The difference between the Internet on April Fool's Day and on other days is on the one it is packed with false stories full of pandering nonsense written by charlatans to gain page views, and on the other it is the first day of April.

And since air disasters necessarily depend on extremely low-probability events, this is not an argument for the proposition "therefore this was most likely not the cause".

We know that whatever happened it had an outrageously low probability. This makes speculation in advance of data useless, because there are an almost unlimited number of highly improbable things that could have happened, and anyone who thinks they can imagine their way to the correct one is innumerate: http://www.tjradcliffe.com/?p=...

From the tortured summary the only thing that's clear is that this technology is nothing like anything in Star Wars or Star Trek, but some illiterate in PR has decided that whatever they actually do is so boring, obscure or useless that the only way to drum up any attention for them is to describe them in terms of something completely unrelated.

Does anyone have any idea what they actually do and how they do it?

This is not even wrong. Payne had the idea first, Russell thought it was wrong, Russell later changed his mind and gave Payne credit: http://blogs.britannica.com/20... His work cites hers.

This is how science is supposed to work, although there is always a factor of fame involved in credit-giving, and women have in general not been as forceful in claiming or defending credit as men.

Furthermore, how many people claiming to be "outraged" by this were even aware of who had been given credit for figuring out the composition of the sun in the first place? Who amongst us is "shocked, shocked" that Russell--whom they had been giving credit to all these years, citing in papers, talking up at cocktail parties--didn't actually make the discovery that is commonly and incorrectly attributed to him?

And this differs from having children the old fashioned way how?

That is the crux: every child born is a genetic experiment today. We hope that it doesn't end up with too many defects. We hope that it's born with eyes (I know someone who wasn't). We hope that it's born without any non-lethal developmental defects (I know a couple of people who have them, caught and fixed by surgery before they became fatal.) We hope they won't develop Type I diabetes (like several of my friends have)... and so on.

Every one of these things is a crap-shoot, and everyone who has kids today is performing an uncontrolled genetic experiment every time.

To claim that this process is necessarily going to be made worse by adding some human intelligence to the mix is problematic. The claim that there is no conceivable therapeutic benefit to engineering certain classes of genetic defect out of the germline is disingenuous, unless you think everyone everywhere for the rest of time is going to have good gene therapy available to them while growing up, which is insane.

To claim "we can't predict what the effects might be so we shouldn't do the research" is bizarre: if we don't do the research, admittedly mostly on animal models, how will we ever know what the effects are? Once we've done the research, we will have a high confidence in the effects, just as we do with any other therapeutic intervention. We all know that iatrogenic disease is a major cause of death and suffering, so wringing our hands about germline modification as if it was unique in that respect is at the very least strange and at worst deeply hypocritical.

All power gets used, and it's understandable that people should be concerned about how the power to edit the human germline will be used. The possibilities for abuse are considerable. If we are ever able to create Brave-New-World style designer slaves, happy in their subjugation, we probably will, for some value of "we".

But the debate should be about how to use this power wisely, not whether we should develop it at all. Someone will, and it's better that that happen out in the open than in some secret lab in $EVIL_NATION or funded by $EVIL_BILLIONAIRE.

Cover design is hard, and most people do judge books by the cover. These books have content that is likely reflected by their covers pretty well, so in that sense I'd say most of them are pretty good.

The one a few pages in about the guy who's annoyed is really quite good: blunt, angry, simple. Since that's what the book looks to be like, how can the cover be bad?

For my book (http://www.amazon.com/Darwins-Theorem-TJ-Radcliffe-ebook/dp/B00KBH5O8K/ref=sr_1_1?s=digital-text&ie=UTF8&qid=1400044028&sr=1-1&keywords=darwin%27s+theorem) one of my first readers was an artist, so I hired her to do the cover art. It captures a lot of things about the book, and it's beautiful on its own, so it's a win.

But I'm sure a purist would find a million things wrong with it, from the ambiguities of the image to my choice of font (not papyrus or comic sans, but any font can be mocked if you work at it hard enough) to the choice of colours (too blue, not enough contrast) to the overall look (too cluttered, too busy)... and so on.

Still, my hope was to keep it reasonably low on the mockability scale, and while it's fun to mock stuff, but I have a depressing feeling that many of these mocked books are selling a lot better than a lot of less-mockable stuff. So maybe I should replace my cover with unicorns and rainbows and leather-clad half-dressed bikers to see if that boosts sales...

Others have pointed out that these were serials, not fixups, although some Victorian authors may have published fixups: the concept is ancient.

Two examples:

1) the Iliad is probably a fixup. The first bunch of books are heavily focused on Diomedes, who then more-or-less disappears completely from the story. There is some contention that the parts of books V and VI dealing with him were once a separate story.

2) going even further back, Gilgamesh is probably a fixup. There's a good deal of evidence that it was assembled from pre-existing stories of Gilgamesh and Enkidu (and also Utnapishtim, the Chaldean "Noah" who was lifted by the early Hebrews along with so much else).

3) and the Bible itself, which seems to have been written rather late in Jewish history, almost certainly assembled from pre-existing stand-alone tales, which explains the contradictions in the two stories of creation and so on.

I'm in the same boat, with the same languages. Python for convenience, C++ for speed. I also use C for really low level embedded (PIC) stuff, but that's it.

This combination gives me the optimal mix of portability and power for the problem domains I'm interested in, and at this point I don't see any reason to leave C++ for anything else. The big trick is to adopt and strictly adhere to a set of reasonable coding standards that keeps you from doing all the stupid things the language lets you do.

C++ demands a higher level of discipline and maturity from developers than most languages because Linus is right: it is incredibly easy to abuse. A bad programmer will write bad code in any language, but C++ makes it really easy for bad programmers to express themselves, and that's a bad thing. That doesn't mean the language is bad, but it does mean it should only be used where its advantages (portability, efficiency, expressive power) are sufficiently great to overcome its weaknesses (excessive complexity, mediocre type safety, excessive complexity.)

Those are great links. Thanks for posting them. But they appear to show the models almost exactly as bad as the the grandparent: both indicate reality is at the very bottom of the model prediction distribution. It's unfortunate that the grandparent is from such a sketchy source, as it demonstrates greater respect for the principles of visual display of information. It shows one thing, it shows it well, and axis that people care about (the vertical) is given reasonable scaling instead of being compressed away by cramming in multiple additional graphs.

Furthermore, consider the lameness of the first claim in the AR5 chapter you like: "Predictions for averages of temperature, over large regions of the planet and for the global mean, exhibit positive skill when verified against observations for forecast periods up to ten years"

This sounds good, until you realize that the best thing that can be said of the models' predictive capacity is that it is better than chance. That is what "positive skill means", and that is all it means.

As someone who has worked in predictive modelling, this is something that people only say when their model has no practical predictive utility. It is easy to get models that show results that are by any measure many standard deviations away from chance, but that are still completely useless for the kind of predictions required by policy makers. To take a trivial concrete example: a model that tells you to "drive east" when your destination is in fact in the eastern half-plane will give results that are far better than chance (which would be driving in any random direction) but it will only rarely get you anywhere close to where you want to go.

The report goes on to list a variety of positive results with varying confidence, but none of them add up to "predictively useful for policy makers" and that's for global and large-scale regional climate. Local climates--which are what we really care about--are far harder to predict.

This is not to say that models are bad science or "global warming is a hoax" or any such nonsense. There is fairly strong evidence that anthropogenic greenhouse gases are a significant contributor to climate change by adding 0.3% to Earth's heat budget at the surface, and that anthropogenic aerosols are likely removing about 0.1% of the effective insolation at the surface, for a net 0.2% gain. These conclusions come from observations on the ocean heat budget, the temporal distribution of warming (which is greater at night than in the day, for example, ruling out solar variation) and the geographic distribution of the warming. It's possible to say all of this--and so have fairly high confidence that humans are having a significant impact on Earth's climate--but still not have much of a clue how the highly non-linear climate system is going to respond in the near or long term.

In some ways, because our economic systems are relatively fine-tuned to the historical climate, which we can predict will undergo fairly significant variation even if we don't know precisely where or what, the details of the future climate matter less than the high confidence it is going to change. We should be investing in robust systems, or we will be facing a significant, ongoing global recession as climate conditions trash economic assumptions.

But claims like the one in TFA are necessarily strongly dependent on model details, and while it's an interesting study, it was done by climatologists, not computational physicists, and that shows in the excessive confidence they place in the detailed model results.

I'm a Canadian who has worked in the US as a non-resident alien, so had to file an American return some years. My Canadian accountant had a tame American accountant she sent clients like me to for stuff like that: US tax law is just too complex for foreigners to bother with.

But taxes aren't the only issue. The OP says, correctly, "My son would have to register for the draft".

This is not a small thing. I know someone who grew up in the US in the '60's--a Canadian born to Canadian parents in Canada whose family had moved to the US--who was refused permission to leave the country at the age of 18 because he was draft-eligible. He got out eventually, but it was a big legal hassle.

The draft is on hiatus just now, but there is no certainty it always will be.

So will you take my word as a computational physicist that climate models--which are nothing but computational physics done by climate scientists rather than computational physicists--are far too uncertain to be robust guides to public policy?

Because that is my professional opinion, and it happens that my profession is the one that matters when judging computational physics, whether it's done by climate scientists, Freeman Dyson, or anyone else.

I've read climate modelling papers. I've looked at climate modelling codes and there documentation (mostly AR4, which is somewhat out of date now.) I was appalled by what I saw: it's all a good attempt to work things out, there's nothing wrong with it as science at all, but I'd rather use Wall Street financial models to guide public spending policy than climate models to guide climate policy. They have a much greater chance of being accurate.

This is not to say that climate models aren't useful inputs to the policy debate, but their accuracy if fantastically over-estimated by policymakers. GCMs have gotten Arctic warming badly wrong (the Arctic has warmed much faster than anyone anticipated) and missed the current--likely temporary--flattening of "global average temperature" increase. This is no surprise you a) look at the models and b) have the professional competency of a computational physicist to judge them. They just don't do the things that accurate models integrated over long timescales have to do, like conserve mass and energy natively.

Models before around 2005 were especially bad with energy conservation, fixing it up by redistributing energy across cells after each time step. Climate scientists were apparently OK with that, because they didn't know enough computational physics. Anyone who has spent a career building models that eventually get checked against reality knows that that is a virtual guarantee that the result will be unphysical nonsense. This is not a political statement: it is simply a fact.

So by all means dis Dyson for not being a climate scientist. But since GCMs are computational physics, you must take my word as a computational physicist over climate scientists, or admit you really don't care who is saying what so long as they say what you agree with.

There are different ways of stating the problem.

1) "Technology is eliminating jobs! How will we cope with the unemployment?"

2) "Technology is increasing productivity! How will we distribute the gains?"

3) "Technology is reducing total workforce requirements! How will we reduce the work week?"

Each of these assumes a different fixed aspect of the economy. The first assumes that industrial capitalism will chug on, basically unchanged, while unemployment rises to unprecedented levels. History suggests this is unlikely.

The second assumes that productivity gains will continue without the incentive of paid work.

The third assumes that paid work will remain the only way of distributing productivity gains.

The rise of industrial capitalism saw enormous social upheaval. It is likely that the rise of total automation will produce something similar. We have no idea what that will be (I certainly don't) but it's important that we recognize that while not everything will change, everything could, and not confine our imaginary futures too narrowly. We're going to be wrong regardless (because our imaginations are terrible tools for knowing reality) but in this case we're more likely to fail by being too narrow in our view than too broad.

One common thread in science denial is post-modernism. The American Right is dominated by post-modernists at the moment, and the Left has been for decades.

By "post-modernists" I mean people who believe that objectivity is not just impossible but actually pernicious, that truth is a social construct, and that "different ways of knowing" are equally legitimate and culturally dependent.

This is in contrast to the scientific mindset that understands that while there is no view from nowhere there is also no view of nowhere, and works hard to see that place that exists independently of the knowing subject as clearly as possible. Pro-science people are Bayesians, so they know certainty is impossible (knowledge is uncertain; faith is certain, and also an epistemic error) and that Bayes' rule provides the only consistent way of updating our beliefs in the face of new evidence, so it doesn't matter what your ancestors or you pastor tells you, there is only one way of knowing.

I'd bet a lot of these "highly educated" anti-vaxxers are victims of post-modernism in this sense. It should be relatively easy to find out how well they know their Derrida, Laccan, Leotard and Foucoult compared to their more vaccination-friendly neighbours.

The odds aren't appreciably closer to zero, the enjoyment is the same or greater, there is no chance of disappointment, and the cost is zero.

If you invest the $104 a year you'd otherwise spend on lottery tickets then with interest at the end of 40 years (from age 20 to age 60) you will have accumulated about $9K, assuming 3.5% interest.

There are two things to say about this:

1) Diet and fitness are hard problems because humans evolved as opportunistic hunter-gatherer-scavengers, so we are moderately well adapted to almost any imaginable lifestyle. When the optimum is broad and shallow (which it necessarily is, especially for diet, unless you are an evolution denialist) it is easy to wander around in the noise.

This is made worse by snake-oil salespeople who are dedicated to the idea that the optimum is narrow and deep, and they can sell you its precise location. They take any minor wobble that scientists identify--which based on evolution is almost certainly noise--and declare it the One True Location of Perfect Health.

2) The alternative is stories. Science fails to get traction with the public because it lacks narrative, which is an idea I explore in a lot more depth here: http://www.amazon.com/Darwins-...