An article published via the Massachusetts Institute of Technology's Open Course Ware platform states a simple and intuitive definition of AI is the design and development of computational models that can mimic human behaviour through processes, intelligence, and rationality.
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Some of the primary abilities of AI systems can be listed below.
Exhibiting logic, reasoning, problem-solving & creative skills, akin to the human mind
Learning from experience
Ability to perceive different kinds of information from other sources
Heuristically tackling or solving any unknown problem
Approaches to AI are myriad, and they have all met with significant challenges in their attempt to replicate the remarkable & malleable learning capabilities of the human mind.
Some of the most prominent subsets/branches/topics/approaches in AI are briefly discussed.
Machine Learning is currently the most robust approach to achieving true AI. ML processes involve computational systems learning and distilling information from training data. ML can be applied to different problems and data sets, with numerous techniques and model modifications enhancing the abilities of an ML model substantially.
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Cognitive Analytics is yet another subset of AI that can replicate the cognitive behaviour of human beings, allowing them to learn, observe & communicate. A cognitive system can extract information from data by identifying & inferring concepts & relationships among data.
Robotics is another prominent branch in AI where process automation is achieved by designing intelligent systems capable of learning, pattern recognition, heuristic problem-solving.
Smart Machines &Expert Systems are two other rising branches that derive ideas from multiple disciplines and other AI branches, with the ultimate aim to achieve human-level intellect.
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