Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Disaster Recovery
recovery-point-objective
A metric that defines the maximum acceptable amount of data loss measured in time for a system after a failure.
Model Evaluation
Robustness
The ability of a model to maintain performance despite variations in input data or conditions.
reinforcement-learning
safe-exploration
A strategy in reinforcement learning that aims to balance exploration and exploitation while minimizing risks.
Models
Sarvam 105B
Sarvam 105B is Sarvam AI's flagship open-weight 105B+ MoE reasoning model for Indian-language chat, coding, long-context work, and agents.
AI platforms
Sarvam AI
Sarvam AI is an India-based sovereign AI platform focused on Indian-language LLMs, speech, translation, document digitization, and enterprise AI agents.
Machine Learning
semi-supervised-learning
A learning approach that combines labeled and unlabeled data for training models.
Development
Structured Outputs
Structured Outputs constrain model responses to match a developer-supplied schema, typically for reliable JSON or function-call arguments.
Data Science
synthetic-data-generation
The process of creating artificial data that mimics real-world data for training machine learning models.
Machine Learning
Unsupervised Learning
A type of machine learning that deals with data that has no labels, aiming to find hidden patterns or intrinsic structures.
Model Evaluation
Variance
Variance measures a model's sensitivity to fluctuations in the training data, contributing to overfitting when high.
Machine Learning
Zero-shot Learning
A machine learning approach where the model predicts classes that it has not seen during training.