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Talkdesk for Salesforce provides relief and recovery with industry solutions

Talkdesk

This technology package can reduce friction in the process with an end-to-end customer experience solution that streamlines the administration of PPP loans. Financial institutions can activate the Small Business Lending Solution in as little as 24 hours with some customers doing so in less than a day!

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23 Inspiring Women to Watch in 2023

TechSee

She is also an experienced National Account Manager with a demonstrated history of working in the hospitality industry. Caroline Yap, Director of AI Practice, Google Cloud – Caroline’s team accelerates customer transformations with AI and Industry Solutions, including Contact Center AI (CCAI), Vertex AI, and DocAI.

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Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

Prerequisites Before getting started, make sure you have the following prerequisites: An AWS account. Follow the instructions in Getting Started with the AWS CDK to set up your local environment and bootstrap your development account. We encourage you to deploy the AWS CDK app into your account and build the Generative AI solution.

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Amazon SageMaker Studio Lab continues to democratize ML with more scale and functionality

AWS Machine Learning

We made it simple to get started with just an email address, without the need for installs, setups, credit cards, or an AWS account. Going forward every customer be required to link their account to a mobile phone number. Eda Johnson, Partner Industry Solutions Manager at Snowflake. Customer success stories.

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Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

We also explore best practices for optimizing your batch inference workflows on Amazon Bedrock, helping you maximize the value of your data across different use cases and industries. Solution overview The batch inference feature in Amazon Bedrock provides a scalable solution for processing large volumes of data across various domains.

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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

Prerequisites In order to provision ML environments with the AWS CDK, complete the following prerequisites: Have access to an AWS account and permissions within the Region to deploy the necessary resources for different personas. Make sure you have the credentials and permissions to deploy the AWS CDK stack into your account.

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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. This walkthrough includes the following prerequisites: An AWS account. Otherwise, your account may hit the service quota limits of running an m5.4x