lol, can’t wait for my Klein bottle shaped package
Note that “optimizing” Amazon package can’t possibly be a very high bar to clear. Just being smart enough to package multiple items coming from the same distribution center on the same delivery route into the same box would do it… Something that other online retailers figured out decades ago but apparently somehow Amazon still hasn’t.
Used to work at an Amazon warehouse, things are a lot more complex then you seem to realize.
Care to expound? Can you explain why a small bottle of vitamins will sometimes come in a box 8 times it’s size. Filled with air bubble packing? I’ve always got the sense that box size was not at all a priority for them.
Depends on how it is fulfilled, if it comes from an Amazon warehouse directly vs directly fulfilled by a third party (if it comes in an Amazon branded box with Amazon tape it probably got fulfilled at an Amazon warehouse).
If it did get fulfilled at an Amazon warehouse, the one I worked at it goes through a process wherein it is retrieved either by a “picker” manually or via a KIVA bot filled with items (depends on how old the warehouse is, I’d be surprised if they’re not all converted to KIVA bot style by now as it’s been nearly ten years since I’ve worked there and I worked in a brand new warehouse at the time and we had the bots style)
So the picker puts it into a bin with several other items all scanned together using the ASIN number (separate Amazon barcode, longer and shorter then other barcodes) which gets loaded onto a conveyer which eventually ends up at a sorter, if it’s AFE (multi-item orders, the department I mostly worked in) it gets pushed to a certain line where it’s manually further sorted from the yellow bin, scanned again and placed into a smaller grey bin (rebin) which goes to another sorter eventually into another line where it gets placed into a wall of cubby-holes (I believe that was called induction), the cubby holes would have all the items for an order, once it’s “complete” you push it through to the other side of the cubby hole where the packers are, the packers have a screen that tells them what items are in the order, along with which box to use, they have a whole wall in front of them of different box sizes, along with a feed of the larger bubble cushin things and an automatic tape dispenser for the box side the system told the packer it needed (it didn’t work a lot of the time so there were also buttons to select a specific box size of tape).
After all that the packer pushes it forward into another conveyer belt, where it is weighed automatically to hopefully ensure it is correct, if it is close enough to the correct weight, it goes out to shipping. (If not, it gets kicked out for problem solvers to figure out what’s wrong with it, that was my main job).
Single item pack is less complex slightly for obvious reasons (don’t have to stage the items together) but is the same basic idea.
Now to answer the questions specifically, why a small bottle of vitamins ends up in a large box, either they ran out of the correct box needed or it was just an incompetent worker who doesn’t care what box they use regardless of what the system tells them they should use. Technically the system could kick it out, but that’s a lot of extra time, effort and a wasted box.
Interesting. Thanks. I’m guessing that Amazon maybe isn’t great at incentivizing workers to care. If the last step for a single item is a human putting it into a box, I could see it being easier to have a stack of big boxes that one would just default to rather than paying attention to size recommendations.
I only lasted 6 months, if that’s any indication lol.
It was a really cool job, but you can’t have your phone while working (have to literally leave it outside in a locker, there are metal detractors you walk through to get in and out), the breaks are way too short (there were times more then half my break was spent just walking from my area to the break room when I did pick), and to top it off, it was a 4/10 shift (overnights for me) and frequently they would tell us on the last day right before midnight that we had to work another full 10 hour day tomorrow.
After several months of 5/12s during “peak” seasons (nov - march) I had enough.
In my experience, every item from the same warehouse comes packaged together. Are you sure the items are sourced from the same warehouse, because they aren’t going to unpack them and pack them together again when they reach the final distribution location. Perhaps it becomes super inefficient to pack items together in super large warehouses, where the items are sourced far apart from each other?
Trolley/Bin packing is a solved problem and NP-complete, this is yet another totally pointless use of AI.
It’s literally a module in the first year of any computer science programme.
Just fitting objects into the smallest box isn’t everything according to the article. This is trying to identify fragile objects and recommend appropriate protective packaging where required to minimize the risk of damage in shipping. If you use a conventional packing algorithm to pack dishes and vases into the smallest box you will receive a box of glass shards on your doorstep. Is AI the best solution? I’m not sure, but using actual statistics of damaged goods and their means of packaging sounds like a worthwhile consideration.
How to properly wrap fragile objects, etc, is again a solved problem.
Best case scenario this is PR nonsense.
That bin packing is an NP-hard problem is more reason for using heuristics like ml, it means that calculating an exact answer quick explodes to unfeasible amounts of computation so using a far more efficient ml solution to give a probablistic answer makes complete sense.
Using ML to research potentially more efficient, in a BigO sense, packing algorithms makes sense.
But that isn’t what they are doing.
They are using image recognition and text analysis to identify the product being packed, and then adjusting the packaging requirements, e.g. more protection = greater volume.
The point I’m making is that they already know what the item is, because inventory codes, so doing visual checks is pointless. They should already know the packing instructions for fragile, etc, items as these are provided by the manufacturer and have already been proven valid by virtue of the product leaving the factory and getting to the Amazon warehouse.
If amazon are ignoring those instructions - and it sounds like they are - then that is a problem they are creating for themselves.
Fitting the items in to the box is still the same problem domain as is taught to first year CompSci students, and is NP-complete. First Fit is extremely efficient when dealing with a relatively small number of items, while optimal solutions are NP-hard, the performance first fit is O(n log n) so not great but not terrible either. Given the myriad combination of item and box size, I’d expect there is a decent amount of triage which can be done and identify “easy to pack” orders (1 or 2 items, no special requirements) which would be essentially a table lookup with O(1) performance.
There are many better algorithms than first fit, I’m just using that as a single example because the point is the same across all of them.
Isn’t that the point though? We think it can’t get any better, let’s let something else confirm it.
AI
Always Indian
Whew, why not let human do this ?
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,
Yeah, it is one of the least bad uses for it.
But then again, using literal tera-watts 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
I think you’re overstating the compute power […]
I don’t actually think so. A100 GPUs in server chassis have a 400 or 500W TDP depending on the configuration, and even if I’m assuming 400, with 4 per watercooled 1U chassis, a 47U rack with those would consume about 100kW with power supply efficiency and whatnot.
Running those for a day only would be 2.4GWh.
Now, I’m not assuming Amazon would own 100s of those racks at every DC, but they probably would use at least a couple of such racks to train their model (time is money, right?). And training them for a week with just two of those would be 35GWh, and I can only extrapolate from there.
So I don’t think that going to TWh is such an overstatement.
[…] and understating the amount of cardboard Amazon uses
That, very possibly.
I have seldom used Amazon ever, maybe 5 times tops, and I can only remember two times. Those two times, I ordered a smartphone and a bunch of electronics supplies, and I don’t remember the packaging being excessive. But I know from plenty of memes that they regularly overdo it. That, coupled with the insane amount of shit people order online… And yes, I believe you are right on that one.
Even so, as long as it is cardboard, or paper, and not plastic and glue, it isn’t a big ecological issue.
However, that makes no difference to Amazon financially, cost is cost, and they only care about that.
But let’s not pretend they are doing a good thing then. It is a cost effective measure for them, that ends up worsening the situation for everyone else, because the tradeoff is good economically, and terrible ecologically.
If they wanted to do a good thing, they could use machine learning to optimise the combining of deliveries in the same area, to save on petrol, and by extension, pollution from their vehicles, but that would actually worsen the customer experience, and end up costing them more than it would save them, so that’s never gonna happen.
So this may be a more efficient use of computing power. Brute force calculation of combinations is costly because there are so many possibilities. A learning model can be fed data from brute force calculations and from humans tasked with packing efficiently to develop an empirical model (this is the AI part) of how to package assorted items. That model could take much less computing power than the Brite force method.
They may also save costs on trucking. Smaller boxes => less full truck.
So this is good to reduce packaging waste and probably fitting more packages on trucks/planes, reducing emissions I am guessing. But how much power does running it cost and how is the power being generated? Is it a net loss for their global emission, or is it just making Amazon save money? I’m still pretty dumb at this stuff
Just use whatever Temu uses.
Temu packagers could fit a whole factory in the boxes Amazon uses to ship my deodorant
