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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. With this launch, customers can now seamlessly share and access ML models registered in SageMaker Model Registry between different AWS accounts.

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How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning

Growing in the media and entertainment space, Veritone solves media management, broadcast content, and ad tracking issues. Amazon Transcribe The transcription for the entire video is generated using the StartTranscriptionJob API. The metadata generated for each video by the APIs is processed and stored with timestamps.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers. For integration between services, we use API Gateway as an event trigger for our Lambda function, and DynamoDB as a highly scalable database to store our customer details.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. In Part 1, we focus on creating accurate and reliable agents.

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Build a news recommender application with Amazon Personalize

AWS Machine Learning

A Lambda function performs the same data transformation operations as the batch ingestion job at the individual record level, and ingests the data into Amazon Personalize using the PutEvents and PutItems APIs. For more information about these metrics, see Evaluating a solution version with metrics.

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Semantic image search for articles using Amazon Rekognition, Amazon SageMaker foundation models, and Amazon OpenSearch Service

AWS Machine Learning

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

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How Games24x7 transformed their retraining MLOps pipelines with Amazon SageMaker

AWS Machine Learning

Games24x7 is one of India’s most valuable multi-game platforms and entertains over 100 million gamers across various skill games. All the training and evaluation metrics were inspected manually from Amazon Simple Storage Service (Amazon S3). This is a guest blog post co-written with Hussain Jagirdar from Games24x7. cpu-py39-ubuntu20.04-sagemaker",

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