Shelf Blog
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
Data augmentation is a pivotal technique in the realm of Natural Language Processing (NLP). It’s used to expand and diversify training datasets, thereby enhancing the performance and robustness of AI models. This technique is crucial for AI practitioners, data scientists, and technologists who aim...
Foundation models are a cornerstone in how we approach, develop, and implement AI technologies. These models, with their ability to learn from vast datasets and adapt to a multitude of tasks, represent a significant leap in AI’s evolution. Whether you’re an IT professional looking to deepen...
Navigating the multifaceted nature of human language is a unique challenge for machines. Ambiguous words, phrases, sentences, and contexts make language models struggle to understand and interpret human language with nuance and precision. Addressing ambiguity, therefore, is crucial for modern...
Augmented Shelf | Issue 4 | April 3, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Street Fighting LLMs Ready for a digital brawl like no other? In a groundbreaking experiment, cutting-edge Language Models (LLMs)...
Recurrent Neural Networks (RNNs) are a class of artificial neural networks uniquely designed to handle sequential data. At its core, an RNN is like having a memory that captures information from what it has previously seen. This makes it exceptionally suited for tasks where the order and context...
At the core of human cognition is the concept of “attention,” a mechanism that allows us to focus on particular elements of our environment while filtering out others. This concept has inspired a transformative feature in deep learning models: the attention mechanism. By emulating the way humans...
A knowledge graph is a structure that connects diverse pieces of information, helping you uncover relationships and insights that might not be immediately apparent. In some cases, you need to bridge two types of data together: structured and unstructured data. In this article, we provide a clear,...
Augmented Shelf | Issue 3 | March 26, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Enterprises Quintuple-Down on GenAI in 2024 New research from a16z punctuates the enterprise sector’s growing bet on...
Data mesh and data fabric are two architectural paradigms that are shaping the future of data management and analytics. At their core, both aim to address the complexities of handling vast and diverse data in modern organizations, but they approach the challenge from different angles. In this...
Whenever you interact with a large language model (LLM), the model’s output is only as good as your input. If you offer the AI a poor prompt, you’ll limit the quality of its response. So it’s important to understand zero-shot and few-shot prompting as you can use these techniques to get better...
Augmented Shelf | Issue 2 | March 19, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Evil Geniuses Vs. ChatDev To evaluate the vulnerability of LLM-based agents, researchers at Tsinghua University in Beijing, China, have...
Large Language Models (LLMs) rely on extensive memory to store and manipulate vast datasets, a key factor that allows them to learn from past inputs and improve their linguistic abilities over time. But what if, alongside remembering, LLMs could also benefit from adaptive forgetting? The notion of...