Easy on those ChatGPT prompts, buddy—marketers eager to incorporate AI into their business strategies need first to learn the key terms that articulate the space. It is a vocabulary that, like that of Web3, endlessly bends back on itself, requiring the knowledge of prior concept upon prior concept like a stack of nesting dolls. How else is one supposed to understand LLMs if they don’t already have neural networks down? Worse yet, how embarrassing it might be to discuss LaMDA when really you meant to talk about LLaMA…

For these reasons, Ad Age has compiled a glossary of all the words and concepts you need to know to get this space straight. And we’ll continue to update it as more terms become necessary to understand. 

Artificial intelligence (AI): The general set of technologies that use advanced computing to perform tasks. Neural networks, machine learning, LLMs—these are all developments that belong under the AI umbrella. While generative AI is a subset of AI, when we say AI we don’t necessarily mean tools that generate content. The history of AI dates back to the 20th century, but advancements beginning in the 1960s led to the capabilities that are available today.

Related: A generative AI guide for brands

Chatbots: The programs running inside messaging apps and on websites that help consumers perform simple tasks. Chatbots were popularized by apps like Facebook Messenger, and they operate like apps within the messaging services. The recent boom in generative AI bots like ChatGPT and Bard will enable these services to be far more advanced and human-sounding.

ChatGPT: A generative AI bot created by OpenAI, which uses GPT technology (see below) to produce an output based on an input. The platform was trained on vast quantities of text taken from websites, articles, books and other sources. It launched publicly at the end of 2022 and quickly exploded in popularity due to its vast array of capabilities, from screenwriting to joke-telling to disseminating knowledge on basically any topic under the sun. 

Related: ChatGPT writes Super Bowl ads

Clusters: A fancy word for a group of people—or anything—sharing a common characteristic. AI programs can identify clusters within mountains of data, uncovering patterns that humans alone can’t perceive or connections that people wouldn't draw. Clusters can lead to developing audiences or segments for marketing purposes, creating a group of people with common traits and targeting them with ads. 

DALL-E: Another generative AI bot created by OpenAI, though its function is in generating images. Like ChatGPT, a user queries the bot with an input (e.g. “Ronald McDonald swimming in a river of fire”) and out comes a corresponding image. The first version of DALL-E launched in January 2021 and its more advanced successor, DALL-E 2, launched in April 2022. This latest version can produce a larger array of images, and even in a diversity of styles (e.g. “Ronald McDonald swimming in a river of fire, in the style of Norman Rockwell”).

Deep Learning: A more advanced branch of machine learning, where a computer teaches itself with only minimal amounts of programming. With deep learning, marketers can make the most use of data and apply it to make predictions about consumer behavior.

Dynamic Pricing: One of the common tasks that deep learning-based programs can perform is setting prices based on consumer data. Dynamic pricing means that each consumer is presented with a price based on their own particular circumstances, depending on the time of day, their financial situation and other factors. Dynamic pricing can come into play in rates for plane tickets, for instance. AI can help craft personalized prices that are most likely to ensure a sale at the most efficient rate.

Generative AI: Generative artificial intelligence is a form of AI that, as its name suggests, generates content. Depending on the specific platform’s capabilities, this content can be images, videos, text, audio, as well as other mediums. The platforms that have recently become popular generate their content from a user’s input, such as “Produce an image of X” or “What is the answer to Y?”

GPT: Generative Pre-trained Transformer, a generative AI model that is trained on reams of data in order to produce an output. The technology was created by OpenAI, and the most recently released version is GPT 3.5 (which is the tech underlying ChatGPT). GPT 4 is expected to launch some time in 2023.

Image recognition: AI looks for patterns in images. Machines can analyze many more images than humans, and with machine learning they can identify what's in the images and reveal patterns that people would never detect. Brands can use image recognition technology, for example, to find every photo online in which their logos appear. That could help brands locate their most loyal customers and tease out other actionable marketing insights. "Computer vision" is a term associated with image recognition, and refers to computer programs that analyze and categorize digital images.

LaMDA: Language Model for Dialogue Applications, a generative AI model developed by Google. It is an LLM like OpenAI’s GPT model. Google launched the first version in Spring 2021, and the second in June 2022. LaMDA powers Bard, Google’s ChatGPT-like bot that will be incorporated in the company’s array of products, including its primary search engine.

Related: How Snap, Google and Meta are embracing generative AI  

LLaMA: Large Language Model Meta AI, a generative AI model developed by Meta. It is an LLM, like OpenAI’s GPT and Google’s LaMDA. Meta has yet to release any kind of chatbot powered by LLaMA, and may not do so for some time given the noncommercial license underlying the model. Meta has said that LLaMA is currently intended for research purposes only. The model launched in February 2023.

LLM: Large Language Model, a class of AI technology whose primary function is to create human-sounding text. The platforms are trained on reams of data and built on intricate neural networks that enable them to make predictions and generate corresponding text. OpenAI’s GPT model is an LLM.

Machine learning: When a machine teaches itself with minimal programming needed. Machine learning can be helpful in direct marketing and email marketing, in particular, by ingesting vast sets of consumer data and using it to determine things such as the best times to send emails. Proponents say it can also identify the clients or customers that would be most receptive to given messages. And machine learning is used in ad targeting to help deliver messages to those audiences.

NLP: This stands for Natural Language Processing and it is the technology that enables machines to interpret what people are saying in words or in text. Sophisticated AI can decipher speech, not just understanding the words but the context. Advanced natural language processing can detect sarcasm and other subtle human tones. Natural language processing is essential to the automated customer service of the future.

Neural Networks: Artificial intelligence programs modeled after the human brain. They incorporate deep learning and natural language processing to perform functions like recognizing handwriting and faces in photos.

OpenAI: An artificial intelligence company that has created some of the most popular generative AI tools, including ChatGPT and DALL-E 2. OpenAI started as a non-profit organization in 2015, founded by a team including Elon Musk, but transitioned into a for-profit company in 2019. While technically independent, OpenAI is heavily backed by Microsoft; the tech giant invested another $10 billion in OpenAI at the start of 2023, and is currently rumored to maintain a 49% stake in the company. Microsoft plans to use OpenAI’s tools in its own products, including the Bing search engine.

Unstructured data: A term for disorganized pools of data that appear random and unconnected. Machine learning can make sense of the data, and it can identify clusters within it and other patterns that could be useful when making marketing decisions. Marketers gather all kinds of data, even if it doesn't seem relevant at the time, because they never know when something interesting is going to pop up.

Weak/Narrow AI: AI that's limited to specific tasks. Basically all of the AI found in marketing is weak. Most AI overall—the code behind everything from virtual assistants to self-driving cars—is actually considered weak. The next evolution is artificial general intelligence, bringing us closer to the long-anticipated, futuristic robots that could outperform any human at any task.