17 posts found
Altruistic projects to create AI models in co-official languages
Artificial intelligence (AI) assistants are already part of our daily lives: we ask them the time, how to get to a certain place or we ask them to play our favorite song. And although AI, in the future, may offer us infinite functionalities, we must not forget that linguistic diversity is still a pe…
AI Data Readiness: Preparing Data for Artificial Intelligence
Over the last few years we have seen spectacular advances in the use of artificial intelligence (AI) and, behind all these achievements, we will always find the same common ingredient: data. An illustrative example known to everyone is that of the language models used by OpenAI for its famous ChatGP…
Federated machine learning: generating value from shared data while maintaining privacy
Data is a fundamental resource for improving our quality of life because it enables better decision-making processes to create personalised products and services, both in the public and private sectors. In contexts such as health, mobility, energy or education, the use of data facilitates more effic…
ALIA and foundational models What are they and why are they key to the future of AI?
The enormous acceleration of innovation in artificial intelligence (AI) in recent years has largely revolved around the development of so-called "foundational models". Also known as Large [X] Models (Large [X] Models or LxM), Foundation Models, as defined by the Center for Research on Foundation Mod…
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…
Data Sandboxes: Exploring the potential of open data in a secure environment
Data sandboxes are tools that provide us with environments to test new data-related practices and technologies, making them powerful instruments for managing and using data securely and effectively. These spaces are very useful in determining whether and under what conditions it is feasibl…
Global principles of AI journalism
General ethical frameworks
The absence of a common, unified, ethical framework for the use of artificial intelligence in the world is only apparent and, in a sense, a myth. There are a multitude of supranational charters, manuals and sets of standards that set out principles of ethical use, although…
Artificial intelligence to improve interoperability in the European public sector
The European Union has placed the digital transformation of the public sector at the heart of its policy agenda. Through various initiatives under the Digital Decade policy programme, the EU aims to boost the efficiency of public services and provide a better experience for citizens.…
New Year's resolution: Apply the UNE data specifications in your organisation
As tradition dictates, the end of the year is a good time to reflect on our goals and objectives for the new phase that begins after the chimes. In data, the start of a new year also provides opportunities to chart an interoperable and digital future that will enable the development of a robust data…
Application of the UNE 0081:2023 Specification for data quality evaluation
The new UNE 0081 Data Quality Assessment specification, focused on data as a product (datasets or databases), complements the UNE 0079 Data Quality Management specification, which we analyse in this article, and focuses on data quality management processes. Both standards 0079 and 008…
