Augmented Reality or Virtual Reality


Artificial intelligence is constantly evolving, each time encompassing more extensive fields: apps, photographs, games …

Artificial intelligence, like robotics, is a new field for many. The terminology in this field is used more and more frequently: “autonomous”, “neural networks”, “deep learning, cloud computing …”.

Some terminologies of artificial intelligence are:

In the field of technology, autonomy is the time that a device with an independent power supply can remain active, until the power supply is exhausted. In AI the autonomy if given to 100% means that the machine or robot does not need help from people. Example, a level 4 autonomy vehicle represents a vehicle that does not need steering wheels or pedals. A vehicle that has reached level 5 autonomy represents a totally independent car that works without an external source.

An algorithm is a prescribed set of instructions or rules well defined, ordered and finite that allows an activity to be carried out through successive steps that do not generate doubts to who should do this activity. These are mathematical formulas and / or programming commands that inform a computer about how to solve problems with artificial intelligence.

Machine learning
The basis of AI is machine learning. Machine learning is the process by which AI uses algorithms to perform artificial intelligence functions. It is the result of applying rules to create results through an AI.

Black box
In systems theory and physics, Black Box is the element that is studied from the point of view of the inputs it receives and the outputs or responses it produces, without taking into account its internal functioning. In other words, from a black box we will be interested in its way of interacting with the environment that surrounds it (sometimes, other elements that could also be black boxes) understanding what it does, but without giving importance to how it does it. On many occasions the AI ​​makes quite complex mathematical operations.
Many times they can not even be understood by the human being, but nevertheless the system creates useful information when doing it.

Resultado de imagen de inteligencia artificial realidad aumentada

Neural networks
Neural Networks are an important basis for the development of AI (Artificial Intelligence). They are inspired in the behavior of the neurons and connections of the human brain trying to create a program, system or machine that is capable of solving difficult problems, acting in a human way, and doing heavy work using conventional algorithmic techniques.

Types of RN (Neural Networks) A neural network or neural network, can refer to:
Artificial neural network, mathematical, computational, artificial, ideal models of a neural network used in statistics, cognitive psychology, and artificial intelligence.
Biological neuronal network, a cluster of physically interconnected neurons whose activity helps to define a recognizable circuit in the nervous system.

Augmented reality glasses
Augmented reality glasses (HMD) is used to display both the images of the places in the physical and social world where the user is located and the virtual objects on the current view. The HMD must be followed with a sensor. This tracking allows the computer system to add virtual information to the physical world.

Machine learning or machine learning (“Machine Learning”)
It is the subfield of computer science and a branch of artificial intelligence whose objective is to develop techniques that allow computers to learn. More specifically, it is about creating programs capable of generalizing behaviors from information provided in the form of examples.

Deep learning
Deep learning (in English, deep learning) is a set of algorithms of automatic learning class (in English, machine learning) that tries to model high-level abstractions in data using architectures composed of multiple non-linear transformations.

Deep learning is part of a broader set of machine learning methods based on learning data representations. Several deep learning architectures, such as deep neural networks, deep convolutional neural networks, and deep belief networks, have been applied to fields such as computer vision, automatic speech recognition, and recognition of audio and music signals, and have been shown to produce cutting edge results in various tasks.

Artificial intelligence (AI)
Also called computational intelligence, it is the intelligence exhibited by machines. In computer science, an ideal “intelligent” machine is a flexible rational agent that perceives its environment and carries out actions that maximize its chances of success in some objective or task. Colloquially, the term artificial intelligence is applied when a machine imitates the “cognitive” functions that humans associate with other human minds, such as: “learn” and “solve problems”.

Source text: Wikipedia

Source video: TEDx Talks

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