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AI and Crypto

Feedback loops shape our destiny.

Purpose​

Explore use cases for using AI with blockchain to automate infrastructure.

Planning Phase​

  • Identify the specific AI capabilities needed for your blockchain application
  • Determine which blockchain platform and AI services are most suitable
  • Evaluate the integration method (e.g., Chainlink Functions for connecting blockchains with external AI services)
  • Consider data privacy and security implications of using external AI services
  • Plan for scalability and cost management of AI API calls

Execution and Testing Phase​

  • Set up development environment with necessary tools (e.g., Chainlink Functions beta, OpenAI API)
  • Implement proper environment variable management for API keys and secrets
  • Use a request configuration file to define parameters for AI requests
  • Craft effective prompts for AI services to get desired outputs
  • Implement error handling and response parsing for AI API calls
  • Simulate AI requests off-chain before deploying to test functionality
  • Optimize token usage and API call frequency to manage costs
  • Test different AI models or services to find the best fit for your use case

Deployment Phase​

  • Deploy smart contracts to the chosen blockchain network
  • Set up and fund a subscription for Chainlink Functions (if using)
  • Implement proper billing and payment mechanisms for AI service usage
  • Ensure secure storage and transmission of API keys and other secrets
  • Set up monitoring and logging for AI requests and responses
  • Implement fallback mechanisms in case of AI service failures
  • Consider implementing caching strategies to reduce redundant AI calls
  • Plan for updates and maintenance of both smart contracts and AI integration

Best Practices​

  • Always encrypt and securely manage API keys and sensitive data
  • Use simulation and testing environments before deploying to mainnet
  • Implement rate limiting and error handling for AI API calls
  • Regularly update and maintain both blockchain and AI components
  • Monitor and optimize gas costs for on-chain operations
  • Implement proper access controls for smart contract functions
  • Document the integration process and provide clear instructions for users
  • Stay informed about updates and changes in both blockchain and AI technologies

By following this checklist, developers can more effectively plan, execute, test, and deploy AI-driven applications on the blockchain, ensuring better integration, security, and performance.

Decentralized AI​

Solving AI centralization: Prevent the centralization of power under a single entity by distributing the models, compute, data, and decision-making across decentralized networks.

  1. Decentralize AI models by running open-source models on local devices ("Edge AI") instead of centralized cloud servers. This allows users to own the model and keep their data private.
  2. Use decentralized computing power to train smaller AI models or fine-tune large models, overcoming the hardware limitations of individual devices.
  3. Decentralize the training data for AI models to prevent political bias and ensure the outputs are not skewed.
  4. Leverage blockchain technology and zero-knowledge proofs to prove the authenticity of AI-generated content and prevent deep fakes, which will be crucial for events like elections.
  5. Incorporate AI into decentralized applications (dApps) and protocols, enabling features like programmatic rewards for creators, trend identification from on-chain data, and scalable content production.
  6. Explore using AI for automated decision-making and governance in decentralized autonomous organizations (DAOs), with transparent parameters that the community can adjust.
  7. Utilize crypto economic incentives to build a consumer-grade network where participants contribute computing power for decentralized AI training and inference.

Blockchain Data​

What is the most important question you could ask yourself to make progress?