Signal creator Moxie Marlinspike wants to do for AI what he did for messaging

Moxie Marlinspike—the pseudonym of an engineer who set a new standard for private messaging with the creation of the Signal ...
Tech Xplore

Discrete spatial diffusion models data while obeying scientific principles

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

Modern Agriculture Evolution: The Role of a China Best Tempered Greenhouse Glass Manufacturer in Vertical Farming

QINHUANGDAO, HEBEI, CHINA, January 8, 2026 /EINPresswire.com/ -- The global agricultural landscape is in a phase of ...
Tech Xplore

One image is all robots need to find their way

While the capabilities of robots have improved significantly over the past decades, they are not always able to reliably and ...
IEEE

Diffusion With Reinforcement Learning for Pedestrian Trajectory Prediction

Abstract: The trajectories of pedestrian movements involve uncertainty, requiring a predictive probability model capable of modeling the underlying multimodality. To predict the trajectory of ...
Microsoft

Machine Intelligence

Diffusion Language Models (DLMs) explores the potential of diffusion-based models to exceed the generative quality of traditional autoregressive language models, while overcoming their current ...
C&EN

3D Molecule Generation via Diffusion Model with a Self-Attention-Based EGNN

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Innovative drugs represent a critical approach to addressing ...
IEEE

Unsupervised Person Re-Identification with Diffusion Model via Semantic-Aware Disentanglement Representation Learning

Abstract: Unsupervised person re-identification (Re-ID) requires learning semantic representation without identity labels. Existing methods entangle identity-related person features with ...
marktechpost

DSRL: A Latent-Space Reinforcement Learning Approach to Adapt Diffusion Policies in Real-World Robotics

Robotic control systems have made significant progress through methods that replace hand-coded instructions with data-driven learning. Instead of relying on explicit programming, modern robots learn ...
C&EN

Development of an Interpretable Machine Learning Model for Neurotoxicity Prediction of Environmentally Related Compounds

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, P. R. China Sino-Danish College, ...