Oracle has announced the availability of six new AI services for its Oracle Cloud Infrastructure platform. Designed for out-of-the-box operation, Oracle said that the new services will “make it easier for developers to apply AI services to their applications without requiring data science expertise,” which is sure to be welcomed by small businesses looking to get into the AI game.
Many companies take on AI projects without knowing how to actualize their concepts, said Oracle Cloud Platform CTO Greg Pavlik. “It’s essential for organizations to bridge the gap between the promise of AI and implementing AI that helps them achieve real results,” Pavlik said. For many companies, these new services from Oracle are the sort of thing that could help reach their AI goals.
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Implementation issues like a scarcity of data science expertise, difficulty in properly training AI models, breaking down data silos or simply getting products to work in a live environment are all major reasons why more organizations haven’t leapt into larger AI products, Oracle said. “As a result [of those issues], companies spend valuable time and resources when they need AI that’s consistent, responsive and capable of working in their business applications and operational environments to deliver actionable results,” Oracle said.
The six new AI services are fully managed parts of Oracle Cloud Infrastructure, and can be pre-trained on business-oriented data or trained in-house on an organization’s own data. The services cover the following use cases:
- OCI Language performs text analysis on documents, customer feedback, support tickets and social media for purposes of sentiment analysis, name recognition, text classification and key-phrase extraction.
- OCI Speech is an automatic, real-time speech recognition service trained on native and non-native speakers. The service can create transcripts, provide closed captions, index content and otherwise help perform analytics on videos.
- OCI Vision is Oracle’s image recognition tool that can be used for document analysis and processing as well as image recognition for multiple applications across various industries, such as detecting manufacturing defects.
- OCI Anomaly Detection can pick up irregularities in products and services to speed error detection and resolution. It has several APIs and SDKs for integration with a variety of programming languages in order to cover a variety of business applications. Other use cases involve fraud detection, equipment failure prediction and anything else relying on detections of small anomalies to establish trends.
- OCI Forecasting is a predictive analytics tool for forecasting a variety of business metrics, like revenue, resource requirements, product demand and more. Oracle also included a confidence interval and explainability portion to help forecast users understand why predictions are what they are, and how to make the right decisions with said predictions.
- OCI Data Labeling is used to label datasets used to train AI models. “Users can assemble data, create and browse datasets, and apply labels to data records through user interfaces and public APIs,” Oracle said. Data sets can be exported and used to train and build models for Oracle’s other OCI AI services.
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