EigenLayer积分收益解读:大家都在「卷」的积分到底值多少钱?

Odaily星球日报Publicado a 2024-02-07Actualizado a 2024-02-07

Resumen

每个积分的价值可能在 0.05 - 0.20 美元之间。

原文作者:ROUTE 2 FI

原文编译:Luffy,Foresight News

EigenLayer 昨天再次开放其质押窗口,并将一直持续到 2 月 10 日。

我曾写过有关 EigenLayer 不同机会的文章,但今天我将探讨 EigenLayer 这些积分的潜在价值。

EigenLayer积分收益解读:大家都在「卷」的积分到底值多少钱?

EigenLayer 积分的计算公式如下:

ETH 数量 x 1 x 24 = 每天 EigenLayer 积分

比如:每天 10 ETH x 1 x 24 = 240 EigenLayer 积分

一个积分值多少钱?

目前这只是猜测,但有些人已经根据假设做出了预测。

EigenLayer积分收益解读:大家都在「卷」的积分到底值多少钱?

假设:

  • 你每天存入的每枚 ETH 可获得 24 EigenLayer 积分

  • TVL 为 1, 670, 000 ETH(38.9 亿美元)

  • 空投快照前 TVL 增长: 100% 

  • 距离快照还有 120 天(2024 年 6 月)

  • 空投百分比预测: 7% 

  • FDV 预测: 150 亿

  • 起始资金: 10 ETH

EigenLayer积分收益解读:大家都在「卷」的积分到底值多少钱?

正如你所看到的,有很多假设条件。最难的部分是确定他们是否会采用积分层级机制,以及 FDV 是多少。 Celestia 目前的 FDV 规模为 180 亿美元,而且随着 EigenLayer 的大肆宣传,我很确定它的 FDV 规模约为 150 亿美元,甚至可能达到 200 亿美元。

根据当前的假设,每个 EigenLayer 积分价值 0.12 美元。我与几个人交谈过,估计每个积分在 0.05 - 0.20 美元左右。在 Whales Market 上,人们正在以 0.15 美元的价格交易积分。我预计这个数字会更低。你可以在这里亲自查看

你可以尝试 Thor Hartvigsen 的 EigenLayer 空投计算器

总而言之,如果你在接下来的 120 天内进行抵押,你的每枚 ETH 将获得大约 400 美元的收益。这个数字可能会更低,甚至可能是 200 美元,但也可能会高得多,每 ETH 1, 000 美元收益并非完全不现实。虽然范围很广,但它应该是今年最有趣的空投之一。是否值得将你的 ETH 投入到智能合约中?我无法给你答案,但如果你不喜欢锁定资本,你应该寻找机会在 Whales Market 上购买积分,但你最终可能会为积分付出高昂的代价。

对我来说,一个开始闪烁的警报是,LST/LRT 的叙事开始感觉有点太简单了。

例如,购买 mETH 并获得 7.2% 年化收益。然后存入 EigenLayer 即可获得 EigenLayer 积分、重质押奖励和 ETH 升值(如果 ETH 价格上涨)。

我不知道,但是当每个人都赢的时候……有什么问题呢?

突然,我有一种感觉,我们又回到了 Anchor Protocol 出现时的「愉悦」状态。

我希望是我错了,但这值得一谈。

我在上一期中提到过这一点,但这里只是重复一下我目前正在玩的 LRT/LST 项目。它们都有优点和缺点,具体取决于你如何看待它们。

如果你是空投猎人:

Swell、EtherFi、Kelp、Puffer、EigenPie、Renzo

如果你想要最高收益:

Mantle ETH (mETH)=ETH 的 7.2% + EigenLayer 积分

如果你想要「安全」:

我在安全上加了引号。因为加密货币中的任何东西都不应该被声明为安全的,甚至 stETH 在 2022 年夏季也发生过严重脱钩。

然而,其中最安全的是(基于它们存在的时间)Lido、RocketPool、Binance Staked ETH。

我认为 Puffer 有坚实的支持,而且我有一种感觉,一段时间后这可能会被认为是更安全的选择之一。

我在参与什么:

我正在参与所有的空投活动和 mETH。就我个人而言,我也喜欢比较,而具有 7.2% APY 的 mETH 非常好。

如果你是一个看涨 ETH 的人,你可以购买 10 个 wstETH,将其存入 AAVE,然后借贷。例如,借入 50% ETH(5 ETH),然后购买 swETH、mETH、ETHx 并按照上面的建议操作以获得空投 + EigenLayer 积分。

另外,请记住,多个 LRT 代币即将推出:Genesis 和 Inception 是其中的两个。此外,Pendle 也有一些 degen 策略,你可以获得高达 30% 的收益率。

切勿在 EigenLayer 中下注超过你能承受的资金,祝你好运!

Lecturas Relacionadas

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

In mid-June, three seemingly independent industry events—the compliance-driven throttling of Fable 5, the open-sourcing of GLM-5.2, and the leaked release timeline for GPT-5.6—are pushing the global AI industry toward a watershed moment. These shifts signal a fundamental restructuring of the industry's underlying logic. First, **"usability" has substantially overtaken "advanced capabilities"** as the primary weight, pushing the global large language model (LLM) supply chain into a "dual-track" phase of controlled closed-source and local open-source coexistence. Second, **the competitive moats of closed-source giants are shifting**. Their technical focus is moving from "language intelligence" toward "spatial intelligence (world models)"—a domain heavily reliant on computing power. Third, faced with常态化 transnational compliance risks, **a "model-agnostic" decoupled design has become a survival necessity for application-layer developers to maintain business continuity.** The article details how Anthropic's Fable 5, despite its advanced engineering feats, was restricted for non-U.S. citizens within 72 hours of launch, highlighting how geopolitical compliance can instantly limit even the most advanced models. In response, the open-source camp, exemplified by Zhipu AI's MIT-licensed GLM-5.2, is gaining market share by offering stable performance improvements and significant cost advantages (up to 70% savings for enterprises), while achieving full adaptation with domestic semiconductor platforms. Meanwhile, closed-source leaders like OpenAI are pivoting. The anticipated GPT-5.6 reportedly shifts focus from language to spatial intelligence and world models, aiming to rebuild a generational gap in areas like 3D understanding, simulation, and industrial design that demand immense compute. The core conclusion is that the LLM supply chain's logic has changed. Enterprises must now evaluate infrastructure based on a composite of technical performance and policy compliance. For developers, complete reliance on a single closed-source API poses unacceptable risk. Implementing a truly model-agnostic architecture—enabling swift switches to compliant, locally deployable open-source alternatives—is no longer just good practice but a fundamental baseline for business continuity.

marsbitHace 44 min(s)

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

marsbitHace 44 min(s)

Is the 'Token Subsidy War' Among AI Giants Almost Over?

The article discusses the ongoing "token subsidy war" among AI giants like OpenAI and Anthropic, questioning whether it's nearing its end. It reveals that current AI subscription prices are heavily subsidized, with some plans offering tokens at up to 70 times the actual cost to attract and retain heavy users, especially developers and enterprises. This strategy mirrors past internet-era subsidy battles, but with a key difference: AI tokens lack "lock-in" effects. Unlike ride-hailing or food delivery apps, users can easily switch between AI providers as APIs become standardized, making it difficult for companies to raise prices post-subsidy. The piece highlights a structural asymmetry in the competition. Giants like Google, with massive advertising revenue, can afford to subsidize tokens indefinitely, akin to using "tokens as a weapon." In contrast, venture-backed companies like OpenAI and Anthropic face pressure to become profitable, especially as they approach IPO. The article cites Google Ventures founder Bill Maris, who suggests Google could slash token prices by 80%, putting immense pressure on competitors. Two potential endgames are presented: the "internet service" model (subsidize, monopolize, then raise prices) and the "utility" model (tokens become a standardized, low-margin commodity like electricity). Given the low switching costs, the latter seems more likely. The competition may not have a single winner but could instead accelerate AI's evolution into a foundational, infrastructure-level technology, akin to a public utility. For now, users continue to benefit from heavily subsidized token costs.

marsbitHace 1 hora(s)

Is the 'Token Subsidy War' Among AI Giants Almost Over?

marsbitHace 1 hora(s)

Beyond the Stadium: The Profitable Games Surrounding the World Cup

"Beyond the Pitch: The Profit Game Around the World Cup" The FIFA World Cup transcends being a sporting spectacle, evolving into a massive global arena for speculation and profit-seeking. The 2026 tournament has amplified this dynamic, creating a multi-layered ecosystem of financial opportunism alongside the football. **Prediction markets** have surged into the mainstream. Platforms like Polymarket and Kalshi saw trading volumes for World Cup contracts soar, attracting new users with their financial trading model and high-profile, chain-based wealth stories that overshadow traditional sports betting in terms of growth and narrative. However, **traditional sportsbooks** remain the dominant force, leveraging established user habits, legal markets, and comprehensive product offerings to handle the vast majority of speculative wagers, with projections suggesting record-breaking betting volumes. Capital markets also react. **"Concept stocks"** in countries like South Korea and Japan experience volatile price swings based on team performance and anticipated fan spending on items like chicken, beer, and viewing parties, effectively becoming a stock market reflecting fan sentiment. The **ticket resale market** has become a sophisticated arena for arbitrage. Prices fluctuate wildly based on team draws and star power, with sellers sometimes listing tickets they don't yet own in a practice akin to short-selling, while FIFA's own "Right to Buy" tokens add another layer of speculative trading. **Collectibles and merchandise** offer another avenue. Panini sticker albums, with their inherent scarcity and nostalgic value, can become high-value collectibles. Limited-edition or locally themed jerseys command significant premiums on secondary markets, and even counterfeit vendors profit from fans' desire for affordable match-day identity. The **cryptocurrency** space has seen a frenzy of speculative, unauthorized World Cup-themed meme coins on chains like Solana. These tokens, often exploiting team names and player imagery, experience extreme pump-and-dump cycles, creating stories of massive gains for a few early entrants and steep losses for many others. Finally, an entire industry thrives on **providing information and tools** to other speculators. Developers create platforms like SeatSidekick to track ticket inventory and prices, while paid Telegram groups and subscriptions sell betting tips and predictions, monetizing the widespread desire for an informational edge. In essence, the World Cup has become a compressed, global laboratory for speculation. While the games determine champions on the field, a parallel, complex network of financial transactions—spanning prediction contracts, bets, stocks, tickets, collectibles, crypto, and information services—settles its own scores in the global market.

marsbitHace 1 hora(s)

Beyond the Stadium: The Profitable Games Surrounding the World Cup

marsbitHace 1 hora(s)

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

This article explains the three primary methods for Codex to interact with a computer, each with distinct use cases, permission boundaries, and trust levels. **1. Computer Use:** This offers the broadest access, allowing Codex to visually control and interact with the graphical user interface of authorized macOS/Windows apps, system settings, and even iOS simulators. It's ideal for tasks lacking APIs or structured tools, such as operating legacy software or multi-app workflows. However, it's the slowest method and has the widest permission scope, requiring careful supervision for sensitive actions. **2. Chrome Extension:** This grants Codex access to the user's logged-in Chrome browser state, including cookies, profiles, and open tabs. It's best for tasks requiring user identity across websites like Gmail, LinkedIn, Salesforce, or internal dashboards. Its key advantage is multi-tab control for complex workflows. While more powerful for browser-based tasks than Computer Use, it carries higher sensitivity as actions are performed under the user's identity. **3. In-App Browser:** This is a browser isolated within the Codex thread, separate from the user's personal browsing data. It excels in web development and debugging scenarios—previewing local servers, testing responsive layouts, or annotating designs directly on the page. Its isolation is a strength for development but a limitation for tasks requiring login sessions. The core principle is to choose the narrowest, safest, and most structured interface for the task. Use plugins or MCPs first, resort to visual control (Computer Use) only for GUI-dependent tasks, employ the Chrome extension for identity-reliant browser work, and prefer the In-App Browser for isolated development. **Appshots** are clarified as a fourth, complementary tool for *inputting* context—capturing a screenshot of a window to point Codex to something—rather than a method for Codex to *act*. Together, this layered approach highlights a key to AI agent productization: not granting unlimited permissions, but constraining them within clear boundaries for specific tasks while preserving user oversight.

marsbitHace 3 hora(s)

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

marsbitHace 3 hora(s)

Trading

Spot
Futuros
活动图片