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Comment Re:Let's Stand Up - A Call to Action (mildly O/T) (Score 4, Informative) 241

Why don't we, through /., set up a site, aggregate information about similiar cases and build up a body of evidence to "[...] show that the RIAA engaged in serial bad-faith lawsuits [...]". In the long run, the space could serve as a place for debate on the current copyright regime, the inflated monetary value assigned to the songs/movies downloaded, etc.

It seems to me like Groklaw would be a perfect place for this sort of activity. After all, isn't it the sort of thing they did in the early days of the SCO trial?

Submission + - Warning: Vista gadgets a potential malware vector

Torodung writes: This in, from the Microsoft Technet Flash newsletter:

A final security note: If you are running Windows Vista Sidebar Gadgets, they are subject to cross-site scripting style bugs. These bugs are extremely serious because script in the Sidebar is capable of running arbitrary code in the context of the locally logged-on user. This article outlines some of the secure programming best practices that should be considered when building Windows Vista Sidebar Gadgets. Check out Inspect Your Gadget for some of the secure programming best practices that should be considered when building Windows Vista Sidebar Gadgets.
In summary, badly coded Gadgets are a potential spyware/malware vector in the Windows operating system, as ActiveX and BHO's were previously, and Gadget input needs to be scrubbed for the same URI problems that Firefox recently fixed in v2.0.0.6, amongst other pitfalls. If you use Vista, you need to keep a careful eye on your Gadgets, and if you code a Gadget, the linked article gives some "best practices" to avoid becoming part of the problem.

Submission + - Algorithm That Seemlesly Patches Holes in Images (

Beetle B. writes: "From the site:

'What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of image completions and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.'

English translation: The algorithm replaces arbitrarily shaped blank areas in an image with portions of images from a huge catalog in a totally seamless manner."

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