---
type: concept
x-llmwiki:
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  contentHash: c9181de7d697fb50310a749bbf8ba33b88834a120ee78a036cd86b9b8aa0a13c
  pageDirectory: concepts
  sources:
    - ai-runtime-example-notebooks-databricks-on-aws.md
  confidence: 0.9
  provenanceState: extracted
  freshnessStatus: unverified
  aliases:
    - computer-vision-on-databricks-ai-runtime
    - CVODAR
    - Computer Vision on AI Runtime
  citations:
    - file: ai-runtime-example-notebooks-databricks-on-aws.md
title: Computer Vision on Databricks AI Runtime
description: Capabilities for computer vision tasks such as object detection and image classification using GPU-accelerated AI Runtime notebooks.
tags:
  - computer-vision
  - deep-learning
  - databricks
timestamp: "2026-06-18T10:44:38.931Z"
---

# Computer Vision on Databricks AI Runtime

Databricks AI Runtime provides pre-configured environments and example notebooks for computer vision tasks, including object detection and image classification. These examples demonstrate how to leverage GPU-accelerated training and inference within the Databricks platform. ^[ai-runtime-example-notebooks-databricks-on-aws.md]

## Availability and preview status

AI Runtime for single-node computer vision tasks is in **Public Preview**. The distributed training API for multi-GPU computer vision workloads remains in **Beta**. Users should refer to the Databricks release notes for the latest status. ^[ai-runtime-example-notebooks-databricks-on-aws.md]

## Example notebooks

The computer vision example notebooks cover:

- **Object detection** – training and evaluating models that identify and localize objects within images.
- **Image classification** – classifying images into predefined categories using deep learning approaches.

These notebooks are part of a broader collection of AI Runtime examples that also cover large language models (LLMs), recommender systems, classic ML, and multi-GPU distributed training. ^[ai-runtime-example-notebooks-databricks-on-aws.md]

## Related concepts

- [AI Runtime](/concepts/ai-runtime.md) – the underlying runtime environment for ML workloads
- Object Detection – a computer vision task supported by the examples
- Image Classification – another common computer vision task
- GPU Computing – hardware acceleration used in the examples
- Deep Learning – the model architecture paradigm used

## Sources

- ai-runtime-example-notebooks-databricks-on-aws.md

# Citations

1. [ai-runtime-example-notebooks-databricks-on-aws.md](/references/ai-runtime-example-notebooks-databricks-on-aws-09849715.md)
