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The Answering Machine Effect
Beyond Hallucination Energy: A Three-Dimensional Framework for Reliable AI Outputs
Living Against Parkinson’s: A Practical Guide to Fighting Back
The Silent Reset: Currency Devaluation and the Extension of the Debt Cycle
The Eye That Sees
From Fuel Protests to Fiscal Risk: What’s Really Happening in Ireland
Real Problems. AI Solutions.
A Memory Gate for AI: Policy-Bounded Acceptance in the Executable Cognitive Kernel
Intelligence Through Execution: The Executable Cognitive Kernel
The “Negative Contrast Trap”: Why AI Writing Overuses “Not X, But Y”
Applied Policy: How to incorporate Policy and Hallucination in self-improving system
Hallucination Energy: A Geometric Foundation for Policy-Bounded AI
From Evidence to Verifiability: Rebuilding Trust in AI Outputs 🔏
Review: What We’ve Learned So Far
✨ TINY CRITICS: Lightweight Reasoning Checks for Large AI Systems
The Nexus Blossom: How AI Thoughts Turn into Habits
Search–Solve–Prove: building a place for thoughts to develop
The Space Between Models Has Holes: Mapping the AI Gap
A Complete Visual Reasoning Stack: From Conversations to Epistemic Fields
🔦 Phōs: Visualizing How AI Learns and How to Build It Yourself
Episteme: Distilling Knowledge into AI
From Photo Albums to Movies: Teaching AI to See Its Own Progress
Case Based Reasoning: Teaching AI to Learn From itself
SIS: The Visual Dashboard That Makes Stephanie's AI Understandable
ZeroModel: Visual AI you can scrutinize
Everything is a Trace: Stephanie Enters Full Reflective Mode
Layers of thought: smarter reasoning with the Hierarchical Reasoning Model
Stephanie's Secret: The Dawn of Reflective AI
The Shape of Thought: Exploring Embedding Strategies with Ollama, HF, and H-Net
Getting Smarter at Getting Smarter: A Practical Guide to Self-Tuning AI
Epistemic Engines: Building Reflective Minds with Belief Cartridges and In-Context Learning
Self-Improving AI: A System That Learns, Validates, and Retrains Itself
Teaching Tiny Models to Think Big: Distilling Intelligence Across Devices
Agent Architectures: Chapter 2
Compiling Thought: Building a Prompt Compiler for Self-Improving AI
Agent Architectures: Chapter 1
Thoughts of Algorithms
Document Intelligence: Turning Documents into Structured Knowledge
Learning to Learn: A LATS-Based Framework for Self-Aware AI Pipelines
Dimensions of Thought: A Smarter Way to Evaluate AI
Programming Intelligence: Using Symbolic Rules to Steer and Evolve AI
Adaptive Reasoning with ARM: Teaching AI the Right Way to Think
A Novel Approach to Autonomous Research: Implementing NOVELSEEK with Modular AI Agents
General Reasoner: The smarter Local Agent
Building a Self-Improving Chain-of-Thought Agent: Local LLMs Meet the CoT Encyclopedia
Self-Improving Agents: Applying the Sharpening Framework to Local LLMs
Building an AI Co-Scientist
Building Clipper: An AI Image Generator You Control
Uncovering Reasoning in LLMs with Sparse Autoencoders
Optimizing Prompt Generation with MARS and DSPy
Fin-R1: a Financial Reasoning LLM with Reinforcement Learning and CoT
MR.Q: A New Approach to Reinforcement Learning in Finance
Using Hugging Face Datasets
Detecting AI-Generated Text: Challenges and Solutions
Shakespeare and the Bible: An AI Investigation
PostgreSQL for AI: Storing and Searching Embeddings with pgvector
Build Smarter AI: Leveraging the Model Context Protocol for Dynamic Context
Getting Started with Neo4j: Build Your First Knowledge Graph
Beyond Text Generation: Coding Ollama Function Calls and Tools
Building AI-Powered Applications with Haystack and Ollama
LiteLLM: A Lightweight Wrapper for Multi-Provider LLMs
The Power of Logits: Unlocking Smarter, Safer LLM Responses
Automating Paper Retrieval and Processing with PaperSearch
RAFT: Reward rAnked FineTuning - A New Approach to Generative Model Alignment
Faiss: A Fast, Efficient Similarity Search Library
K-Means Clustering
Self-Learning LLMs for Stock Forecasting: A Python Implementation with Direct Preference Optimization
Using Quantization to speed up and slim down your LLM
Mastering LLM Fine-Tuning: A Practical Guide with LLaMA-Factory and LoRA
DeepResearch Part 3: Getting the best web data for your research
DeepResearch Part 2: Building a RAG Tool for arXiv PDFs
DeepResearch Part 1: Building an arXiv Search Tool with SmolAgents
FFmpeg: A Practical Guide to Essential Command-Line Options
Writing Neural Networks with PyTorch
Mastering Prompt Engineering: A Practical Guide
Harnessing the Power of Stable Diffusion WebUI
Activation Functions
SVM Support Vector Machine an introduction
More Machine Learning Questions and Answers with Python examples
Rag: Retrieval-Augmented Generation
CAG: Cache-Augmented Generation
Agents: A tutorial on building agents in python
Courses: Free course on Agentic AI
Ollama: The local LLM solution

Recent Posts

🎂 CAKE: Cognitive Amplification Knowledge Engine
The Answering Machine Effect
Beyond Hallucination Energy: A Three-Dimensional Framework for Reliable AI Outputs
Living Against Parkinson’s: A Practical Guide to Fighting Back
The Silent Reset: Currency Devaluation and the Extension of the Debt Cycle
The Eye That Sees
Canada: When Interest Meets Reliable Revenue
From Fuel Protests to Fiscal Risk: What’s Really Happening in Ireland
Real Problems. AI Solutions.
A Memory Gate for AI: Policy-Bounded Acceptance in the Executable Cognitive Kernel
Intelligence Through Execution: The Executable Cognitive Kernel
The “Negative Contrast Trap”: Why AI Writing Overuses “Not X, But Y”
Applied Policy: How to incorporate Policy and Hallucination in self-improving system
Hallucination Energy: A Geometric Foundation for Policy-Bounded AI
From Evidence to Verifiability: Rebuilding Trust in AI Outputs 🔏
Review: What We’ve Learned So Far
✨ TINY CRITICS: Lightweight Reasoning Checks for Large AI Systems
The Nexus Blossom: How AI Thoughts Turn into Habits
Search–Solve–Prove: building a place for thoughts to develop
The Space Between Models Has Holes: Mapping the AI Gap
A Complete Visual Reasoning Stack: From Conversations to Epistemic Fields
🔦 Phōs: Visualizing How AI Learns and How to Build It Yourself
Episteme: Distilling Knowledge into AI
🔄 Learning from Learning: Stephanie’s Breakthrough
From Photo Albums to Movies: Teaching AI to See Its Own Progress

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