Comprehensive Interpretation of the InfoFi Ecosystem: Is it an AI-Powered Attention Market or a New Scythe for Playing Retail Investors for Suckers?

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

• Agricultural Revolution: Committed to solving food scarcity issues, but gave rise to land disputes;
• Industrial Revolution: Aimed at solving the problem of land scarcity, but shifted towards resource competition and capital accumulation;
• Digital Revolution: Competing for Attention.

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

Whether it's Labubu's popularity in the trendy toy market or the live-streaming sales by top streamers, they are fundamentally a competition for user and audience 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—through blockchain, token incentives, and AI technology, it aims to make the production, dissemination, and consumption of information transparent, seeking 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, focusing 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.
• The ability to monetize information: transforming abstract 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 with a social media account.
• Innovation of incentive mechanisms: not only rewarding content creation, but also including multiple aspects such as dissemination, interaction, verification, etc., 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 predictive 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 mechanisms that use collective intelligence to forecast the outcomes of future events. Participants express their expectations regarding future events (, such as election or policy outcomes, sports events, economic forecasts, price expectations, product release dates, etc. ) by buying and selling "shares" linked to specific event outcomes, while market prices reflect the collective expectations of the crowd regarding the event outcomes. A certain trading platform is a representative application promoting the InfoFi concept.

Vitalik has always been a staunch supporter of a certain trading platform for 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 these types of markets as information finance ( info finance )." Vitalik also pointed out the dual nature of a certain trading platform: one is a gambling site for participants, and the other is a news site for everyone else.

Under the framework of InfoFi, prediction markets are not merely tools for speculation, but platforms that excavate and reveal real information through financial incentive mechanisms. This mechanism leverages market efficiency, encouraging participants to provide accurate information, as correct predictions yield economic returns, while incorrect predictions may result in losses. Musk himself also retweeted data a month before the 2024 U.S. election stating "Trump leads with a 51% approval rate on a certain trading platform" and commented: "Due to the involvement of real financial investment, this data is more accurate than traditional polls."

Prediction market platforms include:

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

Mouth Licking Type InfoFi ( Yap-to-Earn )

"Yap-to-Earn" is a colloquial term used in the Chinese crypto community, referring to earning rewards by expressing insights and sharing 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 being assessed for quantity, quality, interaction, and depth through AI algorithms, thereby allocating 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 "嘴撸":

• No on-chain transactions or high capital required, just an X 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 a more transparent reward distribution.
• Points may be converted into token airdrops or ecological privileges, and early participants may receive higher returns.

Current mainstream mouth-play projects or projects that support mouth-play include:

Kaito AI: is a representative platform of Yap-to-Earn, which has collaborated with multiple projects to evaluate the quantity, quality, interactivity, and depth of users' crypto-related content published on X 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 quality content and KOLs through the Yaps system; while project parties achieve the dual goals of precisely reaching target users and expanding brand influence, forming a virtuous ecosystem of win-win for all parties.

Kaito AI has distributed tokens worth over $90 million to various communities, excluding Kaito's own airdrop (, with over 200,000 active Yappers monthly.

Cookie.fun: Cookie tracking AI agents' mindshare ), interaction status, and on-chain data to generate a comprehensive market overview, also tracking the mindshare and sentiment of crypto projects. Cookie Snaps has a built-in rewards and airdrop activity system that offers rewards to Cookie creators who contribute to project attention.

Cookie has partnered with three projects to launch the Snaps event, namely Spark, Sapien, and OpenLedger. Among them, the number of participants in the Spark event exceeded 16,000, while the number of participants in the latter two projects was 7,930 and 6,810 respectively.

Virtuals: Virtuals is not a platform focused on Yap-to-Earn, but rather an AI agent launch platform. However, in mid-April, it launched a new launch mechanism called Genesis Launch on Base. One of the ways to earn points for participation in the launch includes Yap-to-Earn ( supported by Kaito ).

Loud: Loud, as an "attention value experiment" in the Kaito AI ecosystem, occupied more than 70% of the Kaito attention leaderboard through the Yap-to-Earn activity before the official release of the token through the Initial Attention Offering ( at the end of May 2025. The LOUD operating mechanism also revolves around the "attention economy," with the trading fees collected after trading being primarily distributed in SOL to the top 25 users on the attention leaderboard.

Wallchain Quacks: Wallchain is a programmatic AttentionFi project based on Solana, supported by AllianceDAO. Wallchain X Score evaluates the overall influence of users, while Wallchain Quacks rewards high-quality content and valuable interactions. Currently, the Wallchain Quacks customized LLM evaluates creators' content daily, and valuable, insightful content creators will receive Quacks rewards.

) mouth stroking + tasks / on-chain activities / verification: multidimensional contribution value realization

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

Galxe Starboard: Galxe is a Web3 growth platform, and its newly launched Galxe Starboard is dedicated to rewarding real contributions in off-chain and on-chain actions. Projects can define multiple contribution layers, where what matters is not just how many tweets were sent, but the value brought to the entire project, including post engagement, sentiment, virality, interaction with dApps, holding tokens, minting NFTs, or completing on-chain tasks.

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

( Reputation-based InfoFi

Ethos is an on-chain reputation protocol that is entirely based on open protocols and on-chain records, combined with social proof of stake )Social PoS(, generating credibility scores )Credibility Score### through a decentralized mechanism, ensuring the reliability, decentralization, and Sybil attack resistance of its reputation system. Currently, Ethos adopts a strict invitation system. The core function of Ethos is to generate credibility scores, a quantifiable indicator of user trust on-chain. The scoring is based on the following on-chain activities and social interactions: a comment mechanism ( with cumulative utility ), and a guarantee mechanism ( staking Ethereum to endorse other users ).

Ethos also launched a reputation market that allows 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.

GiveRep: Primarily built on Sui, it aims to convert users' social influence and community participation into quantifiable on-chain reputation through their activities on the X platform, and incentivizes user participation through rewards. Commenting and tagging GiveRep's official Twitter under a creator's post allows both the commenter and the creator to earn one reputation point each. To limit abuse, GiveRep restricts this commenting and tagging behavior to no more than 3 times per day, including 3 times (, while creators can receive unlimited points daily. Comments and tags from Sui ecosystem projects and ambassadors will earn additional points.

) Attention Market / Forecast

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

Upside: Upside is a social prediction market ( investors include Arthur Hayes ), rewarding the discovery, sharing, and prediction of valuable content and links, creating a dynamic market through a liking mechanism. Profits are distributed based on ratios.