Classification plays an important role in many applications of artificial intelligence (AI), such as image recognition, speech recognition, and natural language processing. This interesting information came to us from an ABC affiliate out of Australia in their article, “Artificial intelligence technologies could be classified by risk, as government consults on AI regulation.”
In AI, classification is used to train machines to recognize patterns in data and split it into different categories. This enables machines to make predictions, identify anomalies, and make informed decisions. The process of classification in AI involves the use of algorithms that can learn from large datasets through supervised learning techniques.
These algorithms are trained using labeled data sets, where each data point is associated with a particular category. The algorithm then learns how to classify new data points based on the patterns it has learned from the training set. Overall, classification is a crucial concept within AI that enables machines to learn from large datasets and make informed decisions based on their analyses of those datasets’ content.
Content needs to be findable, and that happens with a strong, standards-based taxonomy. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies and associated rule bases for machine-assisted indexing.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
|
Sponsored by Access Innovations, the world leader in taxonomies, metadata and semantic enrichment to make your content findable.
