There are a bunch of AI keywords that create your foundational knowledge of AI. You should know and understand them.
I have recorded a video and described AI keywords with a short, precise explanation. Watch it here:
In this video, I’ve described the following AI keywords:
1- AI (Artificial Intelligence)
Artificial Intelligence, or AI, is a technology that enables computers to simulate human intelligence and problem-solving capabilities.
Examples are Siri or reading a car's plate number at the parking entrance.
2- Generative AI
Generative AI refers to artificial intelligence models that can create new content, such as text, images, audio, or video.
Examples are ChatGPT or DeepSeek.
3- ANI (Artificial Narrow Intelligence)
Artificial Narrow Intelligence, or ANI, is a type of AI designed to perform a single specific task.
Examples are self-driving cars or defect detection in a factory line
4- AGI (Artificial General Intelligence)
Artificial General Intelligence, or AGI, is the potential form of AI that can perform any intellectual task a human can.
5- Agentic AI
Agentic AI refers to AI systems designed to autonomously make decisions, plan, and execute tasks to achieve goals with minimal human intervention.
6- Model
A model is an AI system that has been trained on a dataset to recognize patterns, make predictions, or generate new content.
Examples are GPT-4 model by OpenAI or Gemini 1.5 Flash model by Google.
7- Algorithm
An algorithm is a set of rules or instructions designed to enable machines to learn from data, make decisions, or perform tasks.
8- LLM (Large Language Model)
Large Language Model, or LLM, is a type of AI trained on vast amounts of text data to understand and generate human-like language.
9- Multimodal
Multimodal describes models that can process and generate multiple types of data, like text, images, audio, and video.
An example is Gemini 1.5 by Google that can process and generate text, images, audio, video, and code.
10- Prompt
A prompt is a text input given to an AI model to guide its response or generate desired output.
An example is: Write an email to stakeholders, inform them of the scope and goal of the Sprint, and invite them to the upcoming Sprint Review.
11- ML (Machine Learning)
Machine Learning is a subset of AI that enables systems to learn from data, identify patterns and make decisions or predictions.
12- DL (Deep Learning)
Deep Learning is a subset of machine learning that uses multi-layered neural networks to learn complex patterns and create highly accurate outputs.
13- Supervised Learning
Supervised Learning is a model training approach to learn from paired input-output labeled data to predict outputs for new, unseen inputs.
14- Unsupervised Learning
Unsupervised Learning is a model training approach where a model discovers patterns and structures within unlabeled data.
15- Reinforcement Learning
Reinforcement Learning is a model training approach where a model learns to optimize decisions based on receiving rewards and penalties for actions.
An example is when computers learn to play chess.
16- Diffusion Model
A diffusion model is a generative AI technique that learns by iteratively adding noise to data and then denoise it to create new outputs like images.
An example is that most AI images are generated by Diffusion Models.
17- RAG (Retrieval-Augmented Generation)
Retrieval-Augmented Generation, or RAG, is an AI technique that enhances large language models by retrieving information from external sources to generate more accurate and context-aware responses.
An example is giving your company's HR policy document to a model, then your employees can ask how to use the company parking lots or how to have a work mobile phone.
18- Fine-tuning
Fine-tuning is the further training of a pre-trained AI model on a smaller, domain-specific dataset to enhance its performance for a particular domain.
Examples are fine-tuning a model for medical or legal domains.
19- Token
A token is the fundamental unit of text that an AI model processes, which can be a word, part of a word, or even a single character.
For example, this sentence with 4 words is calculated as 5 tokens:
My name is Mehdi
20- GPT (Generative Pre-trained Transformer)
Generative Pre-trained Transformer, or GPT, is a family of large language models developed by the OpenAI company that generates human-like text based on input prompts.
Hopefully, you enjoyed this fast exploration of the foundational AI keywords.