Red Hat OpenShift AI is a platform for managing the lifecycle of predictive and generative AI models at scale across hybrid cloud environments.
Red Hat OpenShift AI is a platform designed to manage the entire lifecycle of AI models, both predictive and generative, across hybrid cloud environments. Built on open-source technologies, it offers trusted capabilities for data acquisition, preparation, model training, fine-tuning, serving, and monitoring, as well as hardware acceleration. It integrates with Red Hat OpenShift to provide a unified platform for data scientists, engineers, and application developers to collaborate on AI-enabled applications. The platform helps manage the costs of inferencing with distributed serving through an optimized vLLM framework and offers advanced tooling to automate deployments and provide self-service access to models, tools, and resources. Red Hat OpenShift AI aims to simplify the deployment and scaling of AI applications in enterprise environments.
Red Hat OpenShift AI is a platform designed to manage the entire lifecycle of AI models, both predictive and generative, across hybrid cloud environments.
Explore all tools that specialize in build ai-enabled applications. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Explore all tools that specialize in deploy ai models at scale. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Explore all tools that specialize in manage the ai model lifecycle. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Explore all tools that specialize in monitor ai model performance. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Explore all tools that specialize in train and fine-tune ai models. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Explore all tools that specialize in accelerate ai model inferencing. This domain focus ensures Red Hat OpenShift AI delivers optimized results for this specific requirement.
Provides pre-trained AI models via API endpoints, simplifying AI integration into applications. This allows developers to consume AI capabilities without needing to build and manage models themselves.
Uses the vLLM framework for distributed model serving, optimizing inference costs and accelerating performance. This enables efficient scaling of AI applications.
Provides advanced tooling to automate the deployment of AI models, streamlining the process and reducing manual intervention. This includes CI/CD pipelines for model deployment.
Offers self-service access to models, tools, and resources, empowering data scientists and developers to experiment and innovate independently. This includes role-based access control.
Supports hardware acceleration through integrations with NVIDIA, AMD, and Intel, optimizing AI model performance. This allows users to leverage GPUs and other specialized hardware for faster training and inference.
Request access to the Red Hat OpenShift AI trial through the Red Hat website.
Deploy OpenShift AI on your chosen infrastructure (e.g., Red Hat OpenShift Service on AWS, Azure Red Hat OpenShift).
Configure access to data sources for model training.
Select and deploy AI/ML tooling from the provided catalog (e.g., Jupyter notebooks, Kubeflow pipelines).
Train and fine-tune your AI model using the selected tools.
Deploy your trained model using the model serving capabilities.
Monitor the performance of your deployed model using the built-in monitoring tools.
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"Red Hat OpenShift AI is designed to streamline the AI lifecycle, providing a unified platform for building, deploying, and managing AI models across hybrid environments. It aims to improve collaboration between data scientists, engineers, and developers."
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