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You wake up in the morning and your phone unlocks after scanning your face. You get in the car to go to work and your GPS navigation suggests an alternative route because there’s more traffic than usual on the one you take every day. Your favorite shopping app suggests a pair of shoes that suits your style, and your bank sends you a notification about a product that fits in perfectly with your savings plans. Is it magic? No, it's progress. It's artificial intelligence, which has gone beyond science fiction to improve many aspects of our daily lives.

What is artificial intelligence?

Artificial intelligence (AI) is a branch of computer science that develops programs capable of emulating human intelligence processes. In other words, machines can analyze the environment and perform certain actions more or less autonomously to achieve specific objectives.

For example, a chatbot is capable of interpreting the problems posed by the customers of a shop or company and offering them more precise answers, just as a recommendation engine makes suggestions according to the preferences that the user has previously shown.

Despite its current boom, it is not a new concept. In the 1950s, Alan Turing already wondered whether machines would be able to think. This gave rise to what is now known as the "Turing test", which is used to determine whether a computer can be as intelligent as a human being. It consists of exposing a human being to two conversations, one conducted by a machine and the other by a human being. If the person is unable to distinguish which is the machine, it is assumed that the machine is as intelligent as the human. In 1956, John MacCarthy was the first to utter the term "artificial intelligence" at the Darthmouth Conference. 

From that time to the present day, its evolution has been constant and exponential, with new AI disciplines emerging.

Types of artificial intelligence

Antonio Brufau y Josu Jon Imaz en la Junta General de Accionistas 2023
According to their purpose:
 
  • Machine learning: The ability of an artificial intelligence to learn by itself. It is based on a cycle of learning from data, training, and results. There are several subtypes depending on whether its learning requires human supervision or whether the AI is allowed to learn autonomously, according to established rules. It is often used with virtual assistants and chatbots, among others.
  • Deep learning: This aims to recreate how humans learn through what are called neural networks, which consist of interconnected nodes that emulate the network of neurons in a human brain. It is used, for example, in image-based product searches.
  • Reinforcement learning: It is inspired by behavioral psychology and aims to enable AI to design strategies automatically. It is very practical for predictive maintenance or personalizing customer experiences.
  • Generative adversarial networks: These are a type of algorithms that are implemented by a system of two neural networks. These two networks compete with each other. It is used to generate objects and experiences from samples (e.g., photographs).
  • Natural language processing: This investigates how machines communicate with people with the aim of making them understand and extract relevant information. Its applications are manifold, ranging from sentiment or opinion analysis to document anonymization and chatbot training.
  • Computer vision: This teaches computers to "see" and interpret the content of digital images, so that they can produce symbolic information that can be interpreted. It is used for object recognition, image restoration, and scene reconstruction.
  • Speech recognition: It is intended to enable humans to communicate with computers and vice versa and is especially useful for voice-controlled vehicle navigation systems, dictation applications, and systems for people with disabilities.
  • Knowledge graph: A graph is a way of representing relationships between entities and creating links between data and metadata. When the content of graphs is enriched and they are able to perform automatic "intelligent" processing of data, they become knowledge graphs. They are very popular in information organization systems. 
  • Augmented reality: This is a set of technologies that allow the user to interact with the real world through devices that add virtual graphical information, so that the users see the world around them at the same time, but with virtual objects superimposed. It is used in a huge number of applications, from operations to virtual testing of make-up colors to recreating how a particular piece of furniture will look in your home.
Elderly man having difficulty using his computer

Data is at the heart of the development of artificial intelligence. To enhance its value, it is essential to use technological advances and new approaches to design modern data architectures to facilitate access to data. Today, it is useful to be familiar with these concepts:

  • Data Mesh: a self-service infrastructure that allows teams to access resources and tools on demand and decentralizes management while distributing responsibility for data. All data is available anywhere in the company, making it easy to access when needed.
  • Data Fabric: a method to simplify and integrate data management in the cloud and on-premises. It provides uniform access to data across a variety of multi-cloud environments, as well as consistent features.
  • Synthetic Data: These enable a new data set to be generated from another set of data that we need to protect and need to share with third parties. This new set retains the characteristics of the first set but does not allow the original data to be recomposed.

Uses and applications of artificial intelligence

Artificial intelligence is present in many aspects of our lives and can be found in a variety of applications in different fields. So, let's take a look at how to use artificial intelligence:

Elderly man having difficulty using his computer

Artificial intelligence in medicine

In the health sector, there are chatbots capable of analyzing the symptoms we indicate and issuing a preliminary diagnosis. Similarly, by analyzing certain data, it is possible to determine the propensity to develop certain diseases, such as breast cancer, for example.

Elderly man having difficulty using his computer

Artificial intelligence in the education sector

Artificial intelligence is able to make personalized course proposals, improve online tutoring, and analyze students' skills using learning analytics to understand their educational needs.

Elderly man having difficulty using his computer

Artificial intelligence in the transportation and energy sector

Using artificial intelligence not only helps to optimize routes in terms of both time and energy consumption. It also helps to reduce road accidents, anticipate potential problems by predicting the need for vehicle maintenance in advance, and plan transportation routes according to demand and capacity, among other benefits. In addition, it's already a fundamental part of electric vehicles, enabling data to be managed and transmitted between different connected devices. 

Elderly man having difficulty using his computer

Artificial intelligence in banking

Artificial intelligence can detect potential fraud (e.g., money laundering), predict market behavior and advise on the right transactions and products for each customer.

Elderly man having difficulty using his computer

Artificial intelligence in marketing and advertising

Thanks to artificial intelligence, it is possible to make sales predictions for certain products and services, as well as to make personalized recommendations to customers based on previous choices.

Repsol and artificial intelligence

Repsol is aware of the benefits of artificial intelligence for human beings in terms of digital transformation, but it also represents a growth opportunity for Spain's economy. It's estimated that the impact of its application in industry will be €16.5 billion by 2025, as presented at the 1st IndesIA Forum: The impact of Artificial Intelligence in Industry. Repsol CEO Josu Jon Imaz highlighted in this forum the importance of artificial intelligence to "improve competitiveness and help transform the ecosystem."

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Other advantages of ARiA

Lowers operations costs and improves the energy efficiency of the company's assets by predicting energy consumption.

We have avoided the emission of 28,000 metric tonnes of CO2 in 2021. 

It helps other companies to launch and speed up the use of big data and AI in their businesses.