Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...

Explore how Quantization Aware Training (QAT) and Quantization Aware Distillation (QAD) optimize AI models for low-precision environments, enhancing accuracy and inference performance. As artificial ...

Running the example script llm-compressor/examples/quantization_w4a4_fp4/llama3_example.py results in a runtime error. Full traceback is included below.

ENOB describes an analog-to-digital converter’s performance with respect to total noise and distortion. In the earlier parts of this series on analog-to-digital converters (ADCs), we looked at the ...

I'm diving deep into the intersection of infrastructure and machine learning. I'm fascinated by exploring scalable architectures, MLOps, and the latest advancements in AI-driven systems ...

Specifications such as gain error, offset error, and differential nonlinearity help define an analog-to-digital converter’s performance. In part 1 of this series, we discussed an ideal ...

I trained a YOLOv11n model at 192x192 resolution and attempted to quantize it using PPQ with espdl_quantize_onnx. However, I encountered a runtime error during the ...

The cuts, highlighted on an earlier version of the “wall of receipts” posted by Elon Musk’s team, contained mistakes that vastly inflated the amount of money saved. By David A. Fahrenthold Aatish ...