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Iterative fine-tuning on Amazon Bedrock for strategic model improvement

Iterative fine-tuning on Amazon Bedrock for strategic model improvement

Organizations often face challenges when implementing single-shot fine-tuning approaches for their generative AI models. The single-shot fine-tuning method involves selecting training data, configuring hyperparameters, and hoping the results meet expectations without the ability to make incremental adjustments. Single-shot fine-tuning frequently leads to suboptimal results and requires starting the entire process from scratch when improvements are …

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Voice AI-powered drive-thru ordering with Amazon Nova Sonic and dynamic menu displays

Voice AI-powered drive-thru ordering with Amazon Nova Sonic and dynamic menu displays

Artificial Intelligence (AI) is transforming the quick-service restaurant industry, particularly in drive-thru operations where efficiency and customer satisfaction intersect. Traditional systems create significant obstacles in service delivery, from staffing limitations and order accuracy issues to inconsistent customer experiences across locations. These challenges, combined with rising labor costs and demand fluctuations, have pushed the industry to …

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Optimizing document AI and structured outputs by fine-tuning Amazon Nova Models and on-demand inference

Optimizing document AI and structured outputs by fine-tuning Amazon Nova Models and on-demand inference

Multimodal fine-tuning represents a powerful approach for customizing vision large language models (LLMs) to excel at specific tasks that involve both visual and textual information. Although base multimodal models offer impressive general capabilities, they often fall short when faced with specialized visual tasks, domain-specific content, or output formatting requirements. Fine-tuning addresses these limitations by adapting …

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Transforming enterprise operations: Four high-impact use cases with Amazon Nova

Transforming enterprise operations: Four high-impact use cases with Amazon Nova

Since the launch of Amazon Nova at AWS re:Invent 2024, we have seen adoption trends across industries, with notable gains in operational efficiency, compliance, and customer satisfaction. With its capabilities in secure, multimodal AI and domain customization, Nova is enhancing workflows and enabling cost efficiencies across core use cases. In this post, we share four …

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Building smarter AI agents: AgentCore long-term memory deep dive

Building smarter AI agents: AgentCore long-term memory deep dive

Building AI agents that remember user interactions requires more than just storing raw conversations. While Amazon Bedrock AgentCore short-term memory captures immediate context, the real challenge lies in transforming these interactions into persistent, actionable knowledge that spans across sessions. This is the information that transforms fleeting interactions into meaningful, continuous relationships between users and AI …

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Configure and verify a distributed training cluster with AWS Deep Learning Containers on Amazon EKS

Configure and verify a distributed training cluster with AWS Deep Learning Containers on Amazon EKS

Training state-of-the-art large language models (LLMs) demands massive, distributed compute infrastructure. Meta’s Llama 3, for instance, ran on 16,000 NVIDIA H100 GPUs for over 30.84 million GPU hours. Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that simplifies the deployment, management, and scaling of Kubernetes clusters that can scale up to the ranges …

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Scala development in Amazon SageMaker Studio with Almond kernel

Scala development in Amazon SageMaker Studio with Almond kernel

Scala stands out as a versatile programming language that combines object-oriented and functional programming approaches. By running on the Java Virtual Machine (JVM), it maintains seamless compatibility with Java libraries while offering a concise and scalable development experience. The language has distinguished itself in the realm of distributed computing and big data processing, with the …

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