New services for developers and data scientists help customers apply AI to enterprise scenarios.
This week Oracle announced availability of Oracle Cloud Infrastructure (OCI) AI services. This is a collection of services that make it easier for developers to apply AI services to their applications. And it does so without requiring data science expertise.
The new OCI AI services give developers the choice of leveraging out-of-the-box models that have been pre-trained on business-oriented data. They can also choose to custom train the services based on their organization’s own data.
A suite of “pre-trained” service modules to make AI easy
There are six new services help developers with a variety of complex tasks. These range from language to computer vision, and time-series forecasts.
Firstly, OCI Language performs text analysis at scale to understand unstructured text in documents. It can also understand customer feedback interactions, support tickets, and social media.
Then there is OCI Speech, which provides automatic speech recognition through pre-built models trained on thousands of native and non-native language speakers for real-time speech recognition.
OCI Vision provides pre-trained computer vision models for image recognition and document analysis tasks. It also enables users to extend the models to other industry and customer-specific use cases. These include scene monitoring, defect detection, and document processing with their own data.
There is also something called OCI Anomaly Detection. This feature delivers business-specific anomaly detection models that flag critical irregularities early. This in turn enables faster resolution and less operational disruption.
Oracle also released OCI Forecasting. This delivers time-series forecasts through machine learning and statistical algorithms without the need for data science expertise.
The sixth service is OCI Data Labeling. This module helps users build labeled datasets to train AI models, according to Oracle. Users can assemble data, create and browse datasets, and apply labels to data records through user interfaces and public APIs.
“It’s essential for organizations to bridge the gap between the promise of AI and implementing AI that helps them achieve real results,” said Greg Pavlik, chief technology officer, Oracle Cloud Platform.
“Oracle is best positioned to realize the value of AI through our industry-leading expertise in enterprise applications and enterprise data, our next-generation cloud infrastructure, and our deep commitment to building AI services and solutions.”