Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into a thought-provoking discussion on the potential of Long-Context Language Models (LCLMs) to replace traditional methods like Retrieval, RAG, and SQL. Explore the findings of a recent paper that examines LCLMs' ability to handle extended contexts and their performance compared to conventional approaches. Join hosts Nehil Jain, Sonam Gupta, and Korri Jones as they dissect the Loft benchmark for evaluating LCLM performance, analyze multimodal data for SQL tasks, and discuss the efficiency of computational analysis and semantic search. Gain insights into in-context learning, multi-hop reasoning, and chain of thought improvements in LLM applications. Reflect on the importance of evaluation techniques in research and the varying defensibility of different conclusions. Consider the potential of LLMs for product-market fit and optimization while acknowledging both pioneers and learners in the field. Engage with the MLOps community through the provided Slack channel for further questions and discussions. Read more