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Facebook machine learning technology improves; Redditors alaramed.

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Re: Facebook machine learning technology improves; Redditors alaramed.

#23
post #12
post #4

Here's my guess at how it's done: Redditor has facebook app installed on their smartphone (or just uses the website), sets status to "OMG wife is going into labour, at the hospital now". Facebook now knows roughly where redditor was at the specified time based on the ip, they can narrow this down further by looking at keywords in the status message and check it against a list of addresses in the local area and select…

I reckon they use image recognition too. I have a gash digital camera that gets a lot of use; no exif data beyond camera make/model. Anyway; in 2005 I went on a skiing trip to Chamonix. Pics were uploaded about a month later, no Facebook activity at the time (or while I was there). The other day FB asked me if they had been taken in Chamonix. So... something else used there at the very least.

How does Facebook use image recognition to recognize that an image of a baby on a blanket with no surroundings visible was taken inside a certain hospital? I doubt it.

Regarding your Chamonix images, perhaps your friends uploaded photos taken at roughly the same time, with geo-tags? Perhaps you are tagged in some of them? That would make for pretty simple logic:

- Facebook knows that you were at a certain place a certain time through the geo-tagging of those photos, as your user is tagged in one of them

- You upload photos taken at the same time as the photos you were tagged in

Conclusion: You must have taken those photos where the photos you were tagged in were taken.

Re: Facebook machine learning technology improves; Redditors alaramed.

#24
http://en.wikipedia.org/wiki/Scale-invariant_feature_transfo...

Facebook almost certainly has more photo information than TinEye or Flickr, and of indoor environments probably more than Google (which has reverse image search too). Across any given bar or hospital Facebook would have maybe 5-10 other people with albums tagged with the name/gps/check-in. They'd only need one other album though.

SIFT more or less turns every image into a bag-of-words. Your single photo, even at different angles, is going to have a heavy match with photos they have. If you upload a whole album they are going to have tons of matches and they can be more or less certain of the location. To say nothing of adding even the most basic geoip-to-city lookups that would narrow you down to at least five cities that you and your social network inhabit. But the extra information they have is besides the point, SIFT is enough; hospital rooms look alike to us, to SIFT they don't.

Re: Facebook machine learning technology improves; Redditors alaramed.

#25
Wow! A serious competitor to SIRI in place. My guess is they are using combination of techniques - Semantics of your Status as phpnode mentioned with example(heard they have plans to get into semantic search to beat google), EXIF info, IP address and also your friends replies - when is the due? which hospital or Gynic? If hospital name is not mentioned then Gynics details and her hospital location. Do you think all this is used just to make a SUGGESTION?? Its a Billion$?

Re: Facebook machine learning technology improves; Redditors alaramed.

#26
I just tried to upload some photos that facebook hasn't seen yet with or without EXIF info (obviously no or invalid geotagging) and tried geo-tagging some photos I already have uploaded and Facebook hasn't made any suggestion whatsoever. Perhaps I found a way to switch it off but I've just checked the settings and none of the options seems to be concerned with suggestions for geotagging

Re: Facebook machine learning technology improves; Redditors alaramed.

#27
post #4

Here's my guess at how it's done: Redditor has facebook app installed on their smartphone (or just uses the website), sets status to "OMG wife is going into labour, at the hospital now". Facebook now knows roughly where redditor was at the specified time based on the ip, they can narrow this down further by looking at keywords in the status message and check it against a list of addresses in the local area and select…

It's probably a combination of techniques to be honest. They do have some unprecedented access to contextually heavy data, as well as an unusually large base of free labor to supervise the learning...

My creepy moment came when It correctly pointed out the exact location of this photo:

http://www.flickr.com/photos/40127665@N03/4788700749/in/set-...

I was in the middle of Costa Rica. For fear of roaming charges my phone was not on, and I never made a status update. The photo was taken on a D40 at the time, so no location exif data, and frankly the the picture is kind of generic.

My best guess is it used the other photos in the album to gain contextual information. For example this photo was in the same album:

http://www.flickr.com/photos/40127665@N03/4789329722/in/set-...

this, to me, would be extremely easy to recognize.

Re: Facebook machine learning technology improves; Redditors alaramed.

#28
post #24

http://en.wikipedia.org/wiki/Scale-invariant_feature_transfo... Facebook almost certainly has more photo information than TinEye or Flickr, and of indoor environments probably more than Google (which has reverse image search too). Across any given bar or hospital Facebook would have maybe 5-10 other people with albums tagged with the name/gps/check-in. They'd only need one other album though. SIFT more or less turns…

But why that whole technology for just making a Suggestion? There is something else they are working on...something really BIG and a complete game changer I guess.

Re: Facebook machine learning technology improves; Redditors alaramed.

#29
Just checked this.

I took some pics on a regular digital camera (no GPS) in Indore. I uploaded them from New Delhi a few weeks later. And now FB is asking me "Were these pics taken in Indore?". Crazy shit.

Update - I dug through my FB updates. Just before leaving for airport, I updated my status to "Off to Indore" and after coming back to New Delhi, I had some status updates about my office and a local park. Facebook is probably using the the timestamps from image and relating it to locations using some heuristics like status updates, IP addresses, image recognition etc.

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