Categories: AI/ML News

How hardware contributes to the fairness of artificial neural networks

Over the past couple of decades, computer scientists have developed a wide range of deep neural networks (DNNs) designed to tackle various real-world tasks. While some of these models have proved to be highly effective, some studies found that they can be unfair, meaning that their performance may vary based on the data they were trained on and even the hardware platforms they were deployed on.

When to Use MLP, CNN, and RNN Neural Networks

September 2, 2022

In "AI/ML Research"

ICLR 2017 vs arxiv-sanity

March 14, 2017

Artificial neuron merges DRAM with MoS₂ circuits to better emulate brain-like adaptability

The rapid advancement of artificial intelligence (AI) and machine learning systems has increased the demand for new hardware components that could speed up data analysis while consuming less power. As machine learning algorithms draw inspiration from biological neural networks, some engineers have been working on hardware that also mimics the…

August 31, 2025

In "AI/ML News"

AI Generated Robotic Content