Oracle has updated its Cloud Infrastructure Service (OCI) to include a new suite of AI services (AI) with six new tools designed to make it easier and faster for developers and data scientists to apply AI, including machine learning techniques, to different business scenarios.
The new suite of AI services on OCI, Oracle’s public cloud platform for developing and running big data applications, is available now. It will compete with 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 knowledge or understanding of data science.
Despite the race to catch up with the new OCI services, Oracle’s strategy seems logical, according to Constellation Research VP and Principal Analyst Holger Mueller. “Companies that already rely on Oracle databases can benefit from the new services. It also means that Oracle has managed to keep Oracle’s database load on Oracle in-house and has shown that OCI does the best job of running the Oracle database, ”said Mueller.
The new services allow developers not to worry about installing, updating, and maintaining AI platforms and can focus on programming, Mueller noted.
AI to accelerate deployment
The new AI services are expected to reduce the time it takes to manage data and the time it takes to build and deploy applications, said Greg Pavlik, CTO at Oracle Cloud. The time it takes companies to respond to different scenarios could make all the difference to their survival in “volatile and uncertain times,” Pavlik said.
New tools include AI-based speech, voice, vision, anomaly detection, data labeling and forecasting services. The new OCI voice service is designed to enable developers to do text analytics on a large 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, phrase recognition, and entity recognition, among other things.
Oracle’s competitors offer similar features. AWS has intelligent language services such as Comprehend, Lex and Polly, while Microsoft offers the Text Analytics API for advanced analysis.
According to Oracle, the speech service comes with ready-made models that can understand speech in multiple languages in real time. Pavlik said developers can use the service to convert file-based audio into text transcriptions using human speech. The service can be used to provide subtitles in the workflow, index content and improve the analysis of audio and video content.
The AWS Transcribe and Translate service could be considered equivalent to this service. Azure also offers a similar service.
The OCI Vision service is designed to make it easier for developers to train visual models. It comes with pre-trained models for image recognition and document analysis tasks, Pavlik said.
“Also, users can extend the models to other industry and custom use cases such as scene monitoring, error detection and document processing with their own data,” said Pavlik, adding that the service can be used to produce visual anomalies in, extract text from forms, to automate business processes and tag items in images to count products or shipments.
The AWS Rekognition service and Azure Computer Vision offer similar functionality.
Weeding out anomalies and cleaning up data
Organizations spend a lot of time identifying issues with their data and AI models. In order to shorten the time to detect such anomalies, the new AI-Services-Suite contains the OCI-Anomaly-Detection-Service, which can detect critical irregularities at an early stage, which leads to faster resolution times.
“OCI Anomaly Detection is based on the MSET2 algorithm and provides REST APIs and SDKs for multiple programming languages that allow developers to easily integrate anomaly detection models into business applications,” said Pavlik. He added that the tool can be used to detect fraud, predict machine failures, and record data from multiple sources.
Anomaly detection can be seen as a key aspect of AI services and all vendors should offer it, Constellation’s Mueller said. “For Oracle, it is even more relevant given the vast amount of transactional data that is stored in its databases. And being able to recognize an anomaly – and then flag it in analyzes – or even to correct it with measures through AI is extremely important for companies in order to act faster and become more agile, “said Mueller.
As part of the new suite, Oracle has also released the OCI forecasting service, which automatically creates time series forecasts based on pre-built machine learning models without code, Pavlik said. It enables developers to forecast critical business metrics such as product demand and sales.
Oracle also announced OCI Data Labeling, which allows users to create labeled data sets to easily train AI models. According to Pavlik, the new service will enable developers to compile data, create and search data sets, and assign labels to them through user interfaces or public APIs.
“The tagged datasets can be exported and used in model development for many of Oracle’s AI and data science services, including OCI Vision and OCI Data Science, to enable consistent modeling,” said Pavlik.
Tags OracleArtificial IntelligenceCloud