Understanding AI

Artificial Intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

Large language models, such as ChatGPT can sometimes “hallucinate,” a term used to describe the tendency for such models to respond with inaccurate or misleading information.

This is a traditional AI term for systems that use a database of facts and rules to provide assistance or make decisions within a specific domain, emulating human expertise. The "single source" is its specific, curated knowledge base.

A type of deep learning model trained on a large dataset to perform natural language understanding and generation tasks. There are many famous LLMs like BERT, PaLM, GPT-2, GPT-3, GPT-3.5, and the groundbreaking GPT-4.

Machine learning, in artificial intelligence (a subject within computer science), discipline concerned with the implementation of computer software that can learn autonomously.

is a subfield of computer science and artificial intelligence (AI) that uses machine learning to enable computers to understand and communicate with human language.

Responsible AI refers to the approach of creating, implementing, and utilizing AI systems with a focus on positively impacting employees, businesses, customers, and society as a whole, ensuring ethical intentions and fostering trust.

A type of machine learning in which a model is trained on labeled data to make predictions about new, unseen data. Example: A supervised learning algorithm that can classify images of handwritten digits based on labeled training data.

The process of breaking text into individual words or sub words to input them into a language model. Example: Tokenizing a sentence "I am ChatGPT" into the words: “I,” “am,” “Chat,” “G,” and “PT.”