With this in mind, it's concerning with this big ramp-up in number of CS-trained individuals. I feel we have been at the bottom of the barrel for some years already. Given that it has been well-known to everyone for many years that IT is one of the easiest areas to find employment in and that the salary is comparatively good, and the constant media focus on smartphones, apps and whatnot, it seems reasonable to assume that most people with just a faint interest and ability in IT would have pursued that path already. With this ramp-up, it seems there's a high risk that the market will be flooded by sub-par candidates and that it will be much more than what the market is already absorbing. The result will be massive unemployment among those newly trained CS-people, who were never meant to study CS to begin with.
So in short, women don't want to contribute to Wikipedia because the personal gains to them are small. Men do it for the fun of it, for the creative process.
He came up with the idea of using lossy compression techniques to compress the original file, then calculating the difference between the approximate reconstruction and the original file and compressing that data; by combining the two pieces, you have a lossless compressor.
This type of approach can work, Misra said, but, in most cases, would not be more efficient than a standard lossless compression algorithm, because coding the error usually isn’t any easier than coding the data.
Well, this is almost how MPEG movie compresion works - and it really does work! MPEG works by partly describing the next picture from the previous using motion vectors. These vectors described how the next picture will look based on movements of small-ish macroblocks on the original picture. Now, if that was the only element of the algorithm movies would look kind of strange (like paper-doll characters being moved about)! So the secret to make it work is to send extra information allowing the client to calculate the final picture. This is done by subracted the predicted picture from the actual next frame. This difference-picture will (if the difference between the two frames was indeed mostly due to movement) be mostly black but it will contain some information due to noise, things that have become visible due to the movement, rotation etc. So MPEG also contains an algorithm that can very efficiently encode this "difference picture". Basically an algorithm that is very efficient for encoding an almost black picture.
So there you have it - MPEG works by applying a very crude, lossy compression (only describing the picture difference in terms of motion vectors) and in addition transmitting the information required to correct the errors and allow reconstruction of the actual frame.
The only part where the comparison breaks down is that MPEG is not lossless. Even when transmitting the difference picture, further compression and reduction takes place (depending on bandwidth) so that the actual frame can not be reconstructed 100%. Still MPEG is evidence that the basic principle of using a crude lossy compressor combined with sending a compensation, works.
So he definitely lied.
It has also been associated with other cancers. In contrast to this, the alternative painkiller aspirin has been associated with a decreased risk of many different types of cancer, notably colon cancer but also blood cancers as well as many other cancers (too lazy to find all the references). In animals, it can protect animals exposed to other carcinogens from cancer.
Ibuprofen seems to be mixed, in some studies it is associated with increased cancer in other with decreased risk.
By the way, note that aspirin is not a magic bullet against cancer; it is also a blood thinner. People who take it chronically are prone to getting bruises from the slightest hits. This also means it increases the risk of potentially fatal bleeds, as well as certain types of strokes (intercranial haemorrage). On the other hand it decreases the risk of blood clots. The net effect is difficult to assess.
The problem is that it used to be that PhD students were the best students of that year, at least in the natural sciences. I remmeber that when I studied only 1 PhD student was accepted every other year, and he/she would always be one who was very clearly (after a 2 min. conversation) smarter than the rest of the students. Of course that person would also have top grades -- and that was when top grades were more scarce that is the case today.
Today it's not like that. Everything from the top students and down to the "joe average" (i.e. someone with half a brain) in the graduate studies usually gets offered a PhD. In fact, many programs have more PhD's than they can fulfill from the pool of candidate students. There's no prestige about getting a PhD anymore. And since the financial crisis came, it's in some way the opposite, in that the PhD is an obvious path to take for someone who couldn't get a better paying job in the private sector.
This state of affairs is extremely expensive to society. It's expensive to provide an extra 3-year education and salary to people who are just average intelligence. Also, the science that comes out of this is mostly bogus. I.e. not really innovative, just buying a lot of fancy equipment and applying what others already found out. Then publishing it with a twist. There has already been some articles out on how little the science produced in academia is contributing to the economy, and there has also been a few news stories about how the "too many PhD's" has lowered the quality. But it still seems most politicians are in the uncritical "more education" mode... so I suspect it will be a few years until anything substantial happens in this area.
Of course my intuition could be wrong. Maybe it's just that sentience appears to have a different quality but that is just because it is so infinitely complex that our intuition has no grasp of such complexity. And that if it did, we would be able to see how sentience can be developed just from the standard properties of physical matter. I can't exclude that this is the case, I don't see how anyone could.
By the way, I'm curious about you saying that such computers would have to be made from something else than silicon and would have to be ultra-parallel, plastic etc.
I don't see why, if you have already accepted sentience from following from mechanical processes. As long as the materials obey usual physics, the properties of this material could be simulated easily on a computer. You could simulate ultra flexible/plastic neurons on any computer. Likewise, a single-thread can simulate any number of parallel threads with a linear slow-down. So to me it seems that if you go along the mechanistic route, you have to accept that sentience could occur even on the simplest of CPU's (or any kind of Turing machine in fact) just given the right program. Of course the program might execute at a slow speed, but it should be totally equivalent. And this is why I find the premise of "sentience is just complex computation" unappealing.
Another problem is that I find the whole concept of computation somewhat subjective. While computation is well-defined at the "input/output" level, the actual computation process is not. It's usually just abstracted away. And sentience must be a property of the computation process itself and not a property of the actual I/O (after all, I still feel sentient when no one is looking).
If I look at a Turing-machine made of organ-pipes, it's essentially just my interpretation that these organ pipes are operating as a Turing machine executing on some piece of information. You have to look at the system at just the right level and type of abstraction to see it's a Turing machines. To someone not "in" on it, it would just seem like a weird spectacle. The individual physical components are operating exactly as they would if they were not part of a Turing machine. That a computation is taking place is clearly not a physical matter. It just happens that humans have labeled this type of interaction between organ pipes "computation". So couldn't there be some subjective view of the organ pipes implementing a different type of machine running a different program that did not involve sentience? Likewise, couldn't I interpret leafs flying across the street of some sort of calculation? Given the huge number of physical processes going on in a glass of water, and the almost infinitely ways of intepretating what those processes are doing, it seems likely you could find some way of interpreting one process as a sentient process. That's why I think computation is in some way subjective.
So if computation is so subjective, what is it that breathes sentience into the computations making up our brain and thoughts?
By the way I have been debating this with people for 10-15 years. Some people understand immediately what I mean. Others seem to never see the problem. Is that because the latter are more clever and can better see how sentience follows from physics? Or is it because they are not sentient themselves?
The anti-individual abilities agenda is routinely promoted by managers, project managers and other people engaged in the management layers (management consultants, business schools etc.). The motive is pretty clear: Many bosses don't like admitting that the success of their project comes down to individual abilities of a few core members on the project. After all, what is the value of management then, they ask? It's like the tail wagging the dog.
However, this is just denying reality. I can firmly say that on any project of major size I worked on, the was a few 5-10% of people on the project running the show. This in itself is not very surprising, what is surprising is the fact that these 5-10% were not centered at the top of the pyramid. Rather, it was evenly spread out over all 'layers' from 'highest to lowest'. These people (by virtue of their skills and dedication to the project, something that is often lacking with the project management itself!) automatically assume a role of authorities whether management likes it or not. It's simply the only way to get things done. Let's face it, on any project there's going to be a lot of 9-5'ers that don't really care. They are never the ones driving the car, nor should they. It's the 5-10% who has both the ability to and the interest in getting the job done that counts. Those that dream about the project at night and who feel their personal honour is at stake in making it succeed. Also, as Fred Brooks noted in 'a mythical man month', some (sub)projects are like surgery. You need one highly skilled person to be in charge and carry out the job, and the rest of the team members are really just accessories of that person. Their contribution can be important of course, but at the end of the day, all choices, responsibility resides with the 'surgeon' etc.
I think the lesson to be learned from these observations is that management needs to accept that this is the structure that projects will generally fall into, no matter what they do. The job of management is to get the best result out of it. On projects with poor management that creates obstacles for progress and makes lots of bad choices (this often happens on politically infested projects as well as on projects where management doesn't have a clue about the technical aspects), often the project finds a way to completely bypass management. Decisions by management may be outright ignored, or important decisions are never brought up to this level but are just made behind the scenes. This is a very dangerous situation since important decisions may not be properly reviewed and may not even be known by all stake-holders. While most decisions taken may have been correct, it takes just one bad decision to jeopardize the project, and problems related to this kind of "skunkworks decisions" tend to surface very late where they may cause huge problems, sometimes disasters.
The job of management is to embrace the individual abilities, and to listen carefully (but of course not uncritically) to arguments brought forward, no matter if it is from a project manager or a "lowly" techie. They need to make a decent effort to try to understand what they are talking about, even if the explanations are not always clear and even if it can sometimes be highly technical.