What role will SQL play in the development and deployment of AI and ML?

SQL will play a vital role in the development and deployment of artificial intelligence (AI) and machine learning (ML) applications. Here are some of the ways that SQL will be used in AI and ML:

Data preparation: SQL will be used to prepare the training data for AI and ML models. This will involve cleaning the data, removing outliers, and transforming the data into a format that is compatible with the AI or ML algorithm.
Model training: SQL can be used to train AI and ML models by providing the models with access to the training data. This can be done by using SQL queries to extract data from the database and feed it to the models.
Model deployment: SQL can be used to deploy AI and ML models by making the models available to applications. This can be done by using SQL to store the models in the database or by using SQL to create a REST API that exposes the models to applications.
Model monitoring: SQL can be used to monitor the performance of AI and ML models in production. This can be done by using SQL queries to extract data from the database about the models' predictions and accuracy.
In addition to these specific uses, SQL will also play a general role in supporting the development and deployment of AI and ML applications. For example, SQL can be used to manage the data pipelines that feed data to AI and ML models. SQL can also be used to build dashboards and reports that help developers and operators understand how AI and ML models are performing.

Here are some specific examples of how SQL is being used in AI and ML applications:

Google Search: Google Search uses SQL to train its ranking algorithm. The algorithm is trained on a massive dataset of web pages and user data. SQL is used to extract the data from the database and feed it to the algorithm.
Netflix: Netflix uses SQL to recommend movies and TV shows to its users. The recommendation system is trained on a dataset of user viewing history and ratings. SQL is used to extract the data from the database and feed it to the system.
Amazon: Amazon uses SQL to train its product recommendation system. The system is trained on a dataset of customer purchase history and product reviews. SQL is used to extract the data from the database and feed it to the system.
Overall, SQL is a powerful and versatile language that can play a vital role in the development and deployment of AI and ML applications. SQL vendors are constantly adding new features to SQL to make it even more powerful and flexible for AI and ML workloads.