NOTE: This content was partially created with the help of AI.

Artificial Intelligence (AI) refers to computers and machines that can do tasks previously only possible for humans, like problem-solving, decision-making, and learning. Its origins date back to the late 1940s and have come a long way since then, rapidly advancing and transforming many aspects of work and industry, as well as how we communicate and approach tasks with the potential to eliminate some. AI is used in various industries to save time and money, enhance decision-making, and improve efficiency.

For example, the financial industry uses AI to detect fraud, assess risk, and manage portfolios. In manufacturing, AI helps with production and quality control. In healthcare, AI can help diagnose illnesses and develop personalized treatment plans. In education, AI can recommend courses and content. In technology, AI can help programmers work more efficiently.

Machine Learning is a subset of AI that lets machines learn and understand things without being told explicitly what to do. Think of how people learn by experience. Machines can learn from lots of data and then use that knowledge to do things such as classify information, analyze data, and make predictions.

Neural Networks are a type of Machine Learning that uses networks of connected “neurons.” The concept is similar to how the human brain works. However, newer math functions are less like biological neurons. Neural Networks can solve many different kinds of problems by learning from patterns.

Deep Learning is a type of Neural Network known as a “deep neural network” of many layers. It is good at understanding and analyzing large amounts of data.

Convolutional Nets are a type of Deep Learning that are especially good at understanding images and video. They are used to do things such as recognize faces or identify objects in pictures.

References: Artificial Intelligence. Amsterdam: Time-Life Books, 1986.