Large Language Models (LLMs) for Retail
Pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook
The practical impact of generative AI and large language models (LLMs) on society is growing by the day. Within the retail industry, practical applications for innovations such as ChatGPT and Dolly are widespread — including the rapid search of large product catalogs, streamlining customer service with intelligent chatbots, analyzing customer data and sentiments for personalization, and more — all with the goal of increasing customer satisfaction, loyalty and sales.
The fuel that makes an LLM run effectively is high-quality data, and lots of it. Databricks Lakehouse for Retail provides the underlying architecture and tooling to harness your customer and operational data to easily deliver generative AI and LLM models to your entire organization.
Enhancing product search
Large language models (LLMs) can be used to harness the rapidly growing range of content and goods to ensure customer searches yield the desired results. With the Databricks Lakehouse for Retail, organizations can:
Unify product, query and label data within a retailer’s product catalog
Enable rapid search with analytics against numerical arrays
Train and deploy an LLM model with Databricks Model Serving