How StrikePlagiarism.com’s Explainable AI delivers transparent, interpretable AI detection — helping educators ...

Despite that artificial intelligence (AI) has been eagerly awaited to substantially evolve the healthcare landscape across clinical decision-making processes, the clinical applicability of AI still ...

Building and scaling AI with trust and transparency is crucial for any organization. For explainable AI (XAI) to be effective, it must enable transparency, explain the predictions and algorithm and ...

Instead, developers should opt for AI models that are “inherently interpretable” and “provide their own explanations” Rudin discusses in her paper. And contrary to what some AI researchers believe, in ...

The calculation and/or the measurement of the thermal conductivity of materials is a fundamental challenge in materials science, essential for developing technologies in energy management, electronics ...

A collaborative research team led by Professor Pan Feng from the School of New Materials at Peking University Shenzhen Graduate School has developed a topology-based variational autoencoder framework ...

Researchers have developed a new, interpretable artificial intelligence (AI) model to predict 5-year breast cancer risk from mammograms, according to a new study published today in Radiology, a ...

What does it mean to build responsible, ethical AI? What government policies will shape the future of AI? Join Intel’s Melvin Greer, IBM’s Noelle Silver and Daniela Braga from Defined.ai as they ...

Hydrogen fuels represent a clean energy option, but a major hurdle in making its use more mainstream is efficient storage. Hydrogen storage requires either extremely high-pressure tanks or extremely ...

Machine learning models are incredibly powerful tools. They extract deeply hidden patterns in large data sets that our limited human brains can’t parse. These complex algorithms, then, need to be ...