Source: Crash Course
Artificial Intelligence is both a field of study and a type of technology. Artificial Intelligence or AI refers to the capacity of computers or other machines to exhibit or simulate human behavior (OED). (Read More)
AI technologies are data-driven, and largely rely on three major subfields:
One of the important things to note is that we do not currently have Artificial General Intelligence (AGI). AGI, also known as Strong AI or Human-Level Machine Intelligence (HLML) refers to systems capable of conducting a complete range of intellectual tasks at a level equaling that of the best-performing human beings. This type of Artificial Intelligence is still entirely theoretical, but continues to be researched. (Read More)
Generative AI uses techniques that learn from representations of data and model artifacts to generate new artifacts. Generative AI applications are all created on top of Foundational Models: ML models trained on a broad spectrum of generalized and unlabeled data and capable of performing a wide variety of general tasks.
Generative AI can learn from existing artifacts to generate new content that reflect the characteristics of their training data. (Read More)
The most common form that Generative AI takes is as a Chatbot. A chatbot is a computer program that simulates conversation with a human end user, using Natural Language Processing.
The most popular, generalized Generative AI chatbots are:
It is important to recognize that not all chatbots online will use Generative AI to formulate responses. Non-AI chatbots follow prescriptive workflows and cannot generate new responses.
Generative AI tools are new, and many of the free versions use open models, in which developers from outside the organization can examine, modify, and distribute training data and code.