11 posts found
How to build a citizen science initiative considering open data from the start
Citizen participation in the collection of scientific data promotes a more democratic science, by involving society in R+D+i processes and reinforcing accountability. In this sense, there are a variety of citizen science initiatives launched by entities such as CSIC, CENEAM or CREAF, among oth…
Computer use: the AI that learns how to operate your computer
The evolution of generative AI has been dizzying: from the first great language models that impressed us with their ability to reproduce human reading and writing, through the advanced RAG (Retrieval-Augmented Generation) techniques that quantitatively improved the quality of the responses provided…
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…
Citizen science projects that encourage public knowledge
Citizen science is consolidating itself as one of the most relevant sources of most relevant sources of reference in contemporary research contemporary research. This is recognised by the Centro Superior de Investigaciones Científicas (CSIC), which defines citizen science as a methodology and a mean…
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…
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…
RAG - Retrieval Augmented Generation: The key that unlocks the door to precision language models
Teaching computers to understand how humans speak and write is a long-standing challenge in the field of artificial intelligence, known as natural language processing (NLP). However, in the last two years or so, we have seen the fall of this old stronghold with the advent of large language models (L…
Open Data and Sustainable Development Goals
In 2015, the UN adopted the 2030 Agenda for Sustainable Development, an action plan made up of 17 global goals to eradicate poverty, protect the planet and ensure prosperity. This is what is known as the Sustainable Development Goals (SDGs).
In order to measure and evaluate the progress of the SDGs…
