Geoffrey Hinton’s work in back propagation and deep learning are an incremental improvement over the overly simplistic neural networks of the 90s, but "real progress", not even close. His focus on Bayesian networks has failed to deliver just like the symbolic AI that preceded it
Your arguments are not based on facts. The truth is that Kurzweil likes Hawkins' approach and Hawkins' Hierarchical Temporal Memory is a Bayesian network. It was designed from the ground up to use Bayesian statistics for perceptual learning. I am not saying that Hawkins' work is worthless but that it is seriously handicapped by the Bayesian curse.
Lately Kurzweil has come around to see that symbolic and bayesian networks have been holding AI back for the past 50 years. He is now a proponent of using biologically inspired methods similar to Jeff Hawkins' approach of Hierarchical Temporal Memory.
I don't get this. Hawkins' Hierarchical Temporal Memory is a Bayesian network. Dileep George, the mathematician and Bayes fanatic who co-founded Numenta, made sure of that. The last I heard, the Bayesian Brain hypothesis is something that both Hawkins and Kurzweil believe to be the correct approach to AI. They are wrong because, as Turing Award winner Judea Pearl explained, people and animals are not probability thinkers but cause/effect thinkers. And this is coming from a man who spent an enormous amount of time and effort championing the Bayesian approach to AI.
Competent AI researchers at least notice that they do not have a clue how to model what they want to build, and as such have a change of success.
Oh, they have a clue alright. They are convinced that the brain uses Bayesian statistics for perceptual learning. They are wrong.
You have it all figured out (wrongly) and have none.
Nope. Why do you put words in my mouth in such a dishonest way? You got a pony in this race? I've only figured out a small part of it but I've been at it for a long time and, lately, I'm making progress by leaps and bounds. Keeps your ears and eyes open.
The problem with people like Kurzweil, Jeff Hawkins, the folks at the Singularity Institute and the rest of the AI community is that they have all jumped on the Bayesian bandwagon. This is not unlike the way they all jumped on the symbolic bandwagon in the last century only to be proven wrong forty years later. Do we have another half a century to waste, waiting for these guys to realize the error of their ways? Essentially there are two approaches to machine learning.
1) The Bayesian model assumes that events in the world are inherently uncertain and that the job of an intelligent system is to discover the probabilities. 2) The competing model, by contrast, assumes that events in the world are perfectly consistent and that the job of an intelligent system is to discover this perfection.
Luckily for the rest of humanity, a few people are beginning to realize the folly of the Bayesian mindset. When asked in a recent Cambridge Press interview, "What was the greatest challenge you have encountered in your research?", Judea Pearl, an Israeli computer scientist and an early champion of the Bayesian approach to AI, replied: "In retrospect, my greatest challenge was to break away from probabilistic thinking and accept, first, that people are not probability thinkers but cause-effect thinkers and, second, that causal thinking cannot be captured in the language of probability; it requires a formal language of its own."
...they are underground chambers prepared by the alien overlords who have been watching us for millions of years. They'll be making their move on December 21, 2012 to mark the end of an era predicted by Mayan astronomers. Right before the end of the world, the aliens will scoop up their followers in a big rapture. They will hide them and feed them in the underground chambers of the moon away from the chaos on earth. Then the big Yahweh chief of all aliens will make his apparition, as written. He, he.
The US is just as corrupt as those so-called third-world countries. I've had some rather unpleasant experiences with a couple of blatantly corrupt court commissioners at the Los Angeles Superior Court, a cesspool of corruption and malpractice. The shit that goes on at the LASC would make Saddam Hussein blush. I swear.
Amazingly (I knew this poster "smelled" like rebel science), you aren't completely wrong here.
Sorry, wrong. I am 100% right on this issue. All the Bayesian bandwagoneers are out to lunch. The brain does not build a probabilistic model of the world. It builds a perfect deterministic model. Wait for the demo.
Do you have *actual* arguments comparing Bayesian to these hypothetical alternatives
The argument is simple. As Judea Pearl (an early proponent of Bayesian statistics for AI who has since changed his mind) explained, humans are not probability thinkers; they are cause/effect thinkers. If you drop a ball, you know it's going to hit the ground. You don't think that there is a probability that it might not. If you read the word Bayesian in this sentence, you know for certain that you did. There is nothing probabilistic about it. Sure we handle probabilistic sensory signals but we build a perfect model of the world in our cortical memories. We simply compare incoming sensory inputs to our perfect internal model and decide which patterns in memory best fit the sensory evidence. This truth will be forcefully demonstrated in the not distant future. Wait for it.
The Bayesian brain is a myth, a rather dumb one in retrospect.
They haven't done anything that wasn't already being done by others. They're just doing more of it. Essentially, the approach consist of using Bayesian statistics and a hierarchy of patterns. Prof. Hinton pretty much pioneered the use of Bayesian statistics in artificial intelligence. With a rare notable exception (e.g. Judea Pearl), the entire AI community has jumped on the Bayesian bandwagon, not unlike the way they jumped on the symbolic bandwagon in the latter half the 20th century, only to be proven wrong fifty years later.
The Bayesian model essentially assumes that the world is inherently probabilistic and that the job of an intelligent system is to discover the probabilities. A competing model (see links below), by contrast, assumes that the world is perfectly consistent and that the job of an intelligent system is to capture this perfection.
Funny but, in the end, it comes down to this: There should be no such things as top level domains or URLs. It was a flawed idea to begin with. Just use a nondescript ID and voila. Problem solved. How web sites are organized and delivered to us should be left to the market, to the Googles and Microsofts of the world or anybody who can come up with good browsing and navigation system. Personally, I want everything to fit within a hierarchical tree and I want a 3-D browser for navigation.
That's an amazingly complicated task. If the robot can be taught to do that, that's a pretty advanced robot. I wonder how anybody can teach a robot to fold a t-shirt unless you have a load of constraints on movements. In which case, you'd be better off folding your own t-shirt.
I don't think the suddenists have flint spearheads in mind when they speak of something wonderful happening some 50,000 years ago. They're more than likely thinking of the kind of sudden explosion of knowledge that gives rise to horse-driven chariots and temple building civilizations. But I could be wrong.
No OS can be exploit proof if is an algorithmic system, i.e., a Turing machine. Why? Because time is not an inherent part of the Turing computing model. The most important part of a secure software system is timing. No system can be reliable and safe unless it provides a deterministic way to impose which operations should occurr concurrently and which should occur sequentially.
Kaspersky's OS will fail miserably unless he reinvents the computer such that the timing of operations is deterministic. With a deterministic system, it's easy to detect intruders and malfunctions because every intruder and bug will invariably mess up the expected timing and trigger alarms created automatically for that purpose.
So, it doesn't solve the problem of patent trolls at all, it just changes who feeds the patent trolls (in your system, it would be whoever gives money to the independent fund, i.e., everyone).
No. It removes the power of the troll to prevent others from using the invention and force them out of the market. So it prevents them from forming monopolies which have no place in a free market. The troll needs to prove that a lot of work and research went into the invention. For example, Jeff Bezos would get diddly squat for his 1-click invention and Bill Gates could never have built a multi-billion dollar empire on a piece of crap like MS-DOS.
The current patent system is harmful to society because it tramples on freedom and gives unfair powers to patent holders. The purpose of patents is to provide an incentive for innovation and compensate inventors for their hard work. However, it should not infringe on the freedom of others. That would be counter to its purpose. Above all, the system must never serve as a carte blanche for a few to bully others out of the market. What we need is something like this:
1. A special independent fund must be set aside to compensate inventors for their inventions and reward innovation. 2. A retroactive formula must be adopted to calculate the amount of the compensation. 3. The formula must be adjustable so as to establish the best return for society at large in terms of innovations. 4. Last but not least, whatever the formula chosen, it must never infringe on the right of the individual to copy and use any invention for any ethical purpose.
Inventors should register and publish their findings as soon as they can because their compensation will depend on how much society like and use their ideas. Of course, we still need a Patent bureau and a system to manage claims and the proper registrations of inventions. The system should be able to determine the usefulness and popularity of an invention and how much work went into researching and creating the invention. It should also be as automated as possible.
AMD is so focused on competing against Intel that they missed the smart phone and tablet revolution. Few manufacturers need or want their heterogeneous processors. They had their chance and they blew it. It's sad, really.
A finger just won't do it. Fingers are fat. Not like a mouse pointer.
That may be true for current touch screens. But new interface technologies are going to change all that. Soon, you'll be able to use hand and/or finger gestures to control a sharp point on the screen. And that's just the tip of the iceberg. One can think of various other virtual objects and tools that can manipulated with gestures. Computer programming, for example, will one day be done by just anybody, i.e., with the use of simple gestures to build beautiful 3-D structures from a collection of available components. Just dreaming. Nothing wrong with that.
Of course, you will need something bigger and more powerful than a tablet/phone for this sort of thing.
Popper understood relativity better than Einstein. He understood why nothing could move in spacetime. Einstein apparently never realized this. Or if he did, he kept quiet about it. Otherwise, most people would have figured out that there is no such thing as bodies moving along their geodesics in spacetime. Just saying. Take it or leave it.
Slashdot Mirror
Geoffrey Hinton’s work in back propagation and deep learning are an incremental improvement over the overly simplistic neural networks of the 90s, but "real progress", not even close. His focus on Bayesian networks has failed to deliver just like the symbolic AI that preceded it
Your arguments are not based on facts. The truth is that Kurzweil likes Hawkins' approach and Hawkins' Hierarchical Temporal Memory is a Bayesian network. It was designed from the ground up to use Bayesian statistics for perceptual learning. I am not saying that Hawkins' work is worthless but that it is seriously handicapped by the Bayesian curse.
Lately Kurzweil has come around to see that symbolic and bayesian networks have been holding AI back for the past 50 years. He is now a proponent of using biologically inspired methods similar to Jeff Hawkins' approach of Hierarchical Temporal Memory.
I don't get this. Hawkins' Hierarchical Temporal Memory is a Bayesian network. Dileep George, the mathematician and Bayes fanatic who co-founded Numenta, made sure of that. The last I heard, the Bayesian Brain hypothesis is something that both Hawkins and Kurzweil believe to be the correct approach to AI. They are wrong because, as Turing Award winner Judea Pearl explained, people and animals are not probability thinkers but cause/effect thinkers. And this is coming from a man who spent an enormous amount of time and effort championing the Bayesian approach to AI.
Nope. It was printed by Steve Jobs' secret giant 3-D minimalist aluminum/glass printer. Even the imacs were printed.
LOL. You guys are funny.
Competent AI researchers at least notice that they do not have a clue how to model what they want to build, and as such have a change of success.
Oh, they have a clue alright. They are convinced that the brain uses Bayesian statistics for perceptual learning. They are wrong.
You have it all figured out (wrongly) and have none.
Nope. Why do you put words in my mouth in such a dishonest way? You got a pony in this race? I've only figured out a small part of it but I've been at it for a long time and, lately, I'm making progress by leaps and bounds. Keeps your ears and eyes open.
The problem with people like Kurzweil, Jeff Hawkins, the folks at the Singularity Institute and the rest of the AI community is that they have all jumped on the Bayesian bandwagon. This is not unlike the way they all jumped on the symbolic bandwagon in the last century only to be proven wrong forty years later. Do we have another half a century to waste, waiting for these guys to realize the error of their ways? Essentially there are two approaches to machine learning.
1) The Bayesian model assumes that events in the world are inherently uncertain and that the job of an intelligent system is to discover the probabilities.
2) The competing model, by contrast, assumes that events in the world are perfectly consistent and that the job of an intelligent system is to discover this perfection.
Luckily for the rest of humanity, a few people are beginning to realize the folly of the Bayesian mindset. When asked in a recent Cambridge Press interview, "What was the greatest challenge you have encountered in your research?", Judea Pearl, an Israeli computer scientist and an early champion of the Bayesian approach to AI, replied: "In retrospect, my greatest challenge was to break away from probabilistic thinking and accept, first, that people are not probability thinkers but cause-effect thinkers and, second, that causal thinking cannot be captured in the language of probability; it requires a formal language of its own."
Read The Myth of the Bayesian Brain for more, if you're interested.
No. It's a monument to evolution because evolution designs everything even though it's not trying to design anything.
...they are underground chambers prepared by the alien overlords who have been watching us for millions of years. They'll be making their move on December 21, 2012 to mark the end of an era predicted by Mayan astronomers. Right before the end of the world, the aliens will scoop up their followers in a big rapture. They will hide them and feed them in the underground chambers of the moon away from the chaos on earth. Then the big Yahweh chief of all aliens will make his apparition, as written. He, he.
The US is just as corrupt as those so-called third-world countries. I've had some rather unpleasant experiences with a couple of blatantly corrupt court commissioners at the Los Angeles Superior Court, a cesspool of corruption and malpractice. The shit that goes on at the LASC would make Saddam Hussein blush. I swear.
Amazingly (I knew this poster "smelled" like rebel science), you aren't completely wrong here.
Sorry, wrong. I am 100% right on this issue. All the Bayesian bandwagoneers are out to lunch. The brain does not build a probabilistic model of the world. It builds a perfect deterministic model. Wait for the demo.
Do you have *actual* arguments comparing Bayesian to these hypothetical alternatives
The argument is simple. As Judea Pearl (an early proponent of Bayesian statistics for AI who has since changed his mind) explained, humans are not probability thinkers; they are cause/effect thinkers. If you drop a ball, you know it's going to hit the ground. You don't think that there is a probability that it might not. If you read the word Bayesian in this sentence, you know for certain that you did. There is nothing probabilistic about it. Sure we handle probabilistic sensory signals but we build a perfect model of the world in our cortical memories. We simply compare incoming sensory inputs to our perfect internal model and decide which patterns in memory best fit the sensory evidence. This truth will be forcefully demonstrated in the not distant future. Wait for it.
The Bayesian brain is a myth, a rather dumb one in retrospect.
They haven't done anything that wasn't already being done by others. They're just doing more of it. Essentially, the approach consist of using Bayesian statistics and a hierarchy of patterns. Prof. Hinton pretty much pioneered the use of Bayesian statistics in artificial intelligence. With a rare notable exception (e.g. Judea Pearl), the entire AI community has jumped on the Bayesian bandwagon, not unlike the way they jumped on the symbolic bandwagon in the latter half the 20th century, only to be proven wrong fifty years later.
The Bayesian model essentially assumes that the world is inherently probabilistic and that the job of an intelligent system is to discover the probabilities. A competing model (see links below), by contrast, assumes that the world is perfectly consistent and that the job of an intelligent system is to capture this perfection.
See The Myth of the Bayesian Brain and The Second Great AI Red Herring Chase if you're interested in an alternative approach to AI.
Funny but, in the end, it comes down to this: There should be no such things as top level domains or URLs. It was a flawed idea to begin with. Just use a nondescript ID and voila. Problem solved. How web sites are organized and delivered to us should be left to the market, to the Googles and Microsofts of the world or anybody who can come up with good browsing and navigation system. Personally, I want everything to fit within a hierarchical tree and I want a 3-D browser for navigation.
We should go back to using cruise missiles and carpet bombing.
Why stop there? We should go back to sticks, stones, poisons, bows and arrows. That was more humane, right?
Louis
That's an amazingly complicated task. If the robot can be taught to do that, that's a pretty advanced robot. I wonder how anybody can teach a robot to fold a t-shirt unless you have a load of constraints on movements. In which case, you'd be better off folding your own t-shirt.
I don't think the suddenists have flint spearheads in mind when they speak of something wonderful happening some 50,000 years ago. They're more than likely thinking of the kind of sudden explosion of knowledge that gives rise to horse-driven chariots and temple building civilizations. But I could be wrong.
exploit-proof OS
No OS can be exploit proof if is an algorithmic system, i.e., a Turing machine. Why? Because time is not an inherent part of the Turing computing model. The most important part of a secure software system is timing. No system can be reliable and safe unless it provides a deterministic way to impose which operations should occurr concurrently and which should occur sequentially.
Kaspersky's OS will fail miserably unless he reinvents the computer such that the timing of operations is deterministic. With a deterministic system, it's easy to detect intruders and malfunctions because every intruder and bug will invariably mess up the expected timing and trigger alarms created automatically for that purpose.
But in order to properly reinvent the computer, Kaspersky must first solve the parallel programming crisis.
So, it doesn't solve the problem of patent trolls at all, it just changes who feeds the patent trolls (in your system, it would be whoever gives money to the independent fund, i.e., everyone).
No. It removes the power of the troll to prevent others from using the invention and force them out of the market. So it prevents them from forming monopolies which have no place in a free market. The troll needs to prove that a lot of work and research went into the invention. For example, Jeff Bezos would get diddly squat for his 1-click invention and Bill Gates could never have built a multi-billion dollar empire on a piece of crap like MS-DOS.
The current patent system is harmful to society because it tramples on freedom and gives unfair powers to patent holders. The purpose of patents is to provide an incentive for innovation and compensate inventors for their hard work. However, it should not infringe on the freedom of others. That would be counter to its purpose. Above all, the system must never serve as a carte blanche for a few to bully others out of the market. What we need is something like this:
1. A special independent fund must be set aside to compensate inventors for their inventions and reward innovation.
2. A retroactive formula must be adopted to calculate the amount of the compensation.
3. The formula must be adjustable so as to establish the best return for society at large in terms of innovations.
4. Last but not least, whatever the formula chosen, it must never infringe on the right of the individual to copy and use any invention for any ethical purpose.
Inventors should register and publish their findings as soon as they can because their compensation will depend on how much society like and use their ideas. Of course, we still need a Patent bureau and a system to manage claims and the proper registrations of inventions. The system should be able to determine the usefulness and popularity of an invention and how much work went into researching and creating the invention. It should also be as automated as possible.
Not really sure who'd want to at this point, but their market cap is so low almost anyone could take them over.
They got excellent engineers. They should sell themselves to either Apple, Google or Amazon.
AMD is so focused on competing against Intel that they missed the smart phone and tablet revolution. Few manufacturers need or want their heterogeneous processors. They had their chance and they blew it. It's sad, really.
A finger just won't do it. Fingers are fat. Not like a mouse pointer.
That may be true for current touch screens. But new interface technologies are going to change all that. Soon, you'll be able to use hand and/or finger gestures to control a sharp point on the screen. And that's just the tip of the iceberg. One can think of various other virtual objects and tools that can manipulated with gestures. Computer programming, for example, will one day be done by just anybody, i.e., with the use of simple gestures to build beautiful 3-D structures from a collection of available components. Just dreaming. Nothing wrong with that.
Of course, you will need something bigger and more powerful than a tablet/phone for this sort of thing.
Thank you for your 2-cents.
You retard.
LOL. That's funny and I need the humor. Thank you.
Popper understood relativity better than Einstein. He understood why nothing could move in spacetime. Einstein apparently never realized this. Or if he did, he kept quiet about it. Otherwise, most people would have figured out that there is no such thing as bodies moving along their geodesics in spacetime. Just saying. Take it or leave it.