Vertex AI, AI Platform, and Accelerators

Question 1

AI Platform Data Labeling

Answer 1

AI Platform Data Labeling is a service that helps developers obtain high quality data to train and evaluate their machine learning models. It supports labeling for image, video, text, and audio as well as management of all of your labeled data in one place.

Question 2

AI Platform Deep Learning Container

Answer 2

AI Platform Deep Learning Container is a Docker image with the most popular AI frameworks. Machine learning developers and data scientists can customize AI Platform Deep Learning Container and use it with Notebooks, Google Kubernetes Engine (GKE), Vertex AI, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.

Question 3

AI Platform Neural Architecture Search (NAS)

Answer 3

NAS is a managed service leveraging Google’s neural architecture search technology to generate, evaluate, and train numerous model architectures for a customer’s application. NAS training services facilitate management of large-scale experiments.

Question 4

AI Platform Training and Prediction

Answer 4

AI Platform Training and Prediction is a managed service that enables you to easily build and use machine learning models. It provides scalable training and prediction services that work on large scale datasets.

Question 5

Notebooks

Answer 5

Notebooks is a managed service that offers an integrated JupyterLab environment in which machine learning developers and data scientists can create instances running JupyterLab that come pre-installed with the latest data science and machine learning frameworks in a single click.

Question 6

Vertex AI

Answer 6

Vertex AI is a service for managing the entire lifecycle of AI and machine learning development. With Vertex AI, you can (i) manage image, video, text, and tabular datasets and associated labels; (ii) build machine learning pipelines to train and evaluate models using Google Cloud algorithms or custom training code; (iii) deploy models for online or batch use cases all on scalable managed infrastructure (including additional discovery points and API endpoints for functionality replacing the legacy services of AI Platform Data Labeling, AI Platform Training and Prediction, AI Platform Neutral Architecture Search (NAS), AutoML Natural Language, AutoML Video, AutoML Vision, and AutoML Tables); (iv) manage your entire data science workflow using Vertex AI Workbench; and (v) create realistic plans to optimize your business with Optimization AI and related functionality.