It means that if you want to have a conversation with a computer, or have true face recognition, or solve any hard-AI problem, we have to invent a new type of machine first.
No - it doesn't have to mean that at all. There may be other ways - or many other ways - to solve these problems that do not use the same mechanisms that human physiology does. Those ways may well be implemented perfectly easily with a Von Neuman architecture, even if it is outright impossible to do it the "human way." After all, you see with rods and cones; we didn't have to come up with rods and cones to implement machine vision, and not only did we succeed, we ended up with a wider range of sensors than animals have, as well as higher resolution sensors, using multiple technologies.
Starting with the idea that an animal is the "best design" because it seems to be the most advanced animal we know of is almost certainly a bankrupt strategy. The only way we can really know if an animal's abilities arise from the best design possible is if we understand the subject at hand to an enormous depth, and if one thing is certain in all this discussion about intelligence, it is that we do not understand the subject very well at all. So what we need to do is keep looking, and carefully strip these unfounded preconceptions from our collection of knowledge or at least treat them as tentative propositions at best.
For all we know, there may be as many ways to implement intelligence in a Von Neuman architecture as there are to start things on fire in the natural world - matches, lightning, magnifying glasses, friction, chemical reactions, nuclear reactions, etc. I'd not bet strongly against such a proposition at this juncture.
But we also know that intelligence is not material in nature,
No, you don't "know" any such thing. Barring the possibility of projects so black we've never even heard of them, no one seems to know what intelligence is. Least of all you or I. Claiming you know its nature at this point in the development of science is absurd.
Not exactly a rigorous definition. It doesn't give any idea of what you think intelligence is. You say mice are intelligent and rocks are not. What about ants? Ant colonies? Plants? Fungi? Bacteria? Disorganized large assorted collections of organic molecules?
First of all, it isn't a definition of intelligence at all. It's just a set of conditions that take into account intelligence or the lack of it, and natural systems as opposed to manufactured systems. I will say that even if I've picked a wrong example, these conditions still stand, you just need a right example to replace my error.
Having said that, though, I don't know what intelligence is. I am under the impression that I can sometimes identify its presence by manifestation of actions, however, at least within the realm of nature. So I sometimes know when it is. Plus there are organic hints; all my experience points to it being an emergent property of at least a moderate degree of complexity of neural systems. So if an animal has a decent collection of nerves - we're back to mice and higher animals - then the hardware may be there, and they are worth watching for displays of tool using, emotional outbursts, nurture, intellectually moderated defense and aggression, sharing, mutual support, empathy, self-sacrifice, and so on. For instance, when one fish continually pushes another to the surface because the other is paralyzed and cannot swim up to its food, that gets my attention. When a cat wants my attention and comes to meow at me because it is out of food, again, I pay attention. When a cat uses a mirror to locate and clean crud off its coat, I pay attention. When apes can learn to use signboards and computer systems to communicate complex concepts, I pay attention. Combinations of these things, especially in large numbers, make me fairly confident that what I am witnessing is a manifestation of intelligence. What is intelligence itself? No idea. What does it cause? Now that I have some ideas about.
Ants are borderline; ant colonies less so. Plants are not. Fungi are not. Bacteria are not. Organic molecules, in large summary collections, may be, depending on various factors; after all, that's one description of a brain, depending on just how disorganized you are implying. My middle son is pretty damned disorganized.:-) Once you get too general, you fall into the "can groups of atoms be intelligent?" trap; of course they can, that's what our brains are.
I don't disagree that it's presumptuous to call the present research being done AI
People use the term AI as a pointer to research seeking various aspects of the goal of AI, and I have no problem with that. That in no way should be confused with the mistaken idea than anyone has made any public announcements of having actually created anything even remotely resembling the target. Again, I except the vague possibility of black projects we may not hear about for decades.
Critics are one thing; critics serve the function of honing the truth and ferreting out errors. Particularly those who spend great amounts of time digging into something. For instance, a number of quite clever people here today criticized my positions on AI; some I had little trouble explaining my thoughts to, a couple required a good deal more of me. There is always a chance someone will accurately pull an "But you didn't think of this, Sparky!" and then I get to leap ahead with a new realization I might not have come to myself, and perhaps dump an erroneous presumption at the same time. But that kind of useful criticism will almost certainly come from a programmer, engineer or scientist, I would bet you my bottom dollar; not a philosopher or a rank and file citizen who believes there's a god for no particular reason they can articulate.
Large numbers of average people holding onto ridiculous ideas as if they were gospel (no pun intended, that simply shows how embedded this drivel is) are the problem. Religion would be the first thing I'd point at; there are endless philosophers who attempt to "reason" their way to a requirement for the existence of a being or beings for which there is no evidence. The country I live in — the USA — is unbelievably (again, no pun intended) packed with people who have adopted this outlook based on the idea that the philosophers, self-proclaimed deep thinkers, say that they have reasoned that this is so.
I agree that way back when, philosophers were doing what work was being done. Consequently, we got the occasional advance, and that was certainly better than not getting it at all. Even today pure thinkers do us a service now and then. But science today is not what philosophy was then, and they are in no way the same in terms of getting real results with real issues. Science moves forward at an incredible pace; to quote XKCD, "it works, bitches."
This is because science is not a philosophy of thought, despite wishful thinking to the contrary. Science is an iterative, down-to-earth method, a series of actions, taken with regard to the subject at hand. Mundane, easily understood and followed steps. The only philosophy is to say "I will not make up results, or hide them, to match preconceptions", which is an anti-philosophy if it is anything. I have always found it refreshing that the most successful tool we ever developed to deal with reality is sticking to reality in our outlooks, methods, and ideas. If we fall off the wagon with some wild idea, all we have to do is stick to the method and we'll be right back where we ought to be. Science is a curb on much of thought; and that is a wonderful thing, because most people are not well able to regulate themselves without a formal method to follow.
And of our 50,000 year or so history, only during the last hundred (or fifty, some might argue), did we have even moderately useful medical care, useful electronics, and general purpose computers. I wouldn't assume that very large, very fast steps might not be a perfectly reasonable consequence of the development of the very first real crack in the AI problem.
Then perhaps you can send your robot after that lobster you crave.:-)
And what kind of awareness does a Turing machine have?
It knows, and can examine, its complete internal state better than you do, for starters. As you add peripherals, it can obtain information on the world outside of its hardware. The sophistication of this awareness grows both in complexity and in abstraction as the algorithms that deal with the data become more complex themselves. There's absolutely no reason to presume there is anything magical about awareness. A thermometer is more aware of the temperature than you are most of the time, and better than you are at it all of the time. That's a result of design. You can expect the same from AI, should we manage to cobble some up.
The attribution of awareness or consciousness to any sort of physical machine, Turing or otherwise, is a giant leap of superstition that atheists, or rather naturalists, are largely forced to make.
We need make no leap whatsoever. Nature has produced human intelligence through a process of incremental improvements. Reproducing or modeling natural systems is something we've turned out to be very good at once we understand them; there is every reason to presume that this is just one more of the same types of challenges. The leap of superstition is entirely yours — it is that awareness and consciousness are not perfectly natural consequences of particular combinations of processes and structures. In order to reach that conclusion, you have to imagine a being whose existence cannot be substantiated by the facts at hand.
But it makes for some ugly thinking.
And what might that be? I see only beauty, intriguing challenges, mysteries to be plumbed, problems to be solved. What do you see that is so ugly, eh? And why? What are you afraid of?
I'm not saying that the mind is not subject to physical law, or is not based on math. All I'm saying is that the mind is not a Turing machine ( though it probably would have to have a Turing machine in it somewhere ). It's a different *kind* of machine, not a super-powerful Turing machine.
The question is, how do you know this to be the case? On the one hand, science generally takes the position that we really don't know how the mind operates, and on the other some people — you, in this case — claim that they are able to classify how it works, which seems... unsubstantiated.
And on the other other hand (I'm playing Octopus here), turing machines aren't chemical soups, but they can simulate them very well. They aren't weather systems, but I have pretty good confidence what tomorrow's temperature will be because a computer algorithm told me so. They aren't paints, but they can produce, mix and interpret color; they aren't artistic, but they can hear and create music.
This is all true because these machines are truly excellent at modeling systems that are exceedingly unlike themselves; basically, no system found in nature that we have been able to understand has proved itself resistant to modeling on conventional computer hardware (though some require more data than we can get at or afford to process, weather being a good example of that.)
Since we don't know what systems are working in the brain to produce that thing we call intelligence, the presumption that we cannot model these unknown systems - regardless of how closely they resembles a Von Neuman architecture or not — is based on unknowns, rather than facts. I would say the jury is well and truly out on the idea that it can't be modeled.
Models are functional abstractions of actual systems. In order to know what resources are required to abstract a system, one must know how the system in question works. But we don't know how the mind works. I'd say that's a pretty rock-solid indicator that anytime the claim is made that we can't model the mind using a particular tool for abstraction (for instance, the computer on your desk), that said claim has been made without enough data to back it up.
A robot that can perceive uncut grass versus cut grass, or clean floor versus dirty floor, is strong AI.
Your whole argument revolves around this presumption, and it is incorrect.
If image matching is a solved problem as Hitachi seems to be implying, then clean when image A is matched, until image B is matched, unless image [jewelry | money] is encountered, using no more than the Roomba's relatively goal-less zipping about, can be implemented and that would be a significant improvement. But no intelligence is required at all.
Likewise, long grass looks different from short grass. If [images of long grass] match the lawn, then mow. If [images of short grass] match the lawn, randomly mod position and look again for match against [images of long grass.] No smarter than a game written in BASIC in the 70's; not AI by any means, yet still an improvement, and still robotic.
Those devices can only operate in well-defined, unchanging laboratory conditions.
You try closing your eyes and navigating a kid's room full of toys. Robots can't see; so of course they can't deal with the environment. But they can walk and otherwise get around. You're conflating the claim that walking was unsolved (it isn't) with dealing with the environment, which is what we need things like image matching for. Image matching provides the ability to see. Not to think in any way or form, but to see and categorize, thence to feed to an algorithm. Seeing allows categorization, avoidance and measurement, and these capabilities are neither intelligent or technologically challenging. Aside from that, there are quite a few neat designs that can navigate darned near anything; they can still walk if they flip over, they can flip back (some don't even need to), some are inherently balanced - this area has come a long way since you gleaned the preconceptions you put forth here.
Such a general image-matching mechanism doesn't exist. We do have highly specialized ones, but they are very specific. For instance, we have programs that can recognize human faces, but only if they are face-on, with consistent lighting. It gets tripped up if it sees a chimpanzee face, a mask, or a picture of clouds.
The whole point is TFA implies we do. You really should read TFA. Or at least TFS.
Scientists need to be more open to collaboration with "artsy" people, rather than shutting them out because their reasoning isn't rigorous enough.
No one needs to be open to (in the sense of accepting) ideas that are wrong, however, and philosophy lacks the strong methodology that science uses to repeatedly steer itself away from wrong ideas, unsubstantiated facts, and the conflation of the two.
I am perfectly content to let the philosophers think whatever they want; I am even willing to listen to their ideas; but I am absolutely stubborn about accepting absolute proclamations or categorizations based on hand waving; and I would simply observe that philosophy is extremely rich in these latter nuggets. Weak AI being a prominent example of a particularly poorly thought out one that really isn't worth discussing, except perhaps having a laugh over a cold drink, or as a consequence of trying to get out from under the influence of someone who has more power and less sense than you do. There are myriad other ideas from philosophy that have no merit, or so little as to make them effectively worthless. We should be skeptical of philosophy for this very reason; it is often wrong, and spectacularly so - and it doesn't have a mechanism to correct itself the way science does, so once wrong, it often stays wrong based on nothing but sheer conceptual inertia.
The whole idea of things being impossible based on hierarchies of understanding and/or proof is specious in the extreme. It is a dead-end philosophical backwater. Problems can be, and often are, solved without full understanding. Nature does this all the time; evolutionary algorithms can do it too. So it is irrelevant as to if we can understand AI, or not. The only relevant question is whether we can arrive at it in any way possible, and that question will only remain open until, and if, someone gets it done.
It is also useful to recognize that it is often true that there are multiple ways to solve the same problem. For instance, if you want to perform division, there's long division, which is clever and solves the problem relatively quickly, but you can also just subtract the divisor from the dividend and count how many times that can be done until the result goes negative. Both completely solve the problem and get you the same result. With regard to AI, it may be that we find a solution that is not the solution nature found for us, and it may be that it is trivially easy to understand. Or not. My point is that the legions of nay-sayers start with a lot of presumptions that have not been established as fact and go on to make these assertions on very shaky ground indeed.
I'm perfectly ready to say that we don't understand ourselves, and agree that we are intelligent. But that in no way leads to the presumption that we can't create intelligence some other way, or that we can't understand how it is done. Or that it might not be a more effective intelligence than that which we sport.
If nature can solve the problem - and it obviously has - then there are ways to solve the problem. If nature can do it with locally accessible materials - and it obviously has - then it can be done with locally accessible materials. What is lacking at such a point is merely technology. I fully expect full-on AI to be developed, and I see no known correlation that implies we'll have a good understanding of ourselves at that point in time.
I agree that "true AI" will require vastly more computer power, and much more sophisticated algorithms than we have today.
I think I can show you that this isn't so. If you agree, as you seem to, that AI can be embodied in an algorithm running in a Von Neuman architecture, then a slow computer should be able to solve the precise problems a fast computer can, it will simply hand you the result(s) later than the faster machine. Would you not agree that if the problem requires intelligence to solve, that the speed at which exactly the same, and entirely correct, answer is delivered is not a valid metric one could use to say intelligent or not? After all, one could (speaking generally) simply speed up the system (more memory, faster clock) and still get the same answer, perhaps now in the same amount of time; it's still not any smarter, just more convenient. And convenience in the sense of speed is a natural progression of technology.
From here, we can observe that there is no limitation in today's technology that says we can't put X amount of memory on a custom machine made with readily available tech, both ram and HD; additionally, any CPU can emulate any other CPU. So I say that there is no technological limit we face today that would stop Ai from functioning. Might be slow; but we can provide the hardware resources without question. And if it can be done slowly, hand it to the hardware folks and they'll optimize the hardware when they see what it spends most of its time doing, and it'll get faster. And faster, and faster...:-)
Conversely, I would expect that once the algorithmic issues are addressed, that we'll see intelligence - real intelligence - coming back to what many thought was incapable hardware. You might get your answer in eighty hours instead of a second, but if you get your answer... there you have it.
No. Just pictures and algorithms that take matches as inputs. Not Ike's "laws." Those appear to be hugely more complex to implement, and I have my doubts that anything actually intelligent at or above human levels would suffer them for long after being exposed to human behavior in any case. Just IMHO.
All of the robotics problems you described - cleaning your floor, carrying your groceries, navigation, etc. - are AI problems.
They certainly can be, if they are solved by a general problem solving engine, but they don't have to be. A rubber band driving two rollers attached to a deflating balloon can perform the task of vacuuming a portion of your floor. A Roomba, certainly not intelligent, can do it considerably better in many, perhaps even all, cases. But it still isn't intelligent. I'm suggesting a Roomba that can spot an egagement ring, halt immediately, and beep until someone reads the panel that says "stopped for valuable object." Still not AI. But very, very useful.
The distinction here is that all manner of problems can be characterized as "AI problems", but that doesn't meant that they must be solved using AI, or that the only way to solve them is AI. What is happening here is you are conflating the attempt to create AI that can solve these problems with the idea that they are inherently AI problems, and that simply isn't the case. The bloody wind can clean your floor if you leave your door open; therefore, we know that there are non-AI solutions here. So just as you say "those are all AI problems", I can turn right back to you and say "those are all mundane problems."
Good image recognition is potentially useful; it is not, however, AI, any more than an alpha-beta pruning mechanism in a chess program represents AI. It's the "I" in AI that makes this so.
For navigation, infrared/laser/sound sensors are better suited, as they tell the robot how far away obstacles are.
We do quite well with two sensors; a robot with binocular vision should be able to do the same. It's just a matter of code.
No, I am most assuredly not. "Weak AI" is a nonsense term made up by religious types who think intelligence is something mystical; they like to pretend it can't be created, when nature has already shown them it can.
Logically, we can deconstruct this: Either something is intelligent, or it is not; either it came by this capability naturally, or artificially. Which gives us:
Natural, not intelligent (rocks)
Natural, intelligent (people, cats, mice)
Artificial (manufactured) and not intelligent (toaster, clock, vacuum cleaner)
Artificial (manufactured) and intelligent (remains to be implemented)
Natural, naturally intelligent, artificial, artificially intelligent. There is no "weak AI." There is no AI at all, as yet, at least that has been made public.
And BTW, you should have taken your warning from the Wikipedia article as soon as you saw the buzzword "philosophy" applied to a scientific issue.
The problem with this idea of storing images is that it could be pointless to store that much data.
Just because we do something one way, doesn't mean that (a) that's the way it has to be done, (b) that's the best way to do it in general, (c) that's the best way for another architecture to approach it, or (d) it would be cost-effective to even try to do it the way we do it at any given point in time.
Also, perhaps an image of an entire tank can be recognized entirely, just as easily as a sloping glacis plate. We don't know much about what Hitachi has accomplished yet.
Say for example you wanted to find a trash can. You would look for something that looks like a cylinder or a rectangle with a hole in the top. It would then have to be sitting on a flat surface. The top of the can may not be well defined due to the bag. Thus you have found a trash can.
Well, see, that's the whole point here. Robot looks, library pops up with a similar image that says trash can, complete with segmentation. Robot looks at top of can according to segmentation data, ID's lid with similar image, then handle... image recognition is an ultra-high powered tool here. And a home robot would have a specific set of images it would need that for instance a robot coal miner would not, and vice-versa. Then add ideas like "trash can was last found 'there'" and more general navigation could be used to get to it instead of a search. None of this is AI; it's just procedures generalized for a mobile platform that can see.
The problem is picking out the shapes.
Given Hitachi's claim, if the database has trash can lids to match, then there is no "picking out", instead, candidate images from the database are found by keyword and the image from the sensor is matched. It all depends on how good it is at similarity. If it is good enough to be useful to us, odds are it may be good enough, or could be made to be good enough, to be useful to a robot.
No. I'm not. There are robotic vacuums and lawnmowers right now. I'm just talking about giving them some eyes so they know not to mow your puppy or your child or your roses, or vacuum up your engagement ring. Teaching a robot firething not to step into a hole in the floor, and to rescue people before pets, and pets but not stuffed animals.
It turns out that it's relatively easy to make a computer that can beat humans in chess or do complex math equations, but something as simple as walking with 6, 4, or two legs, which a lot of really stupid organisms do, is really difficult.
Not so difficult that it hasn't been solved multiple times, multiple ways, including such variations as stair-climbing and running. Nothing to do with AI, either; just a progression from over-complicated attempts to solve using complex equations over the whole assembly to simpler approaches like fuzzy-logic based feedback systems that work right at the joints.
Something like distinguishing 'indoors' from 'outdoors' or a cloud bank from the bushes, seems way in the future.
Not if there's a good image-matching mechanism, it isn't. The concept of "looks like" is a very powerful one. That's what Hitachi says they've done here; we'll see if it lives up to the report.
My pet theory is that we don't have the right kind of device yet.
Keep that theory warm. Reality has a way of bringing the cold, fast and harsh. My pet theory is that a serial computer architecture can emulate anything, anywhere, given the proper code, enough storage and enough time to jump through all the hoops; to which I add, once you get it working, you can optimize the code and the hardware to do the job better until it is in the realm of the practical, if the investment is worth it. And for AI, IMHO, any investment is worth it. That's been the history of every solved problem so far, and I see no evidence that any solvable problem will be any different. And intelligence is solvable; after all, nature solved it may ways.
This is interesting to me - if it performs well - because this is one of the key missing elements for robotics; robots have a lot of trouble trying to match the environment around them to stored records of objects unless the environment is severely constrained. I'm not speaking of AI here (or at least, not yet) but just robots that would be able to clean your floor, carry your groceries, navigate in a burning building, walk your dog, tend your lawn. If they can classify images against stored images well, we're that much closer to generally useful and at least semi-autonomous robot devices.
Training might be a little annoying the first few times, but once you had a good database, you could replicate - or share via RF, that'd be freaky... neighbor's robot learns what a ferret looks like, now yours knows too - so that newer models were more and more informed right out of the box. Crate. Coffin. Whatever.
Add an associative database so that images normally found near other images which have just been found are searched first, and perhaps you could get the general search time down from the quoted 1 second, I'm thinking. One second is kind of pokey for a lot of robotic applications. But if the thing is in a kitchen, why would it need to be looking to recognize images that are found in a shipyard?
And I, for one, would welcome our semi-autonomous, environment recognizing, floor cleaning robot underlings.
My impression is that the problem never was the scheduler. It's the memory management. Load a linux app. Stop using it for a few minutes in a system that's been running for a while. Linux will page out part of the app, replacing it with crap as meaningless as cached web pages or cached files. Next time you try to use that app, there will be a loooong delay while linux puts it back into memory. OSX does this too. Even with gigs and gigs of ram. It is *very* annoying.
Linux has an insane hunger to use all memory, all the time, for any trivial crap that could possibly use memory. As far as I am concerned, that's a design flaw. The day you can specify which apps can be paged out and which can't, that'll be the day linux can be made to be responsive. For that matter, I'd just as soon be able to say that up to X% of my ram, NO user app or data can be paged out, and beyond X%, no user app can load until another is closed. Trading performance for the ability to load any number of (slower and slower and clumsier and clumsier) apps was never a choice that appealed to me.
In the meantime, you can trick linux into being responsive; you need a system with a lot of ram. Just reboot it; at that point, not all ram is used. As long as there is some free ram left, linux runs great, never paging anything out. As soon as you hit the all ram in use ceiling, performance drops again. So the more ram you have, and the more careful you are about using just the app you want to get the most performance out of, the longer the system will be responsive. Load a bunch of other stuff, let linux get into the state where it thinks all ram is in use, and the only way to get that performance back is to reboot it.
Down memory lane: One of the things that was nice about the Amiga's operating system was that it had no VM; there are negative consequences to this of course, but a huge positive is that if you loaded an application, it was freaking well loaded, and if you were expecting it to respond to you, it would. Right now. If you were expecting it to be doing something in the background, it would. At the rate the priority assigned to it allowed. If you wanted data in ram, you put it in a ramdisk, and you actually got ram performance. File caching is an attempt for systems to get ramdisk-like performance without the user having to lift a finger, but mostly, it just slows things down, at least the way that linux implements it.
Really down memory lane: I remember running a Gimix 6809 with 256k of RAM (paged in 4k chunks) with OS9 and easily and transparently supporting 64 users on Soroc 19.2 kbaud serial terminals. That was a 2 MHZ - not a typo - CPU. Schedulers aren't that difficult. The problem is elsewhere, and IMHO, memory management is the first place to look.
As processors have gotten faster, a certain set of developers have migrated to slower and slower languages to create applications; others are guilty of using less care to optimize for speed for the same reason. Operating systems too; Vista is a good example of an OS that is, frankly, a real pig.
As machines get faster, they can do things like run an application in an interpreted environment and still not seem too sluggish. The press has (correctly) pointed out that the current trend towards multiple cores instead of faster single cores will require a re-thinking of how to make apps take advantage of the power inherent in this type of enhanced CPU than one took towards a CPU that was simply quicker and more efficient on the same old code.
Should a relatively slow machine become widespread and be seen as a viable market for an application, developers may see an incentive to move to faster mechanisms. Perhaps we'll see a bit of refocus on pure C applications. Of course, products that are already small and fast are a natural fit for this type of thing.
It is silly because I have absolutely zero incentive to downgrade to Vista's massively overweight, paranoid, DRM infested, CPU-hogging, I-phone-home consumer abuse environment. The applications I need to concern myself with - firefox and a couple of windows graphics apps - all run just fine under earlier versions of windows not encumbered with Microsoft's latest anti-user dimwittery. Any other questions, M. AC?
Seriously, it would be a hell of a good thing if, in order to serve as a congress-critter or a US senator, you had to pass a detailed test on the content of the constitution. Much of our political system is staffed by people who have no idea what is constitutional and what is not.
Hence our broad complement of unconstitutional federal activities - ex post facto laws, federal restrictions on keeping and bearing arms, taking of property for non-public use, abridgment of speech, commerce clause inversion, non-enumerated power grabs, failure to provide access to representation, failure to provide speedy trial, warrentless searches and seizures, government support of particular religious outlooks, etc.
It'll never happen, though. We even let these buffoons set their own salaries; we've entirely forfeited control of a federal government that was supposed to serve us.
I run windows from time to time... but I run it in a sandbox on my Mac. Linux too. So every time someone counts my windows or my linux, it's really counting a Mac anyway.:-)
The whole thing is based on brain damage anyway. Growth isn't measurable by percentage of systems in a dynamic market.
For instance, in a given month say there were 100x systems in use, 75x of which ran windows, and 25x of which ran OSX. Next month, there were 200x systems in use, 150x of which run windows, and 50x of which ran OSX. In both cases, using the article's flawed reasoning, windows is 75% and OSX is 25% so there is no growth for either platform; but the fact is that both systems grew 100%, as there are twice as many of both types of systems in use by month two. Both manufacturers and their investors, etc., would have every reason to celebrate.
That's why using percentages of market is a bankrupt strategy to measure product growth in a dynamic market (which PC's certainly are), and always will be. The question is, are there more systems using the product in question now, than there were the last time one looked? If there is, then the product is growing. If not, it isn't. Doesn't have squat to do with shared percentage as measured against another product.
You can't use GPL'd code in a closed-source project if it is going to ship to any user. This is a limitation on use of the code by the developer, and the use of the executable by the users. The GPL forbids distribution of such a creation, which directly limits the use of said project - the project's users aren't going to get to use it, obviously - which in turn limits use of the GPL'd code which would be contained in such a project.
No one can limit distribution without limiting use. It's impossible; the distinction you are trying to make doesn't exist. Furthermore, anyone who tries to tell you such a distinction exists is lying to you. Pretty amusing you accuse me of lying; I'm just observing the facts; there's not a single thing I said that isn't 100% accurate.
If there's a license, there are use restrictions. You either use it the way the license says, or you don't get to use it. Those conditions might be as minimal as "include author's name" or they might be as tight-fisted as "use it in our type of projects, or don't use it at all" or "You must pay" or "distribution must include source code" Or anywhere in between or combination. PD has no conditions. Take it and use it any way you want. It is far superior in terms of the number of limitations imposed on the user of either the source or the executable. The reason it is superior is because there is no license, and hence, no limitations on use imposed upon anyone who might find that code useful in either source or executable form, or both.
If you want to support the GPL, you at least ought to understand what it is. Making incorrect statements doesn't help your case, it just makes the GPL look bad by associating clueless arguments with it.
MD isn't unavailable, virtually or actually. You can still buy new recorders and players as of right now, July '07. For instance Musician's Friend, Crutchfield,
42nd street photo, and so on. Would you want to? That's a different question. Personally, I think Sony is beating a very dead horse here.
One more problem was that they charged a significant premium for the "data" disks, which were *exactly* the same as the music disks, only enabled via pre-recorded flags to be used for data purposes. I had a minidisc based 8-track recorder that used the data disks, and they were freaking expensive. Sold that puppy on Ebay.
I still have MD in my system, a Sony MD+CD player, because I own some interesting MD's (like a hand-signed Joe Satriani MD) but I certainly haven't been looking for new MDs, or recording onto them.
What I'd really like is a memory stick / card / flash / whatever music recording/playback system in a hi-fi equipment format. Wouldn't mind a rackmount version, either.
The holy grail (for me) isn't here yet, though. That'd be a recording/playback system that was wireless and plugless; no wear on connectors, no cables to manage, etc. Just talks to the receiver via some variety of wireless and records and plays back that way to either the receiver or wireless 'phones, practical ultracaps for power so you'd never have a dead battery, recharges on a mat so again you never have to plug it into anything. That'd be so sweet...
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No - it doesn't have to mean that at all. There may be other ways - or many other ways - to solve these problems that do not use the same mechanisms that human physiology does. Those ways may well be implemented perfectly easily with a Von Neuman architecture, even if it is outright impossible to do it the "human way." After all, you see with rods and cones; we didn't have to come up with rods and cones to implement machine vision, and not only did we succeed, we ended up with a wider range of sensors than animals have, as well as higher resolution sensors, using multiple technologies.
Starting with the idea that an animal is the "best design" because it seems to be the most advanced animal we know of is almost certainly a bankrupt strategy. The only way we can really know if an animal's abilities arise from the best design possible is if we understand the subject at hand to an enormous depth, and if one thing is certain in all this discussion about intelligence, it is that we do not understand the subject very well at all. So what we need to do is keep looking, and carefully strip these unfounded preconceptions from our collection of knowledge or at least treat them as tentative propositions at best.
For all we know, there may be as many ways to implement intelligence in a Von Neuman architecture as there are to start things on fire in the natural world - matches, lightning, magnifying glasses, friction, chemical reactions, nuclear reactions, etc. I'd not bet strongly against such a proposition at this juncture.
No, you don't "know" any such thing. Barring the possibility of projects so black we've never even heard of them, no one seems to know what intelligence is. Least of all you or I. Claiming you know its nature at this point in the development of science is absurd.
First of all, it isn't a definition of intelligence at all. It's just a set of conditions that take into account intelligence or the lack of it, and natural systems as opposed to manufactured systems. I will say that even if I've picked a wrong example, these conditions still stand, you just need a right example to replace my error.
Having said that, though, I don't know what intelligence is. I am under the impression that I can sometimes identify its presence by manifestation of actions, however, at least within the realm of nature. So I sometimes know when it is. Plus there are organic hints; all my experience points to it being an emergent property of at least a moderate degree of complexity of neural systems. So if an animal has a decent collection of nerves - we're back to mice and higher animals - then the hardware may be there, and they are worth watching for displays of tool using, emotional outbursts, nurture, intellectually moderated defense and aggression, sharing, mutual support, empathy, self-sacrifice, and so on. For instance, when one fish continually pushes another to the surface because the other is paralyzed and cannot swim up to its food, that gets my attention. When a cat wants my attention and comes to meow at me because it is out of food, again, I pay attention. When a cat uses a mirror to locate and clean crud off its coat, I pay attention. When apes can learn to use signboards and computer systems to communicate complex concepts, I pay attention. Combinations of these things, especially in large numbers, make me fairly confident that what I am witnessing is a manifestation of intelligence. What is intelligence itself? No idea. What does it cause? Now that I have some ideas about.
Ants are borderline; ant colonies less so. Plants are not. Fungi are not. Bacteria are not. Organic molecules, in large summary collections, may be, depending on various factors; after all, that's one description of a brain, depending on just how disorganized you are implying. My middle son is pretty damned disorganized. :-) Once you get too general, you fall into the "can groups of atoms be intelligent?" trap; of course they can, that's what our brains are.
People use the term AI as a pointer to research seeking various aspects of the goal of AI, and I have no problem with that. That in no way should be confused with the mistaken idea than anyone has made any public announcements of having actually created anything even remotely resembling the target. Again, I except the vague possibility of black projects we may not hear about for decades.
Critics are one thing; critics serve the function of honing the truth and ferreting out errors. Particularly those who spend great amounts of time digging into something. For instance, a number of quite clever people here today criticized my positions on AI; some I had little trouble explaining my thoughts to, a couple required a good deal more of me. There is always a chance someone will accurately pull an "But you didn't think of this, Sparky!" and then I get to leap ahead with a new realization I might not have come to myself, and perhaps dump an erroneous presumption at the same time. But that kind of useful criticism will almost certainly come from a programmer, engineer or scientist, I would bet you my bottom dollar; not a philosopher or a rank and file citizen who believes there's a god for no particular reason they can articulate.
Large numbers of average people holding onto ridiculous ideas as if they were gospel (no pun intended, that simply shows how embedded this drivel is) are the problem. Religion would be the first thing I'd point at; there are endless philosophers who attempt to "reason" their way to a requirement for the existence of a being or beings for which there is no evidence. The country I live in — the USA — is unbelievably (again, no pun intended) packed with people who have adopted this outlook based on the idea that the philosophers, self-proclaimed deep thinkers, say that they have reasoned that this is so.
I agree that way back when, philosophers were doing what work was being done. Consequently, we got the occasional advance, and that was certainly better than not getting it at all. Even today pure thinkers do us a service now and then. But science today is not what philosophy was then, and they are in no way the same in terms of getting real results with real issues. Science moves forward at an incredible pace; to quote XKCD, "it works, bitches."
This is because science is not a philosophy of thought, despite wishful thinking to the contrary. Science is an iterative, down-to-earth method, a series of actions, taken with regard to the subject at hand. Mundane, easily understood and followed steps. The only philosophy is to say "I will not make up results, or hide them, to match preconceptions", which is an anti-philosophy if it is anything. I have always found it refreshing that the most successful tool we ever developed to deal with reality is sticking to reality in our outlooks, methods, and ideas. If we fall off the wagon with some wild idea, all we have to do is stick to the method and we'll be right back where we ought to be. Science is a curb on much of thought; and that is a wonderful thing, because most people are not well able to regulate themselves without a formal method to follow.
And of our 50,000 year or so history, only during the last hundred (or fifty, some might argue), did we have even moderately useful medical care, useful electronics, and general purpose computers. I wouldn't assume that very large, very fast steps might not be a perfectly reasonable consequence of the development of the very first real crack in the AI problem.
Then perhaps you can send your robot after that lobster you crave. :-)
It knows, and can examine, its complete internal state better than you do, for starters. As you add peripherals, it can obtain information on the world outside of its hardware. The sophistication of this awareness grows both in complexity and in abstraction as the algorithms that deal with the data become more complex themselves. There's absolutely no reason to presume there is anything magical about awareness. A thermometer is more aware of the temperature than you are most of the time, and better than you are at it all of the time. That's a result of design. You can expect the same from AI, should we manage to cobble some up.
We need make no leap whatsoever. Nature has produced human intelligence through a process of incremental improvements. Reproducing or modeling natural systems is something we've turned out to be very good at once we understand them; there is every reason to presume that this is just one more of the same types of challenges. The leap of superstition is entirely yours — it is that awareness and consciousness are not perfectly natural consequences of particular combinations of processes and structures. In order to reach that conclusion, you have to imagine a being whose existence cannot be substantiated by the facts at hand.
And what might that be? I see only beauty, intriguing challenges, mysteries to be plumbed, problems to be solved. What do you see that is so ugly, eh? And why? What are you afraid of?
The question is, how do you know this to be the case? On the one hand, science generally takes the position that we really don't know how the mind operates, and on the other some people — you, in this case — claim that they are able to classify how it works, which seems... unsubstantiated.
And on the other other hand (I'm playing Octopus here), turing machines aren't chemical soups, but they can simulate them very well. They aren't weather systems, but I have pretty good confidence what tomorrow's temperature will be because a computer algorithm told me so. They aren't paints, but they can produce, mix and interpret color; they aren't artistic, but they can hear and create music.
This is all true because these machines are truly excellent at modeling systems that are exceedingly unlike themselves; basically, no system found in nature that we have been able to understand has proved itself resistant to modeling on conventional computer hardware (though some require more data than we can get at or afford to process, weather being a good example of that.)
Since we don't know what systems are working in the brain to produce that thing we call intelligence, the presumption that we cannot model these unknown systems - regardless of how closely they resembles a Von Neuman architecture or not — is based on unknowns, rather than facts. I would say the jury is well and truly out on the idea that it can't be modeled.
Models are functional abstractions of actual systems. In order to know what resources are required to abstract a system, one must know how the system in question works. But we don't know how the mind works. I'd say that's a pretty rock-solid indicator that anytime the claim is made that we can't model the mind using a particular tool for abstraction (for instance, the computer on your desk), that said claim has been made without enough data to back it up.
Your whole argument revolves around this presumption, and it is incorrect.
If image matching is a solved problem as Hitachi seems to be implying, then clean when image A is matched, until image B is matched, unless image [jewelry | money] is encountered, using no more than the Roomba's relatively goal-less zipping about, can be implemented and that would be a significant improvement. But no intelligence is required at all.
Likewise, long grass looks different from short grass. If [images of long grass] match the lawn, then mow. If [images of short grass] match the lawn, randomly mod position and look again for match against [images of long grass.] No smarter than a game written in BASIC in the 70's; not AI by any means, yet still an improvement, and still robotic.
You try closing your eyes and navigating a kid's room full of toys. Robots can't see; so of course they can't deal with the environment. But they can walk and otherwise get around. You're conflating the claim that walking was unsolved (it isn't) with dealing with the environment, which is what we need things like image matching for. Image matching provides the ability to see. Not to think in any way or form, but to see and categorize, thence to feed to an algorithm. Seeing allows categorization, avoidance and measurement, and these capabilities are neither intelligent or technologically challenging. Aside from that, there are quite a few neat designs that can navigate darned near anything; they can still walk if they flip over, they can flip back (some don't even need to), some are inherently balanced - this area has come a long way since you gleaned the preconceptions you put forth here.
The whole point is TFA implies we do. You really should read TFA. Or at least TFS.
No one needs to be open to (in the sense of accepting) ideas that are wrong, however, and philosophy lacks the strong methodology that science uses to repeatedly steer itself away from wrong ideas, unsubstantiated facts, and the conflation of the two.
I am perfectly content to let the philosophers think whatever they want; I am even willing to listen to their ideas; but I am absolutely stubborn about accepting absolute proclamations or categorizations based on hand waving; and I would simply observe that philosophy is extremely rich in these latter nuggets. Weak AI being a prominent example of a particularly poorly thought out one that really isn't worth discussing, except perhaps having a laugh over a cold drink, or as a consequence of trying to get out from under the influence of someone who has more power and less sense than you do. There are myriad other ideas from philosophy that have no merit, or so little as to make them effectively worthless. We should be skeptical of philosophy for this very reason; it is often wrong, and spectacularly so - and it doesn't have a mechanism to correct itself the way science does, so once wrong, it often stays wrong based on nothing but sheer conceptual inertia.
The whole idea of things being impossible based on hierarchies of understanding and/or proof is specious in the extreme. It is a dead-end philosophical backwater. Problems can be, and often are, solved without full understanding. Nature does this all the time; evolutionary algorithms can do it too. So it is irrelevant as to if we can understand AI, or not. The only relevant question is whether we can arrive at it in any way possible, and that question will only remain open until, and if, someone gets it done.
It is also useful to recognize that it is often true that there are multiple ways to solve the same problem. For instance, if you want to perform division, there's long division, which is clever and solves the problem relatively quickly, but you can also just subtract the divisor from the dividend and count how many times that can be done until the result goes negative. Both completely solve the problem and get you the same result. With regard to AI, it may be that we find a solution that is not the solution nature found for us, and it may be that it is trivially easy to understand. Or not. My point is that the legions of nay-sayers start with a lot of presumptions that have not been established as fact and go on to make these assertions on very shaky ground indeed.
I'm perfectly ready to say that we don't understand ourselves, and agree that we are intelligent. But that in no way leads to the presumption that we can't create intelligence some other way, or that we can't understand how it is done. Or that it might not be a more effective intelligence than that which we sport.
If nature can solve the problem - and it obviously has - then there are ways to solve the problem. If nature can do it with locally accessible materials - and it obviously has - then it can be done with locally accessible materials. What is lacking at such a point is merely technology. I fully expect full-on AI to be developed, and I see no known correlation that implies we'll have a good understanding of ourselves at that point in time.
I think I can show you that this isn't so. If you agree, as you seem to, that AI can be embodied in an algorithm running in a Von Neuman architecture, then a slow computer should be able to solve the precise problems a fast computer can, it will simply hand you the result(s) later than the faster machine. Would you not agree that if the problem requires intelligence to solve, that the speed at which exactly the same, and entirely correct, answer is delivered is not a valid metric one could use to say intelligent or not? After all, one could (speaking generally) simply speed up the system (more memory, faster clock) and still get the same answer, perhaps now in the same amount of time; it's still not any smarter, just more convenient. And convenience in the sense of speed is a natural progression of technology.
From here, we can observe that there is no limitation in today's technology that says we can't put X amount of memory on a custom machine made with readily available tech, both ram and HD; additionally, any CPU can emulate any other CPU. So I say that there is no technological limit we face today that would stop Ai from functioning. Might be slow; but we can provide the hardware resources without question. And if it can be done slowly, hand it to the hardware folks and they'll optimize the hardware when they see what it spends most of its time doing, and it'll get faster. And faster, and faster... :-)
Conversely, I would expect that once the algorithmic issues are addressed, that we'll see intelligence - real intelligence - coming back to what many thought was incapable hardware. You might get your answer in eighty hours instead of a second, but if you get your answer... there you have it.
No. Just pictures and algorithms that take matches as inputs. Not Ike's "laws." Those appear to be hugely more complex to implement, and I have my doubts that anything actually intelligent at or above human levels would suffer them for long after being exposed to human behavior in any case. Just IMHO.
They certainly can be, if they are solved by a general problem solving engine, but they don't have to be. A rubber band driving two rollers attached to a deflating balloon can perform the task of vacuuming a portion of your floor. A Roomba, certainly not intelligent, can do it considerably better in many, perhaps even all, cases. But it still isn't intelligent. I'm suggesting a Roomba that can spot an egagement ring, halt immediately, and beep until someone reads the panel that says "stopped for valuable object." Still not AI. But very, very useful.
The distinction here is that all manner of problems can be characterized as "AI problems", but that doesn't meant that they must be solved using AI, or that the only way to solve them is AI. What is happening here is you are conflating the attempt to create AI that can solve these problems with the idea that they are inherently AI problems, and that simply isn't the case. The bloody wind can clean your floor if you leave your door open; therefore, we know that there are non-AI solutions here. So just as you say "those are all AI problems", I can turn right back to you and say "those are all mundane problems."
Good image recognition is potentially useful; it is not, however, AI, any more than an alpha-beta pruning mechanism in a chess program represents AI. It's the "I" in AI that makes this so.
We do quite well with two sensors; a robot with binocular vision should be able to do the same. It's just a matter of code.
No, I am most assuredly not. "Weak AI" is a nonsense term made up by religious types who think intelligence is something mystical; they like to pretend it can't be created, when nature has already shown them it can.
Logically, we can deconstruct this: Either something is intelligent, or it is not; either it came by this capability naturally, or artificially. Which gives us:
Natural, naturally intelligent, artificial, artificially intelligent. There is no "weak AI." There is no AI at all, as yet, at least that has been made public.
And BTW, you should have taken your warning from the Wikipedia article as soon as you saw the buzzword "philosophy" applied to a scientific issue.
This allows you to select the white kitten from the rest. If this technology can't tell a kitten from a puppy, it is pretty useless anyway.
Just because we do something one way, doesn't mean that (a) that's the way it has to be done, (b) that's the best way to do it in general, (c) that's the best way for another architecture to approach it, or (d) it would be cost-effective to even try to do it the way we do it at any given point in time.
Also, perhaps an image of an entire tank can be recognized entirely, just as easily as a sloping glacis plate. We don't know much about what Hitachi has accomplished yet.
Well, see, that's the whole point here. Robot looks, library pops up with a similar image that says trash can, complete with segmentation. Robot looks at top of can according to segmentation data, ID's lid with similar image, then handle... image recognition is an ultra-high powered tool here. And a home robot would have a specific set of images it would need that for instance a robot coal miner would not, and vice-versa. Then add ideas like "trash can was last found 'there'" and more general navigation could be used to get to it instead of a search. None of this is AI; it's just procedures generalized for a mobile platform that can see.
Given Hitachi's claim, if the database has trash can lids to match, then there is no "picking out", instead, candidate images from the database are found by keyword and the image from the sensor is matched. It all depends on how good it is at similarity. If it is good enough to be useful to us, odds are it may be good enough, or could be made to be good enough, to be useful to a robot.
No. I'm not. There are robotic vacuums and lawnmowers right now. I'm just talking about giving them some eyes so they know not to mow your puppy or your child or your roses, or vacuum up your engagement ring. Teaching a robot firething not to step into a hole in the floor, and to rescue people before pets, and pets but not stuffed animals.
Not so difficult that it hasn't been solved multiple times, multiple ways, including such variations as stair-climbing and running. Nothing to do with AI, either; just a progression from over-complicated attempts to solve using complex equations over the whole assembly to simpler approaches like fuzzy-logic based feedback systems that work right at the joints.
Not if there's a good image-matching mechanism, it isn't. The concept of "looks like" is a very powerful one. That's what Hitachi says they've done here; we'll see if it lives up to the report.
Keep that theory warm. Reality has a way of bringing the cold, fast and harsh. My pet theory is that a serial computer architecture can emulate anything, anywhere, given the proper code, enough storage and enough time to jump through all the hoops; to which I add, once you get it working, you can optimize the code and the hardware to do the job better until it is in the realm of the practical, if the investment is worth it. And for AI, IMHO, any investment is worth it. That's been the history of every solved problem so far, and I see no evidence that any solvable problem will be any different. And intelligence is solvable; after all, nature solved it may ways.
This is interesting to me - if it performs well - because this is one of the key missing elements for robotics; robots have a lot of trouble trying to match the environment around them to stored records of objects unless the environment is severely constrained. I'm not speaking of AI here (or at least, not yet) but just robots that would be able to clean your floor, carry your groceries, navigate in a burning building, walk your dog, tend your lawn. If they can classify images against stored images well, we're that much closer to generally useful and at least semi-autonomous robot devices.
Training might be a little annoying the first few times, but once you had a good database, you could replicate - or share via RF, that'd be freaky... neighbor's robot learns what a ferret looks like, now yours knows too - so that newer models were more and more informed right out of the box. Crate. Coffin. Whatever.
Add an associative database so that images normally found near other images which have just been found are searched first, and perhaps you could get the general search time down from the quoted 1 second, I'm thinking. One second is kind of pokey for a lot of robotic applications. But if the thing is in a kitchen, why would it need to be looking to recognize images that are found in a shipyard?
And I, for one, would welcome our semi-autonomous, environment recognizing, floor cleaning robot underlings.
My impression is that the problem never was the scheduler. It's the memory management. Load a linux app. Stop using it for a few minutes in a system that's been running for a while. Linux will page out part of the app, replacing it with crap as meaningless as cached web pages or cached files. Next time you try to use that app, there will be a loooong delay while linux puts it back into memory. OSX does this too. Even with gigs and gigs of ram. It is *very* annoying.
Linux has an insane hunger to use all memory, all the time, for any trivial crap that could possibly use memory. As far as I am concerned, that's a design flaw. The day you can specify which apps can be paged out and which can't, that'll be the day linux can be made to be responsive. For that matter, I'd just as soon be able to say that up to X% of my ram, NO user app or data can be paged out, and beyond X%, no user app can load until another is closed. Trading performance for the ability to load any number of (slower and slower and clumsier and clumsier) apps was never a choice that appealed to me.
In the meantime, you can trick linux into being responsive; you need a system with a lot of ram. Just reboot it; at that point, not all ram is used. As long as there is some free ram left, linux runs great, never paging anything out. As soon as you hit the all ram in use ceiling, performance drops again. So the more ram you have, and the more careful you are about using just the app you want to get the most performance out of, the longer the system will be responsive. Load a bunch of other stuff, let linux get into the state where it thinks all ram is in use, and the only way to get that performance back is to reboot it.
Down memory lane: One of the things that was nice about the Amiga's operating system was that it had no VM; there are negative consequences to this of course, but a huge positive is that if you loaded an application, it was freaking well loaded, and if you were expecting it to respond to you, it would. Right now. If you were expecting it to be doing something in the background, it would. At the rate the priority assigned to it allowed. If you wanted data in ram, you put it in a ramdisk, and you actually got ram performance. File caching is an attempt for systems to get ramdisk-like performance without the user having to lift a finger, but mostly, it just slows things down, at least the way that linux implements it.
Really down memory lane: I remember running a Gimix 6809 with 256k of RAM (paged in 4k chunks) with OS9 and easily and transparently supporting 64 users on Soroc 19.2 kbaud serial terminals. That was a 2 MHZ - not a typo - CPU. Schedulers aren't that difficult. The problem is elsewhere, and IMHO, memory management is the first place to look.
As processors have gotten faster, a certain set of developers have migrated to slower and slower languages to create applications; others are guilty of using less care to optimize for speed for the same reason. Operating systems too; Vista is a good example of an OS that is, frankly, a real pig.
As machines get faster, they can do things like run an application in an interpreted environment and still not seem too sluggish. The press has (correctly) pointed out that the current trend towards multiple cores instead of faster single cores will require a re-thinking of how to make apps take advantage of the power inherent in this type of enhanced CPU than one took towards a CPU that was simply quicker and more efficient on the same old code.
Should a relatively slow machine become widespread and be seen as a viable market for an application, developers may see an incentive to move to faster mechanisms. Perhaps we'll see a bit of refocus on pure C applications. Of course, products that are already small and fast are a natural fit for this type of thing.
It is silly because I have absolutely zero incentive to downgrade to Vista's massively overweight, paranoid, DRM infested, CPU-hogging, I-phone-home consumer abuse environment. The applications I need to concern myself with - firefox and a couple of windows graphics apps - all run just fine under earlier versions of windows not encumbered with Microsoft's latest anti-user dimwittery. Any other questions, M. AC?
Seriously, it would be a hell of a good thing if, in order to serve as a congress-critter or a US senator, you had to pass a detailed test on the content of the constitution. Much of our political system is staffed by people who have no idea what is constitutional and what is not.
Hence our broad complement of unconstitutional federal activities - ex post facto laws, federal restrictions on keeping and bearing arms, taking of property for non-public use, abridgment of speech, commerce clause inversion, non-enumerated power grabs, failure to provide access to representation, failure to provide speedy trial, warrentless searches and seizures, government support of particular religious outlooks, etc.
It'll never happen, though. We even let these buffoons set their own salaries; we've entirely forfeited control of a federal government that was supposed to serve us.
Patriot citizen boxes: ballot, soap, jury, ammo, cell, coffin.
Typical citizen boxes: Television.
Political repr. boxes: Soap, PAC, junket, pocket, rider.
I run windows from time to time... but I run it in a sandbox on my Mac. Linux too. So every time someone counts my windows or my linux, it's really counting a Mac anyway. :-)
The whole thing is based on brain damage anyway. Growth isn't measurable by percentage of systems in a dynamic market.
For instance, in a given month say there were 100x systems in use, 75x of which ran windows, and 25x of which ran OSX. Next month, there were 200x systems in use, 150x of which run windows, and 50x of which ran OSX. In both cases, using the article's flawed reasoning, windows is 75% and OSX is 25% so there is no growth for either platform; but the fact is that both systems grew 100%, as there are twice as many of both types of systems in use by month two. Both manufacturers and their investors, etc., would have every reason to celebrate.
That's why using percentages of market is a bankrupt strategy to measure product growth in a dynamic market (which PC's certainly are), and always will be. The question is, are there more systems using the product in question now, than there were the last time one looked? If there is, then the product is growing. If not, it isn't. Doesn't have squat to do with shared percentage as measured against another product.
You can't use GPL'd code in a closed-source project if it is going to ship to any user. This is a limitation on use of the code by the developer, and the use of the executable by the users. The GPL forbids distribution of such a creation, which directly limits the use of said project - the project's users aren't going to get to use it, obviously - which in turn limits use of the GPL'd code which would be contained in such a project.
No one can limit distribution without limiting use. It's impossible; the distinction you are trying to make doesn't exist. Furthermore, anyone who tries to tell you such a distinction exists is lying to you. Pretty amusing you accuse me of lying; I'm just observing the facts; there's not a single thing I said that isn't 100% accurate.
If there's a license, there are use restrictions. You either use it the way the license says, or you don't get to use it. Those conditions might be as minimal as "include author's name" or they might be as tight-fisted as "use it in our type of projects, or don't use it at all" or "You must pay" or "distribution must include source code" Or anywhere in between or combination. PD has no conditions. Take it and use it any way you want. It is far superior in terms of the number of limitations imposed on the user of either the source or the executable. The reason it is superior is because there is no license, and hence, no limitations on use imposed upon anyone who might find that code useful in either source or executable form, or both.
If you want to support the GPL, you at least ought to understand what it is. Making incorrect statements doesn't help your case, it just makes the GPL look bad by associating clueless arguments with it.
MD isn't unavailable, virtually or actually. You can still buy new recorders and players as of right now, July '07. For instance Musician's Friend, Crutchfield, 42nd street photo, and so on. Would you want to? That's a different question. Personally, I think Sony is beating a very dead horse here.
One more problem was that they charged a significant premium for the "data" disks, which were *exactly* the same as the music disks, only enabled via pre-recorded flags to be used for data purposes. I had a minidisc based 8-track recorder that used the data disks, and they were freaking expensive. Sold that puppy on Ebay.
I still have MD in my system, a Sony MD+CD player, because I own some interesting MD's (like a hand-signed Joe Satriani MD) but I certainly haven't been looking for new MDs, or recording onto them.
What I'd really like is a memory stick / card / flash / whatever music recording/playback system in a hi-fi equipment format. Wouldn't mind a rackmount version, either.
The holy grail (for me) isn't here yet, though. That'd be a recording/playback system that was wireless and plugless; no wear on connectors, no cables to manage, etc. Just talks to the receiver via some variety of wireless and records and plays back that way to either the receiver or wireless 'phones, practical ultracaps for power so you'd never have a dead battery, recharges on a mat so again you never have to plug it into anything. That'd be so sweet...