Retrieval-Augmented Generation (RAG) has revolutionized how Large Language Models (LLMs) access and utilize contextual information. As the demand for more sophisticated AI systems grows, RAG capabilities have also evolved tremendously. In this session, we delve into advanced RAG techniques that enhance search accuracy, improve contextual understanding, and boost overall performance in real-world applications.
AGENDA
Talk 1: Enhancing Retrieval Quality – We look at some techniques such as Cross-encoder reranking, Dynamic retrieval, Ensemble retrieval, and Semantic caching that improve the accuracy and speed of information retrieval in RAG systems
Talk 2: Optimizing RAG for Real-World Applications – We explore practical techniques such as Query expansion and reformulation, Adaptive chunk sizing, Few-shot retrieval, and Retrieval-augmented prompting that enhance RAG systems’ adaptability and performance across diverse real-world scenarios
FEE
This workshop is FREE to attend but seats are limited and available on an invite-only basis. Prior registration is required for receiving an invitation, as per the below process.
REGISTRATION
To register, please do BOTH of the following:
Fill in this Event Registration Form: https://lu.ma/jd3rq1w6 (attendees will be selected and invited based on this EXCLUSIVELY)
Join the waitlist for the soon-to-be-launched Deep Tech Stars app at www.deeptechstars.com (only those on the waitlist will be invited to attend this session, so please register asap)
Please note that we will not be able to accommodate walk-ins.
Please reach Nihal at 9663374431 if you need any clarifications or have any challenges in registration. We look forward to seeing many of you there!
We thank Deep Tech Stars for co-organizing this session with us and NASDAQ for hosting us.
