In my line of work, as someone who’s constantly explaining what I do for a living, it can be a lot for someone to wrap their head around.
Explaining that I cover the world of AI, the abundance of chatbots & AI agents that exist and the companies & bigwigs that throw big swaths of money at the growing tech can be a lot for someone to take in. I can only imagine how much more confused they get when they look up AI as a general search term and come across a bunch of additional technical jargon that scares them away from the trending tech altogether.
I went ahead and offered up a 15-minute lesson on how to start out using ChatGPT (which helped my parents get a decent understanding of one of the most popular AI tools). Now I’m here to break down seven of the most vital terms every AI user should know.
Whether you consider yourself someone who’s just starting to give AI a chance or a power user whose base level of knowledge is already strong enough, it’s still worth learning or getting a quick refresher on the world of AI.
1. Large Language Model (LLM)
A Large Language Model can be broken down easily by delving into what each letter in “LLM” stands for. The “L” represents the “large” amounts of data that it’s trained on, such as the words contained in books, on sites, in articles and across research papers. The second “L” pertains to the human “language” that it’s designed to understand, process and generate on its own.
And finally, the “M” represents the type of AI program that works as a “model” that interprets human patterns and relationships through words instead of just memorizing answers. For instance, an LLM taps into the patterns it’s learned during its training to properly respond to a user’s request to write a birthday message to their friend. Simply put, an LLM is the driving force behind a chatbot that helps it comprehend and generate human language.
2. Generative AI
Generative AI is a type of AI that can generate original content, such as text, images, audio, videos and computer code, based on the instruction you give it via a prompt. I’m sure you’ve come across all sorts of photos of people made to look like they exist in a neon-soaked 80s world, videos of dogs riding a skateboard like a human being and easily discernible AI-generated songs. Generative AI is used to produce those types of content as it’s commanded to create something new instead of just retrieving pre-existing information.
3. Machine Learning (ML)
Think of machine learning as a method in which computers are taught how to recognize patterns and make predictions based on all the data they’ve observed. Instead of having to be given specific instructions by a programmer to complete their task, computers can rely on machine learning to learn from examples to build knowledge over time.
Machine learning is comparable to the way Netflix brings up recommendations, as the streaming service analyzes what you’ve watched, what you’ve given a thumbs up to and what you’ve skipped to make educated decisions about what to suggest you watch next. The more information Netflix has, the stronger its recommendations will be. Machine learning is the core engine that’s crucial to the continued improvement of AI as a whole.
4. Neural Network
A neural network is a computer system that’s comparable to the human brain, as it contains layers of interconnected nodes that process information and identify patterns in the same way that neurons connect and communicate in our heads. It’s the system that helps AI recognize complicated patterns, with it being able to understand that you’re presenting it with a picture of a cat since a neural network helps it learn to recognize the patterns of that animal type.
5. Hallucinations
AI is prone to making mistakes, which are defined as hallucinations. When a chatbot confidently gives you information that is clearly incorrect or entirely made up, you’ve just borne witness to your AI tool hallucinating. AI doesn’t automatically recognize whether the information it’s giving you is true, which can lead it to produce made-up statistics and cite fake sources. As a tip, it’s always worth double- and even triple-checking the information AI feeds you. That rings especially true for those instances where a chatbot gives you medical, financial or legal advice.
6. Prompt Engineering
Prompt engineering is super easy to comprehend: it’s the process of writing detailed instructions that can help a chatbot produce better results for whatever you’re requesting. Now, a prompt is simply what you write into an AI tool. Prompt engineering is what you need to master so you can properly phrase your command so that the AI tool understands exactly what you want and delivers on it.
Going from a basic prompt such as “give me dinner ideas” to a more fleshed-out one such as “Give me [number] dinner ideas that take less than [time] to prepare, cost under [cost] per meal and use ingredients I can find at [name of supermarket” highlights a stronger mastery of prompting chatbots.
7. Tokens
I’m sure you’ve spotted instances of AI subscription plans that include a limit on how many tokens your current plan consumes.
Tokens are pretty much small chunks of text that AI models process when reading and generating language. Since chatbots don’t necessarily process an entire sentence as individual words, they break up portions of the text you put into it as tokens instead. A token can be classified as a single short word, a portion of a longer word, a punctuation mark and even a period. So a question you may type into ChatGPT will push it to break up that sentence into tokens before it processes it to generate a proper response.
Since some AI models have a limit on how much information they can process during a single conversation, tokens are brought up when looking at their subscription plans so you can understand how much they can take in before they reach their limit.
The takeaway
As someone who couldn’t even tell you the difference between a chatbot and an AI agent just a year ago, I’ve taken crash courses on the most important terms every type of AI user should know. I’m sure all the beginners out there won’t become pros at using ChatGPT, Gemini, Claude or any other AI tools overnight. But over time, you’ll recognize its benefits while also keeping the core definitions around AI as a whole in the back of your mind.
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