🚀 Get ready for an exciting adventure at the Tool Face-Off Hackathon, powered by cutting-edge technology and an extraordinary lineup of visionary speakers! 🗓️ Mark your calendars Friday, April 26th, 6:00 PM CET, as we kick off this thrilling journey with our esteemed speakers: 🎙️Anupam Datta, Co-Founder, President, Chief Scientist at TruEra Topic: Evaluating Assistants API & LlamaIndex/MongoDB applications 🎙️Laurie Voss, VP Developer Relations at LlamaIndex Topic: Advanced RAG with agentic strategies 🎙️Prakul Agarwal, ML Product Manager at Mongo DB Topic: RAG and Evaluation for LLM Success 🌐 Come learn with us about Assistants API and LlamaIndex/MongoDB. Let's spark your creativity, shape the future of tech, and compete to win! There's a $10,000 USD cash prize pool and a special prize of $3,000 USD for the best use of each toolset. 👉 Haven't registered yet? Secure your spot now and choose your preferred toolset for this epic clash of titans! Sign up here: lablab.ai/event/assistants-a…

New short course on sophisticated RAG (Retrieval Augmented Generation) techniques is out! Taught by @jerryjliu0 and @datta_cs of @llama_index and @truera_ai , this teaches advanced techniques that help your LLM generate good answers. Topics include: - Sentence-window retrieval, which retrieves not just the most relevant sentence, but a window of sentences around it for higher quality context. - Auto-merging retrieval, which organizes your document into a hierarchical tree structure, where each parent node's text is split among its child nodes. Based on the relevance of the child nodes to a user query, this lets you better decide whether the entire parent node should be provided as context to the LLM. - Evaluation methodology for separately evaluating the quality of the key steps of RAG (context relevance, answer relevance, groundedness) so that you can perform error analysis, identify which part of your pipeline needs work, and tune components systematically. Please check out the course! deeplearning.ai/short-course…

New short course on sophisticated RAG (Retrieval Augmented Generation) techniques is out! Taught by @jerryjliu0 and @datta_cs of @llama_index and @truera_ai , this teaches advanced techniques that help your LLM generate good answers. Topics include: - Sentence-window retrieval, which retrieves not just the most relevant sentence, but a window of sentences around it for higher quality context. - Auto-merging retrieval, which organizes your document into a hierarchical tree structure, where each parent node's text is split among its child nodes. Based on the relevance of the child nodes to a user query, this lets you better decide whether the entire parent node should be provided as context to the LLM. - Evaluation methodology for separately evaluating the quality of the key steps of RAG (context relevance, answer relevance, groundedness) so that you can perform error analysis, identify which part of your pipeline needs work, and tune components systematically. Please check out the course! deeplearning.ai/short-course…

🔑🔓 Unlock the power of LLMs for retrieval augmented generation with @TruLensML and #Milvus and enhance your #AI applications with accurate, relevant information. bit.ly/3RkVxbW by @_jreini of @truera_ai #LLM

Our workshop on building, evaluating, and iterating LLM Agents will be led by industry leaders Jerry Liu, CEO of @llama_index, and Anupam Datta, President and Chief Scientist of @truera_ai. See you on December 5! Register here: hubs.la/Q02b1RZW0