AINoon Lesson 1

Get Ready for AINoon!

Thanks

  • To the host for the great venue!
  • To our sponsors

Administrivia

  • Fire escapes
  • Toilets
  • Cleaning up after ourselves
  • WiFi

Welcome to AINoon!

Hands up if you’ve ever:

  • Used Google’s “AI Overview” instead of opening search results?
  • Asked ChatGPT a question?
  • Used AI to automate a task?
  • Used AI to build an app or write code?

Why AINoon?

  • Generative AI is a powerful tool
    - It unlocks new opportunities for productivity
  • It has limitations we’re not used to
    - Risk of misuse and over-trusting
  • There are many valid concerns
    - Important to understand risks and issues
  • There’s a lot of hype
    - It’s hard to know where to start!

What we’ll cover in AINoon

  • Hands-on practice with Generative AI
  • Leading applications of Generative AI
    - Be equipped to spot opportunities
  • Demystifying how Generative AI works
    - Understand its strengths and limitations
  • Risks and issues to consider when using AI
  • Providing a forum for questions and assistance

What to expect from AINoon

Each lesson will include:

  • Presentation on important AI concepts
  • Follow-along tutorial to get hands-on with AI
  • Optional homework if you want to go further

Get all the slides, tutorials, and homework from:

technoon.org/ainoon

AINoon Structure

  • Lesson 1:
    • Presentation: Intro to AI
    • Tutorial: Using a chatbot for business use-cases
  • Lesson 2:
    • Presentation: How AI works
    • Tutorial: Building an agent with Zapier
  • Lesson 3:
    • Presentation: Common patterns - agents, RAG, and tools
    • Tutorial: Building a chatbot on your docs with Zapier
  • Lesson 4:
    • Presentation: AI risks and challenges
    • Tutorial: “Vibe-coding” an app with Replit

We’ll use convenient tools in tutorials, but the focus is on principles that will apply in any tool

How to get the most out of AINoon

  • As much as possible, don’t do emails and work
    • A lot of the value comes from carefully considering ideas and engaging in the conversation
  • Follow along with the tutorials
    • Even if you’ve used a tool before, look at the results in light of the ideas we’re discussing

Questions?

Intro to AI

  • Establish a common vocabulary
  • Who’s who in the zoo: companies and services
  • How generative AI is being used by businesses

AI Terminology

Artificial Intelligence (AI) ~1950s

  • General term for computers making “intelligent” decisions
  • E.g. Hand-crafted programs that can play checkers

Machine Learning (ML) ~1980s

  • Approach to AI where computers “learn” from patterns in data
  • E.g. Learning from many past emails to identify spam

Deep Learning (DL) ~2000s

  • Approach to ML based on very large (artificial) “neural networks”
  • E.g. Recognising objects in images, topic-labelling of text

Generative AI (GenAI) ~2020s

  • Application of DL to generate text, images, audio, video, etc.
  • What most people mean by “AI” these days
  • The focus of this course

Source: blogs.nvidia.com/blog/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/

Chatbots are the most prominent application of GenAI

  • ChatGPT (OpenAI)
  • Claude (Anthropic)
  • Gemini (Google)
  • Microsoft Copilot (based on OpenAI LLMs)
  • Grok (X)
  • DeepSeek

What can chatbots do for business?

  • Drafting emails and documents
  • Summarising documents and meetings
  • Brainstorming a wide variety of ideas
  • Personalised tutoring for learning new subjects
  • Generating code to assist programmers
  • Data extraction and transformation
    • Turn unstructured text and images into structured data
    • E.g. Identify which team an IT ticket should go to
  • Custom agents: chatbots that retrieve info and take action
    • Answering questions from organisation knowledge bases
    • Personalised customer service
    • Automated handling of events - e.g. IT tickets

Using chatbots for business

  • Public chatbots train future chatbots with your data
  • Companies deploy internal chatbots to protect data
    • Often using business-to-business service offerings
    • E.g. From Microsoft, Amazon, or Google clouds
  • You can run open chatbots on your own computers
    • E.g. Llama (Meta), gpt-oss (OpenAI), DeepSeek
    • Most require specialised hardware, but less powerful chatbots can run on a laptop
    • Check whether licenses allow commercial use

Tutorial Objectives

  • Using a chatbot for business use cases:
    • Brainstorming and drafting
    • Automating web searches
    • Summarising documents
  • Identifying important issues to keep in mind
  • Tips for effective prompting

Tips for crafting better prompts

  • Each prompt should request one thing
  • Start prompts with a persona
    • E.g. “You are an expert in project management…”
  • Ask it to “explain step-by-step”
    • Can get better answers to more complex questions
  • When it’s not doing what you want, be more specific
    • Though it won’t always follow instructions exactly!
  • Seek more tips online for specific use-cases
    • It’s all art/craft, not science/engineering
    • Advice will likely change as models change

The Golden Rule of AI

Don’t trust the output of an AI unless you can verify it

  • Bad: Summarising a document you haven’t read
  • Good: Summarising a document you have read
  • But: For some use cases, speed may be more important than accuracy

Homework

Remember: Don’t use private data with public models!

  • Try ChatGPT’s Think longer (reasoning) mode:
    • “Make a plan to increase visitors to my website”
    • Compare level of detail with/without reasoning
  • Try ChatGPT’s Deep Research mode:
    • “Find a cheap washing machine for a family of four”
    • Searches the web and summarises in a few minutes
  • Generate a video with Google’s Flow
    • Look at the gallery on Midjourney - note the detail in the prompts used
  • Generate speech from text with ElevenLabs