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…
From data strategy to data governance system (part 1)
More and more organisations are deciding to govern their data to ensure that it is relevant, adequate and sufficient for its intended uses, i.e. that it has a certain organisational value.
Although the scenarios are often very diverse, a close look at needs and intentions reveals that many of these…
From data strategy to data governance system (part 2)
In the first part of this article, the concept of data strategy was introduced as the organisation's effort to put the necessary data at the service of its business strategy. In this second part, we will explore some aspects related to the materialisation of such a strategy as part of the design or…
The data sphere we live in: the interconnected data system
As technology and connectivity have advanced in recent years, we have entered a new era in which data never sleeps and the amount of data circulating is greater than ever. Today, we could say that we live enclosed in a sphere surrounded by data and this has made us more and more dependent on it. On…
Artificial intelligence impact on business value chain
The commercial adoption of any new technology and, therefore, its incorporation into the business value chain follows a cycle that can be moulded in different ways. One of the best known models is the Gartner hype cycle. With regard to artificial intelligence and data science, the current discussion…
Factors that define open data impact
The final impact that can be obtained through an open data initiative will ultimately depend on multiple interrelated factors that will be present (or absent) in these initiatives. That is why the GovLab of New York University has analyzed these factors thanks to the study of the several use cases c…
