Overhead
Overhead is the extra compute, memory, or time an AI system needs beyond the core task.
Edge AI
Edge AI is running AI models directly on local devices rather than in the cloud, for…
Federated Learning
Federated Learning is training models across many devices without moving raw data off them, preserving privacy.
MLOps
MLOps is the practices and tools for deploying, monitoring, and maintaining machine learning models in production.
Model Drift
Model Drift is the gradual decline in a model's accuracy as real-world data changes over time.
Vector Database
Vector Database is a database that stores embeddings and retrieves the most similar items quickly, often…
Inference
Inference is the stage where a trained model is used to make predictions or generate output…
Latency
Latency is the time it takes for an AI system to return a result after receiving…
GPU
GPU is a graphics processing unit, hardware widely used to train and run AI models because…
TPU
TPU is a tensor processing unit, custom hardware designed by Google to accelerate machine learning workloads.
API
API is an application programming interface that lets software send input to an AI model and…
Quantization
Quantization is reducing the numerical precision of a model to make it smaller and faster with…