RSS3 Open-Source AI Architecture – turn any LLM into Web3 AI Agents

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[PRESS RELEASE – Singapore, Singapore, March 17th, 2024]

In a world increasingly dependent on artificial intelligence (AI), the shift towards decentralized and open-source AI is crucial to mitigate the risks associated with centralization and to ensure the future of AI benefits everyone, not just a select few. RSS3 has been at the forefront of aggregating Open Information (data from blockchains and decentralized networks) and processing it into AI-ready formats. Their core team has been investigating and building decentralized AI products even before the GPT AI hype. Today marks a significant milestone in RSS3‘s journey as they unveil OpenAgent, the first open-source AI Agent Framework designed to democratize the creation of AI models.

The Open-Source AI Agent Framework – OpenAgent

With OpenAgent, customized AI agents can be created for specific needs such as analysis, prediction, content creation, and transaction automation, drastically shortening the development time of AI agents for independent builders from months to hours, leveling the AI playing field. OpenAgent utilizes a Mixture of Experts (MoE) architecture, which uses a gating network to choose the best expert models for specific tasks. Different expert models are like specialized Lego blocks, each optimized for distinctive functions, working independently yet collaboratively to produce a unified output. Unlike the popular OpenAI GPT models, any LLM (large language model) can be turned into on-chain AI agents with OpenAgent, creating AI agents with precise outputs for analytical or transactional purposes on top of the usual GPT creative content styles. Examples include natural language initiated on-chain transaction AI, on-chain arbitrage AI, and smart contract analytic AI.

Decentralizing AI

OpenAgent also works well with the real-time, AI-ready on-chain data from the RSS3 Network. The decentralization of AI through on-chain data can ensure AI agents’ credibility, foster democratization, and prevent undue influence through the transparency of on-chain data or decentralized networks’ data. For example, through real-time decentralized information from the RSS3 Network, Web3 AI agents can be built which automatically send 100 $RSS3 to Vitalik when he posts something on Farcaster. Another example is Web3 AI agents built from the OpenAgent Framework that automatically analyze the content of all Vitalik’s Farcaster posts and generate content that catches his attention or lists out all tokens of his interest.

Joshua, Founder of RSS3, stated, “OpenAgent’s open-source release is driven by a vision to reduce reliance on centralized AI products, fostering a Web3 AI ecosystem that’s more open, accessible, and diversified. We hope Web3 AI agents can be easily built by utilizing OpenAgent and leveraging RSS3’s aggregated AI-ready on-chain and cross-decentralized-network data to level the playing field for new or independent AI builders.”

Henry, CTO of RSS3, added, “Open-source AI models, like those on platforms such as Hugging Face, promote collaboration and transparency. We hope by taking another step forward in open sourcing our AI Agent Framework, we can collectively move towards a more accountable and resilient AI ecosystem in an increasingly data-driven world. OpenAgent simplify development process and reduce complexity of building Web3 AI applications.”

As RSS3’s OpenAgent takes its first steps into the world, it carries the promise of a more equitable future in AI technology. Through the power of open-source innovation and the commitment to decentralization, RSS3 is not just changing the landscape of AI development; it’s inviting everyone to be a part of this transformative journey.

OpenAgent, the open-source AI Agent Framework, can be found at https://github.com/RSS3-Network/OpenAgent