Follow Slashdot stories on Twitter

 



Forgot your password?
typodupeerror
×

Comment Re:Imagine that! (Score 1) 191

It surprises me that Google doesn't actually have their own online 'newspaper'. They could employ an editor to create a mashup of the best stories online, with a profit-sharing arrangement on ads.

I'd prefer a dedicated web page than, say, facebook injecting clickbait through their universally hated 'Top Stories'.

my two local newspapers have introduced paywalls, with a minimal number of free articles a month. One is fairly decent, the other is Rupert's trashy tabloid, complete with celebrity gossip and miracle weight loss cures. Syndicating the former through Google could reach an international audience, along with selected articles from other online sources and Google's ubiquity would ensure those articles chosen need not be subscription only.

But usually I stick to abc.net.au via RSS for news, despite the vandals in the federal government wanting to destroy it. 8 cents a day...

Comment Re:Wha?!?!!! (Score 1) 172

I read somewhere that NTVDM isn't supported in x86-64 because "long mode" won't execute "8086 Virtual Mode".

Yet supposedly MS could resurrect the software for 64 bit Windows by running the software via the VT-x CPU extension present in most recent x86-64 CPU revisions.

But I guess the effort to make the NTVDM subsystem 64 bit clean isn't worth it...

AI

A Common Logic To Seeing Cats and the Cosmos 45

An anonymous reader sends this excerpt from Quanta Magazine: "Using the latest deep-learning protocols, computer models consisting of networks of artificial neurons are becoming increasingly adept at image, speech and pattern recognition — core technologies in robotic personal assistants, complex data analysis and self-driving cars. But for all their progress training computers to pick out salient features from other, irrelevant bits of data, researchers have never fully understood why the algorithms or biological learning work.

Now, two physicists have shown that one form of deep learning works exactly like one of the most important and ubiquitous mathematical techniques in physics, a procedure for calculating the large-scale behavior of physical systems such as elementary particles, fluids and the cosmos. The new work, completed by Pankaj Mehta of Boston University and David Schwab of Northwestern University, demonstrates that a statistical technique called "renormalization," which allows physicists to accurately describe systems without knowing the exact state of all their component parts, also enables the artificial neural networks to categorize data as, say, "a cat" regardless of its color, size or posture in a given video.

"They actually wrote down on paper, with exact proofs, something that people only dreamed existed," said Ilya Nemenman, a biophysicist at Emory University.

Slashdot Top Deals

Ya'll hear about the geometer who went to the beach to catch some rays and became a tangent ?

Working...