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As the deployment of Large Language Models (LLMs) continues to expand across sectors such as healthcare, banking, education, and retail, the need to understand and effectively evaluate their capabilities grows with each new application. Solid LLM evaluation metrics for assessing output quality are...
Successful AI projects require more than just cutting-edge technology. They demand a clear vision, robust data governance, ethical considerations, and an adaptive organizational culture. In this article, we delve into the common pitfalls that can derail AI projects. We also offer insights and...
Hallucinations and ungrounded results are a significant challenge in Content Processing systems. When AI-generated content contains statements that are inconsistent with the input data or knowledge base, it can lead to the spread of misinformation and erode trust in the system. Microsoft Azure’s...
Subject Matter Experts (SMEs) are the architects of quality and precision in AI development. But how can you be the best SME for your organization’s AI output review initiatives? SMEs are presented with a great responsibility – to identify discrepancies, biases, and areas for potential...
As the use of Retrieval-Augmented Generation (RAG) systems becomes more common in countless industries, ensuring their performance and fairness has become more critical than ever. RAG systems, which enhance content generation by integrating retrieval mechanisms, are powerful tools to improve...
Output evaluation is the process through which the functionality and efficiency of AI-generated responses are rigorously assessed against a set of predefined criteria. It ensures that AI systems are not only technically proficient but also tailored to meet the nuanced demands of specific...
AI Weekly Breakthroughs | Issue 11 | May 22, 2024 Welcome to AI Weekly Breakthroughs, a roundup of the news, technologies, and companies changing the way we work and live. Mannequin Medicine Makes Perfect Darlington College has introduced AI-powered mannequins to train its health and social care...
From the Library of Alexandria to the first digital databases, the quest to organize and utilize information has been a reflection of human progress. As the volume of global data soars—from 2 zettabytes in 2010 to an anticipated 181 zettabytes by the end of 2024 – we stand on the verge of a new...
Acronyms allow us to compact a wealth of information into a few letters. The goal of such a linguistic shortcut is obvious – quicker and more efficient communication, saving time and reducing complexity in both spoken and written language. But it comes at a price – due to their condensed nature...
Effective data management is crucial for the optimal performance of Retrieval-Augmented Generation (RAG) models. Duplicate content can significantly impact the accuracy and efficiency of these systems, leading to errors in response to user queries. Understanding the repercussions of duplicate...
The AI Weekly Breakthrough | Issue 10 | May 15, 2024 Welcome to AI Weekly Breakthroughs, a roundup of the news, technologies, and companies changing the way we work and live. Harry Potter in One Context Window? Gradient.AI Makes It Possible In a feat that would leave even Hermione Granger...
Deep learning vs. traditional machine learning: Which model is right for your needs? Each approach has its unique strengths and applications, but there are key differences between deep learning and traditional machine learning. Traditional Machine Learning Explained Traditional machine learning...