Project Background

DIN was originally named Web3Go.

As of August 2024, a total of $8 million in funding has been completed, with investors including Binance Labs, Hashkey Capital, NGC, Shima Capital, IVC, LIF, Big Brain Holdings, and Archerman Capital.




#dino is the first modular AI native data preprocessing layer.

DIN is built on the Data Intelligence Network, aiming to allow everyone to process data for AI and earn rewards.
#GODINDataForAI


The design and implementation of the DIN protocol are meant to ensure the network can obtain high-quality data through incentive mechanisms.

I've been following the project for a long time, from the initial golden leaves to the current plugins and large-scale activities with the Binance wallet. I feel the token is about to go live, and I hope the token launch is truly the beginning rather than the end, as artificial intelligence and AI are trends and the future.



In the DIN protocol, there are three ways to make money.
Citing the content of the project party

Data Collector: Focusing on on-chain and off-chain data

Bridging the gap between various types of data (trading, wallet addresses, smart contracts) and off-chain data (market sentiment, regulatory changes, social media trends), providing comprehensive insights. This strategy empowers a wide range of user groups, from casual enthusiasts to professional analysts, covering multiple fields such as crypto, healthcare, academia, and industry. Through our two products - Analytix and xData, we ensure users can access actionable, up-to-date information, aiding in making informed decisions in both public and private sectors.

Data Validator: Ensuring Model Accuracy

The Shared Updatable Model Decentralized Prediction (SUM) framework fundamentally changes the way data validation is done by leveraging the decentralized nature of blockchain. This ensures transparency, immutability, and collective improvement of model updates, enhancing prediction accuracy and reducing data tampering risks. SUM fosters a collaborative ecosystem that drives continuous model improvements, promising to usher in a new era of accurate, secure, and transparent predictive analytics.

Data Vectorizer: Simplifying AI Data Preparation

Vector conversion is crucial for AI preparation. It transforms raw data into a structured format that AI models can effectively process. This step is vital for data encoding, numerical standardization, high-dimensional data management, and optimizing AI training and predictions. By making data suitable for AI, vector conversion accelerates AI application development and improves model accuracy and scalability.



I have redeemed all my plugin points, those who haven't redeemed yet should hurry up. I noticed the redemption ratio keeps decreasing since the tokens are limited.

I haven't missed a single day of signing in on Binance, although the points are not much, I hope to enjoy a big pig's trotter rice soon; I have already used 2 pig's trotter rice now.