A new decentralized AI team was created by the Ethereum Foundation, led by Davide Crapis. According to Gil Rosen, co-founder of the Blockchain Builders Fund, this action signifies a shift for Ethereum from a neutral settlement layer to a more “opinionated” Layer-1.
Ethereum Foundation Launches New AI-Focused Team
A decentralized artificial intelligence (AI) team was recently unveiled by the Ethereum Foundation, led by Davide Crapis. The goal is to position the Ethereum blockchain as a foundational settlement and coordination layer for autonomous AI agents, a move that reflects the project’s ambition to shape an open, transparent, and non-monopolized future for AI.
As part of its mandate, the team plans to develop a fully decentralized AI stack to ensure that AI’s evolution is not controlled by a handful of dominant entities. By integrating AI with Ethereum’s decentralized architecture, the team aims to unlock new possibilities for autonomous systems, including on-chain decision-making and trustless coordination between intelligent agents. The launch is widely considered a key step toward democratizing AI development and aligning it with the principles of Web3.
The entry of Ethereum into the AI space will likely have broad implications for the crypto industry, particularly for AI-focused chains. The development was described as both welcome and noteworthy by Gil Rosen, co-founder of the Blockchain Builders Fund.
According to Rosen, the shift in Ethereum from a neutral settlement layer to an “opinionated” Layer 1 was caused by the AI team’s unveiling. The network will now target specific sectors with infrastructure to support them.
An impact on AI-focused Layer 2s is also expected from the decentralized AI team, which signals the emergence of base-layer functionality tailored to their needs.
Across the blockchain ecosystem, numerous projects are building decentralized and censorship-resistant AI infrastructure, laying the groundwork for a transparent AI economy free from centralized control. The future of artificial intelligence is intended to be guided by permissionless innovation rather than gatekeeping by a handful of powerful entities.
Technical limitations that may hinder its competitiveness against newer protocols are faced by Ethereum, but Rosen believes its widespread adoption and interoperability make it well-suited to serve as a global verifiability and settlement layer.
The most successful AI blockchain projects to date have focused on Web2 use cases, while agentic infrastructure chains like Virtuals and Sahara have struggled to gain traction. Rosen attributes their limited impact to the relatively small Web3 AI market compared to Web2 AI. Ethereum, however, is widely believed to have the potential for success.
Rosen told Bitcoin that “the greatest value proposition for Ethereum is its ability to act as a verifiability layer for truth, a concept that has long been promoted by Vitalik [Buterin] through Ethereum’s attestation capabilities.”
Overcoming Technical Challenges and Unlocking Future Potential
It is contended by experts that if Ethereum succeeds as the blockchain verifiability and settlement layer for Web2, the implications could be far-reaching. As Ethereum scales its base chain performance, it may potentially compete as an AI stack for the “long tail of open-source and interoperable models.” This could prove crucial for nation-states wary of over-reliance on tech giants like OpenAI, Google, and Anthropic. In this scenario, Ethereum could act as an AI infrastructure stack in a market as large as its current total valuation.
The belief was voiced by Rosen that AI agents could be a monumental source of demand.
According to Carlo Fragni, a solution architect at Cartesi, two technical challenges will be faced by the decentralized AI team: training models and executing them for inference or classification. He also stressed the importance of determinism.
Fragni asserted that if determinism isn’t properly addressed, reproducible models or inference/classification cannot be had, which makes consensus difficult.
In written responses to Bitcoin , it was clarified by Fragni that training AI models requires large datasets and intensive computation, making decentralized storage and execution difficult. He added that large language models (LLMs), in particular, exceed the capabilities of Ethereum and current zero-knowledge (ZK) solutions. He also noted that rebuilding existing AI libraries from scratch is resource-intensive and slow, making it essential to leverage existing frameworks.
It is speculated by some experts that if Ethereum succeeds as the settlement and coordination layer for the AI economy, the value of ETH could surge. Rosen believes such a transformation could ultimately position ETH as a preferred settlement currency.
It was concluded by Rosen that if Ethereum becomes the layer for a trusted, near real-time digitized world where agents can transact, the demand will surpass even the scenario where every human uses ETH for all their transactions.
