Remove Categorization Remove Metadata Remove Software Engineer
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Autonomous Agents with AgentOps: Observability, Traceability, and Beyond for your AI Application

Unite.AI

These agents perform tasks ranging from customer support to software engineering, navigating intricate workflows that combine reasoning, tool use, and memory. The authors categorize traceable artifacts, propose key features for observability platforms, and address challenges like decision complexity and regulatory compliance.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning Blog

However, model governance functions in an organization are centralized and to perform those functions, teams need access to metadata about model lifecycle activities across those accounts for validation, approval, auditing, and monitoring to manage risk and compliance. Model risk : Risk categorization of the model version.

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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning Blog

Organizations across industries want to categorize and extract insights from high volumes of documents of different formats. Categorizing documents is an important first step in IDP systems. An S3 prefix or S3 object metadata can be used to classify gallery images. George Belsian is a Senior Cloud Application Architect at AWS.

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STUDY: Socially aware temporally causal decoder recommender systems

Google Research AI blog

Furthermore all potentially identifiable metadata was only shared in an aggregated form, to protect students and institutions from being re-identified. Acknowledgements This work involved collaborative efforts from a multidisciplinary team of researchers, software engineers and educational subject matter experts.

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Learnings From Teams Training Large-Scale Models: Challenges and Solutions For Monitoring at Hyperscale

The MLOps Blog

Igor Tsvetkov Former Senior Staff Software Engineer, Cruise AI teams automating error categorization and correlation can significantly reduce debugging time in hyperscale environments, just as Cruise has done. GPU memory leaks, network latency) or software bugs (e.g.,

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MLflow: Simplifying Machine Learning Experimentation

Viso.ai

This issue becomes even more difficult when code is passed between different roles, such as from a data scientist to a software engineer for deployment. Local Tracking with Database: You can use a local database to manage experiment metadata for a cleaner setup compared to local files. Can have tags for tracking attributes (e.g.,

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How 123RF saved over 90% of their translation costs by switching to Amazon Bedrock

AWS Machine Learning Blog

This post explores how 123RF used Amazon Bedrock, Anthropic’s Claude 3 Haiku, and a vector store to efficiently translate content metadata, significantly reduce costs, and improve their global content discovery capabilities. Metadata such as the content type, domain, and any relevant tags. The corresponding translation chunk.