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The Era of Generative AI

Table of Contents

    AI has been an ever-evolving field of computer science with a vast area of applications and use cases. Generative AI stems from it and even shares some similarities. Yet some distinctive features of Generative AI extend the capabilities of traditional AI.

    With Oracle’s recent announcement of their Generative AI, you can leverage AI at a greater scale. Let us introduce the complete scope of Oracle generative AI services to you.

    Oracle Cloud Gen 2: Best Cloud for Training Generative AI Models

    Some unique features showcase the commitment of Oracle to contributing to the AI revolution and making sure that Oracle systems can keep up with the evolving nature of Artificial intelligence.

    A major feature is Oracle Cloud Gen 2.

    Oracle Cloud Gen 2 provides the perfect environment for the development and deployment of AI models. Here are some distinctive and unique features of Oracle Cloud Gen 2 contributing to this:

    1. High-performance infrastructure:
      In order to run and train complex AI models, infrastructures are required to possess high-performance capabilities.

      Oracle Cloud Gen 2 possesses high-performance capabilities and access to a variety of GPUs and CPUs optimized for AI workloads.
    2. Pre-built AI services:
      Oracle Cloud Gen 2 offers several pre-built AI services to solve various issues that businesses face today—for example, natural language processing, computer vision, and machine learning.

      Oracle Gen 2 Cloud also features automated capabilities that reduce the need for manual tasks, enhancing the productivity and efficiency of your organization’s teams.
    3. Easy development and deployment :
      Oracle Cloud Gen 2 provides multiple tools and services that make it easy to deploy AI models. Tools such as OCI Workbench and the OCI Model Registry make the environment more suitable for AI.
    4. Security and compliance:
      Features such as data encryption and access controls provided by Oracle Cloud Gen 2 provide many security and compliance features supporting the development of AI models.
    5. Interconnectivity:
      Oracle Gen 2 cloud is designed for interconnectivity and interoperability. It facilitates a cohesive AI ecosystem that allows businesses to integrate AI applications with databases, tools, and services.

    Larry, CTO of Oracle, has attested to the fact that Oracle Cloud Gen 2 is a powerful and versatile platform well-suited to run AI workloads.

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    Generative AI: What sets it apart?

    We have been discussing Artificial AI and the impact it can have on our working systems since its inception many years ago. But Generative AI is different.

    Some key differentiating factors set generative AI different from traditional AI models are:

    1. A shift from predefined tasks to original output:
      Traditional AI models were designed for specific tasks such as classification, regression, or pattern recognition. They focused on predefined tasks according to the input data.

      On the other hand, Generative AI is capable of generating new content such as text, and images, and going beyond the predefined tasks.
    2. Extended Learning:
      While traditional AI models require a supervised or unsupervised learning approach to identify patterns, generative AI utilizes unsupervised learning without explicit guidance to create original outputs.
    3. Wide training data requirement:
      AI is traditionally trained on labeled datasets with specific input-output pairs relevant to tasks, limiting its scope of application.

      On the other hand, generative AI requires a large and diverse dataset to learn and generate meaningful content.
    4. Use cases:
      Traditional AI models are well-suited for image recognition, language translation, and sentiment analysis tasks. Tasks requiring specific predictions and classifications can be completed using general AI tools.

      For creative fields such as content creation that involve the generation of new and contextually relevant content, generative AI tools are preferred.
    5. Flexibility and Adaptability:
      While traditional AI models are relatively rigid and task-specific, generative AI tends to be more adaptable and versatile. It is capable of handling a range of tasks without significant retraining. The model can adapt to various contexts and generate diverse outputs.
    6. Human-like interaction:
      Traditional AI models are primarily used for providing answers or predictions based on pre-identified patterns.

      If you extend these capabilities, you can leverage generative AI to engage in more natural and human-like conversations, understanding context, and generating coherent and contextually relevant responses.

    Conclusion

    The gap between traditional AI models and generative AI has widened. With the world waking up to a new revolution in AI every day, it is imperative for businesses to implement it in their working ecosystems to enhance efficiency and reduce dependency on manual labor.

    In response to this, Oracle has launched its own suite of Generative AI services. We will be uncovering all aspects of the service offering in detail in the upcoming blogs.

    If you want help with pointing out where Oracle AI services will fit in your organizations, contact Astute Business Solutions today.

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