RTA - the improvement is there specifically for real time analytic workloads. In these kind of workflows the optimal algorithm is O(n) in general case and indexes are useless (query optimizing engine will always choose scans as you need to visit a lot of data). You might know a thing or two about algorithms, but you should brush up on problem analysis 101.

Other mistakes in logic: Index seek and column sort are not different algorithms for the same task so comparing them brings little insight (without considering some other details of the query optimizer). This leads you to nonsensical claim that O(log N) will eventually beat or be equal to O(N log N). It is not eventually, the first will be always faster or equal.

It is not a matter of psyche, but realizing the difference between visual and conceptual information processing in humans.

It's not unlike a GPU vs CPU: while visual is much faster it brings a certain bias.

(For bias look for "optical illusions" and focus more on static ones).

The legislation is intended for Telcos and ISPs according to the excerpt. AFAIK they already have legislation on log retention.

So you have couple of easily detectable cases:
* Missing logs or other log anomalies and no reported breach - bad and easy to check
* Logs with breach activity and no reported breach - bad and possible to check

So the worst case is actually if someone manages to reconstruct the logs, however I would say that would not be so easy these days with redundant and complex systems that log at various levels.

As for reporting the breach - as with anything that you need to report yourself it would require audits of some sorts.

Working virtually is not what makes someone unavailable - I work in a nice mix that allows for comparison. We have four people team: two people at one site, one person off-site in another office (at +6 hours) and another person off-site working from home in the same time zone.

Virtual meetings i.e. voice and sharing a desktop tend to be more more productive than cramping around a monitor or booking a meeting room in most cases. If you manage to add video you can recover a part of non verbal communication channel and sharing control and switching desktops from one person to another allows for very productive work for up to four people to the extent that we sometimes prefer it even when all participants are at the same site. On the other hand the time zone difference of one team member indeed leads to some issues having to wait.

Therefore it is not virtual work that makes it less effective, but it is the working times flexibility or time zone differences that needs to be offset with attention to scheduling that you are highlighting as a cause of productivity loss - and that is a matter of working hours policies not real life vs virtual office setup.

Ah, really? So, if we 'filter' only the 'obedient' units in each genereation how do you define this "obedience"? (Of course, in a way that is essentially(!) different compared to Asimov's second law, as that is your point.)

Saying that this is not a good resource depends on what you compare it to. If you compare to an experienced and brilliant teacher giving lectures to a small group of students then Khan does not really have a chance. If you compare also to best of books he is a bit shaky. But I've read that lots of people find it a good resource and I am not surprised - it is a video, you can do it at your own pace and it has a social network component. If used as additional learning tool I can't see how you could call it anything but a good resource.

Allow me to be more specific, from SO/ISO 31-0

There, corrected that for you according to SI

Oh, now you are piling it up.

True, but... the big thing in the Khan's effort is material nicely divided into chunks which can be skipped or studied in detail. Another big plus is a social component - take a look at stackoverflow and cousins - the social dimension makes these things work. The (not so clear) deficiency of Khan's academy is, while the model is nice, sticking to single source is not enough and is biased (in this case respectably well biased in good way, but inherently imperfect). Still, I see this as a push in the right direction, the trick is not to think of it as a silver bullet. This approach is bloody useful - reminding yourself of certain topic or learning new one can be achieved in an ecosystem of peers, with what seems to be good quality material. Yes, it is, and it will be even in next evolutionary cycles, an education which quality can not be compared to any real live teacher worth his own education, but if you watched the ted video you'd know that the realistic use case for this 'academy' is to be supplemental tool, and as such it has enormous potential. In and out of the classroom. Just don't abuse it or expect things from it that it can not deliver.

If(!) ARM is more energy efficient then it delivers more processing power per unit of power. Principle works the same at 250mW and at 600W. It would also generate less heat. Ability to turn the cores on and off is additional benefit that would further improve efficiency.

Wiki article http://en.wikipedia.org/wiki/High-voltage_direct_current#Advantages_of_HVDC_over_AC_transmission is pretty informative, both for advantages and disadvantages of DC compared to AC.

True. They are not the same, but there is overlap. Topological rarely goes without image memory. Images are encoded, yes, and photographic memory is really rare (http://www.youtube.com/watch?v=jVqRT_kCOLI) and probably there's a reason.

Memory is association. What you call tricks are just using conscious efforts to reinforce associations.
Furthermore, memory can be improved even without conscious meddling in encoding system; one of the standard exercises during drawing classes is to observe different parts of face - for example you spend a week observing people's noses. All the time. Everywhere you go. Result: your perception and memory increases - it is like the compression algorithms that help you encode and associate a given detail (nose, ears, eyes, etc..) improves.
Also, the image is not a single, full detail clue in terms of experience on the level of neuron excitation - your eyes always provide the stream, even looking at the still image - full resolution of your eye can only be achieved on a very limited FOV, that's why you move your eyes while you read this text or while you look at the painting, etc...
It is the encoding system (and hardware) that your brain uses that distinguish the image retention capabilities - be it naturally or consciously trained.

Again true, however, I repeat, spatial (in a sense of topological+image) memory is particularly good in humans. Also, most faces (image) you remember from just one meeting (names are the problem; reinforcing association is useful in remembering the name; but this remembering faces is understandable - we have specialised hardware for that, see http://www.ted.com/talks/vilayanur_ramachandran_on_your_mind.html on what happens when it breaks). Most locations you remember extremely well with quite a lot of detail. Stephen might remember more, but is that optimal? So you do abstract the images, unless there are particularly important to what you do or what you like; at the same time you do remember distinguishing factors: for example you might still remember the exact way to your childhood school, a neighbourhood where you lived ten years ago, student dorm, streets in various cities that you walked and that is not pure abstract topological graph; memory contains enough image detail for recognition (compression algorithms are normally optimised for recognition, not necessarily reconstruction; http://www.youtube.com/watch?v=Ipomu0MLFaI).

Spatial/visual memory is in average person much more powerful then conceptual memory.
All memory is association, but if you compare how efficient you are in remembering, let's say a rather complicated path through a bigger park compared to remembering let's say remembering 8 3-digit numbers, spatial memory easily wins by order of magnitude in an average person (people who have great visual memory or great audio memory might complicate the analysis, so treat those as special cases).
Spatial memory is so good that we expect very much of it, that's why labyrinths are interesting and also that is why when it you get lost or can not find a certain place you forget how good your spatial memory is: most of the time you know exactly where you are, you know how to get to most places you know and most importantly you retain this information without effort for years and years (think about cities you used to live in, airports, houses, etc...).
Using these existing memories is referred to as 'memory palace' (palaces are usually also well structured with many separate spaces) - now, the point is that since all memory is association, you can use existing memory structures (rooms, halls, stairways, etc) to store new information by using your imagination and associating new info with existing one.
Besides the spatial, we are also quite good in remembering how something happened - films, theatre, etc comes to mind. So you take something that we are not so good at and turn it into something we are good at: you use, for example well known room to put the objects that you would like to remember in places that you have a good memory with. Objects can be a coding system for cards, numbers or other less visual information that you would like to store.

'Memory palace' = 'method of loci' is a method, i.e. something that an average person can learn and train her or himself to use efficiently.
It is not particularly new, it is attributed to 5th/6th century (BC) Greek poet. http://en.wikipedia.org/wiki/Method_of_loci

It is actually quite simple and can be taught in an hour or less. Training takes more time.

It is based on a simple fact that our brain is more specialized for remembering spatial facts and relations (has probably a bit to do with being able to quickly remember paths: either to successfully chase that squirrel or find the closest path to the most secure location while running away from a malnourished tiger of some sorts)

These methods map this mental power to non spatial concepts through visual association. Not completely unlike using GPU to do some non graphic tasks efficiently. The trick, in both cases, is to be able to recognize which tasks are best suited for it.