The tools of the AI revolution

In recent decades, those who managed to adapt early (or better still, pre-emptively) to the advent of the Internet found themselves on a clear path to unprecedented economic success. Relying on the Internet to enhance existing businesses or create new ones has been the discriminating factor between success and failure. This has taught anyone doing business that, today more than ever, they need to adapt their pace to that of technological innovation. And if until a few years ago it was still unclear what the ‘next big thing’ would be, today there is no doubt: Artificial Intelligence, in its various forms, is preparing to overturn global economic scenarios, as well as people’s way of life.

As interest in this fascinating technology, which has been portrayed with great evocative power by the media, grows, so does the need for clarity. Broadly speaking, artificial intelligence can be described as the ability of a computer to partially perform functions and reasoning typical of the human mind in order to carry out tasks or solve problems. Albeit reductive, such a definition opens a window on the potential practical implications of this technology.

Specifically, the most interesting “skill” of artificial intelligence today is the possibility of learning autonomously or through examples and refining its capacity to interpret the context and the information it comes into contact with. This ability is called Machine Learning.

The ‘fuel’ of learning is data, exactly as happens for human learning, but with different proportions. In fact, the computing power of supercomputers allows them to process enormous quantities of information in a systematic and virtually infinite manner.

A volume of data that is so large, varied and changing and that requires advanced computing tools such as AI to analyse it (such as that produced by smartphones in their daily use) is called Big Data. Once collected and organised, the data can be fed to Machine Learning algorithms to deduce ordered and contextualised knowledge, which will be the basis for the elaboration of strategies and forecasting models. This process is known as Data Mining.

The importance of Big Data is clear: within that apparently indistinct mass of raw data lies precious information which, once extracted and interpreted, can become strategic for substantially improving products and services, reducing costs, optimising resources and predicting the evolution of future scenarios.

The combined use of data mining and machine learning techniques has resulted in extremely effective analytical tools. Such tools are fundamental for companies willing to adapt their offerings to the changing needs of the global market.

For example, a fashion company could rely on analytics to identify categories of customers that value certain products and when they are most likely to make purchases during the year. This knowledge will give the company a clear picture of their target audience allowing them to tailor their marketing strategies to match gender, age, geography and related preferences.

This can prove vital in optimising marketing costs and avoiding costly and often unsuccessful traditional market research.

Although these technologies have enormous potential, they must always be modelled and redesigned according to the context in which they are integrated. For this reason, each individual case must be evaluated by experts who are able to explore the data, decipher the models and assess the results.

Presago provides companies with a team of data scientists capable of maximising the performance of the technologies used in each project. This allows our partners to gain a strategic advantage over their competitors and open up new business opportunities.

Contact us to book a free consultation.