This session demonstrates how to use large language models (LLMs) to translate ideas directly into cloud architecture blueprints. You’ll learn how to generate designs from these blueprints with natural language processing. We’ll also use an existing LLM model specialized in code generation to understand our language dialect to generate cloud architecture diagrams. Finally, we'll also show you a web app on Google Cloud that allows users to interact with the model and use the generated artifacts in practice.

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Join us to learn how DaVita leverages DocAI and Healthcare NLP to transform kidney care. This session highlights the power of AI in analyzing medical records, uncovering critical patient insights, and reducing errors. Discover how AI enables physicians to focus on personalized care, resulting in significant improvements in healthcare delivery. Join us for this Mini Talk at 'Meet the Experts, hosted by Google Cloud Consulting' at Expo. Seating is limited and on a first-come, first served basis; standing areas are available.

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Join us for an insightful session that explores the exciting future of Google Cloud‘s managed databases, including Cloud SQL, AlloyDB, and Spanner. Vector search capabilities deeply integrated into operational databases enable powerful enterprise generative AI apps. Additionally, learn how AI has the potential to revolutionize the way applications interact with databases. We will delve into exciting frontiers: Natural language processing in databases, and app migration with large language model-powered code migration.

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The latest Google Compute Engine instance families have built-in AI hardware accelerators delivering GPU-level performance for computer vision, natural language processing, speech recognition, recommendation engines, and generative AI models all powered by the latest Intel 4th and 5th gen Xeon CPUs. We will demo a real-time chatbot and CodeGen generative AI application, share performance results across various AI workloads, and highlight our partnerships with the AI software ecosystem and Google Cloud end users.

By attending this session, your contact information may be shared with the sponsor for relevant follow up for this event only.

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Explore Mongodb Atlas — MongoDB’s developer data platform, and learn how to integrate it with various Google Cloud services. During this lab lounge, you will create a fully managed database deployment, set up serverless Triggers that react to database events, and build Atlas Functions to communicate with Google Cloud APIs.

Additionally, you will explore Google Cloud’s NLP APIs, perform sentiment analysis on incoming data, learn how to replicate operational datasets from MongoDB Atlas to BigQuery and build an ML model for classification.

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Large language models offer capabilities that overlap with more traditional approaches to natural language processing tasks like translation. Multimodal large language models have an even broader overlap with traditional speech and image models. You can now choose which approach best suits your needs. Here, you will learn about their strengths and weaknesses compared to neural machine translation techniques and receive an overview of the latest advancements in our SOTA Cloud Translation API, combing ease of use with contextual capabilities of generative AI models, to enhance our customers' translations at scale. Experience how new models trained to perform both transcription and translation can go from speech to text in a target language using one large model.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.