Web3 is transforming the internet, shifting the paradigm to decentralised and user-centric models that promise greater autonomy and security. Central to this revolution are smart contracts – self-executing agreements with terms directly embedded in code – ushering in a new era of automated and secure blockchain transactions. Yet, the next frontier in this evolution is upon us: the integration of artificial intelligence (AI) into smart contracts. This fusion is set to supercharge the capabilities of smart contracts, making transactions not only automated but also intelligent and adaptive in blockchain applications. In this article, we dive into the features of AI-powered smart contracts and their benefits and explore how the intersection of AI and Blockchain heralds a new age of efficiency and sophistication in blockchain technology.

The Differences between Smart Contracts and AI-powered Smart Contracts

Smart contracts, the cornerstone of blockchain technology, operate as self-executing contracts with predefined conditions encoded into the blockchain. These contracts execute actions automatically when specific criteria are met, eliminating the need for intermediaries and ensuring trust and transparency in crypto transactions. However, traditional smart contracts lack adaptability or intelligence beyond their predetermined conditions. While inherently secure due to blockchain technology, they may still be vulnerable to coding errors or exploits in their execution logic.

In contrast, AI-powered smart contracts represent a significant evolution in blockchain technology by integrating artificial intelligence capabilities. These contracts are equipped to comprehensively read, analyse, and link data, allowing them to perform real-time predictive analytics and trend forecasting tasks. By leveraging AI, they streamline decision-making processes based on dynamic information, ensuring precise execution of predefined conditions. Moreover, AI-powered smart contracts possess the capacity to adapt and optimise performance over time, learning from past transactions through machine learning algorithms. The adaptability of AI technology in blockchain applications ensures their responsiveness to evolving circumstances, thereby enhancing efficiency and effectiveness.

In terms of efficiency, AI-powered smart contracts automate tasks that previously required manual intervention, drastically reducing the time and effort needed to execute transactions. Their enhanced accuracy stems from their ability to analyse vast datasets, minimising errors and ensuring precise execution of predefined conditions. Furthermore, these contracts continuously improve over time, leveraging machine learning algorithms to optimise future actions based on past transactions. This adaptability makes them more resilient and more responsive to new information. Additionally, AI-powered smart contracts prove cost-effective by reducing errors, optimising resources, eliminating intermediaries, and lowering blockchain transaction fees and operational costs. Moreover, they provide AI-driven insights that facilitate better decision-making, ultimately enhancing overall cost efficiency.

The Benefits of AI Integration in Smart Contracts

AI enhances the intelligence of smart contracts by enabling them to read, analyse, and link data comprehensively. Unlike traditional smart contracts that execute predefined conditions without flexibility or adaptability, AI-powered smart contracts can process large volumes of data, draw insights, and adapt to new information. This advanced capability gives blockchain-based business networks a competitive edge, allowing for more informed and dynamic decision-making.

1. AI-Enhanced Automated Transactions

One significant way AI-powered smart contracts are revolutionising crypto transactions in Web3 is through enhanced automation. AI algorithms can execute transactions on the blockchain based on predetermined thresholds and events, drastically reducing the need for human intervention. This automation streamlines processes, accelerates transaction times, and ensures more reliable execution, making the entire blockchain transaction ecosystem more efficient and responsive.

Here's an example of a smart contract incorporating the approvePayment() function that utilises an AI algorithm to predict whether the payment should be approved based on historical data. The transfer() function then executes the transfer only if the payment is approved by the AI algorithm.


pragma solidity ^0.8.0;

contract AIEnhancedContract {
    address public payer;
    address public payee;
    uint public amount;
    bool public paymentApproved;

    constructor(address _payer, address _payee, uint _amount) {
        payer = _payer;
        payee = _payee;
        amount = _amount;
    }

    function approvePayment() public {
        // AI algorithm to predict payment approval based on historical data
    }

    function transfer() public payable {
        require(msg.sender == payer, "Only the payer can initiate the transfer");
        require(msg.value == amount, "Incorrect payment amount");
        require(paymentApproved, "Payment not approved by AI");

        payable(payee).transfer(amount);
    }
}

*Note: This is a simplified example for demonstration purposes. In a real-world scenario, the AI algorithm would need to be trained on relevant historical data and may involve more complex machine-learning techniques.

2. Intelligent Decision-Making

AI technology brings intelligent decision-making to smart contracts by analysing vast amounts of data and suggesting optimal decisions. For example, in the context of decentralised finance (DeFi) blockchain applications, AI can analyse market trends, user behaviour, and historical data to suggest the best time to execute trades or adjust interest rates.

Here's a conceptual example of how an AI-enhanced smart contract can analyse market data to suggest optimal interest rates for locked crypto funds:
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pragma solidity ^0.8.0;

contract AIPoweredDeFi {
    address public owner;
    uint public optimalInterestRate;

    event InterestRateUpdated(uint newRate);

    constructor() {
        owner = msg.sender;
        optimalInterestRate = 5; // Initial interest rate set to 5%
    }

    modifier onlyOwner() {
        require(msg.sender == owner, "Only the owner can execute this function");
        _;
    }

    function updateInterestRate(uint marketTrend, uint userBehavior) public only owner {
        // Simulating AI decision-making process
        // In a real-world scenario, this would involve complex AI/ML models
        uint newRate = suggestOptimalInterestRate(marketTrend, userBehavior);
        optimalInterestRate = newRate;
        emit InterestRateUpdated(newRate);
    }

    function suggestOptimalInterestRate(uint marketTrend, uint userBehavior) internal pure returns (uint) {
        // A simple example logic for suggesting interest rate
        // This should be replaced by actual AI analysis logic
        if (marketTrend > 50 && userBehavior > 50) {
            return 7; // Suggest 7% interest rate
        } else if (marketTrend > 50 || userBehavior > 50) {
            return 6; // Suggest 6% interest rate
        } else {
            return 5; // Default interest rate
        }
    }

    // Additional functions for the DeFi platform
    // e.g., deposit, withdraw, etc.
}

In this example, the contract initialises by setting an initial interest rate and defining the owner. The updateInterestRate function allows the owner to adjust the interest rate based on market trends and user behaviour. The suggestOptimalInterestRate function, which currently contains simplified logic, would be replaced in a real-world application by a more complex AI/ML model that analyses extensive data to suggest optimal interest rates. Additionally, when the interest rate is updated, the contract emits an event on the blockchain to ensure transparency and traceability.

3. Predictive Analytics Capabilities

Additionally, AI-powered smart contracts offer predictive analytics capabilities. AI can predict future trends and behaviours, informing the actions of smart contracts. In the context of a crypto trading bot, AI can analyse market data, social media sentiment, and historical price trends to predict which cryptocurrencies are likely to be profitable. The smart contract can then automatically execute trades based on these predictions.

Here's a conceptual example of how a smart contract uses AI to predict the next trending and profitable cryptocurrency by analysing data sources and suggesting trades, which the smart contract then executes automatically:
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pragma solidity ^0.8.0;

contract AIPoweredTradingBot {
    address public owner;
    uint public balance;
    mapping(string => uint) public cryptoHoldings;
    
    event TradeExecuted(string crypto, uint amount, uint price);
    
    constructor() {
        owner = msg.sender;
        balance = 10000; // Initial balance in some stablecoin
    }
    
    modifier onlyOwner() {
        require(msg.sender == owner, "Only the owner can execute this function");
        _;
    }

    function executeTrade(string memory crypto, uint amount, uint price) public onlyOwner {
        require(balance >= amount * price, "Insufficient balance");
        
        // Simplified trade execution logic
        balance -= amount * price;
        cryptoHoldings[crypto] += amount;
        
        emit TradeExecuted(crypto, amount, price);
    }

    function suggestTrade(uint[] memory marketTrends, uint[] memory socialSentiments, uint[] memory historicalPrices) public view returns (string memory, uint, uint) {
        // Simplified AI-based decision making logic
        // In a real-world scenario, this would involve complex AI/ML models
        string memory suggestedCrypto = "ETH";
        uint suggestedAmount = 10;
        uint suggestedPrice = 2000;

        // Example logic to suggest trading ETH based on market data
        if (marketTrends[0] > 70 && socialSentiments[0] > 60 && historicalPrices[0] < 2100) {
            suggestedCrypto = "ETH";
            suggestedAmount = 10;
            suggestedPrice = 2000;
        } else if (marketTrends[1] > 70 && socialSentiments[1] > 60 && historicalPrices[1] < 1) {
            suggestedCrypto = "DOGE";
            suggestedAmount = 1000;
            suggestedPrice = 0.05;
        }

        return (suggestedCrypto, suggestedAmount, suggestedPrice);
    }

    // Function to call suggestTrade and execute the recommended trade
    function analyseAndTrade(uint[] memory marketTrends, uint[] memory socialSentiments, uint[] memory historicalPrices) public onlyOwner {
        (string memory crypto, uint amount, uint price) = suggestTrade(marketTrends, socialSentiments, historicalPrices);
        executeTrade(crypto, amount, price);
    }
}

In this example, the AI-powered smart contract initialises by setting the owner and an initial balance in a stablecoin. The executeTrade function allows the owner to perform trades by deducting the balance and updating crypto holdings. The suggestTrade function simulates AI-based decision-making by analysing market trends, social sentiments, and historical prices to recommend optimal trades. In a real-world scenario, this function would utilise advanced AI/ML models for more accurate predictions on the blockchain. The analyseAndTrade function automates the process by calling suggestTrade to obtain the recommended trade and then executing it using executeTrade. This setup enhances efficiency and accuracy in trading by leveraging AI's predictive analytics, ensuring that trades are informed by dynamic and comprehensive data analysis. Additionally, the contract emits events when trades are executed, providing transparency and traceability, which is crucial in a decentralised digital world.

aelf x AgentLayer – Building the Next Revolutionary AI Blockchain

AI-powered smart contracts represent a revolutionary leap forward in Web3 transactions, offering enhanced efficiency, accuracy, and adaptability to make transactions smarter and more dynamic. Despite challenges, the substantial benefits of this integration make it indispensable for businesses seeking to maintain a competitive edge in the blockchain technology landscape. Embracing AI-powered smart contracts is imperative for navigating the future of blockchain-based transactions successfully.

In collaboration with AgentLayer, aelf is actively pursuing the transformation into an AI blockchain akin to AgentChain. This endeavour prioritises credible verification, evidence storage, sharing, and trading of AI models, data, and computing resources within a decentralised framework. Leveraging AgentLayer's AgentOS, designed specifically for AI application development, aelf aims to provide developers with a comprehensive environment for deploying and managing multiple AI frameworks and models seamlessly. Additionally, by tapping into AgentLayer's PropertyGPT system, which harnesses large language models (LLMs) to generate and validate smart contract properties effortlessly, aelf is poised to leverage the innovative technology stack offered by AgentLayer. Through this collaboration, aelf hopes to harness AgentLayer's expertise and infrastructure to emerge as a prominent player in the AI blockchain landscape.

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*Disclaimer: The information provided on this blog does not constitute investment advice, financial advice, trading advice, or any other form of professional advice. Aelf makes no guarantees or warranties about the accuracy, completeness, or timeliness of the information on this blog. You should not make any investment decisions based solely on the information provided on this blog. You should always consult with a qualified financial or legal advisor before making any investment decisions.

About aelf

aelf, the pioneer Layer 1 blockchain, features modular systems, parallel processing, cloud-native architecture, and multi-sidechain technology for unlimited scalability. Founded in 2017 with its global hub based in Singapore, aelf is the first in the industry to lead Asia in evolving blockchain with state-of-the-art AI integration, transforming blockchain into a smarter and self-evolving ecosystem.

aelf facilitates the building, integrating, and deploying of smart contracts and decentralised apps (dApps) on its Layer 1 blockchain with its native C# software development kit (SDK) and SDKs in other languages, including Java, JS, Python, and Go. aelf’s ecosystem also houses a range of dApps to support a flourishing blockchain network. aelf is committed to fostering innovation within its ecosystem and remains dedicated to driving the development of Web3, blockchain and the adoption of AI technology.

Find out more about aelf and stay connected with our community:
Website | X | Telegram | Discord

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Tool/Platform	What's it about
ChainGPT	An AI-powered assistant for the blockchain and crypto industry, specializing in content creation, language translation, smart contract coding, and more.
aelf	A high-performance, customisable multi-chain blockchain framework with AI-powered smart contracts and a developer-friendly environment.
Quick Intel	An AI-powered crypto security platform that helps investors avoid scams, rug pulls, and honeypots by analysing smart contracts, social sentiment, and on-chain data.
Cogwise AI News Aggregator	An AI-powered news aggregator that analyses real-time news and global trends to predict market movements in the crypto market.
OpenAI Codex	An AI system that transforms natural language into code, automating code creation for smart contracts, blockchain applications, and other development tasks.
QnA3	An AI-powered Web3 knowledge hub that provides real-time information and insights on cryptocurrencies, blockchain projects, and the broader Web3 ecosystem, with unique Solana Actions integrations.
Fetch.ai	A platform that combines AI and blockchain to create autonomous economic agents (AEAs) for various applications, including supply chain optimisation and smart city management.
Octavia	A decentralised digital identity (DID) platform for creating and managing self-sovereign digital identities, empowering users to control their data and online presence.
TensorFlow	A versatile open-source machine learning framework used for building AI models that can analyse blockchain data, enhance security, and predict market trends.
Alethea	A platform that creates 'Intelligent NFTs' (iNFTs) with unique personalities and the ability to engage in conversations, powered by AI and blockchain technology.

Chain	URL	Explorer
AELF	https://aelf-test-node.aelf.io/	https://explorer-test.aelf.io/
tDVW	https://tdvw-test-node.aelf.io/	https://explorer-test-side02.aelf.io/

Feature	Description
Inheritance	ERC-404 inherits from the interfaces IERC-404, IERC721 Receiver, and IERC165, implementing functions specified in these interfaces, behaving as both ERC20 and ERC721.
Data Structures	Mappings track balances, allowances, approvals, and ownership of tokens. Double-ended queue stores ERC721 token IDs. Data for managing ownership and indices of ERC721 tokens.
Constructor	Initialises token name, symbol, decimals, and other necessary variables for ERC20 and ERC721 tokens.
Token Minting and Burning	_mintERC20 function for minting ERC20 tokens. _retrieveOrMintERC721 function for minting ERC721 tokens and retrieving from a bank. _withdrawAndStoreERC721 function for depositing ERC721 tokens into the bank.
Transfers	Functions for transferring ERC20 and ERC271 tokens between addresses. Distinguishes between token types based on ID. _transferERC20WithERC721 function handles transfers involving both types.
ERC20 and ERC721 Interactions	Approve function handles approvals for both token types. Functions like transferFrom, safeTransferFrom, and permit handle transfers and approvals.
EIP-2612 Support	Supports EIP-2612 permit functionality for ERC20 tokens.
Interface Compatibility	Implements necessary functions for ERC-404 and ERC165 interfaces, indicating compatibility with ERC20 and ERC721 standards.

Role	Max Number
BP	2N+1, N starts from 8 in 2022
Candidate node	5*(2N+1)
Voter	No limit

Benefits	Description
Makes smart contracts 'smarter'	AI-driven smart contracts can autonomously modify terms based on predefined conditions and real-time data input, ensuring that the contracts are not just automated but also intelligent and self-improving over time.
Levelled up data analysis	Data is the new oil, and AI is the machinery that refines it. It is possible for AI to reduce large-volume blockchain data analysis time by up to 90%.
Boosts security	Through machine learning models, AI can prevent frauds and detect security threats in real time. It can identify potential breaches, predict future threats, and adapt to evolving security measures.
Lowers carbon footprint	AI algorithms help optimise energy consumption in blockchain operations, given the flak drawn by activities like Bitcoin mining.

AI-Powered Smart Contracts: The Impact of AI On Web3 Crypto Transactions