AI WINTER

What is it and why should it be avoided?

Since its development began in the 1970s, Artificial Intelligence has gone through different stages of expansion and decline, popularly known as AI summers and winters. But why is this happening? What causes this growth and decline? And, more importantly, why does its slowdown, better known as winter, need to be avoided?
Summer and winter in Artificial Intelligence

The terms “AI summer” or “AI winter” were first coined in the United States in 1984, when analysts and scholars of AI evolution discovered that the early years of AI’s great expansion were followed by a significant period of disenchantment, disillusionment and widespread pessimism. Referring to the concept of “nuclear winter” that also emerged at that time, the term “AI winter” was first coined to give a name to the phase that had just become part of AI history.

What motivates the emergence of these two phases? The main key is public interest, as this is a determining factor and the trigger for the popularisation of artificial intelligence and its place at the centre of public debate and focus. This growing interest is causing more and more private companies to bet on the use of artificial intelligence, thus achieving even greater interest in this technology and a consequent increase in funding. The investment is what allows AI to continue to develop and grow exponentially, achieving important advances in this area. This is what is known as the “summer of AI”.

How did we move so dramatically from a time of growth and boom to a time of distrust and slowdown for AI? Once again, the trigger is public interest. The accelerated take-off of this technology is beginning to generate an excessive growth in expectations of its use, which, on many occasions, become unrealistic and unattainable, and this begins to arouse mistrust or loss of interest. And, as was the case in the “summer”, this begins to affect financing, causing a decline in investment. Thus begins an obligatory stage of underdevelopment that we call “winter”.

And now? Is winter coming?

Although it sounds like a question from the popular Game of Thrones series, this is the question that many analysts and AI experts around the world are asking themselves. Do we know where we stand? Artificial Intelligence has been expanding over the last decade, driven in part by the development of Machine Learning and Deep Learning.

It is an era of great advances and major challenges, with great potential for development ahead. According to the Gartner Report “Emerging Trends in AI”, by 2030, 80% of interactions between companies and customers will be managed by AI, which further reinforces the growth forecast for this technology. However, despite the favourable forecasts, it is necessary to continue betting on AI and working on its development in order to guarantee its future.

The only way to avoid AI’s winter is to know its true potential, to bet on it and to keep working on its development.

 

Despite this recent period of expansion, it is essential to continue investing in Artificial Intelligence to avoid falling into the pessimism of winter and to continue working on making the most of this technology, which still has much to contribute.

Because AI is here to stay and revolutionise the market by extracting knowledge from every piece of data to automate countless processes of real use to companies.

But we must focus on realistic solutions that work, such as ENAIA, a single AI platform with different applications to automate all kinds of tasks and offer maximum performance now and in the future.

AI is continuously learning and improving while it is in operation (continual learning), which makes it not only a present solution, but a living technology capable of adapting to future needs, helping companies, like yours, in a wide variety of tasks, such as:

Visual Inspection. ENAIA’s Artificial Intelligence makes all types of visual inspection tasks in companies more efficient.

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Natural Lenguage Processing (NLP). ENAIA’s Artificial Intelligence makes it possible to quickly optimise and organise processes related to natural language.

Predictive Manteinance. ENAIA’s Artificial Intelligence allows companies to look ahead and predict problems before they become a threat.

Data Mining. ENAIA’S Artificial Intelligence can analyse data in tables to extract relevant information.

Predicction of Time Series. ENAIA’s Artificial Intelligence uses data to predict values (past or future) thereby improving the company’s organisation.

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