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Climate change also serves to hobble their rich industrialized enemies and provide an excuse for building nuclear plants.

HP has been hyping memristors for a while now, and it seemed unlikely then and even more unlikely now given their corporate woes. Unless there's something new like a shipping product, why the submission?

Running a Winter Olympics is also 'simply an engineering task at this point'.

> The antagonistic pleiotropy theory actually advocates exactly that inverse correlation, more investment into young years for increased reproductive fitness at the expense of worse later years.

Which would be great if you had any evidence that BMI is largely influenced by such antagonistic pleiotropy. But since BMI is not a disease like Alzheimer's, it doesn't even have prima facie plausibility. This shouldn't be hard: does low BMI in youth predict high BMI at middle or old age? I've never seen any result ever hinting at this, and no one believes that.

> I have concerns about the validity exactly because of the expected tiny effects.

Yes, it does make it harder, but fortunately, that's what we have polygenic scores for. Do you have any power analysis suggesting that the sample size here is inadequate?

> Polygenic traits with extremely high heritability (height being the prime example) top out at 10% of variance explained even when considering all alleles.

Totally wrong, where did you get this idea? The height polygenic score is at >>10% of variance (see Wood or http://ije.oxfordjournals.org/content/45/2/417.full ) and BMI polygenic scores are already at 10% and will go up since all the twin and GCTA estimates indicate larger heritability than that.

> Considering that natural selection is generally considered to not operate on post-reproductive phenotype (prime case is antagonistic pleiotropy literature) I consider any conclusion based on these measures pretty suspect.

Again, why? Is there any reason to think that late life BMI will inversely correlate with BMI such that the old fat people were actually the skinny young people? If it's just measurement error, then it's no worse than most variables which get used in health or sociology research.

> If you can't see selection at high effect alleles I'm not sure you'll be able to detect them in aggregate either, especially with very noisy phenotype data.

All of these are highly polygenic traits. A 'high effect allele' means explaining 1% or less of variance. Selection on such a trait is going to shift the frequency by a tiny amount. Grossly underpowered individually. You have to consider them jointly. Noisy phenotype makes that more, not less, true.

> Still doesn't make much sense to use a secondary trait like educational attainment (58% heritability at highest) over a primary one like IQ (>80% heritability).

Educational attainment is phenotyped much more often than is IQ, so it's both available in this dataset and available in the much larger datasets of the GWAS in question. Aside from being a phenotype of interest in its own right and a case of looking under the lamppost, EA also proxies for intelligence on both the genetic and phenotype level. (In some cohorts, like the UK Biobank, the cognitive performance test used has such low test-retest reliability that anyone who is looking for intelligence variants is going to want to use the education variable anyway!)

> Maybe I missed something, but how well does BMI measured at age 45-50 correlate with BMI at reproductive age?

I'm sure the correlation is <1. But as long as it's not an inverse correlation, it's fine. That is just measurement error which will bias down to 0 the estimate and lead to underestimate of selection.

> Wouldn't a far simpler approach be to measure allelic frequency at regions near GWAS QTLs in multiple generations?

How do you aggregate those QTLs? You can't examine them individually, that would be horrifically underpowered. If you wind up summing them, don't you get a polygenic score back and do what OP did?

"Aware of the conventional wisdom that robotic cars are about to cause an epochal “disruption,” automakers are eager to demonstrate that they are fully engaged. A result has been a drumbeat of announcements auguring the imminent arrival of robotic cars, almost as though they were the next generation of iPhones. The breathless statements are especially beguiling for members of the public without the engineering background required to understand the challenges that remain. In other words, most people."

I'm glad we have a "former technology reporter" to tell us this.

Intelligence is as much a behavior as education is. You observe it by what people do and how they perform. There is no physical or neurological correlate of intelligence like height or brain size or white matter integrity which measures intelligence as well as observing performance does.

As for how education can be genetically mediated, there's many ways. Through intelligence (high genetic correlation/overlap), but also through personality traits, ADHD-proneness, and other mental and physical characteristics which are undoubtedly under genetic control.

Payday loan-style businesses would let people monetize their BI. And that wouldn't work well with rent, which is usually paid in lump sums.

Salary negotiation is outside their comfort zone; yet it doesn't seem to help.

> "haven't learned wage-slave mentality yet"

> In the ensuing outrage, a PowerPoint presentation written by St. John surfaced which included a slide in which he referred to engineers with Asperger syndrome as being "the holy grail" of hires. "They work like machines," he wrote, "don’t engage in politics, don’t develop attitudes and never change jobs."

Someone needs to send all these people patio11's guides to salary negotiation, and maybe some drug to make them more aggressive and disagreeable. (Modafinil?)

I think you've badly misunderstood the paper and its results and are taking some sort of Occupy Wall Street mindset... The 'gradients' the paper is talking about are not exotic gradients which apply only to the general population vs the 1% of the 1% who get into an accident in their Lamborghini and call their dad in the Bahamas who deploys a crack team of white-shoe lawyers to ensure he never appears in court; it's talking about the health gradients you see when you compare the first decile of income nationally to the second decile, the second decile to the third, the fourth decile to the fifth, and so on. (AFAIK, the Swedish administrative data doesn't even give access to the 1% as they topcode or withhold access to their data.)

You see health differences no matter who you define as 'richer' or 'poorer', throughout the general population, in ordinary people. Yes, in the normal people you pass on the street, who have no 'financial advisors' other than their uncle who has some hot stock tips (although I suppose he would count as 'inherited'), who have no 'people investing their money' unless they are unusually prudent and have some Vanguard savings, who are not 'able to afford universities and good health', and so on. The person making $5k a year is less healthy than the person making $20k a year is less healthy than the person making $50k a year, and so on. Where are the monocles and secret cultural rituals there? None of these people 'grew up rich', so you should still see benefits when the $20k person wins a few thousand bucks in the lottery, if the causal effect here is through the money. But you don't.

You could try finetuning training; take the Pascal imageset, do image augmentation (ImageMagick has routines for darkening and 'midnight'-coloring images) to mimic nightime appear; retrain.

> It is however a strawman since no one is claiming that the money in themselves are the issue.

I am, uh, pretty sure that people do claim all the time that money is a pretty big issue and this is why we need more income equality and welfare and jobs.

How necessary is the deep model there? It seems like a simple motion detector would work just as well since he doesn't mention using the lawn himself.

Nifty. You could probably turn this into a useful planning tool for RV camper types if you turned it into a constraint-solver or integer programming problem by using RV or camping locations and adding costs for relocation, to get a cost-effective set of trips up the coasts and back down over the year.

I feel a little embarrassed how long I spent clicking on the temperature curve before finally noticing the little dragbar underneath which is how you change the target temperature on that. The lack of geographical or movement constraints make the results less interesting than OP, though.

"And while prices for mobile VR equipment have come down, it still costs about $850 for each Samsung Gear VR headset plus the Galaxy smartphone that slides into it — costly enough that the firm doesn't have a rig for each client."

I thought Samsung Gear VR cost like $100 and the smartphones were like $400, tops?

"These types of direct property funds — where the fund itself owns the building or property outright — represent a small piece of the mutual fund world.

Yet they have accounted for a growing share of investment in commercial real estate in Britain in recent years. According to a recent Bank of England report, these funds have about $46 billion in assets under management, representing 7 percent of investment in the British market." http://www.nytimes.com/2016/07/07/business/dealbook/3-more-p... the linked article.

So it seems this is maybe 3 percent of the overall British mutual fund market, and a fairly exotic part.

What do you expect from Taleb?

It's probably up there with the Korean DMZ, Chernobyl, and Bikini Atoll as unintentional nature preserves.

The glyphs look amusingly like circuits.

For 'redirected walking', you need a lot of room because you can only bend a little. The Void has done it and researchers have, but they usually have warehouse-like spaces. It won't work in a normal 3m^2 sort of residential room, which is why you need gimmicks like teleporting or omni-treadmills.

If you want to distinguish a particular method, but you can definitely tell that overall, the methods are collectively outperforming chance and so in this dataset, it is possible to infer the direction of causation.

Probably the best way would be making it self-documenting: installing some sort of plaque or stand describing it and why it is scientifically interesting. Then any work crews sent out to destroy it can see the plaque and exercise some discretion in sending it up channels to ask.

No, because a classification accuracy is not a p-value. By construction, a random guesser would achieve 50% accuracy in guessing whether A~>B or A<~B for each pair of cause-and-effects in their dataset. So getting >50% accuracy is the goal here.

Some psychedelics would probably make the experience far more effective as well.

One theory is Durkheim's suicide hypothesis: South Korea's industrial development has ripped apart the traditional society (already badly damaged by the country's partition and the Korean War), and social norms and society have not yet consolidated on new adaptive ways https://www.google.com/?gws_rd=ssl#q=durkheim+suicide+south+...

If so, we can hope that SK will gradually improve, especially if they can figure out how to corral the out-of-control signaling arms-race which is their educational system. (Although this also predicts bad news for China in the coming decades.)

> The best they ever got from cyrotrons was a special-purpose device, not a whole computer. But they reportedly did get a gigahertz clock rate, decades before anybody else.

What did they do with it?

You should read https://intelligence.org/2013/12/21/josef-urban-on-machine-l... and the citations! After that, you almost wonder why no one had applied NNs before.