Remove 2012 Remove Explainability Remove Metadata
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Yehuda Holtzman, CEO of Cipia – Interview Series

Unite.AI

Yehuda was also a co-founder of the software company ExploreGate, where he served as CEO from 2012 to 2016, as well as co-founder of MobileAccess, where he served as President of the company through its acquisition by Corning Incorporated In 2011. Can you explain the advantages of lean edge processing in Cipia’s solutions?

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Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning Blog

The generated response is divided into three parts: The context explains what the architecture diagram depicts. Ref S3BucketName, '/*']] - PolicyName: SNSPublish PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - 'sns:Publish' Resource: !Ref Second, we want to add metadata to the CloudFormation template.

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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

Generative AI solutions often use Retrieval Augmented Generation (RAG) architectures, which augment external knowledge sources for improving content quality, context understanding, creativity, domain-adaptability, personalization, transparency, and explainability. This can potentially improve the accuracy and quality of search results.

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Optimized Deep Learning Pipelines: A Deep Dive into TFRecords and Protobufs (Part 2)

Heartbeat

We can use this opportunity to not only convert these images from JPG to TFRecords, but when converting them, we can even write them with their appropriate label and any other metadata we wish to store with the image itself. jpg': {'class': 132, 'label': 'Hyundai Tucson SUV 2012'}, '00235.jpg':

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Manage Amazon SageMaker JumpStart foundation model access with private hubs

AWS Machine Learning Blog

These can be added as inline policies in the user’s IAM role: { "Version": "2012-10-17", "Statement": [ { "Action": "s3:*", "Effect": "Deny", "Resource": [ "arn:aws:s3:::jumpstart-cache-prod- ", "arn:aws:s3:::jumpstart-cache-prod- /*" ], "Condition": { "StringNotLike": {"s3:prefix": ["*.ipynb",

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Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

AWS Machine Learning Blog

You will see an Amazon Simple Storage Service (Amazon S3) link to a metadata file. On the IAM console, navigate to the SageMaker domain execution role. Choose Add permissions and select Create an inline policy. Copy and paste the link into a new browser tab URL. Let’s look at the file without downloading it.

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Real-Real-World Programming with ChatGPT

O'Reilly Media

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.

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