Glossary

Foundation models are large AI systems trained on massive data, reused for writing, coding, or analysis, saving time and improving efficiency.

Latency in AI refers to the time between input and model response, impacting user experience, real-time performance, and overall system efficiency.

Model serving is the process of making AI models operational, providing real-time predictions, scalability, and high availability for modern applications.

Benchmarking measures AI model performance using standardized datasets and metrics to improve accuracy, scalability, and fairness across systems.