Interpretability is the science of how neural networks work internally, and how modifying their inner mechanisms can shape their behavior--e.g., adjusting a reasoning model's internal concepts to ...

Throw AI a vague question, and what you’ll get back will likely sound plausible enough to be true, even if the question isn’t meant to have a real answer. But from the response you get back, it might ...

Scientists at Hopkins, University of Florida simulate and predict human behavior during wildfire evacuation, allowing for improved planning and safety ...

Microsoft’s research shows how poisoned language models can hide malicious triggers, creating new integrity risks for ...

Learn how Microsoft research uncovers backdoor risks in language models and introduces a practical scanner to detect tampering and strengthen AI security.

In its research, Microsoft detailed three major signs of a poisoned model. Microsoft's research found that the presence of a backdoor changed depending on where a model puts its attention. "Poisoned ...

Looking to scale emotional intelligence training across your organization? Here are 5 key lessons from 40 expert interviews ...

Most people don’t consider the ease or difficulty of training a dog when they choose their dog -- perhaps you should.

As work, technology and human expectations evolve and converge, many once-ubiquitous ideas and so-called leadership “best ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Practitioner-Developed Framework Withstands Scrutiny from Top Behavioral Scientists and Leading LLMs, Certifies Its ...

Moonshot AI’s Kimi K2.5 Reddit AMA revealed why the powerful open-weight model is hard to run, plus new details on agent ...