Oracle Cloud Infrastructure (OCI) AI Services is a collection of services with prebuilt machine learning models that make it easier for developers to apply AI to applications and business operations. The models can be custom-trained for more accurate business results. Teams within an organization can reuse the models, datasets, and data labels across services. OCI AI Services makes it possible for developers to easily add machine learning to apps without slowing down application development.
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Join us on April 5 for a showcase of Oracle’s AI services, and learn how they can help developers apply AI to call center and customer sentiment analysis to deliver better business outcomes.
Digital assistants are virtual devices that help users accomplish tasks through natural language conversations, without having to manage various apps and web sites. Each digital assistant contains a collection of specialized bots that focus on specific types of tasks, such as tracking inventory, submitting time cards, creating expense reports, and checking sales forecast.
When a user engages with the assistant, it evaluates the user’s input and routes the conversation to and from the appropriate bots. Users can access Oracle Digital Assistant through a variety of channels, such as Facebook Messenger, Slack, and mobile apps.
OCI Language is a new AI service for performing sophisticated text analysis at scale. With pretrained models built in, including accents, developers don’t need machine-learning expertise to build sentiment analysis, key-phrase extraction, text classification, named entity recognitions, and more into applications. Developers can easily get started by accessing the service through SDKs in a variety of programming languages and REST APIs. Leverage OCI Language to better understand customer feedback and enhance customer support while complying with customer privacy regulations.
OCI Speech is a new AI service that uses automatic speech recognition (ASR) to provide audio to text conversion using acoustic and language models. Built on the time-tested AI models used by Oracle Digital Assistant, developers can easily convert file-based audio and video data containing human speech into highly accurate text transcriptions across multiple languages. Without specific data science expertise, developers can transcribe digital audio files into normalized, timestamped, and profanity-filtered text. OCI Speech can be used to provide in-workflow closed captions, index content, and enhance analytics on audio and video content.
OCI Vision is an AI service that applies computer vision technology to analyze image-based content. Developers can make API calls to easily integrate pretrained models into their applications, or custom-train models to meet their specific use cases. These models can be used to detect visual anomalies in manufacturing, extract text from documents to automate business workflows, and tag items in images to count products or shipments.
OCI Anomaly Detection is an AI service for building business-specific anomaly detection models that flag critical incidents, resulting in faster time to detection and resolution. OCI Anomaly Detection provides API calls and SDKs for several programming languages, which developers use to easily integrate models with business applications. Automated model selection features train anomaly detection models and deploy them to applications and business operations. OCI Anomaly Detection is built on the MSET2 algorithm, with more than 150 patents and used around the world to monitor the health of nuclear reactors and airplanes, and can be used for fraud detection, predicting equipment breakdown, and receiving data from multiple devices to predict failures.
OCI Forecasting is a fully managed service that delivers time-series forecasts through machine learning and statistical algorithms, without the need for data science expertise. Developers can quickly implement OCI Forecasting through REST APIs and SDKs to predict a variety of metrics including product demand, revenue, and resource requirements, all with confidence intervals and explainability to aid in making business decisions.
Use OCI Anomaly detection to ensure optimal operation of assets, while avoiding excess costs and minimizing operational disruptions in smart manufacturing.
Improve customer satisfaction and also reduce the cost of providing chat-based support with Oracle Digital Assistant’s skill bots.
SS Global, an innovative transportation logistics company, created an IoT application which monitors tire and vehicle conditions via a variety of sensors. They chose OCI Anomaly Detection to identify anomalies in vehicles, such as tire baldness or air leaks, which generate alerts to help prevent small issues from becoming big problems.
Pretrained, customizable models that can be used with and deployed to apps.
Train models on the organization’s application data. Models that understand business context deliver more accurate results.
One usage and publishing experience for models, features, datasets, and labels, with consistent APIs.
Specialized algorithms built over 20 years of data science have been proven in many safety-critical industries.
Expect enterprise-grade AI, architected for security and tested in critical sectors including government, finance, and nuclear energy.
Benjamin Arnulf, Senior Director, Product Strategy, Oracle Analytics
You can use Oracle Analytics Cloud and OCI Vision together for many industry use cases. For example, Children's Medical Research Institute can more quickly analyze microscope images and is significantly reducing their simulation time, increasing the speed at which they can drive progress. This blog describes some steps you can take to get the benefits of using Oracle Analytics Cloud and OCI Vision in a low-code/no-code setting.Read the complete post