Illia Polosukhin, co-founder of NEAR Protocol, has set out the 'AI money' thesis behind NEAR. Writing on Twitter (X), he stressed that staking NEAR gives users access to confidential inference and to IronClaw's always-on agents. The thesis frames NEAR as a means of broadening access to decentralized finance through user-owned intelligence.

The Key Development

The broader crypto market is currently marked by mixed signals, with a range of assets showing fluctuating momentum. Within that environment, NEAR Protocol's focus on integrating AI into its ecosystem stands out, a focus reinforced by Polosukhin's own background: before co-founding NEAR, he worked at Google and co-authored the 2017 paper 'Attention Is All You Need,' which introduced the Transformer architecture that underpins today's large language models. Polosukhin's argument that staking NEAR can unlock sophisticated AI access could draw interest from users seeking innovative financial solutions, a move that aligns with the ongoing evolution of decentralized technologies as projects look to leverage AI for improved user experiences.

Quick Take

• Illia Polosukhin highlights NEAR's AI money thesis.
• Staking enables access to confidential inference.
• IronClaw's always-on agents become available through staking.
• User-owned intelligence is emphasized.
• NEAR seeks to enhance decentralized finance solutions.

What the Data Shows

NEAR is currently recorded at $0, with no reported trading volume over the past 24 hours, according to the report. The lack of volume reflects a broader market trend in which many cryptocurrencies are experiencing reduced trading activity, although continued development within NEAR's ecosystem, particularly its approach to AI and user intelligence, could spark renewed interest.

NEAR Protocol, a sharded proof-of-stake layer-1 blockchain whose mainnet launched in 2020, is a decentralized platform designed to support the development of applications and services. Its focus on AI integration places it in a competitive landscape of blockchain technologies aiming to deepen user engagement and capabilities, a field that includes projects such as Bittensor and the Artificial Superintelligence Alliance building at the intersection of blockchain and machine learning. Confidential inference, the privacy-preserving execution of AI models referenced by Polosukhin, has become an area of growing focus as AI adoption raises questions about who controls user data, and NEAR's emphasis on user-owned intelligence corresponds to growing demand for decentralized solutions that prioritize individual control and privacy.

Key Levels to Watch

The report points to several factors for traders and investors to monitor: AI integration could encourage greater user adoption and engagement, while staking rewards and access to advanced technologies may strengthen NEAR's market position. Overall performance, it adds, will depend on broader market trends and regulatory developments in the crypto space.

Source: Coinfomania