This is an amazing published paper on the feasibility of a space elevator.
http://keithcu.com/wiki/images...

The big take-aways:
* Decreasing the x-sectional surface area by an exponential function as altitude decreases theoretically allows any material to be used, though the volumes required would be prohibitive for any but the strongest materials, and too steep an exponential function makes the geometries also not practically possible
* A yield strength of 46.5 GPa only requires a max-to-min cross-sectional area ratio ("taper ratio") of 10. A lower yield strength would require a larger taper ratio.

The material in this article has a yield strength of 9.6 GPa which is about 7.2% of the maximum strength of graphene and 20% of the way to 46.5 GPa, and I believe stronger than any bulk material previously manufactured. Reaching 46.5 GPa only requires 36% of the 130 GPa maximum strength of graphene, leaving lots of room for falling short on the actual average yield strength of manufactured product, and also including the required engineering safety factor in the design. And if we still fall short, we have some room to raise the taper ratio.

This TEDx video describes spinning carbon nanotubes to give them more than enough strength, which is basically what these people in this article have done! It also addressed the other concerns of the Gizmodo article. Since this manufacturing is firmly in the realm of engineering, now, I would expect to see a regular rate of increasing strengths in produced materials, as the processes improve. http://spaceref.com/space-elev...

TD;DR - Space elevator is entirely possible.

Actually, no. GPa is a unit of *pressure* -- i.e. the force that can be carried in tension per unit of area. It applies to a material in general, not to a shape or particular amount of a material.

The material they created is not a single nanotube (or 15), it's uncountably many of them spun/squashed into a sheet, with a 9.6 GPa maximum tensile stress (i.e. pressure).

100 000 to 2 000 000 speakers would disagree with you. Some/many schools use it (e.g. in China, Australia, the UK) as their 1st second language instruction because it's by far the easiest language to learn, which accelerates future language learning. If more schools/regions can be convinced of its scientifically-measured benefits to language learning, it could take off as purely a learning language. Google Translate even has it as one of its languages (and no, Klingon is not in that list).

True, it's not currently the international auxiliary language of choice, but it's definitely *an* international auxiliary language of choice:
- 32nd on the list of Wikipedias by article count (http://en.wikipedia.org/wiki/List_of_Wikipedias)
- stay for free in 90 countries with 1000+ hosts if you speak Esperanto (http://pasportaservo.org/)
- yearly world congress with thousands of attendees, and yearly youth world congress with hundreds of attendees (http://en.wikipedia.org/wiki/World_Congress_of_Esperanto)

I'm still hopeful...

And that start is growing with double-digit percentages. AND, the majority of new power generation projects in the US (and worldwide) is already renewables (solar/wind/etc), so the trend is only going to accelerate.

Naively projecting that 5% solar power forward at 14% growth per year leads to 50% solar power in 18 years and 100% solar power in 23 years. Of course, that's not an accurate model of what will happen -- a better model would be an s-curve, with the maximum currently unknown -- but it does give a good idea of the rough time scale involved. Around 2 decades until solar power is saturated? That's not so long.

It took a while to get going, with the required government support for the basic research costs, but now this is a self-sustaining free-market endeavour which means it's a trend that now cannot be stopped, thankfully.

The truism about Artificial Intelligence is that once a cutting edge problem in AI gets solved, the masses just redefine it as "computer science algorithm". Image recognition was once the leading edge of AI. It's still AI, just not leading edge anymore (unless you're doing something completely novel, like doing it on a quantum computer). Intelligence *is* pattern recognition, of which image recognition is one type.

Ho.

Ly.

Shit.

15 or 20 years ago, I was saying that because quantum computers perform multiple calculations on similar inputs simultaneously, they'll be perfect for the sorts of pattern recognition tasks needed for (artificial) intelligence. And now these smart people have figured out how to do it for the first time, albeit with a miniscule 4 qubit quantum computer.

But since quantum computing capabilities scale according to 2^n, where n is the number of qubits, a 24 qubit computer (i.e. 6 times the size of what they just built, requiring a molecule with 24 atoms) would be 2^20 = 1 million times as powerful as this 4 qubit computer just demonstrated. A 64 qubit computer would be 10^18 = 1 million million million times as powerful as this 4 qubit computer. Good-bye conventional computer encryption. And hello general-purpose pattern-recognition (i.e. the basis for strong artificial intelligence).

My first thought was that a vat of "carbon-13-iodotrifluroethylene" isn't exactly a general purpose computing device -- except that because their control inputs are a stream of radio waves pulses controlled by a conventional computer, it actually is a general purpose computer. And though I'm no quantum physicist / quantum computer scientist, it seems like it would scale reasonably easily: you just need to find larger organic molecules with similarly discrete nuclear magnetic resonance 'channels' (i.e. independently manipulable/separable by frequency).

I am beginning to sense the coming Kurzweil Singularity...

True, but almost nothing at 300K, and almost none of that in the *near* infra-red.

Examples of human-competitive results using genetic programming (i.e. the algorithm we refer to as Evolution):
http://www.genetic-programming...

And their strict Two Fat Pipe policy means only skinny pipes left for content delivery.

I've never seen a post with 50% of its words spelled incorrectly. Unless it's in French? -- in which case, I guess your keyboard doesn't support accents.

--

Not a grammar nazi. Just couldn't resist on this one.

Sure, it may work exactly as hyped. But that doesn't matter.

Why would I want my hosting coupled to the framework I'm using, and to a particular database as well? If their hosting sucks, or if they raise their rates, I'm stuck.

No thanks!

Upon further reading (http://en.wikipedia.org/wiki/Centrality), methods that use an attenuation factor like I described are called Eigenvector Centrality, which Katz and PageRank are specific implementations of.

I guess I have! :-)

This article and open rankings work is great, but...

My intuition:

Incoming links with degree one should be allocated 1 point. *yep*
Incoming links with degree two should be allocated half of 1 point = 0.5 points. *yep*
Incoming links with degree three should be allocated half of 0.5 points = 0.25 points. *NOPE* It actually gets allocated 0.33 points.

This means degree ten links still get 0.1 point? 10 hops away and they're still showing up significantly? That measure is broken. 10 hops away should score vanishingly small... 0.5^(10-1) = 0.001 points is much more reasonable.

The measure shouldn't be 1/n (harmonic centrality), it should be 0.5^(n-1). I would love to see that set of rankings.

That's a good thing to consider, but in general the natural gas distribution system continues to work just fine during a power outage. There's enough stored pressure in the system to last awhile (not sure exactly how long). And the compressors in the system are either powered by natural gas themselves, or they, too, have natural gas generators as electricity backups.