Background

Manifold Secures $10.5M for Decentralized AI Expansion

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manifold series a funding
Key Points:
  • Manifold’s $10.5M Series A to scale Targon platform.
  • Targon serves over 20 billion inference tokens daily.
  • Investment aligns with growing decentralized AI infrastructure interest.
manifolds-series-a-funding-to-expand-decentralized-ai-platform
Manifold’s Series A Funding to Expand Decentralized AI Platform

Manifold raised $10.5M in a Series A round led by OSS Capital to enhance its Targon platform. The funding aims to bolster decentralized AI infrastructure, benefiting the Bittensor network by supporting over 20 billion daily inference tokens.

Maga

This funding marks a significant industry move towards decentralized AI infrastructure, with Targon facilitating over 20 billion daily tokens.

Funding and AI Expansion

Manifold aims to scale its Targon AI platform through $10.5 million raised in Series A. OSS Capital leads the round, emphasizing decentralized, confidential AI cloud solutions.

Key Players and Network Impact

Key players include OSS Capital, Digital Currency Group, and Shopify’s Tobi Lütke, among others. Targon, based on the Bittensor network, positions itself as a new decentralized AI category.

Infrastructure and Economic Activity

Targon serves over 20 billion inference tokens and operates more than 1,500 GPU nodes, impacting TAO, Bittensor’s native asset. There’s no immediate effect on ETH or BTC markets.

Jacob Steeves, Co-founder, Bittensor, “Targon represents a fundamentally new category: a decentralized, verifiably confidential, and trustless AI cloud.”

Future of Decentralized AI

Enhanced decentralized AI incentives backed by investment signal shifts in infrastructure, bypassing traditional ventures. The initiative is expected to attract greater TAO economic activity.

The funding echoes a trend toward decentralized infrastructure, suggesting potential for subsequent AI-dependent tech developments. As projects like Targon gain traction, decentralization’s role in AI and cloud computing will likely expand.

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