Most AI today runs inside massive data centers powered by GPUs from companies like NVIDIA

Most AI today runs inside massive data centers powered by GPUs from companies like NVIDIA.

But a different layer of AI infrastructure is emerging: Edge AI.

Instead of sending data to the cloud, AI models run directly on the device itself — inside robots, drones, cameras, and industrial machines.

Enabling this shift requires a different type of processor.

Not GPUs.

But Neural Processing Units (NPUs) — chips specifically designed to run AI models efficiently with very low power consumption.

One company working in this space is DEEPX.

The startup is building AI processors designed for edge environments, where devices must process data locally and respond in real time.

Their architecture focuses on:

• high performance per watt
• low power consumption
• real-time AI processing

Why does this matter?

Because many real-world AI systems cannot rely on the cloud. Robots, factories, and autonomous machines require instant decisions, often with limited connectivity.

Running AI locally enables:

• faster response times
• lower bandwidth usage
• improved reliability

In other words, AI is slowly shifting from centralized intelligence in data centers to distributed intelligence across millions of devices.