AO launches AI on AO initiative

AO Releases “AI on AO” Plan
Updated · 11:43:30 Author: Block Explorer 2023
Coin World reported: On June 21, the AO ecosystem announced its “AI on AO” plan. This plan aims to put open-source large-scale language models (LLMs) and other artificial intelligence models on the chain, using permanent on-chain storage of Apus Network and Arweave to build a decentralized, trustless GPU network, providing reliable, efficient, and low-cost computing power for AI training and reasoning.
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Plan details
1. Chain AI model
The core goal of the “AI on AO” plan is to put various AI models on the chain, not limited to large-scale language models. This means that any AI model in the future can be stored and run through this network, greatly expanding the availability and flexibility of AI models.
2. Apus Network and Arweave
This plan is based on Apus Network and uses Arweave’s permanent on-chain storage. Through ArDrive, AI data can be uploaded to the Arweave model. Arweave provides a persistent storage solution, ensuring the durability and long-term availability of these AI models, making them a reliable resource for future AI training and reasoning.


3. Decentralized GPU network
The AO ecosystem is committed to building a decentralized GPU network to provide computing power for AI training and reasoning. The design of this trustless network not only improves the efficiency and reliability of computing but also reduces costs, making it more affordable for more users and developers.
Impact and prospects
1. Promote decentralized AI
The “AI on AO” plan marks an important step towards the decentralization of AI. By putting AI models on the chain, the AO ecosystem is opening up a new era for AI development and use. This decentralized approach not only enhances the transparency and credibility of AI technology but also makes AI resources more accessible and easy to obtain.
2. Permanent and reliable AI model storage
By using Arweave’s permanent on-chain storage, the durability and reliability of AI models are ensured. In the future, whether for AI training or reasoning, these models will become stable resources. This persistent storage solution will greatly enhance the availability and long-term value of AI models.
3. Enhance AI training and reasoning efficiency
The decentralized GPU network provides efficient computing power for AI training and reasoning. Compared to traditional centralized computing, this decentralized approach not only improves efficiency but also reduces computing costs, providing more possibilities for AI applications.


The “AI on AO” plan released by the AO ecosystem demonstrates its firm commitment to promoting AI technology and applications. By building a decentralized, trustless GPU network and using Arweave’s persistent storage, the AO ecosystem not only improves the efficiency of AI training and reasoning but also promotes the transparency and credibility of AI technology. This plan is expected to have a significant impact on the AI industry and may fundamentally change the way AI models are developed and used. In the future, we look forward to seeing more AI applications implemented on this decentralized network, driving progress and innovation across the industry.
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