Oracle today released a new version of Oracle Cloud Infrastructure (OCI) AI services, a set of services that make it easier for developers to incorporate AI into their applications without the need for data science knowledge. Developers can choose between using out-of-the-box models that have been pre-trained on business-oriented data or custom training the services using their own data using the new OCI AI services. The six new services assist developers with a variety of difficult tasks, including language, machine vision, and time-series forecasting.

AI is now required by businesses to speed innovation, assess business circumstances, and provide innovative customer experiences. However, businesses usually face implementation challenges ranging from a lack of data science knowledge to difficulty training models on relevant business data, as well as getting their platform to perform in a live setting and breaking down data silos. As a result, businesses waste time and resources when they need AI that is consistent, responsive, and capable of delivering actionable outcomes in their business applications and operational environments.

'Bridging the gap between the promise of AI and adopting AI that helps them achieve real results is critical for enterprises,' said Greg Pavlik, chief technology officer, Oracle Cloud Platform. 'Through our industry-leading specialist knowledge in development environments and enterprise data, our next-generation cloud infrastructure, and our strong mission is to deliver AI services and solutions, Oracle is best positioned to maximise the potential of AI.'

Oracle's AI services are pre-trained to provide immediate benefit for companies across a broad range of use cases, based on Oracle's experience as the top business applications vendor with the most comprehensive array of cloud apps.

The following are some of the new fully managed AI services:

1) OCI language : 

To analyse unstructured language in documents, customer feedback conversations, support requests, and social media, does text analysis at scale. OCI Language reduces the requirement for machine learning knowledge by providing built-in pre-trained models that let developers to incorporate sentiment analysis, key extraction, text categorisation, named entity identification, and more towards their application domains.

2) OCI speach : 

For real-time voice recognition, it uses pre-built models that have been trained on multitudes of native and non-native language speakers. OCI speech makes it simple for developers to capture file-based audio data usually contains human speech into high - accuracy text transcriptions. It can also be used to including in closed captions, index content, and improve audio and video content analytics.

3) OCI vision

For image identification and document analysis tasks, it provides pre-trained computer vision models. Users can also use their own data to extend the models to various industry and customer-specific use cases including scene monitoring, defect detection, and document processing. OCI Vision can detect visual irregularities in manufacturing, extract information from forms to automate corporate procedures, and count products or shipments by tagging items in photos.

4) OCI Detecting Anomalies : 

Delivers business-specific anomaly detection models that detect key deviations early, allowing for quicker resolution and reduced downtime. Developers may simply incorporate anomaly detection models into business applications using OCI Anomaly Detection's REST APIs and SDKs for numerous programming languages. It is based on the proprietary MSET2 algorithm, which is utilised in highly sensitive scenarios such as nuclear reactor health monitoring around the world, and may be used for fraud detection, equipment breakdown prediction, and data collection from many devices to forecast failures.

5)OCI forecasts

Machine learning and statistical algorithms are used to provide time-series forecasts without the need for data science skills. OCI Forecasting enables developers to quickly produce reliable projections for key business variables such as product demand, revenue, and resource requirements. All of these estimates include confidence intervals and explainbility to aid developers in making the best business decisions possible.

6) OCI data labelling

Users can use this tool to create labelled datasets that can be used to train AI models. Through user interfaces and public APIs, users can assemble data, generate and browse datasets, and apply labels to data entries. For a consistent model-building experience, the labelled data sets may be exported and utilised for model development across all of Oracle's AI and data science services, including OCI Vision and OCI Data Science.

Oracle AI is a collection of artificial intelligence, machine learning, and data science offerings that includes Oracle Digital Assistant, as well as OCI Data Science and Oracle Database Machine Learning, which are used for constructing, managing, and deploying machine learning models. Oracle AI is used by companies all over the world to help automate operations, generate innovation, and make more secure decisions.

Quotes from Customers and Partners

CMRI (Children's Medical Research Institute) is a leading medical and biological research institute in Australia, as well as a registered charity. 'One of the essential components of our research in curing children's cancer is identifying the influence of different treatments on tumours,' said Pablo Galaviz, senior data scientist and bioinformatician at Children's Medical Research Institute. 'We're looking to OCI Vision and OCI Data Labeling services, as well as OCI Data Science, to assist us define the effects of those therapies on cells.' First, we use OCI Data Labeling to label microscope images, and then we use OCI Vision to automate the process of detecting different types of cells.First, we use OCI Data Labeling to label microscope images, and then we use OCI Vision to automate the process of detecting different types of cells. In this way, we make efficient use of Oracle's platform to meet our research objectives.'

SS Global is a forward-thinking transportation firm that offers a comprehensive range of logistical solutions and services. 'Our transportation customers collect data from vehicles, cargo, drivers, and other environmental circumstances like traffic,' Sunil Sharma, CEO of SS Global LLC, explained. 'We needed a compelling anomaly detection solution because detecting anomalies in real time is critical to delivering the desired service level. We selected the OCI Anomaly Detection service because of its capacity to detect anomalies in multivariate complex datasets, as well as Oracle's strong investment in this AI service.'

Bosch Service Solutions is a major global provider of BPO services for complicated business processes and services. 'As a provider of contact centre services, Bosch Service Solutions combines the OCI AI Services of Digital Assistant and Speech to allow our clients to have a natural dialogue with BETO, the Bosch chatbot,' said Kiria Fernandes, Bosch Service Solutions Brasil's head of operations. 'Our clients can engage with us in Portuguese using voice commands to drive specific goals and behaviours, expanding the user experience with conversational AI, streamlining transactions, and increasing productivity.'

NVIDIA is a forerunner in the fields of fast computing and artificial intelligence. 'Oracle AI Services and NVIDIA are delivering the benefits and experience that customers have been looking for by delivering high-performance GPUs to customers in a fully managed fashion for notebook sessions, jobs, and model deployments,' said Ian Buck, senior vice president and general manager of accelerated computing at NVIDIA. 'When OCI AI Services and OCI Data Science are combined with NVIDIA RAPIDS, data scientists and developers can accelerate end-to-end machine learning and data science pipelines on NVIDIA GPUs significantly quicker than they can on CPUs.'