Shaping a New Compute Economy
In the digital era, computing power has become the core infrastructure supporting artificial intelligence (AI), decentralized finance (DeFi), real-time data analytics, and next-generation Web3 applications. Yet, today's compute supply chains are facing unprecedented pressure.
According to IDC, the global demand for AI computing power is growing at a compound annual growth rate (CAGR) of over 26%, expected to reach more than $422 billion USD in related infrastructure spending by 2027. Meanwhile, Gartner forecasts that over 60% of enterprises will integrate AI workflows by 2025, further straining computational needs.
Despite this surging demand, the compute market remains highly centralized and inefficient:
Over 70% of global computational supply is locked inside a few hyperscale data centers.
A staggering 50%–60% of everyday devices' CPU/GPU capacity sits idle for most of the day (Source: McKinsey Digital Report, 2024).
Traditional centralized server farms account for over 2% of global electricity consumption, contributing significantly to carbon emissions (IEA Data, 2023).
This creates a critical supply gap between the rising demand for scalable, cost-effective, eco-friendly compute power and the inefficiency of current centralized models.
Here lies the opportunity:
Distributed idle computing — tapping into the vast, underutilized resources already deployed in users' desktops, browsers, and mobile devices — can reshape the compute economy.
It promises a low-barrier, eco-first, massively scalable alternative to traditional cloud and server infrastructures.
This is where Grid steps in — bridging the gap between idle hardware and real-world computational tasks through a decentralized, community-driven network, while enabling users to monetize unused power seamlessly.
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