Artificial Intelligence (AI) is the intellect demonstrated by machines, as opposed to natural intelligence demonstrated by humans and animals, which involves consciousness and emotion. A subset of AI is machine learning, which refers to the concept that computer programs can learn automatically and adapt to new data without the assistance of humans.
Artificial intelligence (AI) is often applied to projects that design systems endowed with human-like mental processes, such as the ability to reason, discover meaning, generalize, or learn from past experiences.
In common use, artificial intelligence refers to a computers or machines ability to emulate human mental capabilities learning from examples and experiences, recognizing objects, understanding and responding to language, making decisions, solving problems and to combine those capabilities with others in order to carry out functions that humans can do, such as greeting hotel guests or driving a car. Artificial intelligence allows computers and machines to emulate the perceptual, learning, problem-solving, and decision-making abilities of the human mind. Artificial intelligence is built around the principle that human intelligence can be defined so a machine can mimic it effortlessly and perform tasks, ranging from the simplest to the most difficult.
Strong AI, also known as Artificial General Intelligence (AGI), describes programs capable of replicating human brain cognitive abilities. Cognitive Computing vs. Artificial Intelligence The terms artificial intelligence and cognitive computing are sometimes used interchangeably, but generally, artificial intelligence is used in reference to machines that substitute for human intelligence, simulating how we perceive, learn, process, and respond to information in our environment. The journal Artificial Intelligence (AIJ) welcomes papers that address the broader aspects of AI which represent advances in the overall field, including, but not limited to, cognitive science and artificial intelligence, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constrained computing, ethical AI, heuristic retrieval, human-interfaces, intelligent robots, knowledge representation, machine learning, multi-agent systems, natural language processing, planning and actions, and reason under uncertainty. While these definitions might sound abstract to the average person, they serve to bring artificial intelligence into sharper focus as a branch of computing and offer a roadmap to integrating machines and programs with machine learning and other subsets of AI.
Some emergent approaches aim to emulate human intelligence to a very high degree, and they suggest that anthropomorphic features such as artificial brains or the simulation of infant development could one day achieve the crucial points at which general intelligence would emerge. Some programs have achieved human-like experts and practitioners levels of performance at performing some specific tasks, such that AI in this narrow sense is found in applications as varied as medical diagnoses, computer search engines, and speech or handwriting recognition. For instance, machines that compute rudimentary functions, or that identify text by optical character recognition, are no longer considered to embody AI, as the function is now taken as a given, an intrinsic function of computers. Whether or not it is possible to have artificial general intelligence; if machines could solve every problem a human can solve using intelligence, or if there are strict limits on what machines could achieve.