leewayhertz

Vision Transformer Model: Architecture, development and applications

In recent years, deep learning has profoundly impacted computer vision and image processing, bringing about significant advancements and changes. Convolutional neural networks (CNNs) have been the ...
TechSpot

Meet Mu, the small language model in charge of Microsoft's Settings AI agent

In brief: Small language models are generally more compact and efficient than LLMs, as they are designed to run on local hardware or edge devices. Microsoft is now bringing yet another SLM to Windows ...
TechRepublic

Microsoft’s Mu Brings Natural Language Chats to Windows 11’s Settings Menu

A screenshot of Mu performing real-time question answering. Image: Windows YouTube channel The Mu small language model enables an AI agent to take action on hundreds ...
IEEE

Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction

Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
VentureBeat

Meta's new BLT architecture replaces tokens to make LLMs more efficient and versatile

The AI research community continues to find new ways to improve large language models (LLMs), the latest being a new architecture introduced by scientists at Meta and the University of Washington.
IEEE

Fusing Brilliance: Evaluating the Encoder-Decoder Hybrids With CNN and Swin Transformer for Medical Segmentation

Abstract: U-Net has become a standard model for medical image segmentation, alleviating the challenges posed by the costly acquisition and labeling of medical data. The convolutional layer, a ...