Oracle introduced a collection of services, Oracle Cloud Infrastructure AI Services designed to simplify for developers to include AI services in their application by eliminating the need for data science expertise. With the new solution, developers will be able to leverage out-of-the-box models that have been pretrained on business-oriented data or custom training the services based on the organization’s data.
Six new services
The six new services included in OCI AI Services aims to help developers with complex tasks from language to computer vision and time-series forecasts. The solutions are pretrained to offer immediate value for organizations with various use cases. AI services include:
- OCI Language: Performs text analysis at scale to understand unstructured text in documents, customer feedback interactions, support tickets, and social media. With built-in pre-trained models, OCI Language eliminates the need for machine learning expertise and empowers developers to apply sentiment analysis, key-phrase extraction, text classification, named entity recognition, and more into their applications.
- OCI Speech: Provides automatic speech recognition through prebuilt models trained on thousands of native and non-native language speakers for real-time speech recognition. OCI speech enables developers to easily convert file-based audio data containing human speech into highly accurate text transcriptions and can be used to provide in-workflow closed captions, index content, and enhance analytics on audio and video content.
- 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 such as scene monitoring, defect detection, and document processing with their own data. OCI Vision can be used to detect visual anomalies in manufacturing, extract text from forms to automate business workflows, and tag items in images to count products or shipments.
- OCI Anomaly Detection: Delivers business-specific anomaly detection models that flag critical irregularities early, which enables faster resolution and less operational disruption. OCI Anomaly Detection provides REST APIs and SDKs for several programming languages, which developers can use to easily integrate anomaly detection models into business applications. It is built on the patented MSET2 algorithm, which is used worldwide in highly sensitive situations like nuclear reactor health monitoring and can be used for fraud detection, predicting equipment breakdown, and receiving data from multiple devices to predict failures.
- OCI Forecasting: Delivers time-series forecasts through machine learning and statistical algorithms without the need for data science expertise. OCI Forecasting helps developers to quickly create accurate forecasts for their critical business metrics, including product demand, revenue, and resource requirements. These forecasts all have confidence intervals and explainability to help developers make the right business decisions.
- OCI Data Labeling: Helps users build labeled datasets to train AI models. Users can assemble data, create and browse datasets, and apply labels to data records through user interfaces and public APIs. The labeled data sets can be exported and used for model development across many of Oracle’s AI and data science services, including OCI Vision and OCI Data Science, for a consistent model-building experience.
Greg Pavlik, chief technology officer of Oracle Cloud Platform said,
“It’s essential for organizations to bridge the gap between the promise of AI and implementing AI that helps them achieve real results. 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.”