The following is an opinion piece by Chris Anderson, CEO of ByteNova.AI, and does not necessarily reflect the positions of Global Crypto TV.
Artificial intelligence (AI) is straining the physical limits of modern cloud technology, a time when compute resources are scarce and workloads often go idle. Data centers that remain centralized were never built for an economy where model training windows were condensed from months to days.
Due to this fact, the next version of the internet will not reside on servers in a few hyperscale regions. What’s required is a decentralized compute fabric, woven from many operators offering compute capacity in many locations, dynamically routed to where it’s most cost-effective and efficient.
Why this matters is that AI workloads are extremely bursty and hungry for power and specialized hardware, and centralizing compute creates single points of inefficiency. When constrained by local power, cooling, network latency, and supply chains, the whole grid becomes bottlenecked.
The International Energy Agency projects that global data center electricity use could double by 2030, with AI as the primary driver. In the U.S., the power grid is already feeling the strain from the growing demands for AI compute. Together, these forces mean that simply building bigger server farms will not suffice in the long term.
Compute becomes a market
Imagine compute offered like electricity or internet bandwidth, there’d be many buyers, sellers, constant price discovery opportunities, and tiers of reliability. A node might advertise “24 H Hopper-GPU, 2ms latency to network, 99.9% uptime.” A scheduler selects one of many nodes based on price, latency, carbon intensity, or geographic risk.
In this dynamic, buyers pay only for the compute they use; sellers monetize idle capacity. This marketplace approach lowers costs, distributes risk, and improves utilization. Where clouds can’t build fast enough for AI buyers, decentralized compute networks offer smarter coordination of the compute we already have.
The likes of Cloudflare, Akash, and other networks now allow developers to bid for distributed computing directly, sometimes at half the cost of major cloud providers. As AI workloads scale into the zettabyte era, markets (not monopolies) will balance supply and demand.
Security, trust, and verification
It’s important to consider how one person can trust a job that’s running on another person’s machine; how is trust established? That’s where decentralized compute steps in: relying on verification of the information, not mere blind trust. With reproducible builds, cryptographic proofs, and hardware-level attestations, users can confirm that the promised GPU really did the work and returned an authentic result.
Systems like these turn anonymity into accountability, making reputation measurable, and assuring good performance earns repeat business. But, security isn’t the only issue; reliability matters too.
When a node fails, the workload can automatically re-route to another provider, similar to how internet packets reroute around outages commonly seen by internet providers from time to time. This flexibility is exactly what AI workflows require. Model training, simulation, and inference can continue uninterrupted, utilizing spare capacity throughout a decentralized network.
The new internet layer
The shift to decentralized computing represents more than a hardware change and is more aligned with creating a new market structure entirely. Cloud monopolies rely on ownership, whereas their decentralized counterparts rely on orchestration.
Whoever builds the standards for pricing, verifying, and clearing compute jobs at scale will determine what the next layer of the internet looks like and how it functions. Over time, this could resemble a global exchange for processing power, and compute become a liquid asset, one that’s hedged, bought, and sold in real-time.
The internet began as a network of networks, but this next internet layer could become a self-balancing market of markets, where computation flows to where it’s needed most. Centralized data centers will continue to exist, but they will be just one node in a larger web of compute providers within the decentralized network.
AI’s future depends on who can orchestrate the network of nodes, not who owns the servers. When compute becomes a verifiable, decentralized, and carbon-aware market, costs fall, innovation accelerates, and accessibility improves. The next internet won’t live in one place; it’ll live everywhere compute can be found, and trusted.
