Large Language Models with Semantic Search

Overview

For years, keyword search has dominated the landscape of information retrieval, serving as the backbone for everything from news websites to online marketplaces. However, the advent of Large Language Models (LLMs) promises a seismic shift in how we interact with search functionalities.

Our course on Large Language Models with Semantic Search introduces a groundbreaking approach, transforming the traditional search experience into a more intuitive and effective process.

Participants in this course will dive into the intricacies of leveraging LLMs for search, learning about pioneering techniques such as dense retrieval and reranking. These methods not only refine the accuracy of search results but also incorporate the nuanced understanding of language that LLMs provide, offering a superior alternative to keyword-based searches.

By the end of this course, attendees will be equipped with the knowledge to:

• Understand and implement basic keyword search as well as its enhancements through reranking, aligning search results more closely with user queries.
• Apply dense retrieval techniques, utilizing embeddings to interpret and search based on the semantic meaning of texts, thus significantly enhancing search outcomes.
• Gain practical experience in handling large datasets and tackling common challenges associated with search accuracy and consistency.
• Seamlessly integrate LLM-powered search functionalities into websites or any digital project, enriching the user search experience.

Offered independently, this course forms part of our specialized series on Large Language Model (LLM) Courses, designed for those eager to pioneer the integration of advanced AI in search systems.

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Taught by

Jay Alammar, and Luis Serrano

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Subjects