Video description
During the first months of the COVID-19 pandemic, it became crucial to prioritize shipments of critical cargo. In 2020 the Port of Montreal implemented an AI tool for the supply chain—in just six months from preparation to pilot delivery—with the goal of providing advance visibility to supply chain stakeholders by detecting critical cargo (e.g., masks, sanitizer, etc.).
Join us for this Case Study with telecommunications engineer and AI advisor Adrian Gonzalez Sanchez to explore the tool and discover how it performed in practice. You’ll learn how pragmatic innovation (e.g., focusing on specific AI tasks, using only mature techniques, defining the “good enough” results in advance, etc.) and a common goal can lead to successful AI implementation. O'Reilly Case Studies explore how organizations have overcome common challenges in business and technology through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and challenges while hearing their unique perspectives, insights, and lessons learned.
Recorded on November 9, 2021. See the original event page for resources for further learning or watch recordings of other past events.
O'Reilly Case Studies explore how organizations have overcome common challenges in business and technology through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and challenges while hearing their unique perspectives, insights, and lessons learned.
Table of contents
Product information
- Title: Case Study: How the Port of Montreal Used NLP to Fast-Track Critical Cargo in 2020
- Author(s):
- Release date: November 2021
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920623670
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