Grayscale Launches New Fund Targeting Decentralized AI Protocols
The prominent crypto asset manager announced the launch of the Grayscale Decentralized AI Fund LLC on July 17th, which aims to offer investors exposure to protocols in the rapidly evolving artificial intelligence sector within the crypto ecosystem.
The fund will rebalance quarterly and currently features a basket of decentralized artificial intelligence (AI) crypto protocols, such as Bittensor (TAO), Filecoin (FIL), Livepeer (LPT), Near (NEAR), and Render (RNDR).
Grayscale’s New Decentralized AI Fund
Grayscale’s Head of Product & Research, Rayhaneh Sharif-Askary, highlighted that the latest launch of the Grayscale Decentralized AI Fund will provide an opportunity to invest in Decentralized AI at its earliest phase. The exec went on to add that,
“The blockchain-based AI protocols embody the principles of decentralization, accessibility, and transparency, and the Grayscale team feels strongly that these protocols can help mitigate the fundamental risks emerging alongside the proliferation of AI technology.”
The fund will target financing projects in three key areas: the development of chatbots, generative images, and other decentralized AI applications; tackling issues associated with centralized AI, such as deep fakes, misinformation, and authenticity checks against bots; and supporting AI-related infrastructure, including GPU computation, data storage, decentralized marketplaces, and various other services.
Centralization Risks in AI
In its official press release, Grayscale noted that the motivation behind the debut of the fund is the fact that artificial intelligence is largely centralized to a handful of notable companies that are core to driving the technology’s development and mainstream adoption.
In response to the continued technological advancements and practical needs, several decentralized AI companies or protocols have surfaced which are designed to utilize the full potential of AI technology.
The asset manager pointed out that these entities also address some of the limitations and risks associated with centralization. These decentralized AI initiatives, which utilize blockchain technology to distribute ownership and governance, provide unrestricted access to AI technologies and improve transparency.
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