DeepSeek’s Engram Conditional Memory Shows How to Reduce AI Compute Waste

DeepSeek's new Engram AI model separates recall from reasoning with hash-based memory in RAM, easing GPU pressure so teams run faster models for less.

AI-Generated Mental Health Advice Must Shift From Discrete-Classifications To Continuous Multidimensional Psychological Analyses

Mental health is not to be reduced to simple discrete classifications, but that's what AI is doing to us. AI can be ...
devdiscourse

Cities are drowning in waste and data-driven systems may be the only way out

Cities around the world are struggling to keep pace with rising volumes of municipal, industrial, and hazardous waste as urbanization, consumption, and population density intensify. Traditional waste ...
IEEE

Comparison of Deep-Learning Models for Classification of Cellular Phenotype From Flow Cytometry Data

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...
IEEE

Pattern-Based Feature Extraction for Improved Deep Learning in Financial Time Series Classification

Abstract: In this paper, the authors introduce a novel feature extraction method based on pattern detection in financial data to enhance the performance of deep learning models for financial time ...