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Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

At the AWS Summit in New York City, we introduced a comprehensive suite of model customization capabilities for Amazon Nova foundation models. Available as ready-to-use recipes on Amazon SageMaker AI, you can use them to adapt Nova Micro, Nova Lite, and Nova Pro across the model training lifecycle, including pre-training, supervised fine-tuning, and alignment. In this …

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Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach to address this challenge. RAG is …

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Enhance generative AI solutions using Amazon Q index with Model Context Protocol – Part 1

Enhance generative AI solutions using Amazon Q index with Model Context Protocol – Part 1

Today’s enterprises increasingly rely on AI-driven applications to enhance decision-making, streamline workflows, and deliver improved customer experiences. Achieving these outcomes demands secure, timely, and accurate access to authoritative data—especially when such data resides across diverse repositories and applications within strict enterprise security boundaries. Interoperable technologies powered by open standards like the Model Context Protocol (MCP) …

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Beyond accelerators: Lessons from building foundation models on AWS with Japan’s GENIAC program

Beyond accelerators: Lessons from building foundation models on AWS with Japan’s GENIAC program

In 2024, the Ministry of Economy, Trade and Industry (METI) launched the Generative AI Accelerator Challenge (GENIAC)—a Japanese national program to boost generative AI by providing companies with funding, mentorship, and massive compute resources for foundation model (FM) development. AWS was selected as the cloud provider for GENIAC’s second cycle (cycle 2). It provided infrastructure …

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Streamline deep learning environments with Amazon Q Developer and MCP

Streamline deep learning environments with Amazon Q Developer and MCP

Data science teams working with artificial intelligence and machine learning (AI/ML) face a growing challenge as models become more complex. While Amazon Deep Learning Containers (DLCs) offer robust baseline environments out-of-the-box, customizing them for specific projects often requires significant time and expertise. In this post, we explore how to use Amazon Q Developer and Model …

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Build an AI-powered automated summarization system with Amazon Bedrock and Amazon Transcribe using Terraform

Build an AI-powered automated summarization system with Amazon Bedrock and Amazon Transcribe using Terraform

Extracting meaningful insights from unstructured data presents significant challenges for many organizations. Meeting recordings, customer interactions, and interviews contain invaluable business intelligence that remains largely inaccessible due to the prohibitive time and resource costs of manual review. Organizations frequently struggle to efficiently capture and use key information from these interactions, resulting in not only productivity …

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