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HR and Talent in the Era of AI

IBM Journey to AI blog

In this new era, however, generative AI can deliver more using targeted advisors and the use cases that benefit from it will continue to expand. Processes such as job description creation, auto-grading video interviews and intelligent search that once required a human employee can now be completed using data-driven insights and generative AI.

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Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC

AWS Machine Learning Blog

This feature streamlines the process of launching new instances with the most up-to-date Neuron SDK, enabling you to automate your deployment workflows and make sure you’re always using the latest optimizations. AWS Systems Manager Parameter Store support Neuron 2.18 neuronx-py310-sdk2.18.2-ubuntu20.04 COPY train.py /train.py

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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning Blog

These generative AI applications are not only used to automate existing business processes, but also have the ability to transform the experience for customers using these applications. When you create an AWS account, you get a single sign-on (SSO) identity that has complete access to all the AWS services and resources in the account.

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Unearth insights from audio transcripts generated by Amazon Transcribe using Amazon Bedrock

AWS Machine Learning Blog

time.sleep(10) The transcription job will take a few minutes to complete. When the job is complete, you can inspect the transcription output and check the plain text transcript that was generated (the following has been trimmed for brevity): # Get the Transcribe Output JSON file s3 = boto3.client('s3') Current status is {job_status}.")