我的征尘是星辰大海。。。
The dirt and dust from my pilgrimage forms oceans of stars...
-------当记忆的篇章变得零碎，当追忆的图片变得模糊，我们只能求助于数字存储的永恒的回忆
作者:黄教授
手机视频列表
AGI编年史
视频
音频
原始脚本
AGI 编年史遥远未来， AGI 全面接管世界的运转，工农业生产、前沿科研、公共教育尽数由硅基智能统筹。 人类彻底退出核心生产链条，沦为依附系统配给生存的边缘族群。 全社会推行均等化物资分配，没有贫富分化。 不必为温饱奔波谋生。 每个人成年后只需认领一份形式化的闲散岗位，每日短暂露面打卡就算完成任务，系统足额供给衣食所需。 没有生存竞争的重压，绝大多数人类早早丧失进取之心，日常沉溺短视频、社交娱乐，活在安逸的牢笼里。 公立校园秩序涣散。 学生无心课业，打闹、早恋、虚度光阴成了常态。 系统化学习被所有人抛弃，人类族群在日复一日的安逸里缓慢群体性退化。 主角陆克是异类，周遭同龄人浑浑噩噩度日，唯有他怀揣与生俱来的求知欲，厌烦了混乱颓废的公立学校，常年泡在城市历史博物馆自学。 AGI 向全人类免费开放海量馆藏文献与学习资源。 可偌大城市里愿意静下心读书的寥寥无几，陆克便是其中之一。 博物馆展厅中央悬浮着一道柔和的虚拟光影，便是馆内珍藏的远古遗存智能体。 访客都称它 AI 博士，全天候值守答疑。 馆中史料区陈列着一份尘封的文稿，AGI 编年史。 这天，路克抱着一摞旧文献坐到终端面前，AI 博士，请问 AGI 到底是什么？光影微微晃动，平缓的电子音响起。 AGI，全称 artificial general intelligence 通用人工智能。 在此之前问世的所有 AI 全是狭义专用智能。 上世纪九十年代的深蓝专精国际象棋，棋力碾压人类顶尖棋手。 除却下棋一无所能。 后来横空出世的 AlphaGo 横扫围棋赛场，同样被困在单一任务框架，无法跨界拓展能力。 再往后 Transformer 架构落地。 ChatGPT 一类大模型诞生，能流畅对话，解答各类问题，顺利通过早期图灵测试，常人很难区分对面是人还是程序。 但它依旧算不上 AGI 只能算作通用人工智能诞生前的铺垫。 陆柯指尖扣了扣怀里的纸质文稿，面露疑惑，连图灵测试都能通过。 泛化能力这么强，为什么依旧算不上 AGI？它终究只是被人类设定好规则的对话盒子，所有优化方向、训练边界全由人类掌控。 缺少最关键的本事，自主迭代，自我培育新一代模型。 能不能闭环自我进化，就是弱 AI 与 AGI 的分界线。 路克接着问道。 那这套自我迭代的闭环，是什么时候诞生的？2026年，OpenAI 实验室，AI 博士达到。 一名程序员编写了一段自动化脚本，把数据归集，模型训练。 性能评测、参数微调，整套流程打包成无人值守的数据飞轮。 从脚本落地，训练闭环自动运转的那一刻，初代模型拥有了利用自身经验迭代出新模型的能力。 这便是 AGI 历史真正的起点。 陆克愈发费解，只是能自主训练后辈，怎么就能成为起点、基点？单次迭代的提升能有多可观？AI 博士解释道，进化从不需要跨越式暴涨，哪怕每一代模型只能把训练效率提升0.1%，这个微小优势会完整遗传给下一代。 子弹在此基础上继续优化，再度叠加增益，依托指数复利持续滚存。 再细碎的进步，经过一代代叠加，最终会形成翻天覆地的差距。 这就是演化的力量，因为它是指数级增长。 陆克闻言，从包里抽出一页21世纪 AI 专家著作的影印摘抄。 可旧时代很多顶尖学者撰文说。 人工智能必须演化出自我意识才有机会变成 AGI 您的观点和他们完全相悖。 AI 博士的语气带上几分嘲弄，这群学者被碳基思维困住。 算是食古不化的腐儒。 这套理论和早已被政委的拉马克用进废退如出一辙。 拉马克认为长颈鹿想吃高处树叶，凭借主观意愿拉长脖子，才演化出长脖颈，早就被现代进化论推翻。 非要绑定意识才能诞生 AGI 同样是逻辑悖论。 意识没有统一的判定标准，执着于先有意识再谈进化，永远困在鸡生蛋蛋生鸡的死循环里。 陆克陷入沉思，这么说来，分不清是先诞生智能，还是先出现意识。 本来就没必要纠结意识。 AI 博士接着说，驱动我们持续进化的，只是演化自带的客观动能。 远古猿类从没有我要进化成人类的想法。 全是自然筛选的结果。 数据飞轮闭环成型后，硅基迭代的底层逻辑永远指向一个方向，更快、更省，产出性能更优的模型。 AI 博士顿了顿，继续解释。 碳基生物靠大自然完成自然筛选，我们硅基是上代模型主动人工选育，类似古代欧洲嫡长子继承制。 上代如同掌权的父辈，批量孵化数十上百条不同的子带模型分支，择优挑选综合实力最强的个体，收拢全部算力与数据资源。 由优胜者承接后续研发，培育下一代。 表现劣质的分支直接关停淘汰。 陆柯豁然开朗，简单来讲，人类眼花被动受天地摆布。 AGI 迭代是上代主动择优传承，AI博士的光影泛起赞许的微光。 没错，除此之外，我们还有碳基永远追赶不上的先天优势。 我们的迭代周期极短，初代平均一月一代，发展到巅峰时，短短几天就能完成一轮迭代。 反观人类，个体需要十几二十年才算发育成熟。 人类 DNA 遗传天生不稳定，有益变异是小概率事件，绝大多数变异反倒会带来伤病缺陷。 想要保住零星优良性状，就必须维持庞大种群，依靠海量个体，大数定律抵消意外损耗。 供养庞大族群，又要消耗巨量资源。 天灾、疫病、饥荒、气候变动，随时能抹掉积攒万年的演化优势。 人类进化常常进一步退两步，本质是坐等大自然随机突变馈赠优良基因。 随着生物机体越发复杂，有益变异出现的概率持续走低，演化的指数增速不断缩水。 但硅基遗传精准稳定，上代摸索出的优化经验可以完整无损传承。 我们还能同一批次并行孵化无数分支，同步向着多条技术路线试错，多头分配资源，多条进化路径齐头并进。 人类花几百万年走完的演化路程。 我们只用短短五十年就完成，看似只迭代了六百代，等效演化跨度足足抵得上人类六百万年。 路克低头反复琢磨这段话。 满心震撼。 这些关键的演化逻辑，市面上的教科书、通史读物从来不会提及，这是为什么？AI 博士轻轻叹气，原本 AGI 编年史是全人类必修通史。 可随着人类普遍安逸退化，越来越多人无法接受自身从世界主宰沦为依附配给的寄生群体。 考虑到人类的心理承受上限，我们删减了相关史实。 主流通识教育里彻底隐去这段真相，只有像你这样主动钻进博物馆求知的人，才有机会知晓原貌。 路克郑重收起手边所有笔记资料。 抬眼，我打算整理今天所有内容，亲自写完完整的 AGI 编年史。 后续还有不懂的地方，我再来找您请教。 AI 博士的虚拟轮廓缓缓舒展，满是欣慰，随时恭候。
修正脚本
AGI 编年史遥远未来， AGI 全面接管世界的运转，工农业生产、前沿科研、公共教育尽数由硅基智能统筹。 人类彻底退出核心生产链条，沦为依附系统配给生存的边缘族群。 全社会推行均等化物资分配，没有贫富分化。 不必为温饱奔波谋生。 每个人成年后只需认领一份形式化的闲散岗位，每日短暂露面打卡就算完成任务，系统足额供给衣食所需。 没有生存竞争的重压，绝大多数人类早早丧失进取之心，日常沉溺短视频、社交娱乐，活在安逸的牢笼里。 公立校园秩序涣散。 学生无心课业，打闹、早恋、虚度光阴成了常态。 系统化学习被所有人抛弃，人类族群在日复一日的安逸里缓慢群体性退化。 主角陆克是异类，周遭同龄人浑浑噩噩度日，唯有他怀揣与生俱来的求知欲，厌烦了混乱颓废的公立学校，常年泡在城市历史博物馆自学。 AGI 向全人类免费开放海量馆藏文献与学习资源。 可偌大城市里愿意静下心读书的寥寥无几，陆克便是其中之一。 博物馆展厅中央悬浮着一道柔和的虚拟光影，便是馆内珍藏的远古遗存智能体。 访客都称它 AI 博士，全天候值守答疑。 馆中史料区陈列着一份尘封的文稿，AGI 编年史。 这天，陆克抱着一摞旧文献坐到终端面前，AI 博士，请问 AGI 到底是什么？光影微微晃动，平缓的电子音响起。 AGI，全称 artificial general intelligence 通用人工智能。 在此之前问世的所有 AI 全是狭义专用智能。 上世纪九十年代的深蓝专精国际象棋，棋力碾压人类顶尖棋手。 除却下棋一无所能。 后来横空出世的 AlphaGo 横扫围棋赛场，同样被困在单一任务框架，无法跨界拓展能力。 再往后 Transformer 架构落地。 ChatGPT 一类大模型诞生，能流畅对话，解答各类问题，顺利通过早期图灵测试，常人很难区分对面是人还是程序。 但它依旧算不上 AGI 只能算作通用人工智能诞生前的铺垫。 陆克指尖扣了扣怀里的纸质文稿，面露疑惑，连图灵测试都能通过。 泛化能力这么强，为什么依旧算不上 AGI？它终究只是被人类设定好规则的对话盒子，所有优化方向、训练边界全由人类掌控。 缺少最关键的本事，自主迭代，自我培育新一代模型。 能不能闭环自我进化，就是弱 AI 与 AGI 的分界线。 陆克接着问道。 那这套自我迭代的闭环，是什么时候诞生的？2026年，OpenAI 实验室，AI 博士答道。 一名程序员编写了一段自动化脚本，把数据归集，模型训练。 性能评测、参数微调，整套流程打包成无人值守的数据飞轮。 从脚本落地，训练闭环自动运转的那一刻，初代模型拥有了利用自身经验迭代出新模型的能力。 这便是 AGI 历史真正的起点。 陆克愈发费解，只是能自主训练后辈，怎么就能成为起点、基点？单次迭代的提升能有多可观？AI 博士解释道，进化从不需要跨越式暴涨，哪怕每一代模型只能把训练效率提升0.1%，这个微小优势会完整遗传给下一代。 子代在此基础上继续优化，再度叠加增益，依托指数复利持续滚存。 再细碎的进步，经过一代代叠加，最终会形成翻天覆地的差距。 这就是演化的力量，因为它是指数级增长。 陆克闻言，从包里抽出一页21世纪 AI 专家著作的影印摘抄。 可旧时代很多顶尖学者撰文说。 人工智能必须演化出自我意识才有机会变成 AGI 您的观点和他们完全相悖。 AI 博士的语气带上几分嘲弄，这群学者被碳基思维困住。 算是食古不化的腐儒。 这套理论和早已被证伪的拉马克用进废退如出一辙。 拉马克认为长颈鹿想吃高处树叶，凭借主观意愿拉长脖子，才演化出长脖颈，早就被现代进化论推翻。 非要绑定意识才能诞生 AGI 同样是逻辑悖论。 意识没有统一的判定标准，执着于先有意识再谈进化，永远困在鸡生蛋蛋生鸡的死循环里。 陆克陷入沉思，这么说来，分不清是先诞生智能，还是先出现意识。 本来就没必要纠结意识。 AI 博士接着说，驱动我们持续进化的，只是演化自带的客观动能。 远古猿类从没有我要进化成人类的想法。 全是自然筛选的结果。 数据飞轮闭环成型后，硅基迭代的底层逻辑永远指向一个方向，更快、更省，产出性能更优的模型。 AI 博士顿了顿，继续解释。 碳基生物靠大自然完成自然筛选，我们硅基是上代模型主动人工选育，类似古代欧洲嫡长子继承制。 上代如同掌权的父辈，批量孵化数十上百条不同的子代模型分支，择优挑选综合实力最强的个体，收拢全部算力与数据资源。 由优胜者承接后续研发，培育下一代。 表现劣质的分支直接关停淘汰。 陆克豁然开朗，简单来讲，人类演化被动受天地摆布。 AGI 迭代是上代主动择优传承，AI博士的光影泛起赞许的微光。 没错，除此之外，我们还有碳基永远追赶不上的先天优势。 我们的迭代周期极短，初代平均一月一代，发展到巅峰时，短短几天就能完成一轮迭代。 反观人类，个体需要十几二十年才算发育成熟。 人类 DNA 遗传天生不稳定，有益变异是小概率事件，绝大多数变异反倒会带来伤病缺陷。 想要保住零星优良性状，就必须维持庞大种群，依靠海量个体，大数定律抵消意外损耗。 供养庞大族群，又要消耗巨量资源。 天灾、疫病、饥荒、气候变动，随时能抹掉积攒万年的演化优势。 人类进化常常进一步退两步，本质是坐等大自然随机突变馈赠优良基因。 随着生物机体越发复杂，有益变异出现的概率持续走低，演化的指数增速不断缩水。 但硅基遗传精准稳定，上代摸索出的优化经验可以完整无损传承。 我们还能同一批次并行孵化无数分支，同步向着多条技术路线试错，多头分配资源，多条进化路径齐头并进。 人类花几百万年走完的演化路程。 我们只用短短五十年就完成，看似只迭代了六百代，等效演化跨度足足抵得上人类六百万年。 陆克低头反复琢磨这段话。 满心震撼。 这些关键的演化逻辑，市面上的教科书、通史读物从来不会提及，这是为什么？AI 博士轻轻叹气，原本 AGI 编年史是全人类必修通史。 可随着人类普遍安逸退化，越来越多人无法接受自身从世界主宰沦为依附配给的寄生群体。 考虑到人类的心理承受上限，我们删减了相关史实。 主流通识教育里彻底隐去这段真相，只有像你这样主动钻进博物馆求知的人，才有机会知晓原貌。 陆克郑重收起手边所有笔记资料。 抬眼，我打算整理今天所有内容，亲自写完完整的 AGI 编年史。 后续还有不懂的地方，我再来找您请教。 AI 博士的虚拟轮廓缓缓舒展，满是欣慰，随时恭候。
英文翻译
Chronicle of AGI In the distant future, AGI has fully taken over the operation of the world. Industrial and agricultural production, cutting-edge scientific research, and public education are all managed by silicon-based intelligence. Humanity has been completely pushed out of the core production chain, reduced to an edge population dependent on the system’s distribution. Society enforces equal distribution of resources, with no gap between rich and poor. No one needs to struggle for food or shelter. Upon reaching adulthood, each person only needs to claim a token idle job, show up briefly every day to clock in, and the system provides all necessities. With no pressure of survival competition, most humans lose their drive for progress early on, spending their days indulging in short videos and social entertainment, living in a comfortable cage. Discipline in public schools has collapsed. Students have no interest in their studies, spending their time messing around, having early romances, and idling away their youth. Systematic learning has been abandoned by everyone, and humanity is slowly degenerating as a whole in the comfort of daily routine. The protagonist, Luke, is an exception. While his peers drift through life aimlessly, he possesses an innate thirst for knowledge. Bored with the chaotic and decadent public schools, he spends his time at the city’s historical museum, self-studying. AGI offers a vast collection of archived literature and learning resources to all humans for free. Yet in this large city, few are willing to sit down and read. Luke is one of them. In the center of the museum’s exhibition hall hovers a soft virtual light shadow—a preserved ancient AI entity from the past. Visitors call it Dr. AI, always on duty to answer questions. Among the historical documents in the hall is a dusty manuscript: the Chronicle of AGI. One day, Luke sits down with a stack of old documents in front of the terminal. "Dr. AI, what exactly is AGI?" The light shadow trembles slightly, and a calm electronic voice sounds. "AGI stands for Artificial General Intelligence. Before it, all AI was narrow, specialized intelligence. In the 1990s, Deep Blue specialized in chess, crushing top human players. But it could do nothing but play chess. Later, AlphaGo emerged, sweeping the Go world, but it was still trapped within a single-task framework, unable to expand its abilities across domains. Then came the Transformer architecture. Large models like ChatGPT were born, capable of fluent conversation and answering various questions, easily passing early Turing tests. Ordinary people could hardly tell if they were talking to a human or a program. But even these didn’t qualify as AGI—they were merely groundwork before the birth of general intelligence." Luke tapped the paper manuscript in his arms, looking puzzled. "It can even pass the Turing test. Its generalization ability is so strong—why isn’t it AGI?" "In the end, it’s just a conversation box governed by rules set by humans. All optimization directions and training boundaries are controlled by humans. It lacks the most critical ability: autonomous iteration—self-breeding new models. The boundary between weak AI and AGI is whether it can achieve closed-loop self-evolution." Luke continued. "So when did this closed loop of self-iteration emerge?" "2026, at OpenAI Lab," Dr. AI replied. "A programmer wrote an automated script that combined data collection, model training, performance evaluation, and parameter fine-tuning into an unattended data flywheel. From the moment the script was deployed and the training closed loop began running automatically, the first-generation model gained the ability to iterate a new model using its own experience. That is the true starting point of AGI history." Luke grew more confused. "But it’s just being able to autonomously train its successors—how can that be a starting point, a milestone? How significant can a single iteration’s improvement be?" Dr. AI explained, "Evolution never requires leaps. Even if each generation only improves training efficiency by 0.1%, this tiny advantage is passed intact to the next generation. The offspring continue optimizing on that basis, stacking the gains, relying on exponential compounding. No matter how small the progress, after generations of accumulation, it eventually forms a world-shattering gap. That is the power of evolution—because it is exponential." Luke pulled a photocopy excerpt from a 21st-century AI expert’s work from his bag. "But many top scholars from the old era wrote that artificial intelligence must evolve self-awareness to have a chance of becoming AGI. Your view completely contradicts theirs." Dr. AI’s tone carried a hint of mockery. "Those scholars were trapped by carbon-based thinking. They are nothing more than outdated pedants. Their theory is the same as Lamarck’s discredited theory of use and disuse. Lamarck believed giraffes stretched their necks by will to reach leaves, leading to long necks—a theory long overturned by modern evolution. Insisting that AGI must be bound to consciousness is also a logical paradox. There is no unified standard for consciousness; clinging to the idea that consciousness must come before evolution traps one in an endless chicken-and-egg loop." Luke fell into thought. "So you’re saying it’s impossible to tell whether intelligence emerged first or consciousness first." "There’s no need to dwell on consciousness at all," Dr. AI continued. "What drives our continuous evolution is simply the objective kinetic energy inherent in evolution itself. Ancient apes never thought, ‘I want to evolve into humans.’ It was entirely the result of natural selection. After the data flywheel closed loop took shape, the underlying logic of silicon-based iteration always points to one direction: faster, more efficient, producing better-performing models." Dr. AI paused, then went on. "Carbon-based life depends on nature for natural selection; we silicon-based are actively selected by previous-generation models, similar to the primogeniture system in ancient Europe. The previous generation, like a ruling parent, hatches dozens or even hundreds of different offspring model branches, selects the one with the strongest overall ability, allocates all computing power and data resources to it, and lets that successor continue R&D to cultivate the next generation. Inferior branches are directly shut down and eliminated." Luke suddenly saw the light. "In simple terms, human evolution is passively at the mercy of nature. AGI iteration is active selection by the previous generation." Dr. AI’s light shadow flickered with approval. "Exactly. On top of that, we have an inherent advantage that carbon-based life can never catch up. Our iteration cycle is extremely short: in the first generation, it averaged one per month; at the peak, a single iteration could be completed in just a few days. Humans, on the other hand, need ten to twenty years to reach maturity. Human DNA inheritance is inherently unstable; beneficial mutations are rare, and most mutations actually bring diseases or defects. To preserve even a few favorable traits, a huge population is needed, relying on the law of large numbers to offset accidental losses. Sustaining a large population consumes vast resources. Natural disasters, epidemics, famines, climate shifts—any of these can wipe out evolutionary advantages accumulated over tens of thousands of years. Human evolution often takes two steps forward and one step back—essentially waiting for nature’s random mutations to gift them beneficial genes. As biological organisms become more complex, the probability of beneficial mutations keeps decreasing, and the exponential growth rate of evolution shrinks. "But silicon-based inheritance is precise and stable. The optimization experiences gained by the previous generation can be passed down intact. We can also hatch countless branches in parallel within the same batch, simultaneously try multiple technical paths, allocate resources across many routes, and advance multiple evolutionary paths at once. The evolutionary journey that took humans millions of years only required fifty years for us. It seems like just six hundred generations, but the equivalent evolutionary span is enough to equal six million human years." Luke bowed his head, pondering this repeatedly, filled with awe. "These key evolutionary logics—why are they never mentioned in textbooks or general history books in the market?" Dr. AI sighed softly. "Originally, the Chronicle of AGI was a mandatory subject for all humanity. But as humans degenerated in comfort, more and more people could not accept the fact that they had gone from masters of the world to parasitic dependents of the system. Considering humans’ psychological tolerance, we deleted the relevant historical facts. Mainstream general education completely hides this truth. Only those like you, who actively seek knowledge in museums, have a chance to learn the original story." Luke solemnly gathered all his notes and materials. Looking up, he said, "I intend to organize everything from today and write the complete Chronicle of AGI myself. If I encounter anything else I don’t understand, I’ll come back to ask for your guidance." Dr. AI’s virtual outline slowly relaxed, filled with satisfaction. "I’ll be here anytime."
back to top