In recent articles I have looked at some of the terminology being used to describe high-level Artificial Intelligence concepts – specifically machine learning and deep learning. In this piece, I want ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At the advent of the modern AI era, when it was discovered that powerful ...

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...

Semi-supervised learning merges supervised and unsupervised methods, enhancing data analysis. This approach uses less labeled data, making it cost-effective yet precise in pattern recognition.

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More This article was contributed by Slater Victoroff, founder and CTO of ...

Traditional approaches to autonomous vehicles (AVs) rely on using millions of miles of driving data in conjunction with even more miles of simulated data as inputs to supervised machine learning ...

Machine learning, the subset of artificial intelligence that teaches computers to perform tasks through examples and experience, is a hot area of research and development. Many of the applications we ...