AI Is Learning to Do the Jobs of Doctors, Lawyers, and Consultants

Researchers tested AI on hundreds of high-value professional tasks and found models are improving—but not yet ready to do the ...
Major League Baseball

Way-too-early mock: Predicting '26 Draft picks 1-10

Because the MLB Draft Lottery won't happen until this winter, we don't know the 2026 Draft order yet. But that doesn't mean ...

Deep learning tool developed to unravel molecular mechanisms of convergent evolution

Convergent evolution—where distinct species independently evolve similar traits or functions, such as the wings of birds and ...
EurekAlert!

Exploring a novel approach for improving generative AI models

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving ...
Major League Baseball

Yankees Magazine: Learning Curve

It is the night before Max Fried is scheduled to take the ball at Yankee Stadium, and he describes the scene this way: He is ...
eLife

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep Learning

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...
Daily Journal

Man with same name as Babe Ruth charged with using old baseball players' names for settlement fraud

GREENEVILLE, Tenn. (AP) — A Tennessee man with the same name as New York Yankees legend Babe Ruth is facing charges alleging that he used the names of hundreds of dead or retired pro baseball players ...
eLife

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

This study presents DeepTX, a valuable methodological tool that integrates mechanistic stochastic models with single-cell RNA sequencing data to infer transcriptional burst kinetics at genome scale.
Frontiers

Construction of a deep - learning - based rehabilitation prediction model for lower-limb motor dysfunction after stroke using synchronous EEG-EMG and fMRI

Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...
IEEE

Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data

Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

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 ...
IEEE

Algebraic Expressions for Complex Deep Learning Systems Modeling and Analysis

Abstract: Many modern Deep Learning (DL) systems have achieved impressive state-of-the-art results by combining individual sub-systems, including foundation models, to form increasingly more complex ...