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Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

AWS Machine Learning - AI

National Laboratory has implemented an AI-driven document processing platform that integrates named entity recognition (NER) and large language models (LLMs) on Amazon SageMaker AI. In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

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Foundation Model for Personalized Recommendation

Netflix Tech

By Ko-Jen Hsiao , Yesu Feng and Sudarshan Lamkhede Motivation Netflixs personalized recommender system is a complex system, boasting a variety of specialized machine learned models each catering to distinct needs including Continue Watching and Todays Top Picks for You.

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Creating asynchronous AI agents with Amazon Bedrock

AWS Machine Learning - AI

Advancements in multimodal artificial intelligence (AI), where agents can understand and generate not just text but also images, audio, and video, will further broaden their applications. This post will discuss agentic AI driven architecture and ways of implementing.

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Understanding Retrieval-Augmented Generation (RAG) on Google Cloud Platform (GCP)

Xebia

Retrieval-Augmented Generation (RAG) is a key technique powering more broad and trustworthy application of large language models (LLMs). By integrating external knowledge sources, RAG addresses limitations of LLMs, such as outdated knowledge and hallucinated responses.

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How Vidmob is using generative AI to transform its creative data landscape

AWS Machine Learning - AI

Generative artificial intelligence (AI) can be vital for marketing because it enables the creation of personalized content and optimizes ad targeting with predictive analytics. LLMs don’t have straightforward automatic evaluation techniques. Therefore, human evaluation was required for insights generated by the LLM.

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Beyond AI: Building toward artificial consciousness – Part 2

CIO

Beyond the hype surrounding artificial intelligence (AI) in the enterprise lies the next step—artificial consciousness. The first piece in this practical AI innovation series outlined the requirements for this technology , which delved deeply into compute power—the core capability necessary to enable artificial consciousness.

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Building a Beautiful Data Lakehouse

CIO

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. Just starting out with analytics?

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