InfoFi: AI-Powered Attention Market

In 1971, psychologist and economist Herbert Simon first proposed the theory of attention economy, pointing out that in a world of information overload, human attention has become the most scarce resource.

Economist Albert Wenger further reveals a fundamental shift in "The World After Capital": human civilization is undergoing a third leap - from the "scarcity of capital" in the industrial age to the "scarcity of attention" in the knowledge age.

• Agricultural Revolution: Aimed at addressing food scarcity issues, but led to land disputes.
• Industrial Revolution: Aimed at addressing the issue of land scarcity, but shifted towards resource competition and capital accumulation.
• Digital Revolution: Competing for Attention

The underlying driving force of this transformation stems from two key characteristics of digital technology: the zero marginal cost of information replication and dissemination, and the universality of AI computation, but human attention is not replicable.

Whether it's the booming trend of collectible toys or the live-stream selling by top influencers, it is essentially a competition for users' and viewers' attention. However, in the traditional attention economy, users, fans, and consumers contribute their attention as "data fuel," while the excess profits are monopolized by platforms and scalpers. The InfoFi in the Web3 world attempts to disrupt this model — by using blockchain, token incentives, and AI technology to make the production, dissemination, and consumption of information transparent, aiming to return value to the participants.

This article will provide an in-depth introduction to the classification of the InfoFi project, the challenges it faces, and the future development trends.

What is InfoFi?

InfoFi is a combination of Information + Finance, with the core focus on transforming difficult-to-quantify, abstract information into dynamic, quantifiable value carriers. This encompasses not only traditional prediction markets but also the distribution, speculation, or trading of information or abstract concepts such as attention, reputation, on-chain data or intelligence, personal insights, and narrative activity.

The core advantages of InfoFi are reflected in:

• Value Redistribution Mechanism: Return the value monopolized by platforms in the traditional attention economy to the true contributors. Through smart contracts and incentive mechanisms, allow information producers, disseminators, and consumers to share the profits.
• Information Valuation Capability: Transforming abstract concepts such as attention, insights, reputation, and narrative activity into tradable digital assets, creating a trading market for the previously difficult-to-circulate information value.
• Low barrier to entry: Users can participate in value distribution through content creation simply by using their social media accounts.
• Innovation of Incentive Mechanisms: Not only rewarding content creation but also including multiple aspects such as dissemination, interaction, and verification, allowing niche content and long-tail users to also receive rewards. High-quality content receives more rewards, incentivizing the continuous production of high-quality information.
• Cross-domain application potential: For example, the introduction of AI provides advantages such as content quality assessment and market optimization for InfoFi.

InfoFi Classification

InfoFi covers a variety of different application scenarios and models, which can mainly be divided into the following categories:

( prediction market

Prediction markets, as a core component of InfoFi, are a mechanism for forecasting future event outcomes through collective intelligence. Participants express their expectations about future events, such as elections or policy outcomes, sports events, economic forecasts, price expectations, product release dates, etc., by buying and selling "shares" tied to specific event outcomes ). The market price reflects the collective expectations of the crowd regarding the event outcomes. A well-known trading platform is a representative application promoting the InfoFi concept.

The founder of Ethereum has always been a staunch supporter of prediction markets. In his article "From Prediction Markets to Information Finance" published in November 2024, he stated, "Prediction markets have the potential to create better applications in social media, science, news, governance, and other areas. I refer to such markets as information finance ### info finance (." He also pointed out the dual nature of a certain prediction platform: one is a betting site for participants, and the other is a news site for everyone else.

Within the framework of InfoFi, prediction markets are not merely tools for speculation, but platforms that uncover and reveal real information through financial incentives. This mechanism leverages market efficiency and encourages participants to provide accurate information, as correct predictions yield economic rewards while incorrect predictions may lead to losses. Elon Musk himself retweeted data "showing Trump leading with a 51% approval rating on a certain prediction platform" a month before the 2024 U.S. election, commenting: "Because real money is involved, this data is more accurate than traditional polls."

Representative platforms for prediction markets include:

• A certain decentralized prediction market: the largest decentralized prediction market, built on a certain network, using USDC stablecoin as the trading medium. Users can make predictions on events such as political elections, economy, entertainment, and product launches.
• A certain regulated prediction platform: a fully CFTC-regulated prediction market platform in the United States, supports deposits in USDC, BTC, WLD, SOL, XRP, and RLUSD through partnerships with cryptocurrency and stablecoin infrastructure providers, but settles in fiat currency. The platform focuses on event contracts )Event Contracts(, allowing users to trade the outcomes of political, economic, and financial events. Due to regulatory compliance, it has a unique advantage in the U.S. market.

) Mouth Lick Type InfoFi ( Yap-to-Earn )

"Yap-to-Earn" is a colloquial term used in the Chinese crypto community, referring to earning rewards by sharing insights and content. The core concept of Yap-to-Earn is to encourage users to post high-quality, crypto-related posts or comments on social platforms, with most content evaluated through AI algorithms based on quantity, quality, interaction, and depth, in order to allocate points or token rewards. This model differs from traditional on-chain activities ### such as trading or staking (, focusing more on users' contributions and influence within the community.

Characteristics of "Zui Lu":

• No on-chain transactions or large capital required, just a social account is needed to participate.
• Enhance the activity of the project community by rewarding valuable discussions.
• AI algorithms reduce human intervention, filter out bots and low-quality content, ensuring more transparent reward distribution.
• Points may be converted into token airdrops or ecological privileges, early participants may receive higher returns.

The current mainstream mouth-pulling projects or projects that support mouth-pulling include:

An AI platform: It is a representative platform for Yap-to-Earn, which has collaborated with multiple projects to evaluate the quantity, quality, interactivity, and depth of users' crypto-related content posted on social media through AI algorithms, rewarding Yap points for users to compete on the leaderboard to earn token airdrops.

In this way, creators can not only effectively prove their influence and content value through Yaps but also attract precise high-quality attention; ordinary users can efficiently discover high-quality content and KOLs using the Yaps system; while project parties achieve the dual goals of accurately reaching target users and expanding brand influence, forming a virtuous ecological cycle of win-win for all parties.

The platform has distributed tokens worth over $90 million to various communities, excluding its own airdrop ), with more than 200,000 active Yappers each month.

An attention platform: This platform tracks the mindshare ( of AI agents, interaction status, and on-chain data to generate a comprehensive market overview, and also tracks the mindshare and sentiment of crypto projects. A built-in rewards and airdrop activity system provides rewards to creators who contribute to the attention of projects.

The platform has collaborated with three projects to launch activities, namely Spark, Sapien, and OpenLedger. Among them, the number of participants in the Spark activity exceeded 16,000, while the number of participants in the other two projects was 7,930 and 6,810, respectively.

An AI agency platform: It is not specifically a Yap-to-Earn platform, but rather an AI agency launch platform. However, in mid-April, it launched a new launch mechanism called Genesis Launch on Base. One of the ways to earn points to participate in the launch includes Yap-to-Earn ) supported by a certain AI platform (.

A certain attention experiment project: As an "Attention Value Experiment" within a certain AI ecosystem, before the official release of the token through the Initial Attention Offering, abbreviated as IAO), at the end of May 2025, it once occupied more than 70% of the attention leaderboard share through the Yap-to-Earn activity. The operational mechanism of the project is also centered around the "Attention Economy", with transaction fees collected after trading being primarily distributed in SOL to the top 25 users on the attention leaderboard.

A certain blockchain-based attention project: It is a programmatic AttentionFi project based on Solana, supported by a well-known DAO. This project assesses the overall influence of users and rewards high-quality content and valuable interactions. Currently, a custom LLM evaluates creator content daily, and valuable, insightful content creators will be rewarded.

( Mouth Lick + Task/On-Chain Activities/Verification: Multi-Dimensional Contribution Value Realization

Some projects also evaluate users' multidimensional contributions by combining content contributions with on-chain actions such as transactions, staking, NFT minting, or tasks.

A Web3 growth platform: This is a Web3 growth platform that has recently launched a feature aimed at rewarding real contributions in off-chain and on-chain actions. Projects can define multiple contribution tiers, where what's important is not just how many tweets were sent, but the value brought to the entire project, including post engagement, sentiment, viral spread, interaction with dApps, holding tokens, minting NFTs, or completing on-chain tasks, etc.

A decentralized AI model: This model is a decentralized AI model trained on community-selected data, capable of learning from real-time contributions of Web3 users. Specifically, creators publish high-quality content on social media, equivalent to submitting AI validation data; scouts )Scout( identify high-value content on social platforms and mark @MirraTerminal in replies to submit insights, determining what content the AI learns from and helping to shape intelligent AI.

) Reputation InfoFi

A reputation protocol: It is an on-chain reputation protocol, completely based on open protocols and on-chain records, combined with social proof of stake (Social PoS), which generates credibility scores ###Credibility Score( through decentralized mechanisms to ensure the reliability, decentralization, and Sybil attack resistance of its reputation system. Currently, it employs a strict invitation-only system. The core function of the protocol is to generate credibility scores, a quantitative metric of user trust on-chain. The scores are based on the following on-chain activities and social interactions: comment mechanisms ) have cumulative utility (, guarantee mechanisms ) pledge Ethereum to endorse other users ###.

The agreement also launched a reputation market, allowing users to speculate on the reputation of individuals, companies, DAOs, and even AI entities by buying and selling "trust votes" and "distrust votes", essentially going long or short on reputation.

A certain Sui ecosystem reputation project: primarily built on Sui, aims to convert users' social influence and community participation into quantifiable on-chain reputation through their activities on social platforms, and incentivizes user participation through rewards. Commenting on the creator's post by mentioning the official Twitter, both the commenter and the creator receive one reputation point each. To limit abuse, users are restricted to this commenting mention behavior no more than 3 times a day, including 3 times (, while creators can receive unlimited points daily. Comments mentioning from Sui ecosystem projects and ambassadors will earn more points.

) Attention Market/Forecast

Trend Discovery Platform: It is a trend discovery and trading platform based on MegaETH, currently requiring an invitation code to experience. Users can long or short the project's attention.

A social prediction market: is a social prediction market ( investors include a well-known investor ), rewarding the discovery, sharing, and prediction of valuable content and links, creating a dynamic market through a liking mechanism. Earnings are distributed proportionally to voters, creators, and curators. To prevent manipulation of the prediction pool, the weight of likes will decrease in the last 5 minutes of each round.