Technology counts on AI to authenticate and identify people
Not long ago, artificial intelligence was viewed as science fiction. Today, it routinely makes our lives more secure and convenient. AI surrounds us in our everyday lives. Online entertainment providers use it to suggest movies, TV shows and music we might enjoy. Retailers try to influence our current buying decisions based on previous purchases. Chatbots help us make appointments with service providers.
The security industry also deploys artificial intelligence in many ways. Facial recognition counts on AI to authenticate and identify people by the shapes of their faces and features. Robots and drones patrol perimeters looking for anomalies, leaving human officers free to handle other potential threats and events. AI-based software checks feeds from central video monitoring stations to filter out false alarms.
Diving a Little Deeper into the Technology
In recent years, the use of artificial intelligence and its subsets, machine learning and deep learning, have increased exponentially. AI technology enables computers to mimic human intelligence using logic based on if-then rules and decision trees. Statistic techniques used in machine learning allows computers to improve at tasks with experience. Deep learning enables networks to train themselves to perform tasks such as speech and image recognition. There are two main ways of working with these technologies – rule-based algorithms and neural networks.
Rule-based algorithms have limitations. Even the most experienced computer engineer can’t prepare for all potential situations that might arise within a camera’s field of view or an employee arrives at a building entrance with his face covered with a mask and goggles. As a result, these algorithms offer reduced accuracy.
While it’s not accurate to say neural networks work like a human brain, they are inspired by it. Neural-node networks are computing systems that learn to perform tasks by considering examples rather than being programmed with task-specific rules. The machine-learning model memorizes its training data an makes predictions based on specific sets of situations.
Credit: Google News