Tag: Embedded Systems

Why TOPS Doesn’t Matter: How to Choose the Right Edge AI Chip for Wearables

A few months ago, if someone had asked me to compare AI chips for wearables, I probably would have started with the biggest TOPS number on the spec sheet. That's what most product launches highlight, and it's easy to assume…

Quantization vs Pruning: Optimizing LLMs for Edge Devices

QuantizationPruningArchitectural DifferencesLatencyTOPS (Tera Operations Per Second)Power ConsumptionMemory Footprint & BandwidthSoftware EcosystemDeployment ConsiderationsWhich Design Is More EfficientKey Takeaways This Quantization vs Pruning comparison explains how both optimization strategies affect edge LLM deployment efficiency. For large language models (LLMs) on edge devices, quantization primarily optimizes the numerical…

Snapdragon X2 Elite NPU: ARM’s 80 TOPS Architecture for Copilot+ PCs

As AI features become increasingly common in modern laptops, dedicated AI hardware is becoming more important. The Snapdragon X2 Elite NPU is designed to accelerate on-device AI tasks such as real-time transcription, image enhancement, AI assistants, and local language models…