InfoFi Ecosystem Explained: An AI-Powered Attention Market or a New Scythe for Playing People for Suckers?

Author: KarenZ, Foresight News

In 1971, psychologist and economist Herbert A. 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: Aimed at addressing food scarcity issues, but led to land disputes;
• Industrial Revolution: Aimed at solving the problem of land scarcity, but shifted towards resource competition and capital accumulation;
• Digital Revolution: The Battle 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 is Labubu's popularity in the trendy toy market or the live streaming sales of top influencers, it is essentially a competition for the attention of users and viewers. 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 of the Web3 world attempts to disrupt this model—by utilizing blockchain, token incentives, and AI technology, it aims to make the processes of information production, dissemination, and consumption transparent, and seeks 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 future development trends.

What is InfoFi?

InfoFi is a combination of Information + Finance, with the core focus on transforming hard-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: Returning the value monopolized by platforms in the traditional attention economy to the true contributors. Through smart contracts and incentive mechanisms, allowing information producers, disseminators, and consumers to share the profits.
• Information monetization capability: Transforming abstract attention, insights, reputation, narrative activity, etc. into tradable digital assets, creating a trading market for information value that was previously difficult to circulate.
• Low threshold for participation: Users can participate in value distribution through content creation using only their social media accounts.
• Innovation of incentive mechanisms: not only rewarding content creation, but also including dissemination, interaction, verification, and other aspects, allowing niche content and long-tail users to also receive rewards. High-quality content receives more rewards, encouraging 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 Category

InfoFi covers a variety of different application scenarios and models, which can be mainly 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 election or policy outcomes, sports events, economic forecasts, price expectations, product launch dates, etc.) by buying and selling "shares" linked to specific event outcomes, and market prices reflect the collective expectations of the crowd regarding the event outcomes. Polymarket is a representative application promoting the InfoFi concept.

Vitalik has always been a loyal supporter of the prediction market Polymarket. In his article "From prediction markets to info 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 kinds of markets as info finance." Vitalik also pointed out the dual nature of Polymarket: one is a betting site for participants, and the other is a news site for everyone else.

In the framework of InfoFi, prediction markets are not just tools for speculation, but platforms that uncover 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 lead to losses. Musk himself retweeted the data stating "Trump leads with a 51% approval rating on Polymarket" one month before the 2024 U.S. elections and commented, "Due to the involvement of real monetary investment, this data is more accurate than traditional polls."

The representative platforms for prediction markets include:

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

Mouth Lick Type InfoFi (Yap-to-Earn)

"Zui Lu" is the humorous term used by the Chinese crypto community for Yap-to-Earn, which refers 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, mainly assessing the quantity, quality, interaction, and depth of the content through AI algorithms to allocate points or token rewards. This model differs from traditional on-chain activities (such as trading or staking) and places greater emphasis on users' information contributions and influence within the community.

Characteristics of "Zui Lu":

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

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

Kaito AI: is the representative platform for Yap-to-Earn, having partnered with multiple projects to evaluate the quantity, quality, engagement, 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 demonstrate 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 accurately reaching target users and expanding brand influence, forming a positive ecological cycle of mutual benefit for all parties.

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

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Source:

Cookie.fun: Cookie tracks the mindshare, interactions, and on-chain data of AI agents, generating a comprehensive market overview, and also tracks the mindshare and sentiment of cryptocurrency projects. Cookie Snaps features a built-in rewards and airdrop system that rewards Cookie creators who contribute to project attention.

Cookie has collaborated 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 itself is not a platform focused on Yap-to-Earn, but rather an AI agent launch platform. However, in mid-April, a new launching mechanism called Genesis Launch was introduced on Base, and one of the ways to earn points for participating in the launch includes Yap-to-Earn (supported by Kaito).

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The top AI agency projects with high subscription rates on Virtuals, source:

Loud: As an "Attention Value Experiment" within the Kaito AI ecosystem, Loud occupied more than 70% of the Kaito attention leaderboard through the Yap-to-Earn activity before the official release of its token via the Initial Attention Offering (IAO) at the end of May 2025. The LOUD operating mechanism revolves around the "Attention Economy," and after trading opens, the transaction fees collected will be primarily distributed in the form of 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 assesses the overall influence of users, while Wallchain Quacks rewards high-quality content and valuable interactions. Currently, the Wallchain Quacks customized LLM evaluates creator content daily, and valuable, insightful content creators will receive Quacks rewards.

)# Mouth Lick + Tasks / On-chain Activities / Verification: Multi-dimensional Contribution Value Realization

Some projects also integrate content contribution with on-chain behaviors (such as trading, staking, NFT minting) or tasks to comprehensively assess users' multidimensional contributions.

Galxe Starboard: Galxe is a Web3 growth platform, and its latest launch, Galxe Starboard, is dedicated to rewarding real contributions in off-chain and on-chain actions. Projects can define multiple layers of contribution, 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, token holding, minting NFTs, or completing on-chain tasks.

Mirra: Mirra is a decentralized AI model trained on community-curated data, capable of learning from real-time contributions of Web3 users. Specifically, creators publish high-quality content on X, which is equivalent to submitting AI validation data; scouts 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 Type InfoFi

Ethos is an on-chain reputation protocol, fully based on open protocols and on-chain records, and combines Social Proof of Stake (Social PoS) to generate a Credibility Score through decentralized mechanisms, ensuring the reliability, decentralization, and Sybil attack resistance of its reputation system. Currently, Ethos operates on a strict invitation-only basis. The core function of Ethos is to generate a Credibility Score, a quantifiable indicator of a user's on-chain trustworthiness. The score 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: Mainly built on Sui, aims to transform users' social influence and community participation on the X platform into quantifiable on-chain reputation through their activities, and incentivizes users to participate through rewards. Commenting on the creator's post by mentioning GiveRep's official Twitter will grant both the commenter and the creator one reputation point each. To limit abuse, GiveRep restricts the number of such comment mentions by users to 3 times a day (including 3 times), while creators can receive unlimited points daily. Mentions from Sui ecosystem projects and ambassadors will earn more points.

Attention Market / Prediction

Noise: is a trend discovery and trading platform based on MegaETH, currently requiring an invitation code for access. Users can go long or short on project attention.

Upside: Upside is a social prediction market (investors include Arthur Hayes) that rewards the discovery, sharing, and prediction of valuable content and links, creating a dynamic market through a liking mechanism. Earnings are proportionally distributed 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.

YAPYO: An attention market infrastructure in the Arbitrum ecosystem. YAPYO indicates that the rewards in its coordination mechanism are not just profits, but also lasting influence.

Trends: You can tokenize X posts, becoming a trend on the joint curve called "Trend it." Creators are eligible to receive 20% of the joint curve trading fees for each trend.

Token Gate Content Access: Filtering Noise

Backroom: Creators can launch tokenized spaces offering curated content such as market insights, Alpha, and analysis without the need for management or social pressure; users can unlock low-noise, high-value information by purchasing on-chain Keys tied to each creator's space. Keys are not just for access—they are tradable assets with a demand-driven dynamic pricing curve. At the same time, AI processes chat data and signals into actionable insights.

Xeet: A new protocol on the Abstract network that is not yet fully launched, but a referral program has already been introduced where KOLs can earn reward points. Xeet's founder @Pons_ETH mocked that InfoFi has evolved into NoiseFi, stating, "It's time to reduce the noise and enhance the signal." The publicly available information is that Xeet will integrate with Ethos scoring, but Xeet has not disclosed any further information.

Data Insight Class InfoFi

Arkham Intel Exchange: Arkham is an on-chain data query tool, intelligence trading platform, and exchange. Arkham Intel Intel Exchange is a decentralized intelligence trading platform where "on-chain detectives" can earn bounties.

InfoFi Predicament

Prediction Market

• Regulation and Compliance: Prediction markets may be viewed as similar to binary options or gambling markets, facing regulatory pressure. For example, Polymarket was deemed to be operating illegally by the CFTC in the United States for not registering as a designated contract market (DCM) or swap execution facility (SEF), resulting in a fine of $1.4 million in 2022 and requiring it to block U.S. users. The investigations by the U.S. Department of Justice and the FBI in 2024 further highlight its regulatory challenges.
• Insider Trading and Fairness: Prediction markets may be affected by insider information. Large funds can distort prices in the short term. Designing fair rules and mechanisms is one of the key challenges for InfoFi prediction markets.
• Liquidity and Participation: The effectiveness of prediction markets relies on sufficient participants and liquidity. Prediction markets often face the "long tail liquidity problem" on niche topics, where insufficient participants lead to unreliable market information. The introduction of AI agents may partially address this issue, but further optimization is still needed.
• Oracle Design: Polymarket has previously experienced oracle manipulation attacks, resulting in significant losses for users who bet on correct outcomes. In February 2025, UMA, Polymarket, and EigenLayer announced they are collaborating to research the construction of predictive market oracles. Some research ideas include developing an oracle that can support multiple tokens to resolve disputes, with other features under investigation including dynamic binding, AI agent integration, and enhanced security against bribery attacks.

Mouth Lick

• Information noise intensifies, AI content advertisement accounts flood the market, obscuring real signals. Users find it difficult to filter value from a vast amount of content, community trust declines, and the marketing effectiveness of project parties is discounted. According to KOL Crypto Brave (@cryptobraveHQ), "Several project owners have complained about spending 150,000 USDT service fees on Kaito, allocating 0.5%-1% of tokens to KOLs for promotion, but over half of the participants are AI content advertisement accounts. Project parties want to attract leading KOLs and ICTs to participate and have to pay extra, then Kaito contacts the leading KOLs to get involved."
• Most algorithms of lip-sync projects lack public explanations on how to assess content quality, interactivity, and depth, raising user concerns about the fairness of points distribution. If the algorithm favors specific accounts (such as influencers or matrix accounts), it may lead to the loss of quality creators. Kaito has recently made some new upgrades to the algorithm based on community feedback, focusing on prioritizing quality over quantity by default, posts that do not provide project insights and comments will not receive attention, and further combating interaction manipulation and group boosting behaviors.
• The Matthew effect of profit distribution: In most cases, projects and KOLs achieve a win-win situation, but tail content creators and interactive retail investors still face the dilemma of low earnings and fierce competition. Kaito founder Yu Hu stated on June 8 that "of the approximately 1 million registered users on Kaito, less than 30,000 users have received yaps, which is less than 3%. The next growth stage of the network is to maximize the conversion rate." In addition, poor airdrop expectation management can lead to community dissatisfaction. Magic Newton is a relatively successful case in the Kaito AI ecosystem, where Kaito ecosystem recommendations account for 1/3 of all Newton validation agents, allowing mouth-tapping users to earn a lot, but it also faces accusations of being unfriendly to retail investors. In contrast, Humanity has been directly pointed out by the community for "betraying users" and "extreme anti-looting," and this distribution imbalance has triggered a trust crisis.
• The mouth-licking activity attracted users to participate at the beginning, but attention dropped sharply after the rewards were distributed, lacking sustainability. The token market value of LOUD approached 30 million dollars on the day of its launch, but now it is less than 600,000 dollars.
• Attention is not equal to market capitalization ratio.

Reputation

Reputation InfoFi projects such as Ethos are invite-only to control user quality and reduce the risk of witch attacks. However, this mechanism raises the participation threshold, limiting new user onboarding and making it difficult to create widespread network effects.

Malicious operation risk.

The issue of cross-platform recognition of reputation scores is that different protocols have scoring systems that are difficult to interconnect, creating information silos.

InfoFi Trend

Prediction Market

• The combination of AI and prediction markets: AI can significantly enhance the efficiency of prediction markets. For example, AI can provide more accurate predictions in complex scenarios by analyzing massive amounts of data; it can also explore AI agents to address long-tail issues.
• The combination of social media and prediction markets: Prediction markets have the potential to become the core infrastructure of the future information economy. On June 6, X officially announced a partnership with Polymarket, which becomes X's official prediction market partner. Polymarket founder and CEO Shayne Coplan stated, "Combining Polymarket's accurate, fair, and real-time prediction market probabilities with Grok's analytics and X's real-time insights will enable contextual, data-driven insights to be delivered instantly to millions of Polymarket users worldwide."
• Decentralized Governance: Prediction markets can be applied to the governance of DAOs, companies, and even societies, known as 'Futarchy.' Vitalik stated in 2014 that Futarchy is a governance model proposed by economist Robin Hanson, with the core idea being 'vote values, bet beliefs.' The operation is as follows: the community votes to determine a metric for success (such as GDP, company stock prices, etc.); for specific policy proposals, two prediction markets are created (for example, for and against). Participants trade these two tokens, and the prices reflect the market's expectations of whether the policy can optimize the goals; ultimately, the policy with the higher average price is chosen, and token rewards are settled based on actual results. The advantage of Futarchy is that it relies on data rather than political propaganda, personal charisma, or promotion.
• Content and news tools for everyone.

Mouth Licking + Reputation-based InfoFi

• Introduce social graph and semantic understanding technologies to enhance AI's accuracy in evaluating content value, ultimately leading to high-quality content.
• Incentivize high-quality long-tail creators.
• Add reduction or penalty mechanisms.
• Release of the Web3 dedicated InfoFi LLM.
• Multi-dimensional assessment of contributions.
• Reputation-based InfoFi combines with DeFi, where reputation scores serve as the basis for lending and staking credibility.
• The tokenization of abstract assets such as attention, reputation, trends, etc. will give rise to more types of derivatives.
• Not just based on the X social platform.
• The integration with more social platforms and news media drives the formation of an attention and Alpha discovery tool for everyone.

Data Insights InfoFi

• The combination of data analysis charts and creator insights, while simultaneously adding incentive mechanisms related to creation, distribution, etc.
• The combination of data analysis charts and AI analysis.

Summary

The core contradiction of the digital age is the divide between attention creators and value holders. This divide is the original driving force of the Web3 InfoFi revolution.

The core contradiction of InfoFi lies in the inability to balance information value and participation incentives, which may lead to a repeat of the SocialFi "high opening and low closing" scenario. The key to InfoFi is to establish a "trinity" balance mechanism of information mining, user participation, and value return, thereby driving the formation of a better knowledge-sharing and collective decision-making infrastructure. This requires not only the technical realization of attention quantification but also the design of mechanisms to ensure that ordinary participants can obtain reasonable returns from information dissemination, avoiding severe skewing in value distribution.

Moreover, the revolution of InfoFi requires a joint effort from both top-down and bottom-up approaches to truly achieve fairness and efficiency in the attention economy. Otherwise, the Matthew effect of the profit pyramid will turn InfoFi into a gold mining game for a few, going against the original intention of "universal attention value."

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