BINANCE + DIN
♻️ You have 3 ways to earn with DIN :
🔸 Helps process information while earning rewards.
🔸 Add points in the Binance Web3 Wallet in collaboration with DIN.
🔸 Participating in the Binance Square campaign in collaboration with DIN.
If you are interested, I recommend reading the entire article 📖 ... let's first start by understanding what the project is about.
Data Processing + AI + Blockchain = DIN
This combination leverages technology to enhance data processing.
Contribution = Earn rewards
The smart contract determines the rewards for all participants considering the value contribution.
A higher quality contribution will yield a better reward
DIN is designed to empower everyone to cook data for AI and be rewarded.
Many Binance users had their first contact with DIN thanks to the collaboration with 🔶 Binance Web 3 Wallet.
More than 127,000 Binance users are participating and earning points.
• How to participate? :
🔸 Go to wallet
🔸Go to Web 3
🔸Select (Join Now)
• All content in this article is for educational purposes only 📖 .
• The information in this article was obtained from the official Din website 🌐.
This article is sponsored by :
🔸@DIN Data Intelligence Network
🔸@Binance Square Official
🔸@Binance Square
If you also want to participate, use the event # :
🔸 #DIN
🔸 #GODINDataForAI
🔸 #BinanceWeb3Airdrop
• At no time is investment recommended.
• It was advised to participate in the free activities.
🌐 DIN Architecture :
Basically consisting of 3 main phases regarding data processing :
🔸 Data Collectors 📊
🔸 Data Validators 📊
🔸 Data Vectorizers 📊
Participants will be rewarded according to their contribution to the network.
📊 Data Collectors :
The collected information is divided into 2 forms :
🔸 On-Chain Data :
Transactions
Wallet addresses
Smart contracts
🔸 Off-Chain Data :
Market sentiments
regulatory changes
Trends on social media
This strategy empowers a broad spectrum of users, from casual enthusiasts to professional analysts, in sectors such as crypto, medical, academic, and industrial.
• To add data is through :
🔸 Analysis
🔸 xData
This ensures access to actionable information.
📊 Data Validators :
To improve accuracy and reduce data manipulation risks, (SUM) is used.
S : Shared
U : Updatable
M : Models
📊 Data Vectorizers :
To improve the accuracy and scalability of models, vector conversion is performed.
🔸This means that :
Raw data is transformed into a structured format that AI models can efficiently process.
🖼️ In this image you can see the entire DIN protocol :
🔸 Data Collection: Collectors gather on-chain and off-chain data from various sources.
🔸 Validation Routing: Data is sent to selected validators based on their locally implemented models.
🔸 Verification: Validators employ computational resources to predict and determine the accuracy of the data.
🔸 Privacy Processing (Dataset): Validated data undergoes a privacy enhancement via the ZK processor.
🔸 Model Update: The relevant model is refined with the latest data and updated among validators.
🔸 Vector Conversion: Computing nodes transform validated data into vectors.
🔸 Privacy Processing (Vector): Vectors are processed through the ZK processor for privacy.
🔸 Data Finalization: The finalized dataset and vectors are stored in IPFS, making them accessible to third parties.