io.net, a decentralized network designed to power large-scale machine learning, announced its partnership with TARS Protocol, a blockchain platform supported by the Solana Foundation. This collaboration aims to accelerate the integration of decentralized AI tools and Blockchain-as-a-Service (BaaS), benefiting developers and organizations in Web3 ecosystems.
io.net’s Expanding Decentralized AI Ecosystem
Integrating io.net’s decentralized GPU clusters and TARS Protocol’s AI-based solutions will enhance AI deployment. Consequently, the integration is expected to reduce AI model training times by up to 30%, providing a scalable system for Web3 applications. Additionally, this partnership will empower over 1,000 developers and businesses, providing them access to enhanced AI-powered services and tools.
This partnership enhances AI deployment and reduces operational costs while increasing system flexibility. Moreover, io.net’s network of 11,000+ distributed devices will now connect to TARS’ AI Hub, enabling faster AI model training and benefitting the growing decentralized AI infrastructure.
Collaborative Efforts to Expand Decentralized AI Infrastructure
io.net and TARS Protocol have committed to exploring ongoing joint marketing and development initiatives over the next 6 months. This collaboration opens new pathways for technical ecosystem expansion while pushing the limits of decentralized AI.
The shared mission of both FinTech firms is to provide a decentralized infrastructure, offering lower latency, faster AI deployments, and a robust environment for applications like AI operations and cloud gaming. io.net is already a key player in decentralized physical infrastructure networks (DePIN). Its system offers low-latency computing with thousands of GPUs, providing businesses and engineers with scalable solutions.
Hence, the partnership with TARS is essential to establishing a decentralized AI ecosystem. With the ability to scale GPU usage and reduce costs, io.net and TARS Protocol aim to support the growing demand for decentralized computing in industries like AI, gaming, and machine learning.
