Shelf Blog: AI Education
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
It’s no surprise that artificial intelligence is disrupting the job market. Some roles will be automated entirely, while others will evolve as AI takes over repetitive tasks. The question isn’t just what jobs will AI replace—it’s how fast will it happen, and what does it mean for you? AI is...
AI for predictive analytics represents a cutting-edge approach to forecasting future trends and making data-driven decisions with precision. By integrating AI, you can uncover deep insights, identify emerging opportunities, and mitigate potential risks in real-time. In this article, you’ll...
Over 50% of organizations have paused their Copilot initiatives. Why? Because of data quality and data governance concerns. Generative AI is powerful, but when you feed it bad data, it generates bad responses. “Garbage in, garbage out,” as we say. Inaccurate or irrelevant responses hurt user...
Getting your SharePoint data AI-ready isn’t just about flipping a switch. It’s about taking a closer look at the data you already have and setting it up for success. Whether you’re aiming to streamline workflows, unlock actionable insights, boost the user experience, or simply make better use of...
Businesses have long been increasingly inundated with an unprecedented volume of data. The challenge now is not just about storing ample data but managing, classifying, and transforming this structured and unstructured data into fuel for the engine of business. The critical role of data...
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,...
Artificial intelligence engines need data to learn and operate, but the data you and I find meaningful is foreign to machines. Machines need data translated to their preferred language: math. This conversion happens with the help of vectors. What are vectors in machine learning? Vectors are...
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...
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...
A data pipeline is a set of processes and tools for collecting, transforming, transporting, and enriching data from various sources. Data pipelines control the flow of data from source through transformation and processing components to the data’s final storage location. Types of Data Pipelines AI...
The terms “AI interpretability” and “explainability” (XAI) are frequently used but often misunderstood. This confusion is an expected part of grappling with a field that is itself in a state of rapid development and debate. This article aims to clarify the distinction...
Few-shot prompting is a powerful technique that enables AI models to perform complex tasks with minimal data. This method is valuable for organizations looking to leverage AI capabilities without the extensive data requirements and training costs typically associated with traditional AI...