Easy-to-use adaptive immersive technologies incorporating augmented reality (AR) can motivate learning, social engagement and ...

Learn how NVIDIA's latest AI model processes video 10 times faster than real-time and optimizes multimodal data for ...

Early adopters are using the model for diverse applications, such as auto-clipping highlights from live sports, which ...

This repository is the official Pytorch implementation for the paper Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning. If you have any questions, please ...

Read more about Quantum machine learning shows promise for adaptive learning, but classrooms are not ready on Devdiscourse ...

indie Semiconductor (Nasdaq: INDI), an automotive solutions innovator, has announced the signing of a definitive agreement to ...

As of May 2026, the AI landscape has undergone a seismic shift: the era of passive chatbots is over, replaced by autonomous agents capable of executing complex, multi-step tasks. This month, OpenAI, ...

Haptics: the science of touch and tactile perception has become a critical interface for interacting with both virtual and physical environments. Recent ...

AI applications in 2026 power real-world industries with tools for healthcare, transport, finance, education, and automation ...

In this post, we share the motivations, design choices, experiments, and learnings that informed its development, as well as an evaluation of the model’s performance and guidance on how to use it. Our ...

Abstract: This study aims to explore the application of multimodal deep learning models in power system fault diagnosis. To effectively integrate SCADA time-series data and fault waveform image ...