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Find an AI concept.
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AI Agent
An AI system that selects and executes actions over multiple steps to pursue a goal.
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.
AI Memory
Stored conversation state, preferences and task records, distinguished from context windows and model training, with examples of freshness and access boundaries.
AI for Science
AI-assisted scientific prediction and candidate selection, with attention to experimental validation, data leakage and the scope of automated research.
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.
ChatGPT
A conversational AI product from OpenAI that provides natural-language interaction with AI models.
ChatGPT Work
A task environment for creating deliverables with available files and tools, explained through clear goals, access boundaries and reviewable outputs.
Context Window
The amount of tokenized input and generated text a model can consider within one inference context.
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.
Embedding
A numerical vector representation used to encode semantic or structural properties of data.
Fine-tuning
Additional training that adapts a pre-trained model to a narrower task, domain, or behavior.
Foundation Model
A broadly trained model that can be adapted to many downstream tasks and applications.
GPT
Generative Pre-trained Transformer, a family of autoregressive language models associated with OpenAI.
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.
HELM
Holistic Evaluation of Language Models, a framework for evaluating models across scenarios and metrics.
Hallucination in AI
A generated statement that is unsupported, fabricated, or inconsistent with the available evidence or context.
Inference
The process of running a trained model on new input to produce predictions, embeddings, or generated output.
KV Cache
A cache of attention keys and values used to avoid recomputing earlier context during autoregressive generation.
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.
Mistral AI
An AI company providing models and inference services, with a guide to model-specific licenses, hosted versus self-operated deployment and task-level comparison.
Model Card
A structured document that describes a model's intended use, evaluation, limitations, and other important context.
Quantization
A technique that represents model weights or activations with lower numerical precision to reduce resource use.
Red Teaming
Adversarial testing intended to discover failure modes, unsafe behavior, or exploitable weaknesses in an AI system.
Retrieval-Augmented Generation (RAG)
A method that retrieves external information and supplies it to a generative model as context.
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.
Tokenization
The process of converting text or other input into discrete units that a model can process.
Transformer
A neural network architecture that processes sequences primarily through attention mechanisms.
Vector Search
Search that retrieves items by similarity between numerical vector representations.