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Building Multimodal RAG Application #3: Multimodal RAG System Architecture

Towards AI

Last Updated on November 6, 2024 by Editorial Team Author(s): Youssef Hosni Originally published on Towards AI. In the third article of the Building Multimodal RAG Application series, we explore the system architecture of building a multimodal retrieval-augmented generation (RAG) application. Published via Towards AI

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Why Microsoft is outspending big tech on Nvidia AI chips

Dataconomy

has acquired approximately 485,000 of Nvidias Hopper AI chips this year, leading the market by a significant margin according to Financial Times. Microsoft is looking to cultivate its AI services, leveraging technologies from OpenAI, in which it has invested $13 billion. Microsoft Corp.

Azure 103
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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

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Rad AI reduces real-time inference latency by 50% using Amazon SageMaker

AWS Machine Learning Blog

This post is co-written with Ken Kao and Hasan Ali Demirci from Rad AI. Rad AI has reshaped radiology reporting, developing solutions that streamline the most tedious and repetitive tasks, and saving radiologists’ time. In this post, we share how Rad AI reduced real-time inference latency by 50% using Amazon SageMaker.

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Diagrams AI can, and cannot, generate

Hacker News

An exploration of how well AI generates system architecture diagrams

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Killswitch engineer at OpenAI: A role under debate

Dataconomy

This role, geared toward overseeing safety measures for their upcoming AI model GPT-5, has sparked a firestorm of discussions across social media, with Twitter and Reddit leading the charge. OpenAI, long considered a leader in AI safety research, has thus identified this role as a vital safeguard.

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Build a dynamic, role-based AI agent using Amazon Bedrock inline agents

AWS Machine Learning Blog

AI agents continue to gain momentum, as businesses use the power of generative AI to reinvent customer experiences and automate complex workflows. In this post, we explore how to build an application using Amazon Bedrock inline agents, demonstrating how a single AI assistant can adapt its capabilities dynamically based on user roles.

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