Favorite Applications are now open for the first-ever Google for Startups Gemini Founders Forum, a two-day, in-person summit hosted by Google DeepMind and Google Cloud.Held Novem… View Original Source (blog.google/technology/ai/) Here.
Favorite Data science teams working with artificial intelligence and machine learning (AI/ML) face a growing challenge as models become more complex. While Amazon Deep Learning Containers (DLCs) offer robust baseline environments out-of-the-box, customizing them for specific projects often requires significant time and expertise. In this post, we explore how to
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Shared by AWS Machine Learning July 22, 2025
Favorite In 2024, the Ministry of Economy, Trade and Industry (METI) launched the Generative AI Accelerator Challenge (GENIAC)—a Japanese national program to boost generative AI by providing companies with funding, mentorship, and massive compute resources for foundation model (FM) development. AWS was selected as the cloud provider for GENIAC’s second
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Shared by AWS Machine Learning July 22, 2025
Favorite In the manufacturing world, valuable insights from service reports often remain underutilized in document storage systems. This post explores how Amazon Web Services (AWS) customers can build a solution that automates the digitisation and extraction of crucial information from many reports using generative AI. The solution uses Amazon Nova
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Shared by AWS Machine Learning July 21, 2025
Favorite This post was written with Zach Heath of Kyruus Health. When health plan members need care, they shouldn’t need a dictionary. Yet millions face this exact challenge—describing symptoms in everyday language while healthcare references clinical terminology and complex specialty classifications. This disconnect forces members to become amateur medical translators,
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Shared by AWS Machine Learning July 21, 2025
Favorite Extracting meaningful insights from unstructured data presents significant challenges for many organizations. Meeting recordings, customer interactions, and interviews contain invaluable business intelligence that remains largely inaccessible due to the prohibitive time and resource costs of manual review. Organizations frequently struggle to efficiently capture and use key information from these
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Shared by AWS Machine Learning July 21, 2025
Favorite Vector embeddings have become essential for modern Retrieval Augmented Generation (RAG) applications, but organizations face significant cost challenges as they scale. As knowledge bases grow and require more granular embeddings, many vector databases that rely on high-performance storage such as SSDs or in-memory solutions become prohibitively expensive. This cost
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Shared by AWS Machine Learning July 18, 2025
Favorite Evaluating the performance of large language models (LLMs) goes beyond statistical metrics like perplexity or bilingual evaluation understudy (BLEU) scores. For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. This is especially important for
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Shared by AWS Machine Learning July 18, 2025
Favorite Successful generative AI software as a service (SaaS) systems require a balance between service scalability and cost management. This becomes critical when building a multi-tenant generative AI service designed to serve a large, diverse customer base while maintaining rigorous cost controls and comprehensive usage monitoring. Traditional cost management approaches
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Shared by AWS Machine Learning July 18, 2025
Favorite AI-powered speech solutions are transforming contact centers by enabling natural conversations between customers and AI agents, shortening wait times, and dramatically reducing operational costs—all without sacrificing the human-like interaction customers expect. With the recent launch of Amazon Nova Sonic in Amazon Bedrock, you can now build sophisticated conversational AI
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Shared by AWS Machine Learning July 18, 2025