RAG and its evolution
Retrieval Augmented Generation (RAG) is becoming a platform in its own right. In this and the following post, we explore the foundations and more importantly, the evoluti...
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Why the newest LLMs use a MoE (Mixture of Experts) architecture
Mixture of Experts (MoE) architecture is defined by a mix or blend of different "expert" models working together to complete a specific problem....
How data governance contributes to a data-driven culture
Building a data-driven culture is all about leveraging data to make decisions and solve problems. In such organizations, people rely on data to guide their actions. They ...
Exploring foundational machine learning algorithms: Linear regression, decision trees, and K-nearest neighbors
Machine learning algorithms power predictive modeling and data analysis. Linear regression, decision trees, and k-nearest neighbors enable limitless possibilities. This a...
Nine Categories of Innovation-Driven Prompt Engineering
In my previous blog, “GenAI Maturity: From Productivity To Effectiveness,” I discussed the dramatic disparities between the organizational mindset of using Ge...
Boosting innovation initiatives with knowledge graphs
Image by Annette from Pixabay One of the common dilemmas in a typical large enterprise is that multiple groups from different geographies and business units are often spe...
More Math Hallucinations with OpenAI, worse with Gemini
This is not just another rant about OpenAI. I actually have something very positive to say, even if in the end, the answer to my prompt was wrong. It started with the fol...
Hands-on data science where ESG matters most
An interview with Nipa Basu, Global and North American Practice Director, Digital Intelligence, GHD Digital Nipa Basu, PhD Dr. Basu leads the Digital Intelligence practic...
Generative AI alignment: A fundamental science of mind for LLMs
Conceptually, the human mind has more than two principal phases: electrical signals [ions], chemical signals [molecules] and a third phase occurring at the interaction of...
Predictive failure analytics in critical automotive applications: Enhancing reliability and safety through advanced AI techniques
Modern safety-critical applications like cars require failure prediction and reliability assessment. As vehicles become more complex, design reliability is often underest...