NEAR Protocol, a leading consumer blockchain focused on decentralized cloud computing, announced today the launch of NEAR AI, a new research and development lab focused on decentralized artificial intelligence (AI). The lab will be led by Illia Polosukhin, a co-founder of NEAR Protocol and co-creator of the influential Transformers AI architecture.

Additionally, the NEAR Foundation unveiled an AI-focused incubator and investment wing aimed at funding and supporting AI projects built on the NEAR ecosystem. This marks a strategic shift by the blockchain to position itself as a major player in the rapidly evolving AI landscape and push for more use cases for decentralized networks.

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According to the official announcement written by Polosukhin, the NEAR Foundation will invest in optimizing NEAR to become a native ecosystem for decentralized AI research and applications. This includes core infrastructure investments such as data collection and crowdsourcing, curation and rewarding creators, access to computers, and novel ways to monetize it.

Developing global open or decentralized AI is hard due to the number of players involved —however, it’s not impossible. The legal dispute between Elon Musk and Open AI, where Musk alleges that the developer of ChatGPT violated its non-profit mission, is an example of this issue. Open-source AI, as seen in platforms like Hugging Face, emphasizes collaborative development but often lacks coordinated efforts among developers, hindering the creation of models that can learn from each other over time.

On the other hand, decentralized AI, such as NEAR's initiatives, use blockchain to create open networks for shared objectives but face challenges in effectively coordinating those efforts. This contention impacts the democratizing potential, transparency, and trust in AI systems, especially as decentralized voting systems can lead to hierarchical structures with economic power influencing decisions.

“We want NEAR to be the place where any AI application and novel consumer use case can leverage the best User-Owned AI infrastructure, accessible by everyone in the Web3 ecosystem,” Illia Polosukhin said.

Polosukhin emphasized the importance of decentralizing computing power in an industry with so few powerful players like AI. "We do not want to live in a world where a few mega-corporations control the most powerful human resource: intelligence," he stated.

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Near co-founder and former Microsoft developer Alex Skidanov will also lead NEAR.AI alongside Polosukhin.

NEAR's push into AI comes as other blockchains are also looking to leverage the technology to grow their ecosystems and come up with strong use cases.

For instance, FetchAI, SingularityNet, and Ocean Protocol have proposed a merger to build the largest decentralized AI ecosystem. The new ASI token would be the result of the total market capitalizations of the native cryptocurrencies of the three projects, potentially ranking among the top 20 most valuable cryptocurrencies.

Another example is Venice AI, an AI startup focused on privacy and non-censorship. The new company is being developed by Erik Voorhees, the founder of the cryptocurrency exchange ShapeShift. Additionally, the AI startup FLock is launching a crypto rewards program to motivate users to help train its large language model in exchange for the rights to receive FML tokens.

NEAR Protocol was built to address issues like poor interoperability, low throughput, and slow transaction speeds with a layer-one cloud computing platform built from the ground up. This new focus in AI could also boost the role of the Web3 in the democratization of AI development, a practice that requires huge amounts of power and tends to be extremely restrictive to small players.

"The NEAR ecosystem is best positioned to achieve this vision at scale by combining user distribution in the tens of millions, a Web3 developer ecosystem that includes a growing number of AI projects, and ample financial resources stewarded by a not-for-profit Swiss Foundation," the announcement says.

Edited by Stacy Elliott.

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