38 posts found
Explainable artificial intelligence (XAI): how open data can help understand algorithms
The increasing adoption of artificial intelligence (AI) systems in critical areas such as public administration, financial services or healthcare has brought the need for algorithmic transparency to the forefront. The complexity of AI models used to make decisions such as granting credit or making a…
The role of open data in the evolution of SLM and LLM: efficiency vs. power
Language models are at the epicentre of the technological paradigm shift that has been taking place in generative artificial intelligence (AI) over the last two years. From the tools with which we interact in natural language to generate text, images or videos and which we use to create creativ…
Common mistakes in the development of a data strategy
In an increasingly data-driven world, all organisations, both private companies and public bodies, are looking to leverage their information to make better decisions, improve the efficiency of their processes and meet their strategic objectives. However, creating an effective data strategy is a chal…
Destination Earth: a digital Earth twin for a sustainable future
Today's climate crisis and environmental challenges demand innovative and effective responses. In this context, the European Commission's Destination Earth (DestinE) initiative is a pioneering project that aims to develop a highly accurate digital model of our planet.
Through this digital twin…
Open data in local authorities: priorities and highlighted datasets
Local public bodies, such as county councils and municipalities, play a crucial role in opening their data to the public. Making data available to citizens not only builds trust in institutions, but also drives innovation, facilitates citizen participation and promotes informed decision-making. Thro…
SLM, LLM, RAG and Fine-tuning: Pillars of Modern Generative AI
In the fast-paced world of Generative Artificial Intelligence (AI), there are several concepts that have become fundamental to understanding and harnessing the potential of this technology. Today we focus on four: Small Language Models(SLM), Large Language Models(LLM), Retrieval Augmented Generation…
RAG techniques: how they work and examples of use cases
In recent months we have seen how the large language models (LLMs ) that enable Generative Artificial Intelligence (GenAI) applications have been improving in terms of accuracy and reliability. RAG (Retrieval Augmented Generation) techniques have allowed us to use the full power of n…
Data reuse and data governance in the new AI 2024 strategy
The Artificial Intelligence Strategy 2024 is the comprehensive plan that establishes a framework to accelerate the development and expansion of artificial intelligence (AI) in Spain. This strategy was approved, at the proposal of the Ministry for Digital Transformation and the Ci…
The impact of open data along its value chain: Indicators and future directions
The transformative potential of open data initiatives is now widely recognised as they offer opportunities for fostering innovation, greater transparency and improved efficiency in many processes. However, reliable measurement of the real impact of these initiatives is difficult to obtain.
From this…
GRAPH QL. Your best ally for the creation of data products.
The era of digitalisation in which we find ourselves has filled our daily lives with data products or data-driven products. In this post we discover what they are and show you one of the key data technologies to design and build this kind of products: GraphQL.
Introduction
Let's start at the beginni…
