内容来源：https://www.theverge.com/tldr/915176/nft-metaverse-ai-weirdos

内容总结：

近期，硅谷科技圈内一种现象引发关注：部分从业者沉浸于“重新发明轮子”的兴奋中，却忽视了常识与用户真实需求。一位技术从业者曾激动地向作者阐述“大语言模型揭示了知识存在于语言结构中”的“新发现”，而这实际是语言学中结构主义学派早已提出的基础概念。此类将已知理论包装为突破性洞见的情况，在科技精英中并不鲜见——从惊叹“人手结构之复杂”到宣称“发现弗洛伊德创立的内省法”，背后折射出部分从业者因知识壁垒和过度自信导致的认知局限。

这种脱离现实的“傲慢”已从个人认知蔓延至产业逻辑。过去，科技企业的核心是洞察并满足用户需求；如今，许多硅谷公司却热衷于向市场强行推广自己构想的“未来”，从NFT、元宇宙到VR头显，诸多技术概念虽引发投资热潮，却因未能解决真实痛点而迅速沉寂。即便是引发全民讨论的AI技术，其在大众生活中的实际应用仍局限于信息检索和作业辅助，而音乐生成、内容创作等场景则更多被投机者滥用，反而侵蚀了创意生态的生存空间。

值得玩味的是，硅谷著名投资人马克·安德森曾在访谈中提及，一些创业者在压力下尝试致幻剂后“变得平和，却往往选择离开公司”。这番言论无意间揭示了硅谷文化的深层矛盾：当“改变世界”的野心凌驾于对人的真实关怀之上，当技术演进沦为资本逐利的狂欢，科技行业与普通人生活的脱节便日益加剧。或许，塑造未来的真正方式并非将臆想强加于用户，而是回归本质：提供人们真正需要的东西。

中文翻译：

认识许多科技从业者最令人尴尬的一点，就是听他们兴奋地向我讲述那些他们自以为的重大发现。最近我遇到一位熟人，他滔滔不绝地向我展示关于大语言模型的惊人发现：原来知识是建构在语言中的！你可以往ChatGPT里输入一个词，它或许能理解你的意图；或者编造一个词，测试它是否明白你的意思！这些神奇的新工具揭示了英语语料库中蕴藏着多少关于使用者的信息！

硅谷已忘记普通人想要什么

从NFT、AI和元宇宙看"思想领导力"的虚妄

他最终断言大语言模型是与文字发明同等重要的发现。而普通人类早在一个世纪前就已触及这个理念——我对他言论最善意的解读是，他偶然发现了一种天真混沌的结构主义变体，就像经过传话游戏扭曲的索绪尔理论。（近期确有类似研究主张通过文学理论理解大语言模型，其源头正是索绪尔。）我竭力想结束这场对话，不仅因为他对我未能全盘接受其观点流露出的沮丧——这种新行为模式很可能正是过度依赖大语言模型的后遗症。

投身未解难题确实需要某种傲气，但在其他领域，这种傲慢反而会成为负累。

并非所有令你新奇的事物都是真正的创新。比如埃隆·马斯克惊叹于手掌的复杂性，其实这在多个领域都是入门常识：艺术家需要研究如何描绘它们，外科医生需要掌握手术技巧，音乐家和魔术师依赖精细运动技能完成表演，神经科学家和心理学家早在职业生涯初期就接触过皮质小人模型。或是帕尔默·拉奇声称"从没有人对'每个孩子一台笔记本电脑'项目进行过复盘"，只因他不知道有本名为《魅力机器》的专著早已详尽论述。

最荒诞的案例当属Juicero公司——他们售价400美元的榨汁机，实际功能与徒手挤压专用果汁包无异。

发现新事物确实令人兴奋（不信可以问问那些听我狂热赞美欧洲高脂黄油的人），但你不能假定自己新发现的事物对全世界都是新知。这些现象背后普遍存在着某种认知惰性，这种特质在某些科技爱好者中尤为盛行，尤其是那些痴迷创业和企业家精神的人。或许他们长期困在信息茧房中，未能意识到自己的"发现"早已是常识；又或许他们自认绝顶聪明，觉得连自己都不知道的事就不可能有人知道。

挑战未解难题确实需要傲气——你必须相信自己能解决它。但在其他情境下，这种傲慢会带来恶果。它会让人做出怪异举动，比如宣称弗洛伊德发明了内省法，还得意洋洋地表示自己根本不需要这种能力。

曾几何时，软硬件开发者都明白服务用户才是本职

当我自觉发现重要现象时，第一反应总是去图书馆、维基百科或请教专业人士，查证前人是否已有研究。例如脑震荡后，我想寻找关于康复体验的纪实记录——干瘪的医学描述对我毫无帮助。当发现资料匮乏时，我便自己提笔记录。多年后的今天，仍会有经历脑震荡的人循着我当年的搜索路径发来邮件。但这样的行为需要你默认他人是智慧的，承认智者始终存在，并理解人类经验中真正的新鲜事物凤毛麟角。这需要智识上的谦逊，以及体察他人经验的意愿。

这种傲慢不仅让人变成乏味的讨厌鬼，更已渗透到硅谷的职业生态中。就在不久以前，软硬件开发者都清楚他们的职责是服务用户：发现需求，满足需求。但金融危机后的某个时间点，准企业家们开始认为自己的使命是发明未来，而消费者的任务就是接受这个被发明的未来。我猜他们是在模仿自己理解的史蒂夫·乔布斯——比如取消MacBook Air光驱的决策。

但众所周知，乔布斯在1980年代发明未来的尝试以失败告终，甚至被逐出苹果。我们都见证了他回归后的转变。iMac、iPod、iPhone的诞生都源于明确的需求：iMac因易用性取胜；iPod比CD播放器加碟片更便携（还能播放非法下载的MP3）；iPhone的应用商店将其功能性拓展到其他移动设备难以企及的高度。

不知何时起，我们的硅谷主宰者忘记了：要让人们接纳他们对未来的构想，首先得让人们真正渴望它。

从解决问题到追逐风口

部分成功源于运气——在正确时机推出合适产品。但每件产品都为消费者提供了独特价值主张。当然，早期使用者因炫酷而追捧，但普通大众不在乎这个。只有当产品能切实改善生活时，他们才会购买。

如今企业不再专注于解决问题的技术，而是接连追逐NFT、元宇宙、大语言模型等风口。这些技术的共同点是：并非为解决实际市场问题而生，而是为风投和公司敛财而造。NFT如同加密货币，让风投能以极短锁定期快速套现；元宇宙承诺通过将社交活动全面线上化来为Facebook等公司创收（同时实现监控和货币化），还要求用户购买需要定期升级的硬件。

硅谷主宰者们似乎忘记了：要让人们接纳未来愿景，首先得让人真心想要。这就是为什么NFT、元宇宙、Oculus和Vision Pro始终未能真正建立用户基础。诚然，AI更具实用性（比如整理海量数据），大语言模型也获得了广泛用户采纳（至少在免费阶段）。但真正能支撑大语言模型巨额烧钱过程的客户只有一个：美国政府。

然而政府合同只能成就少数赢家。于是我们目睹着AI公司的集体狂舞，其中OpenAI最为滑稽——它竟试图将自己定位为消费品。

被夸大的AI威胁与真实的民生需求

那些宣称AI将主宰未来、取代工作岗位的人，恰恰是最希望预言成真的人。看看萨姆·奥特曼向世界宣称需要ChatGPT教他育儿——你我都真实存在。我们的父母没有大语言模型甚至AI，但我们依然安然长大，因为美国儿童死亡率数十年来远低于人类历史大部分时期。保障我们童年存活的技术是卫生设施、疫苗和抗生素。我敢打赌，一剂强制麻疹疫苗对美国儿童生存的贡献，将远超OpenAI至今耗费数十亿美元取得的所有成果。

说到底，我猜奥特曼实际做的是雇了位保姆。

再看埃隆·马斯克描绘的人形机器人仆从未来。我已有机器人仆从——洗碗机、洗衣机和烘干机。它们虽不灵活，却为我节省了大量劳力。我那台90年代的冰箱和稍晚购买的微波炉，都在没有AI介入的情况下，出色完成了食物储存和烹饪的使命。在这些机器奠定的基础之上，AI似乎难有突破性提升，更何况我的"低科技"设备二十多年都无需更新。省钱对我同样重要。

宣称AI将主宰未来夺走工作的人，往往正是最期待这一切成真的人。这种期待可能源于对自我重要性的迷恋，或成为亿万富翁的渴望，抑或纯粹源于对他人的不理解——最后这点常被低估。若真要给我配备机器人仆从，我的标准很明确：性价比至少要像洗碗机那样实在。

效率至上的迷思

普通人不会像无头苍蝇般试图自动化生活的每个角落。事实上，生活中很多场景根本不需要效率最大化。常有人说AI能让度假规划更轻松，但至少对我来说，规划旅程本身就是乐趣——它让我浏览目的地信息、构思有趣活动、想象实践场景。如果朋友曾到访该地，这便成了获取建议的交流契机。整个过程会随着假期临近不断累积期待感。若真想省事，现有邮轮和主题公园就能满足需求。

大语言模型充其量是企业级技术，或许能让某些数据整理或编程工作更高效。这与大多数人的生活几乎无关。捣鼓代码是很多科技爱好者的兴趣，而我们普通人根本不在乎。让编程更简便也改变不了我不想写代码的事实——我有其他爱好！

对普通人而言，大语言模型的实际用途主要是学业作弊。对成年人则是信息查询——它正在取代谷歌搜索。谷歌搜索质量长期退化，为大语言模型敞开了替代之门。但这种状态能持续多久尚未可知——大语言模型终将收费，而其频繁出错（有时抄袭）的结果正在摧毁它们赖以生成信息的网站。点击查看高质量内容确实效率较低，但若不如此，谁来持续产出优质信息？这个问题至今无解。

当效率破坏系统稳定性

有时低效率恰恰是系统的支撑结构。以股市为例：仅在特定时段、特定日期开放，这意味着恐慌时期存在人为缓冲区间，让人们有时间冷静。这种机制很有效，是个股在狂热时期暂停交易的原因之一。反观加密货币市场全年无休：恐慌无法暂停。加密货币暴跌之所以如此剧烈迅速，正是因为没有熔断机制，没有交易间歇让交易者重整旗鼓。事实上，加密货币恐慌常因市场永不闭市而加剧——很多人 literally 无法入眠。

消费级AI还有其他怪异之处。以AI音乐应用为例，其预设前提是：世界上存在想创作音乐却不愿花时间学乐器的人。这种人恐怕少之又少！音乐家并非垄断创造力——他们只是享受创作过程的人。而我们其他人享受聆听，这本身就是目的。

AI音乐最实用的场景，是帮助那些想挤进Spotify歌单、赚取流量变现的人——也就是骗子。同样，自助出版市场充斥着AI垃圾，并非因为人们渴望表达自我，而是因为在亚马逊上诱骗他人购买垃圾内容太容易。受骗的不仅是普通读者，哈切特出版社被伪作《害羞女孩》欺骗的丑闻就是明证。对大多数人而言，这些AI工具反而增加了接触他人艺术的难度；而对艺术家来说，谋生变得更艰难了。

脱离现实的创新者

这些试图打造征服世界产品的天才们为何从未思考过这些？答案很简单：他们与普通人共同点太少，既不了解普通人的生活，也不理解普通人的价值观。他们沉溺在自我构建的闭环里——收听风投播客，为能否跟上AI代理的步伐而焦虑，与现实越来越脱节。

我怀疑这正是NFT、元宇宙和笨重VR/AR头显诞生的根源。这些东西只吸引风投圈和科技创业圈里过度代表的少数群体。硅谷炒作机器为它们超负荷运转，而结果众所周知：你上次听说无聊猿或加密猫是什么时候？这些 novelty 是否如承诺般为艺术家、音乐人和其他创作者带来持续收入？你最近见过有人戴苹果头显吗？扎克伯格的元宇宙乌托邦可曾站稳脚跟？

我们确实都拿马克·安德森缺乏自省开过玩笑——但这正是硅谷不断向消费者强推他们明确拒绝的"未来"的根本原因。一个无法自我反思的风投永远不会注意到，他对消费主义的每次押注都以相同方式失败。他既没有、也不可能意识到，自己的经历根本无法代表普通人的需求。

"他们变得平和，然后往往辞去工作"

既然提到安德森，我想指出那段采访中未受关注的部分。就在"致命的自省"言论之后，他谈及致幻剂，说曾与播客主安德鲁·休伯曼讨论："我描述硅谷常见的现象：有些人压力过大感到焦虑，有人介绍他们尝试致幻剂。经历之后他们仿佛脱胎换骨，变得异常平和，但接着往往辞去工作。"

据安德森转述，休伯曼认为这些人可能更快乐、更自在。安德森回应："是啊，但他们的公司垮了。"

傲慢的企业家（以及需要他们的风投）只是人群中的少数。我们大多数人宁愿选择幸福，而非创办征服世界的公司——那意味着牺牲大部分清醒时间、兴趣爱好，很可能还有人际关系。塑造未来的真正方式或许不是向消费者发号施令，而是简单给予人们真正想要的东西。

英文来源：

One of the most mortifying things about knowing a lot of techies is listening to them tell me excitedly about some very important discovery that they believe they have made. Recently, I ran into an acquaintance of mine, who began talking my ear off about an amazing discovery he’d made with LLMs. Knowledge, it turns out, is structured into language! You could put one word into ChatGPT and it might understand what you wanted, or make up a word and see if it understood what you meant! These amazing new tools have revealed that the English corpus contains so much about its speakers!
Silicon Valley has forgotten what normal people want
What NFTs, AI and the metaverse tell us about “thought leadership”
Silicon Valley has forgotten what normal people want
What NFTs, AI and the metaverse tell us about “thought leadership”
He concluded that LLMs are a discovery on par with writing.
Regular humans hit on this idea about a century ago; my most generous interpretation of what he was telling me was that he’d hit on a kind of naive, confused version of Structuralism; Saussure via a game of telephone. (There has been recent work on a similar point, which argues that one needs to understand LLMs via literary theory, but it starts with Saussure.) I tried to get out of the conversation as quickly as I could, not least because he seemed frustrated that I didn’t see things exactly as he did — a new behavior and likely a symptom of LLM overuse.
There is a certain amount of hubris required to throw oneself at an unsolved problem. But elsewhere, that hubris is a liability.
Not every discovery that’s new to you is actually new. For instance, there’s Elon Musk marvelling at the complexity of hands; I could point to a variety of disciplines for which this is 101-level stuff: artists, who have to figure out how to draw them; surgeons, who have to figure out how to operate on them; musicians and magicians, who rely on extremely fine motor skill to produce their work; neuroscientists and psychologists, who doubtless encountered the cortical homunculus early in their careers. Or Palmer Luckey claiming that “no one has done a postmortem” on the One Laptop Per Child computing project — because he didn’t know there’s a whole book about it called The Charisma Machine.
At its most absurd nadir, one is reminded of Juicero, a company that sold a $400 juicer that did the same work as squeezing its proprietary juice packs with one’s bare hands.
Look, discovering something that’s new to you is exciting — ask anyone who listened to me yell about the joys of European (higher-fat) butter — but you can’t take for granted that something that’s new to you is new to everyone. These things have in common a certain incuriosity that I have found endemic among a certain kind of tech enthusiast, particularly the ones who are most interested in startups and entrepreneurship. Perhaps they have been so siloed that they did not realize their “discovery” was well -known elsewhere, or perhaps their self-conception is that they are the smartest, and if they don’t know something, no one knows it.
There is a certain amount of hubris required to throw oneself at an unsolved problem — you have to believe you can solve it. But elsewhere, that hubris is a liability. It leads you to do weird things, like announce that Freud invented introspection and that it is a bonus that you simply do not engage in it.
Within recent memory, people who made software and hardware understood their job was to serve their customer
When I think I have observed something important, my first impulse is to go to a library, or Wikipedia, or a person who I think may be knowledgeable, and see what else has been observed. For instance, when I had a concussion, I wanted to see if anyone else had written about what it was like to recover — the dry medical descriptions did very little for me. When I couldn’t easily find an account, I wrote my own. I still receive emails about it, years later, from people who are doing the same search I did, following their own concussions. But doing something like this requires you to take for granted that other people are smart, that smart people have always existed, and that very little in the human experience is new. That requires, you know, intellectual humility — and a willingness to think about other people’s experiences.
While this particular kind of hubris makes people crashing bores, it’s not just an annoying personal trait. It seems to have seeped into the professional side of Silicon Valley as well.
Within recent memory, people who made software and hardware understood their job was to serve their customer. It was to identify a need, and then fill it. But at some point following the financial crisis, would-be entrepreneurs got it into their heads that their job was to invent the future, and consumers’ job was to go along with that invented future. My guess is that they’re aping what they thought Steve Jobs was doing when he, for instance, got rid of the optical drives on the MacBook Air.
But Steve Jobs, famously, failed at inventing the future in the 1980s and got booted from Apple. We all know how things changed when he came back. But the iMac, the iPod, the iPhone were built with a need in mind. The iMac won because it was easy to use. The iPod was easier to take with you than a CD player and a stack of CDs. (It also was a way to play the MP3s you might have illegally downloaded.) The iPhone had the App Store, which expanded its utility well beyond any other mobile device.
At some point, our Silicon Valley overlords forgot that in order for their vision of the future to be adopted, people had to want it.
Some of this was luck — introducing the right product at the right time. But each product offered consumers a distinct value proposition. Sure, early adopters jumped on each of these things because they were cool, but the uncool masses don’t care about that. They’ll buy something if it improves their life in a distinct way.
In the place of problem-solving technology, companies have jumped on successive bandwagons like NFTs, the metaverse, and large language models. What these all have in common is that they are not built to really solve a market problem. They are built to make VCs and companies rich. NFTs, like crypto, let VCs quickly unload investments with abbreviated lockup periods. The metaverse promised to enrich companies like Facebook by having people move all their socializing online, where it could be surveilled and monetized. In addition, Facebook’s metaverse required the purchase of hardware, which would then need regular upgrades.
At some point, our Silicon Valley overlords forgot that in order for their vision of the future to be adopted, people had to want it. That’s why NFTs, the metaverse, and the Oculus and Vision Pro never really found their customer base. AI is, admittedly, more useful — it’s good for organizing large swaths of data, for instance. LLMs have had widespread consumer adoption, at least as long as they remain free. But there is only really one customer for LLMs that can justify the massive cash incineration process that was required to build them: the US government.
There can only be a few winners on government contracts, though. So we are now treated to the spectacle of watching AI companies scramble. OpenAI is perhaps the funniest, because it is attempting to position itself as a consumer product.
The people who tell us that AI will dominate our future and take our jobs are the people who are hoping that will be true.
Consider Sam Altman telling the world that he needed ChatGPT to tell him how to raise a baby. You exist. I exist. Our parents did not have LLMs, or even AI, and yet somehow we survived our childhoods, as did almost everyone else we knew growing up because childhood death rates in the US have been extraordinarily low — compared to most of the rest of human history — for decades. The technologies that allowed us all to survive our childhoods were sanitation, vaccines, and antibiotics. I would put money down that a mandatory measles vaccine will do more for the survival of American children than anything OpenAI has accomplished with all of its billions of dollars to date.
In any event, I presume what Altman actually did was hire a nanny.
Or consider Elon Musk telling us about our future humanoid robot servants. I have a robot servant. Several, actually: a dishwasher, a washer for my clothing, and a dryer. They aren’t very mobile, and yet they have saved me tremendous labor. My fridge is from the ’90s, and my microwave isn’t much younger, and both of those things have been remarkable in what they have done for me: made food storage and cooking easy, without AI involvement. It doesn’t seem like there’s much AI can do to improve things over the baseline that these machines have already established, especially since my “dumb” technology hasn’t required an update in more than 20 years. Saving money is valuable to me, too.
The people who tell us that AI will dominate our future and take our jobs are the people who are hoping that will be true. They may be hoping this because it makes them feel important, or because they want to be billionaires, or because they simply do not understand other people. I think that final point is underestimated. If you are going to provide me with a robot servant, I have a very clear bar: It’s gotta be at least as much bang for my buck as my dishwasher.
There are places in our lives where efficiency isn’t desirable
Normal people aren’t running around like chickens with their heads cut off, trying to automate every single part of their lives. Indeed, there are places in our lives where efficiency isn’t desirable. Vacation planning is sometimes suggested as a place AI can make our lives easier. For me, at least, planning the vacation is a pleasure in and of itself; it allows me to browse information about a place, consider what might be fun, and imagine myself doing it. If I have friends who have been to that place before, it gives me an excuse to talk to them, getting their recommendations. The entire process sharpens the anticipation I feel as the date for the vacation approaches. But if I wish to outsource that, I can do so already — that’s what cruise ships and theme parks are for.
LLMs are, at best, an enterprise technology that may make certain kinds of data organization easier, or coding faster. This has almost nothing to do with most people’s lives. Dinking around with code is a hobby many tech people enjoy and one the rest of us simply don’t care about. Making it easier to write code doesn’t change that I don’t want to write code. I have other hobbies!
The actual use for LLMs in most normal people’s lives is cheating on schoolwork. For adults, it’s looking up information — LLMs are in the process of supplanting Google Search. Google had been degrading its search project for some time, and the results just kept getting worse. This opened the door for an alternative, and the LLMs stepped through. How long that will last, I don’t know — the LLMs themselves will require money at some point and their frequently inaccurate (and sometimes plagiarized) results are killing the websites they rely on to generate information. Sure, it’s more inefficient to click through to a high-quality product, but how else do you plan to continue to have people generate high-quality information? No one has solved this problem.
Musicians aren’t bogarting creativity — they are people who enjoy making music
Sometimes inefficiency is load-bearing. Take, for instance, the stock market. It is only open during certain hours, and only during certain days of the week. That means that during a panic, there is an artificial boundary that gives people time to calm down. This is effective; it’s one of the reasons that individual stocks sometimes undergo a trading halt during periods of hysteria. Now consider crypto, which is open for business 24/7/365: There is no way to pause a panic. One of the reasons the crashes in crypto are so huge and so fast is because there is no breaker to trip and no break in trading to allow traders to regroup. In fact, crypto panics are arguably exacerbated by the fact that many people literally cannot sleep because the market does not close.
There are other ways in which consumer AI is weird. Take the AI music apps, which are predicated on the idea that there are people in the world who want to make music but simply haven’t taken the time to learn how to play an instrument. There are likely very few of those people! Musicians aren’t bogarting creativity — they are people who enjoy making music. The rest of us just enjoy listening, which is an end in itself.
The place where AI music is most useful is for people who want to figure out how to get themselves onto Spotify playlists, accrue streams, and make money — that is to say, scammers. Similarly, the self-publishing market is rampant with AI slop, not because people are desperately trying to express themselves, but because it is easy to trick other people into buying slop on Amazon. And it’s not just the casual readers who get swindled, as demonstrated by the scandal around Shy Girl, the now-withdrawn novel that fooled Hachette. The end result for most people is that these AI tools make it harder for them to access art made by other people. And the end result for artists, of course, is that it’s harder to make a living.
Did Mark Zuckerberg’s Meta utopia ever develop legs?
How is it that all these wunderkinds trying to build the next product to take over the world haven’t thought about this? I think the answer is simple. They do not have much in common with normal people, and haven’t thought much about what normal people’s lives are like, or what normal people value. What they have been doing instead is getting high on their own supply — listening to VC podcasts, freaking themselves out about whether they’ll be able to keep up with AI agents, and otherwise getting increasingly more detached from reality.
I suspect this is how we wound up with NFTs, the metaverse, and the clunky VR/AR headsets. These are things that appeal to a very narrow set of people who are overrepresented in the VC and wannabe-tech-entrepreneur spaces. The Silicon Valley hype cycle worked overtime for those things, and I think we all know how this turned out. When was the last time you heard about a Bored Ape, or a Crypto Kitty, or any of the other novelties that briefly swept the nation? Did those novelties translate into a real, durable income stream for artists, musicians, and other creators, as we were promised? When was the last time you saw someone wearing Apple’s headset? Did Mark Zuckerberg’s Meta utopia ever develop legs?
Look, we all had a bit of fun at Marc Andreessen’s expense about his lack of introspection — but this is precisely the reason Silicon Valley keeps trying to force futures on consumers that they emphatically don’t want. A VC who is incapable of self-reflection will never notice that his bets on the future of consumerism are failing in exactly the same way every time. That VC hasn’t noticed, and indeed can’t notice, that his experience isn’t representative of what the ordinary person wants or needs.
“They come out much more at peace, but then they tend to quit their companies.”
Actually, while I’m picking on Andreessen, I want to point to a bit of that interview that didn’t go viral. It occurs right after the fatal introspection quote, but I think it gets to the real rot at the heart of Silicon Valley’s current culture. In it, Andreessen mentions psychedelics, saying he was discussing them with podcaster Andrew Huberman. “I was describing this phenomenon we see in Silicon Valley, where there are these guys who get under pressure, and they feel anxious or whatever, and someone tells them about psychedelics, and they try it,” Andreessen says. “And they kind of come out the other end as a changed person. They come out much more at peace, but then they tend to quit their companies.”
In Andreessen’s telling, Huberman suggests that these people may be happier, and better off. And Andreessen says, “Yeah, but their company is failing.”
The hubristic entrepreneurs (and the VCs who need them) are a relatively small slice of the population. The majority of us would much rather be happy than try to found a company that takes over the world — sacrificing the majority of our waking hours, our hobbies, and likely many of our relationships in the process. It may be the case that the real way to shape the future isn’t to dictate it to consumers. It is simpler just to give people things they actually want.