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DxChain 3.0 is based on web3.0, upgrades DxChain 2.0 in many aspects, is compatible with EVM and other smart contract platform architectures, optimizes the DPoS architecture, adds a system contract layer, and is committed to creating a support A development platform for smart contracts, which continues to develop the DxChain ecology on top of this platform, and supports cross-chain bridge technology to facilitate users to transfer assets between different chains. On the basis of ensuring security and scalability, Create the most suitable public chain for decentralized applications.
Today, only large companies can run big data tasks and monopolize data-related services. For individuals and small organizations, acquiring data storage services is costly and difficult to obtain data sources. Worse, everyone takes on privacy and data security risks, regardless of whether you're able to get any reasonable return for your data services.
There are some blockchain-based platforms that aim to provide supercomputer services, but there are no existing solutions in the market to provide a decentralized parallel computing environment that supports big data and machine learning.
Therefore, DxChain will be a real game changer in the market.
Blockchain is one of the most innovative technological inventions in recent years, with many important innovative features, such as decentralization and immutability. Unfortunately, today's popular consensus-based protocols still use a lot of computing power to maintain the blockchain itself and fail to provide useful work to the community. Today, people can use Bitcoin and Ethereum to buy goods, and use Hyperledger Fabric to track the flow of products. But outside of financial transactions and tracking assets in supply chains, blockchain has few practical applications. That said, blockchain is not fundamentally changing the way people use the internet.
DxChain designed a platform to solve big data computing in a decentralized environment. Therefore, people can use DxChain as a data marketplace to trade data, and create applications on DxChain to meet various needs, including business operations and business intelligence. Therefore, by applying blockchain to data storage and computing, DxChain will change the basic meaning of the Internet.
DxChain, a decentralized big data and machine learning network, this network is driven by a computing-centric blockchain and contains the following four main innovations:
⚫ A new decentralized Computing framework, introducing Probable Data Computing and verification game;
⚫ A new three-chains-on-chain design to orchestrate the main chain and two side chains : data side chain and computing side chain;
⚫ Introduce Hadoop in DxChain to facilitate big data processing and machine learning;
⚫ Based on DxChain's flexible and powerful system architecture, it is designed to support most business data Designed for exchange and data analysis needs.
DxChain is designed to support various machine learning and data mining algorithms, data storage, music/video streaming and many other applications. Developers from various sectors can utilize DxChain in different ways. Three use cases in the ecosystem supported by DxChain are described below.
Smart Cities:
DxChain users can run machine learning analysis directly on the data sets generated by sensors every day, and create actionable business intelligence reports to guide their daily business decisions. Our ecosystem developers can leverage it to build their own machine learning applications.
Health Care:
Reduce the cost of storing data and traffic. Data is encrypted and stored on the blockchain in an easy-to-handle and secure manner. Enable data exchange and sharing using DxChain's data model to standardize data. Machine learning enables healthcare providers to build their own AI to monitor patients' health and send vital vital signs.
AI model training:
DxChain, a decentralized big data and machine learning blockchain can benefit AI suppliers in many ways. Our ecosystem developers can leverage DxChain to build their own machine learning Dapps.