The summary didn't say anything about Trump. You need to check your glasses prescription. Well...except that Trump accused Obama of spying on him, which *seems* to be unrelated to the article which only talks about foreign intelligence requests. Are you asserting that *that* means spying on Trump?
The deal might also be quite good for Apple, if they can find someone else to buy it off them (while guarantying them memory chips at a really good price).
I do agree that for Apple to hold onto the chip factory would be a diffusion of focus, and thus bad. Acting as a middle-man and taking cheap chips instead of a high purchase price, however, might be a real win. *IF* they can find someone really good to purchase/run the plant.
Actually, the main problem here is fraud, but it's true that the high investment costs of nuclear power plants are a huge contributing factor. But that's so blatant in this case that it hardly needs anyone pointing it out.
Donating to a political group is not a personal lifestyle choice.
If it is a part of your "lifestyle" to force your opinions on others who are unwilling, then it is quite reasonable for them to publicly object, and to encourage others to publicly object. Against you.
Another way to say this is "Your right to swing your fist ends a bit before the other person's nose.".
You're probably correct, but they'd have huge numbers of both false positives and false negatives, and they'd use whopping amounts of CPU time and RAM. Not a good answer.
xfce has it's points, but I *do* prefer KDE. Usually. A few features that I use were broken the last time I tried xfce. (Windows getting stuck under menubars, etc. And if I hid the menubar I had to log out&in to get it back.)
I could have gotten around this by only having the menubar at the bottom of the screen rather than both top and bottom as I prefer, or even not having full width menubars. But it was annoying. (OTOH, I'm not running on slow hardware either, so the advantage was less.)
This depends on the flavor of Mint you pick. Or at least it did the last time I tried it. There was a version based on Unbuntu, and another based directly on Debian. (Of course, Ubuntu is, itself, based on Debian...but it at least used to do lots of massaging for compatibility and adding drivers.)
Not denying that it's "pretty damn corrupt on it's own merits" as I don't have any unbiased evidence, but it's sheer size means that it *is* competitive. It doesn't just look competitive. When you count it as an entity (say for international travel) then it *is* competitive.
Common carrier is the wrong term, but why do they merit "safe harbor" status when they aggressively edit the posts? Probably they don't, but it's going to take a court case to decide that.
Isn't there another story about this currently on the Slashdot front page. Not directly about Twitter, but it sure sounds like it would be precedent. Perhaps not, though, as Twitter may not fall under the DMCA...but it's hard to see why it wouldn't.
Not all AI is generalized. In fact, so far no AI is generalized. So, no, it wouldn't be able to learn the concept of fairness unless that was built into it. Not yet.
OTOH, others have rightfully raised the question of just how fair the current system is. My version of the question is "What would be a precise definition of fairness in an economic trading system?". I have my doubts that anyone can give a defensible answer.
The whole point of the series was that: a) the English phrases that translated the math weren't exact, but the underlying math was, and b) even knowing the underlying math, you couldn't predict what would happen in a complex situation.
The statistical and neural network approaches to AI use crushing amounts of computation. Other approaches use less, but don't scale as well to more complicated problems.
Whatever your approach you will need a very good computer, but with the statistical or neural net approach you will be restricted to toy problems unless you invest heavily in a fancy multiprocessing computer system. Possibly several of them. And that gets expensive.
If you want to learn AI, read the literature, build the examples, and then decide what you want to do. You can learn neural nets with toy problems, but to do much more you're likely to need financial backing. Deep learning is the current "best approach", but it's not the first one, and it may not be the last one. Evolutionary programming in its various forms has a lot going for it.
Identify your purpose. Why do you want to learn AI? What do you hope to accomplish? Perhaps you should study linear algebra after all. Perhaps you should invent your own approach. Select a target problem, and figure out how it should be addressed. AI is a wide subject, and the currently most popular approach won't be the best approach for all problems.
I would posit that no intelligence can fully understand another intelligence of even close to its own capability. The model requires too much storage. Consider just "the magic number seven plus or minus two" for one limit on the complexity of the ideas we can understand. (This doesn't apply to ideas that can be broken down into independent pieces of lesser complexity, but not all ideas can.)
That said, I am a believer in an AI version of the Technological Singularity. I'm even hopeful that it might turn out well, though I wouldn't put even money on it on a bet. The thing is, I *really* doubt we will survive the century if it doesn't happen.
WRT the Laws of Thermodynamics, I think we're pretty clear that they work, we just don't really understand their domain coverage. They pretty clearly don't work in domains where gravity dominates over collisions, but that leaves a whole bunch of areas unspecified.
The problem is that to the extent we can understand the decision making process used by an AI, it doesn't seem to match that used by humans even when it comes to the same conclusion. (Except sometimes in simple cases.)
Probably the thinking process of an AI is totally non-human. Which shouldn't be that surprising.
Well, actually it is. The weights on the "synapses" evolve under feedback. It's not the style of programming normally called "evolutionary programming", but it still works by evolution.
Actually, most of his early robots were non-humanoid. It was only the later robots that were humanoid. Robie (I think that was the name) in Nursemaid ran on treads. Frequently the descriptions weren't precise enough to decide what the precise shape of the robot was.
That said, you are correct that he often designed the robots to facilitate reader identification, even though they were rarely (never?) the viewpoint characters.
It's an even worse problem than that. It's been shown that even an AI system that has superior object recognition (for some particular set of objects) to the average human will also recognize some things that to a human look like noise. They just aren't abstracting the same things to notice that we do. And the creators of they system can't explain what they're noticing.
Now "in principle" one could examine the reasoning step by step, but nobody lives that long. And small pieces examined separately don't help much. Also, a lot of what's going on depends on the relative timing of lots of concurrent processes, so a small piece *really* doesn't help.
Slashdot Mirror
I think here we have the correct reading.
The summary didn't say anything about Trump. You need to check your glasses prescription. Well...except that Trump accused Obama of spying on him, which *seems* to be unrelated to the article which only talks about foreign intelligence requests. Are you asserting that *that* means spying on Trump?
The deal might also be quite good for Apple, if they can find someone else to buy it off them (while guarantying them memory chips at a really good price).
I do agree that for Apple to hold onto the chip factory would be a diffusion of focus, and thus bad. Acting as a middle-man and taking cheap chips instead of a high purchase price, however, might be a real win. *IF* they can find someone really good to purchase/run the plant.
Actually, the main problem here is fraud, but it's true that the high investment costs of nuclear power plants are a huge contributing factor. But that's so blatant in this case that it hardly needs anyone pointing it out.
Donating to a political group is not a personal lifestyle choice.
If it is a part of your "lifestyle" to force your opinions on others who are unwilling, then it is quite reasonable for them to publicly object, and to encourage others to publicly object. Against you.
Another way to say this is "Your right to swing your fist ends a bit before the other person's nose.".
You're probably correct, but they'd have huge numbers of both false positives and false negatives, and they'd use whopping amounts of CPU time and RAM. Not a good answer.
xfce has it's points, but I *do* prefer KDE. Usually. A few features that I use were broken the last time I tried xfce. (Windows getting stuck under menubars, etc. And if I hid the menubar I had to log out&in to get it back.)
I could have gotten around this by only having the menubar at the bottom of the screen rather than both top and bottom as I prefer, or even not having full width menubars. But it was annoying. (OTOH, I'm not running on slow hardware either, so the advantage was less.)
This depends on the flavor of Mint you pick. Or at least it did the last time I tried it. There was a version based on Unbuntu, and another based directly on Debian. (Of course, Ubuntu is, itself, based on Debian...but it at least used to do lots of massaging for compatibility and adding drivers.)
Well, "in her 60's" is still time to worry about lead poisoning. She should wait until she's in her mid to late 70's.
Not denying that it's "pretty damn corrupt on it's own merits" as I don't have any unbiased evidence, but it's sheer size means that it *is* competitive. It doesn't just look competitive. When you count it as an entity (say for international travel) then it *is* competitive.
Common carrier is the wrong term, but why do they merit "safe harbor" status when they aggressively edit the posts? Probably they don't, but it's going to take a court case to decide that.
The problem with that is called "network effects". IIRC similar free programs exist, but not enough people use any of them for them to take off.
Isn't there another story about this currently on the Slashdot front page. Not directly about Twitter, but it sure sounds like it would be precedent. Perhaps not, though, as Twitter may not fall under the DMCA...but it's hard to see why it wouldn't.
Not all AI is generalized. In fact, so far no AI is generalized. So, no, it wouldn't be able to learn the concept of fairness unless that was built into it. Not yet.
OTOH, others have rightfully raised the question of just how fair the current system is. My version of the question is "What would be a precise definition of fairness in an economic trading system?". I have my doubts that anyone can give a defensible answer.
The whole point of the series was that:
a) the English phrases that translated the math weren't exact, but the underlying math was, and
b) even knowing the underlying math, you couldn't predict what would happen in a complex situation.
The statistical and neural network approaches to AI use crushing amounts of computation. Other approaches use less, but don't scale as well to more complicated problems.
Whatever your approach you will need a very good computer, but with the statistical or neural net approach you will be restricted to toy problems unless you invest heavily in a fancy multiprocessing computer system. Possibly several of them. And that gets expensive.
If you want to learn AI, read the literature, build the examples, and then decide what you want to do. You can learn neural nets with toy problems, but to do much more you're likely to need financial backing. Deep learning is the current "best approach", but it's not the first one, and it may not be the last one. Evolutionary programming in its various forms has a lot going for it.
Identify your purpose. Why do you want to learn AI? What do you hope to accomplish? Perhaps you should study linear algebra after all. Perhaps you should invent your own approach. Select a target problem, and figure out how it should be addressed. AI is a wide subject, and the currently most popular approach won't be the best approach for all problems.
I would posit that no intelligence can fully understand another intelligence of even close to its own capability. The model requires too much storage. Consider just "the magic number seven plus or minus two" for one limit on the complexity of the ideas we can understand. (This doesn't apply to ideas that can be broken down into independent pieces of lesser complexity, but not all ideas can.)
That said, I am a believer in an AI version of the Technological Singularity. I'm even hopeful that it might turn out well, though I wouldn't put even money on it on a bet. The thing is, I *really* doubt we will survive the century if it doesn't happen.
WRT the Laws of Thermodynamics, I think we're pretty clear that they work, we just don't really understand their domain coverage. They pretty clearly don't work in domains where gravity dominates over collisions, but that leaves a whole bunch of areas unspecified.
The problem is that to the extent we can understand the decision making process used by an AI, it doesn't seem to match that used by humans even when it comes to the same conclusion. (Except sometimes in simple cases.)
Probably the thinking process of an AI is totally non-human. Which shouldn't be that surprising.
Well, actually it is. The weights on the "synapses" evolve under feedback. It's not the style of programming normally called "evolutionary programming", but it still works by evolution.
Actually, most of his early robots were non-humanoid. It was only the later robots that were humanoid. Robie (I think that was the name) in Nursemaid ran on treads. Frequently the descriptions weren't precise enough to decide what the precise shape of the robot was.
That said, you are correct that he often designed the robots to facilitate reader identification, even though they were rarely (never?) the viewpoint characters.
It's an even worse problem than that. It's been shown that even an AI system that has superior object recognition (for some particular set of objects) to the average human will also recognize some things that to a human look like noise. They just aren't abstracting the same things to notice that we do. And the creators of they system can't explain what they're noticing.
Now "in principle" one could examine the reasoning step by step, but nobody lives that long. And small pieces examined separately don't help much. Also, a lot of what's going on depends on the relative timing of lots of concurrent processes, so a small piece *really* doesn't help.
re: Japanese Proverb: "The nail that sticks out the most gets hammered the most."
The way I heard it was:
The nail the protrudes will be struck down.
I think the translation I heard more clearly reveals the meaning. Think a feudal society.
You can't be serious. Java has many nice features. But Scala won't get you away from the JVM.
Is it stable yet, though? (It *has* been a while since I looked at it.)