13 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…
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…
The dataspace of tourism
Europe is developing a common data space for tourism, aiming to integrate various stakeholders, including local and regional authorities, the private sector, and multiple member states. Spain is among them, where several workshops have already been conducted as part of the process to energize…
Use case development model for data spaces
We live in the era of data, a lever of digital transformation and a strategic asset for innovation and the development of new technologies and services. Data, beyond the skills it brings to the generator and/or owner of the same, also has the peculiarity of being a non-rival asset. This means that i…
The dataspaces starter kit
A data space is a development framework that enables the creation of a complete ecosystem by providing an organisational, regulatory, technical and governance structure with the objective of facilitating the reliable and secure exchange of different data assets for the common benefit of all actors i…
When to use each programming language in data science?
Python, R, SQL, JavaScript, C++, HTML... Nowadays we can find a multitude of programming languages that allow us to develop software programmes, applications, web pages, etc. Each one has unique characteristics that differentiate it from the rest and make it more appropriate for certain tasks. But h…
10 Popular natural language processing libraries
The advance of supercomputing and data analytics in fields as diverse as social networks or customer service is encouraging a part of artificial intelligence (AI) to focus on developing algorithms capable of processing and generating natural language.
To be able to carry out this task in the current…
10 Popular Data Analytics and Machine Learning Libraries
Programming libraries refer to the sets of code files that have been created to develop software in a simple way . Thanks to them, developers can avoid code duplication and minimize errors with greater agility and lower cost. There are many bookstores, focused on different activities. A few weeks ag…
11 libraries for creating data visualisations
Programming libraries are sets of code files that are used to develop software. Their purpose is to facilitate programming by providing common functionalities that have already been solved by other programmers.
Libraries are an essential component for developers to be able to program in a simple way…
