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Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A Closed-Loop Framework for Automating Scientific Research with Iterative Feedback

Marktechpost

Several research environments have been developed to automate the research process partially. Fudan University and the Shanghai Artificial Intelligence Laboratory have developed DOLPHIN, a closed-loop auto-research framework covering the entire scientific research process. In sentiment classification, DOLPHIN improved accuracy by 1.5%

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Improved ML model deployment using Amazon SageMaker Inference Recommender

AWS Machine Learning Blog

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. We train an XGBoost model for a classification task on a credit card fraud dataset. We demonstrate how to set up Inference Recommender jobs for a credit card fraud detection use case.

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How Kakao Games automates lifetime value prediction from game data using Amazon SageMaker and AWS Glue

AWS Machine Learning Blog

Statistical methods and machine learning (ML) methods are actively developed and adopted to maximize the LTV. In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality. Automation can significantly improve efficiency and reduce errors. Auto-generated audit logs : Record data interactions to understand how employees use data.

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From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. Along with protecting against toxicity and harmful content, it can also be used for Automated Reasoning checks , which helps you protect against hallucinations.

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Accelerating sustainable modernization with Green IT Analyzer on AWS

IBM Journey to AI blog

Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificial intelligence (AI) and machine learning (ML). This situation triggered an auto-scaling rule set to activate at 80% CPU utilization. Due to the auto-scaling of the new EC2 instances, an additional t2.large

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning Blog

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities.