Imagine you are developing antibodies—drugs precisely aimed at a target, for example a viral protein or onco-marker. You test a series of antibodies and find that some work, while others do not.

To train artificial intelligence (AI) models, researchers need good data and lots of it. However, most real-world data has already been used, leading scientists to generate synthetic data. While the ...

Forget dashboards – doing data right is all about making better decisions. Our buyer’s guide distills the best of our Data ...

Google DeepMind researchers have a new way to take toxic data and clean it for AI training. It could prove to be a powerful ...

Data Feed Forward turns raw data into predictive power — enabling earlier detection, adaptive testing, and continuous ...

Understanding the brain's functional architecture is a fundamental challenge in neuroscience. The connections between neurons ...

A recent study shows that 1 in 5 people use AI every day. From the chatbot helping you budget smarter to the recommendations ...

Police say 23-year-old Iryna Zarutska was killed on a Charlotte light rail train on Aug. 22 in an apparently random attack by ...

After a hurricane passes, scientists routinely analyze the assorted computer models used to predict its path and power and ...

Discover how Unsloth and multi-GPU training slash AI model training times while boosting scalability and performance. Learn more on how you ...

University of Tennessee, Knoxville’s Katie Schuman and her team developed NODES, a neuromorphic computing system for ...

Symage, a provider of physics-based, high-fidelity synthetic image data for training AI and computer vision models, will ...