Ideas  

In a turn-it-on-it's-head business strategy, Tesla CEO Elon Musk just announced that all of the company's patents will be available and they will not pursue legal action to anyone that uses them.  Could this be the boost that the will push the electric car into the mainstream?

Anyone familiar with the culture of most high-tech companies will be familiar with the belief in creating and hoarding patents in a type of corporate brinkmanship.  Now Tesla CEO Elon Musk is breaking another convention by open sourcing all of the company's patents, making its inventions available for anyone who wants to use them. Will this finally be the tool to open up electric vehicles?

"Too often these days [patents] serve merely to stifle progress, entrench the positions of giant corporations and enrich those in the legal profession, rather than the actual inventors."

In a blog post titled "All Our Patent Are Belong To You" published on Tesla's site, Musk writes that "Tesla Motors was created to accelerate the advent of sustainable transport. If we clear a path to the creation of compelling electric vehicles, but then lay intellectual property landmines behind us to inhibit others, we are acting in a manner contrary to that goal."

Regarding Tesla patents http://t.co/gGBWoInh6C
— Elon Musk (@elonmusk) June 12, 2014

Musk writes:

When I started out with my first company, Zip2, I thought patents were a good thing and worked hard to obtain them. And maybe they were good long ago, but too often these days they serve merely to stifle progress, entrench the positions of giant corporations and enrich those in the legal profession, rather than the actual inventors. After Zip2, when I realized that receiving a patent really just meant that you bought a lottery ticket to a lawsuit, I avoided them whenever possible. 

At Tesla, however, we felt compelled to create patents out of concern that the big car companies would copy our technology and then use their massive manufacturing, sales and marketing power to overwhelm Tesla. We couldn’t have been more wrong. The unfortunate reality is the opposite: electric car programs (or programs for any vehicle that doesn’t burn hydrocarbons) at the major manufacturers are small to non-existent, constituting an average of far less than 1% of their total vehicle sales.

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"If we clear a path to the creation of compelling electric vehicles, but then lay intellectual property landmines behind us to inhibit others," writes Musk, who also heads SpaceX, "We are acting in a manner contrary to that goal. Tesla will not initiate patent lawsuits against anyone who, in good faith, wants to use our technology."

Musk believes that Tesla, other companies making electric cars, and the world would all benefit from a common, rapidly-evolving technology platform. "We believe that applying the open source philosophy to our patents will strengthen rather than diminish Tesla’s position in this regard," he writes.

Perhaps the news isn't so surprising, given the fact that Musk recently gave away what might be another billion dollar business idea in the Hyperloop concept.

Time will tell if the strategy works; both for Tesla and for the environment. It is also unclear if SpaceX, Solar City and Musk's other ventures will follow this path.


SOURCE  Tesla

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 Computer Science  

A new algorithm that tags photos based on the relationships that people in images already have with each other has been developed at the University of Toronto. The algorithm uses the name and location of existing photo tags to build a "relationship graph," where personal connections in the images are calculated.

A new algorithm designed at the University of Toronto has the power to profoundly change the way we find photos among the billions on social media sites such as Facebook and Flickr.  This month, the United States Patent and Trademark Office have issued  patent #8,611,673 on this technology.

Developed by Parham Aarabi, a professor in The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, and his former Master’s student Ron Appel, the search tool uses tag locations to quantify relationships between individuals, even those not tagged in any given photo.

"Essentially, we found that if people are standing close together or are tagged close together inside images – in one image it doesn't tell you a lot of information. But across hundreds of images that someone has on Facebook, it's a very good indicator of how close they are in real life, in a social sense," Aarabi told CTVNews.ca in a phone interview.

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Imagine you and your mother are pictured together, building a sandcastle at the beach. You’re both tagged in the photo quite close together. In the next photo, you and your father are eating watermelon. You’re both tagged. Because of your close ‘tagging’ relationship with both your mother in the first picture and your father in the second, the algorithm can determine that a relationship exists between those two and quantify how strong it may be.

In a third photo, you fly a kite with both parents, but only your mother is tagged. Given the strength of your ‘tagging’ relationship with your parents, when you search for photos of your father the algorithm can return the untagged photo because of the very high likelihood he’s pictured.

“Two things are happening: we understand relationships, and we can search images better,” says Professor Aarabi.

The nimble algorithm, called relational social image search, achieves high reliability without using computationally intensive object- or facial-recognition software.

“If you want to search a trillion photos, normally that takes at least a trillion operations. It’s based on the number of photos you have,” says Aarabi. “Facebook has almost half a trillion photos, but a billion users—it’s almost a 500 order of magnitude difference. Our algorithm is simply based on the number of tags, not on the number of photos, which makes it more efficient to search than standard approaches.”

Work on this project began in 2005 in Professor Aarabi’s Mobile Applications Lab, Canada’s first lab space for mobile application development.

Currently the algorithm’s interface is primarily for research, but Aarabi aims to see it incorporated on the back-end of large image databases or social networks. “I envision the interface would be exactly like you use Facebook search—for users, nothing would change. They would just get better results,” says Aarabi.

While testing the algorithm, Aarabi and Appel discovered an unforeseen application: a new way to generate maps. They tagged a few photographs of buildings around the University of Toronto and ran them through the system with a bunch of untagged campus photos. “The result we got was of almost a pseudo-map of the campus from all these photos we had taken, which was very interesting,” says Aarabi.


SOURCE  University of Toronto

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 Apple

A new Apple patent application signals that iOS may be getting a facial recognition security update. The patent is titled “3-D Object Recognition” and is said to describe a new way to generate 3D facial models using 2D images. The patent was originally filed by a firm called Polar Rose from Sweden that Apple purchased in 2010.

A new Apple patent application describing face-recognition technology suggests an interesting security update for iOS. And that could be just the beginning of what the technology might enable.

The patent titled, “3D Object Recognition,” describes a novel way to generate 3D models using 2D images. It’s a follow-up to a patent Apple already owns, originally filed by Swedish firm Polar Rose, which Apple purchased in late 2010.

In essence, the technology would use multiple photos, or even video, to create a robust 3D representation of a user’s face. With this 3D representation locked in, it could then be compared, on the fly, to a 3D representation built in real time from a 2D image captured from a user’s phone.

The system has obvious applications in system security — namely, a home screen unlocking mechanism that’s not easily fooled. But the technology need not be limited to just face detection. It could also be used to identify an entire body, or employed in medical applications to identify specific organs, or even tumors.

Another Apple patent application dealing with facial recognition discussed a lower-power-intensive way to identify a device owner when he or she approaches the system. And, of course, Apple already employs face detection for identifying people in iPhoto images, but doesn’t use the feature for system security in iOS.

The patent states that there are inherent challenges in using current facial recognition technology in system security. Variations in ambient illumination and face positioning can make it difficult to reliably match source images to real-time camera images.

Apple’s proposed patent gets around the lighting roadblock by analyzing features like corners and other spatial points of reference rather than performing direct image correlation or comparisons of image parts. As for the positioning issue, it can be resolved by using multiple images for your security system’s source material. This way, even if you try to gain access to your phone by looking at its camera from a slightly askew angle, the system will have that angle in its reference library, and still let you in.


SOURCE  Wired

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