Google Unveils Neural Network to Determine the Location of Almost Any Image
technologyreview.com
technologyreview.com
Stallman was asking to not put any kind of his pictures on Facebook, which means your face is recognized now by Facebook, and there's plenty of things to do with that...
Surely, SURELY RMS is not one and only person you have ever heard in your entire life warn about the dangers of putting personal information online, or the dangers of government surveillance. That's all just common sense and being relatively informed and skeptical about the world and the people around you.
RMS says a heck of a lot more than "don't post your pictures on Facebook", much like PETA says a lot more than just, "treat animals ethically", or Earth First says a lot more than just, "don't destroy the environment". If sea levels rise much more in my lifetime, one lesson I will not draw from it is, "Earth First was right!"
If you care about this stuff, donate to the ACLU, not the FSF.
Why, exactly?
Usually I like people to know where the photos I share publicly are taken. Indeed, that's why I go to the trouble of captioning or manually geotagging them.
wouldn't that be much effected by weather conditions and air quality ?
He has done some amazing work extracting geo-location and scene structure based on daylight patterns, shadows cast by clouds, rainbows, etc in images and image sequences.
I'm sure any serious organization actually putting together a product to locate images that have time—but not location—data would try to take advantage of the outdoor color temperature, lighting, global weather records, text recognition, and all that kind of stuff. This was a more focused research project.
The dataset might be a little biased though. I wonder how many pictures are just of people's faces, or food, or random indoor scenes. It's much more difficult to detect a location from such an image. How good are the results if you exclude the images that don't have any clues at all?
As I understand it, the algorithm can identify common types of plants unique to different regions, or architectural features, or popularity of types of cars. So an outdoor photo is more likely to be recognized. But I'm not 100% sure what features it's using. In fact the creators don't even know!
An aside - I was really annoyed by "small-scale experiment shows that PlaNet reaches superhuman performance at the task of geolocating Street View scenes". It's absurd to say computers are superhuman at searching the web for instance, and though this is a much more impressive perception-based result it is still fundamentally very data intensive. Would be nice if 'superhuman' was used a bit less now that Deep Learning has already been proven to be capable of really impressive performance in perception tasks.
That seems an insane amount to me.
Okay. But wouldn't this be more useful as a web service?
Or you think it's like every "new" Google product from a few years where there is a lot of talking before anything.
"Check it out, I'm Mogadishu!"
They go further and use the machine to locate images that do not have location cues, such as those taken indoors or of specific items. This is possible when images are part of albums that have all been taken at the same place.
I'm going to start including pictures of the moon surface in all my albums.
Sorry to say it but they're going to be able to exclude whatever you throw at it.
And even if you found some way to meaningfully degrade the quality, they'll analyse what you do and find a solution for that.
They are not going to suddenly throw their hands up in the air and decide to give up.
It's a matter of how many resources can you throw at the problem and how many can they to counteract you.
How, exactly? You're talking about something that's one of the most poorly understand areas in AI at present, and making it sound like it's a solved problem.
With manpower. I said that they are going to analyse whatever users do to wilfully degrade the service and will find a way to exclude that.
Just like they do with search for years. Somehow they manage to keep their search relevant even though so many people constantly work on coming up with new SEO tricks that would seriously degrade this service if left unchecked.
Of course I cannot know how _exactly_ they will do that, even the persons working on that service cannot know at this moment how exactly they will keep this working in the future since they do not know yet what people will try to do.
This is just the Luddite fallacy repeated over and over. By this logic, we should never develop new informatic methodologies, we should never develop new forms of analysis, we should never develop new software – because of economies of scale exist.
I'll the state the obvious: that's stupid. There's no way to soften that blow.