# Artificial Intelligence glossary

Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.

## Open-Source Software

## Partial Order Reduction

## Particle Swarm Optimization

## Predictive Analytics

## Probabilistic Programming

## Programming Language

## Prolog

## Quantifier

## Quantum Computing

## Reasoning System

## Recurrent Neural Network

## Reinforcement Learning

- What is reinforcement learning in simple terms?
- What is reinforcement learning in simple words?
- What is basic example of reinforcement learning?
- What is the primary purpose of reinforcement learning?
- How reinforcement learning is different from supervised learning?
- What is the learning theory of reinforcement learning?

## Restricted Boltzmann Machine

## Rete Algorithm

## Robotics

## Rule-Based System

## Selection

## Self-Management

## Semantic Reasoner

## Separation Logic

## Simulated Annealing

## Situated Approach

## Situation Calculus

## Sparql

## Spiking Neural Network

## Statistical Classification

## Stochastic Optimization

- Why use stochastic optimization?
- What are stochastic optimization problems?
- What is the difference between deterministic and stochastic Optimisation?
- Which one is the main advantage of stochastic optimization techniques?
- What is an example of a stochastic algorithm?
- What are the disadvantages of stochastic optimization?

## Stochastic Semantic Analysis

## Stanford Research Institute Problem Solver

## Superintelligence

## Agents

## Asi

## Attention

## Double Descent

## Explainable Ai

## Forward Propagation

## Gpt

## Gpu

## Gradient Descent

## Hallucinate/Hallucination

## Hyperparameter Tuning

## Latent Space

## Mixture Of Experts

## Multimodal

## Nerf

## Regularization

## Singularity

## Transformer

## Underfitting

## Validation Data

## Area Under The Curve

## Artificial Neural Networks

## Association Rule Learning

## Batch

## Bias

## Bounding Box

## Clustering

## Cold-Start

## Confidence Interval

## Contributor

## Central Processing Unit

## Cross-Validation

## Structured Data

## Decision Tree

## Deep Blue

## Deep Learning

## Dimensionality

## Embedding

## Ensemble Methods

## Entropy

## Feature Selection

## False Positive

## Feed-Forward (Neural) Networks

## F-Score

## General Data Protection Regulation

## Ground Truth

## Human-In-The-Loop

## Imagenet

## Information Retrieval

- What is an example of information retrieval?
- What is information retrieval explain with two examples?
- What is the meaning of retrieval of information?
- What are the three types of information retrieval?
- What is the goal of information retrieval?
- What is difference between data retrieval and information retrieval?

## Learning Rate

## Multi-Modal Learning

## Multi-Task Learning

## Naive Bayes

## Neuron

## Optimization

## Pre-Trained Model

## Rectified Linear Unit

## Regressor

## Semi-Supervised Learning

- What is semi supervised learning and why is it so important?
- What are the two 2 types of unsupervised learning?
- What are the pros and cons of semi-supervised learning?
- What is the difference between weak supervised and semi-supervised learning?
- What is the difference between semi and self supervised learning?
- What are the two types of supervised learning?

## Support Vector Machines

## Topic Modeling

## Type I Error

## Type Ii Error

## Uncertainty

## Validation

## Vanishing/Exploding Gradients

## Swarm Intelligence

## Technological Singularity

## Theoretical Computer Science

- What is an example of a theoretical computer science?
- What do theoretical computer scientists do?
- What is theoretical computer science?
- How much do theoretical computer scientists make?
- What is the difference between theoretical computer science and artificial intelligence?
- What is the difference between theoretical and practical computer science?