How AI Applications Choose a Blockchain
Blockchain selection should begin with an application's actual workload and compare performance, cost, specialized capabilities, and the development ecosystem. Different networks often serve different layers, and no single answer fits every AI application.
Define the Blockchain's Role First
In AI applications, a blockchain can host smart contracts that let autonomous agents hold and use funds according to rules. It can also coordinate distributed contributions of computing power, models, or data and record verifiable transactions and outputs. Because computation, agent collaboration, and payment settlement have different requirements, teams should first determine which layer of the problem the blockchain needs to solve.
Compare Performance, Cost, and Development Conditions
When many agents operate frequently, teams should closely examine transaction throughput, confirmation speed, and whether fees are low and predictable. Developers must also assess whether a network offers specialized capabilities such as off-chain computation, agent tools, or machine-learning incentives, while checking the maturity of its documentation, components, and community to avoid excessive development and maintenance costs despite technical feasibility.
Combine Networks According to Workload
Decentralized model training or machine-intelligence markets may consider Bittensor; applications requiring graphics-computing resources may examine Render; and tools for autonomous agents may consider Fetch.ai or NEAR. Solana and BNB Chain suit frequent on-chain operations, while Ethereum and its Layer 2 networks are often used for smart contracts and settlement. A real project may also divide responsibilities among multiple networks.
Original Tutorial
https://www.binance.com/zh-CN/academy/articles/best-blockchains-for-building-AI-applications
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