百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

Odaily星球日报Published on 2023-11-06Last updated on 2023-11-06

Abstract

拿多少钱拯救你,我的巴特·辛普森。

原创 | Odaily星球日报

作者 | 南枳

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

《辛普森一家》(The Simpsons)是由美国福克斯广播公司出品,马特·格勒宁创作的一部动画情景喜剧。该剧集获得了大量奖项,其中包括 25 次艾美奖、 26 次安妮奖和 1 次皮博迪奖。1999 年 12 月 31 日期的《时代》杂志将其评为 20 世纪最优秀的电视剧作。

而今日,在《辛普森一家》S35 E5 Treehouse of Horror XXXIV出现了一集有关 NFT 的故事,剧情梗概为 Bart Simpson 被一台机器制作成了首个人类 NFT,而后被 Marge Simpson 从虚拟 NFT 世界中拯救出来。

万事俱备,东风吹起

很快,意大利艺术家Rino Russo发布了 Punk 风的辛普森一家 NFT“Springfield Punks”,其推文内容为“Treehouse of Horror XXXIV 中 Bart 变成了 NFT,现在用 Springfield Punks 的 free mint 进行庆祝吧。”

(Odaily星球日报注:Springfield 是辛普森一家生活的城市。)

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

据悉,该 NFT 的铸造成本约为 0.0025 ETH(约 4.7 美元),而 11 月 6 日 13 时该 NFT 于 Blur 的地板价曾冲到了约 0.4 ETH,较铸造成本涨约 160 倍;截止 15 时,该 NFT 达到了 0.249 ETH,涨幅接近 100 倍。发行后 6 个小时成交额达 740 枚 ETH。

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

实际上,Rino Russo 并非临时来蹭,而是长期发布聚焦于《辛普森一家》的内容,并自八月起就开始制作 Springfield Punks 系列,这次恰逢其会地“踩上”了涉及 NFT 的《辛普森一家》剧集,从而引爆了热度。

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

故事的结尾已经写好

具备讽刺意味的是,该剧集的主旨原本是呈现人们过度 FOMO,NFT 最终崩盘的情景。

在 Bart Simpson 变成 NFT 后,其父亲 Homer J. Simpson 先是表示“我永远失去了一部分”,但看到了 NFT 达 150 万美元的价格后立刻转为兴奋地大喊“YES!!!”(因 Bart 是第一个人类 NFT。)

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

而在 Marge Simpson 即将救出 Bart 时,Homer 更是愿意将 Bart 以一亿美元的价格出售,尽管这将使 Bart 永远被困在区块链上。Homer 表示:

在我错过了一切之后,有机会不错过——房地产泡沫、科技泡沫、第二次科技泡沫、现在的科技泡沫——这一次我想成为那个把所有钱都捐出去的人。

最终,Homer 以 1 亿美元“成为了 NFT”,然而 FOMO 情绪戛然而止,价格闪崩至 0.05 美元。

百倍NFT「Springfield Punks」:反FOMO终成FOMO之源

回到现实:一场反 FOMO 的故事最终成为了 FOMO 的源头,Springfield Punks 价格仍维持着上涨势头,其结局如何?或许已在动画中昭示……

Related Reads

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

NEAR Returns to AI Origins: From Payroll Struggles to Blockchain, Now Focusing on AI Agents and Privacy NEAR Protocol's journey began not with grand blockchain ambitions, but from a practical hurdle: its AI startup founders, including Transformer paper co-author Illia Polosukhin, couldn't efficiently pay international developers in 2017. This led them to pivot and build a high-performance, scalable blockchain. After years navigating various crypto narratives like sharding and cross-chain interoperability, NEAR is now leveraging its AI roots to re-enter the AI arena. A key driver is its "NEAR Intents" layer, which abstracts complex cross-chain transactions. Users simply state their goal (e.g., swap BTC for ETH), and a solver network finds the optimal route. This system has processed over $20B in cross-chain volume, generating significant fee revenue. A major growth area is private transactions via "Confidential Intents/Swaps," which hide trade details until settlement to protect against MEV and front-running. Remarkably, private swaps recently accounted for over 40% of NEAR's transaction volume, highlighting strong demand but also potential regulatory scrutiny. With its AI-founder pedigree, NEAR is positioning itself at the intersection of blockchain, AI agents, and privacy, aiming to become infrastructure for the emerging agent economy while navigating the challenges of its rapid adoption.

marsbit1h ago

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

marsbit1h ago

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

In recent discussions, Vitalik Buterin has frequently emphasized the concept of "CROPS," a framework defining core values for Ethereum's development. CROPS stands for Censorship Resistance, Capture Resistance, Open Source, Privacy, and Security. Initially outlined in the Ethereum Foundation's "EF Mandate," it represents a commitment to user sovereignty, ensuring that the network resists external control, remains open, protects privacy, and prioritizes security. The relevance of CROPS extends beyond Ethereum's foundational principles, becoming crucial in the context of AI integration. As AI agents begin handling wallet operations and automated transactions, the risk increases that users may cede control over their digital assets, privacy, and intentions to centralized AI service providers. A "CROPS AI" would therefore emphasize local execution where possible, privacy-preserving remote model calls (e.g., using zero-knowledge proofs), and transparent, verifiable processes to maintain user agency. Vitalik highlights a significant convergence between "CROPS Ethereum access layer" and "CROPS AI." Both address the same fundamental challenge: how users can access powerful services—be it blockchain data via RPCs or AI models—without exposing sensitive information or relinquishing ultimate control. This intersection points toward a future digital entry point that is more private, secure, and user-controlled. Ultimately, CROPS is not merely an abstract ideal but a practical guidepost. It steers development—from protocol resilience and wallet design to AI agent safety—towards a future where users retain self-sovereignty even as digital systems grow more complex and powerful. In an era of accelerating AI adoption, these "slow variables" of censorship resistance, openness, privacy, and security may define Ethereum's enduring value.

marsbit2h ago

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

marsbit2h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit3h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit3h ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit3h ago

Token Inefficient, Economy Tokenless

marsbit3h ago

Trading

Spot
Futures
活动图片