Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Content scoring tools work, but only for the first gate in Google’s pipeline

Google’s first-stage retrieval still runs on word matching, not AI magic. Here’s how to use content scoring tools accordingly ...
Psychology Today

Diagnosing Schizophrenia With Machine Learning

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
Tech Xplore

Jailbreaking the matrix: How researchers are bypassing AI guardrails to make them safer

A paper written by University of Florida Computer & Information Science & Engineering, or CISE, Professor Sumit Kumar Jha, Ph ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences (CAS), has developed an innovative machine learning framework ...
fandomwire

The Matrix Symbolism: What Every Character Stands for in the Franchise

The name Neo is an anagram for the One, directly hinting at his destiny as the messiah who will save humanity. At the climax of The Matrix (1999), Neo is killed by Agent Smith and then resurrected, ...
Frontiers

Non-destructive detection of microplastics stress in rice seedling: an interpretable deep learning approach using excitation emission matrix fluorescence spectra of root exudates

Introduction: Microplastics (MPs), ubiquitous and insidious pollutants pervading agricultural systems, pose an escalating threat to global food security. This makes the development of nondestructive ...
IEEE

Robust Deep Matrix Factorization With Low-Rank and Hypergraph Learning for Multi-View Data Processing

Abstract: As the advancement of sensing technology and cyber-physical equipment, the complexity and dimensionality of the data from Consumer Internet of Things have increased dramatically. Processing ...
Frontiers

Interleaving cortex-analog mixing improves deep non-negative matrix factorization networks

1 Institute for Theoretical Physics, University of Bremen, Bremen, Germany 2 Institute of Electrodynamics and Microelectronics (ITEM.ids), University of Bremen, Bremen, Germany Considering biological ...
IEEE

Non-Negative Matrix Factorization and Latent Semantic Analysis for Hybrid Feature Selection: A Proposed Machine Learning System for the Detection of Malicious Executable Files

Abstract: During a typical cyber-attack lifecycle, several key phases are involved, including footprinting and reconnaissance, scanning, exploitation, and covering tracks. The successful delivery of a ...