A retail startup wants to add automatic product image recognition to its mobile app within a few days. The team has no machine-learning engineers and prefers to call a simple REST endpoint instead of training or maintaining models. Which Google Cloud AI solution best meets these requirements?
Call the pre-trained Cloud Vision API to label the images.
Build and train a TensorFlow model on Vertex AI Training.
Create an image-classification model with BigQuery ML.
Use AutoML Vision to train a custom image-classification model.
The pre-trained Vision API exposes Google-trained image recognition models through a REST and RPC interface. It delivers labels, object detection, and other features without requiring users to build, train, or manage any models, making it ideal when speed and minimal expertise are priorities. AutoML Vision can work with custom data but still involves collecting data and running training jobs. Vertex AI custom training requires the most effort and ML expertise. BigQuery ML is focused on creating models from structured data using SQL and does not provide ready-made image recognition.
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