AI-Driven Crypto Sector Dominated by Bittensor and NEAR: Grayscale's New Classification
PorAinvest
domingo, 13 de julio de 2025, 7:39 pm ET1 min de lectura
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Bittensor, with a market capitalization of $3.8 billion, leads the AI Platforms category, followed by Near Protocol with a market cap of $3.5 billion. This shift underscores the pivotal role these platforms play in delivering scalable infrastructure for AI-blockchain applications. Other notable projects include Render Network (RENDER) at $2.5 billion, Artificial Superintelligence Alliance (FET) at $2.3 billion, and Worldcoin (WLD) at $2.1 billion, reflecting AI’s broad utility in blockchain ecosystems.
The report also categorizes lower-cap projects under the AI Tools & Resources and AI Apps & Agents subcategories. These projects contribute to the development of decentralized networks that support AI deployment in user-facing services and operational backends. Micro-cap tokens like Venice.ai (VVV), Golem (GLM), and io.net, each valued below $300 million, are included for their focus on decentralized infrastructure and resource-sharing mechanisms.
Grayscale’s classification provides a comprehensive overview of how blockchain technology is evolving alongside AI. As institutional capital continues to flow into these projects, they are expected to play a foundational role in shaping the future of decentralized technology.
References:
1. [https://coinedition.com/ai-focused-crypto-assets-gain-spotlight-in-latest-grayscale-report/](https://coinedition.com/ai-focused-crypto-assets-gain-spotlight-in-latest-grayscale-report/)
2. [https://cybersecuritynews.com/openai-web-browser/](https://cybersecuritynews.com/openai-web-browser/)
Bittensor (TAO) and Near Protocol (NEAR) lead the AI crypto sector with a combined market capitalization of over $7 billion. Grayscale's report introduces a new classification of 17 AI-related assets, with TAO and NEAR dominating the AI Platforms category. Other notable projects include Render Network (RENDER), FET, and Worldcoin (WLD), highlighting AI's role in compute, model hosting, and blockchain-based agent services. Micro-cap projects offer decentralized access to data, compute, and AI tools for scalable deployment across various blockchain networks.
Bittensor (TAO) and Near Protocol (NEAR) have emerged as the dominant players in the AI crypto sector, with a combined market capitalization exceeding $7 billion, according to the latest Grayscale report [1]. The report introduces a new classification of 17 AI-related assets, highlighting the growing intersection of blockchain infrastructure and artificial intelligence (AI) capabilities.Bittensor, with a market capitalization of $3.8 billion, leads the AI Platforms category, followed by Near Protocol with a market cap of $3.5 billion. This shift underscores the pivotal role these platforms play in delivering scalable infrastructure for AI-blockchain applications. Other notable projects include Render Network (RENDER) at $2.5 billion, Artificial Superintelligence Alliance (FET) at $2.3 billion, and Worldcoin (WLD) at $2.1 billion, reflecting AI’s broad utility in blockchain ecosystems.
The report also categorizes lower-cap projects under the AI Tools & Resources and AI Apps & Agents subcategories. These projects contribute to the development of decentralized networks that support AI deployment in user-facing services and operational backends. Micro-cap tokens like Venice.ai (VVV), Golem (GLM), and io.net, each valued below $300 million, are included for their focus on decentralized infrastructure and resource-sharing mechanisms.
Grayscale’s classification provides a comprehensive overview of how blockchain technology is evolving alongside AI. As institutional capital continues to flow into these projects, they are expected to play a foundational role in shaping the future of decentralized technology.
References:
1. [https://coinedition.com/ai-focused-crypto-assets-gain-spotlight-in-latest-grayscale-report/](https://coinedition.com/ai-focused-crypto-assets-gain-spotlight-in-latest-grayscale-report/)
2. [https://cybersecuritynews.com/openai-web-browser/](https://cybersecuritynews.com/openai-web-browser/)

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