Artificial intelligence (AI) is in all the headlines these days. The various uses of AI include facial recognition, personal assistants and self-driving cars, plus much more. Machine learning is a branch of AI that focuses on developing machines that learn patterns from data, without being explicitly programmed to do so. This interesting information came to us from The Rochester Institute of Technology in their article, “Student to Student: Artificial intelligence/machine learning.“
The popular models used for machine learning are typically deep neural networks, which are loosely inspired by how human brains process data. These models work especially well when they are trained on large static datasets to perform a pre-defined task and even outperform humans in some cases.
Machine learning enables analysis of massive quantities of data. While it generally delivers faster, more accurate results in order to identify profitable opportunities or dangerous risks, it may also require additional time and resources to train it properly. Combining machine learning with AI and cognitive technologies can make it even more effective in processing large volumes of information.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
