The Great Big Amplience AI Glossary
To help you get your head around the (sometimes quite confusing) world of AI, we’ve put together a glossary full of clear and simple explanations for some of the key terms around AI technology. We’ll be keeping it updated, so feel free to pop back whenever you’re in need of a little AI understanding.#
* Hello World
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_ Hello World
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Aa
Agent
AI agents are autonomous entities, often software programs but also entire systems (eg: self-driving cars) that act in an intelligent manner (ie: perceive and interact with their environment) to take actions that will achieve specific goals. There are different types of agents, such as simple reflex agents, learning agents, and utility-based agents. Examples of agents include smart vacuums, self-driving cars, personal assistants on your phone or smarthome hub, even computer programs that run on their own without human involvement.
AGI (Artificial General Intelligence)
A hypothetical type of AI that’s equal to or superior to humans, exhibiting self-awareness, consciousness, the ability to adapt to its surroundings, and other uniquely human abilities.
AI (Artificial Intelligence)
A branch of computer science focused on building machines and systems that mimic human intelligence. AI is purpose-built to analyze data, generate content, and make decisions in ways that mirror human processes – ultimately becoming able to manage much larger quantities and different types of data faster and with fewer errors than humans.
Algorithm
A set of instructions used by computers to perform calculations and solve problems. As a subset of machine learning and key part of AI, algorithms are used to replicate tasks humans would normally do, but much faster and with greater power. There are many different types of algorithms, such as linear regression, K-means clustering, support vector machines, and more.
Alignment/Super-Alignment
Alignment is a field of AI safety research concerned with ensuring AI aligns with human values, preferences, and outcomes. Alignment is achieved if the AI intended objectives are completely met; misalignment is when intended objectives are not met, even if partially. Super-alignment is focused on superintelligent AI.
API (Application Programming Interface)
A set of protocols and routines that allow different software applications to communicate with each other and transfer data between themselves. The most commonly used API is REST (or representational state transfer architecture style) sometimes called RESTful APIs. APIs can be used to read, create, update, and delete data.
Cc
Catastrophic Interference/Catastrophic Forgetting
A phenomenon when artificial neural networks forget – either in part or completely – what they have learned after they’re trained on a new task or learn new information. As ANNs are given new information, new pathways are formed between the neurons, and sometimes this causes old pathways to be eliminated or broken. This is unlike humans who retain old knowledge even when learning new; we don’t overwrite memories but add to them.
ChatGPT
An LLM-based chatbot created by OpenAI that interacts with human users in a conversational way via text commands and questions, called Prompts. GPT stands for general pre-trained transformers, a type of Neural Network model using Transformer Model architecture.
Cognitive AI
A subfield of AI that endeavors to build systems that learn and think like humans, including complex reasoning, understand intent and are highly contextual, and excel and natural language processing and creation. They aim to be adaptive, interactive, and handle ambiguous situations better than traditional AI. They are increasingly multi-modal, mirroring the human senses to provide human-like perception.
Computer Vision
A field of AI that trains computers to understand images, videos, and data from other visual sensors through identification and classification of seen objects. Examples of computer vision include facial recognition, self-driving cars, movement analysis in medicine and sports, and plant identification.
Concept Drift
A phenomenon in machine learning where the data changes over time, causing the model to become less accurate or even completely incorrect. Concept drift can be caused by changes in the relationship between input and target variables, learned concepts evolve beyond original bounds, statistical properties change in unforeseen ways. Real life examples would include things like significant changes to laws, drastic shifts in customer behavior or economics such as those during covid, or discoveries that invalidate previous facts such as in science and medicine.
Dd
Data Science
It’s often considered a subset of AI, where practitioners are subject matter experts focused on managing, processing, and interpreting data at scale to drive decisions and extract insights. Complex math and statistics, advanced computer programming, analytics, machine learning, and AI are used by data scientists.