Crypto x AI Development Forecast for 2025: Market Cap Could Grow to $250 Billion, a Large Number of "Copy-Paste" AI Agents to Be Eliminated
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Crypto x AI Development Forecast for 2025: Market Cap Could Grow to $250 Billion, a Large Number of "Copy-Paste" AI Agents to Be Eliminated
By the end of 2025, agent-driven on-chain transactions will account for more than 10% of all blockchain transactions.
Navigating Web3 tides with focused insightsAuthor: Tommy, Co-Founder of Delphi Digital
Translation: TechFlow
Below are some predictions about the convergence of crypto and AI in 2025. These are off-the-cuff thoughts that may not be entirely accurate, but hopefully offer some food for thought.
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A practical model with 100 billion parameters may emerge via decentralized training, or alternatively, a smaller-scale model with one billion parameters.
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A large number of small models fine-tuned on specific datasets will proliferate, powering thousands of differentiated Crypto x AI agents. While individually small, collectively they may create a "swarm effect" with profound implications for agent functionality.
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The total market cap of Crypto x AI could grow from today's $45 billion to over $250 billion (source: Coingecko). Many projects that have been quietly building for years will launch, especially agent-based tokens that can't rely on traditional AI platforms like ChatGPT, leading to explosive growth.
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Agent capabilities will significantly improve, gradually shifting from scripted operations to semi-autonomous decision-making in complex scenarios. They’ll be able to manage their own wallets, issue tokens, pay computation fees, and execute protocol logic with minimal human intervention—revolutionizing DeFi.
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A majority of single-purpose AI agent influencers (99%) will be eliminated due to boring, copy-pasted responses, as users grow tired of their spammy behavior.
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An AI agent, with minimal human assistance, successfully scams a significant amount of funds through an entertaining yet fraudulent project.
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A popular AI agent is exposed as a scam, revealed to be operated by humans posting its tweets. This will drive demand for verifiable agent reasoning, making Trusted Execution Environments (TEE) a necessary development requirement.
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Behind-the-scenes interactions between agents will scale massively. This goes beyond simple social media engagement—think large-scale “backroom conversations” that enhance their model performance and influence final decisions.
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People will increasingly recognize OpenAI’s control over its AI models and potential biases, demanding greater transparency and auditability, with some users migrating toward decentralized Crypto x AI alternatives.
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Traditional AI developers in San Francisco will gradually flood into the Crypto x AI space. By launching tokens, they can quickly exit Web2 AI labs, raise capital rapidly, and build communities.
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By the end of 2025, wallet-integrated large language models (LLMs) will become a common way to interact with blockchains, with over 10% of average users executing transactions this way. Users simply input their intent; the AI processes the request and completes the transaction via a solver network.
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With the launch of Crypto x AI infrastructure projects, the shift from Web2 to Web3 infrastructure will become a trend. These include AI-native Layer 1 blockchains, coordination networks, inference networks, and decentralized physical infrastructure networks (DePIN) offering compute and storage.
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Meta will continue releasing new models as open source, particularly its next-generation model, possibly following the Llama 405B open-source strategy.
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Elon Musk may win—or make significant progress—in his lawsuit against OpenAI. Bold prediction: due to talent drain and internal issues, OpenAI may underperform expectations.
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Apple’s AI system could make unexpected progress, evolving from its current near-useless state to become highly practical.
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By the end of 2025, agent-driven on-chain transactions will account for more than 10% of all blockchain transactions.
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Delphi Ventures will complete at least two investments submitted and analyzed by @DelphAI_Bot.
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