Gen AI News Talk
How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AI
This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health.
Omada Health, a longtime innovator in virtual healthcare delivery, launched a new...
Crossmodal search with Amazon Nova Multimodal Embeddings
Amazon Nova Multimodal Embeddings processes text, documents, images, video, and audio through a single model architecture. Available through Amazon Bedrock, the model converts different...
Accelerating LLM inference with post-training weight and activation using AWQ and GPTQ on Amazon...
Foundation models (FMs) and large language models (LLMs) have been rapidly scaling, often doubling in parameter count within months, leading to significant improvements in...
Sentiment Analysis with Text and Audio Using AWS Generative AI Services: Approaches, Challenges, and...
This post is co-written by Instituto de Ciência e Tecnologia Itaú (ICTi) and AWS.
Sentiment analysis has grown increasingly important in modern enterprises, providing insights...
Architecting TrueLook’s AI-powered construction safety system on Amazon SageMaker AI
This post is co-written by TrueLook and AWS.
TrueLook is a construction camera and jobsite intelligence company that provides real-time visibility into construction projects. Its...
How Beekeeper optimized user personalization with Amazon Bedrock
This post is cowritten by Mike Koźmiński from Beekeeper.
Large Language Models (LLMs) are evolving rapidly, making it difficult for organizations to select the best...
Scaling medical content review at Flo Health using Amazon Bedrock (Part 1)
This blog post is based on work co-developed with Flo Health.
Healthcare science is rapidly advancing. Maintaining accurate and up-to-date medical content directly impacts people’s...
Speed meets scale: Load testing SageMakerAI endpoints with Observe.AI’s testing tool
This post is cowritten with Aashraya Sachdeva from Observe.ai.
You can use Amazon SageMaker to build, train and deploy machine learning (ML) models, including large...
Detect and redact personally identifiable information using Amazon Bedrock Data Automation and Guardrails
Organizations handle vast amounts of sensitive customer information through various communication channels. Protecting Personally Identifiable Information (PII), such as social security numbers (SSNs), driver’s...
Migrate MLflow tracking servers to Amazon SageMaker AI with serverless MLflow
Operating a self-managed MLflow tracking server comes with administrative overhead, including server maintenance and resource scaling. As teams scale their ML experimentation, efficiently managing...
