GCP artificial intelligence services
The AI services in Google Cloud are some of its best services. Google Cloud’s AI services include the following:
- BigQuery ML (BQML)
- TensorFlow and Keras
- Google Vertex AI
- Google ML API
Google BQML is built from Google Cloud BQ, which serves as a serverless big data warehouse and analytical platform. BQML trains ML models from the datasets already stored in BQ, using SQL-based languages. TensorFlow introduces the concepts of tensors and provides a framework for ML development, whereas Keras provides a high-level structure using TensorFlow. We will discuss BQML, TensorFlow, and Keras in more detail in part three of this book, along with Google Cloud Vertex AI and the Google Cloud ML API, which we will briefly introduce next.
Google Vertex AI
Google Vertex AI (https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform) aims to provide a fully managed, scalable, secure, enterprise-level ML development infrastructure. Within the Vertex AI environment, data scientists can complete all of their ML projects from end to end: data preparation and feature engineering; model training, validation, and tuning; model deployment and monitoring, and so on. It provides a unified API, client library, and user interface.
Vertex AI provides end-to-end ML services, including, but not limited to, the following:
- Vertex AI data labeling and dataset
- Vertex AI Feature Store
- Vertex AI Workbench and notebooks
- Vertex AI training
- Vertex AI models and endpoints
- Vertex AI Pipelines
- Vertex AI Metadata
- Vertex AI Experiments and TensorBoard
We will examine each of these in detail in the third part of this book.
Google Cloud ML APIs
Google Cloud ML APIs provide application interfaces to customers with Google’s pre-trained ML models, which are trained with Google’s data. The following are a few AI APIs:
- Google Cloud sight APIs, which include the Google Cloud Vision API and Cloud Video API. The pre-trained models of the sight APIs use ML to understand your images with industry-leading prediction accuracy. They can be used to detect objects/faces/scenes, read handwriting, and build valuable image/video metadata.
- Google Cloud language APIs, which includes the Natural Language Processing API and Translation API. These powerful pre-trained models of the Language API empower developers to easily apply natural language understanding (NLU) to their applications, alongside features such as sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis. The Translation API allows you to detect a language and translate it into the target language.
- Google Cloud conversation APIs, which include the Speech-to-Text, Text-to-Speech, and Dialogflow APIs. The pre-trained models of the Conversation APIs accurately convert speech into text, text into speech, and enable developers to develop business applications for call centers, online voice ordering systems, and so on using Google’s cutting-edge AI technologies.
AI is the ability of a computer (or a robot controlled by a computer) to perform tasks that are usually done by humans because they require human intelligence. In the history of human beings, from vision development (related to the Cambrian explosion) to language development, to tool development, a fundamental question is, how did we humans evolve and how can we teach a computer to learn to see, speak, and use tools? The GCP AI service spectrum includes vision services(image recognition, detection, segmentation, and so on), language services(text, speech, translation, and so on), and many more. We will learn more about these services later in this book. We are certain that many more AI services, including hand detection tools, will be added to the spectrum in the future.
