操作指南:如何将Farcaster空投机会最大化?

Odaily星球日报Published on 2024-06-03Last updated on 2024-06-03

Abstract

每个空投猎手都必须在Farcaster上建立社交存在。

原文作者:FIP Crypto | Airdrops Made Simple

原文编译:深潮 TechFlow

本文将帮助你充分利用 Farcaster 平台,确保你有最大的机会参与未来的空投。

Farcaster 是一个最近筹集了 1.5 亿美元的去中心化社交网络 SocialFi 项目。尽管像 Lens Protocol 这样的项目已经存在了更长时间,但 Farcaster 凭借与 Layer 3 和 Zora 等流行 DApp 的整合,迅速获得了最多的关注。每个空投猎手都必须在 Farcaster 上建立社交存在。以下是浏览此平台的分步指南:

1.创建 Warpcast 账户

Warpcast 是使用 Farcaster 基础设施的最流行客户端。其他客户也使用 Farcaster,但本文将重点放在最著名的 Warpcast 上。

创建 Warpcast 账户最烦人的部分是无法使用加密货币支付 5 美元/年的费用。只能通过 iOS/Android 进行账户创建,并且 5 美元/年的费用只能在应用中以法币支付购买。这违背了去中心化的理念。输入你的电子邮件地址后,你将获得一个全新的助记词。

操作指南:如何将Farcaster空投机会最大化?

这与钱包的助记词分开,需要同样妥善保管。

1.将你的空投钱包链接到 Warpcast

这是确保你的链上活动符合未来空投资格的重要步骤。例如,@Spectral_Labs 的空投奖励了在 Base 上活跃的 Warpcast 用户。我的两个钱包(Warpcast + 空投)都在这份资格名单中(但我未能获得此次空投资格)。

因此,我强烈建议将你的空投钱包链接到 Warpcast,以防未来的空投考虑你的 Farcaster 活动。我分享了一个连接钱包的快速指南

2.将 Layer 3 账户链接到 Warpcast

你需要一个 Warpcast 账户来完成某些 Layer 3 任务。但是将 Warpcast 链接到你的 Layer 3 账户稍微复杂一些。在点击Farcaster 链接后,必须在 Warpcast 上完成一个 Layer 3 任务以链接账户。但这可能因人而异。

3.在 Warpcast 上保持活跃

Spectral 的空投奖励了至少有以下条件的 Farcaster 账户:

❍ 10 个粉丝

❍ 10 个点赞

❍ 10 个发布

因此,一个活跃的 Warpcast 账户可能会让你有资格参与未来的空投。但 Warpcast 的算法与 Twitter 不同。如果你在主页上发布(默认情况下),你只是与关注者分享。

操作指南:如何将Farcaster空投机会最大化?

这在开始时几乎没有人,所以,如果你想获得更多点赞和粉丝,最好的方法是在频道上发帖。频道类似于 Twitter 的社区功能,任何人都可以创建和加入频道。获得点赞和关注的最佳方式是发布到有更多关注者的频道,如:

❍ /base

❍ /ethereum

❍ /farcaster

要创建频道,你需要花费应用内货币(Warps),稍后我会详细说明:

4.购买和使用 Warps

Warps 是某些链上操作所必需的,包括:

❍ 给其他用户的帖子赠送 Warps(类似于打赏)

❍ 将 Warpcast 账户连接到其他应用

❍ 在某些频道发布

❍ 创建自己的频道

❍ 铸造 NFT

你需要用 ETH 以 5 美元兑换 500 个 warps 的比例购买Warps

操作指南:如何将Farcaster空投机会最大化?

好消息是这可以用加密货币支付。创建频道需要每年 2500 个 Warps(25 美元)。我认为创建和管理频道可能是 Farcaster 空投的一个乘数。有些频道要求每次发布支付 10 个 Warps,这些 Warps 会转给频道所有者。Warpcast 在 FAQ 中提到,积累 Warps 没有任何好处,所以最好花掉你拥有的Warps。Warps 只能在 Warpcast 客户端中使用,不能转移到其他客户端。

5.互动 Frames

Frames 是 Farcaster 最新的功能,可以将任何 cast 变成互动应用。

操作指南:如何将Farcaster空投机会最大化?

我发现它们大多数都很卡,尤其是在通过它们完成 Layer 3 任务时(有些任务需要一段时间才能验证)。但在可能的情况下,我尽量与 Farcaster 上看到的任何 Frames 互动。这也可能是未来空投的一个标准。你可以用 Fileverse创建一个 Frame

6.获得 Power Badge

Power Badge 专门奖励活跃的 Warpcast 用户,我正在努力获得一个。尽管算法不是公开的。Warpcast 暗示了授予的标准:

❍ 活跃度(发布的频率)

❍ 亲和力(power 用户是否喜欢你的发布)

❍ 标记(如果你的帖子被标记为垃圾信息)

我给一个有 Power Badge 的人发了私信,他提到他通过“有意识地努力获得拥有 Power Badge 的 OG 的反应” 获得了这个徽章。因此,我建议你与 Power Badge 用户互动。但不要给垃圾信息,尽量有创意地评论,这样你更有可能获得他们的点赞,增加你获得 Power Badge 的机会。

所有这些看起来可能很繁琐,但这正是我们比那些懒得创建账户的人更有优势的地方。

原文链接

Related Reads

Without It, There Would Be No ImageNet... Now It's Gone

Amazon is shutting down its crowdsourcing platform, Mechanical Turk (MTurk), on September 30th, ending a 21-year run. Launched in 2005, MTurk connected businesses with a global online workforce to perform small, repetitive tasks—known as Human Intelligence Tasks (HITs)—that were easy for humans but difficult for computers at the time. At its peak, it hosted over 500,000 workers worldwide. MTurk played a pivotal, though often unseen, role in the rise of modern AI. Its most famous contribution was to the creation of the ImageNet dataset. In the late 2000s, researcher Fei-Fei Li and her team faced the monumental challenge of manually sorting and labeling millions of internet images to build a large-scale visual database for training AI. They turned to MTurk, distributing the work to nearly 50,000 workers from 167 countries. This "human-in-the-loop" effort made the massive ImageNet project feasible. ImageNet, in turn, became the foundational benchmark for the 2012 ImageNet Large Scale Visual Recognition Challenge. The victory of Geoffrey Hinton and his students' deep convolutional neural network, AlexNet, on this dataset dramatically demonstrated the power of deep learning, catalyzing the AI revolution that followed. Now, MTurk is closing. The platform has declined as the very AI it helped build has become capable of automating the simple tasks it once provided. Furthermore, the AI industry's data needs have evolved, shifting towards more specialized expertise for model tuning and evaluation, served by newer platforms. Ironically, some studies suggest MTurk workers themselves began using AI tools like ChatGPT to complete tasks, adding a layer of automation to the "artificial artificial intelligence" service. The shutdown marks the end of an era where human effort, distributed globally via the internet, laid the crucial groundwork for the intelligent machines of today.

marsbit13m ago

Without It, There Would Be No ImageNet... Now It's Gone

marsbit13m ago

Bill Gates' Latest Long-Form Article: The Real Trouble with AI is That We Aren't Ready

Bill Gates' latest essay, "The turbulent AI era is here. The choices we make now are critical," warns that society is unprepared for the profound social and economic transition AI will bring. While optimistic about AI's long-term potential in healthcare, education, and other fields, Gates focuses on the "transition period" over the next 10-20 years. He argues this transition differs from past technological shifts like the Industrial Revolution because AI automates cognitive labor itself, potentially reducing the total number of future jobs. Risks like enhanced cyber-attacks and social disruption are already emerging, not distant future threats. A key concern is "low-cost intelligence substitution," where AI performs defined tasks cheaper than humans, gradually thinning workforces. Gates introduces the concept of "Human Reserved" jobs—roles like nursing or delivering serious medical news—where human judgment and empathy should remain central, even if AI is technically capable. To manage the transition, he calls for new governance, stronger social safety nets, retraining, and international cooperation, especially between the US and China. Crucially, he proposes taxing AI usage and robots to slow displacement and fund social programs. The core dilemma Gates presents is that AI could become humanity's "greatest equalizer" or its "worst source of injustice," depending on whether its immense productivity gains are broadly shared or concentrate wealth and power. The fundamental challenge is not just advancing the technology, but adapting our social and economic systems to it.

marsbit29m ago

Bill Gates' Latest Long-Form Article: The Real Trouble with AI is That We Aren't Ready

marsbit29m ago

Just Now, Anthropic Unveils Physical MCP: Claude Begins Controlling the Real World

Anthropic has announced the Model Hardware Standard (MHS), a new standard enabling AI agents like Claude to safely control physical devices. Building on the Model Context Protocol (MCP), MHS standardizes communication between AI agents and hardware such as microscopes, robotic arms, and lasers, marking a significant step for AI from the digital into the physical world. Developed in collaboration with HHMI Janelia Research Campus, MHS uses standardized drivers to translate basic commands (e.g., read, write) into a format any programmable device can understand. This drastically reduces integration time from weeks to hours or minutes and allows agents to discover and operate new devices using natural language tags that describe machine properties and safety limits. Agents can control devices via MCP, command-line interfaces, or APIs. They can sequence operations, monitor results, adjust parameters in real-time, and generate deterministic scripts for long-running tasks. Early tests show Claude interacting with hardware exploratively, like a scientist, learning to calibrate a laser and scripting the process. Early adopters and partners include AWS, Automata, Danaher, Doosan Robotics, and Tecan, who are integrating MHS support into their platforms. While promising, challenges remain: Claude's physical reasoning is limited, requiring expert oversight, and MHS currently only works with programmable hardware. Anthropic plans further refinements and broader device support before open-sourcing the standard.

marsbit1h ago

Just Now, Anthropic Unveils Physical MCP: Claude Begins Controlling the Real World

marsbit1h ago

History's Only Asset with a 100% Win Rate After 4 Years of Holding

**Title: The Only Asset with a 100% Win Rate Over Any 4-Year Holding Period** This article analyzes which major, freely-tradable assets have historically never produced a nominal loss over any rolling 4-year holding window. It concludes that only two distinct categories achieve this: ultra-low-risk contractual assets and Bitcoin. Among traditional risk assets, none maintain a perfect 4-year record. The S&P 500 had negative 4-year periods (e.g., 1929-1932: -64.8%). The Nasdaq 100 fell roughly 60% from 2000-2003. Gold saw a ~47.7% loss from 1981-1984. US real estate declined about 23.3% from 2007-2010. Even long-term US Treasury bonds (e.g., 2021-2024: -19.8%) and corporate bonds can produce 4-year losses due to interest rate and market price risks. In contrast, the first category achieving 100% nominal success includes assets like rolling 3-month US Treasury Bills, 4-year certificates of deposit (CDs), and US Treasuries held to maturity within 4 years. Their "guarantee" stems from contractual obligations and credit backing (e.g., FDIC insurance, US sovereign promise), not price appreciation. The sole exception in the high-risk category is Bitcoin. Analysis of daily data from 2010-2026 across 4,419 rolling 4-year windows shows a 100% positive return rate. The worst 4-year period (April 2021 to April 2025) still yielded a +32.6% total return (~7.3% CAGR). This record is unique because Bitcoin has no issuer, promises no cash flows, and has endured severe drawdowns (70-90%), yet its market price has always recovered within a 4-year span. The key distinction is the source of the "100%": contractual assets offer known, low nominal returns, while Bitcoin's record stems purely from historical price appreciation despite extreme volatility. The article suggests that for Bitcoin, the ability to hold for 4+ years is more critical than active trading strategies.

marsbit1h ago

History's Only Asset with a 100% Win Rate After 4 Years of Holding

marsbit1h ago

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

This article details the dramatic rise and near-collapse of a hedge fund built by Leopold Aschenbrenner, a 24-year-old former OpenAI researcher. The fund, named Situational Awareness, amassed $45 billion in assets within two years. Its explosive growth stemmed from Aschenbrenner's influential 165-page manifesto predicting AGI's arrival by 2027 and his high-profile Silicon Valley connections. The fund employed an extremely aggressive strategy: high concentration and 400% leverage to bet long on AI infrastructure stocks while shorting legacy software firms. In July, this structure backfired when both sides of the trade reversed simultaneously—AI stocks plunged while shorted stocks rallied—triggering massive losses that nearly wiped out all equity. Major player Jane Street reportedly lost billions. The fund's leveraged public portfolio was ultimately sold at a discount to Citadel. The SEC is now investigating banks like Goldman Sachs for their role in facilitating the fund's high-leverage trades. The article compares this to past blow-ups like Archegos, highlighting systemic failures in risk management where the pursuit of short-term profits overrode due diligence. It questions whether such risky leverage concentrated in the AI sector, currently at record highs, poses a broader systemic threat. Ironically, Aschenbrenner, who studied AI safety at OpenAI, designed a fund structure prone to uncontrolled failure. Days after the crisis, he reportedly raised another $400 million for new investments.

marsbit1h ago

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

marsbit1h ago

Trading

Spot
活动图片