17 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 importance of data training for public sector workers
There is no doubt that digital skills training is necessary today. Basic digital skills are essential to be able to interact in a society where technology already plays a cross-cutting role. In particular, it is important to know the basics of the technology for working with data.
In this context, p…
What data governance should look like in open source AI models
Open source artificial intelligence (AI) is an opportunity to democratise innovation and avoid the concentration of power in the technology industry. However, their development is highly dependent on the availability of high quality datasets and the implementation of robust data governance framework…
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…
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…
Data policies that foster innovation
The importance of data in today's society and economy is no longer in doubt. Data is now present in virtually every aspect of our lives. This is why more and more countries have been incorporating specific data-related regulations into their policies: whether they relate to personal, busin…
Segment Anything Model: Key Insights from Meta's Segmentation Model Applied to Spatial Data
Image segmentation is a method that divides a digital image into subgroups (segments) to reduce its complexity, thus facilitating its processing or analysis. The purpose of segmentation is to assign labels to pixels to identify objects, people, or other elements in the image.
Image segmentation is c…
Vinalod: The tool to make open datasets more accessible
Public administration is working to ensure access to open data, in order to empowering citizens in their right to information. Aligned with this objective, the European open data portal (data.europa.eu) references a large volume of data on a variety of topics.
However, although the data belong to di…
Open data as a tool for education and training
The demand for professionals with skills related to data analytics continues to grow and it is already estimated that just the industry in Spain would need more than 90,000 data and artificial intelligence professionals to boost the economy. Training professionals who can fill this gap is a major ch…
What are the main elements of a data space?
For a data space to function properly, it is necessary to have sufficient actors to cover a set of roles and a set of technological components. These elements enable a common governance framework to be established for secure data sharing, ensuring the sovereignty of the participants over their own d…
