The Future of AI and Machine Learning on Oracle Cloud Infrastructure

There are several technological advancements in this highly competitive world. Artificial Intelligence (AI) and Machine Learning (ML) are popular technologies nowadays. Therefore, businesses want to know the future of AI and ML on Oracle Cloud Infrastructure (OCI).

In this blog, we will discover the AI and ML innovations in Oracle Cloud Infrastructure.

Why Choose Oracle AI and ML services?

Oracle AI helps businesses with accelerated infrastructure, artificial intelligence, and machine learning services. It assists with AI training and inferencing by offering ultra-low latencies for standalone Graphical Processing Units (GPU) and clusters with thousands of nodes.

AI services help developers to add pre-built models to applications and operations. With ML services, data scientists can build, train, and deploy models with their favorite open-source frameworks or benefit from faster in-database machine learning.

• Oracle has an extensive collection of AI and ML services and applications that make IT leaders powerful enough to bring innovations to the market faster.
• It also increases the responsiveness of businesses to enhance performance and security.
• Oracle Cloud Infrastructure Services enables developers to customize models faster using proprietary knowledge bases from OCI AI services.
• In all cloud regions, OCI is available at low prices. Plus, organizations can use its cloud services for any workload, whether it's across clouds or in data centers.
• It has a primary focus on scalability, performance, cost, security, and governance.
• With its set of services, it enables enterprise-wide collaboration and governance by allowing the team to share models, data sets, and labels across services.
• Developers can use AI in applications and business processes easily through OCI Generative AI, which offers pre-built AI language models.
• Oracle Cloud Infrastructure also provides Generative AI Agents to help customers by combining the power of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with enterprise data, enabling them to query diverse enterprise knowledge bases.
  
  

Oracle Cloud Infrastructure Approach to AI

Oracle stands out with its unique approach to AI, which focuses on the different needs of businesses. Here are the latest AI-enabled functionalities from Oracle Cloud Infrastructure.

OCI Generative AI

Generative AI is a new service introduced in Oracle Cloud Infrastructure. It allows for the seamless addition of generative AI capabilities (based on LLMs) into applications and workflows through simple APIs.

It uses LLMs from Cohere, the leading generative AI company for enterprise-grade LLMs. Here are the pre-built models of OCI Generative AI.

• Command Model

  It is a highly performant generation model of Cohere that takes user commands as input and generates text based on the instructions. OCI Generative AI offers two model sizes: a 52 billion parameter model and a 6 billion parameter model.

• Summarization Model Endpoint

  On top of Cohere’s command model, summarization runs as an optimization with no need to instruct it. However, customers can enter the text to summarize and can define parameters like length and format of summarization.

  Customers can use a 52 billion parameter model for summarization. It can summarize news articles, blog posts, documents, and many more.

• Embed Model

  With this model, customers can transform text into a semantic numeric representation of high-dimensional vectors.

Current AI/ML innovations in Autonomous Database

The Autonomous Database of Oracle Cloud Infrastructure is using AI/ML for enhanced performance and streamlined workflow. Let’s discover the new features Oracle has introduced in an Autonomous Database for businesses.

Select AI

• With the help of LLMs, it generates SQL queries based on natural language conversations.
• It allows applications to integrate private data with genAI productivity.
• OCI Generative AI and Select AI both support multiple LLMs and Cohere.

Spatial Machine Learning

• It helps to improve Oracle machine learning.
• Spatial Machine Learning increases model performance by enabling the use of location data.
• It supports Spatial ML algorithms such as regression, classification, clustering, and anomaly detection.

Model Monitoring UI

• It introduced a “no-code” UI in Oracle Machine Learning.
• It helps to simplify ML model monitoring to detect concept and quality drift.
• ML monitoring UI provides support for MLOps by consolidating model and data monitoring into one streamlined UI.

Operational Graph Views on Knowledge Graphs

• Graph Studio also uses the new “no-code” UI.
• It provides graph analytics, such as pathfinding on knowledge graphs, without any data duplication.
• It helps to reveal insight by analyzing connections within a knowledge graph.

Embedded AI in Fusion Cloud Applications

Businesses can embed classic and generative AI into their applications through Oracle Fusion Cloud Applications. It gives access to AI outcomes quickly, whenever needed. It allows easy adoption of the latest AI capabilities, which results in better productivity, improved decision-making, automated processes, and reduced costs. Let’s discover more about Oracle Fusion Cloud Applications.

Enhanced Data

Oracle Fusion Cloud primarily focuses on high-quality and real-time data that helps in innovation, automation, and all smart features. Sometimes, Oracle DataFox data is used to augment customer data for AI application features.

Automated Processes

Businesses can now operate faster and minimize manual intervention with automation. With Oracle Cloud ERP, they can now automate over 90% of standard financial transactions.

Intelligent Insights

Oracle Cloud ERP eliminates the guesswork and provides intelligent insights in real time. Plus, it helps to make analysis and action plans.

Faster Actions

Oracle Fusion Cloud Applications connect the whole business and allow organizations to use financial insights for seamless actions, such as inventory management, production schedules, or program management.

Continuous Learning

Embedded AI offers Oracle AI applications that use the latest machine learning practices with built-in feedback loops to human-in-the-loop input.

Machine Learning on Oracle Cloud Infrastructure

Machine Learning is growing quickly with the latest advancements. Businesses are getting better insights from data and driving innovation through open-source tools, GPUs, and Large Language Models (LLM).

Oracle Cloud Infrastructure (OCI) has introduced the OCI Data Science feature store to help Data Scientists and ML engineers. From data ingestion and transformation to model building and experimentation, the OCI Data Science feature store is an efficient feature management for machine learning that supports and automates the entire workflow.

OCI Data Science Feature Store: Key Functionalities

The Cloud Infrastructure services of Oracle present OCI Data Science Feature Store. It helps with automation in the cloud, built-in MLOps capabilities, and enterprise-grade security. Let’s discover its features and functionalities.

• Centralized Feature Management

  A centralized library for features.

• Feature Consistency and Reproducibility

  OCI Data Science Feature Store ensures that features are computed consistently and can be reused over several models, which importantly enhances the reproducibility of ML projects.

• Real-time and Batch features

  It helps in seamless management by providing batch and real-time features. Plus, it assists with a large variety of ML applications, from fraud detection to customer recommendations.

• Accelerated Time to Production

  It reduces the time taken for a model to move from a development stage to a production stage.

• Reduces Costs

  OCI Data Science Feature Store minimizes storage and computation costs and improves resource efficiency.

• Collaboration and Governance

  With a shared and centralized library of features, teams can collaborate easily. Additionally, it provides tools for monitoring, validation, and version control.

• Programmatic and Declarative Programming Support

  It offers support for programmatic interfaces through SQL, Python, and PySpark interfaces.

You can learn more with Oracle-certified cloud services partners like Astute Business Solutions.