AWS re:Invent 2024 Highlights: Top takeaways from Swami Sivasubramanian to help customers manage generative AI at scale

TutoSartup excerpt from this article:
Companies like Rocket Mortgage are building on an AI-driven platform powered by Amazon Bedrock to create AI agents and automate tasks—working to give their employees access to generative AI with no-code tools... Q: Are there key innovations that build on the experience and lessons learned at Amazon in adopting generative AI? How are you bringing those capabilities to your customers Swami Siva...

And that’s a wrap!

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After 20 years, and 3283 posts adding up to 1,577,106 words I am wrapping up my time as the lead blogger on the AWS News Blog... It has also been a privilege to be able to meet and to hear from so many of you that have faithfully read and (hopefully) learned from my content over the years... Over the years I have written tens of thousands of lines of assembly code (6502, Z80, and 68000), Visual Ba...

AWS Weekly Roundup: Amazon EC2 F2 instances, Amazon Bedrock Guardrails price reduction, Amazon SES update, and more (December 16, 2024)

TutoSartup excerpt from this article:
This year Andy Jassy, now President and CEO at Amazon, returned to re:Invent and shared some thoughts in these videos... Drawing on experiences Amazon has had building distributed systems at massive scale, Werner Vogels, VP and CTO at Amazon, shared critical lessons and strategies he has learned for managing complex systems in his keynote... Amazon Elastic Compute Cloud (Amazon EC2) – A new...

Multi-tenant RAG with Amazon Bedrock Knowledge Bases

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For organizations developing multi-tenant products, such as independent software vendors (ISVs) creating software as a service (SaaS) offerings, the ability to personalize experiences for each of their customers (tenants in their SaaS application) is particularly significant... This personalization can be achieved by implementing a RAG approach that selectively uses tenant-specific data... We fo...

How Amazon trains sequential ensemble models at scale with Amazon SageMaker Pipelines

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This helps with data preparation and feature engineering tasks and model training and deployment automation... In this post, we provide an example of an ensemble model that was trained and deployed using Pipelines... With the ability to preprocess incoming data prior to training, we can make sure that our models are fed with high-quality data... We need a compute environment that is highly sca...

Implementing login node load balancing in SageMaker HyperPod for enhanced multi-user experience

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His expertise spans machine learning, data engineering, and scalable distributed systems, augmented by a strong background in software engineering and industry expertise in domains such as autonomous driving... In these clusters, the concept of login nodes is available, which cluster administrators can add to facilitate user access... These login nodes serve as the entry point through which users...

How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart

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Recognized for his innovative problem-solving skills and ability to lead cross-functional teams, Dan leverages his extensive software engineering background and strong communication abilities to bridge the gap between complex AI concepts and practical business solutions... A great example of such innovation is our customer Clearwater Analytics and their use of large language models (LLMs) hosted ...