Author: Aaron Ploetz

Vectors and vector search are key components of large language models (LLMs), but they are useful in a host of other applications across many use cases that you might not have considered. How about the most efficient way to deliver retail goods? 

In two prior articles in this series, I told a story of a hypothetical contractor who was hired to help implement AI/ML solutions at a big-box retailer, and then explored how this distributed systems and AI specialist used vector search to drive results with customer promotions at the company. Now, I’ll walk you through how this contractor uses vector search to optimize trucking routes.

The journey to implementing artificial intelligence and machine learning solutions requires solving a lot of common challenges that routinely crop up in digital systems: updating legacy systems, eliminating batch processes, and using innovative technologies that are grounded in AI/ML to improve the customer experience in ways that seemed like science fiction just a few years ago. 

To illustrate this evolution, let’s follow a hypothetical contractor who was hired to help implement AI/ML solutions at a big-box retailer. This is the first in a series of articles that will detail important aspects of the journey to AI/ML.