Shelf Blog: AI Education

Data hydration, the process of enhancing and enriching existing data, has become increasingly vital in the era of big data and artificial intelligence. In this article, we explore the concept of data hydration, the challenges organizations face in managing structured and unstructured data, and the...

As artificial intelligence continues to push boundaries and redefine industries, Generative Adversarial Networks (GAN) have emerged as a game-changer. GANs are transforming the way we generate creative content, from artwork to music, and are revolutionizing fields such as healthcare, art,...

For the successful implementation of Artificial Intelligence (AI), the significance of properly integrating content metadata in AI with Large Language Models (LLMs) cannot be overstated. LLMs, such as Llama, Mistral and Claude, have become instrumental in a myriad of applications, ranging from...

Computers are great at understanding numbers, but not with words. In order to help machines understand, manipulate, and produce words, we have to convert those words to numbers using a process called text vectorization. Text vectorization is the process of turning words and documents into...

From its inception in the theoretical halls of mid-20th century academia to the sophisticated, AI-driven algorithms of today, the evolution of NLP has not only advanced our understanding of language processing but also pushed the frontiers of what’s possible, transforming how we interact...

We encounter content chunks every day. Think of a recipe. A recipe contains content components like a title, a list of ingredients, cooking times, pictures of food, and instructions that contain individual steps. These are “chunks” that together compose a recipe. The process of chunking this...

Natural Language Processing (NLP) is an interdisciplinary field blending computer science, artificial intelligence, and linguistics, aimed at enabling computers to understand, interpret, and engage with human language in both written and spoken forms. NLP combines computational linguistics with...

The field of Natural Language Processing (NLP) has witnessed significant advancements, yet it continues to face notable challenges and considerations. These obstacles not only highlight the complexity of human language but also underscore the need for careful and responsible development of NLP...

Can we really trust Artificial Intelligence? Let’s face it. AI has trust issues. AI is rapidly permeating our lives. But perhaps even more rapidly permeating, are fears about AI. Fears that are largely due to a lack of transparency as to how AI works. These concerns are evident in questions people...

What Is Bias in AI? In the realm of artificial intelligence (AI), bias is an anomaly that skews outcomes, often reflecting societal inequities. AI bias can originate from various sources, including the data used to train AI models, the design of algorithms themselves, and the way results are...

The effectiveness of AI implementations, such as generative AI, is intrinsically linked to the quality and structure of the underlying data. However, maintaining the relevance and quality of this data is not a one-time task. It requires a continuous improvement approach, where machine learning...

In machine learning, embeddings are a technique used to represent complex, high-dimensional data like words, sentences, or even entire documents in a more manageable, lower-dimensional space. An analogy would be nice. Right. Think about Lego bricks. A lot of them. High-dimensional data is like the...