HLTH 2023: Bringing AI to health responsibly
Favorite Google leaders take the stage at HLTH to discuss the transformative power of AI for health. View Original Source (blog.google/technology/ai/) Here.
Build an image-to-text generative AI application using multimodality models on Amazon SageMaker
Favorite As we delve deeper into the digital era, the development of multimodality models has been critical in enhancing machine understanding. These models process and generate content across various data forms, like text and images. A key feature of these models is their image-to-text capabilities, which have shown remarkable proficiency
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Shared by AWS Machine Learning October 6, 2023
Personalize your generative AI applications with Amazon SageMaker Feature Store
Favorite Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. The applications also extend into retail, where they can enhance customer experiences through dynamic chatbots and AI assistants, and into digital marketing, where they can organize customer feedback and recommend
Read More Shared by AWS Machine Learning October 6, 2023
A personal letter from Catharina Maracke, Chair of the Open Source Initiative
Favorite Dear OSI Community, I trust this message finds you well. It is with mixed emotions that I announce my decision to step down from my role as Chair of the Open Source Initiative (OSI). This transition has not been an easy one, but I believe it is the right
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Shared by voicesofopensource October 6, 2023
Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium
Favorite Large language models (LLMs) have captured the imagination and attention of developers, scientists, technologists, entrepreneurs, and executives across several industries. These models can be used for question answering, summarization, translation, and more in applications such as conversational agents for customer support, content creation for marketing, and coding assistants. Recently,
Read More Shared by AWS Machine Learning October 5, 2023
Improve prediction quality in custom classification models with Amazon Comprehend
Favorite Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption across enterprise and government organizations. Processing unstructured data has become easier with the advancements in natural language processing (NLP) and user-friendly AI/ML services like Amazon Textract, Amazon Transcribe, and Amazon Comprehend. Organizations have started to use AI/ML services
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Automate prior authorization using CRD with CDS Hooks and AWS HealthLake
Favorite Prior authorization is a crucial process in healthcare that involves the approval of medical treatments or procedures before they are carried out. This process is necessary to ensure that patients receive the right care and that healthcare providers are following the correct procedures. However, prior authorization can be a
Read More Shared by AWS Machine Learning October 4, 2023
Create an HCLS document summarization application with Falcon using Amazon SageMaker JumpStart
Favorite Healthcare and life sciences (HCLS) customers are adopting generative AI as a tool to get more from their data. Use cases include document summarization to help readers focus on key points of a document and transforming unstructured text into standardized formats to highlight important attributes. With unique data formats
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Simplify medical image classification using Amazon SageMaker Canvas
Favorite Analyzing medical images plays a crucial role in diagnosing and treating diseases. The ability to automate this process using machine learning (ML) techniques allows healthcare professionals to more quickly diagnose certain cancers, coronary diseases, and ophthalmologic conditions. However, one of the key challenges faced by clinicians and researchers in
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Scalable spherical CNNs for scientific applications
Favorite Posted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research, Athena Team Typical deep learning models for computer vision, like convolutional neural networks (CNNs) and vision transformers (ViT), process signals assuming planar (flat) spaces. For example, digital images are represented as a grid of pixels on a plane.
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Shared by Google AI Technology October 4, 2023