可能几年后就不再那么相关了。当然你可以做一种迁移学习，但那样你就得不停地迁移，永无止境。
GUILLAUME VERDON (02:44:51) Yeah, that’s right. Because the base of the stack doesn’t change. Everything else… Your knowledge might become not as relevant in a few years. Of course there’s a sort of transfer learning you can do, but then you have to always transfer learn, constantly.
Lex Fridman (02:45:04) 我想你越接近技术栈的底层，迁移学习就越容易，跨度也越小。
LEX FRIDMAN (02:45:04) I guess the closer you are to the base of the stack, the easier the transfer learning, the shorter the jump.
Guillaume Verdon (02:45:10) 对。你会惊讶于，一旦你在各种物理场景中掌握了核心概念，它们竟能如此自然地迁移到理解其他非物理系统中去。e/acc的那些著述——原则与信条那几篇帖子——就是基于物理学的。那其实就是我尝试将非平衡热力学的思维方式应用于理解周围世界的一次实验，而它最终催生了e/acc和这场运动。
GUILLAUME VERDON (02:45:10) Right, right. And you’d be surprised, once you’ve learned concepts in many physical scenarios, how they can carry over to understanding other systems that aren’t necessarily physics. And I guess the e/acc writings, the principles and tenet posts, that was based on physics, that was kind of my experimentation with applying some of the thinking from out of [inaudible 02:45:36] thermodynamics to understanding the world around us, and it’s led to e/acc, and this movement.
Lex Fridman (02:45:42) 如果你把自己看作这台资本主义机器中的一个齿轮，一个人类个体——你认为死亡是一个特性还是一个bug？你想要永生吗？
LEX FRIDMAN (02:45:42) If you look at you’re one cog in the machine, in the capitalist machine, one human, and if you look at yourself, do you think mortality is a feature or a bug? Would you want to be immortal?
Guillaume Verdon (02:45:57) 不。我认为从根本上说，在”热力学耗散适应”这个概念中，”耗散”二字赫然在列。耗散是重要的，死亡也是重要的。物理学界有句老话：物理学的进步，是一场葬礼接一场葬礼地推进的。
GUILLAUME VERDON (02:45:57) No, I think fundamentally, in thermodynamic dissipative adaptation, there’s the word dissipation. Dissipation is important, death is important. We have a saying in physics, physics progresses one funeral at a time.
Lex Fridman (02:46:16) 是的。
LEX FRIDMAN (02:46:16) Yeah.
Guillaume Verdon (02:46:17) 资本主义同样如此。公司、帝国、人——万物终有一死。不过我确实认为我们应该延长寿命，因为世界日趋复杂，我们需要更长的训练周期来消化越来越多的数据，从而真正理解和预测世界。如果高神经可塑性的窗口是有限的，那我们理解世界的能力就有一个硬性上限。所以，我支持死亡——因为它确实重要。如果你有一个永远不死的国王，那会是灾难。系统将无法持续适应，对吧？
GUILLAUME VERDON (02:46:17) I think the same is true for capitalism. Companies, empires, people, everything. Everything must die at some point. I think that we should probably extend our lifespan, because we need a longer period of training, because the world is more and more complex. We have more and more data to really be able to predict and understand the world. And if we have a finite window of higher neuroplasticity, then we have sort of a hard cap in how much we can understand about our world. So, I think I am for death, because again, I think it’s important. If you have a king that would never die, that would be a problem. The system wouldn’t be constantly adapting, right?
Guillaume Verdon (02:47:05) 你需要新鲜血液，需要年轻一代，需要颠覆性力量来确保系统始终在适应、始终保持可塑性。否则，如果事物永生不灭——比如一家永远霸占市场的垄断公司——它们就会钙化，在不断变化的动态环境中变得不再最优、不再具有高适应性。所以，死亡为年轻和新鲜事物腾出了空间。我认为这是自然界中每个系统的必要组成部分。总而言之，我支持死亡，但也确实认为更长的寿命、更持久的神经可塑性窗口、更大的大脑，应该是我们努力追求的方向。
GUILLAUME VERDON (02:47:05) You need novelty, you need youth, you need disruption to make sure the system’s always adapting, and malleable. Otherwise, if things are immortal, if you have, let’s say corporations that are there forever, and they have the monopoly, they get calcified, they become not as optimal, not as high fitness in a changing, time varying landscape. And so, death gives space for youth and novelty to take its place. And I think it’s an important part of every system in nature. So yeah, I am for death, but I do think that longer lifespan, and longer time for neuroplasticity, bigger brains should be something we should strive for.
Lex Fridman (02:47:52) 有意思的是，Jeff Bezos和Beff Jezos在这一点上达成了共识：所有公司终将消亡。Jeff的做法是他所说的”Day One思维”——试图不断自我革新，尽可能延长公司的寿命。但最终它也会死去，因为持续的自我革新实在太难了。你害怕自己的死亡吗？
LEX FRIDMAN (02:47:52) Well, and that, Jeff Bezos, and Beff Jezos agree that all companies die. And for Jeff, the goal is to try to, he calls it day one thinking, try to constantly, for as long as possible, reinvent, sort of extend the life of the company. But eventually it too will die, because it’s so difficult to keep reinventing. Are you afraid of your own death?
Guillaume Verdon (02:48:23) 我心中有很多想法，有很多想在这个世界上实现的事情，趁我还在的时候。但我不觉得自己害怕死亡。
GUILLAUME VERDON (02:48:23) I think I have ideas and things I’d like to achieve in this world before I have to go, but I don’t think I’m necessarily afraid of death.
Lex Fridman (02:48:34) 所以你并不执着于你此生获得的这副身体和这颗头脑？
LEX FRIDMAN (02:48:34) So you’re not attached to this particular body, and mind that you got?
Guillaume Verdon (02:48:38) 不执着。我相信未来一定会有比我更好的版本，或者……
GUILLAUME VERDON (02:48:38) No, I’m sure there’s going to be better versions of myself in the future, or…
Lex Fridman (02:48:46) 分叉？
LEX FRIDMAN (02:48:46) Forks?
Guillaume Verdon (02:48:47) 分叉，对吧？基因层面的分叉，或者其他形式的。我真心相信这一点。我认为世界的每一个比特、每一个[听不清]都在通过我们在e/acc中描述的这个过程不断适应，其中运行着一种类进化算法。保持这种适应的可塑性，才是整台机器得以持续优化的方式。所以，我不认为自己是一个需要永远保留的最优解。未来一定会出现在诸多方面更优的解。
GUILLAUME VERDON (02:48:47) Forks, right? Genetic forks, or other, right? I truly believe that. I think there’s a sort of evolutionary-like algorithm happening at every bit, or [inaudible 02:49:03] in the world is sort of adapting through this process that we described in e/acc. And I think maintaining this adaptation malleability is how we have constant optimization of the whole machine. And so, I don’t think I’m particularly an optimum that needs to stick around forever. I think there’s going to be greater optima in many ways.
Lex Fridman (02:49:25) 你认为这一切的意义是什么？这台机器运转的”为什么”是什么？e/acc这台机器的？
LEX FRIDMAN (02:49:25) What do you think is the meaning of it all? What’s the why of the machine? The e/acc machine?
Guillaume Verdon (02:49:32) 为什么？答案就是热力学。这就是我们存在于此的原因，这就是催生生命、文明、技术演化和文明增长的力量。但我们为什么有热力学？为什么偏偏是这个宇宙？为什么是这些特定的超参数、这些自然常数？这就进入了人择原理和可能宇宙的景观问题，对吧？我们恰好处在一个允许生命存在的宇宙中。那为什么？是否存在许多宇宙？这个我不知道。但我们是否有可能设计新的宇宙，或者创造口袋宇宙，并设定其超参数，使得我们的存在与那个宇宙之间存在某种互信息——使我们在某种意义上成为它的创造者？我觉得这……真的非常诗意。当然这纯属猜想。但这也正是为什么破解量子引力如此重要——它会让我们知道，这一切是否有可能。
GUILLAUME VERDON (02:49:32) The why? Well, the why is thermodynamics. It’s why we’re here. It’s what has led to the formation of life, and of civilization, of evolution of technologies, and growth of civilization. But why do we have thermodynamics? Why do we have our particular universe? Why do we have these particular hyper-parameters, the constants of nature? Well then you get into the anthropic principle, and the landscape of potential universes, right? We’re in the universe that allows for life. And then why, is there potentially many universes? I don’t know. I don’t know that part. But could we potentially engineer new universes, or create pocket universes, and set the hyper-parameters so there is some mutual information between our existence in that universe, and we’d be somewhat its parents? I think that’s really… I don’t know, that’d be very poetic. It’s purely conjecture. But again, this is why figuring out quantum gravity would allow us to understand if we can do that.
Lex Fridman (02:50:39) 在这之上还有一层：为什么这一切看起来如此美丽、如此令人激动？探索量子引力的征程本身就让人心潮澎湃。为什么？为什么我们会被它吸引、被它牵引？那种解谜的、创造性的力量，似乎支撑着这一切。
LEX FRIDMAN (02:50:39) And above that, why does it all seems so beautiful and exciting? The quest to figuring out quantum gravity seems so exciting. Why? Why is that? Why are we drawn to that? Why are we pulled towards that? Just that puzzle solving creative force that underpins all of it, it seems like.
Guillaume Verdon (02:51:01) 我认为我们在追求一种东西——就像大语言模型试图最小化其内部模型与真实世界之间的交叉熵一样，我们也在试图最小化我们的预测与真实世界之间的统计偏差。在某些能量尺度或物理尺度上，如果我们没有任何可见性、没有预测和感知的能力，那对我们来说简直是一种冒犯。我们渴望更好地理解世界，从而能够最好地引导它——或者引导我们穿越其中。
GUILLAUME VERDON (02:51:01) I think we seek, just like an LLM seats to minimize cross entropy between its internal model and the world, we seek to minimize… Yeah, the statistical divergence between our predictions and the world, and the world itself. And having regimes of energy scales, or physical scales in which we have no visibility, no ability to predict, or perceive, that’s kind of an insult to us. And we want to be able to understand the world better in order to best steer it, or steer us through it.
Guillaume Verdon (02:51:37) 归根结底，这是一种进化而来的能力——你越能预测世界，就越能捕获效用或自由能，用于自身的存续和增长。量子引力，就像是知识获取的最终Boss——一旦我们攻克了它，潜在的可能性将是巨大的。但从现在到那一步之间，在介观尺度上还有太多要学习的东西。关于我们这个世界，还有海量的信息有待获取，在感知、预测和控制的工程化方面还有大量工作要做，才能攀上卡尔达舍夫文明等级的更高阶梯。对我们来说，这就是我们这个时代的宏大挑战。
GUILLAUME VERDON (02:51:37) And in general, it’s a capability that has evolved because the better you can predict the world, the better you can capture utility, or free energy towards your own sustenance and growth. And I think quantum gravity, again, is kind of the final boss, in terms of knowledge acquisition, because once we’ve mastered that, then we can do a lot, potentially. But between here and there, I think there’s a lot to learn in the meso scales. There’s a lot of information to acquire about our world, and a lot of engineering perception, prediction, and control to be done, to climb up the Carta shift scale. And to us, that’s the great challenge of our times.
Lex Fridman (02:52:22) 当你不确定前路在何方时，让模因来开路。
LEX FRIDMAN (02:52:22) And when you’re not sure where to go, let the meme pave the way.
Guillaume Verdon (02:52:26) 没错。
GUILLAUME VERDON (02:52:26) That’s right.
Lex Fridman (02:52:27) Guillaume，Beff，感谢今天的对话。感谢你正在做的工作，感谢你向这个世界注入的幽默与智慧。这次对话太精彩了。
LEX FRIDMAN (02:52:27) Guillaume, Beff, thank you for talking today. Thank you for the work you’re doing. Thank you for the humor, and the wisdom you put into the world. This was awesome.
Guillaume Verdon (02:52:37) 非常感谢你的邀请，Lex，我深感荣幸。
GUILLAUME VERDON (02:52:37) Thank you so much for having me, Lex, It’s a pleasure.
Lex Fridman (02:52:40) 感谢收听本期与Guillaume Verdon的对话。如需支持本播客，请查看简介中的赞助商信息。最后，让我以阿尔伯特·爱因斯坦的一句话作结：”如果一个想法初听之下并不荒谬，那它就毫无希望可言。”感谢收听，期待下次再见。
LEX FRIDMAN (02:52:40) Thank you for listening to this conversation with Guillaume Verdon. To support this podcast. Please check out our sponsors in the description. And now, let me leave you with some words from Albert Einstein. “If at first the idea is not absurd, then there is no hope for it.” Thank you for listening. I hope to see you next time.