What are AI agents?
A timeline of AI agents
1966: ELIZA is developed by Joseph Weizenbaum at MIT. ELIZA is one of the first AI agents simulating conversation through pattern matching, and is considered one of the earliest examples of a chatbot.
1980: MYCIN, an expert system developed at Stanford University, is an AI agent that diagnoses bacterial infections and suggests treatments. MYCIN operates based on rules and knowledge encoded by medical experts.
2011: IBM Watson defeats human champions on the game show Jeopardy!, demonstrating its ability to process and understand natural language. This is an important step in developing AI agents capable of complex reasoning and information retrieval.
2014: Google DeepMind’s AlphaGo, an AI agent developed to play the board game Go, defeats a world champion, proving that AI can perform complex strategic games.
2020: OpenAI’s GPT-3 is released, pushing the boundaries of natural language generation and understanding with 175 billion parameters.
2022: Google DeepMind’s AlphaFold solves a 50-year-old problem in biology by predicting protein folding with remarkable accuracy.
2023: OpenAI’s ChatGPT, Anthropic’s Claude AI, and Google Gemini have become widely used conversational AI models, showcasing improvements in AI interaction and reasoning capabilities.
2025: Eliza Labs launches ElizaOS, an open-source platform on the Solana blockchain designed for building and managing AI agents and simulations.
AI agents in blockchain and cryptocurrency
Key use cases of AI agents in crypto
Automating trading strategies: AI agents identify arbitrage opportunities and execute trades.
Enhancing security: These agents monitor wallets, detect phishing attempts, and ensure compliance.
Managing virtual assets: AI handles play-to-earn earnings in gaming and the metaverse.
Supporting blockchain infrastructure: AI automates node deployment, smart contract execution, and gas fee optimization.
The future of AI agents in blockchain
Conclusion
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