Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.
AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields:
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.
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.
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.
Is the ability of computers to analyze, understand and generate human language, including speech. This allows everyday language between humans and computers.
Are key to AI because they provide the heavy compute power that’s required for iterative processing. Training neural networks requires big data plus compute power.
Generates massive amounts of data from connected devices, most of it unanalyzed. Automating models with AI will allow us to use more of it.