Generative AI

What is Artificial Intelligence?

AI is a field of science concerned with building computers and machines that can reason, learn, and act in such a way that would normally require human intelligence or that involves data whose scale exceeds what humans can analyze.

Commonly used terms

You will hear a lot of commonly used technical terms when talking about AI.

• Algorithm: A finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation.
• Bias: Assumptions made by an AI system in order to simplify the process of learning and performing the task(s) it was designed for.
• Deep Learning: A subset of machine learning methods based on neural networks with representation learning.
• Deepfake: A piece of media created by deep learning or other AI technology to misrepresent reality.
• Large Language Model: A neural network with a large number (usually billions) of parameters, with large amounts of text used as its training data. 
• Machine Learning: A field of research focused on how machines can "learn" (i.e., become capable of more and more advanced tasks).
• Natural Language Processing: The study of AI systems can be used to process and generate human language.
• Neural Networks: In machine learning, these are computational models inspired by the structure and function of biological neural networks in the brain.
• Parameter: A variable within an AI system that is used to make predictions.
• Prompt: The user input that a generative AI model responds to.

What is Generative AI?

Generative AI refers to Artificial Intelligence systems that can create new content, such as text, images, or music, rather than simply analyzing or processing existing data. Large language models (LLMs) are a subset of generative AI, as they have the ability to generate coherent and contextually relevant text based on a given prompt or input.

The key feature of LLMs in relation to generative AI is their ability to produce human-like text in a variety of styles and contexts. They can generate anything from news articles, stories, poetry, and code. This capability has numerous applications in fields such as content creation, natural language understanding, and more.