Also Google: "Our standard for 'what a machine couldn't possibly do' is identifying a stop sign."
Stuff you get now often requires cultural information, like "sidewalk" isn't a cross-cultural name, I'd guess almost everyone knows it, but meh. What classes as a store, is a lawyers office a store? Also, I seem to recall I had "click on all minivans"?? Not sure what one of those is, nor really what is classed as a car in USA, is an MPV a car [I'd guess that's what a minivan is?]? Do pedestrian crossing lights (green/red man) count as [part of] traffic lights? I've often wanted a short description of the locus of the terms they're using. Of course it never tells you if you failed, just gives you a further captcha, which it might have done anyway.
Current Assignee: Juniper Networks Inc
The V2 was just annoyingly badly designed because the questions were badly put.
I'd always assumed that was noise carefully tuned to throw off one machine learning model or another that was being used to beat the captcha, sort of like this: https://www.theverge.com/2017/11/2/16597276/google-ai-image-...
I think it might be the same when they switch to other types of objects (like crosswalks or bikes). Someone's model got too good, so they had to change to something else. I also get the impression that they add delays to the tile refresh before they do that.
I suspect Google now uses robots to generate captchas for humans, under the assumption their image recognizers are far better than anyone else's. They already have some very well ones for other products (self driving cars, street view) and lots of street-level city imagery. That would explain why their captchas are so difficult for humans to solve -- they're testing if you see things like their "AI," not like other humans.
I was thinking it was trying to dirty up the image just like the lenses on cameras get dirty. What happens to the image recognition when there's water spots, dirt, mud, etc on the lens that keeps parts of the image obscured?
If you have the clean version of the image, you need to get that classified by a human - then you can throw noisy versions of it into the training set for your AI. You don’t need to ask a human, hey, I added noise to a picture of a yield sign. Is it still a picture of a yield sign?
With the possibility of almost uniquely identifying us on the web through fingerprinting... Google, of all companies is in the perfect position to know that my web request was made by me... And therefore I'm not a robot.
You can only conclude that recaptcha is a ml training exercise.
They're not secretive about it
The article explains that this is part of what reCAPTCHA does, e.g.:
> Finally they combine all of this data with their knowledge of the person using the computer. Almost everyone on the Internet uses something owned by Google – search, mail, ads, maps – and as you know Google Tracks All Of Your Things. When you click that checkbox, Google reviews your browser history to see if it looks convincingly human.
But your point is otherwise right in that it's used for ML training, which Google admits as another commenter pointed out.
Human [n]: Entity that uses Google®-brand services.
— Google Dictionary, 2020 edition
Or, maybe they feel I'm not pulling my own weight, seeing as I rarely ever click on adds. They probably need more monkeys to feed the beast so I get selected to train their AI beast.
Edit: It could also be that I'm always running on incognito mode.
I recall the modern (non-text) captchas used to be cars pretty much every time. Then, the images started getting grainier as they apparently wanted to improve their recognition in different conditions. Then crosswalks and store fronts became quite common, eventually with the same kinds of noise distorting images. Now I've started seeing things like buses, bridges, motorcycles, bicycles, etc. It feels like they've finished getting enough data for improving Google Maps and have begun moving towards collecting data for their self-driving car projects.