On-chain data interprets the potential of Crypto x AI

Translation: Golden Finance xiaozou

As the Crypto x AI field welcomes more and more projects, we are beginning to see how encryption technology and artificial intelligence technology work together on the chain.

In this article, we will explore how the potential of Crypto x AI is reflected in on-chain data.

Most on-chain transactions will be completed by AI agents. This trend is evident in Autoolas’ prediction market agent. Agent transaction volume has tripled since the beginning of the year, with weekly transaction volume exceeding 38k in the past month, and approximately 63% of transactions being Gnosis Safe transactions.

The Autonolas agent showed that even though there are only approximately 453 agents running on the chain, their activity is able to generate more transactions than human activity from Gnosis Safe. Agents enable a more efficient future of task collaboration, where their output may exceed human activity on the chain.

Crypto is inspiring coordinated AI development

DeAI projects are leveraging crypto capabilities to lead new markets, attract talent and research funding. For example, Morpheus has approximately 6,000 addresses with deposits of 93,000 stETH to increase liquidity and incentivize the development of artificial intelligence.

Token incentives are used to fund new applications/projects, create superior models through competition, and improve model quality through RLHF. In addition to talent and skills, they also attract high-value assets such as computing resources and data.

The value of artificial intelligence depends on its training data. Crypto can enhance data collection through token incentives. For example, Hivemapper uses its network of over 63,000 users to collect map data while driving. Since the beginning of 2024, Hivemapper has burned over $174,000 worth of tokens due to data needs.

Other examples are rDAO, which incentivizes personal data. Reddit licenses user data to AI companies for more than $200 million — but users may not be compensated — while rDAO compensates users who provide the data. So far, more than 154,000 users have provided their personal data to rDAO for AI training.

AI inference is driving on-chain transactions, especially:

• Ora’s AI oracle performed 1,700 transactions via opML
• Io.Net’s BC8 over 30,000 on Aptos in the past month Paid Inference Transactions

As AI makes smart contracts smarter, inference related transactions will grow.

The increasing number of on-chain activities of AI heralds a future where

• intelligent agents will dominate on-chain transactions
• There will be new ways to incentivize AI development
• compensation for new data
• The growth of on-chain reasoning

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