Training Artificial Intelligence Models with GCP GCS Data

GCP GCS

A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics. Google Cloud Storage (GCS) is a popular object storage service that can be used as a data lake. It provides a simple and cost-effective way to store, manage, and analyze large amounts of data. GCS is designed for very high durability and availability.

Artificial Intelligence Models

Artificial intelligence (AI) models are computer programs that can perform tasks that would normally require human intelligence to complete. AI models are popular because they can automate tasks that would otherwise require human intervention, such as image recognition, natural language processing, and decision making. AI models can also help businesses make better decisions by providing insights into customer behavior and business operations.

With the growing popularity of both GCP GCS for storage and artificial intelligence models for AI deployments, it is unsurprising that many organizations are seeking to train artificial intelligence models using data in GCP GCS. Kaspian offers native connectors for this operation. Just register your GCP GCS datastore and link your model training job; Kaspian's autoscaling compute layer makes it easy to train and deploy artificial intelligence models using any data in your cloud with minimal setup or management.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.