Shelf Blog
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
10 Ways Duplicate Content Can Cause Errors in RAG Systems
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...
5-Point RAG Strategy Guide to Prevent Hallucinations & Bad Answers This guide designed to help teams working on GenAI Initiatives gives you five actionable strategies for RAG pipelines that will improve answer quality and prevent hallucinations.
Choose Your AI Weapon: Deep Learning or Traditional Machine Learning
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...
Data Quality Is Critical to GenAI’s Expanding Impact in Finance
The generative AI (GenAI) market for financial services is expected to grow by 28% over the next decade. This means that we will soon be able to say farewell to the traditional cumbersome processes that once defined the financial sector – manual data entry, lengthy decision-making for loan...
Exorcist-Lite Robots, Gemini’s Med Fellowship, Founders Forecast an AI Surge: AI Weekly Breakthroughs
The AI Weekly Breakthrough | Issue 9 | May 8, 2024 Welcome to The AI Weekly Breakthrough, a roundup of the news, technologies, and companies changing the way we work and live Gemini’s Medical Fellowship Training Two weeks ago, we explored the ability of LLMs in taking medical board exams across...
The Knowledge Manager’s Handbook to Data Science for Generative AI
Artificial intelligence (AI) is a transformative force that’s reshaping industries, processes, and even the very fabric of how decisions are made. As AI systems become more integral to organizational operations, it is essential that we understand the foundational elements that ensure these systems...
GenAI in Banking Is a Double-edged Sword of Risk and Reward
In the banking sector, every percentage point in efficiency can translate to billions in revenue. According to McKinsey, GenAI could potentially add $340 billion in revenue to the sector’s annual global revenues. This represents a 4.7% increase in total industry revenues – a surge comparable...
The Critical Role of Data Quality in AI Implementations
AI has revolutionized how we operate and make decisions. Its ability to analyze vast amounts of data and automate complex processes is fundamentally changing countless industries. However, the effectiveness of AI is deeply intertwined with the quality of data it processes. Poor data quality can...
Why “Garbage In, Garbage Out” Should Be the New Mantra for AI Implementation
The adage “Garbage In, Garbage Out” (GIGO) holds a pivotal truth throughout all of computer science, but especially for data analytics and artificial intelligence. This principle underscores the fundamental idea that the quality of the output is linked to the quality of the input. As...
Even LLMs Get the Blues, Tiny but Mighty SLMs, GenAI’s Uneven Frontier of Adoption … AI Weekly Breakthroughs
The AI Weekly Breakthrough | Issue 8 | May 1, 2024 Welcome to The AI Weekly Breakthrough, a roundup of the news, technologies, and companies changing the way we work and live Even LLMs Get the Blues Findings from a new study using the LongICLBench benchmark indicate that LLMs may “get the...
Continuously Monitor Your RAG System to Neutralize Data Decay
Poor data quality is the largest hurdle for companies who embark on generative AI projects. If your LLMs don’t have access to the right information, they can’t possibly provide good responses to your users and customers. In the previous articles in this series, we spoke about data enrichment,...
Fix RAG Content at the Source to Avoid Compromised AI Results
While Retrieval-Augmented Generation (RAG) significantly enhances the capabilities of large language models (LLMs) by pulling from vast sources of external data, they are not immune to the pitfalls of inaccurate or outdated information. In fact, according to recent industry analyses, one of the...