27 posts found
The rise of predictive commerce: open data to anticipate needs
In a world where immediacy is becoming increasingly important, predictive commerce has become a key tool for anticipating consumer behaviors, optimizing decisions, and offering personalized experiences. It's no longer just about reacting to the customer's needs, it's about predicting what they…
How to ensure the authenticity of satellite imagery
Synthetic images are visual representations artificially generated by algorithms and computational techniques, rather than being captured directly from reality with cameras or sensors. They are produced from different methods, among which the antagonistic generative networks (Generative Adversarial…
Changes to the INSPIRE cchemes: What do they mean and how to adapt?
In February 2024, the European geospatial community took a major step forward with the first major update of the INSPIRE implementation schemes in almost a decade. This update, which generates version 5.0 of the schemas, introduces changes that affect the way spatial data are harmonised, transformed…
GeoPackage in INSPIRE: efficiency and usability for geospatial data geospatial data.
In the field of geospatial data, encoding and standardisation play a key role in ensuring interoperability between systems and improving accessibility to information.
The INSPIRE Directive (Infrastructure for Spatial Information in Europe) determines the general rules for the establishment of an Inf…
Using Pandas for quality error reduction in data repositories
There is no doubt that data has become the strategic asset for organisations. Today, it is essential to ensure that decisions are based on quality data, regardless of the alignment they follow: data analytics, artificial intelligence or reporting. However, ensuring data repositories with high levels…
Understanding Word Embeddings: how machines learn the meaning of words
Natural language processing (NLP) is a branch of artificial intelligence that allows machines to understand and manipulate human language. At the core of many modern applications, such as virtual assistants, machine translation and chatbots, are word embeddings. But what exactly are they and why are…
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…
Open data and generative AI: synergies and use cases
Artificial intelligence (AI) is revolutionising the way we create and consume content. From automating repetitive tasks to personalising experiences, AI offers tools that are changing the landscape of marketing, communication and creativity.
These artificial intelligences need to be trained wi…
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…
Complying with Europe. The Mobility High Value Datasets Regulation
Spain, as part of the European Union, is committed to the implementation of the European directives on open data and re-use of public sector information. This includes the adoption of initiatives such as the Implementing Regulation (EU) 2023/138 issued by the European Commission, whic…
