Remove AI Modeling Remove ETL Remove ML Engineer
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Bring your own AI using Amazon SageMaker with Salesforce Data Cloud

AWS Machine Learning Blog

With this capability, businesses can access their Salesforce data securely with a zero-copy approach using SageMaker and use SageMaker tools to build, train, and deploy AI models. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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The Undisputed Champion of Open Source Generative AI

TheSequence

The release of Stable Diffusion was a sort of Sputnik moment in the evolution of open-source generative AI models. For the first time, a company was trusting the benefits of open-source distribution ahead of the ethical concerns associated with generative AI models. Union AI raised $19.1

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning Blog

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.