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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. At the time, I knew little about AI or machine learning (ML). seconds, securing the 2018 AWS DeepRacer grand champion title!

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AWS doubles investment in AWS Generative AI Innovation Center, marking two years of customer success

AWS Machine Learning Blog

When we launched the AWS Generative AI Innovation Center in 2023, we had one clear goal: help customers turn AI potential into real business value. We combine Amazon’s decades of AI leadership with deep technical knowledge and extensive, secure real-world deployment experience.

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AWS achieves ISO/IEC 42001:2023 Artificial Intelligence Management System accredited certification

AWS Machine Learning Blog

Amazon Web Services (AWS) is excited to be the first major cloud service provider to announce ISO/IEC 42001 accredited certification for AI services, covering: Amazon Bedrock , Amazon Q Business , Amazon Textract , and Amazon Transcribe. Responsible AI is a long-standing commitment at AWS.

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

AWS Machine Learning Blog

With the advent of generative AI and machine learning, new opportunities for enhancement became available for different industries and processes. AWS HealthScribe combines speech recognition and generative AI trained specifically for healthcare documentation to accelerate clinical documentation and enhance the consultation experience.

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Build generative AI applications on Amazon Bedrock with the AWS SDK for Python (Boto3)

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning Blog

Companies across all industries are harnessing the power of generative AI to address various use cases. Cloud providers have recognized the need to offer model inference through an API call, significantly streamlining the implementation of AI within applications.

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

AWS Machine Learning Blog

To reduce costs while continuing to use the power of AI , many companies have shifted to fine tuning LLMs on their domain-specific data using Parameter-Efficient Fine Tuning (PEFT). Manually managing such complexity can often be counter-productive and take away valuable resources from your businesses AI development.

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