Introduction
Lesson 1 of 10
Welcome! In today’s lesson, we’ll break down what Generative AI is and how it can be applied in your professional life. Whether you’re managing marketing campaigns, planning lessons, conducting research, or optimizing business processes, understanding AI can provide you with new ways to boost productivity and efficiency. Let’s explore how this technology works and what it can offer to professionals like you.
Generative AI represents an unparalleled learning opportunity, reminiscent of the transformative moment when the internet first became accessible to the masses but magnified exponentially. It’s a gateway to a new era of creativity, efficiency, and problem-solving, offering tools and possibilities that were previously unimaginable. Just as the internet revolutionized communication and access to information, generative AI empowers us to create, innovate, and learn at an unprecedented scale—times 100,000. From automating tasks and generating content to sparking new insights, it’s a leap forward that can redefine industries and reshape the way we think, work, and learn.
What is AI?
Artificial Intelligence (AI) functions like a digital assistant designed to handle tasks that typically require human intelligence, such as data analysis or decision-making. There are various types of AI, each specialized for different purposes. Generative AI, in particular, focuses on creating new content—like text, images, or even solutions—based on the input it receives. Understanding these types of AI can help you leverage them effectively in your personal and professional tasks.
- Narrow AI: Designed for specific tasks (like Siri or Alexa)
- General AI: Hypothetical AI that could perform any intellectual task a human can
- Machine Learning: AI that improves with experience
- Generative AI: AI that can create new content
In this course, when we say “AI,” we’re specifically talking about Generative AI.
What is “Generative” AI?
Generative AI is a type of artificial intelligence that creates new content, such as text, images, or code, based on patterns it learns from large datasets. Think of it as an advanced digital tool capable of drafting reports, generating ideas, and solving complex problems efficiently. While it’s not flawless and certainly has limitations, Generative AI enhances professional and personal tasks, offering new ways to improve productivity and creativity across various fields without replacing human expertise.
Where Does Generative AI Obtain Information?
An LLM, or Large Language Model, is like a very advanced and highly trained digital brain that can understand and generate human-like text. Think of it as a super smart assistant that has read a huge library of books, articles, websites, and other text materials. It’s designed to recognize patterns in language, so it learns the way words and ideas connect to make sense.
How Generative AI Gets Its Information
Generative AI, including LLMs, gets its information by being trained on massive amounts of text from the internet, books, news articles, academic papers, and other publicly available sources. During training, the AI reads all of this text to learn the structure of language and how different topics are discussed. It doesn’t understand the world like a human does, but it learns patterns, facts, and relationships by seeing how often certain words and concepts appear together.
How It Works in Practice
When you ask it a question or give it a “prompt” (an entry into the chat window), the AI predicts the most likely way to respond based on all the patterns it learned. It uses its vast “memory” of text to create a response that fits what you asked. It’s not pulling information from a database or looking things up in real-time; instead, it’s generating responses based on the patterns it knows. So, it’s not simply regurgitating information from some other location. It’s generating a unique response that is largely based on trying to predict what you are seeking at that moment, and because of this, it’s important to understand the concept of “Bad Data IN / Bad Data OUT”.
Be Very Specific.
We’ll cover how to write good “prompts” or entries into ChatGPT in a different lesson but suffice it to say that if you ask a very general question you should expect very general, often unhelpful information back in return.
Bad Prompt:
“Tell me about marketing.”
This prompt is too broad and vague. It doesn’t give any specific direction so that the response could cover anything from marketing history to strategies, channels, or best practices. It’s hard for the AI to know what you really want.
Best Prompt:
“Explain the most effective digital marketing strategies for B2B SaaS companies targeting mid-sized enterprises, focusing on lead generation, content marketing, and account-based marketing (ABM). Include specific tactics that have been successful in recent years.”
This version is much more specific. It tells the AI:
- What to focus on: Digital marketing strategies.
- Who it’s for: B2B SaaS companies targeting mid-sized enterprises.
- Key topics to cover: Lead generation, content marketing, and ABM.
- Time frame: Tactics that have been successful in recent years.
By being specific and clear about what information you’re looking for, the prompt guides the AI to provide a detailed and relevant response tailored to your needs.
Key Points:
- Training Data: It learns from a broad set of information available on the internet—essentially any public text that was available during its training period.
- Pattern Recognition: It recognizes how words, phrases, and ideas are used together to predict the best way to respond, even if it doesn’t “understand” the information like a human.
- No Real-Time Access:
It doesn’t browse the web for answers when you ask it something; it relies on the information it absorbed during training.Remember above when I said it gets better and smarter daily? ChatGPT now does access the web, but it does so merely for context. It doesn’t regurgitate blocks of text from web pages. It synthesizes the response from many, many sources of information.
What Makes Generative AI Special?
By far, the first two questions that new users ask are:”Yes, but what can I do with it?” and “Okay, how do I use it and become proficient at it?” Asking “What can I do with it?” is a bit like asking how long is a piece of string or how high is up. A good, albeit basic, analogy is to think of generative AI as a tool. There are perhaps 1000 ways that one can use a Swiss Army knife. It’s the same with Generative AI, except the knife keeps improving and becoming more valuable daily. In terms of use cases, you are limited only by your own imagination.
Generative AI is a versatile tool capable of producing a variety of content based on your needs. It can:
- Draft professional reports, articles, and presentations.
- Create visual content like infographics or digital artwork.
- Compose music or design audio elements.
- Generate and debug code.
- These capabilities make it a valuable asset for professionals seeking to boost productivity, enhance creativity, and streamline complex tasks efficiently.
The “Jet Engine for Your Mind”
Steve Jobs once called the personal computer a “bicycle for the mind,” enhancing our mental capabilities. If that’s true, then Generative AI is a jet engine! It supercharges your ability to create, learn, and solve problems.
Real-World Examples:
- Writing: AI can draft emails, reports, and even entire books
- Healthcare: Doctors use AI to spot patterns in medical images, detecting diseases earlier
- Education: Students use AI for research and to explain complex topics
- Business: Companies use AI for customer service, data analysis, and product development
Popular Generative AI Tools:
- ChatGPT (by OpenAI)
- Claude (by Anthropic)
- Gemini (by Google)
- Microsoft Copilot (by Microsoft)
While these tools have similar capabilities, some are better than others at specific tasks:
- ChatGPT: Great all-rounder, excellent for writing and coding
- Claude: Known for nuanced responses and ethical considerations
- Google Gemini: Strong in multilingual tasks and information retrieval
- Microsoft Copilot: Integrates well with Microsoft products for productivity
In this course, we’ll primarily be using ChatGPT, but the skills you learn here will apply to any Generative AI tool.
Which One Should I Use?
What we teach here are core AI skills that are “platform-agnostic,” meaning that they’ll work well on almost any generative AI model. Most above are free to try, and because AI can be a bit overwhelming, we’d encourage you to start with ChatGPT first and then experiment with all of them. Some are better than others at specific things, like writing, for example.
Practical Exercise
Choose two or three Generative AI tools, i.e., Perplexity, ChatGPT, Claude, Microsoft Copilot, Google Gemini, etc.
For each tool, ask the question, “What are the key components of a good prompt?”
Review each of the outputs and give consideration to the following:
What similarities were present in each output?
What were the differences?
Was one “better” than the other and why?
Which one listed references?
Was it important to you that references were listed?
PRO TIP: Open 2-3 tabs on your web browser so you can quickly compare output differences, or set up two browser tabs as split screen so you can see their outputs at the same time!
You can do this exercise with any prompt, but since we’re learning about creating better prompts (so that we will get better output back) it helps to start with:
What are the key components of a good prompt?AI for Everyone
Generative AI isn’t just for tech experts; it’s a tool for professionals in all fields. It empowers you to enhance your skills, streamline tasks, and explore new ways of working. As you dive into the world of AI, remember that you don’t need a technical background to make the most of it—just an open mind and a willingness to experiment. Let AI become your partner in achieving efficiency and innovation in your work.
Assignment
Nobody told me there was going to be homework. Ugh.
No worries! Throughout the course most of what is required will simply be copying and pasting a prompt from this course into ChatGPT. We’re going to get you using the tool right away so you can learn by doing. That said, if you haven’t already got one, your assignment for today is to go now and set up a ChatGPT account, then bookmark it in your browser because you’ll be using it often.
Most of the generative AI models offer free and fee-based accounts. For now, it’s fine for you to set up a free account, but eventually if you use the tool a lot you’re going to want a paid account because it removes usage limits or increases them (# of prompts per day you can query) and a paid account gives you access to the latest models for better responses. Best of all, it’s literally the cost of two lattes per month. As of this writing, it’s $20/month and well worthwhile.
Once you get your account created, if you’d like to better understand the differences between a free account and a paid subscription, just copy this prompt and drop it into ChatGPT:
Explain the differences between the free version and the paid subscription version of ChatGPT. Present the information in a table format with side-by-side columns for each version, focusing on features, capabilities, limitations, access to model versions, response speed, and availability. Include examples to illustrate how the user experience varies between the two options.Next Lesson
Next, we’ll explore the benefits and limitations of Generative AI, helping you understand what it can (and can’t) do.
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