New algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.

More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.

Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.

MAIA is a multimodal agent that can iteratively design experiments to better understand various components of AI systems.

A new study shows someone’s beliefs about an LLM play a significant role in the model’s performance and are important for how it is deployed.

Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.

A new technique enables users to compare several large models and choose the one that works best for their task.

New CSAIL research highlights how LLMs excel in familiar scenarios but struggle in novel ones, questioning their true reasoning abilities versus reliance on memorization.

This new tool offers an easier way for people to analyze complex tabular data.

The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.