The key observation here is that you're much likely to see false positives coming from the implausible than from the plausible. This is simple statistics -- if p=.05, that means there's a 5% chance that "no effect" would be mistaken for "effect". In cases where there should be no effect (prior probability near 0), 5% of the time you'll get a false positive and almost 0% of the time you'll get a real positive. In cases where it's plausible there could be a real effect (say, prior probability 50%), you'll get false positives only 2.5% of the time (5% of the 50% there isn't an effect) to go with 50% real positives.
Thus, the argument goes, in order to reduce the ratio of false positives to real signal, we should require more signal from implausible experiments. That is, we should make the required p value scale with the prior probability. This is a form of bias, but it's a very appropriately scientific form of bias -- bias based on evidence rather than error-prone forms of cognition. (This is simply a statistical reframing of the statement "extraordinary claims require extraordinary evidence".)

When a dog owner wants to train his dog, the procedure is well-known and quite simple. The owner runs two loops: one of positive feedback and one of negative ditto. Whenever the dog does something right, the positive feedback loop is invoked and the dog is treated with a snack. Whenever the dog does something wrong, the dog is scolded and the negative feedback loop is used.

The result is positive and negative reinforcement of the dogs behavior. The dog will over time automatically behave as the owner wants and never even think of misbehaving.

When a programming language trains its leashed programmer, it likewise uses positive and negative feedback. Whenever a problem is easily solvable in the constructs and features of said language, it reinforces the use of those features and constructs. And also in the same vein, if something is hard to do in the language, the programmer will shy away from thinking the idea, since it may be too hard to do in the language. Another negative feedback loop is when resource usage of a program is bad. Either it will use too much memory of too many CPU resources to carry out its work. This discourages the programmer from using that solution again.

The important point is that while all practical general purpose languages are Turing complete, the way they train programmers to behave as they want is quite different. In an Object Oriented language for instance, the programmer is trained to reframe most - if not all - questions as objects of bundled fields and methods. A functional programmer is trained to envision programs as transformations of data from the form X into the form Y through the application of a function. And so on.

All of Earth's Water in a Single Sphere

Both the presence of zinc deposits and veins of gypsum are very suggestive—water was likely once present in the Endeavour Crater region. Comparison with sandstone found elsewhere on Mars hints that Cape York's water was transitional. The hydrothermal deposits mark the early period, when volcanic activity was more common, while the evaporative deposits show a later period, when seas covered much of the Martian surface. The warm water required to form and precipitate gypsum hints that perhaps transient pools may have been habitable

Mathematics for Computer Science
revised Monday 19
th March, 2012, 17:49
Eric Lehman
Google Inc.

It turned out that those subjects with a growth mindset were significantly better at learning from their mistakes. As a result, they showed a spike in accuracy immediately following an error. Most interesting, though, was the EEG data, which demonstrated that those with a growth mindset generated a much larger Pe signal, indicating increased attention to their mistakes. (While those with an extremely fixed mindset generated a Pe amplitude around five, those with a growth mindset were closer to fifteen.) What’s more, this increased Pe signal was nicely correlated with improvement after error, implying that the extra awareness was paying dividends in performance. Because the subjects were thinking about what they got wrong, they learned how to get it right.

The problem with praising kids for their innate intelligence — the “smart” compliment — is that it misrepresents the psychological reality of education. It encourages kids to avoid the most useful kind of learning activities, which is when we learn from our mistakes. Because unless we experience the unpleasant symptoms of being wrong — that surge of Pe activity a few hundred milliseconds after the error, directing our attention to the very thing we’d like to ignore — the mind will never revise its models. We’ll keep on making the same mistakes, forsaking self-improvement for the sake of self-confidence. Samuel Beckett had the right attitude: “Ever tried. Ever failed. No matter. Try Again. Fail again. Fail better.”

Rereading Darwin
Science now takes for granted the importance of forces and time spans we can’t perceive directly

So it’s worth taking a moment to contemplate what we now know: The Earth is 4,540,000,000 years old. Life has been around for at least 3,500,000,000 of those years.

In 2010, scientists discovered that even at lower latitudes, the moon is not entirely dry, with faint traces of ice surviving beneath the surface, making lunar soil about twice as wet as the sands of the Sahara — which by moon standards is practically drenched. Now, NASA's Lunar Reconnaissance Orbiter (LRO) has found that the PSRs indeed have a whole lot more water than that, with up to 2% of the surface in those blacked-out regions consisting of ice crystals.

A collection of the best open data sets and open-source tools for data science, wrapped in an easy-to-use REST/JSON API with command line, Python and Javascript interfaces. Available as a self-contained VM or EC2 AMI that you can deploy yourself.

When you crumple up your gift-wrapping paper this year, you'll create a shape so complex that it has defeated the most sophisticated computers

the LHC was built to figure out what the Higgs field is (or Higgs fields are), how it works (or they work), and whether it is (or they are) elementary or composite.

A virus with the potential to kill up to half the world’s population has been made in a lab. Now academics and bioterrorism experts are arguing over whether to publish the recipe, and whether the research should have been done in the first place.

Electrical stimulation of subjects' brains is found to accelerate learning in military and civilian subjects, although researchers are yet wary of drawing larger conclusions about the mechanism

Navier-Stokes

This is incredible...researchers at Berkeley have developed a system that reads people's minds while they watch a video and then roughly reconstructs what they were watching from thousands of hours of YouTube videos. This short demo shows how it works:

Smithsonian scientists and colleagues report that snails successfully crossed Central America, long considered an impenetrable barrier to marine organisms, twice in the past million years -- both times probably by flying across Mexico, stuck to the legs or riding on the bellies of shorebirds and introducing new genes that contribute to the marine biodiversity on each coast.

The tree design takes up less room than flat-panel arrays and works in spots that don't have a full southern view. It collects more sunlight in winter. Shade and bad weather like snow don't hurt it because the panels are not flat. It even looks nicer because it looks like a tree. A design like this may work better in urban areas where space and direct sunlight can be hard to find.

Whether you’re using wireless internet in a coffee shop, stealing it from the guy next door, or competing for bandwidth at a conference, you’ve probably gotten frustrated at the slow speeds you face when more than one device is tapped into the network. As more and more people—and their many devices—access wireless internet, clogged airwaves are going to make it increasingly difficult to latch onto a reliable signal.

But radio waves are just one part of the spectrum that can carry our data. What if we could use other waves to surf the internet?

Plate tectonics is the great unifying theory of geology, which makes it all the more amazing that it has only been accepted for about 50 years. If you think we’ve got it all figured out by now, a paper published this week in Science may surprise you. And you'd be wrong if you were expecting to read about some dusty rock cores. The new information comes from a much shinier source: diamonds.

Contrary to popular culture, diamonds are not formed from the metamorphosis of coal under tremendous heat and pressure. It makes for nice poetry, but it’s not true. The real story is actually a bit more interesting than that.