📢 Gate Square Exclusive: #WXTM Creative Contest# Is Now Live!
Celebrate CandyDrop Round 59 featuring MinoTari (WXTM) — compete for a 70,000 WXTM prize pool!
🎯 About MinoTari (WXTM)
Tari is a Rust-based blockchain protocol centered around digital assets.
It empowers creators to build new types of digital experiences and narratives.
With Tari, digitally scarce assets—like collectibles or in-game items—unlock new business opportunities for creators.
🎨 Event Period:
Aug 7, 2025, 09:00 – Aug 12, 2025, 16:00 (UTC)
📌 How to Participate:
Post original content on Gate Square related to WXTM or its
Grass Network: The Decentralization Revolution of AI Data Layer
Grass Network: Build a Decentralization Data Layer to Promote AI Development
Grass is a decentralized network scraping platform deployed on the Solana chain, combining AI, Depin, and Solana technology. Its positioning is as the Data Layer for AI, aimed at helping to train artificial intelligence models by utilizing unused internet bandwidth. Grass achieves web scraping through a browser extension application, leveraging individuals' idle bandwidth resources, and rewards users with Grass Points. The project's goal is to redefine the internet incentive structure, allowing users to directly benefit from the internet and ensuring that the value of the internet is in the hands of users. Currently, the Grass network has over 2 million user-operated nodes, scraping a large amount of data for AI models.
Technical Architecture
Grass has built a sovereign data Rollup network on Solana, enabling the protocol to handle all transactions from data sources to processing, validation, and construction of data sets. The core components of the network include:
Validator: Receives, verifies, and batches the router's web transactions, generating ZK proofs to validate on-chain session data.
Router: Connects Grass nodes to validators, maintains network traceability, and relays bandwidth.
Grass Node: Utilize unused user bandwidth to fetch public Web data.
Zk Processor: Proves the validity of batch processing Web request session data and submits the proof to the L1 blockchain.
Grass Data Ledger: Store the fetched data and link the data to the corresponding chain for proof.
Edge embedding model: Convert unstructured Web data into a structured model for cleaning, normalization, and structuring.
Technical Features
The Grass network is located between the client and the web server, handling web requests and fetching data. Its main technical features include:
Data lineage: Record the source and metadata of each dataset through the Grass data ledger and ZK processor.
High throughput: Using ZK processors and Rollup technology to handle a large number of Web requests.
Incentive Mechanism: Rewards based on node contribution to encourage network expansion.
Grass Node Operation and Security Mechanism
Grass node operation is free, and users can participate through the following steps:
The node reputation score mainly considers integrity, consistency, timeliness, and availability. In terms of security, Grass takes the following measures:
Grass token Features
Grass token holders can participate in the network in the following ways:
Currently, the annualized staking yield of Grass is approximately 45%, with about 33% of the tokens participating in staking, and the amount staked exceeds 26 million.
Router Staking and Returns
Users can stake Grass on Router to earn rewards. Currently, the staking amount of Grass in DBunker is about 1.43 million, with a minimum staking period of 7 days and a commission of 10%. Users can connect their wallets and stake Grass to receive Router staking rewards.
Summary
Grass is committed to building a fair and open Decentralization Data Layer, aimed at addressing the ethical issues of internet data extraction and data quality. Through innovative technical architecture and features, Grass provides a transparent, incentive-driven data source for AI companies and protocols. As an important player in the intersection of web3 and AI, the development prospects of Grass are worth looking forward to.