How AI In Web3 Makes The Layers Of Web3 Intelligence?
An integral part of AI is machine learning and the addition of ML in Web3 will spread through various layers of the web3 stack.
Here are the three web3 layers that provide ML-driven insights.
1. Intelligent Blockchain
Present blockchain platforms concentrate on developing key distributed computing components that lead to the decentralized processing of financial transactions. Mempool structures, consensus mechanisms and oracles are the key building blocks behind such operations. With these techniques, the next generation of layer 1 (companion) and layer 2 (base) blockchain will combine ML-driven capabilities as the chief components of traditional software infrastructures like networking and storage will become more intelligent.
To mention, blockchain runtime utilizes ML prediction to make transactions in order to create scalable consensus protocols. AI adds security to the blockchain, AI applications can undergo data mining, defect fraudulent activities, predict actions, and prevent attacks. Apart from that, the blockchain will also attain benefit from AI as AI protocol might be able to forecast transactions and develop consensus protocols that can quickly scale.
2. Intelligent Protocols
Web3 stack can also incorporate ML capabilities with the utilization of smart contracts with certain protocols. DreFi depicts this trend most prominently. We do not have much distance to see the lending protocols with ML model-based intelligent logic. For Instance, imagine a DeFi platform with an intelligent score that balances loans from various types of wallets.
3. Intelligent dApps
DApps (Decentralized Applications) are expected to be the most fabulous web3 solutions with in-built ML-driven features. To point out, This trend is evident already in NFTs and will persist to grow. The next-gen NFTs will transform from static images to artifacts with the assistance of intelligent behavior. Such NFTs are ready to adapt their behavior to the mood of their owners’ profiles.
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