-- Decentralized AI infrastructure platform GemiGPT has announced the integration of its compute architecture with the high-performance, energy-efficient data centers of Microsoft Azure. This upgrade ushers in a hybrid model of “high-end infrastructure + decentralized execution,” accelerating the expansion of the platform into a globally distributed, green AI network.
Microsoft Azure—one of the the most advanced AI compute ecosystems of the world—offers globally deployed GPU clusters and high-throughput inference services optimized for performance and sustainability. GemiGPT will now offload large-scale inference and compression tasks to Azure nodes, while its GPT-NEXUS micro-task engine continues to schedule edge-level jobs across its decentralized network. The result is a hybrid architecture built around a “green core + decentralized edge” model.
“We do not view centralization and decentralization as mutually exclusive,” said Ethan Calloway Maya, a GemiGPT representative. “A truly global AI network must balance performance, scalability, and environmental sustainability.”
At the heart of this transition is the adoption of the green compute clusters of Azure for heavy workloads, while maintaining the Flow-Vault clean-energy node network to handle edge inference and data interactions. In parallel, the GPT-SAFE module of GemiGPT has been adapted to meet cross-jurisdictional compliance and data privacy standards—supporting full-chain task traceability and encrypted processing across both centralized and decentralized environments.
This architecture not only improves model response speed and system resilience but also establishes the technical foundation for a sustainable, globally distributed AI model training framework.
Founded by former OpenAI researcher Ethan Calloway and ex-Head of Azure Global Infrastructure Maya, the GemiGPT core team includes alumni from MIT, the Polygon Web3 ecosystem, and major AI infrastructure divisions across leading cloud platforms. The team has conducted technical collaborations with the MIT Artificial Intelligence Lab, focusing on decentralized compute frameworks, green energy scheduling, and trustless model verification protocols.
Key innovations such as the dynamic task sharding of GPT-NEXUS and the clean energy incentives of Flow-Vault reflect this shared vision for a “global public AI compute” infrastructure.
By fusing green master nodes, decentralized distribution, and intelligent governance under one architectural framework, GemiGPT is shaping a prototype for post-AI infrastructure. The team believes that the next generation of AI will not be born in Silicon Valley but will emerge from green nodes across the Sahara, Southeast Asia, and Latin America—bringing decentralized intelligence to a global stage.
Contact Info:
Name: Nina Kartika
Email: Send Email
Organization: GemiGPT Neural Systems Inc.
Website: https://www.gemigpt.com
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