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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. Enable a data science team to manage a family of classic ML models for benchmarking statistics across multiple medical units.

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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning

This is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. When summarizing healthcare texts, pre-trained LLMs do not always achieve optimal performance.

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Reduce conversational AI response time through inference at the edge with AWS Local Zones

AWS Machine Learning

Their applications span a variety of sectors, including customer service, healthcare, education, personal and business productivity, and many others. They enable applications requiring very low latency or local data processing using familiar APIs and tool sets.

APIs 78
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 120
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A progress update on our commitment to safe, responsible generative AI

AWS Machine Learning

Red-teaming engages human testers to probe an AI system for flaws in an adversarial style, and complements our other testing techniques, which include automated benchmarking against publicly available and proprietary datasets, human evaluation of completions against proprietary datasets, and more.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. In Part 1, we focus on creating accurate and reliable agents.

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How CPQ Helps B2B eCommerce Businesses Close More Deals Faster

Cincom

4- Improving Deal Closure Rates with Real-Time Insights CPQ provides real-time analytics on customer preferences, pricing trends, and competitor benchmarks. Select a solution that supports API-based integration with your existing eCommerce platform (e.g., Shopify, Magento, Salesforce Commerce Cloud).

B2B 40