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Find an AI concept.
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AI Agent Oversight
Human control over agent goals, tool permissions, execution and outcomes, including meaningful reviews and recovery from failures.
AI Alignment
Research and design for relating AI behavior to human intentions, values and constraints, including reward proxies, feedback and operational evaluation.
Anthropic
An AI company that develops the Claude model and product family and conducts AI safety research.
BERT
Bidirectional Encoder Representations from Transformers, an encoder-based language representation model.
Claude
A family of general-purpose AI models and conversational products developed by Anthropic.
Data Provenance
Information about where data came from, how it was collected, and how it changed before use.
Datasheets for Datasets
A documentation framework for describing how datasets were created, composed, maintained, and intended to be used.
Foundation Model
A broadly trained model that can be adapted to many downstream tasks and applications.
GPU
A highly parallel processor widely used to train and run modern machine-learning models.
Gemini
A family of multimodal AI models and products developed by Google.
Google DeepMind
Google's AI research organization, formed from the combination of DeepMind and Google Brain teams.
HELM
Holistic Evaluation of Language Models, a framework for evaluating models across scenarios and metrics.
Large Language Model (LLM)
A general-purpose language model trained on large datasets and usually built at substantial scale.
MMLU
Massive Multitask Language Understanding, a benchmark covering many academic and professional subject areas.
Mixture of Experts (MoE)
A model architecture that routes each input to a subset of specialized parameter blocks called experts.
Model Card
A structured document that describes a model's intended use, evaluation, limitations, and other important context.
OpenAI
An artificial intelligence research and deployment organization known for GPT models and ChatGPT.
Red Teaming
Adversarial testing intended to discover failure modes, unsafe behavior, or exploitable weaknesses in an AI system.
Safety Evaluation
Testing designed to measure risks, harmful behaviors, and the effectiveness of safeguards in an AI system.
Sovereign AI
Control over AI data, infrastructure, models and operational capabilities, examined separately from data location and supplier branding.
System Card
Documentation describing a deployed AI system, including capabilities, evaluations, mitigations, and limitations.
Tensor Processing Unit (TPU)
Google's specialized machine-learning accelerator, explained through matrix computation, software compatibility and workload-level evaluation.