How Artificial Intelligence Works

ARTIFICIAL INTELLIGENCE

Artificial intelligence works by combining huge amounts of data with reckless, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. Artificial intelligence is a far-reaching field of study that includes many theories, methods and technologies, as well as the following major categories:

·         A NEURAL NETWORK.    It is a type of machine learning that is made up of interconnected units that processes information by responding to external inputs, relaying information between each unit. The process requires multiple passes at the data to find connections and derive meaning from undefined data.

·         COGNITIVE COMPUTING            It strives for a natural, human-like interaction with machines. Using AI and cognitive computing, the ultimate goal is for a machine to simulate human processes through the ability to interpret images and speech – and then speak coherently in response.  

·         MACHINE LEARNING       It automates analytical model building. It uses methods from neural networks, statistics, operations research and physics to find hidden insights in data without explicitly being programmed for where to look or what to conclude.

·         DEEP LEARNING   It uses huge neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data. Common applications include image and speech recognition.

·         COMPUTER VISION          It relies on pattern recognition and deep learning to recognize what’s in a picture or video. When machines can process, analyze and understand images, they can capture images or videos in real time and interpret their surroundings.

·         NATURAL LANGUAGE PROCESSING             It is the ability of computers to analyze, understand and generate human language, including speech. The next stage of NLP is natural language interaction, which allows humans to communicate with computers using normal, everyday language to perform tasks.

·         GRAPHICAL PROCESSING UNITS       These are key to Artificial Intelligence because they provide the heavy compute power that’s required for iterative processing. Training neural networks requires big data plus compute power.

·         THE INTERNET OF THINGS       It generates massive amounts of data from connected devices, most of it unanalyzed. Automating models with AI will allow us to use more of it.

·         ADVANCED ALGORITHMS         These are being developed and combined in new ways to analyze more data faster and at multiple levels. This intelligent processing is key to identifying and predicting rare events, understanding complex systems and optimizing unique scenarios.