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# Zuvu AI and Vana Collaborate to Promote Decentralized AI on Bittensor
Zuvu AI and Vana revealed a collaboration on February 26, with the goal of reinforcing decentralized AI on Bittensor. The intention is to develop a more accessible and financially viable AI environment.
Zuvu AI, previously called SocialTensor, provides experience in growing four Bittensor (TAO) subnets, while Vana, recently guided by Binance founder Changpeng Zhao, contributes its innovative user-controlled data network.
The partnership aims to investigate a fresh AI development model that is accessible, collaborative, and economically sustainable through the integration of essential layers of the decentralized AI stack.
## Producing Actual Worth
Art Abal, Managing Director of the Vana Foundation, mentioned that the collaboration integrates Vana’s data layer, Bittensor’s subnet network, and Zuvu’s economic layer to enhance Vana’s DataDAO environment and tackle crucial obstacles in AI development.
Zuvu offers assistance for the AI economic layer, enabling investment, staking, trading, and monetization of models, agents, and data, generating new prospects in a swiftly expanding market. The press release mentions that the partnership arises as the AI market is predicted to reach trillions of dollars by 2032.
## DeFi’s Increasing Disturbance
This collaboration is tactically integrated with Bittensor, leveraging its incentive-driven network to scale AI development. By merging user-controlled data with permissionless computation and economic incentives, the partnership mirrors the disturbance of decentralized finance on conventional finance.
According to Abal and Zuvu AI COO Daniel Raissar, the collaboration is anticipated to improve the diversity of Bittensor’s subnets, support Vana’s DataDAO expansion, and position Zuvu as a leader in the financialization of AI, potentially influencing industry standards.
This collaboration leverages the increasing trend of AI with publicly available source code, akin to Bittensor’s growth to 45 operational subnetworks. It directly addresses the requirement for alternatives that diverge from major, centrally controlled AI enterprises.
