Absolutely. Seems like a simple, easy solution. It's a win for the guys who otherwise have to queue up for years for H1B, and it's a win for the guys that dont want to compete for jobs with people paid three times less than them.

So, why not fork wikipedia? What's to stop that? Or is it like, it's not ideal, but it mostly works ok?

On the whole, my own experiences with Wikipedia have been more or less ok:
- as a contributor: on high traffic pages, trying to edit something is not going to get very far. But... whatever
- as a contributor: on low-traffic pages, as far as I know, edits mostly go through, unless you say something that conflicts too much with someone else's agenda. Adding equations: works ok. Adding some opinion on someone's personal bio page: might not get very far
- as a reader/end-user: most stuff is approximately correct, most of the time, at least for the uses I make of it, ie looking up some scientific or mathematical concept

Well, iphones have less memory than Android devices at the same price point. iPhone 6 has 1GB memory https://en.wikipedia.org/wiki/... Even the Zuk Z1, which is 2-3 times cheaper, has 3GB ram... https://en.wikipedia.org/wiki/...

So, it's more like, ios somehow manages to run things efficiently, using less memory than its android counterparts. But it doesnt take much to push ios outside the envelope of reasonable performance, given the limited available memory of iphone devices.

I have a ZUK Z1, and after a full day, 6am to 6pm, it's somewhere around 60-80%, depending on how much I've been using it. Admittedly it weighs 180g or so, but seems not to be a downside to me.

I think it's more like, people who say AI will never happen are imagining the kind of AIs in terminator: androids walking around with lasers.

This xkcd says it quite well: http://www.xkcd.com/652/

Or more concretely:
- our primary industry, ie mines and so on, are increasingly automated
- second industry, ie factories, are heavily automated, already
- tertiary, ie services, are well under way
- military (drones and so on) is well under way

There is a quota of 80,000 H1Bs per year. This is currently filled randomly, according to a lottery. Why not simply rank the applicants by their salary, from highest first, and give an H1B to the top 80,000 salaries?

Solves two problems, win-win:
- makes sure that only the most critical employees enter
- means that those critical employees can enter easily, without having to do endless lotteries...

Have you seen the roads around Baidu headquarters, ie near Wudaokou? Jam packed with traffic, except at 4am. From around 7am in the morning, it takes 20-30 minutes to go a couple of kilometres...

Usually, you need a mixture of approaches to get things to work. Idealism in software engineering, or in engineering, works about as well as idealism in politics, ie it doesnt really, it misses key points. But, in both areas, it's much easier to create a platform on idealism, and so people who propose one single idealistic viewpoint often do quite well.

In practice, in software engineering, saying 'all tests must be automated, 100%', misses that some things are really hard to test automatically, but can be tested by hand quite simply. Similarly for creating test harnesses, mocking, which this article is the hardware-engineering equivalent for. Sometimes it's easier to mock, and do real 'unit-testing', and sometimes it isnt, and insisting that every project, and every part of every project, uses the exact uniform standard, might not always work as well as it looks like it will in the Powerpoint presentation :-P

Pale Moon is trademarked, https://github.com/MoonchildPr... If you fork it, you have to change the name, just like the original Firefox, and also Truecrypt.

this is one of those articles where what the article says, and what people think, have a discrepancy. It reminds me of articles with titles like:

"Java developers claim uses no more memory than C++"
"C++ developers claim no more bugs than python"
"Python developers claim runs as fast as C"

They're using a standard technique. Convolutional networks started to become big with LeCun's 1998 paper on learning to recognize hand-written digits http://yann.lecun.com/exdb/pub... . His lenet-5 network could identify the digit accurately 99% of the time.

Convolutional networks are starting to become used to play Go, eg 'Move evaluation in Go using Deep Convolutional Neural Networks', by Maddison Huang, Sutskever and Silver, http://arxiv.org/pdf/1412.6564... Maddison et al used a 12-layer convolutional network to predict where an expect would move next with 50% accuracy :-)

Progress on convolutional networks moves forward all the time, in an incremental way. If we had one article per day about one increment it would quickly lose mass appeal though :-) The article is about one increment along the way, but does symbolize the massive progress that is being made.

Convolutional networks work well partly because they can take advantage of the massive computional capacity made available in GPU hardware.

Yes, check this out 'High Confidence Predictions for Unrecognizable Images', by Nguyen, Yosinkski and Clune, http://arxiv.org/abs/1412.1897 . It's a paper that shows an image that the net is 99.99% sure is an electric guitar, but looks nothing like :-)

For the technically minded, the paper's authors propose that the reason is that the network is using a discriminative model, rather than a generative model. That means that the network learns a mathematical boundary that separates the images that it sees, in some kind of high-dimensional transformed space. It doesn't learn how to generate such new images, ie, you cant ask it 'draw me an electric guitar' :-) Maybe in a few years :-)

The authors don't compare the network too much with the human brain though, ie, are they saying that the human brain is using a generative model? Is that why the human brain doesn't see a white noise picture, and claim it's a horse?

"Democracy is the worst form of government, except for all the others" - Winston Churchill

Note that encfs is perfect for this:
- encrypts using AES-256
- easy to use
- works on linux :-)
- and there's at least one app for Android that is compatible with the encryption protocol
- each file still is stored as a single file so:
      -- no issues with losing all your data at once :-)
      -- replication can still be file by file
- works through Fuse, doesn't need admin rights, kernel drivers and stuff :-)

http://www.arg0.net/encfs
http://en.wikipedia.org/wiki/E...