What is AI, artificial intelligence, and its applications?

Artificial intelligence is based on the principle that human intelligence can be defined and structured in such a way that a machine can easily imitate it and perform tasks, from the simplest to the most complex. In other words, the aim of artificial intelligence is to imitate human cognitive activity.

Although it is true that this concept has boomed in recent years, given that researchers and developers in this field are making advances with surprising speed in terms of imitating activities such as learning, reasoning and perception, the development of this technology has gone through highs and lows since Alan Turing developed what is regarded as the first AI project in 1951.

Although some researchers believe that, given the level and pace of development, at some point systems could even exceed the capacity of humans to learn or analyse any subject, for others there are aspects of intelligence (such as emotional) that machines can never have, since all cognitive activity is permeated by value judgments that are subject to human experience.

Parts of AI

Although it is part of it, the terms Artificial Intelligence and Machine Learning (ML) are often used interchangeably, the latter referring to the functionality of certain computer programs to automatically learn new data and adapt to it without help from humans. Deep-learning techniques allow for this machine learning by absorbing huge amounts of unstructured data, such as text, images or video.

Another component that makes up artificial intelligence is natural language processing (NLP), which is the processing of human language by a computer program. One of the oldest and best-known examples of NLP is spam detection, which examines the subject and text of an email to decide if it is junk. The current approaches to NLP rely on machine learning. NLP tasks include text translation, sentiment analysis and voice recognition.

All the parts related to robotics (which are used to do tasks that are difficult for humans to perform, or that are repetitive) are also included in AI (in fact, one of the first images that comes to mind when we talk about AI is robots). Autonomous driving systems also fall under this umbrella.

In any case, all progress in AI is made possible by processing the large volumes of data used to train these systems so they can analyse the data in search of correlations and patterns. They also use these patterns to make predictions about future states.

Where to apply AI

In order to train it first so it can function later, the development of AI requires vast amounts of data. It is those sectors with the highest volume (especially if the data is digital) that have the greatest potential to apply AI.

• Health. One of the biggest bets involves health. Companies are applying machine learning to make better and faster diagnoses - such as for cancer - than humans. As it happens, it is for cancers with the most data (such as breast cancer) that these algorithms are proving most successful.
• Manufacturing. The manufacturing industry has been incorporating robots into its workflow for decades to do unique tasks separate from human workers. These robots are relying more and more on AI, which allows them to be more efficient and operate in new areas, such as logistics.
• Transport. AI is fundamental to the operation of autonomous vehicles, since it is responsible for managing traffic, predicting flight delays and making transport safer and more efficient. This applies to land, sea and rail transport.
• Security. Organisations are applying machine learning to security information and event management (SIEM) software and related areas to detect anomalies and identify suspicious activities indicative of threats. By analysing data and using logic to identify similarities with known malware, AI can provide alerts on new and emerging attacks much earlier than human employees and previous iterations of technology.

In addition, AI is expected to be applied in the future to other areas that are now less digitised, such as everything related to, for example, law.