AI content generation is about feeding your AI models with semantic and contextual information. The result is a platform that can ‘understand’ what an item is, and how it should be used. AI creates content using semantic knowledge in any form of content including video, 3d, VR and more.
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Implementing Multi-Modal RAG Systems
Large language models (LLMs) have evolved and permeated our lives so much and so quickly that many we have become dependent on them in all sorts of scenarios.
Findings of the IWSLT 2024 Evaluation Campaign
Ibrahim Said Ahmad†, Antonios Anastasopoulos††††, Ondřej Bojar¶, Claudia Borg††, Marine Carpuat‡, Roldano Cattoni§, Mauro Cettolo§, William Chen‡‡, Qianqian Dong¶¶, Marcello Federico§§, Barry Haddow‡‡‡, Dávid Javorsky¶, Mateusz Krubiński¶, Tsz Kin Lam‡‡‡, Xutai Ma‡‡§, Prashant Mathur§§, Evgeny Matusov¶¶¶, Chandresh Kumar Maurya¶¶†, John P. McCrae†††, Kenton Murray†††, Satoshi Nakamura§§§, Matteo Negri§, Jan Niehues††¶,…
Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock
There’s a growing demand from customers to incorporate generative AI into their businesses. Many use cases involve using pre-trained large language models (LLMs) through approaches like Retrieval Augmented Generation (RAG). However, for advanced, domain-specific tasks or those requiring specific formats, model customization techniques such as fine-tuning are sometimes necessary. Amazon…
What Are Foundation Models?
Editor’s note: This article, originally published on March 13, 2023, has been updated. The mics were live and tape was rolling in the studio where the Miles Davis Quintet was recording dozens of tunes in 1956 for Prestige Records. When an engineer asked for the next song’s title, Davis shot…