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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. The following diagram illustrates the conceptual architecture of an AI assistant with Amazon Bedrock IDE.

AWS
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Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

We address the challenges of landmine risk estimation by enhancing existing datasets with rich relevant features, constructing a novel, robust, and interpretable ML model that outperforms standard and new baselines, and identifying cohesive hazard clusters under geographic and budgetary constraints.

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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Flipboard

Recent advances in generative AI have led to the rapid evolution of natural language to SQL (NL2SQL) technology, which uses pre-trained large language models (LLMs) and natural language to generate database queries in the moment. Toby also leads a program training the next generation of AI Solutions Architects.

SQL
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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning Blog

The growing need for cost-effective AI models The landscape of generative AI is rapidly evolving. Although GPT-4o has gained traction in the AI community, enterprises are showing increased interest in Amazon Nova due to its lower latency and cost-effectiveness. simple_w_condition Open Can i make cookies in an air fryer?

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

AWS
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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning Blog

This framework is designed as a compound AI system to drive the fine-tuning workflow for performance improvement, versatility, and reusability. Likewise, to address the challenges of lack of human feedback data, we use LLMs to generate AI grades and feedback that scale up the dataset for reinforcement learning from AI feedback ( RLAIF ).

AI
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Adobe enhances developer productivity using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

To address these challenges, Adobe partnered with the AWS Generative AI Innovation Center , using Amazon Bedrock Knowledge Bases and the Vector Engine for Amazon OpenSearch Serverless. For those interested in working with AWS on similar projects, visit Generative AI Innovation Center.

AWS