New enterprise generative AI service helps organizations automate business processes, improve decision-making, and enhance customer experiences
Oracle announced the limited availability of Oracle Cloud Infrastructure (OCI) Generative AI service. The new generative AI service will support large language models (LLMs) to help organizations automate end-to-end business processes, improve decision-making, and enhance customer experiences, while keeping their data secure and private.
Built on OCI in collaboration with Cohere, the leading AI platform for enterprise, the OCI Generative AI service is a managed service that enables users to integrate LLMs in their own applications through an available API. Once generally available, this service and Cohere models will work seamlessly with AI Vector Search, a feature of Oracle Database 23c that provides retrieval augmented generation (RAG), a generative AI technique that combines pretrained LLMs and proprietary business data to deliver responses with higher accuracy. This service will also form the basis for generative AI capabilities embedded across Oracle’s suite of SaaS applications, including Oracle Fusion Cloud Applications Suite, Oracle NetSuite, and industry applications such as Oracle Cerner.
“Oracle’s unique industry knowledge has enabled us to create state-of-the-art generative AI services for organizations to automate their processes, make better decisions, and improve the experiences they deliver to customers,” said Clay Magouyrk, executive vice president, Oracle Cloud Infrastructure. “Through our partnership with Cohere, customers will be able to embed generative AI easily and securely into their technology stack with full confidence that our solutions align with their most stringent data security and privacy requirements. Our approach further enables organizations to refine these models using their own data—so the models will understand their internal operations like no one else.”
With its low-cost, secure, high-speed AI infrastructure, OCI will enable customers to use Cohere’s models as a managed service specifically targeted for enterprise use cases. Customers using the OCI Generative AI service run their workloads in a dedicated infrastructure on Oracle’s unique AI Supercluster architecture. This enables customers to control their specific cost and throughput requirements, whether they are fine-tuning models with their own data or deploying their custom models.
Also Read: Join Privacera at Big Data London to Discuss Data Security Governance in the Age of Generative AI
The new OCI generative AI service includes the following models:
- Command: This model takes a user’s prompt and generates text. Available in two different sizes, Command is highly customizable for business use cases, including text generation, text summarization, RAG, and chat.
- Summarize: This model does abstractive summarization of the text and enables the user to configure the results with a variety of parameters to support unique use cases. For example, summarizing complex documents for legal teams, technical support documentation for customer service representatives, and long email chains for busy employees.
- Embed: This text representation model translates text into numerical vectors that models can understand. It provides industry-leading English and multilingual models (100+ languages) for a range of use cases, including semantic search, text classification, search engine for RAG and legacy search improvement.
“Oracle and Cohere center our enterprise AI offering on the principles of data security, model customization, latency, and helping companies quickly, meaningfully, cost-efficiently, and responsibly deploy AI technology,” said Martin Kon, president & COO, Cohere. “We are working closely together with Oracle to enable enterprises to supercharge their businesses with AI, with a data security and privacy-first approach.”
“Oracle has been a valuable partner for Altair and with Altair’s focus on computational science and artificial intelligence, Altair has begun integrating large language models into our solutions because of their transformative promise,” said Sam Mahalingam, chief technology officer, Altair. “We believe generative AI will transform the way we work. For example, customers will be able to describe the desired outcome in natural language format and an LLM will automatically produce solutions. In data analytics, customers will no longer need to code for machine learning but simply ask for the predictions. In engineering, customers can describe product properties and the models will do the design. The applications are limitless.”
In addition to the OCI Generative AI service news, Oracle AI has continued to add enhancements to existing services with multiple limited availability programs, including:
- Oracle Digital Assistant: Adds generative AI features to allow customers to integrate LLMs and other generative capabilities into their digital assistants. In addition, developers can use generative AI to build digital assistants more quickly and efficiently.
- OCI Language Healthcare NLP: Adds healthcare insights with natural language processing. This new feature of the OCI Language service helps better process language in the medical domain. New models will help recognize medical terms, relationships and entities in records such as clinical trials notes, patient progress notes, and electronic health records.
- OCI Language Document Translation Experience: Adds new document translation feature to support a wide range of formats – Word, PPT, HTML, JSON, and Excel – ensuring content remains intact and translated across diverse file types.
- OCI Vision: Adds Facial Detection, gaining the ability to recognize faces and facial features in images, and expanding the number of OCI Vision use cases.
- OCI Speech: Adds diarization, allowing the service to embed speaker information into transcribed sections of audio. Diarization makes OCI Speech a valuable tool for organizing, analyzing, and extracting meaningful information from spoken interactions.
- OCI Data Science: Adds Feature Store, a central repository used to manage features developed by data science teams. Feature Store provides a cohesive framework where features are meticulously documented, shared, stored, and served in a streamlined manner.
SOURCE: PRNewswire
