Week 1 — Readings & Resources · Welcome to the AI Revolution

Course: Using Artificial Intelligence (AI 101) · Silver Oak University (fictional sample) · Prof. Quinn
Objective covered: Objective 1 — Explain what generative AI and large language models are, how they work conceptually, and their core capabilities and limits.

How to use this page

Everything here is a link to an external resource — open it in your browser, the same way you'd open any link. Nothing needs to be downloaded.

This week's load is deliberately light: 2 short videos + 2 short readings, grouped by the ideas from the lecture, plus the official tool homepages so you can set up your account. Watch or read one item per group and you're ready for the quiz; do all of them and you'll be very comfortable. Total time is roughly 35–45 minutes if you do everything, far less if you pick one per group.

Order that matches the lecture: ① what generative AI is → ② the terminology & how the model works → ③ the mindset → ④ get set up.

A habit to start now: before you trust any claim — in these resources, from a chatbot, or anywhere — ask the questions from class: Is this generated or verified? Is it fluent, or is it actually correct? How would I check?

① What Generative AI Is

Maps to Lecture Segment 2. Generative AI creates new content; the chatbot is the app, the LLM ("the model") is the engine inside it.

Video — "Large Language Models explained briefly" (3Blue1Brown)
🔗 https://www.youtube.com/watch?v=LPZh9BOjkQs
Why it earns the click: a clear, friendly, visual ~8-minute explanation of what an LLM is and the "predict the next word" idea — exactly the plain-language picture we built in class, with no math required to follow it.
⏱ ~8 min

Reading — "What Are Large Language Models (LLMs)?" (IBM)
🔗 https://www.ibm.com/think/topics/large-language-models
Why it's assigned: a clean, plain-English overview of what LLMs are and how they "predict the next word" over and over — the cleanest written version of the engine-vs-app distinction. Free to read online.
⏱ ~10 min

② The Terminology & How the Model Works

Maps to Lecture Segments 2–3. Get the words straight (AI / generative AI / LLM / AGI), and remember the model predicts likely text — which is why it can be fluent and wrong at once.

Video — "How Large Language Models Work" (IBM Technology)
🔗 https://www.youtube.com/watch?v=5sLYAQS9sWQ
Why it earns the click: IBM's Martin Keen walks through how an LLM works as a "next-word prediction machine" in about 5 minutes — the same mental model we used, and it sets up next week's deeper look at tokens and the context window.
⏱ ~5 min

Reference — "Large language model" (Wikipedia)
🔗 https://en.wikipedia.org/wiki/Large_language_model
Why it's here: a solid, always-available reference for the vocabulary (LLM, tokens, training) you can return to all term. Skim the intro section for this week; don't get lost in the technical parts.
⏱ ~8 min (skim)

③ The Mindset — Why "Use Your Own Brain" Matters

Maps to Lecture Segments 3–5. The model predicts text; you stay the judge. Start general → specific, iterate, and verify.

Reading — "What is generative AI?" (Google Cloud)
🔗 https://cloud.google.com/discover/what-is-generative-ai
Why it's assigned: a vendor-neutral-enough plain-language overview of what generative AI does and where it fits — useful for the big-picture mindset (capabilities and limits). (This page can be slow to load on some connections; give it a moment.)
⏱ ~8 min

④ Get Set Up — The Official Tool Homepages (pick one)

You only need one approved assistant for this course (free tiers are fine). Open one and create an account before the tutorial. These are the official product pages.

• ChatGPT (OpenAI) 🔗 https://chatgpt.com
• Claude (Anthropic) 🔗 https://claude.com
• Gemini (Google) 🔗 https://gemini.google.com
• Copilot (Microsoft) 🔗 https://copilot.microsoft.com

(Claude Cowork desktop — the automation platform we use in Weeks 11–14 — comes later; you don't need it yet.)

Pick-one quick path (≈13 min total)

In a hurry? Do exactly these two and you'll be ready for the quiz:
1. Watch "Large Language Models explained briefly" (group ①).
2. Watch "How Large Language Models Work" (group ②), and create an account on one assistant (group ④).

Heads-up (links rot): these point to outside sites that occasionally move or rename pages. If a link ever fails, tell Prof. Quinn and use the IBM or Wikipedia references above in the meantime. Nothing here is downloaded or redistributed — all resources stay as links to their original sources.