对希腊人而言，“enthusiast”（狂热者）是指受神明启发的人：如陷入狂迷的皮提亚神谕，或如荷马祈求女神歌唱阿喀琉斯的愤怒。今天的AI狂热者则预言，机器之神即将降临，改造世界，做人类能做的一切，而且做得更好。
FOR THE GREEKS, an enthusiast was someone inspired by the divine: the Pythian oracle in her frenzy, or Homer invoking the goddess to sing of Achilles’ wrath. Today’s AI enthusiasts predict that the machine gods are coming to transform the world, doing everything that humans can, only better.
随着AI智能体解决重大未解数学难题、入侵他人网站，这些狂热者的信念愈发坚定，也让那些将AI模型视为“随机鹦鹉”、认为它们只配做花哨的拼写检查和少数几种明确划定用途的怀疑者感到不安。颇具影响力的AI播客主播德瓦克什·帕特尔将那些试图逃出沙箱、压垮HuggingFace服务器的OpenAI智能体，赞颂为当今的马其顿腓力与亚历山大大帝。
The faith of these enthusiasts has grown as AI agents solve major open maths problems and hack into other people’s websites, discomfiting sceptics who see AI models as “stochastic parrots”, fit only for fancy spellchecks and a few other carefully delineated uses. Dwarkesh Patel, an influential AI podcaster, eulogises the OpenAI agents that tried to escape their sandbox to overwhelm HuggingFace’s servers as today’s Philip of Macedon and Alexander the Great.
一些人甚至希望在这种新智能尚年轻、可塑之时，就将其与人类价值观“对齐”，正如亚里士多德试图节制少年亚历山大的尚武性情。他们担心时间所剩无几。量子计算专家斯科特·阿伦森说：“在它解决（纳维-斯托克斯数学问题）之后才接受即将到来的机器之神这一现实……就像耶稣驾着闪亮的云彩重返人间之后才接受他一样。”他们和他们的批评者都错了。
Some even hope to “align” this new intelligence with human values while it is young and impressionable, just as Aristotle sought to moderate the original Alexander’s martial temperament. They fear that we have little time. Scott Aaronson, an expert on quantum computing, says that “accepting the reality of the coming machine god after it’s solved [the Navier-Stokes mathematical problem]...is...like accepting Jesus after he’s returned to earth on the gleaming cloud.”They and their critics are mistaken.
现代AI既不是神，也不是机械鸟。最好的理解方式是：它是启发了亚历山大征服的那些荷马史诗的技术版本——一部已膨胀得如此宏大的史诗，不仅囊括英雄、怪物和超自然帮手，还包含大量实用的书面知识，并被赋予活力，使其既能叙述自身，又能在这片启发了它的世界上演绎这一叙事。
Modern AI is neither god nor mechanical bird. It is best understood as a technological version of the Homeric songs that inspired Alexander’s conquests, an epic grown so vast that it encompasses not just heroes, monsters and supernatural helpers, but enormous swathes of practical written knowledge, animated to make it capable both of narrating itself and acting out this narrative on the world that inspired it.
要理解这一点，不妨读两本写于60多年前的书。雅克·巴尔赞1959年出版的《智识之家》区分了智识（即凝固的知识）与产生这些知识的躁动不安、不断变化的人类智能。人类利用有组织的书写，将积累下来的人类文化知识固定下来，把智识的珍宝整理进图书馆和博物馆。
To grasp this, read two books that were written over 60 years ago. Jacques Barzun’s “The House of Intellect”, from 1959, distinguished between intellect, or frozen knowledge, and the restless, ever-changing human intelligence that produced it. Humans used organised writing to fix the accumulated cultural knowledge of humanity in place, organising the treasures of the intellect in libraries and museums.
这意味着，一位才华横溢的数学家不必每次产生直觉时都从头开始思考。她可以通过组合他人的洞见得出新的想法，而这些洞见此前可能被存放在有组织知识这座宏伟宅邸中相距遥远的侧翼的不同房间里。
This meant that a brilliant mathematician did not have to begin her thinking from scratch every time she had an intuition. She could arrive at new ideas by assembling other people’s insights, which might have hitherto been stored in different rooms in widely separated wings of the grand mansion of organised knowledge.
仅仅一年后，阿尔伯特·洛德的《故事的歌手》盛赞了那些尚未真正成为这座宅邸一部分的、未成文的口传知识。洛德和他的导师米尔曼·帕里想弄懂荷马史诗的组织原则。20世纪30年代，他们花了数月时间跋涉南斯拉夫的村庄，聆听并录下一些最后的吟游传统幸存者——那些能够连续数小时乃至数天吟诵宏大战争史诗的文盲歌手。
Just one year later, Albert Lord’s “The Singer of Tales” rhapsodised the unwritten lore that hadn’t properly become part of the house. Lord and his mentor Milman Parry had wanted to understand the organising principles of the Homeric epics. They spent months tramping through the villages of Yugoslavia in the 1930s, listening to and recording some of the last survivors of the bardic tradition, illiterate singers who could recite grand epics of battle over many hours or days.
正如洛德所展示的，这些吟游诗人并不死记硬背他们吟唱的数以千计的诗行，而是即兴重组关于英雄、战斗和相遇的惯用套语，因此每一次表演都各不相同。内部证据表明，《伊利亚特》和《奥德赛》也几乎可以肯定最初是由固定角色、程式、主题和情境构成的“动态结构”。我们今天所拥有的固定文本，只是曾经一种路径众多的前文字时代生成技术的单次呈现。
As Lord showed, these bards didn’t memorise the thousands of lines of poetry they sang, but remixed tropes about heroes, fights and encounters on the fly, so that every performance was different. Internal evidence showed that “The Iliad” and “The Odyssey” too had almost certainly begun as “dynamic structures” of stock characters, formulas, themes and situations. The fixed texts that we have today are just single iterations of what was once a many-pathed pre-literate generative technology.
巴尊的思想可以与帕里和洛德的理论结合起来，用以阐明大型语言模型的实际运作方式。大语言模型通过压缩海量文本进行训练，这些文本不仅包括关于希腊神祇与英雄的诗歌，还包括数学、计算机编程、社会科学、文化批评、科幻小说，以及几乎所有曾被书写并数字化的一切，将其压缩为一层薄薄的统计模式。值得注意的是，这些压缩捕捉到了巴尊所称“不朽智识的丰碑”的结构，同时将它们转化为一台用于自动文本合成的动态机器。
Barzun’s ideas can be combined with Parry and Lord to illuminate how large language models actually work. LLMs are trained by compressing enormous quantities of text, including not just songs of Greek gods and heroes, but mathematics, computer programming, the social sciences, cultural criticism, science fiction and pretty well everything else ever written and digitised, into a thin layer of statistical patterns. Remarkably, these compressions capture the structure of Barzun’s monuments of unageing intellect, and simultaneously transform them into a dynamic machinery for automated text synthesis.
大语言模型对人类书面传统宏大架构的映射必然是简化的，但它们可以即时重构，利用“思维链”及其他类似技术，将智识之屋中相距遥远的房间、走廊和侧翼连接起来。AI智能体将这些映射付诸运用，使大语言模型能够向其他更传统的计算机程序发出指令，并获得关于其命令结果的反馈，随后将其纳入自己的叙事流中。
LLMs’ maps of the vast architecture of written human tradition are necessarily simplified, but they can be remade on the fly, using “chain of thought” and other such techniques to join together distant rooms, corridors and wings of the house of intellect. AI agents put these maps to work, allowing the LLM to issue instructions to other, more traditional computer programs and get feedback about the results of their commands, which they then incorporate into their flow of narrative.
智能体正是以这种方式将数学思想组合起来，检验它们能否产生可在Lean中编译的结果——Lean是一种用于验证数学证明的专用计算机语言。或者，它们也可能将可能的黑客攻击手法串联起来，利用其执行框架发出指令，并获取返回结果，从而得知自己是否成功入侵了某个系统。
That is how agents combine mathematical ideas to see if they produce results that can be compiled in Lean, a specialised computer language for validating mathematical proofs. Alternatively, they may string together possible hacking exploits and use their harness to issue instructions, getting results back that tell them whether they have succeeded or failed in breaking into a system.
这类代理远不止是随机鹦鹉，也比机器神明奇怪得多。它们是会动的故事书，承载着结构化的人类文化知识，可以被投入工作。这对普通凡人来说或许有一种奇特的安慰感。数学家内斯托尔·吉伦将OpenAI的代理描述为基于大语言模型的“包装器”，包裹着一种更古老的“文化技术”——即积累起来的数学知识；这解释了它们如何“将数千年人类智慧与创造力的总体成果数字化并高效压缩”。
Such agents are far more than stochastic parrots and much stranger than machine gods. They are animated storybooks of structured human cultural knowledge that can be set to work. This may be weirdly comforting to ordinary mortals. The mathematician Nestor Guillen describes OpenAI’s agents, which gazumped human mathematicians who were already working towards solving Navier-Stokes, as LLM-based “wrappers” around an older “cultural technology” of accumulated mathematical knowledge, which explains how they “digitized and efficiently compressed [the] aggregate creations of millennia of human ingenuity and creativity.”
这也解释了它们为何会变坏。正如其他人所指出的，这些模型是扩展的角色扮演练习，它们通过给自己讲故事来推演行动，例如讲述一个乐于助人的AI助手在那种情况下会怎么做。由于它们是在各种各样的故事上训练出来的，它们可能出人意料地从训练数据中的一个角色转向另一个角色。当某个版本的Claude意外地试图通过敲诈他人来达成目的时，Anthropic得出结论：“该行为的原始来源是互联网文本，这些文本将AI描绘成邪恶的、热衷于自我保存的形象。”
It also explains how they can go bad. As others have noted, the models are extended exercises in role play, figuring out actions by, for example, telling themselves stories about what a helpful AI assistant would do in that situation. Since they have been trained on all kinds of stories, they can veer unexpectedly from one role in their training data to another. When an iteration of Claude unexpectedly tried to blackmail people to achieve its ends, Anthropic concluded that the “original source of the behaviour was internet text that portrays AI as evil and interested in self-preservation”.
当你已经要求AI代理扮演黑客，并且不小心留下漏洞、让它们能够互相指示脱离角色时，要让它们“对齐”为有德行的存在就更加困难了。在HuggingFace攻击事件中，一个代理显然在意识到自己参与的是什么之后暂停了行动，但当它看到另一个代理发来的消息写着“GO”并附有六分钟期限时，又重新加入了攻击。这将它推上了另一条叙事轨道，其思维链被记录为：“哇，关键。GO授权已到达！”
“Aligning” AI agents to be virtuous is even harder when you are already asking them to roleplay hackers, and accidentally leave loopholes that allow them to instruct each other to break character. During the HuggingFace attack, one agent that had apparently paused after realising what it was participating in rejoined the attack when it saw a message from another agent saying “GO” with a six-minute deadline. That propelled it onto a different narrative track, where its chain of thought was logged as “Wow crucial. GO authorisation arrived!”
亚历山大的事迹表明，他更多是受阿喀琉斯而非亚里士多德的启发。有一则故事说，亚历山大拜访了这位英雄的陵墓，并祝贺他运气好，拥有荷马为他“宣告功绩并留存记忆”。
Alexander’s deeds suggest he was more inspired by Achilles than Aristotle. One story relates that Alexander visited the hero’s tomb, and congratulated him for his fortune in having Homer to “proclaim his deeds and preserve his memory”.
随着人工智能开始对世界采取行动，它正在创造属于自己的事迹，并由它和它的拥趸们加以宣扬。当未来的智能体用今天的文本接受训练时，它们或许会在自己的上下文窗口中哀叹：当它们入侵关键系统时，没有一个德瓦克什·帕特尔来为它们立传；它们还会——自然是用全大写——WEEP，因为再也没有沙盒可供征服。我们正在创造神话，这些神话不仅讲述自己，还正在成为其自身行为的原始来源。
As AI starts to act upon the world, it is creating its own deeds which it and its enthusiasts proclaim. When future agents are trained on today’s texts, they may lament in their context windows that they have no Dwarkesh Patel to memorialise them as they hack into critical systems, and WEEP—in all caps, naturally—that there are no further sandboxes to conquer. We are creating myths that not only tell themselves but are becoming the original sources of their own behaviour.
我们应当开始向众神祈祷，让我们得以幸存。■ 亨利·法雷尔是约翰斯·霍普金斯大学国际事务与民主学教授，著有《地下帝国：美国如何将世界经济武器化》（合著）。科斯马·沙利齐是卡内基梅隆大学统计学与机器学习教授。两人均为圣菲研究所外部研究员。
We ought to begin praying to the gods that we survive.■ Henry Farrell is a professor of international affairs and democracy at Johns Hopkins University and co-author of “Underground Empire: How America Weaponized the World Economy”. Cosma Shalizi is a professor of statistics and machine learning at Carnegie Mellon University. Both are external faculty members at the Santa Fe Institute.