MIT researchers use large language models to flag problems in complex systems
The approach can detect anomalies in data recorded over time, without the need for any training.
The approach can detect anomalies in data recorded over time, without the need for any training.
New algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.
CSAIL researchers introduce a novel approach allowing robots to be trained in simulations of scanned home environments, paving the way for customized household automation accessible to anyone.
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.
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.