Not really.

I'd say there's a good argument that all of the information I give Google actually exceeds what a personal assistant would know about me. The real difference (thus far) lies in the assistant's ability to understand human context which Google's systems lack. But that's merely a problem to be solved.

Note, BTW, that I'm not saying everyone should want what I want, or be comfortable giving any search engine enough information to be such an ideal assistant. That's a personal decision. I'm comfortable with it... but I'm not yet getting the search results I want.

I think systems built by man that knows a sufficient amount about me, my interests and my needs can. We're not there yet, certainly, but the question was what I want... and that's it.

Put it this way: Suppose you had a really bright personal assistant who knew pretty much everything about you and could see what you are doing at any given time, and suppose this assistant also had the ability to instantly find any data on the web. I want a search engine that can give me the answers that assistant could.

I want a search engine that searches for what I want, not what I type, and not even what I think I want.

Not really ISPs, at least as we traditionally think of them. Mobile network operators.

The MNO in question isn't the middleman, it's the service provider. It provides service to the balloons, which relay it to regions that are too remote to service now.

No, most of these regions aren't served because it's uneconomical. It's not that no one is willing to invest, it's that it's not an "investment" if you know up front that the ROI will be negative. Putting up a bunch of cell towers to serve remote African farmers, for example, doesn't pan out economically because there's no way the farmers can afford to pay high enough fees to cover the costs of all the infrastructure. Project Loon aims to fix this by radically lowering the cost of serving those regions, to a point where it is economical, so the fees the people in the region can afford to pay are sufficient to make serving them profitable.

As for why Google is partnering with MNOs rather than deploying their own connectivity? I don't know but I'd guess a couple of reasons. First, I expect it will be feasible to scale faster by partnering with entities who already have a lot of the infrastructure in place, particularly when you consider all of the legal and regulatory hurdles (which in many areas means knowing who to bribe, and how -- Google, like most American companies, would not be very good at that). Second, by working through local companies Google will avoid getting into power struggles with the local governments. Google is helping their local businesses to grow, not replacing them.

(Disclaimer: I work for Google, but I don't know anything more about this than what I see/read in the public press.)

Why wouldn't a randomized subsample from 10M people get funded? The required sample size doesn't grow as the population does.

Affects child development. The pattern looks like autism, but nobody's drawn that conclusion; what they have concluded is that electronic devices are more interesting to children than the real world, and cause them to develop emotionally stunted, withdrawn, and more interested in things than people. It's notable you can identify an autistic infant by watching if it's interested in human faces or in objects.

So, yeah. Interactive electronic devices, TVs with robust entertainment content, and so forth draw the attention of children and disrupt their social development. It's believed a similar, but weaker, effect occurs on adults. This is generally framed as "electronic screens are bad", and I don't feel like typing out term papers about what's actually being said because I like to take science for what it is: a pile of important data that must be analyzed for subtle patterns to derive better conclusions on one side, and a simple and complete conclusion useful to engineers but useless to scientists on the other.

You can debate the science if you want, but it's out there, and people have used it to engineer systems of education and general guidelines for the upbringing of children. Such engineered guidelines haven't been scrutinized as scientific principles, but neither has a Boeng 747.

It's more like having the scientific understanding of how lithium ion polymers behave with regard to electron potential creation, and how electrolytic solutions work, and then selecting an electrolytic solution and a lithium ion polymer and putting them together to build a battery. At the end of the day, you've done some work, taken some measurements, made some tweaks, gotten consistent results, patented your Li-Polymer cell, and started manufacturing and selling it in products; it works; but you haven't gotten any science down saying it works the way you believe it works. All you can do is spout about the science that you had for precursor, the things you slapped together, and the results you got.

This might surprise you, but a lot of things are held on the thin branch of slapping a bunch of well-understood science together. Many drug treatments, for example, are held together by science that says certain biochemical effects are useful in a certain way, and science that shows the drug has those effects; we often come back with the conclusion that an entire class of drugs with a long history and variants both ancient and modern are actually totally ineffective because of this.

To put this into context: we have hard science showing that exposing kids to electronic screens is bad. Science backs up that exposing children to electronic screens is bad. We don't have science examining, say, Waldorf Education, which avoids exposing children to electronic screens until they're like 7-8 years old, against new-fangled high-tech Apple Elementary School with iPads all over the place. We've looked at scientific evidence showing that exposure to electronic screens is harmful to child development and determined that a school of education should avoid doing exactly that, in the same way that we've looked at science suggesting antimony should not be in a child's diet in significant quantities and concluded that diets without antimony are better for kids than diets with antimony.

I may be responding to a troll here, but, no, the GP is correct. P-values are about probability. They're often used in the context of evaluating a correlation, but they needn't be. Specifically, p-values specify the probability that the observed statistical result (which may be a correlation) could be a result of random selection of a particularly bad sample. Good sampling techniques can't eliminate the possibility that your random sample just happens to be non-representative, and the p value measures the probability that this has happened. A p value of 0.05 means that there's a 5% chance that your results are bogus in this particular way.

The problem with p values is that they only describe one way that the experiment could have gone wrong, but people interpret them to mean overall confidence -- or, even worse -- significance of the result, when they really only describe confidence that the sample wasn't biased due to bad luck in random sampling. It could have been biased because the sampling methodology wasn't good. I could have been meaningless because it finds an effect which is real, but negligibly small. It be meaningless because the experiment was just badly constructed and didn't measure what it thought it was measuring. There could be lots and lots of other problems.

There's nothing inherently wrong with p values, but people tend to believe they mean far more than they do.