Artificial Intelligence

Artificial Intelligence, or AI, was coined by John McCarthy in 1956. It's been a hotly contested term ever since. mainly due to the implications of the word "intelligence." We can divide AI into two categories.

What we have right now:

Narrow/Weak AI: a program or machined trained on one thing, and it (hopefully) does that one thing well.

What we have in movies:

Strong AI: A more general, overall intelligence. Think Terminator.

Supervised Learning

In contrast to machine learning, this is a model or an algorithm that has human help, such as already labeled data

Training Data

The data inputted into algorithms and models in order to create something like machine learning models or ChatGPT

Black Box AI

Referring to things we don't understand or see - many machine learning algorithms are black boxes because we don't fully understand how it is making its decisions

GPT

Generative Pre-Trained Transformer - a type of language model

LLM (Large Language Model)

Machine learning models that recognizes and generates text, because it has been trained on massive sets of textual data

Machine Learning

Think of machine learning as a field of study within AI; in machine learning, an algorithm may identify rules and patterns in the data with a human specifying them

Natural Language Processing

Another field of study within AI; it uses an understanding of structure, grammar, and the meaning of words to help a computer "understand." Some examples include speech to text, Grammarly, text summarizers, etc. 

Neural Networks

A method in artificial intelligence that teaches computers to process data in a similar way to the human brain

Deep Neural Networks

Many layered neural networks - the input goes through many layers before you get the output in this type of model