Pump.fun 收入突破 1 亿美元,Polymarket 在八月的表现超过了 NFTs

深潮Pubblicato 2024-09-03Pubblicato ultima volta 2024-09-03

两个平台都经历了迅猛的崛起,收入和交易量都已超过 1 亿美元。

撰文:Zack Abrams,The Block

编译:Koala,火星财经

自今年一月推出以来,热门的模因币发行平台 Pump.fun 已经从超过一百万种模因币中累计获得了 1 亿美元的收入。

另一个热门加密项目 Polymarket 在八月份的交易量超过了所有链上所有 NFTs 的总和,数据显示来自分析平台 CryptoSlam。

加密行业一直以来都吸引了大量投机者,不论是好是坏。因此,两大最热门的加密平台——模因币发行平台 Pump.fun 和去中心化预测市场 Polymarket——都建立在投机的基础上也就不足为奇了。

有趣的是,这两个平台可以看作是彼此的对立面。在 Pump.fun 上,用户对模因币进行投机,这些模因币除了品牌和社区价值外没有任何内在价值主张,这意味着很难预测哪些币种能够脱颖而出并吸引粉丝。而在 Polymarket 上,用户在交易市场头寸时被鼓励利用所有可用的信息,从政治选举到埃隆·马斯克本周会发多少条推文,都可以进行预测。

加密行业一直以来都吸引了大量投机者,不论是好是坏。因此,两大最热门的加密平台——模因币发行平台 Pump.fun 和去中心化预测市场 Polymarket——都建立在投机的基础上也就不足为奇了。

有趣的是,这两个平台可以看作是彼此的对立面。在 Pump.fun 上,用户对模因币进行投机,这些模因币除了品牌和社区价值外没有任何内在价值主张,这意味着很难预测哪些币种能够脱颖而出并吸引粉丝。而在 Polymarket 上,用户在交易市场头寸时被鼓励利用所有可用的信息,从政治选举到埃隆·马斯克本周会发多少条推文,都可以进行预测。

但这两个平台都经历了迅猛的崛起。根据 Dune Analytics 的数据仪表板,Pump.fun 自 2024 年 1 月推出以来,开发者的累计总收入最近已超过 1 亿美元。Pump.fun 的开发者从平台上的所有交易中收取 1% 的费用。Pump.fun 甚至最近取消了部署代币的费用,使用户比以往更容易创建新的模因币。

然而,上周五 Pump.fun 的日收入是自 5 月 24 日以来的第二低单日收入。该平台能否继续激励用户创建和交易模因币,将对其未来增长至关重要,否则该项目可能会像 friend.tech 一样,成为一个曾经火爆的 Web3 社交平台,在过去三个月内基本停止盈利。根据 The Block 的数据,friend.tech 的收入已经大幅下降。

Polymarket 超越了 NFT 交易量

根据 The Block 和 CryptoSlam 的数据,Polymarket 也在本月取得了显著成就:其交易量超过了所有链上 NFT 的总和。在过去的 30 天内,NFT 的交易量仅约为 3.77 亿美元,而 Polymarket 的平台上则达到了 4.63 亿美元的交易额。

根据 The Block 的数据,随着 2024 年总统大选的临近,Polymarket 的活跃交易者数量自 5 月以来稳步增长。该平台甚至聘请了选举预测专家内特·西尔弗(Nate Silver)作为顾问,尽管美国用户官方上并不被允许使用该网站。

目前在这个预测市场上,前总统唐纳德·特朗普在 2024 年总统大选中略微领先于副总统卡马拉·哈里斯。接近 7.5 亿美元的资金已经押注在选举结果上。

Crypto di tendenza

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77 Bloody Codes: When the '$5 Wrench' Shatters the Privacy Myth of France's Crypto Elite

**Summary** In the first half of 2026, France recorded 77 violent crimes—including kidnappings, illegal confinement, and extortion—targeting cryptocurrency holders, a 71% increase over the 45 cases in all of 2025. This equates to an attack every 2.3 days, making France a global hotspot for so-called "wrench attacks," where criminals use physical violence to coerce victims into surrendering crypto assets. High-profile cases include the 2025 kidnapping of Ledger co-founder David Balland, who was shown with a severed finger in a ransom video, and an attempted kidnapping of the family of Paymium's CEO in Paris. Prosecutors note these are not isolated incidents but part of structured criminal networks, sometimes involving minors. Several factors contribute to France's vulnerability: a large holder base (approx. 7.3 million people), the presence of major crypto firms and executives, a culture of public disclosure among enthusiasts, and potential data leaks. The trend is spreading across Europe, which now accounts for over 40% of such global attacks. Research indicates a correlation between Bitcoin price surges and increased wrench attacks. In response, French Interior Minister Laurent Nuñez announced a three-pillar action plan focusing on enhanced intelligence sharing, deeper cooperation with the industry association Adan, and improved operational and cross-border coordination. Authorities have made over 200 arrests in the past year. Security experts warn that digital asset safety now extends to the physical world. They advise holders to use hardware wallets, avoid disclosing holdings on social media, enable multi-factor authentication, and report suspicious activity. The situation underscores the urgent need for the crypto community to shift from a "show-off" culture to one of discretion as physical security becomes paramount.

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Both OpenAI and Anthropic are 'Developing Their Own Chips' — Beyond Cost, the Control Over Computing Power is Paramount

OpenAI and Anthropic are both advancing plans to develop custom AI chips, driven by the need to control computing power and reduce costs. According to reports, Anthropic is in early-stage development of its own chips and in talks with Samsung for manufacturing, while OpenAI is collaborating with Broadcom and TSMC, aiming to deploy its first inference chip by late 2026. The primary motivation extends beyond just lowering expenses. For these large model companies, chips are core production assets. By designing specialized hardware (ASICs) tailored to their specific model architectures—OpenAI's being more sparse and Anthropic's more dense—they aim to achieve deeper software-hardware co-design. This synergy can significantly improve inference speed, energy efficiency, and overall unit economics, offering advantages that off-the-shelf GPUs cannot. This move does not signify an immediate replacement for suppliers like Nvidia. The process from design to deployment takes 18-24 months, and Nvidia's GPU ecosystem remains deeply entrenched. Instead, custom chips provide a strategic alternative and negotiating leverage, allowing companies to use them for specific, high-volume workloads like inference while still relying on external GPUs and TPUs for other tasks. The trend reflects a broader industry shift where AI competition is evolving from pure algorithmic prowess to integrated control over the entire software-hardware stack. Companies like Google, Amazon, Meta, and Microsoft are already on this path. For foundries like Samsung, securing orders from AI leaders like Anthropic represents a significant opportunity to expand its footprint in the advanced semiconductor market for AI. Ultimately, the race for "computing sovereignty" is now a central battleground for major AI players.

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