In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in critical applications like healthcare and autonomous driving.

Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know ...

Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...

Modern human and veterinary medical interventions to combat infectious diseases depend on the continued efficacy of ...

2024 is going to be a huge year for the cross-section of generative AI/large foundational models and robotics. There’s a lot of excitement swirling around the potential for various applications, ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

The Bohr Model of Hydrogen revolutionized our understanding of atomic structure and behavior. In this video, we simplify the calculations of force and velocity within the hydrogen atom using Bohr’s ...

People's decisions are known to be influenced by past experiences, including the outcomes of earlier choices. For over a century, psychologists have been trying to shed light on the processes ...