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…
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…
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…
A common language to enable interoperability between open dataset catalogs
Open data plays a relevant role in technological development for many reasons. For example, it is a fundamental component in informed decision making, in process evaluation or even in driving technological innovation. Provided they are of the highest quality, up-to-date and ethically sound, data can…
MAMD Methodology: The Alarcos Model of Data Improvement
There is such a close relationship between data management, data quality management and data governance that the terms are often used interchangeably or confused. However, there are important nuances.
The overall objective of data management is to ensure that data meets the business requirements tha…
Kaggle and other alternative platforms for learning data science
The profession of the data scientist is booming. According to him 2020 LinkedIn Emerging Jobs Report, the demand for data science specialists grew 46.8% compared to the previous year, being especially demanded in sectors such as banking, telecommunications or research. The report also indicates…
Examples of uncommon open data repositories
Beyond public administrations, libraries, museums and cultural foundations data, the interest in open data knows no borders. We invite you to discover it in this post.
Normally, the concept of open data is associated with those repositories managed by public administrations, foundations and cultural…
Play to be the best with data
Publicly competing with your colleagues to solve a complex problem based on data is an irresistible motivation for some people. Almost as tempting as gaining relevance in a field of expertise as exciting and lucrative as data science.
Public competitions to solve complex problems, whose raw material…
