为什么 DePIN 现在如此受欢迎?

币界网Published on 2024-08-20Last updated on 2024-08-20

币界网报道:

作者:Jasper De Maere,CoinDesk;编译:邓通,

2019 年左右,DePIN 计划的首波重点是数字基础设施,但现在我们看到其他类型的网络正在兴起(DePIN 代表去中心化的物理基础设施网络)。以数据或服务网络为中心的项目正变得越来越普遍。最终,我将 DePIN 归类为 1) 使用基于区块链的去中心化协调来运营基础设施和 2) 依赖或影响物理基础设施(如服务器、传感器或财产)的项目。

在讨论驱动因素之前,我们需要了解 DePIN 项目几乎总是由双边市场组成。这些市场有需求方和供应方。

  • 需求方。用户寻找服务或产品来解决特定问题或需求,可以通过服务或 dApp 来满足。

  • 供应方。市场中分散的基础设施(包括节点、硬件、传感器等)通过项目或 dApp 的前端托管。

那么,这些市场的双方发生了什么?

供应方

让 DePIN 供应变得更简单,可以实现更好、更多样化的供应,从而更贴近多样化的需求方。

我看到供应方上线背后的两个主要驱动因素:

  • 成本曲线下降;

  • 实用代币设计改进。

成本曲线

从历史上看,托管基础设施需要前期资本,而只有大型中心化实体才能获得这些资本。随着成本曲线下降,几乎任何人都可以成为基础设施提供商。

最近的研究表明,过去二十年,内存成本下降了 100 倍,计算(GPU)成本下降了 100-300 倍。尽管对这些资源的需求在增长(甚至出现短缺),但托管大量计算或内存的准入门槛已大幅降低。构建基础设施所需的资本正在减少,使更多人能够参与、运行节点,并使网络更加稳健,而不会出现关键故障点。

实用代币

实用代币的设计长期以来被视为一门暗黑艺术。在过去的几年中,技术诀窍一直在迅速改进,以提供更强大的代币模型。

DePIN 网络通常依赖于实用代币,因为它们具有网络效应,因为这些代币可以协调具有不同经济利益的利益相关者之间的激励。合理的代币设计对于创建正确的博弈论和激励支持网络的行为至关重要,并适当奖励贡献。实用代币还有助于启动初始网络效应,现在越来越多的代币工程师在设计过程中使用情景分析和统计数据。这将带来更强大的设计,能够经受时间和市场波动的考验。

需求方

从历史上看,DePIN 项目一直受到需求限制,这意味着服务和应用程序虽然上线,但由于各种原因,其接受率较低。不断增长的需求最终使 DePIN 业务变得可行,从而启动了改进的飞轮。

我看到需求方上线背后的三个主要驱动因素:

  • DePIN 的可用性正在提高;

  • 隐私和安全越来越令人担忧;

  • 数据生成正在激增。

可用性

说实话:如今许多 Web3 应用对于没有在加密货币上花费大量时间的人来说都是无法使用的。账户抽象和支持 AI 的 UX 应该可以解决这个问题。

2024 年是账户抽象(向用户隐藏区块链交易的一些技术接线)在 Web3 上流行起来的一年。人们意识到当前的 Web3 用户体验可能不足以说服主流用户从 Web2 过渡,这一认识最近引起了广泛关注。如今,有大量公司专注于 UX 和账户抽象。与此同时,我们看到 ERC-4337(2023 年以太坊升级正是专注于此)真正在包括 DePIN 在内的广泛项目中得到采用。

与此同时,自近两年前 GPT 推出以来,人工智能经历了复兴,模型不断改进,集成发展迅速。目前正在区块链上开发的人工智能助手将简化应用程序的使用,减少对人性化前端的需求。

隐私与安全

对数据保护的担忧被证明有利于 DePIN 的采用,由于其去中心化的特性,DePIN 从根本上改善了数据保护。

虽然隐私悖论是一个有据可查的现实,但自从人工智能在社会中传播以来,用户越来越担心。特别是在数据管理方面,隐私和安全是一个日益严重的问题。我们看到的证据表明,用户越来越多地寻找优先保护个人信息的替代解决方案。DePIN 采用去中心化方法,从本质上增强了隐私和安全性,使其成为个人和企业更具吸引力的选择。经过几十年的冷漠之后,人们对这个话题的敏感度日益提高,这为 DePIN 创造了良好的条件。

数据生成

据估计,每天大约会产生 3.5 亿 TB 的数据。人类正在生成前所未有的大量数据,这些数据需要存储在内存中并用计算机处理,而 DePIN 在这方面非常擅长……

我们正在创建比以往更多的数据。据估计,当今所有数据的 90% 都是在过去两年内生成的。随着 Gen AI 的发展,数据真正成为了 21 世纪的石油,因此我们需要确保妥善存储数据。以前,许多公司和个人都不确定数据是存储在裸机服务器还是云中;现在,数据存储方面有了更多的决策过程。随着 DePIN 的成熟,它越来越成为更成熟的数据存储和处理选项的可行替代方案。

未来前景

DePIN 有很多发展空间,这也解释了用户、投资者和整个社区的兴奋。我坚信 DePIN 很快就会重新定义社会中经济重要基础设施的组织方式,至少将其定位为与传统基础设施平起平坐。

Related Reads

2028: The Arrival of Recursive Self-Improvement (RSI)

**AI Recursive Self-Improvement (RSI): The Countdown to 2028 Begins** AI is no longer just a trained tool but is starting to rewrite its own evolutionary pace. According to Anthropic co-founder Jack Clark, there is a 60% probability that by the end of 2028, Recursive Self-Improvement (RSI) will become a reality. This means AI could autonomously design and build a more capable next-generation version of itself without any human researcher involvement—Claude 10 creating Claude 11, for instance. Supporting this timeline, Google DeepMind's CEO Demis Hassabis confirms that all leading AI labs are intensely focused on RSI, making it an industry-wide priority. He expresses profound concern, stating this potential is what keeps him awake at night. Concrete data underscores this acceleration: - METR evaluations show current top models like Claude are solving tasks up to the 16-hour limit of existing test frameworks. - In Epoch AI's challenging MirrorCode benchmark, Claude Opus 4.7 recreated complex software in hours for a fraction of the human cost. In one extreme test, AI autonomously coded for 19 days straight. - Anthropic reports over 80% of its codebase is now written by Claude, and researcher productivity has increased up to 8-fold since 2024. - OpenAI's policy blueprint highlights RSI as a major upcoming governance challenge. CEO Sam Altman reportedly hinted RSI might arrive within six months, potentially delaying OpenAI's massive IPO. The implication is an impending "intelligence explosion," where AI-driven progress outpaces human control. The central question is no longer if it will happen, but whether humanity is ready.

marsbit7m ago

2028: The Arrival of Recursive Self-Improvement (RSI)

marsbit7m ago

World Models, Metaverse, Digital Twins, Physical AI: Are They the Same Thing?

Title: World Models, the Metaverse, Digital Twins, Physical AI: Are They the Same Thing? The article clarifies that concepts like the metaverse, Web3, simulation platforms, digital twins, and Physical AI are not the same thing but are all part of the broader trend of blurring the lines between the digital and physical worlds. It positions "world models" as the foundational "cognitive layer" or "operating system" that enables AI to understand and simulate the world. Key distinctions are made: - The **Metaverse** is a destination for immersive social and economic experiences. World models could act as its "engine," generating interactive 3D content efficiently. - **Web3** focuses on decentralized ownership and economics (rules layer), operating on a different technical level than world models. - **Simulation Data Platforms** (e.g., for autonomous vehicles) are a 1.0 version, relying on manual design. World models represent a 2.0 version, using AI to generate realistic, varied scenarios autonomously. - **Digital Twins** create high-fidelity, real-time mirrors of physical systems (e.g., a factory). World models go a step further by enabling predictive simulation of future states. - **Physical AI** (robots, AVs) refers to AI that acts in the physical world. World models are a core component, providing the understanding and prediction needed for planning. A proposed hierarchy places world models at the cognitive layer, supported by infrastructure (compute, data) and supporting application tools (simulation, digital twins), action systems (Physical AI), user experiences (metaverse), and rules (Web3). In conclusion, while distinct, many of these previously hyped concepts may ultimately rely on advances in world model technology to fulfill their promises, as world models provide the essential cognitive foundation for simulating and interacting with complex environments.

marsbit11m ago

World Models, Metaverse, Digital Twins, Physical AI: Are They the Same Thing?

marsbit11m ago

"Shocking" CPO: How Does the Glass Bridge Actually Work? Detailed Explanation from Corning

Chinese CPO stocks plunged over 6% following Corning's announcement of its Glass Bridge platform at a Seoul tech conference. The new technology utilizes wafer-level glass ion-exchange waveguides for passive alignment between fibers and photonic chips, potentially simplifying traditional CPO architectures that rely on complex Fiber Array Units and active alignment equipment. This raised market concerns about reduced long-term demand for mid-stream CPO components. Corning's official documentation details Glass Bridge as a platform for fiber-to-PIC connectivity in NPO, CPO, and high-density modules. Its key features include wafer-level manufacturing for consistent, cost-effective production; a standardized, removable MT ferrule interface for ecosystem integration; and a separable high-density connector design supporting over 24 channels for assembly flexibility. Corning positions the technology as complementary to FAUs, addressing limitations in ultra-high-fiber-count scenarios. The market reaction reflects a broader reassessment of the AI optical interconnect value chain. Funds shifted from CPO and PCB manufacturing stocks towards glass substrate concept stocks like Kaisheng Technology and Dyer Laser. Analysts note glass substrates are seen as a next-gen advanced packaging material, offering a potential path for domestic industry differentiation amid AI-driven demand for high-performance, large-scale packaging, marking a structural migration in value towards upstream specialty materials.

marsbit12m ago

"Shocking" CPO: How Does the Glass Bridge Actually Work? Detailed Explanation from Corning

marsbit12m ago

A Group of Suzhou Engineers Unexpectedly Attain Financial Freedom

In Suzhou, a group of engineers from Lianxun Instruments, a leader in optical communication testing equipment, have achieved remarkable wealth after the company's IPO. Listed just two months ago on the STAR Market, the company's stock price surged approximately 30 times, making it the only A-share stock priced above 2,000 yuan. This surge created substantial fortunes for nearly 100 technical employees who held a collective 15.91% stake through employee stock ownership platforms, valued at over 36 billion yuan at the current market cap. Among them, nearly 40 became billionaires, while even the smallest holdings exceeded 5 million yuan in value. Founded in 2017 by Hu Haiyang, Yang Jian, and Huang Jianjun, Lianxun Instruments was established to address China's reliance on foreign high-end testing instruments. The company grew rapidly with a strong focus on R&D, where technical staff make up nearly 80% of its workforce. Early implementation of employee stock plans helped retain this core talent. The company's explosive growth is fueled by booming AI computing demand, with clients including major global optical module leaders. Its revenue skyrocketed from 276 million yuan in 2023 to 1.194 billion yuan in 2025, turning a profit in 2024. The IPO has also generated massive returns for early investors, including Suzhou's state-owned capital, which saw a hundredfold return. This story reflects a broader trend in China's markets, where technology firms in AI, semiconductors, and optics are creating new wealth, rewarding engineers and technical teams who are now central to modern capital-driven success stories, marking a shift from previous eras dominated by internet and real estate tycoons.

marsbit2h ago

A Group of Suzhou Engineers Unexpectedly Attain Financial Freedom

marsbit2h ago

Trading

Spot
活动图片