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All about generative AI

The future of ideas: artificial creativity

What is generative AI?

AI is already emerging as the future of technology, from its most mundane applications to the great possibilities it has opened up in fields ranging from cybersecurity and health to agriculture and industrial processes.

The possibilities and applications of generative AI are as vast as the areas of human knowledge. Also in the great challenges ahead of us as a society, such as emissions reduction and the energy transition. Repsol, which is steadily advancing in its digital transformation, is already using them in its Competence Center.

Artificial intelligence systems are capable of creating texts, codes, images, or audio by learning from big data models. The so-called generative AI, which Repsol is already applying to achieve its goal of reaching net zero emissions by 2050.

To understand the potential of generative AI, it is necessary to understand how it works in conjunction with big data and deep learning. Starting from large volumes of data, artificial intelligences are capable of automatically learning patterns and structures and creating similar models. This is a field of knowledge in continuous development, but today generative AI already offers many promising applications, ranging from entertainment, information, and the arts, to the fields of computer programming, mathematics, or scientific research.

Advantages of generative AI

The applications of generative AI are evolving rapidly and extending to more and more areas of knowledge:

Work context

They increase worker productivity and make their day-to-day work more efficient, allowing them to focus on strategic issues where they can contribute more value and freeing them from more mechanical or repetitive work.

Artistic creation

They are able to replicate human language and use large volumes of data to learn how to create all kinds of designs, which can be used to come up with creative ideas to complement those of human creators.

Companies and institutions

Based on the learning of large amounts of information, it generates predictions based on statistical models. Its use in marketing, investment, or product design ensures that decisions are made based on data and information analysis.

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Examples of generative artificial intelligence

Generative AI can learn and is capable of reproducing messages and creating new ideas from any type of language or code, which opens up a very wide range of applications. Informative or commercial texts, technical reports, conversational bots, content translation, image creation, or even video are some of the most obvious applications, but its utilities can be much broader and more complex when we enter specific professional fields.
In programming and application development, for example, generative AI can automate part of the tasks required to write the code that leads to new software or to check bugs, thus speeding up the process. Meanwhile, with a similar learning system, generative AI can create musical compositions instantaneously from text commands, once it has understood the musical language.
Undoubtedly, one of the areas in which generative AI can have the most promising applications is in the field of healthcare, where cross-checking the enormous amount of information that exists in record time is, on many occasions, a vital issue. For example, generative AI is capable of analyzing large volumes of amino acid sequences and creating similar models, which will be of great use for medical and pharmaceutical research. Mathematical language can also be reproduced by these Artificial Intelligence systems, which are capable of generating complex algorithms quickly and efficiently.
In terms of design, generative AI is already used for decision making, for example, in product prototyping, construction, or fashion, as it allows trends to be defined and predicted based on data analysis.

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Our generative AI projects

Aware of the great possibilities that are opening up for companies, Repsol has launched the first generative AI Competence Center in the energy sector in Europe in order to safely and responsibly explore the opportunities that generative artificial intelligence offers its businesses and employees in meeting its goal of net zero emissions by 2050.

The team that makes up this center is multidisciplinary, given the nature of the project: data scientists and data engineers, as well as experts from different fields such as cybersecurity, auditing, people and organization professionals, or legal specialists, among other profiles. All will explore how generative AI can be used to accelerate the digital transformation of the company and identify and implement the uses that will generate value in their business areas. The work of the Competence Center will also make it possible, thanks to these applications, to make the day-to-day work of Repsol employees easier and increase the company's efficiency in the development of technological solutions. The main objectives of this Competence Center are:

Identify and implement cases in which the use of these new Generative AI models could add value to our business units by accelerating their digital transformation.
Promote new ways of working for our professionals that will allow them to explore these tools to make them more beneficial in their day-to-day work.
Improve productivity through the development and application of technological and digital solutions.

Now immersed in the 2^nd wave of the digital program (2023–2025), we face a great challenge, to be able to develop and implement solutions based on generative AI that accelerate Repsol's Digitalization Program in a safe and responsible way.