Small Language Models Outperform Frontier AI On Cost, Speed And Accuracy

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...

Beckhoff's TwinCAT CoAgent Accelerates Automation Programming with Built-In AI Tools

TwinCAT CoAgent delivers powerful AI-assisted engineering and programming support across every stage of the automation ...

Best AI-Native Loan Origination Platforms in 2026

Best AI-Native Loan Origination Platforms in 2026. Loan origination is being rebuilt around AI. I'm the founder of SecureLend ...
Slator

AI Translation’s Key Benchmark Takes Aim at Low-Resource Languages

The Eleventh Conference on Machine Translation (WMT26) has moved into its active evaluation phase, with test data releases and submission windows now opening across several of the conference’s shared ...
Tech Xplore

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
IEEE

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach

Several domains increasingly rely on machine learning in their applications. The resulting heavy dependence on data has led to the emergence of various laws and regulations around data ethics and ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

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