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# Zuvu AI and Vana Unite to Boost Decentralized AI on Bittensor
On February 26th, Zuvu AI and Vana revealed a collaboration designed to fortify decentralized artificial intelligence on Bittensor. The two firms are collaborating to construct a more accessible and economically viable AI environment.
Zuvu AI, previously known as SocialTensor, has expertise in broadening four Bittensor (TAO) subnets, while Vana, recently counseled by Binance founder Changpeng Zhao, contributes its groundbreaking user-owned data network.
This alliance aims to assess a novel model for AI advancement that is open, cooperative, and financially sound by incorporating crucial tiers of the decentralized AI stack.
## Generating Genuine Worth
Art Abal, Managing Director of the Vana Foundation, remarked that the partnership incorporates Vana’s data layer, Bittensor’s subnet network, and Zuvu’s economic layer to enhance Vana’s DataDAO ecosystem and tackle key challenges in AI development.
Zuvu offers backing for the AI economic layer, enabling investment, staking, trading, and monetization of models, agents, and data, thereby establishing fresh prospects in a quickly expanding market. As per the press statement, the collaboration arrives at a juncture when the AI market is forecasted to attain trillions of dollars by 2032.
## The Increasing Disruption of DeFi
The partnership’s integration with Bittensor is tactical, capitalizing on its incentive-driven network to broaden AI development. By merging user-owned data with permissionless computing and economic incentives, the collaboration mirrors the disruption of decentralized finance on conventional finance.
As per Abal and Zuvu AI COO Daniel Raissar, the partnership is anticipated to amplify the diversity of Bittensor’s subnets, bolster the expansion of Vana’s DataDAO, and establish Zuvu as a frontrunner in AI financialization, potentially impacting industry practices.
This partnership mirrors the prevailing open-source artificial intelligence movement, exemplified by Bittensor’s growth to 45 operational subnets, and also addresses the demand for substitutes to concentrated AI behemoths.
