Oracle Strengthens Cloud Infrastructure with Suite of AI Tools

Oracle has updated its cloud infrastructure service (OCI) with a new suite of artificial intelligence services with six new tools that should make it easier and faster for developers and data scientists to apply AI, including machine learning techniques, to various business scenarios.

The new suite of AI services on OCI, Oracle’s public cloud platform used to develop and run big data applications, is now available. It will compete with the Amazon Web Services (AWS) SageMaker platform and Microsoft’s Azure Machine Learning Studio, which is designed for use by enterprise developers who may not have in-depth expertise or knowledge of data science.

Despite catching up with the new OCI services, Oracle’s strategy seems logical, according to Constellation Research VP and chief analyst Holger Mueller. “Companies already in Oracle databases can take advantage of the new services. It also means that Oracle has managed to keep Oracle’s database load in-house on Oracle and has shown that OCI manages the Oracle database best,” said Mueller.

The new services allow developers to worry about installing, updating and managing AI platforms, allowing them to focus on programming, Mueller noted.

AI to accelerate implementation

The new set of AI services is expected to reduce the time it takes to manage data and the time it takes to build and deploy applications, said Greg Pavlik, chief technology officer at Oracle Cloud. The time it takes for companies to respond to diverse scenarios can make all the difference to their survival in “volatile and uncertain times,” Pavlik said.

The new tools include AI-based language, speech, vision, anomaly detection, data labeling and forecasting services. The new OCI Language service is designed to enable developers to perform text analysis at scale. The service can understand unstructured text in documents, customer feedback interactions, support tickets and social media, Pavlik said. The service also comes with pre-trained models that allow developers to deploy them out-of-the-box and gain insights in the form of sentiment analysis, sentence detection, and entity recognition, among other capabilities.

Oracle’s competitors offer similar capabilities. AWS has intelligent language services such as Comprehend, Lex, and Polly, while Microsoft provides Text Analytics API for advanced analytics.

The Speech service comes with pre-built models that can understand speech in different languages ​​in real time, according to Oracle. Pavlik said developers can apply the service to convert file-based human speech audio into text transcripts. The service can be used to provide subtitles in the workflow, index content, and improve analytics of audio and video content.

AWS’s Transcribe and Translate service can be considered an equivalent of this service. Azure also offers a similar service.

The OCI Vision service is designed to make it easy for developers to train visual models. It comes with pre-trained models for image recognition and document analysis tasks, Pavlik said.

“It also allows 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,” said Pavlik, adding that the service can be used to detect visual anomalies in production, extract text from forms to automate business workflows and tag items in images to count products or shipments.

The AWS Rekognition service and the Azure Computer Vision offer similar capabilities.

Remove discrepancies and clean up data

Companies spend a lot of time tracking down problems with their data and AI models. To reduce the time it takes to detect such anomalies, the new AI service suite includes the OCI Anomaly Detection service, which can identify critical anomalies early, leading to faster resolution times.

“OCI Anomaly Detection, built on the MSET2 algorithm, provides REST APIs and SDKs for various programming languages, which developers can use to easily integrate anomaly detection models into enterprise applications,” said Pavlik. He added that the tool can be used to detect fraud, predict machine failures and capture data from multiple sources.

Anomaly detection can be considered an important aspect of AI services and all vendors should offer it, Constellation’s Mueller said. “It’s even more relevant to Oracle, given the massive amounts of transactional data stored in its databases. And being able to detect an anomaly — and then flag it in analytics — or even fix it with actions through AI is huge for enterprises to act faster and become more agile,” Mueller said.

As part of the new suite, Oracle has also released the OCI Forecasting service, which automatically provides time series predictions based on pre-built machine learning models without the need for code, Pavlik said. It enables developers to forecast critical business metrics such as product demand and revenue.

Oracle also announced OCI Data Labeling, which allows users to create labeled datasets to easily train AI models. According to Pavlik, the new service will allow developers to compose, create, browse, and label data sets via user interfaces or public APIs.

“The tagged datasets can be exported and used for model development in many of Oracle’s AI and data science services, including OCI Vision and OCI Data Science, for a consistent model building experience,” said Pavlik.

Copyright © 2021 IDG Communications, Inc.

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