Recurrent neural networks enable computers to process text, videos, time series, and other sequential data.
The quest for creating thinking machines has split artificial intelligence into two fields: Narrow AI, what we have, and general AI, what we wish to achieve
By Rana Gujral
Artificial intelligence as a discipline consists of hundreds of individual technologies, concepts, and applications. These terms have become increasingly important as STEM education expands and there is a boom in practical household and...
By Gabor Takacs
Web tracking is the practice by which websites and third-party companies collect information about users’ online activity. The basis of tracking is the accurate identification of users – you are detected and identified...
Narrow AI technologies are very good at solving specific problems, but they fall short of fulfilling the requirements for human-level AI.
By Katie Kuchta
How long since you let your fingers go walking through the Yellow Pages? Or cracked open an encyclopedia? Or called the library looking for help with homework?
If you’re like most of the online...
The two main types of machine learning categories are supervised and unsupervised learning. In this post, we examine their key features and differences.
Convolutional neural networks (CNN), or ConvNets, have become the cornerstone of artificial intelligence (AI) in recent years. Their capabilities and limits are an interesting study of where AI stands today.
Everything you need to know about symbolic artificial intelligence, the branch of AI that dominated for five decades.
To create better artificial intelligence hardware, researchers have been drawing inspiration from the brain. The result is neuromorphic chips, which have grown in popularity in the past years.