Google's TurboQuant compression tech cuts LLM memory use by 6x with no accuracy loss

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Google, Cohere launch new audio AI models

Google LLC and Cohere Inc. today released new artificial intelligence models optimized for audio processing tasks.  The ...
Scientific Research Publishing

FOCUS-Net: A Hybrid Denoising and Confidence-Weighted Attention Fusion Framework for Robust Alzheimer’s Disease Classification from MRI Data ()

1 Department of Computing and Informatics, University of Nairobi, Nairobi, Kenya. 2 Department of Computer Science, Mountains of the Moon University, Fort Portal, Uganda. Alzheimer’s Disease (AD) is a ...
www.cs.cmu.edu

Winding numbers: a topological tool for geometry processing

This post explains the key findings and algorithm of our 2023 SIGGRAPH paper “Winding Numbers on Discrete Surfaces” . What problem does this paper solve? For a given point on a surface, we would like ...
American Bar Association

Inhuman Reason: Predictive Policing Algorithms and the Fourth Amendment

Several law enforcement agencies have used or are currently using artificial intelligence to process data on how crime varies geographically, looking at trends to inform where they police. Beyond ...
EDN

Single-supply single-ended input to pseudo class A/B differential output amp

From the micromixer topology by Barrie Gilbert [1], this amplifier allows a single-ended input to be converted to a Class A/B current output from a single supply. Wow the engineering world with your ...
IEEE

Fast Imaging Algorithm for Layered Dielectrics Based on Spatial Inhomogeneous Single-Input Single-Output Array

Abstract: Array-based millimeter wave (MMW) holographic imaging technology has shown great application potential in nondestructive evaluation (NDE) of dielectric materials (such as composites). With ...
Frontiers

A three-step, “brute-force” approach toward optimized affine spatial normalization

The first step in spatial normalization of magnetic resonance (MR) images commonly is an affine transformation, which may be vulnerable to image imperfections (such as inhomogeneities or “unusual” ...