Embodied AI world models drew $6 billion in Q1 2026 alone, but new analysis from Fusion Fund investors argues the LLM scaling ...

The AI model type capturing the most attention across robotics and autonomous vehicles right now is the vision-language-action model, or VLA. At embedded AI conferences this year, particularly the ...

Abstract: The integration of visual and textual data in Vision- Language Pre-training (VLP) models is crucial forenhancing vision-language understanding. However, the adversarial robustness of these ...

Introduction: Echocardiography is essential for cardiac assessment, yet interpretation requires substantial expertise and suffers from inter-observer variability. Current AI approaches often rely on ...

Vision-Language Action (VLA) models have enabled language-driven robotic manipulation by integrating language instructions, visual perception, and action generation. However, existing VLA approaches ...

I've often wondered if the way in which individuals view and treat their own and other dogs is related to how they view animal-human relationships in general. Based on discussions with many people, I ...

Speculative decoding is a widely adopted technique for accelerating inference in large language models (LLMs), yet its application to vision-language models (VLMs) remains underexplored, with existing ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...

A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to ...

A much faster, more efficient training method developed at the University of Waterloo could help put powerful artificial intelligence (AI) tools in the hands of many more people by reducing the cost ...