2024年7月– date –
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Method prevents an AI model from being overconfident about wrong answers
People use large language models for a huge array of tasks, from translating an article to identifying financial fraud. However, despite the incredible capabilities and versatility of these models, they sometimes generate inaccurate resp... -
Study: When allocating scarce resources with AI, randomization can improve fairness
Organizations are increasingly utilizing machine-learning models to allocate scarce resources or opportunities. For instance, such models can help companies screen resumes to choose job interview candidates or aid hospitals in ranking ki... -
MIT researchers advance automated interpretability in AI models
As artificial intelligence models become increasingly prevalent and are integrated into diverse sectors like health care, finance, education, transportation, and entertainment, understanding how they work under the hood is critical. Inte... -
Proton-conducting materials could enable new green energy technologies
As the name suggests, most electronic devices today work through the movement of electrons. But materials that can efficiently conduct protons — the nucleus of the hydrogen atom — could be key to a number of important technologies for co... -
Large language models don’t behave like people, even though we may expect them to
One thing that makes large language models (LLMs) so powerful is the diversity of tasks to which they can be applied. The same machine-learning model that can help a graduate student draft an email could also aid a clinician in diagnosin... -
AI model identifies certain breast tumor stages likely to progress to invasive cancer
Ductal carcinoma in situ (DCIS) is a type of preinvasive tumor that sometimes progresses to a highly deadly form of breast cancer. It accounts for about 25 percent of all breast cancer diagnoses. Because it is difficult for clinicians to... -
Machine learning unlocks secrets to advanced alloys
The concept of short-range order (SRO) — the arrangement of atoms over small distances — in metallic alloys has been underexplored in materials science and engineering. But the past decade has seen renewed interest in quantifying it, sin... -
Creating and verifying stable AI-controlled systems in a rigorous and flexible way
Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes... -
AI method radically speeds predictions of materials’ thermal properties
It is estimated that about 70 percent of the energy generated worldwide ends up as waste heat. If scientists could better predict how heat moves through semiconductors and insulators, they could design more efficient power generation sys... -
How to assess a general-purpose AI model’s reliability before it’s deployed
Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled data. They can be applied to a variety of tasks, like generating images or answering customer questions. But...
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