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Artificial Intelligence - Student Guide

Artificial Intelligence (AI) vs Generative AI (GenAI)

Artificial intelligence (AI) refers to computer systems that perform tasks typically requiring human intelligence. AI is at work in applications we use everyday, including the speech recognition used by Google translate, Siri, and Alexa, the natural language processing used by search engines like Google, and the predictive text used for autocomplete and smart compose.  

Generative AI (GenAI) is “a type of artificial intelligence that involves creating machines or computer programs that can generate new content, such as images, text, or music. Unlike traditional AI systems that rely on predefined rules or pre-existing data to make decisions, generative AI models use algorithms and neural networks to learn patterns and relationships in data and generate new outputs based on that learning” (Kwantlen Polytechnic University, n.d., p. 1).

Kwantlen Polytechnic University. (n.d.). Generative AI: An Overview for Teaching and Learninghttps://tinyurl.com/4etx244v

Terminology note

As many of us have come to use the term AI to refer to generative AI tools, throughout this guide you will find the following terms used interchangeably: AI, Generative AI, GenAI

Types of Generative AI

Many different types of generative AI can create text, images, sound, video, and more. The following information describes common types of generative AI and includes examples of tools.

 

Text generators

Text-based generative AI tools create new text similar to the data they were trained on. The training process for these AI chatbots involves consuming large amounts of text from data from webpages, books, and other sources, then analyzing the text to find patterns and relationships in human language. Because of this training process, these tools are commonly referred to as Large Language Models (LLMs). They use probability to predict which words should appear in sequence. As Stephen Wolfram explained, “it’s just saying things that ‘sound right’ based on what things ‘sounded like’ in its training material.”

  • AI chatbots can produce essays, blogs, scripts, news articles, reflective statements, and even poetry. 
  • Some chatbots rely on their training data to produce content, while others are grounded in a source of facts.
  • Examples of generative AI that can create text content include: ChatGPTPerplexity AI, and Microsoft Copilot.

 

Image generators

This type of AI learns through analyzing datasets of images with captions or text descriptions. If it knows what two different concepts are, like a cat and a skateboard, it can merge those concepts together when prompted to create an image of a cat on a skateboard.

  • Generative AI image tools can produce diverse images in a range of media, everything from photorealistic oil painting style to anime.
  • Examples of generative AI that can create imagery include: DALL·EMidjourney, and Stable Diffusion.

 

Sound and music generators

AI music generators analyze music tracks and metadata (artist name, album title, genre, year song was released, associated playlists) to identify patterns and features in particular music genres. They may also be trained on song lyrics. If a music generator has only been exposed to one type of music (e.g., classical), then the music it generates will sound similar to those works.

  • Examples of generative AI that can create audio content include: AIVA and Soundful.

 

Video generators

Creating a video typically requires the use of audio, visual, and text elements. Some generative AI video programs have harvested existing videos to learn how to create new ones, while others have sourced the three elements to create video from audio, visual, and text sources. There are even generative AI video programs that have been trained to use video editing software, so they can apply effects to a video that you have created, such as adding captions, transitions, and animations.

 

Research discovery and explanation generators

Some generative AI tools can automate parts of the research process and make long, complex texts easier to decipher. This type of AI often analyzes research papers that users upload to extract key information or summarize a paper.

  • Examples of generative AI that can support research discovery and generate explanations include: Elicit and Scite.

Note: Many of these tools cost money to use or to access premium features, like more recent content and faster processing speeds. However, in some cases you can create a basic account for free or explore the tool with a short-term trial.

Further Learning

Telus International. (2024). 50 AI terms every beginner should know. https://www.telusinternational.com/insights/ai-data/article/50-beginner-ai-terms-you-should-know

Dev Explain. (2023, March 8). What is Artificial Intelligence? AI Explained [Video]. YouTube. https://www.youtube.com/watch?v=zFJAnNdDVF0

The Royal Institution. (2023, October 12). What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata [Video]. YouTube. YouTube. https://www.youtube.com/watch?v=_6R7Ym6Vy_I&t=2s

 
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