Despite the promise of data-based innovations in medicine, proponents often overlook the special risks of bringing medicine into the age of artificial intelligence. As a starting point, we can take ...

In a recent study published in the Nature Medicine journal, researchers assessed the efficacy of the machine learning model in the prediction of mental health crises. The timely recognition of ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Deep learning automation startup Deci AI Ltd. today announced the launch of a free and open-source artificial intelligence tool that can profile datasets for model training purposes. The company said ...

Researchers have applied the tools of neuroscience to study when and how an artificial neural network can overcome bias in a dataset. They found that data diversity, not dataset size, is key and that ...

At first thought, computing the similarity/distance between two datasets sounds easy, but in fact the problem is extremely difficult, explains Dr. James McCaffrey of Microsoft Research. A fairly ...

I’ve finished reading “The Alignment Problem” (ISBN: 9780393635829), by Brian Christian. As the subtitle states, it’s an attempt to discuss fuzzier aspects of human value with the growing relevance of ...

A fairly common sub-problem in many machine learning and data science scenarios is the need to compute the similarity (or difference or distance) between two datasets. For example, if you select a ...