AI & Machine Learning
How modern AI is built and run: large language models, transformers, training, fine-tuning and alignment, the GPU compute behind them, and the shift to agentic AI.
Introduction to Artificial Intelligence: How AI Works and Where It Is Used
What AI is and how the terms nest, how models learn, what AI is genuinely good at, its real limits, and the 2026 market, energy and policy picture.
Inside Large Language Models: How ChatGPT, Claude & Gemini Work
How LLMs actually work — transformers and self-attention, model families, fine-tuning and LoRA, RLHF and DPO, the GPU compute bill, RAG and agentic AI.
Open Source LLMs Explained: Open-Weight Models, Uses, Benefits and Limits
How open-weight and fully open models work, what their licences allow, where they fit, and the trade-offs of running them.
ITSM for Agentic AI: How to Manage AI Agents as Enterprise Services
How to manage enterprise AI agents with service inventory, CMDB relationships, observability, change, incident, access and cost controls.
Bittensor and Blockchain Explained: Subnets, TAO and the Market for Machine Intelligence
How Bittensor uses a blockchain to price machine intelligence — subnets, miners, validators, Yuma Consensus, TAO emissions, dTAO and the risks that come with them.