Alignment (Alignment)
Alignment
The process of ensuring that an AI system's objectives, outputs, and behaviours align with human goals and values. This is especially important in advanced systems that may develop behaviours not explicitly intended.
Example: Ensuring a chatbot for mental health support never recommends harmful actions regardless of prompts.
Application Programming Interface (API) (Application Programming Interface (API))
Application Programming Interface (API)
A set of defined rules and protocols that allow different software systems to communicate and exchange data.
Example: Using the OpenAI API to send a prompt and receive a language model-generated response in your web app.
Artificial General Intelligence (AGI) (Artificial General Intelligence (AGI))
Artificial General Intelligence (AGI)
A theoretical form of AI that can perform any intellectual task that a human being can. It generalises learning across domains.
Example: An AGI system could learn music composition, perform surgery, and pass a philosophy exam without task-specific programming.
Artificial Intelligence (AI) (Artificial Intelligence (AI))
Artificial Intelligence (AI)
The simulation of human intelligence in machines that are programmed to think, reason, and act autonomously.
Example: AI powers personal assistants like Siri and autonomous driving systems like Tesla Autopilot.
AI Ethics (AI Ethics)
AI Ethics
A discipline concerned with the moral implications of AI development and use, including fairness, privacy, accountability, and non-discrimination.
Example: Creating guidelines to prevent hiring algorithms from discriminating based on gender or ethnicity.
Augmented Intelligence (Augmented Intelligence)
Augmented Intelligence
A collaborative model where AI complements and enhances human intelligence rather than replacing it.
Example: AI-powered radiology tools that highlight anomalies for doctors, who make the final diagnosis.
Autonomous Agent (Autonomous Agent)
Autonomous Agent
An AI system capable of making its own decisions and taking actions to achieve its goals without human intervention.
Example: A self-driving delivery robot navigating city streets and avoiding obstacles independently.
Backpropagation (Backpropagation)
Backpropagation
A technique for training neural networks by updating weights in reverse from output to input layers, minimising prediction errors.
Example: Used in training image classifiers to reduce the error rate in recognising handwritten digits.
Bias (Algorithmic Bias) (Bias (Algorithmic Bias))
Bias (Algorithmic Bias)
Unintended and systematic favouritism in AI outcomes due to imbalanced or non-representative training data.
Example: A facial recognition system that misidentifies people of colour more frequently due to underrepresentation in training data.
Big Data (Big Data)
Big Data
Extremely large datasets that require special tools to store, analyse, and extract value, often used to train AI models.
Example: Using millions of user interactions to train recommendation engines for e-commerce platforms.
Black Box Model (Black Box Model)
Black Box Model
A type of AI or machine learning model whose internal logic is not easily interpretable by humans, making it difficult to understand how decisions are made.
Example: A deep neural network used to approve loans but offering no clear explanation for why one applicant was accepted and another rejected.
Cognitive Computing (Cognitive Computing)
Cognitive Computing
AI systems designed to simulate human thought processes, such as reasoning and learning, using techniques like NLP and pattern recognition.
Example: A cognitive computing system that helps legal professionals analyse case law and predict outcomes.
Computer Vision (Computer Vision)
Computer Vision
A field of artificial intelligence that enables computers to interpret and process visual data such as images and video.
Example: Facial recognition systems that identify people in security footage using computer vision.
Corpus (Corpus)
Corpus
A large collection of written or spoken texts used to train language models.
Example: The Common Crawl dataset is a public web corpus used to train large language models like GPT.
Data Drift (Data Drift)
Data Drift
The phenomenon where input data changes over time, causing model performance to degrade.
Example: A predictive maintenance model for industrial equipment becomes less accurate as new sensor technology is introduced.
Data Labelling (Data Labelling)
Data Labelling
The process of annotating data with tags or labels to make it suitable for supervised learning.
Example: Labelling thousands of tumour images as benign or malignant to train a cancer detection model.
Data Mining (Data Mining)
Data Mining
The process of discovering meaningful patterns, correlations, and anomalies in large datasets.
Example: Retailers using data mining to identify that people who buy nappies often buy beer as well.
Deep Learning (Deep Learning)
Deep Learning
A subfield of machine learning that uses multi-layered neural networks to model complex patterns in data.
Example: Deep learning is used in language models like GPT-4 and image generation models like Stable Diffusion.
Diffusion Models (Diffusion Models)
Diffusion Models
A class of generative models that learn to produce data by gradually transforming random noise into structured outputs.
Example: Stable Diffusion creates photorealistic images from text prompts using diffusion techniques.
Embedding (Embedding)
Embedding
A numerical vector representation of data, often used to capture the semantic meaning of words, images, or sentences.
Example: In NLP, the word 'bank' may have similar embeddings to 'money' but different from 'riverbank' depending on context.
Epoch (Epoch)
Epoch
A full iteration over the entire training dataset during the training process of a machine learning model.
Example: If a dataset has 1,000 examples and a model sees all of them once during training, that's one epoch.
Ethical AI (Ethical AI)
Ethical AI
A design and deployment philosophy that ensures AI technologies operate transparently, equitably, and in line with societal values.
Example: An AI hiring tool that includes bias checks to prevent discrimination against minority candidates.
Expert System (Expert System)
Expert System
An AI system that mimics the decision-making abilities of a human expert in a specific domain using rules and logic.
Example: An expert system used in agriculture to recommend crop treatments based on soil data and pest history.
Explainable AI (XAI) (Explainable AI (XAI))
Explainable AI (XAI)
AI systems designed to make their internal processes and decisions understandable to humans, increasing trust and accountability.
Example: A medical diagnostic AI that not only provides a recommendation but also explains which symptoms led to that conclusion.
Few-shot Learning (Few-shot Learning)
Few-shot Learning
A machine learning method where a model is trained or fine-tuned using only a small number of labelled examples.
Example: Customising an LLM to write legal emails after showing it just 10 examples.
Fine-tuning (Fine-tuning)
Fine-tuning
The process of taking a pre-trained model and further training it on a new, smaller dataset to specialise it for a specific task.
Example: Fine-tuning a general LLM like GPT on internal legal documents to create a legal drafting assistant.
Foundation Model (Foundation Model)
Foundation Model
A large-scale model trained on diverse and broad data that can be adapted to many downstream tasks.
Example: GPT-4 and PaLM 2 are foundation models capable of summarisation, Q&A, translation, and more.
Fuzzy Logic (Fuzzy Logic)
Fuzzy Logic
A form of logic that deals with approximate values instead of fixed true/false (binary) logic, useful for reasoning under uncertainty.
Example: Used in climate control systems to adjust temperature based on fuzzy inputs like 'a bit hot' or 'very cold'.
Generative Adversarial Network (GAN) (Generative Adversarial Network (GAN))
Generative Adversarial Network (GAN)
A generative model architecture where two networks — a generator and a discriminator — compete to improve output quality.
Example: GANs are used to create deepfake videos or generate realistic product photos from sketches.
Generative AI (Generative AI)
Generative AI
A category of artificial intelligence that can create new content — such as text, images, music, or video — from training data.
Example: ChatGPT generating blog posts or Midjourney creating digital artwork from textual prompts.
Generative Pre-trained Transformer (GPT) (Generative Pre-trained Transformer (GPT))
Generative Pre-trained Transformer (GPT)
A class of large language models developed by OpenAI that uses transformer architecture and is pre-trained on vast amounts of text data to perform a variety of language tasks.
Example: GPT-4 is capable of writing essays, translating languages, and summarising documents with minimal prompting.
Genetic Algorithm (Genetic Algorithm)
Genetic Algorithm
An optimisation technique inspired by natural selection where solutions evolve over time through mutation, crossover, and selection.
Example: Used to design efficient neural network architectures by simulating survival of the fittest.
Hallucination (Hallucination)
Hallucination
The generation of plausible-sounding but factually incorrect or nonsensical content by an AI model.
Example: A language model invents a non-existent citation or provides false historical facts.
Heuristic (Heuristic)
Heuristic
A practical approach to problem-solving that doesn't guarantee a perfect solution but is sufficient for immediate goals.
Example: Using a rule of thumb to estimate delivery time in a logistics AI system.
Hyperparameter (Hyperparameter)
Hyperparameter
A configuration value set before training a machine learning model, such as learning rate or number of layers.
Example: Adjusting the batch size from 32 to 128 to improve training speed and model performance.
Inference (Inference)
Inference
The process of using a trained machine learning model to make predictions or generate outputs from new input data.
Example: Using a fine-tuned GPT model to draft emails for a customer support team.
Intent Detection (Intent Detection)
Intent Detection
A task in natural language understanding where the system identifies the user’s goal or purpose in a message.
Example: In a chatbot, recognising 'I want to book a flight' as a travel booking intent.
Internet of Things (IoT) (Internet of Things (IoT))
Internet of Things (IoT)
A network of interconnected physical devices embedded with sensors, software, and other technologies to collect and exchange data.
Example: Smart thermostats and fridges that report usage data and adjust settings using AI analytics.
Interpretability (Interpretability)
Interpretability
The extent to which a human can understand the internal mechanics of a machine learning model and its decision-making process.
Example: A decision tree is more interpretable than a deep neural network because its decisions are traceable.
Jupyter Notebook (Jupyter Notebook)
Jupyter Notebook
An open-source interactive computing environment that allows users to write code, visualise outputs, and document analysis in a single interface.
Example: Data scientists use Jupyter Notebooks to prototype machine learning models and share results.
K-Nearest Neighbours (KNN) (K-Nearest Neighbours (KNN))
K-Nearest Neighbours (KNN)
A simple, non-parametric machine learning algorithm used for classification and regression. It makes decisions based on the closest training examples in the feature space.
Example: To classify a new fruit as an apple or pear, KNN checks which labelled fruits are closest in shape and colour.
Knowledge Graph (Knowledge Graph)
Knowledge Graph
A data structure that uses nodes and edges to represent and store interlinked descriptions of entities and their relationships.
Example: Google's knowledge panel is powered by a knowledge graph that connects entities like people, places, and events.
Language Learning Model Optimisation (LLMO) (Language Learning Model Optimisation (LLMO))
Language Learning Model Optimisation (LLMO)
Techniques used to improve the performance, efficiency, or adaptability of large language models for specific tasks or domains.
Example: Using quantisation and instruction tuning to optimise an LLM for enterprise use.
Large Language Model (LLM) (Large Language Model (LLM))
Large Language Model (LLM)
A type of deep learning model trained on vast amounts of textual data capable of generating, understanding, and reasoning with human language.
Example: ChatGPT and Claude are LLMs trained to assist in writing, coding, and answering questions.
Latent Space (Latent Space)
Latent Space
A high-dimensional abstract representation where similar inputs are grouped close together, used in generative models and embeddings.
Example: In image generation, manipulating the latent space can change features like brightness or emotion.
Learning Rate (Learning Rate)
Learning Rate
A key hyperparameter in training that controls how much model weights are adjusted with respect to the loss gradient.
Example: A high learning rate may lead to overshooting minima, while too low a rate slows training progress.
Machine Learning (ML) (Machine Learning (ML))
Machine Learning (ML)
A branch of AI that enables systems to learn from data and improve performance without being explicitly programmed.
Example: Spam filters use machine learning to classify emails as spam or not based on past examples.
Model Drift (Model Drift)
Model Drift
A phenomenon where the accuracy of a model declines over time due to changes in data or environment.
Example: A fraud detection model becomes less accurate as fraud tactics evolve.
Model Training (Model Training)
Model Training
The process of feeding data to a machine learning model and adjusting its parameters to minimise error.
Example: Training a recommendation engine on customer purchase history to suggest new products.
Multimodal AI (Multimodal AI)
Multimodal AI
AI systems capable of processing and integrating multiple types of data such as text, images, audio, and video.
Example: A model like GPT-4 Vision that can read text and interpret images at the same time.
Natural Language Processing (NLP) (Natural Language Processing (NLP))
Natural Language Processing (NLP)
A subfield of AI focused on the interaction between computers and human (natural) languages. It enables machines to read, understand, and respond in human language.
Example: NLP is used in voice assistants, language translation apps, and chatbots.
Neural Network (Neural Network)
Neural Network
A machine learning model inspired by the structure of the human brain, composed of layers of interconnected nodes (neurons).
Example: Neural networks are behind deep learning models used in image and speech recognition.
Noise (Noise)
Noise
Random or irrelevant information in data that can obscure meaningful patterns and negatively affect model performance.
Example: Sensor errors or typo-filled data entries can be considered noise.
Ontology (Ontology)
Ontology
A structured framework that categorises and defines relationships among concepts within a domain, often used in semantic AI systems.
Example: An ontology in healthcare might define how symptoms relate to diseases and treatments.
Overfitting (Overfitting)
Overfitting
A modelling error where a machine learning model captures noise in the training data and performs poorly on new data.
Example: A model that memorises training answers but can't handle unseen test data is overfitted.
Predictive Analytics
The use
