Introduction

Sahel Jain is an engineer at eu.com, has some experience at Stanford. We discussed the intersection of traditional classic information retrieval and the transition to your modern day large language models or gender-driven models. The real Jedi mind trick that he talked about is that if you do have to wait for something for a long time can you give the user something to do in the interim whether that's filling out a survey or telling them something funny?

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Episode notes

MLOps Coffee Sessions #150 with Saahil Jain, The Future of Search in the Era of Large Language Models, co-hosted by David Aponte.

// Abstract

Saahil shares insights into the You.com search engine approach, which includes a focus on a user-friendly interface, third-party apps, and the combination of natural language processing and traditional information retrieval techniques. Saahil highlights the importance of product thinking and the trade-offs between relevance, throughput, and latency when working with large language models.

Saahil also discusses the intersection of traditional information retrieval and generative models and the trade-offs in the type of outputs they produce. He suggests occupying users' attention during long wait times and the importance of considering how users engage with websites beyond just performance.

// Bio

Saahil Jain is an engineer at You.com. At You.com, Saahil builds searching and ranking systems. Previously, Saahil was a graduate researcher in the Stanford Machine Learning Group under Professor Andrew Ng, where he researched topics related to deep learning and natural language processing (NLP) in resource-constrained domains like healthcare. His research work has been published in machine learning conferences such as EMNLP, NeurIPS Datasets & Benchmarks, and ACM-CHIL, among others. He has publicly released various machine learning models, methods, and datasets, which have been used by researchers in both academic institutions and hospitals across the world, as part of an open-source movement to democratize AI research in medicine. Prior to Stanford, Saahil worked as a product manager at Microsoft on Office 365. He received his B.S. and M.S. in Computer Science from Columbia University and Stanford University, respectively.

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Website: http://saahiljain.me/

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