Edge Computing

Edge computing moves processing power from centralized cloud data centers to locations closer to where data is generated and consumed—in cell towers, local servers, retail locations, factories, and even on-device. It's the architectural shift that makes low-latency AI, real-time gaming, and spatial computing possible at scale.

The fundamental problem edge computing solves is physics: the speed of light imposes minimum latency on any round-trip to a distant data center. For applications that require millisecond-level response times—AI agents making real-time decisions, multiplayer gaming, autonomous vehicles, augmented reality overlays—that latency is unacceptable. Edge computing brings the computation to within a few miles of the user rather than hundreds or thousands.

By 2026, edge computing has matured from emerging technology to critical, mainstream infrastructure. The shift has been driven primarily by the need to support AI-driven applications at the point of interaction. Running LLM inference at the edge allows AI agents to operate with the responsiveness users expect, without the cost and latency of routing every request to a central cloud.

Edge computing works in concert with 5G networks, which provide the high-bandwidth, low-latency wireless connectivity needed to reach edge-deployed compute. Together, they form the infrastructure substrate for the agentic web—where AI agents operate fluidly across cloud, edge, and device, choosing the optimal execution point for each task based on latency, cost, and privacy requirements.