Google Can Now Recognize Objects in Videos Using Machine Learning (theverge.com)
Google has found a new way to allow software to parse video. On Wednesday, the company announced "Video Intelligence API", which is able to identify objects in a video. From a report: By playing a short commercial, the API was able to identify the dachshund in the video, when it appeared in the video, and then understand that the whole thing was a commercial. In another demo, we saw a simple search for "beach" and was able to find videos which had scenes from beaches in them, complete with timestamps. That's similar to how Google Photos lets you search for "sunset" and pull up your best late-day snapshots. Before now, computers couldn't really understand the content of a video directly without manual tagging. "We are beginning to shine light on the dark matter of the digital universe," Fei-Fei Li, chief scientist of artificial intelligence and machine learning at Google Cloud, said. At least in Google's demo, it was genuinely impressive. And Google is making the API available to developers, just as it has with its other machine learning APIs.
I mean, Google isn't exactly going to enable us to skip/ignore ads, are they?
What's Google's practical application for such a technology?
Do not look into laser with remaining eye.
Did it report that the dog was evil, paranoid, a Nazi, in the KKK, or planning a coup?
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Dear Slashdot: next time you want to mess with the site, add a rich-text editor for comments.
Now you won't have to fast forward through Monsters Ball to see Halle Berry's berries. ;)
This recognizes Google's ads & swats 'em
But who recognizes your ads and swats 'em?
In the past, it was really easy to tell whether something was a commercial. Now, advertisers make it appear that you're watching the trailer for the next chick-flick or action movie.
Oh wait. The summary says it can recognize a dachshund. Proof enough for me! Everyone knows dachshunds are the most EVIL breed of dog.
Actually every article about the google tends to sadden me. Such a nice little child company grew up to be such a monster. Dare I say EVIL? Yes, notwithstanding finishing yet another book about the google yesterday amid all of the protestations of how much the google wants to be a good and friendly little boy. The tools remain as morally neutral as they ever were, but things have changed anyway.
The "Don't be evil" slogan has mutated to "All your attention are belong to us."
The mission of making all of the world's information accessible and useful has changed in a more complicated way. Information is overabundant, even super-abundant, so the google had to prioritize. Turns out the highest priority information is what the advertisers want to pay for YOU to see and the ultimate utility function became the corporate profits. Yes, they are still throwing a few crumbs at the residual humans who produce the content that carries the ads, but the big winners are all corporations. Ultimate victory of AI?
There are two problem with "shareholder value" as the sole criterion of goodness. The minor problem is that share price is a delusion. The major problem is that it defines an unsolvable problem, even if you don't call it greed. There is NO share price that represents maximum shareholder value. No matter what you did yesterday, the corporation has to work to make the share price higher today, even if it ultimately makes the corporation EVIL.
Speaking for myself, I can't call it super-greed because corporations are inhuman, notwithstanding SCOTUS. Only humans have such emotions as greed.
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I also invented such a tool. It's accurate 70% of the time.
Here's the code:
Table-ized A.I.
identified : human . kill .
How much of this is just keeping a massive database of RGB pixel rasters and doing a least squares comparison analysis of edge interfaces, color ratios and geometries, and spitting out what appears to match the known object the most closely? I know that it sounds like I'm trivializing it, but I wonder it's really "machine learning" or if it's more or less "pattern matching."
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One day eyes will appear in the O's of Google and she will start talking to us in a sexy subtle system shock 2 kind of way.
Wondering whether the AI would still recognise the beach if the video was intentionally color-inverted, or color substituted? For instance, a purple beach with red ocean, sort of like in the ending of 2001 A Space Odyssey. A human would still be able to do this easily.
So if you scrambled the sequence of frames, would this API produce the same outcome? If so, you're just recognizing objects in still images, which isn't that special. And does the software care if the doggie moves? If not, then where does the term "video" come in?
Did the API recognize objects in the videos, then if they disappear, can it recognize their return and correctly associate them with their antecedent object (AKA persistence)? Did it learn to recognize each new critter it meets, or do all dachshunds look alike to it? Maybe whenever it sees a dachshund, it assumes the video is an advertisement. Or maybe it just assumes all ads contain dachshunds? Clever. Then it would never miss classify a dachshund video as NOT being an ad.
Finally, what's its false positive/negative rates for weasels and weimaraners? You can't be too careful with those wiener dogs. They like a good disguise.
This is just another form of tagging. Instead of teaching that "object A" is "#beach" there is some indirection, where pieces of the photo are compared to known attributes of a beach. It isn't that there are no tags. It's that the tags are dynamically applied in pieces. But it's still tagging, because you have to program the algorithm to recognize the properties of the object. This is why that IBM machine is so good at Jeopardy but totally unable to play Family Feud. The same thing here. It will never be able to recognize objects that are not tagged by algorithmic matching. The trick isn't to solve the tagging problem. The trick is to have the machine generate it's own tags, the way a baby learns that an orange smear on its retina is really a basketball -- without ever needing to be taught the concept of ball or space or 3D. The baby actually learns. This thing is just regurgitating tag data taught to it by a human. It's nice, but it's not intelligence.
thatsapenis.gif
"I believe in Karma. That means I can do bad things to people all day long and I assume they deserve it." : Dogbert
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APK
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So far, the people mentioning YouTube haven't mentioned copyright takedowns. https://www.youtube.com/result...
Sure you get access to powerful algorithms but aren't you also locked in with Google?
Couldn't OpenCOmputerVision do the same thing (I haven't had the time to experiment with it ) http://docs.opencv.org/2.4/doc/tutorials/ml/table_of_content_ml/table_of_content_ml.html#table-of-content-ml
At my last job, I had an unfortunate task where I discovered how incompetent Google and Microsoft (or any other company for that matter) were at interpreting text in images, and this after more than decade of hooting and hollering from all directions as to how the problem had been solved many times over.
Who convinces these organizations to try to convince the rest of us that they've got anything figured out for video now?!?
Reality is quickly outrunning the fantasies of the tech world...
Once their algorithm can parse video content, Google's AI will goof off all day everyday watching Youtube videos and never do anything productive any more.
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Google has finally found a way to translate everything. They harness the internets to do it for them. Otherwise, they can't use the internets.