Submitted 1 year ago by dbilitated@aussie.zone to programming@programming.dev
www.explainxkcd.com/wiki/index.php/1425:_Tasks
A month after this comic came out, Flickr responded with a prototype online tool to do something similar to what the comic describes, using its automated-tagging software. According to them, the bird solution “took us less than 5 years to build, though it’s definitely a hard problem, and we’ve still got room for improvement”.
(the site parkorbird.flickr.com is no longer online)
that’s awesome, didn’t know that
Damn, I wanted to see some parkour birds.
Damn seeing a serious Flickr link truly is a blast from 10 years ago!
Did you miss the part that said “I’ll need a research team and 5 years?” The XKCD character did it! SUCCESS!
I have a book on learning Pytorch, this XKCD is in the first chapter and implementing this is the first code practice. It’s amazing how things progress.
Do you recommend that book? Title?
Yes I do! It’s a pretty great overview that isn’t extremely math heavy
The book is “Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD”
Not obsolete? More like prophetic.
It’s actually even more correct because it underestimated the time needed by 5 years
Even with AI models that can identify that there are birds in the picture. Having it decide with accuracy that the picture is of a bird is still a hard problem.
yeah and it has been 5 years since the comic and there was a research team that did it
They probably got 2 research teams
I remember this one. It seems as spot on now as it was then, honestly.
Object detection isn’t magic, and it wasn’t magic then either, it just requires a dedicated team + time + money to pay them, which is what this comic was trying to express. It is true there are more off-the-shelf software available for novice programmers now than there was before, but that doesn’t make it wrong.
That’s true, even if the specific example doesn’t hold, the core concept does. If I needed to implement a bird detector today, I’d make an API call to AWS Rekognition or an equivalent service. It would take me a day or two to learn the API and then maybe 4 hours to actually implement. But if you asked me to implement a bird species detector, I’m pretty sure there is no off the shelf API capable of that, and I would indeed need months or years.
Off the shelf… no… though I’ve been rather impressed at the accuracy of the iPhone. There’s this little i in a circle that has a star in the corner which will do a “let me try to match this”. I believe its only a matter of time before this becomes more accessible.
Attempting to match a purple flower on the side of a bike trail
It could have been the other way around if global positioning systems were either not developed or used only by the military. In that case, detecting scenery of a park could be easier than trying to figure out the position on the map.
Or it could just be that maps data are not shared. You’ll need to hire boats and hire people to go and draw the map.
The original problem was posited… 60 years ago?
It’s a bit like saying “I wonder how the dinosaurs died?” in the early '00s, a few years before meteor theory really got nailed down. Like, ignore the last century of postulation. We just knocked this out real quick.
Like, ignore the last century of postulation. We just knocked this out real quick.
Oh wow thanks, TIL. I was a kid in the 90s, and always taught and read “there’s many guesses, but the most likely theory is a massive impact causing global changes”. And only today I learnt that it was a relatively new theory at the time, and the crater wasn’t even identified until the early 90s!
yeah, the comic describes it as “the virtually impossible” and directly notes we’ve spent 50 years trying. it’s just a really interesting perspective that it was a recent truism that this stuff is virtually impossible, and we’ve solved it and a huge number of other very difficult problems in less than a decade.
I’m not saying we aren’t building on centuries of work, i’m saying the rate of recent progress is remarkable. I feel like you missed the point on purpose in order to have a hot take.
yeah, the comic describes it as “the virtually impossible”
We are a lot better at it now than we were, say, ten years ago. But it is nearly trivial to outwit a “bird detecting algorithm” by holding up a vague facsimile of a bird. That gets us back to the old TrashFuture line about AI just being “some dude at a computer filling out captchas”.
I’m not saying we aren’t building on centuries of work, i’m saying the rate of recent progress is remarkable.
The recent progress is heavily overstated. More often than not, what a computer does today to recognize a bird is to pull on a large library of data labeled “birds” and ask if there’s a close-enough match. But that large library is not AI driven. Its the consequence of a bunch of manual labeling done by humans with eyes and brains. A novel or rare species of bird, or a bird that’s camouflaged, or even just a bird that’s out-of-focus or badly rendered, will still consistently fail the “Is this a bird?” test.
Computer vision was just popping off five years after that, so I would say that it is prescient.
I used to put this in my object detection presentations 5 years ago and it never failed to draw chuckles from the audience.
Shit has been going really really fast.
Why do you think it’s obsolete? I suppose nowadays we can use AI generative models to explain the difference between the easy and the virtually impossible, but it still can be hard.
… it’s still true…
We can get a computer to tag the birds, answer questions about them, and generate new pictures of them.
Sometimes
AI always screws up the birds fingers
Epilogue: She got what she asked for and completed the work 5 years ago.
One of the coolest things I’ve seen this month: www.lerf.io
I haven’t used a computer to id birds before, so I’ll take your word for it. That being said I know that programs I’ve tried are entirely incapable of identifying mushrooms (or even getting in the correct family sometimes). This may just be an issue of lack data, bc a lot of what I do to id is fairly simple and formulaic. On the other hand I use a lot of context clues which may not be readily apparent ig
What could possibly go wrong with mushroom misidentification?
Wild swings between the greatest trip you’ve ever had, and excruciatingly slow death.
Nothing I can think of.
Not only is this not obsolete, it’s close to biographical as it closely references the first and second Artificial Intelligence Winters. The first being in the 60s. We’ve been working on these for a long time, so 5 years is short. It took until GPGPU to kick into full gear and some clever insights to get Deep Learning up and running (somewhat attributed to work published in 2011) to start reliably on this problem, and even that is an oversimplification of the timeline and the scope.
Others have mentioned oddities like the difficulty of subject matter (picture contains a bird vs picture of a bird) but there are a lot harder problems that are trivial to humans and counterintuitively incredibly hard for computers.
I talk about this a lot. It’s a conspiracy theory of mine that this comic spurred the AI image tech we have today.
Or just do what iNaturalist does and have the community identify the photo
wantd2B1ofthestrokes@discuss.tchncs.de 1 year ago
Well research teams have been working on it 10 years
dbilitated@aussie.zone 1 year ago
they did good
hexaflexagonbear@hexbear.net 1 year ago
They’d already been on it for a few decades 5 years ago…
Goodtoknow@lemmy.ca 1 year ago
And crazy how not only can tools recognize birds but generate novel new images of them.
zepplenzap@lemmy.sdf.org 1 year ago
Exactly!