Artificial Intelligence, Explained

From personal assistants like Siri, to movie suggestions on Netflix, artificial intelligence (NYSE:AI) is rapidly becoming ubiquitous in everyday life. As this technology continues to advance in capability and prevalence, we sought to explore AI and several closely related subtopics: machine leaning, deep learning, and neural networks. What are the Differences between Artificial Intelligence, Machine Learning, and Deep Learning? While artificial intelligence (AI), machine learning (ML), and Deep Learning (NYSE:DL) are often used interchangeably, there are several key differences. One way to visualize the relationship is through a series of concentric circles. AI is the macro topic which encompasses the entire field of study, while ML is a subtopic within AI. DL is a further refinement of ML and represents the most cutting edge of AI applications that are being used today.1 At a basic level, artificial intelligence is the concept of machines accomplishing tasks which have historically required human intelligence.1 AI can be broken down into two distinct fields: Applied AI: Machines designed to complete very specifics tasks like navigating a vehicle, trading stocks, or playing chess – as IBM’s Deep Blue demonstrated in 1996 when it defeated chess grand master Gerry Kasparov. General AI: Machines designed to complete…

Link to Full Article: Artificial Intelligence, Explained

Pin It on Pinterest

Share This