Google DeepMind Releases MoR Architecture, Significantly Enhancing Inference Efficiency of Large Models

Google DeepMind has launched the MoR architecture: A revolutionary breakthrough in the inference efficiency of large models.

Google DeepMind Releases MoR Architecture, Significantly Enhancing Large Model Inference Efficiency

Google DeepMind Releases MoR Architecture: A Revolutionary Breakthrough in Large Model Inference Efficiency ...
ZDNet

Meta's 'data2vec' is a step toward One Neural Network to Rule Them All

The race is on to create one neural network that can process multiple kinds of data -- a more-general artificial intelligence that doesn't discriminate about types of data but instead can crunch them ...
Semiconductor Engineering

Convolutional Neural Networks: Co-Design of Hardware Architecture and Compression Algorithm

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
EE World Online

AI-native chip with integrates 2 MB SRAM, Cortex-M4F CPU and analog sensor interfaces

Ambient Scientific has introduced the GPX10 Pro, a system-on-chip designed specifically for edge AI applications. The device ...
Ars Technica

Optical neural network at 50zJ per op? Nope, but it’s still a good idea

Artificial intelligence (AI) has experienced a revival of pretty large proportions in the last decade. We've gone from AI being mostly useless to letting it ruin our lives in obscure and opaque ways.