November 27, 2018 at 11:30AM - November 28, 2018 at 5:00PM
This MIT CTL Roundtable is exclusively for members of the MIT CTL Supply Chain Exchange and invited guests. If you are not a member of the Supply Chain Exchange and are interested in attending this roundtable, please reach out to Katie Date at <datecl@mit.edu>.
Location:
Tuesday, 11/27/18: MIT Samberg Conference Center, 50 Memorial Drive, 6th floor (Building E52)
Wednesday, 11/28/18: MIT E40-356 (SCM Lab)
Agenda | FAQ
Companies are awash in data, and fast-evolving analytics using Artificial Intelligence (AI) and Machine Learning (ML) technologies can turn this mass of data into actionable information that ultimately increases competitiveness.
But feedback from industry practitioners suggests that while these advances are being harnessed in the supply chain domain, there is a need for more education on AI/ML methods as well as opportunities to explore their potential for solving key supply chain problems.
The MIT Center for Transportation & Logistics (MIT CTL) Supply Chain Exchange will address these knowledge gaps in a 1 ½-day event at the MIT campus, Cambridge, MA, on November 27-28, 2018.
Building on past roundtable discussions on supply chain analytics, the event in November 2018 will focus on the use of AI/ML in supply chain planning. The discussions will center on specific AI/ML applications in forecasting, demand planning, operations planning and supply chain design.
The event will kick off with a half-day primer on AI/ML technology, that will include examples of applications in logistics, transportation and supply chain management generally. This will be followed by a one-day roundtable, during which attendees will discuss emerging applications of AI/ML in supply chain planning within the areas explored during the initial primer session. Attendees also will share their experiences of applying AI/ML technology.
MIT CTL roundtables are highly interactive events where participants learn from each other. There are no PowerPoint presentations and attendance numbers are carefully managed – the emphasis is on generating a rich discourse in an open environment.