Your AI might look smart on benchmarks but could be brittle in the real world, leading to unexpected failures and eroding ...

Just as no serious business today can operate without an internet strategy, no life sciences organization will remain ...

Microsoft, MS, has drawn industry attention with an artificial intelligence (AI) paper it released late last month. The AI ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional ...

Every fantasy season, deep sleepers emerge from the shadows—players buried on depth charts or overlooked on draft day who end up swinging matchups. These are the players worth circling in 2025, the ...

This repository helps interpret SAEs and transcoders trained on protein-level representations from ESM2 using both GO Analysis and automated LLM-assisted interpretations, and SAEs trained on amino ...

Abstract: Deep reinforcement learning (DRL) has emerged as a promising solution for autonomous operations of autonomous aerial vehicles (AAVs) in unknown environments. However, learning to navigate ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Introduction: Predicting the relationship between diseases and microbes can significantly enhance disease diagnosis and treatment, while providing crucial scientific support for public health, ...

College of Mathematics and Statistics, Northwest Normal University, Lanzhou, China. Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the ...

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...