Microsoft's new AI training method eliminates bloated system prompts without sacrificing model performance

Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...
IEEE

Fast Transfer Learning Method Using Random Layer Freezing and Feature Refinement Strategy

Abstract: Recently, Moore-Penrose inverse (MPI)-based parameter fine-tuning of fully connected (FC) layers in pretrained deep convolutional neural networks (DCNNs) has emerged within the inductive ...
Phys.org

AI method accelerates liquid simulations by learning fundamental physical relationships

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...
IEEE

An Efficient Inductive Learning Model for Inferring Gene Regulatory Networks

Abstract: Identifying gene regulatory networks (GRNs) from gene expression data has been a critical focus in systems biology. This paper proposes an efficient inductive learning framework based on a ...
Nature

Machine learning slashes the testing needed to work out battery lifetimes

Chao Hu is at the School of Mechanical, Aerospace, and Manufacturing Engineering, University of Connecticut, Storrs, Connecticut 06269, USA. The second category, data-driven lifetime prediction, uses ...
techxplore

Why reinforcement learning breaks at scale, and how a new method fixes it

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have an important impact. That may feel especially true, for example, when ...