ARTIFICIAL INTELLIGENCE TECHNOLOGIES
There are numerous advances and teaches that include Artificial Intelligence, which have their own parts of numerical and designing review. How about we investigate the most applicable advances, beginning with acknowledgment frameworks through to AI frameworks.
Automatic speech recognition
Programmed discourse acknowledgment is a discipline having a place with acoustics, that perceives phonemes in a voice signal. The voice acknowledgment frameworks process the signatures gathered by a mouthpiece to distinguish the words articulated by the client.
Natural language processing (NLP)
While speech recognition focuses on pure conversion of voice to text, Natural Language Processing NLP is a discipline that is more closely linked to the field of linguistics, and its objective is to understand what the user means when making a certain command, question, or statement (either written or vocal) and what he expects to achieve. In addition, it analyzes the mood to find subjective patterns. In short, it is the field that helps communication (mainly sound and written) between machines and humans.
Visual Recognition
Visual acknowledgment is the discipline dependent on handling a picture or video signal, determined to perceive examples, shapes, and in the best cases, precisely recognizing the various components in a picture.
Text Recognition
Text recognition could be considered a part of visual recognition, as its main objective is to recognize and identify text in image formats. It is common to use OCR (Optical Character Recognition) tools for this work.
Robotics (either mechanical or robotic software, such as RPA)
Robotics covers a wide range of devices. Whenever a system or robot shows signs of intelligence, for example, being able to make decisions, however basic they may be, we can be talking about Artificial Intelligence. Remember that AI does not have to be especially sophisticated, it exists at all levels, even the most basic ones, and it must be differentiated from the ability to learn from machines; that is, Machine Learning.
Machine Learning
Machine Learning is the discipline, within Artificial Intelligence, that tries to get a system to learn and relate information the way a person would. To do this, it uses algorithms that are able to detect patterns in previous data, being able to create future predictions, as well as new trends such as Deep Learning and its neural network algorithms.
Cognitive Intelligence
Cognitive Intelligence is a combination of the previously mentioned technologies with the aim of creating artificial intelligence services capable of having human understanding. It is the union of visual recognition, sound, reading comprehension, NLP and Machine Learning to create systems capable of understanding information related to human interaction and responding accordingly.
ARTIFICIAL INTELLIGENCE CATEGORIES
It is not easy to categorize artificial intelligence, and the truth is that it is best practice to categorize it based on the algorithms used by a particular system. However, some experts have tried to create artificial intelligence groups based on their approach.
According to computer scientists Stuart Russell and Peter Nerving, artificial intelligence can be divided into the following categories:
Systems that think like humans
These systems try to emulate human thought quite literally using artificial neural network models.
Systems that act like humans
These systems focus on acting as humans; They are more linked to classical robotics and are less flexible.
Systems that think rationally
These systems try to apply human logic when it comes to perceiving, reasoning and acting. They are not focused on emulating the neuronal behavior of the brain but are trained to act in a human way in a given environment. An example of this is expert agents.
Systems that act rationally (ideally)
They try to emulate human behavior in a rational way, obtaining their own conclusions to given environmental conditions. The differential point in these systems is trying to apply rationality to their decisions.
A more common categorization is one that divides 2 large groups:
Weak (or narrow) AI
Known by its acronym ANI (Artificial Narrow Intelligence), and although the name may seem somewhat derogatory, it covers all the Artificial Intelligence in existence today. It is Artificial Intelligence dedicated to solving a specific or set of problems in an optimal way, but without the possibility of extending to general problems without the relevant programming. Even the most advanced virtual assistants fall into this category.
Strong (or GENERAL) AI
Known by the acronym AGI (Artificial General Intelligence), it is Artificial Intelligence capable of matching or surpassing human intelligence in the capacity of reasoning and deduction. Today it is a utopia that only exists in science fiction because although the machines already outperform humans in a multitude of capacities (including vision and auditory recognition in some areas), they do not have real feelings, native cognitive abilities, self-awareness or the ability to adapt to any scenario.
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