Generative AI : Important Generative AI Concepts

Generative AI Glossary

Below are some important terms for understanding generative AI: 

• "Generative AI: Technology that creates content — including text, images, video and computer code — by identifying patterns in large quantities of training data, and then creating original material that has similar characteristics. Examples include ChatGPT for text and DALL-E and Midjourney for images."
• "Hallucination: A well-known phenomenon in large language models, in which the system provides an answer that is factually incorrect, irrelevant or nonsensical, because of limitations in its training data and architecture."
• "Large language model: A type of neural network that learns skills — including generating prose, conducting conversations and writing computer code — by analyzing vast amounts of text from across the internet. The basic function is to predict the next word in a sequence, but these models have surprised experts by learning new abilities."
• "Natural language processing: Techniques used by large language models to understand and generate human language, including text classification and sentiment analysis. These methods often use a combination of machine learning algorithms, statistical models and linguistic rules."
• "Neural network: A mathematical system, modeled on the human brain, that learns skills by finding statistical patterns in data. It consists of layers of artificial neurons: The first layer receives the input data, and the last layer outputs the results. Even the experts who create neural networks don’t always understand what happens in between."

All definitions from:

Pasick, A. (2023, March 27). Artificial Intelligence Glossary: Neural Networks and Other Terms Explained. The New York Times. https://www.nytimes.com/article/ai-artificial-intelligence-glossary.html