MLOps

AI MLOps

What is AIOps and How is it Different from MLOps?

BAILeY explains AI Ops and what makes it different from ML Ops

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AI Red Hat

OpenShift AI helps you set up an MLOps “conveyer belt”

Many developers struggle with putting a model into deployment. The difficulty of updating models in production often leads to hesitancy and delays. The concept of MLOps deals with putting models into production without it being painful or risky. With Red Hat OpenShift AI, data scientists can create models with their preferred tooling, create pipelines to […]

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AI Red Hat

OpenShift AI as a foundation

Red Hat’s AI platform enables the development and deployment of models across the public cloud, data center, and edge. It manages cluster resource requests, such as scaling up and down GPUs, and fosters collaboration between developers and data scientists. All by expanding the DevOps tooling provided within OpenShift, providing additional capabilities such as model serving […]

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AI Open Source Red Hat

A collaborative platform with OpenShift AI

Red Hat OpenShift AI provides a secure, reliable and consistent platform across the hybrid cloud.  Data scientists, MLOps engineers, and application developers can work together on the same cloud-native platform, leading to faster business insights with trusted outcomes. Providing innovative AI/ML tooling from the open source world but with the support and security of Red […]

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AI Large Language Models MLOps

Foundation Models in the Modern Data Stack

This video is from MLOps.community. // Abstract As Foundation Models (FMs) continue to grow in size, innovations continue to push the boundaries of what these models can do on language and image tasks. This talk describes our work on applying foundation models to structured data tasks like data linkage, cleaning, and querying. We discuss the […]

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AI Red Hat

Data science pipelines on OpenShift

Guillaume Moutier describes the new data science pipelines capability within Red Hat OpenShift Data Science that allows data scientists, data engineers and app developers to ingest data and clean it within the Jupyter environment, and then deploy as an OpenShift pipeline. Data practitioners can automate the full cycle within and intuitive drag-and-drop UI. Check out […]

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AI Generative AI Red Hat

Unlock the Power of Generative AI with the Right Platform Stack

Taneem Ibrahim and Selbi Nuyryev describe the work in the Open Data Hub community about building an AI/ML stack for generative AI and foundation models. With project CodeFlare and open source technology work with CAIkit, KubeRay and Text Generation Inference Service (TGiS), KServe to prompt-tune pre-trained models and provide resource efficiency across the hybrid cloud. […]

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AI Generative AI Red Hat

Get the Scoop on OpenShift AI from Red Hat’s Chris Wright

Chris Wright, Red Hat CTO, describes Red Hat OpenShift AI and how it extends Red Hat’s application platform to help data scientists and developers collaborate to bring ai-enabled applications into the enterprise. Leveraging DevOps principles, OpenShift AI works across the entire model development lifecycle to help AI/ML teams build, deploy and monitor models across the […]

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AI Red Hat

What is OpenShift AI?

Will McGrath gives a high-level overview of what is Red Hat OpenShift AI, a portfolio of products, built on OpenShift, that allows you to build, train, deploy and life-cycle manager models across the hybrid cloud. As a core offering within the OpenShift AI family, Red Hat OpenShift Data Science provides MLOps tooling such as model […]

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AI Red Hat Startups

From startup to production – an AI/ML success story

An agriculture startup explores how to bring AI models into production to promote healthy crops. Watch the company work through leveraging multiple data types, building the model on a shared AI platform, and successfully bringing the model into production. This video highlights the benefits of Red Hat  OpenShift Data Science in a fun, informal way!

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