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## Zuvu AI and Vana Unite Efforts to Decentralize AI on Bittensor
Zuvu AI and Vana revealed a collaboration on February 26th with the intention of enhancing decentralized AI within the Bittensor network. Their goal is to establish a more economically viable and transparent AI environment.
Zuvu AI (previously known as SocialTensor) offers experience in scaling four Bittensor (TAO) subnets, while Vana, recently guided by Binance founder Changpeng Zhao, contributes its innovative user-controlled data network.
This partnership aims to examine a novel model for open, collaborative, and economically sustainable AI development by incorporating essential layers of the decentralized AI stack.
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## Producing Tangible Worth
Art Abal, Managing Director of the Vana Foundation, remarked that this collaboration unites Vana’s data layer, Bittensor’s subnet network, and Zuvu’s economic layer. This integration seeks to enhance Vana’s DataDAO environment and tackle considerable obstacles in AI development.
Zuvu fuels the AI economic layer, facilitating investment, staking, trading, and monetization of models, agents, and data, thereby generating new prospects in a swiftly expanding market. According to the press release, this collaboration arrives at a moment when the AI market is anticipated to reach trillions of dollars by 2032.
## DeFi’s Increasing Disturbance
The integration with Bittensor is tactical, leveraging its incentive-driven network to scale AI development. By merging user-controlled data with permissionless computation and economic incentives, this partnership mirrors the disturbance decentralized finance is bringing to traditional finance.
According to Abal and Zuvu AI COO Daniel Raissar, this collaboration is projected to enhance Bittensor’s subnet variety, support Vana’s DataDAO expansion, and position Zuvu as a frontrunner in AI financialization, potentially impacting industry practices.
This partnership corresponds to the increasing propensity of AI open sourcing, reflecting the growth of ventures such as Bittensor to 45 operational subgrids. It tackles the rising requirement for substitutes to unified AI behemoths, furnishing a more dispersed and approachable means to AI progress.
