Centuries may seem like a long time to you. Just like it did to people a few centuries ago, for whom "not until the 21st century" might as well have been "forever". But it's not really very long. Especially compared to this technology, which can store it stably for millions of years.
I think we're really just arguing about the definition of "intelligence". Of course, there's no "right" answer to questions like that, since all definitions are ultimately arbitrary. We can define a series of syllables to mean whatever we want. But some some definitions are clearly unreasonable, such as if they contradict themselves or conflict with the way everyone else in the world uses the word. So let me explain the requirements I think a reasonable definition of intelligence needs to meet.
Consider the statement, "Humans have intelligence." That's completely uncontroversial. Any neuroscientist would agree with it. So would any person on the street who knows nothing about neuroscience. It was equally uncontroversial 30 years ago when much less was known about the human brain, or 300 years ago when nothing was known about it.
Conclusion: any reasonable definition of intelligence cannot rely on technical knowledge of how the human brain works. It needs to let an average person with no specialized knowledge conclude that humans do, in fact, have intelligence.
It's easy to be misled by the fact that we do understand how computers work. It's tempting to say, "That's just a database lookup. That's just a brute force search through a tree. It isn't intelligence." But what if we eventually learn that the human brain works in essentially the same way? It would be embarrassing to have to admit that humans don't have intelligence after all! Actually, it doesn't matter whether that happens or not. If a definition allows any possibility that humans might be discovered not to have intelligence, then it clearly conflicts with how everyone else in the world uses the word.
So how should we define intelligence? I just did a web search for dictionary definitions, and here are some representative ones:
the ability to acquire and apply knowledge and skills
the ability to learn or understand or to deal with new or trying situations
the ability to apply knowledge to manipulate one's environment or to think abstractly as measured by objective criteria
capacity for learning, reasoning, understanding, and similar forms of mental activity; aptitude in grasping truths, relationships, facts, meanings, etc.
These don't all agree with each other, but there are a few central elements they all share. Clearly any definition of intelligence must involve the following features:
1. The ability to take in new information.
2. The ability to use that information to make decisions that are appropriate in a particular situation.
Does a chess playing computer take in new information and use it to make appropriate decisions? Certainly yes. What about a machine translation program? Yes again. So there are reasonable definitions of "intelligence" under which those programs do qualify. Of course, there are other possible definitions. We could require a higher level of adaptability: not just the ability to solve one specialized type of problem, but the ability to devise entirely new methods for solving entirely new types of problems. That would also be a reasonable definition, and those programs do not meet it.
So we're really talking about two different types of intelligence that involve two different definitions. Fortunately, the AI community has already provided us with two different terms to use for them: "weak AI" for the specialized, single purpose type of intelligence, and "strong AI" for the general purpose, human-like intelligence. They're very different from each other, but each of them meets at least one reasonable definition of "intelligence".
It sounds like you want to define intelligence entirely in terms of how you do something, not in terms of what you do. But that raises a difficult question: what techniques count as "intelligence"? And how do you decide that?
Consider playing chess. You say that computer chess programs are not intelligent because we understand how they work, and those are different from what a human does. But human chess playing is actually pretty easy to understand:
1. Inexperienced players work almost entirely by trying to predict the next few moves: "If I do this, what will my opponent do next?" They aren't very good at it, because they aren't very experienced.
2. Slightly more experienced players still do this, but they're better at it, and they also have added some heuristics to decide what is a good outcome, like, "I want to control the center of the board." They have memorized the standard point values attached to pieces, so they can better answer questions like, "Is trading a rook for two pawns a good idea?" And they have memorized some standard opening sequences that they can use without having to really think at all.
3. Expert players continue to do all of these things, but much better. They also have added a third approach: they have a fantastic memory for board configurations they have seen in the past, and can recognize at a glance that a particular arrangement of pieces is one they know, and that it leads to a win for black.
That is what humans do. And all of these techniques are ones that computer chess programs can also be programmed to use. You want to say that human chess players use some mysterious power called "intelligence" that is different from what computers do. But that just isn't true.
Likewise, you say that humans translate a text by "understanding" it, which you define with the Potter Stewart approach of, "We can't explain it, but we know it when we see it." But do we really know it when we see it? If we can't explain it, how can we be certain we actually are seeing it when we think we are? Neuroscience still has a long way to go in fully explaining what happens in your brain when you "understand" something, but based on what we know so far, it is entirely possible that human understanding is nothing more than symbol manipulation. Your brain contains lots of symbols (each stored as a pattern of neuron activation) that represent objects, concepts, etc. And you have learned relationships between those symbols, and rules for manipulating them. Exactly like a computer does.
Perhaps that isn't really how humans brains work, but based on our current knowledge, it's at least entirely possible. That also, of course, is exactly how computers work. So maybe human understanding is something fundamentally different from any current AI. But it's also entirely possible that it isn't. Until we can fully explain human understanding, we have to assume that anything that looks like understanding may actually be it.
And even if we determine that human understanding is fundamentally different from AI, that still leaves us with the question of how to define "intelligence". If two systems solve the same problem and reach the same result, what qualifies one as being "intelligent" and the other not? This is ultimately just about how to define a word. We may want to define it in a way that only includes humans and excludes everything else. But do we have any justification for that? Or is it just human prejudice, wanting to be able to claim that we are somehow special?
It's important to distinguish between weak and strong AI. When a human plays chess, we consider that to be an act of intelligence, even without having any idea what's going on in their brain. We therefore need to accept a computer that plays chess as also being intelligent. Ditto for translating a document from German to English, or figuring out the best route for driving to the airport. When a human does these things, we call it intelligence. Our judgement that they are "displaying intelligence" is not based on understanding how they did it. We therefore must accept a computer that does them as being intelligent too.
But this is weak AI. It can do the specific tasks it has been designed to do, and may do them extremely well. But it isn't general. If you give it a new task it wasn't designed to do, it can't analyze the task and figure out how to do it. That would be a strong AI, and that's what we haven't managed to create.
Except that many of these questions can be answered by pure data mining. Is Earth a planet? You'll find a high number of references to "Earth" and "planet" close together, so that suggests the answer is yes. Ditto with "Abraham Lincoln" and "President of the United States". In fact, you can do a trivial grammatical transformation to make the question into a statement ("Earth is a planet"), and you'll probably find many occurrences of that sentence on the web. Contrast that with the questions described in the article, which are carefully designed to make that sort of analysis useless.
That's a pretty big "hopefully". How confident are you it will never happen?
Let's put some numbers to this. All it takes is one full scale nuclear war to pretty thoroughly trash the planet. What do you think the odds are of having a full scale nuclear war in any given century? We've managed to escape having one so far, but it's only been 68 years since nuclear weapons were invented. Shall we be optimistic and put the probability at 10%? Then you should expect a nuclear war sometime in the next 1000 years. Want to be really really optimistic and say there's only a 1% chance of a full scale nuclear war in any century? Then you should expect one sometime in the next 10,000 years.
Spreading humanity beyond earth seems like a very good idea to me, if we want it to thrive long term. Earth is a great place for humans, but we have the engineering capability to create other places that are just as nice.
the first big change we had was Fire and the wheel... then we were stagnant for a very very long time.
Please don't just make things up like this. Check your facts. Otherwise you're spreading misinformation to people who assume you know what you're talking about.
The earliest controlled use of fire by pre-humans was about 400,000 years ago.
In between there were a few minor developments, like pottery (about 20,000 years ago), metalworking (about 11,000 years ago), etc.
You could have looked these things up just as easily as I can, if you cared to. Don't make things up. Don't spread misinformation. Check the facts, and then say what's true.
Because of course, no significant progress was made between 1013 and 1863. We didn't have any little things like the renaissance, the second agricultural revolution, the first industrial revolution, etc. There were no significant technological advances like the printing press, the spring-driven clock, the steam engine, or anything like that. Nor any scientific advances like classical mechanics, thermodynamics, and so on. Nope. Absolutely nothing.
What's amazing is how cheap this is. It's already within the range of what we (as a society) could easily afford if we really wanted to. It's less than the cost of the Iraq war. And remember, this study was based on 1975 technology! I'm sure that price could easily be brought down.
Also, there's a big difference between a one-off space colony and an ongoing model for space colonization. The first one is expensive because you have to develop the technology and create the infrastructure. But you can reuse all that for the next, and the one after.
It's funny. You think this is "ridiculous", while half the other people commenting on this story are saying, "Duh! Isn't that obvious?" I'm with them. If a drought causes the food supply in your area to collapse, how would that not lead to conflict?
Whether you think something is ridiculous is completely irrelevant. What matters is whether it's true. And that needs to be decided based on evidence, not your gut reaction about whether it's ridiculous.
Could you justify why you think it's a good rule of thumb? Saying that equations "break the flow of prose" is a purely subjective, aesthetic judgement. Many people would disagree. Saying they "don't work well in explaining things" is objectively false, at least when the thing you're trying to explain is intrinsically mathematical. Writing whole paragraphs of vague, confusing prose to imprecisely describe something that could have been precisely stated with a simple equation is a very bad way of explaining things.
I'm not suggesting equations should be used gratuitously when discussing non-mathematical subjects. But math is fundamental to a lot of things that get discussed all the time in the popular press: finance, economics, public opinion surveys, medical experiments, fuel efficiency, and so on.
This rule is circular. Why doesn't the general public understand equations? Because equations never come up in anything they read. Why don't equations come up in anything they read? Because editors think their audience won't understand them.
The solution is to educate their audience. I don't mean sending everyone off to more years of math classes. I mean just including very simple equations now and then in their articles and explaining what they mean. That's a journalist's job: to educate their readers about things it's important for them to know.
If someone can't understand "a=F/m" (or "acceleration=force/mass"), do you really think they have any idea what "acceleration is inversely proportional to mass" means?
If equations (even very simple ones) were more common in the popular press, then people wouldn't be so afraid of them, and editors wouldn't feel the need to remove all equations even from books on very mathematical subjects.
Was the alley really pitch black? Or did it just seem dark in contrast to the brightly lit areas on either side? I bet it was the latter. Almost nothing is ever truly dark in a city, there's so much ambient light.
Bright outdoor lights often make things less safe, not more. They destroy your night vision, create deep shadows, and make it impossible to see anything that isn't brightly lit. Dim uniform light is much safer than brightly lit areas alternating with unlit ones.
The whole concept of "intellectual property" is dishonest and misleading. It takes several fundamentally different and unrelated things -- patents, copyrights, trademarks, service marks, trade secrets -- and tries to portray them as all being the same thing. And each of those categories contains many unrelated things. Patents can cover physical objects, processes, computer algorithms, business methods, non-functional design features, etc. Copyrights can cover written works, images, sound recordings, musical scores, movies, software, etc. By calling all of these things "intellectual property", you imply that they're all the same thing, and if you support any one of them, you need to support all of them. But they're not the same thing. They're very different, and there's no reason they need to all be treated the same way.
True, and this is even more true on GPUs than CPUs. They do a lot less to shield you from the low level details of how your code gets executed, so those details end up having a bigger impact on your performance. And to make it worse, those details change with every new hardware generation!
But for a new user just getting into GPU programming, it's easier to learn those things in the context of a simple programming model like OpenACC than a complicated one like CUDA or OpenCL. That just forces them to deal with even more complexity and hardware details right from the very start. OpenACC can produce good results if used well. And once you've learned to do that, you're in a better position to tackle the harder technologies.
OpenACC is what you're looking for. It uses a directive based programming model similar to OpenMP, so you write ordinary looking code, then annotate it in ways that tell the compiler how to transform it into GPU code.
You won't get as good performance as well written CUDA or OpenCL code, but it's much easier to learn. And once you get comfortable with it, you may find it easier to make the step from there into lower level programming.
The parent post is much closer to my own experiences than the grandparent post. Programmers definitely count as research staff, and a Ph.D. is not required to get those positions, although it certainly does help. And although you will probably never be a PI, you can still have a lot of freedom and influence in terms of what you work on and how you pursue it.
Academia is very different from the corporate world. For one thing, the management structure is very flat. Research staff report to professors, and professors don't really report to anyone except their funding agencies. Unless you want to go into university administration, there is no ladder to move up. A staff job doesn't lead to anything except other staff jobs. (Once you have enough publications you could try to become a professor, but a Ph.D. is essential for that.) A professorship doesn't lead to anything except other professorships.
The real hierarchy in academia is based on reputation in your field. As you get more publications and your work becomes known, you'll start getting invitations to speak at conferences, people start wanting to collaborate with you, etc. And that is totally possible for staff as well as professors.
Does anyone else find this story very suspicious? I mean, VPN services are completely mainstream, widely used by business people. I bet that even MasterCard and Visa use them. And suddenly we're told there's a conspiracy to ban them. And the poster attributes this to the NSA wanting to spy on us. All based on completely anecdotal reports from one company that you've probably never heard of before.
I suspect the summary will turn out to be a complete misrepresentation, and the truth will be something far less evil and far less interesting than this post makes it out to be.
For all practical purposes, San Francisco is part of Silicon Valley. Sure, originally it meant a small cluster of towns in Santa Clara county, but today Silicon Valley really includes everything surrounding the southern arm of San Francisco Bay. There are lots of people who live in San Francisco and work in Palo Alto. You just can't divide it up any more.
Actually, they're currently working to incorporate Simbody, a simulation engine designed for engineering applications. That should provide much better realism.
What you are describing is the Copenhagen interpretation of quantum mechanics, which is not universally accepted, and in fact has been steadily decreasing in popularity for decades. At one point it was accepted as the "conventional wisdom", mainly because there wasn't any better alternative, but that was a very long time ago. Today we have lots of better alternatives, and at least among people who actively study interpretations of quantum mechanics, it is not widely believed anymore.
No. Tunneling is caused by the leakage of the wavefunction through a barrier, which is a gradual, continuous process. Some interpretations of quantum mechanics claim that the collapse of the wavefunction (the point where it goes from being partly on each side of the barrier to being entirely on one side) is instantaneous. But that's very controversial, and many other interpretations disagree. But tunneling itself - the uncontroversial, well established phenomenon - is very definitely continuous and non-instantaneous.
Slashdot Mirror
Centuries may seem like a long time to you. Just like it did to people a few centuries ago, for whom "not until the 21st century" might as well have been "forever". But it's not really very long. Especially compared to this technology, which can store it stably for millions of years.
I think we're really just arguing about the definition of "intelligence". Of course, there's no "right" answer to questions like that, since all definitions are ultimately arbitrary. We can define a series of syllables to mean whatever we want. But some some definitions are clearly unreasonable, such as if they contradict themselves or conflict with the way everyone else in the world uses the word. So let me explain the requirements I think a reasonable definition of intelligence needs to meet.
Consider the statement, "Humans have intelligence." That's completely uncontroversial. Any neuroscientist would agree with it. So would any person on the street who knows nothing about neuroscience. It was equally uncontroversial 30 years ago when much less was known about the human brain, or 300 years ago when nothing was known about it.
Conclusion: any reasonable definition of intelligence cannot rely on technical knowledge of how the human brain works. It needs to let an average person with no specialized knowledge conclude that humans do, in fact, have intelligence.
It's easy to be misled by the fact that we do understand how computers work. It's tempting to say, "That's just a database lookup. That's just a brute force search through a tree. It isn't intelligence." But what if we eventually learn that the human brain works in essentially the same way? It would be embarrassing to have to admit that humans don't have intelligence after all! Actually, it doesn't matter whether that happens or not. If a definition allows any possibility that humans might be discovered not to have intelligence, then it clearly conflicts with how everyone else in the world uses the word.
So how should we define intelligence? I just did a web search for dictionary definitions, and here are some representative ones:
the ability to acquire and apply knowledge and skills
the ability to learn or understand or to deal with new or trying situations
the ability to apply knowledge to manipulate one's environment or to think abstractly as measured by objective criteria
capacity for learning, reasoning, understanding, and similar forms of mental activity; aptitude in grasping truths, relationships, facts, meanings, etc.
These don't all agree with each other, but there are a few central elements they all share. Clearly any definition of intelligence must involve the following features:
1. The ability to take in new information.
2. The ability to use that information to make decisions that are appropriate in a particular situation.
Does a chess playing computer take in new information and use it to make appropriate decisions? Certainly yes. What about a machine translation program? Yes again. So there are reasonable definitions of "intelligence" under which those programs do qualify. Of course, there are other possible definitions. We could require a higher level of adaptability: not just the ability to solve one specialized type of problem, but the ability to devise entirely new methods for solving entirely new types of problems. That would also be a reasonable definition, and those programs do not meet it.
So we're really talking about two different types of intelligence that involve two different definitions. Fortunately, the AI community has already provided us with two different terms to use for them: "weak AI" for the specialized, single purpose type of intelligence, and "strong AI" for the general purpose, human-like intelligence. They're very different from each other, but each of them meets at least one reasonable definition of "intelligence".
It sounds like you want to define intelligence entirely in terms of how you do something, not in terms of what you do. But that raises a difficult question: what techniques count as "intelligence"? And how do you decide that?
Consider playing chess. You say that computer chess programs are not intelligent because we understand how they work, and those are different from what a human does. But human chess playing is actually pretty easy to understand:
1. Inexperienced players work almost entirely by trying to predict the next few moves: "If I do this, what will my opponent do next?" They aren't very good at it, because they aren't very experienced.
2. Slightly more experienced players still do this, but they're better at it, and they also have added some heuristics to decide what is a good outcome, like, "I want to control the center of the board." They have memorized the standard point values attached to pieces, so they can better answer questions like, "Is trading a rook for two pawns a good idea?" And they have memorized some standard opening sequences that they can use without having to really think at all.
3. Expert players continue to do all of these things, but much better. They also have added a third approach: they have a fantastic memory for board configurations they have seen in the past, and can recognize at a glance that a particular arrangement of pieces is one they know, and that it leads to a win for black.
That is what humans do. And all of these techniques are ones that computer chess programs can also be programmed to use. You want to say that human chess players use some mysterious power called "intelligence" that is different from what computers do. But that just isn't true.
Likewise, you say that humans translate a text by "understanding" it, which you define with the Potter Stewart approach of, "We can't explain it, but we know it when we see it." But do we really know it when we see it? If we can't explain it, how can we be certain we actually are seeing it when we think we are? Neuroscience still has a long way to go in fully explaining what happens in your brain when you "understand" something, but based on what we know so far, it is entirely possible that human understanding is nothing more than symbol manipulation. Your brain contains lots of symbols (each stored as a pattern of neuron activation) that represent objects, concepts, etc. And you have learned relationships between those symbols, and rules for manipulating them. Exactly like a computer does.
Perhaps that isn't really how humans brains work, but based on our current knowledge, it's at least entirely possible. That also, of course, is exactly how computers work. So maybe human understanding is something fundamentally different from any current AI. But it's also entirely possible that it isn't. Until we can fully explain human understanding, we have to assume that anything that looks like understanding may actually be it.
And even if we determine that human understanding is fundamentally different from AI, that still leaves us with the question of how to define "intelligence". If two systems solve the same problem and reach the same result, what qualifies one as being "intelligent" and the other not? This is ultimately just about how to define a word. We may want to define it in a way that only includes humans and excludes everything else. But do we have any justification for that? Or is it just human prejudice, wanting to be able to claim that we are somehow special?
It's important to distinguish between weak and strong AI. When a human plays chess, we consider that to be an act of intelligence, even without having any idea what's going on in their brain. We therefore need to accept a computer that plays chess as also being intelligent. Ditto for translating a document from German to English, or figuring out the best route for driving to the airport. When a human does these things, we call it intelligence. Our judgement that they are "displaying intelligence" is not based on understanding how they did it. We therefore must accept a computer that does them as being intelligent too.
But this is weak AI. It can do the specific tasks it has been designed to do, and may do them extremely well. But it isn't general. If you give it a new task it wasn't designed to do, it can't analyze the task and figure out how to do it. That would be a strong AI, and that's what we haven't managed to create.
Except that many of these questions can be answered by pure data mining. Is Earth a planet? You'll find a high number of references to "Earth" and "planet" close together, so that suggests the answer is yes. Ditto with "Abraham Lincoln" and "President of the United States". In fact, you can do a trivial grammatical transformation to make the question into a statement ("Earth is a planet"), and you'll probably find many occurrences of that sentence on the web. Contrast that with the questions described in the article, which are carefully designed to make that sort of analysis useless.
Hopefully we will never destroy our planet.
That's a pretty big "hopefully". How confident are you it will never happen?
Let's put some numbers to this. All it takes is one full scale nuclear war to pretty thoroughly trash the planet. What do you think the odds are of having a full scale nuclear war in any given century? We've managed to escape having one so far, but it's only been 68 years since nuclear weapons were invented. Shall we be optimistic and put the probability at 10%? Then you should expect a nuclear war sometime in the next 1000 years. Want to be really really optimistic and say there's only a 1% chance of a full scale nuclear war in any century? Then you should expect one sometime in the next 10,000 years.
Spreading humanity beyond earth seems like a very good idea to me, if we want it to thrive long term. Earth is a great place for humans, but we have the engineering capability to create other places that are just as nice.
the first big change we had was Fire and the wheel... then we were stagnant for a very very long time.
Please don't just make things up like this. Check your facts. Otherwise you're spreading misinformation to people who assume you know what you're talking about.
The earliest controlled use of fire by pre-humans was about 400,000 years ago.
The earliest known wheel is from about 5000 years ago.
In between there were a few minor developments, like pottery (about 20,000 years ago), metalworking (about 11,000 years ago), etc.
You could have looked these things up just as easily as I can, if you cared to. Don't make things up. Don't spread misinformation. Check the facts, and then say what's true.
Because of course, no significant progress was made between 1013 and 1863. We didn't have any little things like the renaissance, the second agricultural revolution, the first industrial revolution, etc. There were no significant technological advances like the printing press, the spring-driven clock, the steam engine, or anything like that. Nor any scientific advances like classical mechanics, thermodynamics, and so on. Nope. Absolutely nothing.
What's amazing is how cheap this is. It's already within the range of what we (as a society) could easily afford if we really wanted to. It's less than the cost of the Iraq war. And remember, this study was based on 1975 technology! I'm sure that price could easily be brought down.
Also, there's a big difference between a one-off space colony and an ongoing model for space colonization. The first one is expensive because you have to develop the technology and create the infrastructure. But you can reuse all that for the next, and the one after.
It's funny. You think this is "ridiculous", while half the other people commenting on this story are saying, "Duh! Isn't that obvious?" I'm with them. If a drought causes the food supply in your area to collapse, how would that not lead to conflict?
Whether you think something is ridiculous is completely irrelevant. What matters is whether it's true. And that needs to be decided based on evidence, not your gut reaction about whether it's ridiculous.
Could you justify why you think it's a good rule of thumb? Saying that equations "break the flow of prose" is a purely subjective, aesthetic judgement. Many people would disagree. Saying they "don't work well in explaining things" is objectively false, at least when the thing you're trying to explain is intrinsically mathematical. Writing whole paragraphs of vague, confusing prose to imprecisely describe something that could have been precisely stated with a simple equation is a very bad way of explaining things.
I'm not suggesting equations should be used gratuitously when discussing non-mathematical subjects. But math is fundamental to a lot of things that get discussed all the time in the popular press: finance, economics, public opinion surveys, medical experiments, fuel efficiency, and so on.
This rule is circular. Why doesn't the general public understand equations? Because equations never come up in anything they read. Why don't equations come up in anything they read? Because editors think their audience won't understand them.
The solution is to educate their audience. I don't mean sending everyone off to more years of math classes. I mean just including very simple equations now and then in their articles and explaining what they mean. That's a journalist's job: to educate their readers about things it's important for them to know.
If someone can't understand "a=F/m" (or "acceleration=force/mass"), do you really think they have any idea what "acceleration is inversely proportional to mass" means?
If equations (even very simple ones) were more common in the popular press, then people wouldn't be so afraid of them, and editors wouldn't feel the need to remove all equations even from books on very mathematical subjects.
Was the alley really pitch black? Or did it just seem dark in contrast to the brightly lit areas on either side? I bet it was the latter. Almost nothing is ever truly dark in a city, there's so much ambient light.
Bright outdoor lights often make things less safe, not more. They destroy your night vision, create deep shadows, and make it impossible to see anything that isn't brightly lit. Dim uniform light is much safer than brightly lit areas alternating with unlit ones.
The whole concept of "intellectual property" is dishonest and misleading. It takes several fundamentally different and unrelated things -- patents, copyrights, trademarks, service marks, trade secrets -- and tries to portray them as all being the same thing. And each of those categories contains many unrelated things. Patents can cover physical objects, processes, computer algorithms, business methods, non-functional design features, etc. Copyrights can cover written works, images, sound recordings, musical scores, movies, software, etc. By calling all of these things "intellectual property", you imply that they're all the same thing, and if you support any one of them, you need to support all of them. But they're not the same thing. They're very different, and there's no reason they need to all be treated the same way.
True, and this is even more true on GPUs than CPUs. They do a lot less to shield you from the low level details of how your code gets executed, so those details end up having a bigger impact on your performance. And to make it worse, those details change with every new hardware generation!
But for a new user just getting into GPU programming, it's easier to learn those things in the context of a simple programming model like OpenACC than a complicated one like CUDA or OpenCL. That just forces them to deal with even more complexity and hardware details right from the very start. OpenACC can produce good results if used well. And once you've learned to do that, you're in a better position to tackle the harder technologies.
OpenACC is what you're looking for. It uses a directive based programming model similar to OpenMP, so you write ordinary looking code, then annotate it in ways that tell the compiler how to transform it into GPU code.
You won't get as good performance as well written CUDA or OpenCL code, but it's much easier to learn. And once you get comfortable with it, you may find it easier to make the step from there into lower level programming.
The parent post is much closer to my own experiences than the grandparent post. Programmers definitely count as research staff, and a Ph.D. is not required to get those positions, although it certainly does help. And although you will probably never be a PI, you can still have a lot of freedom and influence in terms of what you work on and how you pursue it.
Academia is very different from the corporate world. For one thing, the management structure is very flat. Research staff report to professors, and professors don't really report to anyone except their funding agencies. Unless you want to go into university administration, there is no ladder to move up. A staff job doesn't lead to anything except other staff jobs. (Once you have enough publications you could try to become a professor, but a Ph.D. is essential for that.) A professorship doesn't lead to anything except other professorships.
The real hierarchy in academia is based on reputation in your field. As you get more publications and your work becomes known, you'll start getting invitations to speak at conferences, people start wanting to collaborate with you, etc. And that is totally possible for staff as well as professors.
Does anyone else find this story very suspicious? I mean, VPN services are completely mainstream, widely used by business people. I bet that even MasterCard and Visa use them. And suddenly we're told there's a conspiracy to ban them. And the poster attributes this to the NSA wanting to spy on us. All based on completely anecdotal reports from one company that you've probably never heard of before.
I suspect the summary will turn out to be a complete misrepresentation, and the truth will be something far less evil and far less interesting than this post makes it out to be.
It wasn't even true three decades ago. It was just a piece of FUD used by the oil lobby to scare people away from solar.
For all practical purposes, San Francisco is part of Silicon Valley. Sure, originally it meant a small cluster of towns in Santa Clara county, but today Silicon Valley really includes everything surrounding the southern arm of San Francisco Bay. There are lots of people who live in San Francisco and work in Palo Alto. You just can't divide it up any more.
Actually, they're currently working to incorporate Simbody, a simulation engine designed for engineering applications. That should provide much better realism.
What you are describing is the Copenhagen interpretation of quantum mechanics, which is not universally accepted, and in fact has been steadily decreasing in popularity for decades. At one point it was accepted as the "conventional wisdom", mainly because there wasn't any better alternative, but that was a very long time ago. Today we have lots of better alternatives, and at least among people who actively study interpretations of quantum mechanics, it is not widely believed anymore.
Tunneling is instantaneous.
No. Tunneling is caused by the leakage of the wavefunction through a barrier, which is a gradual, continuous process. Some interpretations of quantum mechanics claim that the collapse of the wavefunction (the point where it goes from being partly on each side of the barrier to being entirely on one side) is instantaneous. But that's very controversial, and many other interpretations disagree. But tunneling itself - the uncontroversial, well established phenomenon - is very definitely continuous and non-instantaneous.