Enterprise AI Deployment
From what AI is, through how large language models and open-weight models work, to running agents as managed enterprise services and the security controls that keeps them safe.
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Introduction to Artificial Intelligence: How AI Works and Where It Is Used
An introduction to artificial intelligence: what AI is, how machine learning and neural networks work, where it delivers value, and its real limits in 2026.
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Inside Large Language Models: How the Engines Behind ChatGPT, Claude, and Gemini Actually Work
How large language models actually work: transformers and self-attention, encoder and decoder families, fine-tuning and LoRA, RLHF and DPO alignment, the GPU compute bill, RAG, and the shift to agentic AI.
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Open Source LLMs Explained: Open-Weight Models, Uses, Benefits and Limits
Open source LLMs explained: how open-weight and fully open models work, where they fit, what licences allow, and the trade-offs of running them.
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ITSM for Agentic AI: How to Manage AI Agents as Enterprise Services
ITSM for agentic AI applies service inventory, CMDB, incident, change, observability, governance and cost controls to AI agents that use enterprise tools and data.
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AI Agents and Cybersecurity: Agentic AI Risks and Controls
A practical guide to AI agents and cybersecurity: prompt injection, excessive agency, tool permissions, non-human identities, MCP security, SOC monitoring, physical AI risk and the controls buyers should require before agents get production access.
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