Artificial Intelligence isn’t only about cloud data centres crunching billions of parameters. Increasingly, the action happens at the edge — in your phone, your car, your wearable, or even in a tiny sensor on a factory floor.
But the edge is a tricky environment. Power is limited, heat budgets are tight, latency needs are real-time, and connectivity may be patchy. That’s why a diverse landscape of edge AI chip architectures has emerged.
At Novomorphic, we’ve broken this complexity down into seven super categories that cover almost every architecture powering edge AI today. Let’s dive in.
| Feature | Strength | Weakness |
|---|---|---|
|
Flexibility |
Handles diverse AI + non-AI tasks |
Requires optimization |
|
Power use |
Powerful but energy-hungry |
Not ideal for battery devices |
|
Ecosystem |
Mature tools (CUDA, OpenCL, DSP SDKs) |
Complexity in tuning |
