In my previous article, I discussed the importance of AI explainability and the different categories of AI explainability, explainable predictions, explainable algorithms and interpretable ...

When AI falters, it’s easy to blame the model. People assume the algorithm got it wrong or that the technology can’t be trusted. But here’s what I've learned after years of building AI systems at ...

Explainable AI provides human users with tools to understand the output of machine learning algorithms. One of these tools, feature attributions, enables users to know the contribution of each feature ...

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...

While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an unsolved problem in physics. To gain insight into the system, a team of ...

An AI tool has made a step forward in translating the language proteins use to dictate whether they form sticky clumps similar to those linked to Alzheimer's Disease and around fifty other types of ...

An area of great hope and promise for applied artificial intelligence (AI) deep learning is at the intersection of neuroscience and oncology, both challenging fields known for their inherent ...

A team has developed an explainable AI model for automatic collision avoidance between ships. The Titanic sunk 113 years ago on April 14-15, after hitting an iceberg ...

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights – including a model-estimated probability score ...

In todays fast evolving financial landscape, artificial intelligence and machine learning are changin how credit decisions get made. But the traditional “black box” models cause worry 'cause nobody ...