AWS Machine Learning Blog
Category: Advanced (300)
Streamline workflow orchestration of a system of enterprise APIs using chaining with Amazon Bedrock Agents
In this post, we explore how chaining domain-specific agents using Amazon Bedrock Agents can transform a system of complex API interactions into streamlined, adaptive workflows, empowering your business to operate with agility and precision.
How healthcare payers and plans can empower members with generative AI
In this post, we discuss how generative artificial intelligence (AI) can help health insurance plan members get the information they need. The solution presented in this post not only enhances the member experience by providing a more intuitive and user-friendly interface, but also has the potential to reduce call volumes and operational costs for healthcare payers and plans.
Align Meta Llama 3 to human preferences with DPO, Amazon SageMaker Studio, and Amazon SageMaker Ground Truth
In this post, we show you how to enhance the performance of Meta Llama 3 8B Instruct by fine-tuning it using direct preference optimization (DPO) on data collected with SageMaker Ground Truth.
Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval
In this post, we discuss best practices for working with Foundation Model Evaluations Library (FMEval) in ground truth curation and metric interpretation for evaluating question answering applications for factual knowledge and quality.
Implementing advanced prompt engineering with Amazon Bedrock
In this post, we provide insights and practical examples to help balance and optimize the prompt engineering workflow. We focus on advanced prompt techniques and best practices for the models provided in Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models from leading AI companies such as Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. With these prompting techniques, developers and researchers can harness the full capabilities of Amazon Bedrock, providing clear and concise communication while mitigating potential risks or undesirable outputs.
Get the most from Amazon Titan Text Premier
In this post, we introduce the new Amazon Titan Text Premier model, specifically optimized for enterprise use cases, such as building Retrieval Augmented Generation (RAG) and agent-based applications. Such integrations enable advanced applications like building interactive AI assistants that use enterprise APIs and interact with your propriety documents.
GenASL: Generative AI-powered American Sign Language avatars
In this post, we dive into the architecture and implementation details of GenASL, which uses AWS generative AI capabilities to create human-like ASL avatar videos. GenASL is a solution that translates speech or text into expressive ASL avatar animations, bridging the gap between spoken and written language and sign language.
Elevate healthcare interaction and documentation with Amazon Bedrock and Amazon Transcribe using Live Meeting Assistant
Today, physicians spend about 49% of their workday documenting clinical visits, which impacts physician productivity and patient care. Did you know that for every eight hours that office-based physicians have scheduled with patients, they spend more than five hours in the EHR? As a consequence, healthcare practitioners exhibit a pronounced inclination towards conversational intelligence solutions, […]
Improve AI assistant response accuracy using Knowledge Bases for Amazon Bedrock and a reranking model
AI chatbots and virtual assistants have become increasingly popular in recent years thanks the breakthroughs of large language models (LLMs). Trained on a large volume of datasets, these models incorporate memory components in their architectural design, allowing them to understand and comprehend textual context. Most common use cases for chatbot assistants focus on a few […]
Inference AudioCraft MusicGen models using Amazon SageMaker
Music generation models have emerged as powerful tools that transform natural language text into musical compositions. Originating from advancements in artificial intelligence (AI) and deep learning, these models are designed to understand and translate descriptive text into coherent, aesthetically pleasing music. Their ability to democratize music production allows individuals without formal training to create high-quality […]