OUR INTRODUCTION TO APPROACHES ALGORITHMS:
MULTIDIMENSIONAL INTELLIGENCE


To date, defining intelligence is a very complex task even for us humans.
In psychology, there are many experts who have discussed the subject but one in particular has exposed the theory of multiple intelligences.
Howard Gardner, this is the name of the expert, defines intelligence as:

the ability to solve problems or create products that are valued in a culture or community”.

This definition of his contains within it different forms of intelligence, giving it a multidimensional meaning.
Although these different intelligences are possessed by everyone, in each of us one can be more developed than another.
Another important concept is that they are closely connected to each other and interact in a very complex way. A very simple and significant example can be found in everyday life in the act of cooking a dish. This sets in motion and relates more than one of our intelligences: reading the recipe (natural intelligence); calculate the necessary ingredients (mathematical intelligence); take into account personal tastes (intrapersonal intelligence) and those of others (interpersonal intelligence). If everyone is aware of their stronger and weaker intelligences, they can use the stronger ones to develop or compensate for the weaker ones.
In developing our technology we have applied the concept of multiple intelligences to make the creation of a strong artificial intelligence a reality.
In DREOS AI we identify the different types of intelligences with the term "approaches".
These can operate individually or be interconnected. Each approach can substantially change the entire system depending on the task performed or the study performed.

We have 8 different types of approaches:

  • mathematical

    Ability to use numbers effectively and to think well. This intelligence includes sensitivity to principles and relationships, ability to evaluate concrete or abstract objects.

  • medical

    It is not a type of human intelligence but is the computer system approach used to study medical information at the level of composition of living system. (structure of the human body).

  • interpersonal & intrapersonal

    INTRAPERSONAL: self-recognition and the ability to act adaptively on the basis of that knowledge. Have an accurate self-description; awareness of one's deepest moods, intentions and desires.
    INTEPERSONAL: Ability to perceive and interpret the moods, motivations, intentions and feelings of others. This may include sensitivity to facial expressions, voice, gestures and the ability to respond to others effectively and pragmatically.

  • psychological

    Ability to use emotional, cognitive, social and behavioral processes in a conscious methodology and to learn what they mean when they are used in an unconscious methodology; ability to treat these processes subjectively based on context.

  • philosophical

    It is not a type of human intelligence, but it is our computer system's approach of studying, learning, identifying an idea, concept, notion as a problem (or set of problems) that requires more and more effort to the search for a solution.

  • Musical

    Ability to perceive, discriminate, transform and express musical forms. Ability to accurately discriminate pitch of sounds, timbres and rhythms.

  • physics

    It is not a type of human intelligence but is the computer system approach of using physical theories to represent life and the external environment used for learning. It is based on the application of the simple concept according to which any information can be represented in the form of a wave.

  • biological

    It is not a type of human intelligence but is the computer system approach used to study medical information at the level of chemical processes and phenomena that characterize each living system.

DATA OPERATIONS OF OUR TECHNOLOGY

In order for our approaches to work at their best, we apply specific operations to each data present in memory (or to any data received as input). This allows DREOS AI, through the use of training and learning processes, to acquire every minimum information from each data, in order to make the study or task performed by the system as reliable as possible.

We have developed 7 different types of operations (performed in the order in which they are listed):

RECOGNITION: system carries out a preliminary study of the data to identify and contextualize the type of data
ANALYZER: after having made an initial study on the data, the system carries out a deep study to look for any additional information that could be detected following the contextualization of the data
CLASSIFICATION: the data are analyzed and classified: they are assigned a weight that will vary with each life cycle of the system
DETECTION: exploiting its knowledge and the information acquired from the data through the previous operations, DREOS AI adds features to the data that represent the ideas or intuitions that the system believes are fundamental for the weight of the data
CREATION: Leveraging the ideas and insights of the system, it can create completely new data to apply to different contexts or scenarios. The creation of a data can be done either starting from scratch or by combining one or more data. (An example would be creating a series of equal data with slightly different weight to use depending on the context)
ATOMYZER: each data is divided into its smallest part (atomized) and each of them becomes a new input data to which all the operations are applied again. (This operation allows the data to be constantly updated and dynamic)
TRANSFORMATION: the data can be transformed into a new data with different structure, format or type