Favorite Embedding models power many modern applications—from semantic search and Retrieval-Augmented Generation (RAG) to recommendation systems and content understanding. However, selecting an embedding model requires careful consideration—after you’ve ingested your data, migrating to a different model means re-embedding your entire corpus, rebuilding vector indexes, and validating search quality from scratch.
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Shared by AWS Machine Learning February 6, 2026
Favorite This is a guest post co-written with David Meredith and Josh Zacharias from Associa. Associa, North America’s largest community management company, oversees approximately 7.5 million homeowners with 15,000 employees across more than 300 branch offices. The company manages approximately 48 million documents across 26 TB of data, but their
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Shared by AWS Machine Learning February 6, 2026
Favorite Learn how Google’s NAI framework uses AI to make technology more adaptive, inclusive and helpful for everyone. View Original Source (blog.google/technology/ai/) Here.
Favorite Google Cloud built an industry-first AI tool to help U.S. Ski and Snowboard athletes. View Original Source (blog.google/technology/ai/) Here.
Favorite Learn more about Google’s new ad that will run during football’s Big Game on February 8. View Original Source (blog.google/technology/ai/) Here.
Favorite Marketing teams face major challenges creating campaigns in today’s digital environment. They must navigate through complex data analytics and rapidly changing consumer preferences to produce engaging, personalized content across multiple channels while maintaining brand consistency and working within tight deadlines. Using generative AI can streamline and accelerate the creative
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Shared by AWS Machine Learning February 5, 2026
Favorite Google AI announcements from January View Original Source (blog.google/technology/ai/) Here.
Favorite Performing research and clinical analytics on vast amounts of clinical data can be difficult. Healthcare data scientists and epidemiologists possess deep domain expertise in patient care, disease patterns, and clinical outcomes, yet they often spend weeks navigating complex data infrastructures, writing boilerplate code, and wrestling with technical barriers before
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Shared by AWS Machine Learning February 4, 2026
Favorite Building production-ready AI agents requires careful planning and execution across the entire development lifecycle. The difference between a prototype that impresses in a demo and an agent that delivers value in production is achieved through disciplined engineering practices, robust architecture, and continuous improvement. This post explores nine essential best
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Shared by AWS Machine Learning February 4, 2026
Favorite Many organizations need to manage file uploads across different cloud storage systems while maintaining security and compliance. Although Google Drive provides APIs for integration, organizations often don’t have the technical experts to interact with these APIs directly. Organizations need an intuitive way to handle file uploads using natural language,
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Shared by AWS Machine Learning February 4, 2026
Shared by AWS Machine Learning February 6, 2026
