Overcome The Challenges of AI Implementation With Oracle AI

Artificial Intelligence (AI) offers immense potential, but implementing AI results in several obstacles, from data quality to integration issues. In this blog, we will discover the challenges in detail and the solutions to overcome them easily with Oracle AI and its powerful strategy.

Challenges of AI Implementation

Here are the challenges that businesses encounter during the AI implementation in their computer systems.

Data

Generally, AI systems are data-driven and need high-quality information to function correctly. Poor quality or insufficient data may lead to inaccurate results or biased data. It requires labeled data for training, especially in specific domains.

Infrastructure

AI systems require a lot of computing power to run. That’s why organizations need to ensure that their computer systems are upgraded to use AI effectively in their business processes.

Integration

AI systems don’t always work well with existing computer systems, particularly legacy systems. It becomes challenging to ensure compatibility, security, and minimal disruption to an existing system for a successful AI implementation.

Scalability and Performance

AI models require significant resources for training and inference. Scaling AI systems to handle large datasets and real-time processing while maintaining performance is challenging, especially in resource-constrained environments.

AI Models Management

It needs quality data and technologies to manage AI/ ML models. While managing AI models, you need to consider version control, reproducibility, and model performance over time. Plus, it also needs to manage model complexity and address scalability issues.

Security

AI systems work with large amounts of data that need to be protected. If this is not done properly, it will result in security risks.

Why Choose Oracle For AI Workloads?: 11 Reasons to Know

Let’s discover the reasons to choose Oracle for AI.

• OCI’s AI infrastructure improves the performance of dedicated custom on-premises compute clusters meanwhile offering elasticity and consumption-based costs of the cloud.
• Oracle Cloud Infrastructure offers industry-leading cluster network bandwidth which helps in scaling incredibly large clusters when compared to other hyper-scale cloud providers.
• With Oracle Generative AI service, customers will get on-demand elasticity and scalability, predictable price performance, and the development of private model endpoints.
• During AI model training, OCI provides a unique cloud architecture that quickly shuttles data between advanced CPUs and GPUs to deliver the best possible performance.
• It offers data gravity to Oracle’s SaaS applications or databases.
• Oracle is the simplest and most cost-effective solution for AI workloads because it helps with no hidden fees, monthly subscription, and only PAYG for what businesses use.
• It is designed for enterprise or ISV scale (many models serving many customers).
• Oracle provides white glove service to its customers, which means a high-level of detailed-oriented service.
• With Oracle AI, businesses will get pre-trained and customizable models for industry and specified use cases. It can easily be used as a part of the e2e data journey.
• It offers a single discovery and publishing experience for models, features, datasets, and labels. Plus, businesses will also get consistent APIs and experiences.
• Oracle AI uses open-source tools, frameworks, and models. These AI models are easy to run anywhere and businesses can use best-of-breed AI capabilities.

Oracle’s AI Strategy: AI For Everyone

Now, it’s time to look over the Oracle strategy for AI implementation.

1. Ready-to-Go

Data and AI-powered applications that offer adaptive intelligent apps, intelligent UX, and conversational agents.

2. Ready-to-Build

It provides an AI platform that helps to build, train, deploy, and manage.

3. Ready-to-Work

Here, it offers an autonomous database that helps with self-driving, self-securing, and self-repairing.

Oracle AI: An Effective Solution For AI Implementation

Here are the different Oracle AI solutions for your business.

Generative AI

• OCI offers Generative AI models that include advanced language comprehension to build the next generation of enterprise applications.
• It is a fully managed service that is readily available through API for the seamless integration of versatile language models. These models have a wide range of use cases, such as writing assistance, summarization, and chat.

Generative AI Agents

• OCI Generative AI Agents service provides an agent that combines the power of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with enterprise data. As a result, users can easily query diverse enterprise data sources.
• It enables users to access and understand updated information via a chat interface and agents can take actions on the basis of findings, if needed in the future.

Digital Assistant

• OCI Digital Assistant is a conversational AI platform for automated customer self-service and enterprise business processes.
• It performs deep learning and semantic parser-based Natural Language Processing (NLP) for the enterprise.
• It offers enterprise horizontal and vertical skills, and skill development requires no code or low-code tool.

Language Service

• In OCI Language service, models are trained on industry data to perform language analysis.
• It allows businesses to train language models with their data and without any data science expertise.
• It can identify the language of the text, key phrases, and entities in the text.
• With OCI language service, businesses can classify text content into more than 600 categories and subcategories for data analysis support.
• It also helps with aspect-level sentiment analysis and text translation.

Speech Service

• OCI Speech service automatically transcribes the audio and video files into text through advanced deep learning techniques.
• It eliminates the need for data science expertise.
• It doesn’t require any data movement because it processes data directly into the object storage.
• It helps to generate timestamped grammatically accurate transcriptions.

Vision Service

• With OCI Vision service, customers will get state-of-the-art models and fully managed model infrastructure that will be pre-trained for image recognition tasks.
• It offers visual and textual features for searchable PDFs, document language detection, and document classification without any deep learning pipeline.

Document Understanding

• In OCI Document Understanding, developers will be able to extract texts, tables, and other key elements from document files with the help of APIs and command-line interface tools.
• It helps to automate tedious business processes through prebuilt AI models and customize document extraction to fulfill industry-specific requirements.

Anomaly Detection

• OCI Anomaly detection helps in developing multiple anomaly detection models and automatically selects the most accurate to indicate critical incidents earlier.
• It can automatically identify and fix data quality issues.
• OCI Anomaly detection is based on industry-leading and proven anomaly detection techniques like MSET-2 and deep learning MADORA kernel.
• It helps to increase accuracy by detecting anomalies that span across several sensors.

Forecasting Service

• With the OCI Forecasting service, businesses can forecast any time series metric, such as product demand, revenue, and the number of service requests.
• It helps to build multiple models and automatically selects the most accurate one for the business.
• It can deliver forecasts with explainability that creates transparency in predicted outcomes.

You can learn more about the Oracle AI services with Astute Business Solutions, an Oracle-certified solutions partner. It helps businesses with a wide range of solutions for an easy implementation of AI.