Federated Learning

AI Bias

Systematic errors in AI outputs that arise from biased training data, flawed assumptions, or prejudicial algorithm design.

Causal Inference

The process of determining cause-and-effect relationships from data, going beyond correlation to establish causation.

AI Feature Store

A centralised platform for storing, managing, and serving machine learning features consistently across training and inference.

AI Inference

The process of using a trained AI model to make predictions or decisions on new, unseen data.

AI Training

The process of teaching an AI model to recognise patterns by exposing it to large datasets and adjusting its parameters.

Hyperparameter Tuning

The process of optimising the external configuration settings of a machine learning model that are not learned during training.

AutoML

Automated machine learning that automates the end-to-end process of applying machine learning to real-world problems.

Reinforcement Learning from Human Feedback

A training paradigm where AI models are refined using human preference signals, aligning model outputs with human values and quality expectations through reward modelling.

Direct Preference Optimisation

A simplified alternative to RLHF that directly optimises language model policies using preference data without requiring a separate reward model.

Model Merging

Techniques for combining the weights and capabilities of multiple fine-tuned models into a single model without additional training, creating versatile multi-capability systems.

The economic model governing the pricing and allocation of computational resources for AI inference, including per-token billing, rate limiting, and credit systems.

The simulation of human intelligence processes by computer systems, including learning, reasoning, and self-correction.

A technique where a language model is given a small number of examples within the prompt to guide its response pattern.

Google's custom-designed application-specific integrated circuit for accelerating machine learning workloads.

An initial instruction set provided to a language model that defines its persona, constraints, output format, and behavioural guidelines for a given session or application.

An inference acceleration technique where a small draft model generates candidate token sequences that are verified in parallel by the larger target model.

An AI program that emulates the decision-making ability of a human expert by using a knowledge base and inference rules.

An AI algorithm that generates a sequence of actions to achieve a specified goal from an initial state.

Machine Learning

A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed.