#币安人生 AI large models have multifaceted impacts on the cryptocurrency market, bringing both technological innovations and efficiency improvements while also introducing new risks and challenges. Specifically, they are as follows:

- Smart contracts and development efficiency improvement: AI large models can understand and generate code in programming languages such as Solidity. Coupled with security frameworks, they can quickly generate standardized smart contract code, and customize advanced features such as burn taxes and governance parameters, reducing the smart contract development cycle by over 60%.

- Trading strategies and market analysis optimization: AI large models can construct trading strategies based on user natural language, automatically completing code generation, historical backtesting, and real-time execution. For example, in the ChatGPT-4o integration system of the 3EX exchange, the AI-generated grid trading strategy has an annualized return that is 23% higher than manual strategies, with a maximum drawdown reduced by 18%. At the same time, AI can analyze massive on-chain data and social media sentiment, providing support for market predictions.

- Risk monitoring and security audit enhancement: AI-driven monitoring systems can simultaneously track liquidity changes in multiple DeFi protocols, quickly complete stress tests and trigger hedge positions when risks occur, speeding up response time by 200 times compared to manual responses. Additionally, AI audit models, combined with semantic analysis capabilities, can complete traditional audits that would take teams much longer in a short time, effectively intercepting smart contract vulnerability attacks.

- Market hotspots and investment narrative shifts: AI has become one of the most important narrative engines in the crypto market, with AI concept tokens represented by Fetch.ai and Bittensor receiving market attention and attracting capital inflows. The market is enthusiastically pricing cutting-edge concepts such as "AI agents owning wallets and trading autonomously" and "decentralized AI training and inference," and investors are incorporating "AI integration capabilities" into one of the core dimensions of project evaluation.

- Increased regulatory and compliance difficulties: AI large models may be used to forge fake project white papers, trading data, etc., for market manipulation and fraud activities, such as the deepfake scam in 2024 that resulted in over $25 billion in cryptocurrency losses. At the same time, AI agents lack physical identities and are difficult to verify through traditional identity verification, posing new challenges for regulatory agencies. $BNB $XRP $SOL