Datasets fuel AI models like gasoline (or electricity, as the case may be) fuels cars. Whether they're tasked with generating text, recognizing objects, or predicting a company's stock price, AI ...

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 ...

The data needed to power ML and AI is vast. Organizations need to understand the factors that go into decisions about where or how it will source its data. IFI CLAIMS Patent Services has a global ...

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 ...

Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

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 ...

Electronic design automation (EDA) or computer-aided design (CAD) is a category of software tools for designing electronic systems, such as integrated circuits (ICs). By EDA tools, designers can ...

Science and data are interwoven in many ways. The scientific method has lent a good part of its overall approach and practices to data-driven analytics, software development, and data science. Now ...

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 ...