Google Can Now Recognize Objects in Videos Using Machine Learning (theverge.com) 47
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.
So what is the practical application? (Score:3)
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?
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Same as for photos. Save the user having to manually tag them. Enable natural language search like on Star Trek.
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Same purpose for which Google was founded -- Indexing and Search.
As a consequence, this will make it easier for them to develop things like more accurate copyright enforcement. Instead of encoding and indexing features of videos, they can now be indexed with higher-level labels ("John Oliver", "episodes of [SHOW]", etc). This tech will be able to counter current Youtube copyright-detection-circumvention techniques such as cropping, scaling, and image-mirroring. Not only can videos be indexed by the identif
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"Show me the video where [PERSON] talked about [OBJECT]"
Oooh, oooh, wait, I know that one!!
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Re:Copyright takedowns (Score:1)
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Re: So what is the practical application? (Score:1)
Digital fingerprinting of everyone that's ever submitted a video. Good luck getting a job in a few years if you've ever done amateur porn to "pay for college." This tech will also end up helping security cameras detect normality in real time. Didn't go on your morning walk today? It'll know. Also, City Cop training will go from 6 months to 2 tops and AI does all thinking for them with claims of it being "objective." in determining what is suspicious or not. Think drones from the TV show "Colony" but powered
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Access to Google's APIs for anything that amounts to more than hobbyist use is paid. Google will sell API services to companies needing to classify things in their videos, just like they do with their Vision API right now. Google has revenue streams other than advertising.
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Better search. So much of the internet is video now.
By any chance... (Score:3)
Did it report that the dog was evil, paranoid, a Nazi, in the KKK, or planning a coup?
http://searchengineland.com/go... [searchengineland.com]
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Now you won't have to fast forward through Monsters Ball to see Halle Berry's berries. ;)
Could have just watched Swordfish.. It's odd seeing Wolverine staring Storm's boobies.
But can the AI recognize EVIL objects? (Score:3)
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.
BeenThereDoneThat (Score:1)
I also invented such a tool. It's accurate 70% of the time.
Here's the code:
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I also invented such a tool. It's accurate 70% of the time.
Here's the code:
You need to wrap it in a delay loop to reach 70% accuracy. You have to make it wait long enough for the copyright infringing videos to be deleted. If you want to include all of those transient videos then I think we can get to 80% or 90% with a two-answer program. If less than the delay time, the answer is "Copyright infringement" and if the video is older than the delay time, it switches to "Cat video" as the answer.
Need to research the modal time to deletion for copyrighted videos on YouTube... I have bee
T-100 (Score:1)
identified : human . kill .
The nuts and bolts of this? (Score:2)
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."
What if the video colors were inverted? (Score:2)
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Well, it's really machine learning, and of course machine learning is 'just' pattern matching of a sort. The important thing is that the ML system (in particular deep learning) is learning what to match. Before deep learning, the features that object recognition used were usually hand-created, consisting of SIFT points, HOGs, etc. and then the image would be represented by some array of these features that could then be classified (using a SVM or other technique). the deep learning part is that it learns
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Thank you for the SIFT, HoG, and SVM tags, I do a bit of optimization in my job and I was curious if some of the things we do were applied in similar spaces. I know now the short answer is 'sort of.'
That's . . . (Score:2)
thatsapenis.gif
Self-Delusion (Score:1)
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...
This will be the end of Google (Score:2)