It's a pretty bland memo and a thinly veiled advertisement for AWS.

* One person sees 1 of 4 images and another far away guesses the image. Supposedly it's accurate ~33% of the time instead of 25%. Fun but it can't be replicated by anyone else. Selection bias, poor design, and bad meta analysis explain the difference.

* ~54% of the, a person can detect if they're being stared at, whereas we'd expect 50%. Again, cannot be replicated in better designed studies and bad study design and selection bias explain the other results.

* By a small but supposedly statistically improbably amount, people can get a dice to roll by "wishing" for it. Again, cannot be replicated and can be explained with p-hacking anyhow.

The blog fails to answer the most basic question: do right-side sleepers with a metal bedframe aligned with a radio tower have a higher incidence of left-side cancers that can explain the general population discrepancy?

Most health focused runners should be walking at an incline or running downhill except for 1-2 high intensity interval days. There are huge benefits to low intensity activity and higher doses are almost always better. The sort of intense, grueling runs that most people do are likely counterproductive. It's like running a race every day as a workout. It's just not sustainable and unhealthy at high doses.

(Of course, if the goal is to be a runner and not simply be healthy, you'll need to push your body to a point where running is like walking but it takes a long time to do correctly.)

Do you mean hyperlinks?

They're not hiding anything: https://www.consumerreports.org/cro/about-us/our-partners/co...

Of course, it's not as black and white here, but sample size and effect size should be considered in relation to each other. Previous research and theoretical expectations should also play a leading role.

I think there are salary differences across careers for a variety of complex market reasons. If I had understood the degree to which money would dictate the security of my family, I'd have spent my years as a lowly paid graduate student and post-doc becoming a surgeon or working in finance instead of becoming a mathematician. My bay area salary is much better than my tenure track salary but still a fraction of what I could actually be making. Nurses, too, are free to retrain.

I will concede that this issue is not personally important to me.

Most nurses are paid hourly, so the "long hours" is a moot point.

My nurse friends all make around 100,000 per year after overtime, which they're eager to get. The average full time salary without overtime is ~80,000.

For a 2 year degree, this is very decent money in most states and I think we'd struggle to name a career with such low education requirements and high salary.

I really appreciate the work of medical professionals and don't want to belittle their work. But I think nursing does standout as a counterexample to the point you're making.

Neither of your links mention nursing.

I think you're either paraphrasing deceptively, or you are being intellectually lazy. Perhaps it is better to not assume malice...

The rest of the quote is:

"In total, 144 participants received an mRNA vaccination between the baseline and the follow-up scan. We performed separate analyses for participants with vaccination as well as for participants without vaccination. The results were not different from the findings of the full cohort as presented. The cardiac effects of vaccination require further research."

Makefiles on the other hand, are not unreasonably effective in this sense. Makefiles are, in fact, _reasonably_ effective... like a coffee maker that brews coffee well.

As a follow-up to those courses, there are also some courses about the middle ages by Philip Daileader that pick-up the story at the decline of the Western empire.

(Also, I'm deriving great value from the Wondrium app).

I don't think it takes very much imagination to understand why the loss of diversity in an ecosystem might have negative implications for that ecosystem.

For whatever it's worth to you, Science magazine is a companion to the extremely prestigious Science Journal and it often tries to summarize the research in the journal. The tiniest amount of searching shows that the biologist whose work is being summarized a is one of the leading experts in this area.

We've already solved the tough algorithmic challenges relevant to most industries and those software engineers spend their time writing specifications that just happen to be programs. Their job is to have hours of discussion and think through edge cases to provide an exact description of the business requirements. Good engineering means thinking through edge cases and gray areas while the PMs and designers capture broad requirements from users and focus on high level details. You're not going to replace engineers in this capacity without human level, general AI.

Further, you cannot capture the needs of a tech-enabled business with natural language descriptions while remaining unambiguous and changeable. If you had an AI to write your programs, you'd still have engineers writing specifications into the AI (and even more importantly, deciding on those specifications down to the most intricate if details).

We will in fact see an explosion, or at least mild expansion, of software engineering into areas that are algorithmically challenging. AI will manage to solve the tough algorithmic parts and engineers will drive the AI through increasingly specialized languages. In this world, AIs will act like compilers.

But it's just super futuristic and naive to think that a PM will tell GPT-3 what to make like a Google Home and have it pop out the other side.

Other supplements have shown benefits in these sorts of studies without standing up to more exacting experiment design.

So potentially interesting results but nothing worth getting invested in.

Clearly, drugs aren't doing anything for this author's ability to discern intelligent thought from vapid, intellectual posturing.

The thinking goes that, if only we could become pure and stop partaking in the evils of consumer capitalism, we might appease a hidden power and be saved from a myriad of bogeyman such as climate change.

This mindset fails to reasonably consider the certainty and enormity of the threat. Organized civilization is likely to end. Billions will die and we might very well become extinct.

The problem must be attacked with the full force of human intellect. It's so damn obvious that "wait for everyone to become super duper conscientious" is a fool's plan.