Although history has not always been kind to it, artificial intelligence is definitely here to stay. People continue to conduct groundbreaking research in the field of AI on a daily basis. They also try to find new ways to integrate it into other areas of our lives.
Data from PricewaterhouseCoopers indicates that business leaders expect artificial intelligence to be fundamental in the future, with 72% of them actually calling it a business advantage. So, it is obvious that many more will want to jump in the AI bandwagon and help revolutionize the world. This also means we will continue to hear more about machine learning, algorithms, supervised learning, deep learning, and many other concepts we might not comprehend. And let’s be honest, researchers and technical experts are not helping either. Most of the times they talk about neural networks and deep learning and how great they are in image recognition, but they fail to explain what exactly the terms mean. Today, understanding the main terminology and concepts in AI is essential for everyone in the business world.
The idea of a device being ‘intelligent’ has been embedded in the human mind since antiquity. Yet, the term artificial intelligence has been defined and founded as an academic discipline much later, in 1956.
Artificial intelligence refers to a specific field of computer engineering that focuses on creating systems capable of gathering data, making decisions and/or solving problems. In plain English, the term refers to intelligent behavior displayed by a machine. This means that computers can now perform more tasks that were done by humans. If in the past, computers could conduct simple logical tasks such as solving certain math problems, today they can also carry on conversations, identify objects or people in pictures and even recognize core emotions.
Algorithms are the cornerstone of artificial intelligence. They represent a set of rules (math formulas and/or programming commands) that help a regular computer learn how to solve problems with AI. Although they are initially set by programmers, these rules allow computers to learn without any further human interaction. The algorithms are tweaked using machine learning, which means the programs start to adapt these rules for themselves.
One of the most important subsets of artificial intelligence is machine learning (ML). They are so connected that, sometimes, people even substitute the terms for one another. But this should not be the case. Machine learning is the part of artificial intelligence that allows computers to improve themselves over time as a result of experience and practice. According to computer scientist Arthur Samuel, who coined the term in 1959, machine learning enables computers to learn without being explicitly programmed.
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