The processing speed of a "machine" and "human" thinking ability.
When people talk about Artificial Intelligence, they immediately think of robots capable of understanding and deciding on actions to be taken and of a futuristic world in which machines and humans coexist.
Reality and Artificial Intelligence
In reality, Artificial Intelligence and its use are much more real than we can imagine and are now being used in various areas of daily life, for example:
- Healthcare and Scientific Research to diagnose diseases based on the patient's symptoms
- Sales and Marketing for predictive, statistical and simulation activities
- Security and Risk Management to prevent possible threats and/or accidents
- Automation and Process Processing to optimize management time and make machines perform some of the once manual tasks, such as classification or cataloging of data
Artificial Intelligence can generally be defined as a set of multiple theories and techniques that are combined for the development of a system capable of autonomously and creatively tackling specific problems, showing in that context intellectual capacity sometimes superior to that of humans.
The operation of an AI
From the point of view of these abilities, the functioning of an AI is mainly substantiated through four different functional levels:
- comprehension: through the simulation of cognitive abilities of correlating data and events the AI is able to recognize texts, images, tables, videos, voice and extract information from them;
- reasoning: through logic the systems are able to connect the multiple information collected;
- learning: here we are talking about systems with specific capabilities for analyzing data inputs and their "correct" return in output;
- interaction (Human Machine Interaction): here we are referring to the way AI functions in relation to its interaction with humans. This is where NLP - Natural Language Processing systems, technologies that enable humans to interact with machines (and vice versa) by exploiting natural language, are strongly advancing.
Within the discipline of AI, two areas of study that deserve some clarity are Machine Learning and Deep Learning.
- Machine Learning: A subset of AI that provides systems with the ability to learn automatically and improve with experience, without being explicitly programmed; the system can "train" itself by correcting errors autonomously through specific external input.
- Deep Learning: A subset of Machine Learning inspired by the structure of the biological brain; it does not require programmer intervention to "learn," thus emulating the learning process of the human mind. In this case, the mathematical model alone is not enough; Deep Learning requires purpose-designed artificial neural networks (deep artificial neural networks) and a very powerful computational capacity capable of "holding up" different layers of computation and analysis (which is what happens with the human brain's neural connections).
It may sound like a futuristic level of technology, but these systems are already in use today, for example in voice or image recognition, autonomous driving, web search, and much more.
This and much more will be discussed during the Online Edition of Digital Innovation Days 2020, buy your Early Bird ticket now for €79 instead of €149!
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Riccardo Inglisa
Brand Ambassador Digital Innovation Days