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

AWS Machine Learning Blog

At the time, I knew little about AI or machine learning (ML). But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML. Panic set in as we realized we would be competing on stage in front of thousands of people while knowing little about ML.

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Easily deploy and manage hundreds of LoRA adapters with SageMaker efficient multi-adapter inference

AWS Machine Learning Blog

For example, marketing and software as a service (SaaS) companies can personalize artificial intelligence and machine learning (AI/ML) applications using each of their customer’s images, art style, communication style, and documents to create campaigns and artifacts that represent them. year-over-year (13.8% on a GAAP basis, 57.9%

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Build Interactive Machine Learning Apps with Gradio

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Publish AI, ML & data-science insights to a global community of data professionals. In this blog, we’ll take a fun, hands-on approach to learning the key Gradio components by building a text-to-speech (TTS) web application that you can run on an AI PC or Intel® Tiber™ AI Cloud and share with others.

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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning Blog

The call processing workflow uses custom machine learning (ML) models built by Intact that run on Amazon Fargate and Amazon Elastic Compute Cloud (Amazon EC2). This pipeline provides self-serving capabilities for data scientists to track ML experiments and push new models to an S3 bucket.

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How Qualtrics built Socrates: An AI platform powered by Amazon SageMaker and Amazon Bedrock

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Qualtrics harnesses the power of generative AI, cutting-edge machine learning (ML), and the latest in natural language processing (NLP) to provide new purpose-built capabilities that are precision-engineered for experience management (XM). To learn more about how AI is transforming experience management, visit this blog from Qualtrics.

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Life beyond the leaderboard

DrivenData Labs

It often serves as an ongoing reference to benchmark and demonstrate development efforts in the broader ML/AI ecosystem. For example, following the Hateful Memes challenge, the research team at Meta AI published the results in the Proceedings of Machine Learning Research and discussed them at NeurIPS 2020.

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How climate tech startups are building foundation models with Amazon SageMaker HyperPod

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For more information on how SageMaker HyperPods resiliency helps save costs while training, check out Reduce ML training costs with Amazon SageMaker HyperPod. For example, Amazon is the largest corporate purchaser of renewable energy in the world, every year since 2020. We have made significant progress over the years.

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