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Comment: Re:Mixed feelings (Score 1, Informative) 694

by fatherjoecode (#40461615) Attached to: ADA May Force Netflix To Provide Closed Captioning On Content

I am all for "fair access" but if the CC was not made available by the content maker, than how is it netflixes fault for not having them? Shouldnt the judge be charging the movie maker for not providing CC to begin with??

There are no CC's on any Netflix streaming videos. None. Even if the the movie producer provides CC on the DVD, Netflix can't be bothered transmitting it on the streamed content.

Comment: Don't know why link To Original Source is ... (Score 1) 1

by fatherjoecode (#40461443) Attached to: Google's Neural Network Teaches Itself to Recognize Cats
fouled up.

It connects to an NY Times log-in page. Here's the original link again.

And here's the text of the article:
June 25, 2012
How Many Computers to Identify a Cat? 16,000 By JOHN MARKOFF

MOUNTAIN VIEW, Calif. — Inside Google’s secretive X laboratory, known for inventing self-driving cars and augmented reality glasses, a small group of researchers began working several years ago on a simulation of the human brain.

There Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own.

Presented with 10 million digital images found in YouTube videos, what did Google’s brain do? What millions of humans do with YouTube: looked for cats.

The neural network taught itself to recognize cats, which is actually no frivolous activity. This week the researchers will present the results of their work at a conference in Edinburgh, Scotland. The Google scientists and programmers will note that while it is hardly news that the Internet is full of cat videos, the simulation nevertheless surprised them. It performed far better than any previous effort by roughly doubling its accuracy in recognizing objects in a challenging list of 20,000 distinct items.

The research is representative of a new generation of computer science that is exploiting the falling cost of computing and the availability of huge clusters of computers in giant data centers. It is leading to significant advances in areas as diverse as machine vision and perception, speech recognition and language translation.

Although some of the computer science ideas that the researchers are using are not new, the sheer scale of the software simulations is leading to learning systems that were not previously possible. And Google researchers are not alone in exploiting the techniques, which are referred to as “deep learning” models. Last year Microsoft scientists presented research showing that the techniques could be applied equally well to build computer systems to understand human speech.

“This is the hottest thing in the speech recognition field these days,” said Yann LeCun, a computer scientist who specializes in machine learning at the Courant Institute of Mathematical Sciences at New York University.

And then, of course, there are the cats.

To find them, the Google research team, led by the Stanford University computer scientist Andrew Y. Ng and the Google fellow Jeff Dean, used an array of 16,000 processors to create a neural network with more than one billion connections. They then fed it random thumbnails of images, one each extracted from 10 million YouTube videos.

The videos were selected randomly and that in itself is an interesting comment on what interests humans in the Internet age. However, the research is also striking. That is because the software-based neural network created by the researchers appeared to closely mirror theories developed by biologists that suggest individual neurons are trained inside the brain to detect significant objects.

Currently much commercial machine vision technology is done by having humans “supervise” the learning process by labeling specific features. In the Google research, the machine was given no help in identifying features.

“The idea is that instead of having teams of researchers trying to find out how to find edges, you instead throw a ton of data at the algorithm and you let the data speak and have the software automatically learn from the data,” Dr. Ng said.

“We never told it during the training, ‘This is a cat,’ ” said Dr. Dean, who originally helped Google design the software that lets it easily break programs into many tasks that can be computed simultaneously. “It basically invented the concept of a cat. We probably have other ones that are side views of cats.”

The Google brain assembled a dreamlike digital image of a cat by employing a hierarchy of memory locations to successively cull out general features after being exposed to millions of images. The scientists said, however, that it appeared they had developed a cybernetic cousin to what takes place in the brain’s visual cortex.

Neuroscientists have discussed the possibility of what they call the “grandmother neuron,” specialized cells in the brain that fire when they are exposed repeatedly or “trained” to recognize a particular face of an individual.

“You learn to identify a friend through repetition,” said Gary Bradski, a neuroscientist at Industrial Perception, in Palo Alto, Calif.

While the scientists were struck by the parallel emergence of the cat images, as well as human faces and body parts in specific memory regions of their computer model, Dr. Ng said he was cautious about drawing parallels between his software system and biological life.

“A loose and frankly awful analogy is that our numerical parameters correspond to synapses,” said Dr. Ng. He noted that one difference was that despite the immense computing capacity that the scientists used, it was still dwarfed by the number of connections found in the brain.

“It is worth noting that our network is still tiny compared to the human visual cortex, which is a million times larger in terms of the number of neurons and synapses,” the researchers wrote.

Despite being dwarfed by the immense scale of biological brains, the Google research provides new evidence that existing machine learning algorithms improve greatly as the machines are given access to large pools of data.

“The Stanford/Google paper pushes the envelope on the size and scale of neural networks by an order of magnitude over previous efforts,” said David A. Bader, executive director of high-performance computing at the Georgia Tech College of Computing. He said that rapid increases in computer technology would close the gap within a relatively short period of time: “The scale of modeling the full human visual cortex may be within reach before the end of the decade.”

Google scientists said that the research project had now moved out of the Google X laboratory and was being pursued in the division that houses the company’s search business and related services. Potential applications include improvements to image search, speech recognition and machine language translation.

Despite their success, the Google researchers remained cautious about whether they had hit upon the holy grail of machines that can teach themselves.

“It’d be fantastic if it turns out that all we need to do is take current algorithms and run them bigger, but my gut feeling is that we still don’t quite have the right algorithm yet,” said Dr. Ng.

This article has been revised to reflect the following correction:

Correction: June 25, 2012

An earlier version of this article misstated the size of the human visual cortex.

AI

+ - Google's Neural Network Teaches Itself to Recognize Cats-> 1

Submitted by
fatherjoecode
fatherjoecode writes "I thought this was so cool:

Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own.

Presented with 10 million digital images found in YouTube videos, what did Google’s brain do? What millions of humans do with YouTube: looked for cats.

The neural network taught itself to recognize cats, which is actually no frivolous activity. This week the researchers will present the results of their work at a conference in Edinburgh, Scotland. The Google scientists and programmers will note that while it is hardly news that the Internet is full of cat videos, the simulation nevertheless surprised them. It performed far better than any previous effort by roughly doubling its accuracy in recognizing objects in a challenging list of 20,000 distinct items.

It's not just humans that are looking at cat videos."
Link to Original Source

Education

+ - High School TED Class thanked by Chris Anderson->

Submitted by Anonymous Coward
An anonymous reader writes "An independent school in Dayton, OH has created a class around the videos and philosophy of the TED conferences that has reached a global audience itself. Students in the class not only discuss and dissect selected presentations — this year's group actually created their own response videos in a YouTube channel set up by their teacher. Chris Anderson, owner and curator of TED, even directly responded to the class' thank yous in a personal and touching off-the-cuff video."
Link to Original Source
Programming

+ - Last surviving ENIAC programmer has died.->

Submitted by
fatherjoecode
fatherjoecode writes "Jean Bartik passed away on 4 April 2011. She "was the last surviving member of the group of women who programmed the Eniac, ..., which is credited as the first all-electronic digital computer". For must of my life I was mistaken in the belief that the films of the woman who turned the dials of ENIAC were following programming instructions from someone else. It turns these women were the programmers and their contributions went unrecognized for many decades."
Link to Original Source
Google

+ - Google's Electric Car Scheme Kills the Road Trip?->

Submitted by i4u
i4u (234028) writes "There's nothing more emblematic of the American spirit than the road trip. It's the most authentic expression of the feeling of Manifest Destiny that doesn't involve, y'know, murdering people. Few things in life do more to clear your head and revitalize your soul than a lonely drive through the desert or up and down a mountainous coast. Road trips are the best...but we might be the last generation to truly enjoy them.

Google wants robots to drive our cars."

Link to Original Source
Google

+ - Google Lobbies Nevada To Allow Self-Driving Cars-> 1

Submitted by b0bby
b0bby (201198) writes "The NY Times reports that "Google, a pioneer of self-driving cars, is quietly lobbying for legislation that would make Nevada the first state where they could be legally operated on public roads. ...The two bills, which have received little attention outside Nevada’s Capitol, are being introduced less than a year after the giant search engine company acknowledged that it was developing cars that could be safely driven without human intervention. ""
Link to Original Source

+ - Mainstream Media Looks at Anonymous->

Submitted by
ScuttleMonkey
ScuttleMonkey writes "In an uncharacteristically accurate writeup of Anonymous, the Guardian has published a look at the assembled mob behind the mask. A great place to send those unfamiliar with who or what Anonymous really is. 'This collective identity belongs to no one in particular, but is at the disposal of anyone who knows its rules and knows how to apply them. Anonymous, the collective identity, is older than Anonymous, the hacktvist group – more to the point, I propose that the hacktivist group can be understood as an application of Anonymous, the collective identity.'"
Link to Original Source

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