Semiconductor Engineering

Balancing Training, Quantization, And Hardware Integration In NPUs

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

Outlier-aware Quantization Framework Co-designed With Heterogeneous NVM For SLM Deployment on Edge Platforms (UCSD et al.)

Efficient SLM Edge Inference via Outlier-Aware Quantization and Emergent Memories Co-Design” was published by researchers at ...
Forbes

How Mixed-Precision Quantization Could Break AI’s Power Addiction

It turns out the rapid growth of AI has a massive downside: namely, spiraling power consumption, strained infrastructure and runaway environmental damage. It’s clear the status quo won’t cut it ...
InfoWorld

What is model quantization? Smaller, faster LLMs

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...
InfoWorld

Model quantization and the dawn of edge AI

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...