10 posts found
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…
How Artificial Intelligence and Open Data can re-imagine our cultural future
We are currently in the midst of an unprecedented race to master innovations in Artificial Intelligence. Over the past year, the star of the show has been Generative Artificial Intelligence (GenAI), i.e., that which is capable of generating original and creative content such as images, text or music…
Hot OSM: Collaborative mapping to coordinate emergency response
The humanitarian crisis following the earthquake in Haiti in 2010 was the starting point for a voluntary initiative to create maps to identify the level of damage and vulnerability by areas, and thus to coordinate emergency teams. Since then, the collaborative mapping project known as Hot OSM (OpenS…
Open data as a source of knowledge for generative artificial intelligence
Generative artificial intelligence refers to machine’s ability to generate original and creative content, such as images, text or music, from a set of input data. As far as text generation is concerned, these models have been accessible, in an experimental format, for some time, but began to generat…
Artificial Intelligence applied to the identification and classification of diseases detected by radiodiagnosis
In this post we have described step-by-step a data science exercise in which we try to train a deep learning model with a view to automatically classifying medical images of healthy and sick people.
Diagnostic imaging has been around for many years in the hospitals of develo…
Formulas for accelerating data collaboration
After a period in which efforts were focused on releasing data, mainly from the public sector, in conditions in which it could be reused to create value in its different forms (economic, social, cultural, etc.), we are finding increasing activity around collaboration between organizations to solve b…
Google as a reuse of open data
The bet of the technological giant Google with open data it has been evident in various initiatives carried out in recent years. On the one hand, they launched the search engine Google Dataset Search, that facilitates the location of open data published in hundreds of repositories of international i…
Data Science, machine learning and deep learning
Data science is an interdisciplinary field that seeks to extract actuable knowledge from datasets, structured in databases or unstructured as texts, audios or videos. Thanks to the application of new techniques, data science is allowing for answering questions that are not easy to solve through othe…
The ecosystem that nourishes open data
On too many occasions, open data initiatives are born in governments as purely technical projects whose purpose is simply creating a data catalog, when, in reality, they should be seen as collaborative transformation projects that take place within complex and variable environments, in which th…
