Tutorials AI Fundamentals Tutorial
What Are LLMs
What Are LLMs: free step-by-step lesson with examples, common mistakes, and interview tips — part of AI Fundamentals Tutorial on Toolliyo Academy.
On this page
AI Fundamentals Tutorial · Lesson 32 of 120
What Are LLMs
Foundations & ML ✓ → DL, LLM & NLP → Build & Safety → Projects
DL, LLM & NLP · 2 — Language & vision · ~6 min · Generative AI & LLMs
What is this?
Large Language Models (LLMs) are neural nets trained to predict the next token of text. They can draft, summarize, and answer — but they do not magically know your private database.
Why should you care?
Copilots and chat features in AIVerse apps usually sit on an LLM plus your prompts, tools, or RAG.
See it live — copy this example
Treat examples as Python-style notes you can paste into a notebook or rewrite in your stack. Prefer public sample data — never real private records.
# Mental model
prompt = "Summarize this ticket in 2 bullets: ..."
# LLM predicts tokens → reply text
# Without retrieval, it may invent detailsWhat happened?
- You send a prompt; the model generates tokens one by one.
- If facts are missing, it may hallucinate unless you retrieve them.
Practice next
- Write one good prompt and one vague prompt for the same task.
- Compare which would be safer in production.
- List data the model should never invent.
- Add “If unknown, say unknown”.
- Limit reply to 50 words.
Remember
LLMs predict tokens. Prompts steer behavior. Private facts need retrieval or tools.
Support draft
Agent drafts a reply from a ticket.
Outcome: You treat the draft as assistive, not ground truth.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
Sign in to ask a question or upvote helpful answers.
No questions yet — be the first to ask!