profitnew.ru Open in urlscan Pro
2606:4700:3030::ac43:b81c  Public Scan

Form analysis
0 forms found in the DOM

Text Content

AI: WHAT IS ARTIFICIAL INTELLIGENCE, MAIN TOOLS FOR STREAMLINING AND AUTOMATING
PROCESSES AND WORKFLOWS

Where algorithms are applied and what advantages they ensure, from Marketing to Recruiting. A guide to clarify the real opportunities for business and the solutions available. Updated data from the Artificial Intelligence Observatory of the Polytechnic of Milan



Artificial Intelligence is already part of our daily lives and is now used in more than half of large Italian companies. Everyone knows about driverless cars or voice assistants like Apple's Siri, Microsoft's Cortana or Google's Alexa, but there are many lesser-known examples.

Intelligent algorithms, capable of self-learning, suggest products to buy, films or songs in line with our tastes, they know how to answer customer questions via chat, they can recognize a person's face to enable a access, sort documents based on content, support doctors in reading x-ray images and diagnoses, filtering CVs to select the ideal candidate. And so on.

The Polytechnic of Milan provides this definition of AI: “Artificial
Intelligence, in English Artificial Intelligence (AI), is the branch of computer
science that studies the development of hardware and software systems equipped
with capabilities typical of human beings and capable to autonomously pursue a
defined purpose by making decisions that, until that moment, were usually
entrusted to human beings.”

The typical capabilities of human beings concern, specifically, the
understanding and processing of natural language (NLP – Natural Language
Processing) and images (Image Processing), learning, reasoning and the ability
to plan and interact with people, machines and the environment. Unlike
traditional software, an AI system is not based on programming (i.e. on the work
of developers who write the operating code of the system) but on learning
techniques. That is, algorithms are defined that process an enormous amount of
data from which the system itself must derive its understanding and reasoning
capabilities.

Machine Learning
These are systems that serve to “train” the software so that by correcting
errors it can learn to carry out a task/activity independently.

For example, the mechanical arm supported by AI, and therefore intelligent, is
able to assemble a piece even if it is not where it should be because the
control algorithm, instead of providing the coordinates, activates an optical
recognition that searches for the piece everywhere the area that the arm can
reach.

And if the machine or the man offering the pieces repeats the mistake several
times, the robot learns that that is the new position and immediately goes to
look for the piece there. Machine Learning is evolving along a line of research
based on the use of neural networks organized into multiple levels of depth and
therefore called Deep Learning.

Deep Learning
These are recently developed learning models (since 2012) inspired by the
structure and functioning of our brain, which emulate the human mind.
In this case, the mathematical model alone is not enough: Deep Learning requires
ad hoc designed artificial neural networks (deep artificial neural networks) and
a very powerful computational capacity capable of “supporting” different layers
of calculation and analysis (which is what happens with the neural connections
of the human brain).

It may seem like a futuristic level of technology but in reality these are
systems already in use in pattern recognition, voice or image recognition and
NLP – Natural Language Processing systems.


error: Content is protected !!