Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...

By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...

What's the real value in AI tools — and what separates those who use them well from those who don't? Sam Ransbotham, host of ...

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to ...

In both cases, it would be better to train the machine learning model with a loss function that ignores the human’s objective and then adjust predictions ex post according to that objective. We ...

In our study, a novel SAST-LLM mashup slashed false positives by 91% compared to a widely used standalone SAST tool.

In two separate blog posts, the Menlo Park-based tech giant detailed the new AI models. There are three models in total. SAM 3 for image and video tracking and segmentation, SAM 3D Objects for ...