Putting the "I" Back into BI
TL;DR Preface—The System 0 Origin Story For my AI projects back in 2004, SCL and TOSN, the main architectural concept centered on how I imagined our conscious and subconscious work. In my notes, I referred to the conscious as the "single-threaded consciousness". The single-threaded consciousness made sense to me because we have just one body, … Continue reading System 0: The Default Mode Network of AGI
Skip Intro. 🎉 Welcome to the AI “Go-to-Market” 3rd Anniversary Special!! 🎉 Starring ... 🌐 The Semantic Web ⚙️ Event Processing 📊 Machine Learning 🌀 Vibe Coding 🦕 Prolog … and your host … 🤖 ChatGPT!!! Following is ChatGPT 5's self-written, unedited, introduction monologue—in a Johnny Carson style. Please do keep reading because this blog … Continue reading Conditional Trade-Off Graphs – Prolog in the LLM Era – AI 3rd Anniversary Special
This is Part 2 of a 3-part series where I make the case that pre-aggregated OLAP is essential in this era of AI. The intent of this post is to describe just enough of how a pre-aggregated OLAP engine works for those who are unfamiliar with this technology: Those who have joined the business intelligence … Continue reading The Ghost of OLAP Aggregations – Part 2 – Aggregation Manager
The phrase “thinking outside the box” traces back to a deceptively simple puzzle: nine dots arranged in a 3×3 grid. The challenge is to draw four straight lines through all the dots without lifting your pencil. Most people fail at first because they instinctively keep their lines inside the square boundary implied by the dots. … Continue reading Outside of the Box AI Reasoning with SVMs
Enterprise Intelligence and Time Molecules link through the Tuple Correlation Web. Introduction The main takeaway of this blog is an explanation of how my two books, Enterprise Intelligence (June 21, 2024) and the more recently published Time Molecules (June 4, 2025), connect. Time Molecules is a follow-up to my first book, Enterprise Intelligence. It connects … Continue reading BI-Extended Enterprise Knowledge Graphs
Welcome to the Prolog in the LLM Era Summer Vacation Special! Starring … Prolog ... knowledge graphs ... ChatGPT o4-mini ... neuro-symbolic AI ... and our special guest ... Thinking Fast and Slow! In this episode (Part 11 of the series), I wish to address how neuro-symbolic AI relates to this series. After all, the series title, Prolog … Continue reading Thinking Reliably and Creatively – Prolog in the LLM Era – Summer Vacation Special
In this mind-bogglingly complex world in which we live—countless moving parts fraught with imperfect information of many types—a versatile highly-functioning intelligence requires quick access to a wide variety of information in order to make intelligent decisions. It's not that all decisions should be made from that full breadth of information. It's that all decisions are … Continue reading Thousands of Senses
My new book, Time Molecules, is available!! This is its launch-day blog (June 4, 2025)! Time Molecules is a book about bringing process awareness to business intelligence (BI). Traditional BI flattens reality into snapshots— scalar values, points of information— leaving us staring at dimensionally flattened shadows on a wall. But life unfolds over time, and … Continue reading From Data through Wisdom: The Case for Process-Aware Intelligence
As I mentioned in a previous post, Sample From My Talk - NFA, I will be delivering two sessions at the Data Modeling Zone 2025 (DMZ) in Phoenix. It will be happening from Tuesday, March 4, 2025 through Thursday, March 6, 2025. That post included a preview one of my two sessions, Beyond Ontologies and Taxonomies—focusing on … Continue reading Trophic Cascades of AI
Think about the usual depiction of a network of brain neurons. It’s almost always shown as a sprawling, kind of amorphous web, with no real structure or organization—just a big ball of connected neurons (like the Griswold Christmas lights). But this image misses so much of what makes the brain remarkable. Neurons aren’t just randomly … Continue reading Embedding Machine Learning Models into Knowledge Graphs
Soft Coded Logic 