Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

The ever-increasing selection of microcontrollers brings the challenge of porting embedded software to new devices through much manual work, while code generators are used only in special cases. Since ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

"Reading demographics from a pathology slide is thought of as a 'mission impossible' for a human pathologist, so the bias in pathology AI was a surprise to us." To conduct the study, researchers at ...

Trump fired the Bureau of Labor Statistics head. In Argentina, the government manipulated the inflation rate. Economists went rogue to calculate the real rate, and people lost trust in the numbers.

The latest generative AI models are not just stand-alone text-generating chatbots—instead, they can easily be hooked up to your data to give personalized answers to your questions. OpenAI’s ChatGPT ...

LangExtract lets users define custom extraction tasks using natural language instructions and high-quality “few-shot” examples. This empowers developers and analysts to specify exactly which entities, ...

A new computational tool helps researchers map molecular interactions, revealing the pathways associated with disease. Understanding how molecules interact inside our cells is key to uncovering how ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

Have you ever stared at a massive spreadsheet, overwhelmed by the chaos of mixed data—names, IDs, codes—all crammed into single cells? It’s a common frustration for anyone managing large datasets in ...