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Building Multimodal RAG Application #3: Multimodal RAG System Architecture

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. Last Updated on November 6, 2024 by Editorial Team Author(s): Youssef Hosni Originally published on Towards AI. This member-only story is on us.

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Towards an Adaptable Systems Architecture for Memory Tiering at Warehouse-Scale

Hacker News

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Evolution of the Unix System Architecture: An Exploratory Case Study

Hacker News

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Understanding REST API: A comprehensive guide

Data Science Dojo

Layered System: REST API should be designed in a layered system architecture, where each layer has a specific role and responsibility. The layered system architecture helps to promote scalability, reliability, and flexibility. The uniform interface helps to simplify the API and promotes reusability.

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Apple Workshop on Privacy-Preserving Machine Learning 2024

Machine Learning Research at Apple

We develop system architectures that enable learning at scale by leveraging advances in machine learning (ML), such as private federated learning (PFL), combined with… However, accessing the data that provides such insights — for example, what users type on their keyboards and the websites they visit — can compromise user privacy.

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Acoustic Model Fusion for End-to-end Speech Recognition

Machine Learning Research at Apple

The E2E systems implicitly model all conventional ASR components, such as the acoustic model (AM) and the language model (LM), in a single network trained on audio-text pairs. Despite this simpler system architecture, fusing a separate LM, trained exclusively on text corpora, into the E2E system has proven to be beneficial.

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Killswitch engineer at OpenAI: A role under debate

Dataconomy

Understanding system architecture A killswitch engineer at OpenAI would be responsible for more than just pulling a plug. The role necessitates a deep understanding of system architecture, including the layers of hardware and software that run AI models like upcoming GPT-5.