Connecticut Innovations Invests in Yuma Asset Management’s Bittensor Subnet Token Strategies

Connecticut Innovations Invests in Yuma Asset Management’s Bittensor Subnet Token Strategies
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Connecticut Innovations (CI) has invested in Yuma Asset Management’s subnet token strategies through its AI/Q Fund, marking another institutional step into decentralized AI (deAI).

Key Highlights:

  • Investor: Connecticut Innovations (CI)
  • Investment Vehicle: AI/Q Fund
  • Fund Manager: Yuma Asset Management, a firm focused on institutional access to Bittensor’s decentralized AI ecosystem
  • Objective: To expand exposure to Bittensor’s infrastructure and strengthen Connecticut’s position as a hub for emerging innovation

About Connecticut Innovations

Connecticut Innovations (CI) is the state’s strategic venture capital arm and the leading source of financing and ongoing support for Connecticut’s innovative, high-growth companies. CI provides access to capital, talent, and networks to help startups scale and position Connecticut as a center for technological advancement and entrepreneurship.

About Yuma’s Investment Strategies:

  • Yuma Subnet Composite Fund:
    • Modeled after the NASDAQ Composite
    • Offers market-cap weighted exposure across all active Bittensor subnets
  • Yuma Large Cap Subnet Fund:
    • Modeled after the Dow Jones Industrial Average
    • Focused on targeted exposure to top-performing subnets

What this investment means

  • The investment signals growing institutional confidence in Bittensor as the foundation for decentralized AI infrastructure.
  • Yuma’s products simplify access for investors by abstracting technical complexity, allowing participation in subnet markets without operating nodes or managing on-chain assets.
  • Each subnet in the Bittensor ecosystem represents a unique market for AI model development, enabling scalable and open innovation.

This move reinforces Connecticut’s leadership in supporting next-generation AI and blockchain ventures while advancing institutional integration with decentralized intelligence networks.

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