Tech Times

Recursive Self-Improvement Now Has a Co-Evolving Evaluator: Cambridge-NVIDIA Paper Raises the Stakes

Recursive self-improvement AI now has a co-evolving evaluator: a Cambridge and NVIDIA preprint introduces the Red Queen Gödel ...
Tech Xplore

Ferroelectric memory enables one chip to sample randomness and compute for generative AI

For the first time, a research team has demonstrated an artificial intelligence semiconductor technology that integrates the ...

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 ...
Eos

Machine Learning Rediscovers Equations Governing Ocean Biogeochemistry

Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.

From 15 hours to one minute: How AI/ML is speeding up GM’s development

And they just kind of iterated their way to something that was marginally feasible.” The first few hundred years of inventing “was this era of highly empirical iterative design development and ...
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 ...