1. The Ghost in the Machine: What is Generative AI?
Introduction to Large Language Models (LLMs), how they differ from search engines, and setting up accounts with safety protocols.
Understanding neural networks (biological vs. artificial).
Usage of Cloud Computing and APIs.
System architecture basics.
Probability basics (Next token prediction).
Learning Objectives
- Define Generative AI and LLMs.
- Distinguish between a search engine query and a generative prompt.
- Establish digital citizenship and safety rules for AI use.
Standards Alignment
Pathways
Materials & Costs
| Item | Est. Cost |
|---|---|
| Chromebooks or Laptops | $300 per unit (amortized) |
| Access to Gemini (Google) or ChatGPT (Free Tier) | $0 |
| Projector/Smartboard | $0 (Facility use) |
Federal Compliance Data
Both
- • Instruction in laboratory science (Computer Science)
- • Exposure to new technology
- • Educational software/subscriptions
- • Computer hardware lease/purchase for student use
Provides core instruction in Computer Science principles, a required rigorous curriculum component for UBMS and encouraged for UB.
Regulatory Citations
T Teacher Guide
Start by asking students to predict the next word in the phrase 'Peanut butter and...'. Explain that LLMs do this with math.
Perform a live demo: Google 'How does a car engine work' (result: links) vs. ChatGPT 'Explain a car engine to a 5-year-old' (result: synthesis).
Strictly review data privacy: Do not put PII (Personally Identifiable Information) into the AI.
S Student Mission
Create or log in to your designated AI account.
Enter the prompt: 'Explain how Large Language Models work to a 5-year-old.'
Open Wikipedia and search 'Large Language Model'.
Write down three differences between the AI explanation and the Wikipedia entry.