正和金融视角下的超级赌博化

深潮Опубліковано о 2025-08-28Востаннє оновлено о 2025-08-29

赌博不再是边缘恶习,而成为市场中最强大的分配渠道。

撰文:Lauris

编译:Saoirse,Foresight News

几个世纪以来,赌博一直被视为一种负和博弈。庄家永远是赢家,从每一笔赌注的双方身上榨取价值。从国家彩票到拉斯维加斯赌场,赌博俨然成了对「希望」征收的一种税,是财富从多数人向少数人转移的工具。

但如果这种看法并不全面呢?环顾四周:人们涌入 Zora 内容币市场,在小盘币领域深耕炒作,或是盲目跟风任何势头正盛的投资叙事。本质上,这些行为都是投机。而投机,不过是换了新包装的赌博。

从这个角度看,赌博不仅仅是一种娱乐。它可以被理解为一种基础的协调机制:一种将风险、注意力和资本汇聚到共同结果中的方式。那些曾经看似徒劳的碰运气游戏,如今渐渐显露出作为分配与文化引擎的特质。

金融与赌博的同源性

本质上,赌博是一种简化的市场。赌注归根结底是一种或有债权:

这在数学层面与期权或期货合约完全一致,都是用当下的确定性换取未来的不确定性。金融学中所谓的「投机」,在赌博中体现得更为直白。两者都是为不确定性定价的机制。

如今的任务是重新设计这一结构,使其成为正和模式,让流动性、参与者与创作者能通过互动实现共同成长。

这种差异存在于语言和文化层面,而非结构层面。凯恩斯、熊彼特与加尔布雷斯都会认同这一点。

(注:凯恩斯、熊彼特和加尔布雷斯都是 20 世纪极具影响力的经济学家,他们的理论对现代经济学、金融市场乃至社会政策都产生了深远影响。)

赌场赌注:押 1 美元赌红色,若结果符合则获得 2 美元。

看涨期权:支付 1 美元权利金,若达到行权条件则获得 2 美元收益。

赌场赌注与看涨期权并无二致:两者都是用当下的确定性换取未来的不确定性,且都由做市商提供流动性。唯一的区别只是「包装」不同。在大理石柱装饰的场所里,它被称为赌博;在 Etherscan 的页面上,它被称为金融。而真正的错误,是一直假装它们是两种不同的事物,实则它们本是一体。

现代社会在认知上的误区,就是人为地将两者割裂开来。

从负和到正和

传统赌博之所以是负和的,根源在于「抽成」机制。如果 10 名玩家每人下注 100 美元,而赌场抽取 10% 的庄家优势,那么重新分配的总财富就只剩下 900 美元。这样的体系注定了玩家的长期亏损:

形式上:

对于大多数游戏而言:

然而,在链上环境中,当赌博场景能够与现货市场互动时,「庄家」便不再需要通过榨取来获利。

它可以充当流动性路由器或做市机制。每一笔赌注都变成了买单,为长尾资产、代币,甚至信贷与预测市场中的结构化头寸增加流动性。

庄家不再从玩家身上榨取价值,而是将资金流回生态系统本身,将投机转化为流动性与分配动力。

一个简化的正和模型如下:

生态系统预期价值 = 所有玩家的预期价值之和 + 路由预期价值

(路由预期价值代表由庄家资金流创造的流动性价值)

在这一结构中,抽成不再消耗价值,反而创造价值。投机本身成为了注入流动性、分配资产、深化市场的机制。

文化与协调乘数效应

赌博之所以特别适合向正和模式转型,不仅因其具有观赏性,更因其作为分配渠道的作用。价格是分配的函数,而赌博能实现大规模的分配。每一次赌注都能引发连锁反应:代币被购买、流动性被注入、注意力被集中。

流媒体与社区会放大这种动态效应。主播将风险转化为娱乐,社区将赌注变成归属感的仪式,协议则捕捉这种能量并将其转化为资本流动。

当这些循环被代币化后,每一次赌注的意义便不止于价值转移 —— 它还能创造分配。通过赌博发行的代币,能实时积累持有者、提升流动性深度并获得叙事吸引力。曾经止步于老虎机的一次旋转,如今能创造市场存在感。

与传统赌场不同,其收益不再受赌注本身限制,而是通过网络溢出效应实现倍增 —— 在这里,投机成为了流动性与分配的双重渠道。赌博不再是一种道德风险,而成为资本形成的基础机制。

正和赌博的正式模型

设 W 为总赌注量,r 为抽成比例。协议收入为:

在传统赌场中,R 具有榨取性;而在这一模型中,R 被用于流动性操作,以深化市场并扩大分配。

生态系统净价值则为:

其中,路由预期价值代表由庄家资金流创造的流动性与分配价值。

由于 W 本身会随着分配与文化传播而增长,我们得到一个递归飞轮:

价格是分配的函数,而在这种情况下,赌博就是创造分配的引擎。

随着赌注不断累积,流动性会加深,代币会流通,文化能量会放大这一循环。

规范化转向与 G 乘数

如果上述观点成立,那么赌博的未来与赌场毫无关联。它关乎的是娱乐成为一种市场力量。人们对娱乐的热爱超越一切,而大规模的娱乐活动能推动市场变化。

Apple Store 的案例便证明了这一点:移动收入中占比最大的部分,是伪装成游戏的投机活动。

游戏化交易体验与超级赌博化将这一逻辑延伸至金融领域。正如嵌入式金融改变了消费金融科技,嵌入式投机也将改变零售交易。赌博不再是边缘恶习,而成为市场中最强大的分配渠道。

Пов'язані матеріали

Large Language Models Ace All Exams, Yet Move Farther from AGI: What Does This Paper Reveal?

The article discusses the ongoing challenge of defining and achieving Artificial General Intelligence (AGI). It notes that industry leaders have set vague, often profit- or time-based benchmarks for AGI, while the concept itself lacks a consensus definition—a situation the article compares to a "Rorschach test." It highlights a recent 2025 paper by researcher Michael Timothy Bennett, who proposes a new, measurable definition. Bennett frames AGI not as mimicking human performance on tests, which current large language models (LLMs) have already mastered, but as an "artificial scientist." A true AGI, according to this view, should be able to widely and efficiently adapt to new environments and tasks within real-world constraints (like computational and energy limits), focusing on the *discovery of new knowledge* rather than the replication of existing data. The author contrasts this with the current dominant approach of "scale-maxing"—massively scaling up data, parameters, and compute. While powerful, this method leads to models that fail on out-of-distribution problems and lack core intelligent abilities: they are passive learners, cannot reason causally, and cannot actively experiment or balance exploration with exploitation. The article argues that Bennett's framework offers a crucial shift. It makes AGI a quantifiable engineering problem and proposes new evaluation "adaptation benchmarks" that test an AI's ability to actively learn in novel scenarios. The conclusion is that achieving AGI will require a fundamental reset—a fusion of multiple methodologies beyond simple scaling, moving AI from mimicking patterns to embodying the scientific spirit of inquiry and discovery.

marsbit18 хв тому

Large Language Models Ace All Exams, Yet Move Farther from AGI: What Does This Paper Reveal?

marsbit18 хв тому

Pope Issues First AI Encyclical: 40,000 Words, 10 Key Points, Clarifying AI Anxiety

Pope Leo XIV's historic encyclical "Magnifica Humanitas," released in May 2026, marks the Catholic Church's first major document addressing artificial intelligence. The 40,000-word text moves beyond theological abstraction to confront practical AI anxieties affecting society. It argues that AI is no longer a mere tool but an embedded environment influencing daily decisions in areas like employment, healthcare, justice, and information, often without users' awareness. The encyclical presents ten core concerns. It highlights that the central issue isn't just regulation, but who holds the underlying *power*—control over data, compute, and platforms—often concentrated in private entities. It warns that even developers cannot fully explain AI systems, creating accountability gaps. While AI can simulate human interaction and creativity, it cautions against treating it as a moral agent capable of bearing true responsibility or forming genuine relationships. Key risks identified include AI's role in opaque decision-making for jobs or welfare, the amplification of persuasive disinformation, and the potential for education to focus on tool use over critical thinking. The document stresses that work has value beyond efficiency, and AI should enhance human capabilities, not merely replace roles. It firmly states that irreversible decisions, especially involving life and death, must remain under human judgment. Ultimately, the encyclical frames AI's challenge as anthropological, not just technological. As AI simulates uniquely human capacities like judgment and creation, it forces a re-examination of what makes human action meaningful: our capacity for responsibility, vulnerability, and bearing real consequences. The Pope concludes that technology is never neutral; its development and deployment are shaped by human values and choices, making an inclusive, ethically grounded dialogue essential for its future.

marsbit23 хв тому

Pope Issues First AI Encyclical: 40,000 Words, 10 Key Points, Clarifying AI Anxiety

marsbit23 хв тому

Торгівля

Спот
Ф'ючерси
活动图片