AI Terminology
Welcome to the AI Terminology section of the AI blog! This comprehensive glossary is designed to help you navigate the complex world of artificial intelligence. Here, you’ll find clear, concise definitions and explanations of key terms and concepts in AI, from foundational ideas like machine learning and neural networks to advanced topics such as reinforcement learning and variational autoencoders. Whether you’re a beginner or an expert, this resource is tailored to enhance your understanding and keep you up to date with the latest advancements in the field.
Human Intelligence
Human intelligence has been defined in many ways including as one's capacity for logic, abstract thought, understanding, self-awareness, communication, learning, emotional knowledge, memory, planning, creativity, and problem-solving.
Theory of Mind
Theory of mind systems are a type of artificial intelligence that focuses on understanding others' thoughts and beliefs.
Deliberative Machines
Deliberative machines represent the next step in AI evolution, capable of reasoning, planning, and making decisions through complex goal-oriented thought.
Limited Memory
Limited memory is a type of artificial intelligence that can remember and use past data to make decisions.
Reactive Machines
Reactive machines are a type of artificial intelligence that are designed to respond quickly to changes in their environment.
Artificial Superintelligence (ASI)
Artificial superintelligence (ASI) can generally be described as a computer that has surpassed human intelligence in all areas.
Self-Attention Mechanism
The self-attention mechanism enables AI models to understand relationships between words or image features simultaneously, making their outputs more coherent and context-aware.
Turing Test
The Turing Test measures whether a machine can exhibit conversational intelligence so convincing that humans cannot tell it apart from another human.
Transformer
The Transformer model revolutionized AI by introducing self-attention, enabling machines to understand context and relationships across entire sequences with unprecedented accuracy.
Artificial General Intelligence (AGI)
Artificial general intelligence (AGI) is a field of study focused on developing artificial intelligence systems that can learn and perform any intellectual task that a human can.
Deep Reinforcement Learning
Dive into Deep Reinforcement Learning: Understand how AI learns from mistakes to improve decisions in complex environments. Perfect for tech enthusiasts and professionals.
Attention Mechanism
An Attention Mechanism is a neural network component that prioritizes relevant information in data, enhancing context understanding and model accuracy.
Deep Learning
Deep learning is a branch of artificial intelligence that deals with the simulation of human intelligence by machines.
Semi-Supervised Learning (SSL)
Semi-supervised learning combines labeled and unlabeled data to train models more accurately while reducing the cost of manual annotation.