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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning Blog

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. In this post, we discuss how to operationalize generative AI applications using MLOps principles leading to foundation model operations (FMOps).

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How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

Data refinement: Raw data is refined into consumable layers (raw, processed, conformed, and analytical) using a combination of AWS Glue extract, transform, and load (ETL) jobs and EMR jobs. Deployment times stretched for months and required a team of three system engineers and four ML engineers to keep everything running smoothly.

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The Undisputed Champion of Open Source Generative AI

TheSequence

. 📝 Editorial: The Undisputed Champion of Open Source Generative AI Stability AI is synonymous with open-source generative AI. The release of Stable Diffusion was a sort of Sputnik moment in the evolution of open-source generative AI models. Union AI raised $19.1

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. This post is co-written with Jayadeep Pabbisetty, Sr.

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Bring your own AI using Amazon SageMaker with Salesforce Data Cloud

AWS Machine Learning Blog

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. Einstein Studio’s bring your own model (BYOM) experience provides the capability to connect custom or generative AI models from external platforms such as SageMaker to Data Cloud.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning Blog

Stephen is especially passionate about Security and Generative AI, and helping customers and partners architect secure, efficient, and innovative solutions on AWS. Bhajandeep Singh has served as the AWS AI/ML Center of Excellence Head at Wipro Technologies, leading customer engagements to deliver data analytics and AI solutions.

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Search enterprise data assets using LLMs backed by knowledge graphs

Flipboard

His mission is to enable customers achieve their business goals and create value with data and AI. He helps architect solutions across AI/ML applications, enterprise data platforms, data governance, and unified search in enterprises.

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