Computers have one goal in mind . They serve a purpose . In their role as a dispatching engine , the purpose is to provide the most efficient outcomes for your deliveries .
A . I . at Work
The concept is captivating but how does it work ? As on-demand shipments are created in the courier and logistics software , the Autonomous Dispatch automation tool evaluates the parameters for the shipments against available drivers and parses through hundreds of considerations in seconds to assign the most efficient driver to take the job .
The level of thinking and customization that goes into Autonomous Dispatch - and the timeliness of its computing and results - are not possible in traditional dispatching .
“ Think about a game of pool . Most novices look at the table and consider the easiest and closest shot to sink a ball . World champion pool players may be thinking a few steps ahead and considering if they make this move and that move , then what would be my third and fourth shot ?” describes Beans . ai CBO , Akash Agarwal . “ A . I . is thinking in the same way but even more than four steps ahead . It is thinking 10 , 20 , 50 steps ahead , not only for this one game of pool but for hundreds of games of pool - or hundreds of drivers in our case - all at the same time . It is a much larger data set than you or I are used to thinking about .”
Computers have one goal in mind . They serve a purpose . In their role as a dispatching engine , the purpose is to provide the most efficient outcomes for your deliveries . Whether you want the most time efficient choices or the most efficient itineraries with the least miles driven , Autonomous Dispatching will provide you with the driver assignments to achieve the goal at hand .
“ Automation is simply purpose-built thinking focusing solely on the task at hand , with the task being to provide the best possible results based on the shipment and driver options you have at your disposal ,” adds Agarwal .
The Nuts & Bolts of Machine Learning
A . I . at its core is advanced machine learning to problem solve based on the data it receives . The computer-driven problem solving performs a sequence of algorithms - or computations and measurements - that run over and over and over again to produce a solution .
As it receives more information for new shipments , it takes the data from the last set of algorithms and the results that were produced creating an adaptive , dynamic approach with each cycle . The technology is essentially learning and adjusting to provide the most efficient delivery patterns for your business over time .
“ Machine learning and cloud computing have advanced over the last few years . What used to require a room full of servers at IBM can now be done on a laptop on-the-go during your busy day ,” adds Agarwal . “ With the advancement of technology , algorithms now run faster than ever . You can complete more calculations in even less time . This allows us to build robust , highly customized solutions . To have this powerful automation integrated into a full shipment management platform was a feat that was not technologically feasible years ago .”
24 customized logistics & delivery Magazine I spring 2023