Learn how AI works — from first principles to advanced concepts.
Millions of examples — text, images, code
Model learns patterns, relationships, grammar
You give it a prompt, it predicts the response
Text, image, code, or action — generated for you
🧠Alan Turing publishes "Computing Machinery and Intelligence" — the Turing Test
📝John McCarthy coins "Artificial Intelligence" at the Dartmouth Conference
💬ELIZA — the first chatbot, mimics a psychotherapist
♟️IBM Deep Blue beats world chess champion Garry Kasparov
🏆IBM Watson wins Jeopardy! against human champions
🎮Google DeepMind's AlphaGo beats professional Go player Fan Hui
📄Google publishes "Attention Is All You Need" — the Transformer architecture
🚀GPT-3 released — massive leap in language model capability
🔥ChatGPT launches — 100M users in 2 months, AI goes mainstream
📸GPT-4, Claude, Gemini — multimodal AI becomes standard
🤖AI agents, video generation (Sora), open-source models rival closed-source
🌐Agentic AI, AI regulation globally, AI-native applications dominate
Designed for one specific task. All current AI is this type.
Human-level intelligence across any task. Does not exist yet.
Beyond human intelligence. Theoretical.
How did we get from a theoretical question in 1950 to ChatGPT in your pocket? A visual timeline of AI's evolution.
AI isn't new — the foundations were laid 75 years ago. What changed in the last decade is compute power and data. The Transformer architecture (2017) is the single most important breakthrough that made today's AI possible.
No jargon, no math. Here's exactly how AI models like ChatGPT work under the hood — with diagrams.
AI doesn't 'think' like humans do. It predicts the next word based on patterns in data. The magic isn't intelligence — it's scale. Enough data + enough compute creates the illusion of understanding.
Not all AI is the same. Learn the difference between the AI we have today and what's coming next.
All AI we have today is 'Narrow AI' — great at one thing, helpless at everything else. AGI doesn't exist yet, and claims that it does are exaggerated. The gap between today's AI and true general intelligence is still massive.
The technology behind ChatGPT, Claude, and Gemini explained without equations. Just intuition and visuals.
The Transformer is the most impactful AI invention since neural networks themselves. It solved two problems that blocked earlier AI: long-range context and parallel training. Every major AI system uses it.
The way you ask changes everything. Learn the techniques to get useful answers from AI every time.
The biggest mistake people make is treating AI like a search engine. AI is a reasoning engine — give it context, examples, and constraints. Be specific. The difference between a bad prompt and a good one is often just a few words.
AI bias, hallucinations, privacy, and safety explained. Why these issues matter and what Australia is doing about them.
AI safety isn't just about Skynet. The real risks today are bias, privacy violations, and confident misinformation. Australia's AI Safety Institute is doing good work, but most businesses aren't prepared for the compliance requirements coming in 2027.
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