Model architecture
Defines how information is represented, learned, transformed, and generated.
Seven Layers · Layer 5
AI Infrastructure
About this section
AI infrastructure is the software and operational layer that makes models usable at scale. It moves data into training systems, schedules computation, deploys models, connects them to applications, observes their behavior, controls access, and keeps cost and latency within practical limits.
Models create capability. Infrastructure turns that capability into a dependable, measurable, and economical system.
This layer sits between model architecture and hardware. Architecture defines the computational design of a model. Hardware supplies processors, memory, networking, storage, and physical facilities. Infrastructure coordinates those resources and exposes them to developers, companies, and end users.
AI infrastructure
Trains, deploys, serves, evaluates, secures, and operates models.
AI hardware
Provides the physical compute, memory, networks, storage, power, and cooling.
AI application
Uses model capabilities and infrastructure to deliver a customer outcome.