When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Through data, algorithms communicate with their environments and get to “know about” and “learn from” what is happening around them. Algorithms without living data are no more than sheer mathematical ...

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Categorizing patients with cancer by their disease stage can be an important tool when conducting administrative claims-based studies. As claims databases frequently do not capture this information, ...

Maybe they should have called it DeepFake, or DeepState, or better still Deep Selloff. Or maybe the other obvious deep thing that the indigenous AI vendors in the United States are standing up to ...

This article was originally published at The Conversation. The publication contributed the article to Space.com's Expert Voices: Op-Ed & Insights. Professional astronomers don’t make discoveries by ...

Artificial-intelligence programs, like the humans who develop and train them, are far from perfect. Whether it’s machine-learning software that analyzes medical images or a generative chatbot, such as ...