Also, despite my 30+ years on this Earth, I vastly more trust a 'professional' shopper to pick out good veggies than I do myself. I respect that you're different, but I can say with 100% certainty that the produce picked out by my instacart shoppers is excellent and better than I could do. Never a single complaint there, at least from me.
Do they really rush? From my side, they seem to take their sweet time. They text frequently, asking questions, suggesting replacements not shown in the app, etc. The whole process feels slow and relaxed.
I don't eat meat so I don't know about that. But I would assume the same as veggies. Instacart does a top-top job picking quality ingredients for me. Definitely better than I would know how to do myself.
Who is more likely to know the freshest spinach? Not me, that's for sure. An instacart shopper who is there all day? Much more likely to get good results.
I do have issues with instacart, but none of the concerns you've mentioned have in any way harmed me. My main issue is that the delivery times seem to be not communicated to the driver. So it will tell you 10am - 11am, but the driver will show up at 9:50 and not know that they are early. Sometimes also, the selection available on the website will be mislabelled in category (tomatoes in bath care, or something).
Otherwise it has been really incredible for me, overall.
We're delivering autonomous checkout to Amazon's competitors across the world. Amazon can only crush us if they crush the entire retail sector, which will be a tall order, especially with the slew of startups emerging to help defend retailers from Amazon's entry into the brick and mortar world.
This is where a camera-only approach really shines, which is why the team has gotten so much adoption from retailers. This tech is literally the way incumbents can fight back against Amazon's encroachment.
I don’t doubt this technology is the future or will be a big market, but let’s not kid ourselves that this will generate more human connection.
This is a fair initial take, and we should clarify why we think we're improving the social experience. A big part of why Lyft or Uber feels different than taking a cab is that there's no transactional portion of your interaction with the driver. Get into the car, chat a bit, say goodbye, and be on your way. By removing transactional mechanics you can focus on the human element. If you look at the Amazon Go stores, or the Standard Store, you see a similar effect. You walk in, and rather than immediately seeing bulky machines manned by people with the sole intent of transacting, instead you see people walking around chatting and helping you find what you need. They're not there to take your money, they're there to help you, exclusively. That changes the nature of the interaction, and is the experience we're trying to deliver across retail.
Go to any store that has self-checkout currently. Usually there is one attendee servicing 4 machines. No one comes up to you to chat, they only come over when theres a problem. When you go to a manned-checkout, they usually ask how you are doing, if you found everything ok, if you want to join a loyalty program...etc. Some of the checkout people I know very well over the years in my community. One even gave my infant daughter free socks because she has grandchildren.
You wont get that in this future. Those checkers will be gone. You'll just have employees minding their own business tending to their work, like you will with yours.
These are actually very valid points and why most solutions tend to go for a sensor fusion approach that leverages the best of computer vision along with other sensor modalities. Using only ceiling cameras will not get you to the kind of accuracy that most retailers require to confidently rely on the technology.
Even if you placed more cameras (not only ceiling cameras, but also in the shelves and other areas of the store pointing at different angles), leaving aside the cost (which adds up), people will always be able to occlude the items from the cameras (even unintentionally). To put it in numbers (as an example): computer vision can get you 80% of the way in terms of accuracy / detecting items grabbed, for the rest you need other sensors.
The main benefit over other self checkout systems is the time customers wait in line. If you have been to Amazon Go, the experience of walking out without waiting is quite magical.
I wasn't trying to detect which item was removed, just that an item was removed, so it was a good bit simpler. I was using Matlab to analyze with old school computer vision algorithms to analyze the video (this was before deep learning was common).
It mostly worked--it could highlight when an item was removed from a shelf, but it wasn't useful enough for much other than maybe helping security to manually review tapes for evidence of shoplifting.
The biggest problem for them were that they after all, all required some amount of human intervention for work. Because of that, the store had to buy both a self-checkout machines, then hire a guy to click buttons on the machine, then a security guy who looks if nobody tries to do any tricks and rough up ones who do.
I think the better way is how it is done in China: you have gigantic (shipping container sized) wending machines placed all around residential blocks and such. Works well for packaged products, but not for fresh produce. When it needs service, a truck comes in, picks it up whole, and a new, fully restocked one is placed in its place in a few hours by the same truck with a crane.
Have you hired sleight of hand artists to field test the machines? I’d be very impressed if a determined actor could not fool a set of overhead cameras.
