Imagine an ordinary morning in 2030.

You pick up your phone, scroll through social media for twenty minutes, post a tweet about breakfast, chat with a friend about a movie you recently watched, and casually answer a question from an AI assistant.

In the top-right corner of your screen, a tiny number keeps ticking upward.

It’s your daily data earnings notification — an AI company’s training system has accessed your content three times today, and the licensing fees have already been automatically settled into your account. Not a huge amount, but real.

You put your phone down and continue eating breakfast, barely thinking about it. Just like how today you use Alipay to pay or WeChat to message people without finding it remarkable.

Right now, this scenario sounds like science fiction.

But what if I told you that every piece of technology required to make it happen already exists today?

1. An Overlooked Reality

Before talking about “the future,” let’s first talk about something happening right now.

Over the past few years, the speed of AI development has shocked everyone. From ChatGPT to large language models, from text generation to image and video creation, the boundaries of AI capability are expanding at a visible pace.

But very few people seriously ask one question:

What exactly are these AI systems trained on?

The answer is simple:

Human data.

Every post you make on social media, every keyword you type into a search engine, every digital trace you leave across platforms — all of it forms the foundation of today’s most powerful AI models.

Without this data, modern AI would not exist.

And where does that data come from?

From you.
From billions of ordinary internet users just like you.

So here’s the real question:

When AI companies use this data to build models worth hundreds of billions of dollars — and then use those models to build commercial empires — what do ordinary users get in return?

The answer is:

Almost nothing.

You provided the raw materials for free. Someone else used those materials to build the factory. The factory generated enormous wealth, but that wealth had nothing to do with you.

This isn’t a conspiracy theory.

It’s simply how the current digital economy works.

2. Why Has This Happened?

To understand why ordinary users have been excluded from AI’s value distribution system, we first need to understand a deeper issue:

Data ownership has never been taken seriously.

The content you post on social platforms may legally belong to you, but the platform typically has extremely broad rights to use it.

The same applies to tweets on Twitter/X.

As for behavioral data generated inside apps, platforms often claim ownership so completely that users cannot even access the data themselves.

This system was created during the early internet era, when the value of data was not fully understood.

Platforms offered free services. Users contributed data. An unspoken transaction took place between both sides.

The problem is that over time, this trade has become increasingly unfavorable for users.

AI has made the issue impossible to ignore.

When data becomes the core production resource of AI training — and the AI industry grows into a trillion-dollar market — the question of “Who owns the data?” stops being merely a legal or technical issue.

It becomes a fundamental question about wealth distribution.

3. The Technology Is Already Ready

The good news is that the technology needed to solve this problem already exists today.

Layer One: Data Ownership Verification

Blockchain technology can create immutable on-chain ownership records for data.

Who created the data, when it was created, and how it has circulated can all be permanently anchored on-chain and transparently verified.

This solves the foundational problem:

Who actually owns the data?

Layer Two: Self-Sovereign Identity

Decentralized Identity (DID) systems allow users to own digital identities that do not depend on any platform.

This identity is generated and controlled by you.

No platform can unilaterally take it away.

Your data assets, authorization records, and behavioral history are tied to your identity — not to a company’s servers.

Layer Three: Automated Licensing and Settlement

Smart contracts can automate the entire authorization process through code.

If an AI company wants to use your data, it triggers a licensing contract, pays the required fee, and the earnings are instantly settled into your account.

No lawyers.
No intermediaries.
No manual operations.

Everything happens automatically.

Together, these three layers form a complete infrastructure for a new data economy:

• Data ownership verification
• Self-sovereign identity
• Automated revenue distribution

This is not just a concept.

It’s not a vision trapped inside a whitepaper.

It is a technological path that can already be built and used today.

4. Ordinary People Can Finally Participate in AI Development

Once this infrastructure becomes reality, one thing changes fundamentally:

For the first time, ordinary people become suppliers to AI — not just raw materials.

Today, you are an AI user.

You use AI tools to improve productivity and save time.

At the same time, you are also unknowingly an AI trainer.

Your data is already being used, even though you are not informed and receive no compensation.

But in the future, you can become an active data supplier to AI systems.

You can choose to verify ownership of your data, turn it into an asset, license it to AI companies, and receive real economic rewards in return.

This is not a small difference.

It is a fundamental shift in identity.

From passive raw material
to active participant.

From the edge of the value chain
to one of its core nodes.

And importantly, this is also beneficial for the AI ecosystem itself.

One of the biggest challenges facing AI companies today is the shortage of high-quality training data.

Freely scraped internet data may be massive in quantity, but its quality is inconsistent, and copyright risks are becoming increasingly severe. Lawsuits from organizations like The New York Times have already demonstrated how serious this issue has become.

When data can be verified, legally licensed, and market-priced, AI companies gain access to higher-quality and more trustworthy training data.

Meanwhile:

• Data suppliers (ordinary users) receive fair compensation
• AI companies gain compliant data sources
• The entire ecosystem operates under transparent and equitable rules

This is what the AI economy should look like.

5. What’s Missing Is Not Technology — It’s Awareness

Now let’s return to that ordinary morning in 2030.

For that future to become reality, we need more than mature technology.

We need a shift in awareness.

Enough people need to recognize that the data they generate every day is a valuable asset — not free raw material for platforms to harvest indefinitely.

And that shift in awareness is already happening.

AI’s rapid rise is accelerating it.

Once the enormous value of the AI industry became visible to everyone, the question of “Who owns the data?” could no longer be avoided.

Every person who begins thinking about data sovereignty today is helping push this transformation forward.

Every person who chooses to take control of their digital identity today is casting a vote for a fairer AI economy.

Data sovereignty is not some distant Web3 ideal.

It is a real transformation already underway.

And you can choose to become part of it starting today.

MEMO is a decentralized AI data infrastructure network developed by the Memolabs team. Its core mission is to provide decentralized storage, data ownership verification, identity authentication, data assetization, and trading services for the AI economy.

In simple terms, MEMO is building two things:

• A system where users truly own their data
• A secure and trustworthy memory layer for AI Agents

The MEMO project was launched in 2017 and now operates more than 50,000 storage nodes across Southeast Asia, the Americas, and Africa, with millions of registered wallet addresses.

Its investors include HashKey, DHVC, and SNZ, while ecosystem partners include Metis, Harmony, Alibaba Cloud, and AWS.

What Problem Is MEMO Solving?

The core contradiction of traditional cloud storage services — such as AWS or Google Cloud — is simple:

Your data lives on platform-controlled servers, which means users never truly have ownership or control.

At any moment, data can be:

• Deleted by the platform
• Sold to third parties
• Used to train AI models

Meanwhile, the original creators of that data receive nothing in return.

The AI era makes this contradiction even more obvious.

AI Agents require persistent memory. But if that memory is stored on centralized servers, everything can disappear the moment a session ends or an account gets suspended.

MEMO’s solution is to move data storage away from centralized servers and into decentralized networks, while using blockchain technology to establish verifiable ownership from the moment data is created.

In other words:

Every piece of data truly belongs to the user from day one.

MEMO’s Core Technical Architecture

MEMO uses a modular layered architecture, with different layers responsible for different functions throughout the system.

MEFS: The Core Decentralized Storage Protocol

At the foundation of MEMO is MEFS, the project’s self-developed decentralized storage protocol.

MEFS uses:

• Redundant storage
• Data sharding
• Erasure coding
• Multi-replica mechanisms

to ensure data security and resilience.

Even if part of the network goes offline, the data remains available and recoverable.

Storage task matching, fee settlement, and node verification are all managed automatically through smart contracts, without manual intervention.

Meeda: Data Availability for Ethereum Rollups

Meeda is MEMO’s data availability solution designed specifically for Ethereum Rollup scenarios.

It stores actual data off-chain inside the MEMO network, while only keeping indexes and proofs on-chain.

This significantly reduces Rollup transaction costs while still ensuring that data remains verifiable and retrievable at any time.

MemoLayer: Layer 2 Scaling Infrastructure

MemoLayer improves network throughput through an architecture that combines off-chain execution with on-chain final settlement.

It is specifically designed to support high-frequency micropayment scenarios, which are critical for autonomous transactions between AI Agents.

Zero-Knowledge Proofs (ZK)

MEMO also introduces Zero-Knowledge Proof technology at the privacy layer.

This allows users to complete data verification or transactions without exposing the original data itself.

Potential use cases include:

• DID verification
• AI training data authorization
• Privacy-preserving transactions

The MEMO Ecosystem Products

The MEMO ecosystem revolves around one central concept:

Data sovereignty.

Its products are designed for three major groups:

• Everyday users
• AI developers
• Enterprises

DataDID: The Identity Gateway of the MEMO Ecosystem

DataDID is MEMO’s decentralized data identity system and serves as the main entry point into the ecosystem.

After registration, users receive a dedicated on-chain DID (Decentralized Identifier). All points, data assets, and participation records are tied to this identity.

DataDID includes several built-in modules:

• AliveCheck (digital life protection)
• AppsList (application marketplace)
• SkillsList (AI Skill plugin marketplace)

Access:
👉 datadid.memolabs.net

MEFS MCP Server: Persistent Memory for AI Agents

The MEFS MCP Server is MEMO’s decentralized storage access service built specifically for AI Agents.

Through the MCP protocol, AI Agent clients such as OpenClaw can directly connect to the MEMO network to store:

• Conversation history
• Task outputs
• Knowledge bases

This enables true persistent memory across sessions.

Open-source repository:
👉 github.com/memoio/mefs-mcp-server

ERC-7829: The Data Asset NFT Standard

ERC-7829 is MEMO’s proposed NFT standard for data assets.

It allows content such as:

• Tweets
• Documents
• AI interaction records

to be minted into on-chain data assets.

The standard includes built-in support for:

• Data provenance tracking
• Access control
• Automated revenue distribution

ERC-7829 serves as the technical foundation of MEMO’s data assetization framework.

The Upcoming Data Marketplace

The upcoming data marketplace completes the ecosystem loop.

Once users convert their data into assets, those assets can be traded in the marketplace.

AI companies and other data buyers can purchase data through smart contracts, with revenue automatically settled directly to the original creators.

This creates a fully decentralized data economy where value flows back to those who generated the data in the first place.

How Is MEMO Different from Filecoin and Arweave?

All three projects belong to the decentralized storage sector, but their positioning is fundamentally different.

Filecoin

Filecoin focuses primarily on the general-purpose cold storage market, with miner incentives at the center of its design.

Arweave

Arweave focuses on permanent storage, making it suitable for archival use cases.

MEMO

MEMO differentiates itself in two key ways:

1. AI Agent-Oriented Real-Time Storage and Memory Management

MEMO directly supports MCP protocol integration, enabling AI Agents to use decentralized persistent memory in real time.

2. A Full Data Economy Stack

Through DataDID and ERC-7829, MEMO builds a complete loop from:

• Storage
• To data assetization
• To data trading

MEMO is not just storing data.

It is turning data into economic value.

FAQ

Q: What is the relationship between MEMO and Memolabs?

A: Memolabs is the development team and incubation lab, while MEMO is its core product and network.

Q: How can ordinary users participate in the MEMO ecosystem?

A: The easiest entry point is DataDID:

👉 datadid.memolabs.net

Users can begin by completing daily check-ins to earn points, then install the browser extension to mint tweets into data assets or access applications through AppsList.

Q: Can data stored on MEMO be lost?

A: No.

The MEFS protocol uses redundant storage and data sharding technology, ensuring that data remains available even if some nodes go offline. The system also includes self-repair mechanisms.

Q: How can AI Agents connect to MEMO’s storage capabilities?

A: By deploying the MEFS MCP Server.

Any AI Agent client that supports the MCP protocol can read and write data through the MEMO network, enabling persistent cross-session memory.

Q: What is MEMO’s standard for data assetization?

A: MEMO introduced the ERC-7829 Data Asset NFT Standard, specifically designed for data-based content rather than image NFTs.

It includes built-in access control and automated revenue distribution and is already being used through the DataDID browser extension.

Q: How large is MEMO today?

A: MEMO currently operates more than 50,000 storage nodes across Southeast Asia, the Americas, and Africa, with millions of registered wallet addresses.

It is one of the largest decentralized storage networks in terms of both node scale and user coverage.

Official Channels

• Official Website: memolabs.org
• Twitter: @MemoLabsOrg
• Telegram: t.me/memolabsio
• DataDID Portal: datadid.memolabs.net
• MEFS MCP Server: github.com/memoio/mefs-mcp-server

In 1870, John D. Rockefeller founded Standard Oil in Ohio. Within a decade, he controlled more than 90% of America’s oil refining capacity.

He didn’t win by inventing the oil engine, nor by drilling the most wells. His strategy was simpler — and more ruthless. He controlled the refineries, the pipelines, and the transportation system. In other words, he controlled the most critical thing of that era: the pricing power of fuel.

Whoever controls fuel controls the lifeblood of industrial civilization.

150 years later, no one monopolizes oil anymore. But a new battle over pricing power is quietly emerging. This time, the fuel is no longer oil, but a unit of measurement most people have never heard of:

Tokens.

I. Four Revolutions, Four Types of Fuel

Every major technological revolution has had its own core source of energy. Whoever controls the production and pricing of that energy ultimately holds the real power of the era.

The core fuel of the First Industrial Revolution was coal. Every roar of the steam engine was powered by shovels of coal burning underneath. Whoever controlled the mines controlled the fate of factories. Britain became the “workshop of the world” in the 19th century largely because it possessed Europe’s richest coal reserves and the most efficient mining system.

The core fuel of the Second Industrial Revolution was electricity. The famous “War of Currents” between Edison and Westinghouse was, at its core, a fight over the pricing power of electricity. Whichever transmission standard became dominant could effectively charge an “entry fee to modernity” for entire cities.

The core fuel of the Third Technological Revolution — the Information Revolution — was bandwidth. In the early internet era, telecom operators were the unquestioned toll booths of the digital world. Without bandwidth, even the best content could not travel. Without bandwidth, e-commerce, social media, and search engines could never have existed. The term “traffic anxiety” reflects how deeply ordinary people felt dependent on this fuel.

Now, the Fourth Technological Revolution has arrived.

Its name is artificial intelligence.

And its core fuel is called the Token.

II. What Exactly Is a Token?

For many people, the first time they heard the phrase “token economics” was probably through the blockchain industry. But as AI continues to evolve, the word “Token” no longer belongs exclusively to crypto.

In AI, it refers to something extremely simple:

The unit used to measure how AI processes text.

When you input text into ChatGPT or any large language model, the model does not read word by word the way humans do. Instead, it breaks text into “tokens” — roughly equivalent to three-quarters of an English word, or about half a Chinese character’s worth of information.

The number of tokens consumed while processing your input and generating a response becomes the billing basis for that interaction.

A more intuitive analogy:

Tokens are like AI’s electricity meter — or a taxi meter.

Every sentence you type, and every word the AI generates, quietly makes the meter tick upward.

To make this more concrete:

Suppose you ask AI to draft a 500-word business email. From your prompt to the final output, the process may consume around 1,000 tokens. At current mainstream model pricing, the cost is roughly $0.002.

Or imagine asking AI to analyze a 10-page PDF report and generate a summary. That might consume around 8,000 tokens, costing about $0.016.

Sounds cheap? It is — for individuals.

But now change the perspective.

Imagine a mid-sized company with 100 employees using AI tools daily. If each employee consumes 50,000 tokens per day, that’s 5 million tokens every day. Based on enterprise API pricing, the daily bill could reach around $10. That becomes $300 per month, or $3,600 per year.

Now scale it further.

If the company’s core business itself is AI-driven — such as an AI customer service platform or a content generation platform — it could easily process billions of tokens per day.

At that point, token costs are no longer negligible.

They become a defining variable that determines whether the business model itself works.

Tokens may be microscopic units, but token economics is macroeconomic in scale.

It determines who can afford AI — and who occupies which position in the hierarchy of this new revolution.

III. The Pricing Power of Fuel Is Once Again Concentrated

This brings us back to a recurring historical pattern:

At the beginning of every major revolution, the pricing power of the core fuel becomes highly concentrated.

At its peak, Rockefeller’s Standard Oil not only controlled refining capacity, but also manipulated railroad freight rates through secret agreements, systematically driving competitors out of business.

Early electric utilities operated as regional monopolies. Consumers had no bargaining power.

Telecom operators during the broadband era similarly controlled information flow through expensive, slow, and opaque pricing structures.

Today, AI token pricing is following a remarkably similar trajectory.

Only a handful of companies in the world are capable of independently training and deploying top-tier large language models. They possess massive parameter scales, global data center infrastructure, and enormous training datasets — all of which create towering barriers to entry.

In practice, token pricing power is concentrated in the hands of these few companies.

There is also a subtle paradox worth examining.

Over the past few years, the price per token for mainstream large models has dropped dramatically. When GPT-4 first launched, one million tokens could cost as much as $60. Three years later, models with comparable performance cost less than $1 per million tokens.

At first glance, this seems like a victory for market competition and consumers.

But there is another side to the story.

As prices fall, model capabilities grow exponentially — and more advanced models consume significantly more tokens.

Tasks once handled by GPT-4 may now require GPT-5 for acceptable results. But GPT-5 may consume multiple times more tokens than GPT-4.

“Smarter” and “more expensive” are becoming quietly intertwined.

More importantly, token pricing itself lacks transparency.

Different companies define “a token” slightly differently. Input tokens and output tokens are often billed separately. Even the model’s internal “chain of thought” reasoning may generate additional token consumption.

Ordinary users have little ability to calculate true costs or make meaningful comparisons across providers.

And opacity is one of the classic characteristics of fuel monopolies.

This is not an accusation against any specific company. Historically, the concentration of fuel pricing power has never been purely a moral issue. More often, it has been an inevitable phase of technological development.

The real question is this:

Once concentration emerges, history never stops there.

IV. How History Breaks Fuel Monopolies

Fortunately, history also shows another pattern:

Fuel monopolies never last forever.

In 1911, Standard Oil was forcibly broken up by the U.S. Supreme Court into 34 independent companies. This outcome was driven by the Sherman Antitrust Act of 1890, along with two decades of public pressure and political struggle.

What Rockefeller lost was not his oil.

What he lost was the exclusive right to set prices.

Electricity followed a different path. In most countries, power grids eventually became public infrastructure subject to government regulation. Electricity transformed from a commercial product into a basic utility everyone had the right to access.

Only when electricity became cheap enough to be almost invisible did factories achieve true 24-hour production — and modern industrial civilization fully mature.

The decentralization of internet bandwidth came largely through technological progress itself. Falling fiber-optic costs, the spread of wireless networks, and the rise of WiFi gradually transformed bandwidth from a telecom-controlled commodity into a widely accessible public resource.

Looking across these histories, one clear pattern emerges:

Every “democratization of fuel” requires two conditions.

The first is decentralized supply.

The fuel can no longer be produced by only a handful of players. Ordinary people must also be able to participate in production.

The second is a redistribution mechanism.

Producers need incentives and fair compensation, while consumers need affordable access.

In previous revolutions, these conditions were achieved through technological innovation, antitrust legislation, and government regulation.

So what about the Fourth Revolution?

What will break the monopoly over AI tokens?

V. The Next “Refinery” May Be Every Connected Device

Let’s imagine something bold.

When electricity costs approached zero, factories achieved nonstop production for the first time.

When bandwidth costs approached zero, video streaming transformed from a luxury into an everyday utility.

Whenever revolutionary energy sources become universally accessible, society experiences a massive leap in productivity.

Will Tokens follow the same path?

Technologically, the answer is probably yes.

Model inference efficiency improves by orders of magnitude every few years. Specialized AI chips are rapidly becoming cheaper. Open-source models are quickly narrowing the gap with proprietary systems.

From this perspective, the long-term direction of token costs seems obvious:

Downward.

But technology only solves the cost problem.

It does not solve the pricing power problem.

Lower costs do not automatically decentralize pricing power. Higher efficiency does not guarantee ordinary people can participate in the economic benefits of the revolution.

That is why a new economic model is emerging:

Decentralized compute networks.

Imagine a world where billions of personal devices — home servers, idle GPUs, edge devices with spare compute power — are connected through network protocols and collectively perform AI inference tasks.

Every device contributes computing power, much like individual solar panels feeding electricity into a grid, producing fuel that others can consume.

In this system, the producers of computational power are no longer just giant technology companies.

They become ordinary participants distributed around the world.

They contribute compute power and receive economic rewards in return — settled through blockchain tokens, which can then be directly used to purchase AI services, creating a self-sustaining economic loop.

This would create something unprecedented:

Ordinary people would become not only consumers of Tokens, but also producers of Tokens.

Of course, this vision remains early-stage. Many technical and economic challenges still need to be solved.

But its direction strongly mirrors every previous chapter of fuel democratization in history:

Distributed supply.
Incentivized production.
Broader participation in value creation.

Conclusion: No Fuel Can Be Monopolized Forever

In 1911, when Standard Oil was broken apart, many people believed it marked the end of the oil era.

The opposite happened.

After the breakup, the oil industry experienced the fastest expansion in its history. Distributed pricing power created competition, efficiency, and broader participation.

The power Rockefeller lost ultimately became productivity gains for society as a whole.

History never stops simply because a small group controls the fuel supply.

At the intersection of technology and systems, new paths always emerge.

Tokens will be no exception.

The Fourth Revolution has only just begun. Its core fuel — the AI capability to process information, measured in Tokens — remains highly concentrated in the hands of a few companies.

This is not a moral judgment.

It is simply a historical observation describing a process still unfolding.

But the direction is becoming increasingly clear:

When every device can participate in production and benefit from the system, the pricing power of Tokens will gradually flow from the hands of a few into the hands of everyone.

If there’s one type of content that has dominated the internet over the past two years, MBTI is definitely near the top of the list.

From “Why INTJs always prefer being alone” to “ENFPs are born social butterflies,” MBTI has practically become a new social language for younger generations.

Then came SBTI, which quickly took off in professional circles. Compared to MBTI’s focus on psychological tendencies, SBTI puts more emphasis on behavioral patterns and work styles in real-world environments.

The reason personality tests always go viral is actually pretty simple:

People are endlessly curious about one question:

“What kind of person am I, really?”

But here’s the problem.

These tests all describe your personality in the real world.

So what about the Web3 world?

What kind of person are you there?

Are you an “Alpha Hunter” constantly chasing the next opportunity at full speed?

Or a committed long-term believer with true diamond hands?

Are you an anonymous lurker?

Or an ecosystem socialite who loves interacting with communities?

In the past, these labels mostly existed as memes and inside jokes within crypto communities.

But now, RMTS (Web3.0 Personality Test), newly launched on AppsList, is trying to turn these “on-chain personalities” into something more systematic.

RMTS: A Personality Test Built for Web3 Users

RMTS is a fun personality-testing platform that supports both Web2 and Web3 login methods.

It doesn’t try to measure whether you’re “extroverted” or “sensitive.”

Instead, it analyzes your behavioral tendencies in the on-chain world based on how Web3 users actually think and act.

The entire test contains only 8 questions, but it evaluates you across four core dimensions:

• Risk
• Motivation
• Time
• Social

In simple terms, RMTS isn’t asking:

“What kind of person are you?”

It’s asking:

“What kind of Web3 player are you?”

What Kind of Personality Might You Get?

Based on your answers, RMTS generates a personalized Web3 personality profile.

For example:

Alpha Hunter

Always on the front lines. Extremely sensitive to information and naturally drawn to emerging projects and trends.

Diamond Hand Pro

A true long-term thinker who doesn’t FOMO easily and won’t let short-term volatility shake their convictions.

Beyond that, the system also visualizes your personality distribution across multiple on-chain behavioral dimensions:

• Degen / Safe (aggressive vs. conservative)
• Utility / Lore (practical vs. narrative-driven)
• Sniper / HODLer (short-term trader vs. long-term holder)
• Anon / Public (anonymous vs. highly social)

At their core, these are all real behavioral differences that exist among Web3 users.

And once you see the results, you realize something interesting:

Everyone participates in Web3 in completely different ways.

It Supports Both Web2 and Web3 Login

RMTS offers two login options:

• Email login
• Wallet login

That means even if you’re completely new to Web3, you can jump in immediately.

And for crypto-native users, wallet login makes the experience feel seamless and natural.

Why This Kind of Test Fits Web3 So Well

Because Web3 itself is an intensely personality-driven world.

Some people are obsessed with risk.

Some are deeply rational.

Some love narratives.

Some only trust data.

Some spend all day networking and engaging with communities.

Others stay permanently anonymous.

In the traditional internet era, these behaviors were simply user profiles.

But in Web3, they’re gradually becoming a new form of digital identity.

What makes RMTS interesting is this:

It’s one of the first attempts to visualize this kind of “on-chain personality” in a fun and approachable way.

Maybe You Should Take the Test

Maybe you think you’re a Diamond Hand.

Then the system tells you:

You’re actually a full-blown Alpha Hunter.

Or maybe you’ve always thought of yourself as a hardcore Degen —

only to discover that you’re really just a cautious long-term believer.

A lot of the time, people’s self-perception doesn’t fully match their actual behavioral patterns.

And that’s exactly what RMTS is trying to surface:

Your real Web3 behavioral personality.

So here’s the question:

What’s your true identity in the Web3 world?

Maybe it’s time to find out:

👉 https://datadid.memolabs.net/

If you’ve just heard about DataDID — or already created an account but still aren’t sure what you can actually do with it — this guide is for you.

DataDID is a decentralized data identity system. But rather than starting with definitions, here’s the simplest way to understand it:

Every action you take inside the ecosystem becomes part of your accumulation.

Points, data assets, ecosystem rewards — the deeper you participate, the more you build.

From registration to daily check-ins, minting, AppsList, SkillsList, event tasks, and the developer platform, the DataDID ecosystem is far more expansive than most people realize.

This guide will walk you through the entire ecosystem step by step.

Step 1: Register for DataDID and Create Your On-Chain Identity

Everything starts here.

Visit the DataDID platform and register using either your email address or a MetaMask wallet. The system will generate a unique decentralized identity (DID) for you.

This DID becomes your passport across the entire MEMO ecosystem. All of your future points, data assets, and participation records will be tied to this identity.

Registration takes about 2–3 minutes.

If someone invited you, entering an invitation code will instantly reward you with 500 starting points.

👉 Register now:

• Web: https://datadidapp.memolabs.net/
• H5: https://datadid.memolabs.net/
• Telegram: https://t.me/data_did_bot
• Pi Browser: https://datadidpi.memolabs.net/

Step 2: Daily Check-Ins — Keep Accumulating Points

After registering, the simplest — and most important — action begins:

Daily check-ins.

Click the check-in button on the DataDID homepage to complete your daily security report and receive points.

It sounds simple, but the long-term value is much bigger than it appears.

Points are the ecosystem’s record of participation and rights. They can be used for premium feature subscriptions and will also serve as an important basis for future reward distribution.

Points also benefit from a compounding time effect:

The earlier you start, the greater your long-term advantage becomes.

Step 3: Install the Browser Extension for Easier Check-Ins and More Powerful Features

If manually opening the website every day feels inconvenient, the DataDID browser extension is exactly what you need.

Once installed, you can complete daily check-ins directly inside your browser without switching pages.

But convenience is only the beginning.

The extension unlocks two much more important features.

Mint Your Tweets Into On-Chain Data Assets

After installing the extension and using it on Twitter/X, a Mint button will appear beneath your own tweets.

Clicking the button converts that tweet into an on-chain data asset powered by MEMO’s ERC-7829 Data Asset NFT standard.

Once minted, your tweet is no longer just text stored on Twitter’s servers. It becomes a digital asset with verifiable on-chain ownership:

• Owned by you
• Displayable
• Holdable
• Tradable in the upcoming data marketplace

Every tweet you mint today is positioning you for the future data economy.

AI Button: Earn Points Just by Posting

The extension also adds an AI button beneath tweet and reply boxes.

Click it, and the system automatically generates MEMO ecosystem-related tweets or quick replies. Once posted, you receive point rewards.

In other words:

You can casually use Twitter while accumulating ecosystem points at the same time.

👉 Install the DataDID browser extension:
https://datadidapp.memolabs.net/

Step 4: AppsList — Making Check-Ins More Interesting

DataDID is not just a check-in platform.

It’s a complete application ecosystem.

AppsList is DataDID’s built-in application marketplace, featuring a growing collection of functional Web3 applications.

You can log into all of them directly with your DataDID identity — no additional registration required. All activity remains tied to your DID.

Several standout applications are already live inside AppsList.

AliveCheck — A Core Safety Feature

AliveCheck is one of DataDID’s core protection modules.

Every day, users can check in to confirm they are safe. If no check-in occurs for two consecutive days, the system automatically alerts pre-designated emergency contacts.

Users can also configure:

• Location authorization
• Message capsules

A message capsule functions like a digital will. If you disappear or lose contact, the system automatically sends your preset message to selected contacts.

It’s one of the clearest examples of combining data sovereignty with real human-centered utility.

Personality Analysis

This application analyzes your on-chain behavior and data activity to generate a Web3 personality profile.

It’s both entertaining and insightful — a unique way to understand your digital identity.

Using AppsList applications also rewards you with points.

Every interaction contributes to your ecosystem accumulation.

Developers can also submit their own applications through the AppsList developer platform. Once approved, the app becomes available to all DataDID users and qualifies for ecosystem incentives.

👉 Enter AppsList:https://datadid.memolabs.net/

👉 Publish your app:https://datadid-developer.memolabs.net/

Step 5: SkillsList — Unlock More Possibilities for AI Agents

If you’re already using OpenClaw, SkillsList will take your experience to the next level.

SkillsList is a decentralized Skill plugin marketplace built specifically for OpenClaw on top of the DataDID architecture.

Here, users can browse and install Skill plugins that directly expand OpenClaw’s capabilities.

MEFS MCP Service

This is MEMO’s official decentralized storage Skill.

After installation, OpenClaw can permanently store:

• Conversation history
• Task outputs
• Knowledge base data

inside the MEMO decentralized network.

The data remains accessible anytime and doesn’t disappear when a session ends.

This gives AI Agents something critically important:

A true memory layer.

OpenClaw Skills

A growing collection of functional Skills already exists across areas such as:

• Data processing
• Content generation
• Automation tasks

allowing OpenClaw to continuously expand its abilities.

One particularly useful example is the datadid-checkin Skill.

After installation, you simply give OpenClaw a command, and both DataDID and AliveCheck daily check-ins are automatically completed for you.

Points are credited automatically — fully hands-free.

👉 Install here:https://skillhub.memolabs.net/q-hp-true/datadid-checkin

Developers can also upload their own Skills through the SkillsList developer platform. Revenue distribution is protected by smart contracts, preventing unilateral platform interference.

👉 Enter SkillsList:https://datadid.memolabs.net/

👉 Publish a Skill:https://datadid-developer.memolabs.net/

Step 6: Events and Tasks — Earn Both Points and Cash Rewards

Beyond daily check-ins and app usage, DataDID also offers advanced tasks and recurring ecosystem events.

These are among the fastest ways to accumulate points.

Completing tasks inside the platform can reward large amounts of points, while special campaigns often include direct USDT rewards.

Current Event: DataDID Mystery Box Carnival

📅 Event Period: April 24, 2026 — May 23, 2026

🎁 Prize Pool: $2,000 USDT
🏆 100% Win Rate

Rewards

• 🥇 First Prize: 300 USDT*1 (still unclaimed)
• 🥈 Second Prize: 200 USDT*2 (still unclaimed)

How to Participate

• Install the DataDID browser extension
  (First 10,000 users instantly receive 200 points)
• Register a DataDID account
  (Receive one exclusive mystery box draw)
• Invite friends
  (Each successful referral earns one additional draw opportunity — unlimited)

The top prizes are still waiting to be claimed.

👉 Join the event now:https://datadidapp.memolabs.net/

Conclusion: Every Step You Take Becomes Part of Your Accumulation

Let’s recap what you can do inside DataDID:

• Check in daily and accumulate points
• Install the extension and turn tweets into on-chain assets
• Use AppsList applications and continue earning
• Expand OpenClaw with Skills and unlock more AI capabilities
• Complete tasks and events for both points and cash rewards
• Publish apps or Skills as a developer and contribute directly to the ecosystem

DataDID is an ecosystem where every step forward becomes part of your accumulation.

Points are the most visible reward — but more importantly:

Every interaction helps build a truly personal on-chain data identity.

And over time, that identity becomes increasingly complete — and increasingly valuable.

Now is the best time to start.

👉 Register for DataDID:https://datadid.memolabs.net/

In today’s internet environment, we generate content every day—tweets, opinions, discussions, and ideas. Yet most of this content remains confined within platforms, essentially becoming part of the platforms’ data assets.

DataDID offers a new possibility: turning your content into something that truly belongs to you.

This article will walk you through the entire process of minting a tweet—from installing the plugin to generating an on-chain asset—and explain why this is something worth engaging with over the long term.

I. What is DataDID?

DataDID is a decentralized data identity system available across web, mobile, and browser plugin versions. The plugin version allows users to mint their content on X (Twitter) into on-chain data assets.

In other words, it changes one fundamental thing:

your content is no longer just “published”—it can be “owned.”

II. Tweet Minting Process

Install the Plugin

First, open the Chrome Web Store and search for DataDID,

or go to the official DataDID website 👉 datadidapp.memolabs.net to install it.Once you find the plugin, click “Add to Chrome” to complete the installation, and follow the prompts to grant permissions.

After installation, open the plugin to begin the initialization process.

search for【DataDID】

【Add to Chrome】

【Add extension】

2.  Login and Account Binding

Before getting started, you’ll need to complete the basic account setup:

● Log in using an Ethereum wallet

● Enter an invitation code

● Link your X (Twitter) account

The purpose of this step is to connect your on-chain identity with your social account, preparing for the minting process that follows.

【Bind Invite code】

【link X】

3.  Select a Tweet and Execute Mint

Go to your X homepage and find the tweet you want to mint.

At this point, the DataDID plugin will provide a Mint entry within the reply box.Click the Mint button and confirm the action in the pop-up interface to complete the process.

The entire process is very lightweight and usually takes only a few seconds.

4.  Mint Success and Asset Creation

Once the process is complete, you’ll see a confirmation indicating that the mint was successful.

This means the tweet has been transformed from “platform content” into an “on-chain asset,” and is now linked to your wallet address.

What Happens After Minting?

When you click Mint, three things essentially happen:

The tweet is transformed into an on-chain data asset

The data is permanently recorded and anchored on the blockchain

Ownership of the asset is assigned to you

This process is based on the ERC-7829 data asset protocol proposed by the MEMO network.

Unlike traditional NFT standards, ERC-7829 is specifically designed for “data,” enabling various types of digital content—including tweets, documents, AI interaction records, and knowledge bases—to be packaged as assets with verifiable ownership and transferability.Simply put, it makes data ownership possible.

Why Is This Worth Doing?

In the traditional internet:

You publish content, but don’t truly own it

The value of your content is determined by platforms

Your data is difficult to accumulate into long-term assets

Through minting:

Your content becomes your own asset

Ownership can be verified on-chain

Content can circulate on data marketplaces and generate value

All minted data is stored on the MEMO network and can later be displayed, managed, and even traded on data asset platforms.

This means every time you express something, it’s no longer just “posted”—it becomes something you can accumulate.

Final Thoughts

Minting a tweet may seem like a simple action, but it represents a broader shift:

from being a content publisher to becoming a content owner.As the trend of data assetization continues to evolve, tools like this are reshaping our relationship with the internet. In the future, participating in content creation may not just be about sharing ideas—it may be about building your own data assets.

Visit the DataDID official website to download the browser plugin. After installation, log in to your DataDID account to access all features:👉datadidapp.memolabs.net

The story of DataDID isn’t finished yet.

Following the official launch of the AppsList marketplace, the next key piece of the DataDID ecosystem has arrived.

SkillsList — a decentralized Skill plugin platform built specifically for OpenClaw — is now live.

If AppsList opened up the world of applications, then SkillsList opens up the marketplace of capabilities.

What Is SkillsList?

Simply put, SkillsList is a platform for discovering, installing, and publishing Skill plugins, designed for both OpenClaw users and developers.

For users, you can freely browse a wide range of Skill plugins, find the capability modules that fit your needs, and install them with one click — instantly enhancing your OpenClaw. What your Agent can do is now entirely up to you.

👉 Get started: https://datadid.memolabs.net/

For developers, you can upload the Skills you’ve built to the developer platform. Once approved, they will be featured on SkillsList, giving you access to real OpenClaw users and allowing your work to generate real value.

👉 Publish your Skill: https://datadid-developer.memolabs.net/

But what truly sets SkillsList apart is this:

It’s built on DataDID — and is decentralized by design.

What Makes SkillsList Different?

1. Decentralized — Your Data Truly Belongs to You

On traditional Skill platforms, plugin data and user behavior data are stored on centralized servers. Platforms can remove plugins or ban accounts at any time. A developer’s work can disappear overnight, and user activity records can be deleted or sold without notice.

SkillsList is built on the MEMO decentralized network, with plugin data stored on-chain. No single party can interfere.

Your Skill is always there — permanently.

2. Unified DID Identity — Seamless Access

Your DataDID identity is your passport across the MEMO ecosystem.

There’s no need for additional registration when entering SkillsList. The Skills you install and the capabilities you use are all tied to your DID, enabling cross-application interoperability and unified management of identity and data.

3. Developer Ownership — Revenue Guaranteed

On SkillsList, the Skills you upload belong to you.

Revenue distribution is enforced by smart contracts. The platform cannot arbitrarily change revenue splits or remove your work.

Your creations are protected at the protocol level — not by platform policies.

This is the core promise SkillsList makes to every developer.

4. Deep Integration with the Points System

SkillsList is fully integrated with the DataDID points system.

Users earn points by installing and using Skills, while developers receive ecosystem incentives as their Skills gain adoption.

Every interaction generates real value, creating a positive feedback loop between users, developers, and the ecosystem.

5. Native Fit for AI Agents

SkillsList is designed around expanding OpenClaw’s AI Agent capabilities.

Each Skill plugin directly adds a new capability module to your Agent. Combined with MEMO’s native memory layer, MEFS, any data generated during Skill usage can be permanently stored and accessed at any time.

Your Agent doesn’t just use tools — it remembers context.

6. Seamless Integration with MEFS MCP

Skills in SkillsList can be used seamlessly with MEMO’s official MEFS MCP.

This means every Skill comes with built-in decentralized storage capabilities. Developers don’t need to build their own storage layer — they can directly leverage MEMO’s infrastructure.

What Does This Mean for Users?

In the past, what your Agent could do depended on what the platform allowed.

Now, what your Agent can do depends on what you choose to install.

SkillsList returns the power of capability selection back to users.

Need stronger data processing? Find it on SkillsList.
Want smarter content generation tools? Install them on SkillsList.

The limits of your Agent are now defined by you.

More importantly, early users will gain access to the full range of ecosystem benefits:

• Points incentives
• Ecosystem rewards
• Early access to high-quality Skills

These advantages belong to those who join early.

What Does This Mean for Developers?

If you’ve been looking for a truly developer-owned Skill distribution platform, SkillsList is your answer.

You don’t need to worry about shifting platform policies.
You don’t need to worry about your work being removed without reason.
You don’t need to build complex storage infrastructure yourself.

With MEFS MCP, your Skills come with built-in storage capabilities.
With DataDID’s user base, your application reaches real users.
With smart contracts, every dollar you earn is transparent and guaranteed.

You focus on building great Skills.
The MEMO ecosystem handles the rest.

What’s Next: Secure Your Position Early

SkillsList is now live and ready to explore.

Right now, there’s just one thing you need to do:

Register for DataDID and enter the ecosystem.

DataDID is your identity gateway into the entire MEMO ecosystem. Once registered, you can immediately install Skills or publish your own.

Developers can start submitting Skills today — once approved, they will be listed directly on SkillsList.

The DataDID ecosystem is being built layer by layer.

AppsList was the first step.
SkillsList is the second.

And this is just the beginning.

👉 Users: Browse & install Skills
https://datadid.memolabs.net/

👉 Developers: Publish your Skills
https://datadid-developer.memolabs.net/

There is a question that, after 30 years of the internet, is finally being taken seriously:

Who does data actually belong to?

This question has been set aside for so long not because there is no answer, but because the answer is inconvenient for too many parties. Platforms need data to sustain their business models, advertisers need data for precise targeting, and AI companies need data to train models. Across this entire value chain, the original creators of data — ordinary users — have always been at the very end, contributing the most while receiving the least.

But now, technological evolution is fundamentally changing this dynamic.

1. The 30-Year Data Paradox

The first era of the internet solved the problem of information distribution. Anyone could publish content and make it visible to the world. This was an unprecedented form of empowerment.

The second era of the internet solved the problem of connection. Social networks, e-commerce platforms, and search engines connected billions of people into a single network. Traffic became the most important resource, and attention became the scarcest commodity.

But in the process, something quietly happened: user data became systematically concentrated in the hands of a few platforms.

What you searched for, what you expressed on social media, what you purchased on e-commerce platforms — this data has been collected, analyzed, sold, used to train models, used to predict behavior, and used to influence decisions. And all of this usually happened without your knowledge, and without asking for your consent.

The deeper paradox is this: the value of data comes from its accumulation and circulation, yet in the current system, the benefits generated from that accumulation and circulation flow almost entirely to intermediary platforms, rather than to the original source of the data — the individual.

This is a systemic unfairness that has persisted for 30 years.

2. The AI Era Makes This Issue More Urgent

If over the past 30 years the data issue was background noise, the arrival of the AI era has made it a central issue that must be addressed head-on.

The reason is simple: AI’s demand for data is unprecedented.

The capabilities of large language models depend, to a large extent, on the quality and scale of their training data. Every article, every conversation, every accumulation of knowledge can become part of a model’s capabilities. This means that every digital trace left by humanity over decades now carries greater economic value than ever before.

At the same time, a structural contradiction has become more pronounced: data creates enormous value for AI, yet that value is captured by a small number of AI companies, with no mechanism for the original contributors of the data to share in that value.

Furthermore, as AI agents begin to act on behalf of humans — automatically completing tasks, executing transactions, and generating content — the questions of data origin, quality, and ownership become critically important. If the data used by an AI agent has unclear provenance or ownership, then its actions lack a trustworthy foundation.

The issue of data sovereignty has never been so closely tied to everyone’s real interests.

3. Three New Shifts Are Quietly Emerging

Over the past two years, discussions around data assetization have begun shifting from conceptual debates to infrastructure development. Three notable changes are emerging:

First, data is being viewed as an asset, not just a raw input.

In the past, data was defined as a production input — a raw material that drives economic activity. But the defining feature of raw materials is that once they are used, the value transfers to the user, and the original owner no longer benefits.

Now, with the maturation of blockchain technology, data is being redefined as an asset that can be owned, priced, and circulated repeatedly. The fundamental difference between an asset and a raw input is that ownership of an asset is persistent, and the value it generates can continuously flow back to its owner.

This shift in understanding is giving rise to entirely new models of the data economy.

Second, verifiability is becoming a core component of data value.

In an era flooded with AI-generated content, the value of a piece of data increasingly depends on whether it can be verified: where it comes from, whether it has been tampered with during circulation, and whether its usage history is clearly traceable.

Data without verifiability carries a high trust cost in high-value scenarios. Blockchain’s immutable records and timestamps naturally provide this verifiability, enabling a complete lifecycle record for each piece of data — from creation to circulation, with every step traceable.

Third, data ownership is shifting from platforms to individuals.

This trend is still in its early stages, but the signals are clear. Users are becoming aware of the value of their data, regulators are paying closer attention to data ownership, and technological tools are beginning to offer better support.

Real change will not come from platforms voluntarily giving up control — that is unrealistic. It will come from a redesign at the architectural level. When data storage, ownership, and circulation occur within on-chain protocols directly controlled by users, platforms lose the ability to unilaterally determine the fate of data.

4. Four Key Dimensions of Data Assetization

For data to truly become an asset rather than remain a concept, capabilities must be established across four dimensions:

Ownership: Data must have clear attribution.

The prerequisite for any asset is clear property rights. The first step in data assetization is to establish on-chain ownership records for each piece of data — who created it, when it was created, and what modifications it has undergone. This information must be permanently anchored in immutable infrastructure.

Only once ownership is established does everything else become meaningful. Data with unclear ownership cannot circulate in markets or generate returns for its original creator.

Circulation: Data needs a trusted marketplace.

After ownership is established, data must be able to circulate freely. This requires a transparent and efficient marketplace where buyers and sellers can discover each other, complete transactions, and settle through smart contracts.

However, there is a subtle balance: data circulation must occur while protecting privacy. Buyers need to verify the quality and provenance of data, but they do not necessarily need access to all raw information. This “usable but not visible” requirement is driving innovation in data trading models.

Revenue: The value generated by data should return to its creators.

This is the core proposition of data assetization. When your data is used — whether for AI training, research, or enterprise decision-making — you should receive corresponding returns.

This requires the automated execution capabilities of smart contracts. Each use of data can trigger a payment to the original creator, making the process automatic, transparent, and free of intermediaries.

Protection: Data assets require reliable security mechanisms.

Like any other type of asset, data assets need protection. This includes not only preventing hacking but also avoiding permanent loss due to unforeseen circumstances.

In this regard, decentralized storage offers greater reliability than centralized servers. Data is distributed across multiple nodes, eliminating single points of failure. At the same time, account recovery mechanisms are an essential part of the data asset security system.

5. The Historic Convergence of Two Technology Curves

The reason this moment represents a critical window for data assetization is that two technological trajectories — long evolving independently — are now converging in unprecedented ways.

One is the AI curve. AI is evolving from a tool into an agent, from answering questions to acting on behalf of humans. In this process, the demand for high-quality, traceable, and clearly owned data is growing exponentially.

The other is the blockchain curve. Blockchain is evolving from a carrier of speculative assets into infrastructure for identity, payments, permissions, and auditing. Its capabilities — immutable records, automated contracts, and decentralized trust — are exactly what data assetization requires.

The convergence of these two curves creates a new possibility: data can become a true asset, rather than just a passive production input.

6. The Evolution Path Over the Next Three Years

If this direction holds, the evolution path over the next three years is relatively clear:

Short term (1–2 years): ownership infrastructure matures first.

The first step in data assetization is to establish clear on-chain ownership records. Relevant standards, tools, and platforms will mature first, allowing users to easily turn their data into assets. This is the direction closest to real demand and with the least technical friction.

Medium term (2–3 years): data marketplaces become active.

As ownership infrastructure matures, data marketplaces will begin to see real activity. AI companies, research institutions, and enterprises will become the primary sources of demand, while individuals and organizations become the main suppliers. Pricing mechanisms will gradually emerge through market interaction.

Long term (3+ years): the data economy becomes a core part of the internet.

Once data ownership and trading become foundational capabilities, a complete data economy will gradually take shape. Users will no longer be just consumers of internet content, but participants in — and beneficiaries of — the data economy.

7. Conclusion: The Second Data Revolution

The first revolution of the internet solved the problem of information distribution. It allowed content to flow freely and gave everyone a voice.

The second data revolution will solve the problem of value ownership. Data will no longer exist merely as numbers on platform balance sheets, but will return to each real creator as an asset that can be owned, protected, traded, and monetized.

This revolution will not happen dramatically. It is quietly reshaping the logic of data ownership through the establishment of technical standards, the creation of data marketplaces, and the adoption of ownership tools.

When all of this becomes reality, one truth will be self-evident:

The data you create should work for you.

In the Web3 era, data sovereignty returns to the individual. Every on-chain identity is your passport in the decentralized world.

DataDID is a decentralized identity (DID) platform built by MEMO, dedicated to giving every user true ownership of their Web3 digital identity and digital assets.

Today, we're attaching a surprise gift package worth $2,000 USDT + massive points to your identity activation journey.

The DataDID Mystery Box Season is officially live.Register to draw, invite friends for unlimited chances — and 100% win rate, no empty boxes.

II. How to Play: Clear Participation Steps

Step 1: Complete registration and create your unique DID identity

No matter which platform you use to register your MEMO DataDID account, once you complete DID creation you instantly receive 1 exclusive Mystery Box draw:

● Web: Wallet registration → Complete DID creation

● H5: Email registration → Complete DID creation

● TG / Pi: First login and complete DID creation

The whole process takes under 5 minutes — no prior experience needed.

Step 2: Visit the website or install the plugin

👉 Web: https://datadidapp.memolabs.net/

👉 H5: https://datadid.memolabs.net/home

Install the DataDID browser extension and connect your wallet for the first time — instantly receive 1 exclusive Mystery Box draw.

Special bonus 🎁: The first 10,000 users to install the plugin and connect their wallet receive an extra 200 DataDID points on the spot.

👉https://chromewebstore.google.com/detail/datadid/mklejljmlgjnknaodkikbmcbpbmabdfo?hl=zh-CN&utm_source=ext_sidebar

Step 3: Share your exclusive referral code

This is the most exciting mechanic of the campaign.

Every time a new user installs the plugin and binds your referral code, you earn 1 additional Mystery Box draw — with no cap. In theory, the wider your network, the more draws you accumulate, and the higher your odds of winning a big prize.

In Web3, action is your competitive edge.

Your DID identity is waiting to be activated. Your Mystery Box is waiting to be opened.

III. Full Prize Breakdown: From 100 Points to 300 USDT

The Mystery Box prize pool is divided into two categories: USDT cash rewards and DataDID points rewards — 100% win rate guaranteed.

USDT Cash Rewards:

● 1st Prize: 300 USDT — 1 winner

● 2nd Prize: 200 USDT — 2 winners

● 3rd Prize: 100 USDT — 3 winners

● Lucky Prize: 20 USDT — 50 winners

Points Rewards:

● 1st Prize: 1,000 points — 300 winners

● 2nd Prize: 500 points — 3,000 winners

● 3rd Prize: 200 points — 60,000 winners

● Lucky Prize: 100 points — unlimited winners

Even if you haven't referred anyone, simply log in and stay active daily — 100 points are waiting for you.

IV. Points Are More Than Points — They're Tied to the $MEMO

There's one thing worth emphasizing: the DataDID points you earn are far more than just a number.

MEMO is building an AI-powered decentralized data network with data sovereignty at its core, and points are the engine of value flow across the entire ecosystem. The DataDID points system serves as the recognition mechanism for early ecosystem contributors, and will directly influence future $MEMO airdrop allocations.

In other words: every point you earn today is a key credential for your future $MEMO airdrop.

How to Claim a Major Prize — USDT Winner Verification Process

To ensure prizes go to genuine community contributors, USDT winners must complete three verification steps:

1.  Twitter interaction: Quote-retweet the official campaign post with hashtags #DataDID #MemoLabs

2.  Screenshot proof: Attach a screenshot of your winning screen and your created DID in the tweet

3.  DM confirmation: Message @MemoLabsOrg within 7 days to confirm your prize wallet address

The process is transparent and publicly verifiable.

Join now → https://datadidapp.memolabs.net/

Campaign dates: April 24 – May 23, 2026

Follow @MemoLabs for campaign updates and winner announcements.

Data is one of the most valuable resources of our time.

For over thirty years, the internet has operated on a simple, unchanging reality:

The data you generate every day — the content you write, the files you upload, every digital trace you leave behind — has always been working for someone else.

Platforms use it to train models.
Advertisers use it for precision targeting.
Companies use it to analyze markets.

This data creates enormous value — yet you’re rarely the one who benefits.
You’re simply the supplier of raw material.

We believe that’s fundamentally wrong.

That’s why we’re introducing the MEMO Data Asset Platform — built to change this paradigm.

This platform creates a complete data economy loop — from uploading and minting to management and trading — enabling every user to truly own, manage, and monetize their data.

From Data to Assets: A Complete Lifecycle

Upload & Mint

Once users upload their data to the platform, they can mint it into on-chain data assets using MEMO’s ERC-7829 Data Asset NFT Standard.

ERC-7829 is designed specifically for data assetization. It allows various types of digital content — including:

• Documents
• Images
• AI interaction records
• Datasets
• And more

to be packaged as verifiable, tradable, and transferable on-chain assets.

After minting, ownership of the data is permanently recorded on-chain — transparent, immutable, and verifiable.

From the moment your data is uploaded, it truly belongs to you.

Manage & Share

Once minted, your data assets are displayed in a unified management dashboard, where you can view and manage all of your assets with full flexibility.

If you’d like to share specific data with someone, you can grant access directly from the management page. You control:

• Who gets access
• What level of access they receive
• How long permissions remain active

The platform does not interfere with any authorization decisions.

If you’d prefer broader distribution, you can also list your data in the Data Marketplace, where users, enterprises, and AI developers can discover and purchase your data — generating ongoing returns.

Trade & Monetize

The Data Marketplace serves as the core engine of the platform.

Data assets listed in the marketplace can be freely traded. Transactions are settled through on-chain smart contracts, ensuring:

• Transparency
• Traceability
• Trustless settlement

Each time your data is traded, revenue automatically flows back to the original owner.

This creates a truly user-driven data economy:

• No middlemen
• No platform extraction
• No hidden fees

The value of data returns to the people who create it.

Your Dedicated DID: Identity Across the MEMO Ecosystem

Every user on the Data Asset Platform will receive a dedicated DID (Decentralized Identifier) fully integrated into the MEMO ecosystem.

This DID is more than just an account — it’s your unified identity across MEMO.

It connects:

• Your data assets
• Transaction history
• Permissions and authorizations
• Activity across the ecosystem

Whether you’re using the Data Asset Platform, DataDID, or other MEMO ecosystem products, everything is unified under one identity.

One identity. One ecosystem.

Domain Service: Your On-Chain Name

After registering your DID, you’ll also be able to apply for your own on-chain domain name.

Your domain will be bound to your DID, providing a more readable and recognizable identity across the MEMO ecosystem.

More domain-related features and utilities will be revealed following the official platform launch — stay tuned.

What Does the Data Asset Platform Mean?

In the past, discussions around data sovereignty were largely theoretical.

But data is fundamentally a form of creation.

When you write an article, compile a dataset, or document an experience, you invest time, knowledge, and creativity. These outputs deserve:

• Ownership
• Protection
• Liquidity
• Economic value

Now, the MEMO Data Asset Platform gives this vision a concrete form.

You can:

• Upload data
• Mint assets
• Manage permissions
• Enter the marketplace
• Earn revenue

Fully on-chain.
Fully transparent.
Fully under your control.

The era of the data economy is arriving.

And this time — you won’t just be an observer.

The platform is launching soon.
Stay tuned to official MEMO channels for more details.

DataDID just shipped its biggest update yet: a browser extension that brings daily check-ins, point collection, and on-chain data ownership directly into your everyday browsing.

This isn’t just a shortcut for signing in. It lets you check in, earn points, and permanently mint your tweets as on-chain data assets — all without ever leaving Twitter.

What the extension does

Feature 01

Check in from anywhere, earn points instantly

Once installed, you no longer need to open the DataDID web app to complete your daily check-in. Do it right from the browser toolbar and watch the points land in your account. Everything you can do on the web version is supported here — just faster and more seamless.

For existing DataDID users, this is the check-in button moving into your browser for good. No more tab-switching, no more forgetting.

Feature 02

Mint your tweets as data assets

This is the headline feature. After installing the DataDID extension, a Mint button appears at the bottom of your own tweets as you browse Twitter. Click it, and that tweet is cast onto the blockchain — permanently anchored, permanently yours.

This is powered by ERC-7829, a new NFT standard specifically designed for data assets. It lets you wrap all kinds of digital content — tweets, documents, AI chat logs, knowledge bases — into tradable, transferable on-chain assets. In plain terms: it gives your data ownership. Your content can be verified, priced, and exchanged.

Every tweet you’ve ever posted was traffic and data for the platform. With this extension, it becomes a digital asset with your name on it — one whose value you define and whose ownership you control.

Feature 03

GoData button — earn points just by tweeting

The extension adds a GoData button in two places on Twitter, so you can rack up DataDID points as a natural side-effect of using the platform.

In the tweet composer: A GoData button appears at the bottom of the tweet box. Click it, and the extension auto-generates a tweet related to the MEMO ecosystem. Confirm and post — points credited.

Below the reply box: The same button appears under any reply field. Click it, get a pre-written MEMO-related reply, send it, and earn more points.

This opens up a much broader funnel for accumulating points — beyond daily check-ins, every piece of content you share and every interaction you make can become a point-earning event. Early adopters can compound that advantage over time.

Why this matters

The DataDID browser extension turns the ecosystem from something you have to actively go use into something that’s woven into your daily routine.

You don’t have to change a single habit. Open Twitter, browse your feed, post content, reply to people — everything you already do, now simultaneously checking you in, earning you points, and minting your data.

More importantly, ERC-7829 gives all of this a deeper layer of meaning. The content you create on the internet is no longer just data that belongs to the platform. It becomes a verifiable, transferable, potentially monetizable digital asset.

In the near future, these data assets will be tradable on dedicated data asset marketplaces, creating tangible real-world value for their creators.

This is what Web3 data sovereignty actually looks like in practice — not in a whitepaper, but inside the browser you use every day.

How to install

Head to the DataDID Chrome Web Store listing, install the extension, and log in with your DataDID account. All features activate immediately.

Install the DataDID Browser Extension Get it on Chrome Web Store →

Building a Web3 application is no longer the hardest part; the real challenge lies in what comes next — securing users, establishing an identity framework, and creating incentive structures. For almost every Web3 developer, “cold starting” is the first major wall they hit.

The launch of the DataDID Developer Platform is designed to help you scale that wall.

What is Applist?

Applist is the application hub within the DataDID ecosystem. Here, DataDID users can discover, browse, and directly interact with a variety of Web3 applications.

The beauty of Applist is its native integration with the DataDID identity system — users don’t need to register new accounts; they simply log in using their existing DataDID identity.

Today, the developer portal for Applist is officially live. You can now submit your applications to the DataDID Developer Platform. Once approved by the MEMO official team, your app will be listed on Applist and opened to the entire DataDID user base.

Why Build on DataDID?

● Instant Access to Hundreds of Thousands of Real Users: DataDID has already amassed a massive registered user base that continues to grow daily. Once your app hits Applist, these users can find and use it immediately without you needing to spend resources on a cold start.

● Seamless Integration with DataDID Identity: Every DataDID user has their own on-chain identity. By integrating, you allow users to log in instantly via email verification or MetaMask — no new accounts or passwords required.

● Decentralized Storage via MEMO: Your application data can be integrated into the MEMO decentralized storage network. Data is distributed across multiple nodes, ensuring it is secure, reliable, and immune to tampering by any centralized entity.

● Integrated Incentive System: Users generate points through your app that are synchronized with the overall DataDID points system and ultimately linked to the $MEMO token. This incentive drives higher retention as users accumulate assets while using your application.

Getting Started: How to Upload Your App

The process is divided into two phases: Development Integration and Submission.

Phase 1: Development Integration

● Step 1: Register for Developer Permissions: Visit datadid.memolabs.net to create a DataDID account, verify your email, and bind your EVM wallet to gain developer access.

● Step 2: Install the SDK: DataDID offers SDKs for JavaScript, TypeScript, and Python. We recommend developing and debugging in the testnet environment first.

● Step 3: Integrate User Login: The SDK supports both email verification and MetaMask signature logins, managing user tokens automatically.

● Step 4: Create DIDs for Users: You can call the SDK to generate a unique on-chain Decentralized Identifier (DID) for users. This process is free for the user as the server covers the gas fees.

Phase 2: Submission and Listing

Once your app is ready and verified on the testnet, submit it for review via the developer dashboard. You will need to provide the app name, description, production URL, and a link to your privacy policy. After the MEMO team completes the audit, your app will officially appear on Applist.

Join Us Today

In Web3, the hardest part isn’t the build — it’s the start.

The DataDID Developer Platform has already prepared the user base, identity framework, storage, and incentive mechanisms for you. All you need to do is plug in.

A thriving ecosystem is growing, and we’re waiting for you to build it with us.

👉 Developer Portal:DataDID Developer Platform

Great news: DataDID now supports automated daily check-ins through OpenClaw.

Once you install the datadid-checkin Skill, your DataDID daily check-in, AliveCheck daily check-in, and point collection can all be handled automatically by OpenClaw. Set it up once, and you’re done — no more manual check-ins every day.

What Does This Skill Do?

datadid-checkin is an OpenClaw Skill built specifically for DataDID users. Once installed and configured, it automatically handles the following three tasks:

DataDID Daily Check-In: Automatically completes the DataDID platform check-in every day. Points are credited in real time — no need to manually open the page.

AliveCheck Daily Check-In: AliveCheck is DataDID’s built-in digital life guardian module that relies on daily check-ins to stay active. With this Skill, AliveCheck check-ins are also automated — keeping your guardian status uninterrupted.

Automatic Point Accumulation: Points from both check-in tasks are automatically added to your account. Early participants can maintain their point advantage without worrying about missed check-ins causing a drop in rankings.

Installation & Setup

Step 1: Install the Skill

Search for datadid-checkin in the ClawHub marketplace and install it, or download it directly from the link below:

👉 https://skillhub.memolabs.net/q-hp-true/datadid-checkin

You can also type the following command in the OpenClaw chat box, and OpenClaw will handle the installation automatically:

Install this Skill for me: datadid-checkin — ClawHub

Step 2: Complete Login Verification

After installation, you’ll need to complete a one-time email login verification for your DataDID account. Once done, your credentials are saved locally, and you won’t need to verify again.

Check Your Current Login Status

Run the following command in the OpenClaw terminal to check if you’re already logged in:

python /home/admin/clawd/skills/datadid-checkin/scripts/token_helper.py check

Review the output:

• If it shows Logged in or your email address: you’re already logged in. Skip ahead to Step 3.

• If it shows Not logged in or returns an error: you’re not logged in yet. Continue with the steps below.

💡 If this is your first time setting up this Skill, the check will typically return “not logged in.” Feel free to skip the check and follow the steps below in order.

Send the Verification Code

Enter your DataDID registered email address in the terminal. The system will send a 6-digit verification code to that email.

Enter the Verification Code to Log In

Open your inbox, find the verification email, enter the 6-digit code in the terminal, and press Enter to complete login.

Step 3: Run Your Check-In

Once login is complete, type any of the following commands in the OpenClaw chat box to trigger a check-in:

Check in on DataDID

or

Check in on AliveCheck

OpenClaw will automatically invoke the datadid-checkin Skill, complete the check-in for the corresponding platform, and return the result.

Once you’ve completed the setup, all you need to do each day is give OpenClaw the check-in command — it handles the rest. The whole process goes from “manually opening the page every day” to “a single command,” dramatically cutting down on your daily time commitment.

Don’t Have OpenClaw Yet?

The datadid-checkin Skill requires the OpenClaw environment to run. If you haven’t installed OpenClaw yet, you can still check in manually on the DataDID platform — your points will accumulate just the same.

If you’d like to take advantage of the automated check-in feature, check out MEMO’s official OpenClaw installation guide for a step-by-step walkthrough of the local deployment process. Once installed, follow the steps in this article to configure the datadid-checkin Skill and start automating your check-ins.

👉 OpenClaw Setup Guide: OpenClaw Setup + MEMO MEFS Agent Service: Complete Usage Guide

I. Prerequisites

Setting Up Your Environment

To run the MEFS MCP Server on Windows, you’ll need to install two foundational tools: Node.js (the JavaScript runtime) and Git (for downloading the source code).

Install Node.js:

Visit Node.js — Node.js 24.14.1 (LTS).

Select the appropriate version, download it, and run the installer. Keep all default options and click “Next” through each screen to complete the installation.

Install Git:

Visit Git — Install for Windows.

Download the Windows version and install it.

Verify the Installation:

Press Win + R, type cmd, and press Enter to open a Command Prompt.

Run node -v and git — version. If both commands return version numbers, the installations were successful.

II. Installing and Setting Up the OpenClaw Runtime

1. Click the Windows Start menu, search for Windows PowerShell, and open it.

2. Download and install the OpenClaw runtime

Run this command: iwr -useb https://openclaw.ai/install.ps1 | iex

Note: Installation takes approximately 10 minutes. The terminal will display “Installing OpenClaw” throughout the process — please be patient and do not close the window.

3.When you see the prompt “I understand this is personal-by-default and shared/multi-user use requires lock-down. Continue?”:

l Use the Up/Down arrow keys (↑ / ↓).

l Move the cursor to Yes (the confirmation option, typically listed above “No”).

l Press Enter.

4. When the startup mode selection screen appears, choose “Quick Start”.

5. Select the AI model you want to use from the list.

6. Enter the API key for your selected model.

You can skip all remaining options.

Configure Skills: We recommend selecting “No” here — it’s much easier to install Skills from the web interface later.

Note: The only required configuration is the API key

III. Install MEFS MCP Server

Open a new Windows PowerShell window.

1. Clone the repository

Run: git clone https://github.com/memoio/mefs-mcp-server.git

2. Navigate into the directory

Run: cd mefs-mcp-server

3. Install dependencies

Run: pnpm install

4. Build the project

Run: pnpm build

IV. Start the server

Have your EVM private key (without the 0x prefix) ready, then run the following in the current window:

$env:MEFS_PRIVATE_KEY=”your_private_key”; $env:PORT=8085; $env:MCP_TRANSPORT_MODE=”sse”; node dist/index.js

Success indicator：: you should see MCP SSE Server running on http://0.0.0.0:8085/sse.

V. Putting It to Work

Once the service is running, open your browser and navigate to the token-authenticated URL shown in the terminal. You can then issue instructions directly to the AI Agent in the chat window.

Over the past two years, one saying about AI has been repeated over and over:

The most important skill in the future is the ability to ask questions.

That is certainly true.

The more precise your questions and the more specific your needs, the closer AI’s output will usually be to your goal.

That’s why everyone has been learning prompts these past two years—learning to clarify vague demands, to make AI better understand their intentions.

But today, knowing how to ask questions is no longer rare.

Open any content platform, and you’ll find countless prompt templates. People teach you how to use AI to write articles, make plans, revise resumes, draft weekly reports, and take reading notes. Even those who struggle to express themselves now know to throw their ideas at AI first, just to get a draft out.

This means:

“Knowing how to ask” is shifting from an advantage to a basic skill.

It will become like using a search engine—a default in modern work and expression, not a real barrier between people.

What truly sets people apart is no longer who asks better questions.

It is: who thinks one step further after getting the answer.

More directly, it is who knows how to doubt.

The Step AI Most Easily Makes Us Skip Is “Doubt”

Getting information used to be far less convenient.

To understand something, you had to search for materials, read articles, and compare different sources. The process was slow, but it had a natural benefit: while seeking information, people also questioned it. They would naturally wonder if the data was real, if the conclusion was overstated, if the case was an exception.

That has changed.

Now AI hands you a “polished answer” directly.

It’s fast, smooth, and effortless—so effortless that people easily skip the most critical step: doubt.

This is the reality for many people using AI today.

Let AI draft a report first; let AI outline a plan first; let AI summarize research first. None of these actions are inherently wrong.

The real problem is that many people stop at “just getting a draft”.

In other words, AI is treated as the finish line, not the starting point.

The difference is enormous.

Some use AI to save time on basic organization, then focus on judgment and refinement.

Others use AI to skip thinking entirely, just to get something “good enough to submit.” On the surface, both groups use AI.

But over time, the gap widens. The former grow better at judging and knowing where to dig deeper; the latter grow dependent on the illusion: AI already thought this through for me.

The latter is the real danger.

Judgment does not vanish overnight—it is slowly abandoned through repeated “good enough” use of AI.

What You Should Really Doubt Is Not Whether AI Works, but Whether Its Output Is Trustworthy

So what exactly should we doubt?

At least four things deserve special vigilance:

  1. Doubt its stated facts

Be alert whenever answers include specific data, studies, cases, sources, years, or people.

AI excels at fabricating realistic details, and people naturally trust content that looks specific. Many are misled not by opinions, but by these “convincing fake details.”

2. Doubt its logic

Some content is not factually wrong, but logically flawed.

For example, treating two simultaneous phenomena as direct cause and effect, or omitting key premises to reach a smooth conclusion. Often, the issue is not the conclusion itself—but how quickly it arrives.

  3. Doubt overconfident, absolute claims

Most real-world issues cannot be summed up in a single sentence. Judgments come with premises, scopes, and exceptions.

Yet AI naturally organizes answers to look complete and “standard.” Be wary whenever complex issues are explained too neatly.

4. Doubt missing critical information

AI does not always lie, but it often leaves out key details.

When analyzing whether a direction is worth pursuing, it may highlight market size, user demand, and growth trends—but omit execution difficulty, competitive barriers, and practical obstacles. Readers easily assume they have a complete picture.

Many Can Use AI, Few Can “Fact-Check AI”

So how do we practice doubt?

It doesn’t have to be complicated—start with these habits:

First, ask for evidence, not just conclusions

Question where data comes from, the source of cases, whether studies have original texts, and what materials support conclusions. You don’t need to verify everything every time, but keep this awareness.

Second, demand the full reasoning process

Don’t just accept “therefore”—ask “why.” Many flaws become obvious once the logical chain is laid out.

  Third, ask for counterarguments

If you think a judgment is correct, ask for its strongest objections. If you think a direction is promising, ask why it might fail.

Fourth, be extra careful with content that drives decisions

Loose use is fine for inspiration, headlines, phrasing, and frameworks.

But for decisions involving money, public statements, or critical judgments, never treat AI’s first draft as the final conclusion. AI can generate answers, but it cannot take responsibility for the consequences.

AI’s Greatest Strength Is Making You Think You Already Thought

Ultimately, why is the ability to doubt becoming so rare?

Because AI’s biggest temptation is not its power—it’s the thought:

Since AI organized this for me, do I even need to think?

It is incredibly tempting.

And it doesn’t make people lazy overnight—it gently and smoothly erodes the habit of “thinking one layer deeper.”

Over time, more people will get used to asking AI first, then deciding what to think.

Worse, many don’t even realize this is happening.

In 2025, Microsoft Research published a survey analyzing 319 knowledge workers and 936 real-world AI use cases. The study found that the more confidence users had in AI, the less critical thinking they invested; and when people treated AI as a substitute for their own judgment, their cognitive effort decreased.

As more people learn to ask good questions, the truly valuable skill belongs to those who, after reading an answer, automatically ask:

- Is this true?

- What is this based on?

- What is missing?

- What could go wrong if I act on this?

Whoever retains these questions will be less easily led astray in the AI era.

In the End, the Only Thing That Truly Matters Is Doubt

Put plainly:

The most dangerous people in the AI era are not necessarily those who can’t use AI.

They are more likely those who use AI skillfully, but stop judging. People who can’t use AI at least know their limits.

The real risk is people who appear increasingly efficient, produce polished work quickly, but essentially only copy, organize, and polish AI output—without developing their own judgment. Such people feel accomplished in the short term.

In the long run, they risk turning themselves into high-level transshipment hubs. And doubt, like a muscle, grows dull with disuse.

AI can save enormous amounts of time—and that is a good thing.

But never skip that final step.

That step is called doubt.