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AI courses to boost your skills and stay ahead

AI News

Participants learn the basics of AI, strategies for aligning their career paths with AI advancements, and how to use AI responsibly. The course is ideal for individuals at any career stage who wish to understand AI’s impact on the job market and adapt proactively.

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AI Bias & Cultural Stereotypes: Effects, Limitations, & Mitigation

Unite.AI

Artificial Intelligence (AI), particularly Generative AI , continues to exceed expectations with its ability to understand and mimic human cognition and intelligence. However, in many cases, the outcomes or predictions of AI systems can reflect various types of AI bias, such as cultural and racial.

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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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Meta SAM 2.1 is now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

in SageMaker JumpStart SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the SageMaker Python SDK. Alternatively, you can use the SageMaker Python SDK to programmatically access and use SageMaker JumpStart models. You can deploy any of the selected models on SageMaker AI. Deploy Meta SAM 2.1

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Build a RAG-based QnA application using Llama3 models from SageMaker JumpStart

AWS Machine Learning Blog

Organizations generate vast amounts of data that is proprietary to them, and it’s critical to get insights out of the data for better business outcomes. Generative AI and foundation models (FMs) play an important role in creating applications using an organization’s data that improve customer experiences and employee productivity.

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Mixtral 8x22B is now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

You can now discover and deploy Mixtral-8x22B with a few clicks in Amazon SageMaker Studio or programmatically through the SageMaker Python SDK, enabling you to derive model performance and MLOps controls with SageMaker features such as Amazon SageMaker Pipelines , Amazon SageMaker Debugger , or container logs. Preston Tuggle is a Sr.

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Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

AWS Machine Learning Blog

For more information on Trainium Accelerator chips, refer to Achieve high performance with lowest cost for generative AI inference using AWS Inferentia2 and AWS Trainium on Amazon SageMaker. This image is also compatible with Python 3.10, indicated by the py310, and is based on Ubuntu 20.04.