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Racing into the future: How AWS DeepRacer fueled my AI and ML journey

AWS Machine Learning Blog

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer —a fully autonomous 1/18th scale race car driven by reinforcement learning. But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML.

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Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations

AWS Machine Learning Blog

During re:Invent 2023, we launched AWS HealthScribe , a HIPAA eligible service that empowers healthcare software vendors to build their clinical applications to use speech recognition and generative AI to automatically create preliminary clinician documentation.

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AWS and Accel Launch “ML Elevate 2023” to Empower India’s AI Startup Ecosystem

Analytics Vidhya

In an exciting collaboration, Amazon Web Services (AWS) and Accel have unveiled “ML Elevate 2023,” a revolutionary six-week accelerator program aimed at empowering startups in the generative artificial intelligence (AI) domain.

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WordFinder app: Harnessing generative AI on AWS for aphasia communication

AWS Machine Learning Blog

David Copland, from QARC, and Scott Harding, a person living with aphasia, used AWS services to develop WordFinder, a mobile, cloud-based solution that helps individuals with aphasia increase their independence through the use of AWS generative AI technology. The following diagram illustrates the solution architecture on AWS.

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PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023. In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning Blog

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions. Tuning these parameters can help limit the length or influence the randomness or diversity of the model’s response.

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Step-by-Step Roadmap to Become a Data Engineer in 2023

Analytics Vidhya

The post Step-by-Step Roadmap to Become a Data Engineer in 2023 appeared first on Analytics Vidhya. While not all of us are tech enthusiasts, we all have a fair knowledge of how Data Science works in our day-to-day lives. All of this is based on Data Science which is […].