Transform your GenAI applications with Retrieval Augmented Generation (RAG), the innovative approach that defines how organizations harness the value of their data with LLMs. In our latest eBook by Eduardo Alvarez and Sancha N., we’ll explore some of the Intel hardware and software building blocks that optimize RAG application and enable contextual, real-time responses, while simplifying deployment and enabling scale. Learn more and access the eBook here: https://intel.ly/3wNn7am #GenAI #Developer #LLM
Open.Intel
11mo
What a great resource. Thanks for sharing! RAG is a powerful solution for context-based challenges in large language models (LLMs). However, interconnecting all the parts in a production environment can be challenging due to the lack of standardized methods. Initiatives like OPEA (Open Platform for Enterprise AI) are essential for creating common standards involving the community/devs to be part of the process, making RAG technology more accessible and easier to adopt across various industries.
Jahangir Alam
11mo
Great advice!
Intel Corporation
11mo
RAG opens up doors for businesses to leverage their data in a unique and efficient way! Eduardo and Sancha did a phenomenal job explaining how we can support business goals in a secure environment.
Intel Business
11mo
RAG is a powerful approach that saves valuable time and cost when compared to retraining and fine-tuning.
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Software Development | Data Analytics| AI & Machine Learning| Cybersecurity
11moVery helpful! One question. Do you foresee any challenges with RAG? If so, how do you intend to address them?