AI Glossary | Greendragonai

AI Artificial Intelligence - is a system that uses machine learning and algorithms to

simulate human intelligence.

AI Alignment - A field that aims to guide AI systems to align with humans’ intended goals and ethical principles.

AI Bias - Happens when machine learning algorithms produce prejudiced results. Several

factors can result in bias, such as When AI systems are either inadvertently or deliberately trained with biased data When the algorithm makes incorrect inferences during the learning process

AI Bias - is also known as machine learning bias or simply bias.

AI Ethics Moral guidelines for AI’s responsible use, design, and development. AI ethics are

meant to guide businesses and organizations to reduce the risks associated with

using and developing AI.

Algorithm - A set of instructions for an AI machine detailing how to solve a problem or perform a

Task.

Anthropomorphism - The tendency of humans to attribute human qualities to nonhumans like animals and chatbots. Because chatbots and other AI models are created to sound or appear

human, people tend to anthropomorphize them, attributing either a “he” or “she” Pronoun.

Artificial general intelligence (AGI) - A type of AI that can think, learn, perform intellectual tasks that humans do, and execute tasks it’s not trained to do. Also known as deep AI, AGI is still a theoretical type of AI as of this writing.

Artificial neural network (ANN) - See neural network.

Association rule learning - An unsupervised machine learning technique that aims to discover interesting relations among the variables in large datasets. In marketing, this learning technique

can find hidden patterns that provide insights into your business strategies and customer segmentation.

Augmented intelligence - The use of AI to enhance human intelligence and inform decision making instead of the AI performing tasks and processing data independently to replace humans.

Automatic speech recognition - Also known as speech recognition, a capability that enables an app to recognize and convert spoken language into a written format. It is also known as computer speech

recognition and speech to text.

Chatbot - A chatbot is a software designed to interact with humans through conversations. AI-powered chatbots use natural language processing (NLP) to interpret a user’s query and intent so they can provide marketing, sales, or after-sales support.

ChatGPT — or Chat Generative Pre-trained Transformer — is a large language model (LLM)-powered chatbot developed by OpenAI. It enables users to interact with it using human-like conversation.

CLIP -, or Contrastive Language-Image Pre-training, is a neural network by OpenAI that learns visual concepts from natural language supervision. Capable of learning from images and text, CLIP was trained on images with text captions from the Internet.

Copilot - is Microsoft 365’s AI assistant feature that builds on OpenAI’s GPT-4 large language models (LLMs).

DALL-E - is an AI system that uses machine learning to create images and art from a user’s description. Its most recent version, DALL-E 2, has higher-resolution images.

Data mining - is the process of sorting large data sets and spotting patterns that will be valuable for businesses to analyze further and inform their decisions.

Deep Blue - is a computer developed by IBM in 1997. It is known as the first chess-playing system to win a match against a chess world champion.

Deep learning.

Deep learning - is an advanced form of AI that imitates how the human brain works. Instead of relying on an algorithm to perform a task, deep learning uses neural networks like our brains, letting it make predictions based on patterns it has learned before.

Deepfake - A portmanteau of “deep learning” and “fake,” a deepfake is an AI-generated image, audio, or video depicting fake events. It uses powerful machine learning and AI to manipulate or create deceiving content.

Discriminator - A discriminator in a generative adversarial network (GAN) is a classifier that tries to identify real data from fake data created by the generator. The goal is for the discriminator to improve its ability to distinguish real from fake, as the generator tries to improve at creating fakes.

Garbage in, garbage out (GIGO) GIGO - is a computer science concept that low-quality data input will also result in low-quality output. The concept also applies in the AI realm: If AI is trained with biased and low-quality data, the output will be biased and mediocre.

Generative adversarial network (GAN) - A GAN is a type of machine learning that comprises two neural networks (a generator and a discriminator) competing with each other. The generator creates an output based on an input, while the discriminator identifies whether the output is real or not.

Generative AI - Generative AI is AI that creates content based on existing data it’s been trained on.

Generative pre-trained transformer (GPT) - Generative pre-trained transformer or GPT is a type of large language model (LLM) that’s trained to generate content. First launched by OpenAI in 2018, GPT now has GPT-4 as its latest model as of this writing. It’s one of the best LLMs that businesses can use today.

Natural language generation (NLG) - Natural language generation or NLG is the process of using AI to transform data into natural language that humans can understand. The data can be written or spoken.

Natural language processing (NLP) - Natural language processing or NLP is a branch of AI that studies how computers understand, interpret, and generate data in human language.

Neural network - Also called an artificial neural network (ANN) or simulated neural network (SNN), a neural network is a subset of machine learning. It mimics the way the human brain’s neurons signal to one another to solve a problem or deliver an answer.

Pathways Language Model (PaLM) - PaLM is Google’s transformer-based large language model. It can perform various tasks, including:

Commonsense and arithmetic reasoning, Explaining jokes, Generating codes

Predictive AI - Predictive AI is a method of analyzing data using statistical algorithms to predict upcoming outcomes.

Prompt - A prompt is a human user’s input to an AI system, which will generate an output or result.

Prompt engineering - Prompt engineering is the process of crafting and refining prompts for a generative AI model. AI users utilize prompt engineering to improve the output from the AI model.

Reinforcement learning - Reinforcement learning is a machine learning training method based on feedback. An AI agent learns how to behave in an environment through the feedback it receives: It gets positive feedback for every desired behavior and a penalty for every unwanted behavior.

Reinforcement learning from human feedback (RLHF) - Reinforcement learning from human feedback (RLHF) is a tactic that trains AI models with direct human feedback. Instead of getting a reward or punishment, the AI models get feedback from humans, typically in the form of ranking the models’ behaviors.

Speech recognition - See automatic speech recognition.

Supervised learning - Supervised learning is a subset of machine learning. It uses a pair of input-output data with labels to train algorithms. For example, supervised learning algorithms can train an image-recognition model by pairing an image of a dog and labeling it as a dog so it can identify a dog from a photo.

Synthetic data - Synthetic data is data generated by a computer to replace real-world data. Why would this be done? To protect sensitive data, reduce bias, and enhance AI models.

Transformer - A transformer is a deep learning model type for natural language processing. It can process the context of words in a sentence and produce an output based on a sequence of data throughout a conversation.

Turing test - The Turing test is an evaluation method that determines if a computer can think like a human. Developed by Alan Turing in 1950, the test involves a human evaluator who analyzes a conversation between a human and a machine. If the evaluator can’t differentiate between the computer and human, the machine passes the test.

Glossary

Black box AI - A black box AI is an AI system that doesn’t show how it operates and processes user input. After you provide a black box AI input, it will produce an output. However, you cannot view its code and analyze its logic for producing such results.

OpenAI - Open AI is a private American AI research lab established in 2015. It has developed and launched several AI models, including GPT-4, ChatGPT, CLIP, and DALL-E.

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