Are You Confused With AI Terminology?
This glossary provides clear, accessible definitions and examples of key terms used in the world of Generative AI, Frugal AI, and related computing fields. Our focus is on demystifying high-level technical concepts and the principles underpinning Frugal AI — from low-resource innovation to responsible deployment.
Glossary of Terms
Algorithm
Definition: A set of rules or steps used for solving a problem or performing a task, especially by a computer.
Example: A recommendation system uses a collaborative filtering algorithm to suggest movies.
API (Application Programming Interface)
Definition: A set of tools and definitions that allow software programs to communicate with each other.
Example: OpenAI provides an API that developers use to integrate ChatGPT into apps.
Artificial Intelligence (AI)
Definition: The simulation of human intelligence in machines that are programmed to think and learn.
Example: AI powers autonomous vehicles by processing sensor data and making decisions.
ASR (Automatic Speech Recognition)
Definition: A technology that converts spoken language into text using specialized audio processing models.
Example: Google Assistant uses ASR to convert your spoken query into text.
Bias (in AI)
Definition: Systematic errors in AI systems that result from flawed data, design, or assumptions, often leading to unfair outcomes.
Example: A facial recognition model performs poorly on darker-skinned individuals due to biased training data.
Big Data
Definition: Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations.
Example: Retailers analyze big data from loyalty cards to personalize offers.
Chatbot
Definition: A computer program designed to simulate conversation with human users.
Example: A bank’s chatbot answers FAQs about account services.
Cloud Computing
Definition: Delivery of computing services (like servers, storage, databases) over the internet.
Example: AWS cloud services host large-scale AI training models.
Compute Power
Definition: The processing capacity of a computer, often required in large quantities for AI tasks.
Example: Training GPT-4 requires thousands of GPUs running in parallel.
Dataset
Definition: A structured collection of data, often used to train or test machine learning models.
Example: ImageNet is a large dataset used to train computer vision models.
Deep Learning
Definition: A subset of machine learning involving neural networks with many layers.
Example: Deep learning models detect tumors from medical images.
Diffusion Models
Definition: A type of generative model used in AI to produce images, audio, and other content.
Example: DALL·E uses diffusion models to generate images from text prompts.
Embedding
Definition: A numerical representation of data (e.g., words, sentences) that captures semantic meaning.
Example: Word2Vec converts words into embeddings used for similarity detection.
Efficient AI
Definition: AI systems designed to minimize resource usage (compute, memory, energy) while delivering effective results.
Example: An optimized image classifier that runs on low-power edge devices.
Energy-Efficient AI
Definition: AI systems optimized to consume less energy, helping reduce environmental impact.
Example: A vision system in a smart thermostat using lightweight AI to reduce home energy use.
Ethical AI
Definition: The practice of designing AI technologies in ways that prioritize fairness, accountability, and transparency.
Example: An AI tool is audited to ensure it doesn’t discriminate against job applicants.
Fine-tuning
Definition: Adjusting a pre-trained AI model on a new, often smaller, dataset to perform specific tasks better.
Example: GPT-3 is fine-tuned on legal documents to draft contracts.
Foundation Model
Definition: A large AI model trained on broad data that can be adapted to many different tasks.
Example: GPT-4 is a foundation model that can be adapted for many tasks.
Frugal AI
Definition: An approach that maximizes environmental and societal impact with minimal resources, focusing on efficiency and cost-effectiveness. It emphasizes simplicity, affordability, sustainability, and accessibility.
Example: Using a small, locally hosted language model on a Raspberry Pi for offline healthcare in rural clinics.
Generative AI
Definition: A type of AI that can create new content (text, images, music, etc.) based on training data.
Example: Midjourney generates artwork based on short descriptions.
GPU (Graphics Processing Unit)
Definition: Hardware used to accelerate AI computations, especially for training models.
Example: NVIDIA’s GPUs are commonly used to train deep learning models.
Hallucination (in AI)
Definition: When an AI model generates plausible but incorrect or fabricated information.
Example: ChatGPT might say ‘Albert Einstein was born in 1950,’ which is a hallucination.
Hyperparameters
Definition: Configurable variables used to control the learning process in machine learning models.
Example: Changing the learning rate affects model training speed and accuracy.
Inference
Definition: The process of using a trained model to make predictions or generate outputs.
Example: An AI model classifies a photo of a dog during inference.
Input Prompt
Definition: The initial text or data given to a generative model to guide its output.
Example: Typing ‘write a poem about spring’ is an input prompt for ChatGPT.
Large Language Model (LLM)
Definition: A type of AI model trained on vast amounts of text to understand and generate human-like language.
Example: Claude and LLaMA are examples of large language models.
Latency
Definition: The delay between input and response time in computing systems.
Example: Low latency is important in AI-powered real-time video conferencing tools.
Machine Learning (ML)
Definition: A branch of AI focused on systems that learn from data to improve their performance over time.
Example: Spotify uses ML to generate Discover Weekly playlists.
Model Training
Definition: The process of teaching an AI model to make predictions or decisions based on data.
Example: A model is trained on labeled photos to recognize traffic signs.
Neural Network
Definition: A computing system inspired by the human brain’s structure, used in deep learning.
Example: Neural networks power handwriting recognition apps.
Natural Language Processing (NLP)
Definition: A field of AI that enables computers to understand and interpret human language.
Example: NLP helps AI understand customer service emails.
Open Source
Definition: Software whose source code is freely available and can be modified or shared.
Example: Hugging Face hosts open-source models for developers.
Optimization
Definition: The process of adjusting a model or algorithm to improve its performance.
Example: Optimizing a model can reduce energy usage and improve speed.
Parameter
Definition: A value within a model that the learning algorithm adjusts to fit the training data.
Example: Transformer models have billions of trainable parameters.
Pretraining
Definition: The initial phase of training a model on a large dataset before fine-tuning it for specific tasks.
Example: BERT was pretrained on Wikipedia before fine-tuning.
Reinforcement Learning
Definition: A machine learning approach where an agent learns by receiving rewards or penalties.
Example: Robots learn to walk using reinforcement learning.
Responsible AI
Definition: The practice of developing and deploying AI in a manner that is ethical and beneficial to society.
Example: A company publishes its AI ethics policy to ensure responsible AI.
Sustainable AI
Definition: AI technologies designed to have a minimal environmental footprint across their lifecycle.
Example: Using solar-powered edge devices to run crop monitoring AI models in the field.
Token
Definition: A unit of text (like a word or part of a word) used by language models during processing.
Example: The sentence ‘I love AI’ has 3 tokens.
Transformer
Definition: A deep learning model architecture that underlies most modern language models.
Example: Transformers are used in ChatGPT for language understanding.
Text-to-Speech (TTS)
Definition: Technology that converts written text into spoken voice.
Example: TTS allows visually impaired users to listen to webpages.
Vector Database
Definition: A type of database optimized for storing and retrieving vector representations (e.g., embeddings).
Example: Pinecone stores embeddings for fast semantic search.
Voice Synthesis
Definition: The creation of artificial speech using AI techniques.
Example: ElevenLabs creates realistic synthetic voices.
Workflow Automation
Definition: The use of technology to perform recurring tasks or processes with minimal human intervention.
Example: Zapier automates tasks like posting Slack messages.
Zero-shot Learning
Definition: The ability of an AI model to correctly make predictions on tasks it was not explicitly trained on.
Example: GPT-4 answers questions on topics it hasn’t seen before.