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2 Minutes Read

Artificial Intelligence

Artificial intelligence (AI) is a field of computer science and engineering that deals with designing intelligent agents, which are systems that can reason, learn, and act on their own. Research aims to create systems that exhibit natural intelligence—the ability to think abstractly, reason well about situations and solve problems. 

A simple definition of artificial intelligence is "the ability of a machine to simulate or emulate the behavior of humans." Although there are many applications for AI, one key area is in robotics, where machines can be made to behave like people and interact with their environment. In fields such as finance, medical diagnosis, and telesphing, AI is used to make complex decision-making processes more efficient. Although there are many different types of AI, the central concepts behind all AI techniques are learning and inference. In machine learning, artificial intelligence algorithms are taught to identify patterns in data by training on a set of labeled examples. Then, predictions about new data are made based on what these patterns seem to mean.

Inference is the process of drawing conclusions from facts or data. It involves assessing various possibilities based on what is known currently.

Moreover, AI relies on two fundamental logical concepts: propositional calculus and predicate logic. In propositional calculus, symbolic equations are used to represent the relationships between propositions. In predicate logic, terms such as "is" and "has") are used to denote relations between variables. AI algorithms use these symbols in order to make inferences about the world around them. One of the most significant advancements in AI was the development of machine learning algorithms. These algorithms are able to learn from data and improve their performance over time by automatically discovering patterns. The first time machine learning worked well was in spam filtering, where a system was able to get better at recognizing spam emails over time.

Since then, many other areas have benefited from this type of AI technology, including finance (where predictions about financial markets are used as inputs into investment decisions), speech recognition (where computer systems can be taught how to interpret human language) and medical diagnosis (where patient histories and symptoms are used to make predictions about the onset of diseases).

In short, AI projects are always trying to make machines better at making accurate and fair predictions about the world. 

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