Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
robotics
explainable-robotics
A field of study focused on making robotic systems understandable and transparent to users.
Data Analysis
exploratory-data-analysis
An approach to analyzing data sets to summarize their main characteristics.
Safety
faithfulness
faithfulness is a core generative-AI concept used across modeling, product, and governance discussions.
Data Processing
feature-extraction
The process of transforming raw data into a set of usable characteristics for model training.
Data Processing
feature-selection
The process of selecting a subset of relevant features for model training.
Machine Learning
Federated Learning
A machine learning approach that allows models to be trained across decentralized devices or servers holding local data samples.
Machine Learning
few-shot-learning
A machine learning paradigm that trains models with very few labeled examples.
Machine Learning
fine-tuning
The process of adjusting a pre-trained model on a new, often smaller dataset to improve performance on a specific task.
Training
fine-tuning dataset
fine-tuning dataset is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
flash attention
flash attention is a core generative-AI concept used across modeling, product, and governance discussions.
Product
full fine-tune
full fine-tune is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
function calling
function calling is a core generative-AI concept used across modeling, product, and governance discussions.
Artificial Intelligence
Generative AI
AI systems that can create new content, such as text, images, or music.
Machine Learning
Generative Modeling
A type of modeling that generates new data instances that resemble the training data.
Deep Learning
generative-adversarial-networks
A class of machine learning frameworks that generate new data samples via adversarial training.
machine-learning
generative-models
Models that can generate new data instances similar to the training data.
Data
GGUF
GGUF is a core generative-AI concept used across modeling, product, and governance discussions.
Data
grounding
grounding is a core generative-AI concept used across modeling, product, and governance discussions.
Product
GSM8K
GSM8K is a core generative-AI concept used across modeling, product, and governance discussions.
Data
guardrails
guardrails is a core generative-AI concept used across modeling, product, and governance discussions.
Safety
HNSW
HNSW is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
HumanEval
HumanEval is a core generative-AI concept used across modeling, product, and governance discussions.
Machine Learning
Hyperparameter Tuning
The process of optimizing the parameters that govern the training process of a machine learning model.
Machine Learning
Hyperparameters
Settings or configurations that govern the training process of a machine learning model.