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    What's New in Domino

    The Spring 23 release of our Enterprise MLOps platform makes cutting-edge AI accessible to all enterprises – unleashing model velocity to grow revenue, improve the customer experience, and outcompete your peers.

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    Accelerate AI impact

    Domino Spring 23 natively integrates open-source AI tools Ray 2.0, MLFlow and Feast to harness the power of generative AI. Scalable APIs make it easy to deploy complex models into the business with low latency.

    Ray 2.0
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    MLFlow Integration
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    FEAST
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    Scalable APIs
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    Train massive models

    Domino supports Ray 2.0 which enables data science teams to develop and train generative AI models at scale, including ChatGPT. The integration with Domino's on-demand, auto-scaling compute clusters streamlines the development process, while also supporting data preparation via Spark and machine learning and deep learning via XGBoost, TensorFlow, and PyTorch.
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    Simplify lifecycle management

    Domino's integration with MLFlow simplifies machine learning lifecycle management for data scientists. The integration lets data scientists track, reproduce, and share machine learning experiments and artifacts within their Domino projects, while Domino's security layer ensures metrics, logs, and artifacts are secured.
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    Improve feature governance

    Feast, an open-source feature store for machine learning, now integrates natively within Domino.  It lets users easily query and transform ML features. This integration allows teams to reuse feature logic consistently and efficiently across data science projects while tracking feature lineage and ensuring data accuracy and security.
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    Low latency for complex workflows

    Domino now supports low latency, scalable APIs through Seldon supporing models with complex workflows like model ensembles and data processing at prediction time on unstructured data, such as video and speech.   This makes it possible for customers to automate complex, intelligent decisions using techniques such as computer vision and natural language processing.  
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    Domino Nexus

    Domino Nexus is generally available in Spring 23.  Nexus is a single pane of glass that lets you run data science and machine learning workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, so you have one place to build, deploy, and monitor models.

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    Domino Cloud

    Spring 23 includes the launch of Domino Cloud, a fully-managed SaaS version of the Domino MLOps platform, which accelerates AI time-to-value by providing scalable resources and a secure, governed enterprise-grade platform. Customers can save costs by paying only for the compute used while still accessing GPUs and distributed compute frameworks. Domino Cloud eliminates the need for data science teams to worry about deploying, upgrading or managing infrastructure, allowing them to focus on their core responsibilities.

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    Domino Code Assist

    Domino Code Assist (DCA) is a revolutionary product that lets anyone generate Python and R code for everyday data science and analytics tasks by making simple selections in a GUI.  It plays a critical role for any organization looking to upskill analysts and SMEs to increase overall data science capacity.  DCA shortens the learning curve for novice coders and facilitates coaching from more experienced data scientists. Experts also benefit from the time savings of not having to write redundant code for common tasks.

    DCA ships with Spring 23.  It can be added to environments running Domino 4.x and later.

     

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    Domino 5 Blog Series

    Dive deeper into the powerful innovations and unique benefits of Enterprise MLOps

    A New Approach to Scaling Data Science and Analytics Talent Learn More
    Python is the New Excel Learn More

    Learn more about Domino 5

    See why over 20% of the Fortune 100 trust the Domino Enterprise MLOps platform for their mission-critical data science work.

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