model deployment

MLOps

MLOps combines machine learning and software operations to deploy, monitor, update, and govern models reliably in production.

Jun 16, 2026 by Marcus Lee • 1 min read

YAML

YAML is a human-readable configuration format used in machine learning pipelines, model experiments, deployments, and AI automation workflows.

Jun 11, 2026 by Marcus Lee • 1 min read

RunPod

RunPod is a notable gpu cloud and serverless ai compute company mentioned in 2026 AI technology coverage across AI infrastructure, cloud compute, model deployment, and developer infrastructure.

Jun 9, 2026 by AIstify Team • 4 mins read

Baseten

By AIstify Team Jun 9, 2026 • 4 mins read

Baseten is a notable ai model deployment and inference company mentioned in 2026 AI technology coverage across AI infrastructure, cloud compute, model deployment, and developer infrastructure.

LLMOps

By Marcus Lee Jun 8, 2026 • 1 min read

LLMOps is the discipline of developing, deploying, evaluating, monitoring, and maintaining applications built around large language models.

Checkpoint

By Ethan Caldwell Mar 7, 2026 • 1 min read

A checkpoint is a saved snapshot of model parameters and training state that can be restored or deployed later.

Inference

By Daniel Mercer Mar 5, 2026 • 1 min read

Inference is the process in which a trained AI model applies learned patterns to new input and produces a prediction, decision, or generated response.