In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...

Users around the world have rushed to adopt artificial intelligence—especially in safety-critical fields—but a new study has revealed the hype has prioritized technology for technology's sake instead ...

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...

A new review titled Artificial Intelligence and the Discovery of Antibiotics: Reinventing with Opportunities, Challenges, and ...

This challenge is examined in Application of AI in Cyberattack Detection: A Review, published in the journal Sensors, where researchers explore how artificial intelligence techniques, from ensemble ...

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 ...

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...

In an era where AI adoption frequently outpaces regulatory readiness, Archana Pattabhi, Senior Vice President at a leading global bank, led a forward-looking transformation that redefined how ...

How are AI Agents transforming DeFi? From autonomous risk management to liquidity optimization and smart contract security, ...