Statistics education and reasoning constitute a fundamental area of inquiry in contemporary educational research. Scholars are increasingly exploring methods to enhance students’ abilities to ...

With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

Neuro-symbolic AI is a unique form of artificial intelligence that combines the strengths of neural and symbolic AI architectures. This powerful AI model can model cognition, learning, and reason, ...

Optimization and statistics are everywhere, touching all engineering disciplines in an ever more sophisticated way. Nowhere are they more important than in the rapidly evolving field of machine ...

Statistical machine learning is at the core of modern-day advances in artificial intelligence, but a Rochester Institute of Technology professor argues that applying it correctly requires equal parts ...

Scarlett Howard received funding from Australian Government Research Training Program (RTP) Scholarship, RMIT University, Fyssen Foundation, L’Oreal-UNESCO for Women in Science Young Talents French ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I continue my ongoing analysis of the ...

Companies like OpenAI and China’s DeepSeek offer chatbots designed to take their time with an answer. Here’s how they work. By Cade Metz and Dylan Freedman Cade Metz reported from San Francisco and ...

What if artificial intelligence could learn without any data? No datasets to train on, no human-labeled examples to guide it—just a system that evolves and improves entirely on its own. It sounds like ...