# AI Inference Guide — Agentic Design


## Overview

Core Concepts (6) · Overview · Model Advisor · Fundamentals · Non-Determinism · Interaction & APIs · Agentic Patterns · Planning & Deployment (5) · Optimization (4) · Tools & Services (2) · Operations & Practice (4)

## What is AI Inference?

AI inference is the process of using a trained ML model to make predictions or generate outputs from new input data. Unlike training, inference can be optimized for speed, efficiency, and deployment.

## Edge and Device Inference

- **Privacy** — Local execution reduces data sent to third parties
- **Cost profile** — Shift compute to user hardware
- **Low latency** — Avoid network round trips
- **Offline capable** — Work offline once models cached

## Key Technologies

- **WebGPU** — High-performance GPU acceleration in browsers
- **WebAssembly (WASM)** — Near-native CPU performance in browsers
- **Model quantization** — Trade model size against task quality
- **ONNX Runtime** — Cross-platform inference with hardware optimization