Ritual Teams Up with EigenLayer
Ritual partners with EigenLayer to enhance AI capabilities on Ethereum, leveraging restaking mechanisms for decentralized AI services and economic security.
Ritual, a pioneering AI network, has announced a strategic partnership with EigenLayer, a protocol that extends Ethereum’s staking and security model. This collaboration is set to develop novel Actively Validated Services (AVSs) designed to power Ritual’s Infernet and future sovereign chain, while providing unique opportunities for Ethereum operators to engage in AI-centric operations with potential new revenue streams.
The Ritual team plans to launch the world’s first sovereign, community-owned AI network with the Infernet as its initial offering. This product enables smart contracts to leverage AI models for various applications through a decentralized oracle network. Following this, Ritual aims to introduce a sovereign chain with a custom-built VM optimized for AI operations.
EigenLayer’s restaking mechanism is pivotal to the partnership as it allows Ethereum stakers to bolster the economic and security framework of other applications, including Ritual’s AVSs. This symbiosis is intended to provide a strong level of decentralization and security for AI operations on the Ritual network from the outset. Additionally, it offers an innovative form of yield for EigenLayer operators participating in Ritual’s ecosystem.
The collaboration is set to roll out various AVSs. One significant innovation is the facilitation of model operations through EigenLayer operators, who can restake to provide services such as inference, fine-tuning, and training of AI models. This integration will allow these operators to partake in revenue streams as Ritual integrates payment channels for these services.
Another critical aspect is the Proof Marketplace within Ritual, offering computational integrity for model operations. This feature is essential for ensuring that model outputs, particularly those used by smart contracts, are verifiable and have not been tampered with. Once EigenLayer introduces slashing mechanisms, nodes providing these proofs can be held accountable, thus upholding the integrity of the operations.
Model routing is also a component of the partnership, where users can be matched with the most suitable models and nodes based on their preferences. This will be possible with the help of routers over Ritual, facilitated by restaked EigenLayer nodes, enhancing the user experience by connecting them to the optimal resources.
The partnership between Ritual and EigenLayer represents a step towards a more secure and decentralized future for AI on the blockchain. This alliance not only enriches the Ethereum ecosystem but also opens up new frontiers for staking to secure AI services.
The potential of this partnership is vast, and both Ritual and EigenLayer are actively seeking community input to explore other innovative uses of staking for service development. For more updates, interested parties can follow both entities on Twitter and find information on running a Ritual node in their documentation.
On November 8, 2023, Ritual, a pioneering decentralized AI platform, announced a successful seed funding round of $25 million. The round was spearheaded by leading investors Archetype, Accomplice, and Robot Ventures. Co-founded by notable Web3 investor Niraj Pant and data analytics expert Akilesh Potti, Ritual is set to tackle the challenges of AI centralization by prioritizing transparency, computational integrity, and data privacy.
Ritual’s innovative approach will empower Web3 companies to provide verifiable, on-chain proof of AI interactions, catering especially to the secure handling of sensitive financial and health-related data. By leveraging cutting-edge zero-knowledge proof technology alongside Optimistic Machine Learning, the platform aims to uphold computational integrity. Furthermore, Ritual is committed to enhancing access to GPU resources for advanced image processing, ensuring a more equitable and efficient ecosystem for AI development and application.
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