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Artificial Intelligence is an ever-evolving field that is redefining the way we interact with technology and the world around us. The branches of artificial intelligence range from deep learning that powers image and voice recognition, to natural language processing that powers chatbots and machine translators, and to industrial automation in robotics. In this article, we explore the diverse and exciting applications of artificial intelligence, revealing how each of them is shaping the future and opening up new possibilities. This is what the next era of innovation will look like.

The various branches of artificial intelligence are shaping the future and opening up new possibilities in the era of innovation.

15 branches of artificial intelligence

The impact of artificial intelligence on society is profound and covers various areas, including business. The use of artificial intelligence tools has proven to be a powerful tool to drive efficiency in organizations. The fields of application of artificial intelligence in companies are many, and some are aimed at meeting very different needs. 1. Machine learning

Machine learning is the branch of science that seeks to develop artificial intelligence techniques that allow computers to learn by themselves. To do this, programs are created that can generalize certain responses from unstructured information, which is provided as examples. This induces knowledge on the part of the computer.
2. Fuzzy logic

Known as heuristic logic. This technique focuses on the relative nature of an observed scenario as a differential position. It is a type of logic that takes two values ​​at random, contextualized and related to each other. For example, considering a 2-meter tall person as tall after having previously taken the value of a one-meter tall person as short.
3. Artificial life

It consists of the study of life and artificial environments that show qualities typical of living beings in simulation environments. One of the artificial intelligence techniques with the most future projection in the field of research.
4. Expert systems

This refers to an information system that is based on knowledge of a highly complex and very specific application area. It serves as a consulting and expert assistant for the users of its interface.

AI is used when it is considered useful to incorporate into a computer system knowledge or behavior in response to events that would be more typical of a human being.

These are environments that provide answers to very specific problems, being able to make inferences very similar to those of a human being about the specific knowledge consulted.
5. Data Mining

This technique consists of the discriminated extraction of information that is implicit in the data handled. This information, previously unknown, is intended to be used in some other process. Data mining probes, prepares and explores the data in order to extract some information that is hidden in it. 6. Bayesian Networks

Also known as belief networks, these networks are a multivariate probabilistic model that relates a set of random variables using a directed graph to explicitly indicate a casual influence.

With a probability update engine called Bayes' Theorem, these networks become a very useful tool when calculating probabilities in cases of new evidence. It is one of the types of networks that are called casual.

Branches of AI
7. Knowledge engineering

It consists of generating new knowledge that did not previously exist. It is done from the information contained in document databases and by cross-referencing the content of the files.

It is a technique based on the "actor-network" theory, revealing networks and creating new ones. It also involves the exercise of the "translation-translation" theory, bringing actors together and relating them, with the aim of producing a translation in which to take the statements or modalities to new evolutionary stages.
8. Artificial neural networks

Neural networks are a paradigm of automatic learning and processing, inspired by the way the nervous system of animals works. They consist of a system of interconnected neurons in a network that collaborate with each other to create an output response.
9. Reactive systems

These are critical application systems, and a failure or error can have serious consequences, to the point of putting human lives or the outcome of important economic investments at risk.

Their behavior in these real-time environments is determined both by the succession of actions that are executed and by the moment in which each of them occur and are processed.
10. Rule-based systems

These consist of knowledge representation models that are widely used. They are appropriate for scenarios in which the knowledge that needs to be represented arises naturally in a structure of rules.
11. Case-based reasoning

This is a process for solving issues based on solutions to previous problems. Case-based reasoning uses analogies for new reasoning.

It is considered not only to be a powerful calculation tool for computers, but also that human beings use the same principle to solve everyday problems. 12. Knowledge Representation Techniques

It is a system that serves to analyze the way of thinking in a formal way. A symbol environment is used for the representation of a domain of discourse, together with the functions that can infer about the processed objects.
13. Semantic networks

They are ways of representing linguistic knowledge for which the concepts and the interrelations between them are represented by graphs. They are used for the representation of conceptual and mental maps, among other functions.
14. Computational linguistics

It is a multidisciplinary field of applied linguistics in computer science. It uses computer systems for the study and treatment of language. To do this, it attempts to logically model natural language from a programmable point of view.
15. Natural language processing

Natural language processing (NLP) is a discipline of the branch of engineering for computational linguistics. It is used for the formulation and research of mechanisms for computing efficiency for communication services between people or between people and machines using natural languages.

The fields of development and research in artificial intelligence serve to develop mechanisms and applications that allow the design of new methods of working and communicating with machines and computing environments. The future of artificial intelligence in companies promises greater integration and collaboration between humans and machines. There are already many leading companies that use big data and artificial intelligence, making reality what until very recently was part of fiction.

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• #Artificial Intelligence
• #Systems
• #Bayesian Networks
• #Machines