AI Buzzwords Explained
Simple, everyday definitions for AI and automation terms. No PhD required.
AI Agent
generalExample:
An AI agent could read your inbox, summarize new emails, and send replies on your behalf.
AI Image Generator
toolsExample:
A blogger can use an AI image generator to create custom illustrations for posts.
AI Writing Tool
toolsExample:
Tools like Jasper or Copy.ai help marketers draft ad copy and product descriptions.
API (Application Programming Interface)
technicalExample:
An API allows Zapier to connect Gmail with Slack.
Artificial Intelligence (AI)
generalExample:
Using AI, a calendar app can automatically suggest meeting times based on everyone’s availability.
Automation
practicalExample:
An automation could take new email attachments and save them to Google Drive automatically.
ChatGPT
toolsExample:
ChatGPT can draft an email reply in seconds when you paste the incoming message.
Content Generation
practicalExample:
A YouTuber might use AI content generation to draft video scripts.
Fine-Tuning
technicalExample:
A company fine-tuned GPT-4 with its internal support documents to create a custom helpdesk bot.
Hallucination
practicalExample:
When an AI writes a fake citation for a research paper, that is a hallucination.
Large Language Model (LLM)
technicalExample:
ChatGPT is a Large Language Model trained to generate and understand text.
Neural Network
technicalExample:
A neural network can learn to recognize handwritten numbers by adjusting weights between its nodes.
No-Code
practicalExample:
Using Zapier, you can connect Gmail and Slack without writing a single line of code.
Make (formerly Integromat)
toolsExample:
Make can pull data from a form, process it, and upload it to Google Sheets in real-time.
Low-Code
practicalExample:
In Airtable, you can set up workflows with drag-and-drop blocks but also add custom code if needed.
Overfitting
technicalExample:
A model that memorizes its training data but fails to predict new data correctly is overfitting.
Personalization (AI)
practicalExample:
AI can personalize newsletters by suggesting articles based on each reader’s past clicks.
Prompt Engineering
practicalExample:
By asking “Write me a 3-step business plan for a coffee shop” instead of “Tell me about coffee,” you are doing prompt engineering.
Repurposing Content
practicalExample:
An AI tool can turn a podcast transcript into a blog post and a Twitter thread.
Social Media Automation
practicalExample:
AI tools can automatically schedule Instagram posts at the times with the highest engagement.
Token
technicalExample:
The phrase “AI is fun” uses four tokens: AI | is | fun.
Transformer
technicalExample:
GPT-4 and GPT-5 are based on the transformer architecture, which uses attention to focus on relevant parts of input data.
Voice Cloning
toolsExample:
A podcaster could use voice cloning to generate an intro in their own voice without re-recording.
Zapier
toolsExample:
With Zapier, a new Gmail message can automatically create a task in Trello.
Workflow
generalExample:
An AI workflow might listen for new emails, summarize them, and save the summary in Notion.
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