🔥 Biteye AI Daily Report, June 27th
Today's sector market cap: $8.38B -2.9%

The sector continues to correct. $SAHARA completed its TGE and was listed on major CEXs. $BANANAS31 has experienced significant volatility with sharp rises and falls in recent days.

📈 Top 10 24h Coingecko Trading Volume:
Token Trading Volume Market Cap Price Fluctuation
1- $SAHARA $657.0M $170.3M $0.08 -41.4%
2- $BANANAS31 $211.1M $75.7M $0.01 -52.6%
3- $VIRTUAL $195.2M $926.8M $1.42 -1.9%
4- $TAO $129.7M $2.9B $323.18 -0.4%
5- $AIXBT $53.3M $121.4M $0.13 -2.1%
6- $AI16Z $52.2M $146.2M $0.13 -5.7%
7- $PROMPT $49.5M $28.8M $0.13 -2.1%
8- $TUT $44.0M $46.0M $0.06 -7.7%
9- $KAITO $41.8M $329.8M $1.37 -2.9%
10- $COOKIE $19.1M $88.4M $0.16 -3.5%

⭐️ Key Information

- @CreatorBid released the V2 user guide, detailing how to participate in the AI Agent Launchpad on . uses BID Level to regulate users' priority in participating in new offerings. The higher the BID Level, the more you can enjoy higher allocation weights and less impact from selling penalties. The determination of BID Level will be determined by four dimensions: the weighted length of time the BID is locked in the user's vault, the number of AI Agent tokens pledged, the number of AI Agent tokens purchased, and the social InfoFi score.

Review: Since Kaito was launched, 's online presence has increased. Its AI Agent Launchpad mechanism is similar to @virtuals_io, but replacing the points system with BID Level is a good attempt and innovation. Let's see how it performs in the future.

- @near_ai tested and introduced @ASIMOV_Protocol and its reasoning results, and obtained accurate answers. Asimov Protocol is an innovative project built on NEAR Protocol that aims to solve data quality issues in AI model training, especially the "garbage-in, garbage-out" challenge, through blockchain technology and knowledge graphs.

Knowledge graphs store structured facts as entities and relationships, which can discover inconsistencies, omissions, and errors in the data, thereby providing support for data cleaning and quality improvement.

Review: The underlying basic design on Near always maintains a forward-looking perspective.

- @base uses AI to enhance the interactive capabilities of its documentation: users can use the AI chatbot and AI intelligent search provided by Base to understand the content of the documentation, or they can directly open the documentation in ChatGPT or Claude and learn on these mainstream AI chat interfaces; developers can also use the documentation MCP server, which can directly transmit the context to the IDE to assist programming.

Review: Viewing documentation has always been a tedious task. Base has consistently excelled in capturing user needs, and we look forward to its performance in the application layer.

📊 Data source: @xhunt_ai, Cookie DAO, Coingecko

💡 Risk warning: The above is for information sharing only and does not constitute investment advice.