A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an ...

Toyota Research Institute said its findings largely support the recent surge in popularity of LBM-style robot foundation ...

A major scientific advance in protein modeling developed by Microsoft Research AI for Science, has been published in Science.

Following the success of LLMs, the AI industry is now evolving with multimodal systems. In 2023, the multimodal AI market ...

Although machine learning (ML) techniques have advanced malware detection, they remain vulnerable to adversarial attacks. Current research primarily focuses on adversarial examples targeting single ML ...

Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities directly from ...

Machine learning and artificial intelligence (AI/ML) methods are beginning to have significant impact in chemistry and condensed matter physics. For example, deep learning methods have demonstrated ...

No previous knowledge of pattern recognition or machine learning concepts is assumed. This is the first machine learning textbook to include a comprehensive coverage of recent developments such as ...

Business schools are redesigning their curricula to produce graduates who interpret machine learning models, and make critical decisions in data-rich environments ...