Thursday, July 24, 2025
Making AI Theory Testable. There’s a gap between the Agent Function and the Agent Program and what the Agent should do and what it does do. ATDD can help bridge this. Here I detail how.
Sunday, June 29, 2025
A very interesting paper on Critical Thinking in an LLM (or lack thereof) Our study investigates how language models handle multiple-choice questions that have no correct answer among the options. Unlike traditional approaches that include escape options like None of the above (Wang et al., 2024a; Kadavath et al., 2022), we deliberately omit these choices to test the models’ critical thinking abilities. A model demonstrating good judgment should either point out that no correct answer is available or provide the actual correct answer, even when it’s not listed.
Friday, June 27, 2025
I wish I had time to finish: my research on the Evolution of Probalisitic Reasoning in AI Particularly Dempster-Shafer and Bayesian Networks How LLMs and Bayesian networks can be used for Risk Management create an youtube/insta/tiktok vid for my latest post on LLM Agent But I don’t!! So this is me putting it to one side…
Thursday, June 26, 2025
Building a Self-Consistency LLM-Agent: From PEAS Analysis to Production Code - a guide to designing an LLM-based agent.
Thursday, June 19, 2025
The article discusses how to implement Bayes Theorem in a learning agent that updates its beliefs about an environment based on new evidence, illustrated through a game involving guessing a number derived from a dice throw.
Wednesday, June 4, 2025
What is knowledge? Wtf am I trying to learn! Claude “thinks” this post is mental masturbation 😆 well even the physical version serves a good purpose! 🤷🏼♂️
Tuesday, May 20, 2025
Introduction In the previous post, I shared my view on “Why Study Logic?”, we looked at the Knowledge Representation and highlighted the importance of Logic and Reasoning in storing and accessing Knowledge. In this post I’m going to highlight a section from the book “Introduction to Artificial Intelligence” by Wolfgang Ertel. His approach with this book was to make AI more accessible than Russel and Norvig’s 1000+ page bible. It worked for me.
Monday, May 19, 2025
Introduction The purpose of this article is to help me answer the question “Why am I studying Logic?”. If it helps you, that’d be great, let me know! The question comes from a nagging feeling of, why don’t I see logic used more in the ‘real world’. It could be a personal bias as I more easily see the utility of Rosenblatt’s work, where he looked at both Symbolic Logic and Probability Theory to help solve a problem and choose Probability Theory ([NN Series 1/n] From Neurons to Neural Networks: The Perceptron), with that we had the birth of the Artificial Neuron and the rest is history!
Friday, May 16, 2025
“[IA Series 3/n] Intelligent Agents Term Sheet” breaks down essential AI terminology from Russell & Norvig’s seminal textbook. Learn what makes agents rational (or irrational), understand different agent types, and follow a structured 5-step design process from environment analysis to implementation. Perfect reference for AI practitioners and students. Coming next: how agents mirror human traits. #ArtificialIntelligence #IntelligentAgents #AIDesign
Saturday, May 10, 2025
First draft in public 😱 😆🤓 What’s the best way for an agent to build a semantically sound and syntactically correct knowledge base? Dog fooding my course material means the first step is to define the task environment. /Checks notes Task Environment: The description of Performance, Environment, Actuators, and Sensors (PEAS). This provides a complete specification of the problem domain. So how can I implement this 🤔 First I need to think on the domain, something different to the examples (e.
Thursday, April 24, 2025
The document discusses various search algorithms used by Intelligent Agents for navigating mazes, detailing their types, characteristics, tradeoffs, and implementations.
Thursday, April 24, 2025
This text introduces key concepts and algorithms related to intelligent agents in AI, focusing on search terms, uninformed and informed search strategies, and adversarial search techniques.