The Core of Human-Machine-Environment System Intelligent Communication: Seamless Connectivity and Multimodal Interaction The goal of Human-Machine-Environment System Intelligent Communication is to ...

Reinforcement learning (RL) [6] stands out as a powerful ML technique for training agents to achieve optimal behaviour in ...

It’s a looming challenge for homeland security as we race to integrate artificial intelligence into command, control, and ...

Google’s Strategic Acquisition of DeepMind A Landmark Deal in Artificial Intelligence Back in January 2014, Google made ...

1. From 'Simulating Humans' to 'Data-Driven': The Ultimate Goal and Implementation Path of AI ...

The Princeton team developed a "bullshit index" to measure and compare an AI model's internal confidence in a statement with ...

Discover how AI is reshaping industries, creating $10 trillion in value, and surpassing the industrial revolution in speed and scale. AI is ...

Current GUI grounding approaches rely heavily on large-scale pixel-level annotations and training-time optimization, which are expensive, inflexible, and difficult to scale to new domains. we observe ...

Depression treatment often involves a complex and lengthy trial-and-error process, where clinicians sequentially prescribe medications to identify the most effective ...

"In general, the actor-critic algorithm commonly used in reinforcement learning employs separate neural networks for the actor and the critic." While artificial neural networks (ANNs) were found to ...