The Model Context Protocol (MCP) introduces structural elements that shape agentic system design, bringing both constraints and benefits. It incorporates an MCP server that mediates interactions, processes requests, and enforces permissions.By regulating context handling, MCP can limit persistent memory, potentially hindering long-term goal tracking and autonomous function. Its intermediary layer reduces direct memory control, requiring […]

The inefficiency of current data pre-processing in GIS is a significant challenge, driving the need for new paradigms like knowledge graphs. Traditional geo-enrichment services are often constrained by predefined categories and restricted data access. In contrast, knowledge graphs provide a more open and extensible approach to geo-data enrichment.Knowledge Graphs: A Flexible and Powerful AlternativeA Geographical […]

While testing accuracy and relevance during enrichment,  biases suddenly emerged when we included spatial data in knowledge graphs. We started seeing biases in all sorts of spatial statistics  and temporal statistics when using natural language processing technologies. Most knowledge graphs don’t do any meaningful in place-name disambiguation so the London in the UK is always […]

Knowledge Graph Enrichment Management – Highlights AI systems can mirror human-like processes of information gathering, analysis, and synthesis—but at scales impossible for human researchers to achieve individually. As research continues its rapid expansion, such multi-agent systems will likely become essential tools for maintaining comprehensive, up-to-date knowledge graphs.Large language models (LLMs) serve as the technological foundation […]

AI Revolution: Many Industries Facing Extinction – Will Your Career Survive? In the last few months it has become clear that unless we wake up and smell the coffee, AI is going to eat our lunch.Here are some of the industries that are most at risk from AI automation ranked from most affected to least […]

Everyone’s buzzing about NotebookLM generating podcasts, but they’re missing the real revolution. This isn’t just another AI toy – it’s a silent earthquake reshaping how organizations work from the ground up.Forget the consultants telling you about RAG implementation roadmaps and maturity assessments. While they’re drawing flowcharts, your competitors are already transforming their businesses.Here’s the raw […]

Agentic AI Architecture An Implementation SummaryAgentic AI systems act independently to achieve goals – they don’t just respond, they decide and do. Think of them as digital agents that can plan, act, and adapt without constant human oversight.Architecture & Components:Uses a “beehive” model where multiple specialized AI agents work togetherMulti-layer architecture: input, orchestration, data storage, […]

AI-Powered Document Management for Tax Law: Implementation Summary A modern eDiscovery system built on Alfresco DMS with AI integration for tax law document processing. Core Architecture– Alfresco DMS backbone with custom collectors for email, WhatsApp, Slack, and Discord– IBM Granite3 and Deepseek R1 LLMs via Ollama for intelligent processing– Asynchronous message server enabling flexible model […]

LPG Cylinder Failure Prediction using Bigquery and ML: Implementation Summary1. OverviewThis project predicts LPG cylinder failure using machine learning and visualizes findings in a dashboard. It leverages BigQuery ML for modeling, Python (Google Colab) for data analysis, and Looker Studio for visualization. The goal is to identify at-risk cylinders and understand failure causes.2. Problem StatementThe […]

Clearos to Truenas SMB server migration SummaryMotivation:Clearos 7 reached its end of life  and showed performance problems.Clearos to Truenas was necessary for better storage performance, reliability, scalability, and support. Step 1: assess your current setupThe existing setup was a Clearos as a file server  in CAT computer lab in South Africa. Its primary function is […]

/ The core types of ambiguity include recognition ambiguity (multiple possible interpretations of input), segmentation ambiguity (uncertainty in grouping inputs), and target ambiguity (uncertainty about which component should handle input). These different forms require specific architectural considerations. This necessitates adaptable AI architectures. Here are key approaches to address ambiguity:Probabilistic Reasoning: Model uncertainty with tools like […]