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 ...
SDxCentral

FriendliAI may have the inference solution to AI memory ills

FriendliAI also offers a unique take on the current memory crisis hitting the industry, especially as inference becomes the dominant AI use case. As recently explored by SDxCentral, 2026 is tipped to ...
Semiconductor Engineering

Neural Network Model Quantization On Mobile

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...
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 University of California San Diego and San Diego State University. Abstract ...