This…actually seems like a good use of AI? I generally think AI is being shoehorned into a lot of use cases where it doesn’t belong but this seems like a proper place to use it. It’s serving a specific and defined purpose rather than trying to handle unfiltered customer input or do overly generic tasks,
Eh, I doubt that. Bin packing is a very well-researched problem. It’s one of those nasty NP ones but we already have very good algorithms giving very good approximations in very short amounts of time the chance that throwing machine learning at the problem helps is not zero, but close to it. What that kind of approach certainly won’t get you is guarantees, those approximation algorithms can be configured to spit out solutions that are at most 1% or whatever you want worse than the optimal solution.
I doubt this actually has anything to do with Amazon’s logistics operations it’s just their marketing team wanting to hype up Amazon for AI.
But then again, using literal tera-watts-hours of compute power to save on the easiest actually recyclable material known to man (cardboard), maybe that’s just me, maybe I’m too jaded, but it sounds like a pretty bad overall outcome.
It isn’t a bad deal for Amazon, tho, who is likely to save on costs, that way, since energy is still orders of magnitude cheaper than it should be[1], and cardboard is getting pricier.
if we were to account for the available supply, the demand, and the future (think sooner than later) need for transition towards new energy sources… Some that simply do not have the same potential. ↩︎
This…actually seems like a good use of AI? I generally think AI is being shoehorned into a lot of use cases where it doesn’t belong but this seems like a proper place to use it. It’s serving a specific and defined purpose rather than trying to handle unfiltered customer input or do overly generic tasks,
Eh, I doubt that. Bin packing is a very well-researched problem. It’s one of those nasty NP ones but we already have very good algorithms giving very good approximations in very short amounts of time the chance that throwing machine learning at the problem helps is not zero, but close to it. What that kind of approach certainly won’t get you is guarantees, those approximation algorithms can be configured to spit out solutions that are at most 1% or whatever you want worse than the optimal solution.
I doubt this actually has anything to do with Amazon’s logistics operations it’s just their marketing team wanting to hype up Amazon for AI.
Yeah, it is one of the least bad uses for it.
But then again, using literal tera-watts-hours of compute power to save on the easiest actually recyclable material known to man (cardboard), maybe that’s just me, maybe I’m too jaded, but it sounds like a pretty bad overall outcome.
It isn’t a bad deal for Amazon, tho, who is likely to save on costs, that way, since energy is still orders of magnitude cheaper than it should be[1], and cardboard is getting pricier.
if we were to account for the available supply, the demand, and the future (think sooner than later) need for transition towards new energy sources… Some that simply do not have the same potential. ↩︎
I think you’re overstating the compute power and understating the amount of cardboard Amazon uses