Researchers have created a new AI algorithm called Torque Clustering, which greatly enhances an AI system’s ability to learn and identify patterns in data on its own, without human input.
Researchers have developed a new AI algorithm, Torque Clustering, which more closely mimics natural intelligence than existing methods. This advanced approach enhances AI’s ability to learn and identify patterns in data independently, without human intervention.
Torque Clustering is designed to efficiently analyze large datasets across various fields, including biology, chemistry, astronomy, psychology, finance, and medicine. By uncovering hidden patterns, it can provide valuable insights, such as detecting disease trends, identifying fraudulent activities, and understanding human behavior.
“In nature, animals learn by observing, exploring, and interacting with their environment, without explicit instructions. The next wave of AI, ‘unsupervised learning’ aims to mimic this approach,” said Distinguished Professor CT Lin from the University of Technology Sydney (UTS).
To read more, click here.