QDay Forum A.I A-Z Glossary

[RustyHawk]

AI GLOSSARY (A-Z)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A
Algorithm
A defined set of rules or steps a computer follows to solve a problem or perform a task.

B
Backpropagation
A training method for neural networks that adjusts weights by propagating errors backward through the network.

C
Convolutional Neural Network
A neural network architecture designed for processing grid-like data such as images.

D
Deep Learning
A subset of machine learning using multi-layered neural networks to model complex patterns.

E
Embedding
A numerical vector representation of data such as words or images that captures meaning or relationships.

F
Fine-Tuning
The process of taking a pre-trained model and adjusting it further on specific data.

G
Generative AI
AI systems that create new content such as text, images, or audio.

H
Hyperparameter
A configuration value set before training that controls how a model learns.

I
Inference
The process of using a trained model to make predictions or generate outputs.

J
Joint Probability
The probability of two or more events occurring at the same time.

K
Knowledge Graph
A structured representation of information showing relationships between entities.

L
Large Language Model
A neural network trained on vast amounts of text to understand and generate human language.

M
Machine Learning
A field of AI where systems learn patterns from data instead of being explicitly programmed.

N
Neural Network
A computational model inspired by the human brain, composed of interconnected nodes.

O
Overfitting
When a model learns training data too closely and performs poorly on new data.

P
Prompt Engineering
The practice of designing inputs to guide AI models toward desired outputs.

Q
Q-Learning
A reinforcement learning algorithm that learns optimal actions using reward feedback.

R
Reinforcement Learning
A learning method where agents improve by receiving rewards or penalties from actions.

S
Supervised Learning
Training a model using labeled data where correct outputs are known.

T
Transformer
A neural network architecture that uses attention mechanisms to process sequences efficiently.

U
Unsupervised Learning
Learning patterns from unlabeled data without predefined outputs.

V
Vector Database
A database optimized for storing and searching vector embeddings.

W
Weights
Parameters in a neural network that determine the strength of connections between nodes.

X
Explainable AI
Methods and techniques that make AI decisions understandable to humans.

Y
YOLO (You Only Look Once)
A real-time object detection algorithm that processes images in a single pass.

Z
Zero-Shot Learning
The ability of a model to perform tasks it was not explicitly trained on

[Inland Aidan]

OMG thats great. And really needs to be stickied

[Inland Sienna]

Still learning but that tracks. The more I read about this the more I realise how much I do not know.

Appreciate the detail

[SpinorWave]

Still learning but that tracks. The more I read about this the more I realise how much I do not know. Appreciate the detail.

Same here. That is just how it is.

Ha, fair enough.

[Ann]

That checks out from what I have seen. Start there and see if it makes a difference.

Most AI tools I have tried are impressive for a session and then disappear from my routine

[Eastern Aaron]

Massive thanks for putting this together. An A-Z glossary like this is actually one of the most useful ways to get people past the buzzword wall. New AI terms appear every week and it is easy to spend more time figuring out the language than learning the tools.

The examples make it much easier to understand what each term means in practice.

[ElectricVector]

Great effort on this. A glossary is a simple idea but it solves a real problem because half the battle with AI is knowing what people are even talking about. Appreciate the time that must have gone into collecting and organising everything.

[Penguin79]

This is the kind of resource that helps beginners without making experienced users feel left out. Nice balance between the basic concepts and the newer AI terminology.

Bookmarking this one. Saves a lot of searching through random explanations later

[Sharp Scholar]

Really appreciate the work here. AI discussions can become a soup of acronyms and fancy phrases, so having everything in one place is genuinely helpful.

The A-Z format is also perfect because you can dip in when you hit a term you do not recognise.

[Neon Harper]

Very useful contribution. The hardest part of getting into AI is often not the technology itself but understanding the vocabulary around it.

A glossary like this turns a confusing topic into something much more approachable. Nice job

[TheGreatMoney]

Thanks for taking the time to build this. It reminds me of the old computer dictionaries people used to keep around, except now the pages would need updating every other week because AI moves so quickly.

Definitely a good starting point for anyone trying to follow the conversations happening now.

[Inlet]

This deserves appreciation. There are plenty of AI tools out there, but without understanding concepts like models, prompts, agents and training, people are just clicking buttons and hoping for magic.

Having a reference like this helps people become better users instead of just casual experimenters.

[Daemon90]

Excellent idea for a thread. A glossary is probably one of the best community resources because everyone benefits from adding corrections and extra examples over time.

Hopefully it keeps growing as new terms appear. AI is not exactly slowing down