Favorite Large language models (LLMs) excel at generating human-like text but face a critical challenge: hallucination—producing responses that sound convincing but are factually incorrect. While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business
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Shared by AWS Machine Learning February 21, 2025
Favorite Generative AI is revolutionizing enterprise automation, enabling AI systems to understand context, make decisions, and act independently. Generative AI foundation models (FMs), with their ability to understand context and make decisions, are becoming powerful partners in solving sophisticated business problems. At AWS, we’re using the power of models in
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Shared by AWS Machine Learning February 21, 2025
Favorite Providing effective multilingual customer support in global businesses presents significant operational challenges. Through collaboration between AWS and DXC Technology, we’ve developed a scalable voice-to-voice (V2V) translation prototype that transforms how contact centers handle multi-lingual customer interactions. In this post, we discuss how AWS and DXC used Amazon Connect and
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Shared by AWS Machine Learning February 21, 2025
Favorite This post was written with Dian Xu and Joel Hawkins of Rocket Companies. Rocket Companies is a Detroit-based FinTech company with a mission to “Help Everyone Home”. With the current housing shortage and affordability concerns, Rocket simplifies the homeownership process through an intuitive and AI-driven experience. This comprehensive framework
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Shared by AWS Machine Learning February 21, 2025
Favorite This post is co-written with Sajin Jacob, Jerry Chen, Siddarth Mohanram, Luis Barbier, Kristen Chenowith, and Michelle Stahl from Verisk. Verisk (Nasdaq: VRSK) is a leading data analytics and technology partner for the global insurance industry. Through advanced analytics, software, research, and industry expertise across more than 20 countries,
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Shared by AWS Machine Learning February 20, 2025
Favorite Data is the lifeblood of modern applications, driving everything from application testing to machine learning (ML) model training and evaluation. As data demands continue to surge, the emergence of generative AI models presents an innovative solution. These large language models (LLMs), trained on expansive data corpora, possess the remarkable
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Shared by AWS Machine Learning February 20, 2025
Favorite Formula 1® (F1) races are high-stakes affairs where operational efficiency is paramount. During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as
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Shared by AWS Machine Learning February 19, 2025
Favorite At AWS re:Invent 2024, we launched a new innovation in Amazon SageMaker HyperPod on Amazon Elastic Kubernetes Service (Amazon EKS) that enables you to run generative AI development tasks on shared accelerated compute resources efficiently and reduce costs by up to 40%. Administrators can use SageMaker HyperPod task governance
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Shared by AWS Machine Learning February 19, 2025
Favorite Foundational models (FMs) and generative AI are transforming how financial service institutions (FSIs) operate their core business functions. AWS FSI customers, including NASDAQ, State Bank of India, and Bridgewater, have used FMs to reimagine their business operations and deliver improved outcomes. FMs are probabilistic in nature and produce a
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Shared by AWS Machine Learning February 19, 2025
Favorite Use Google Lens to search your screen within the Google app or Chrome on iOS. Plus, AI Overviews are coming to more Lens queries. View Original Source (blog.google/technology/ai/) Here.
Shared by AWS Machine Learning February 21, 2025
