Posted: 10/1/2011 7:46:26 PM EDT
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I am by no means a computer expert, nor am I a biologist. Just an average guy.
I do know that the most powerful computer known is the brain. It is faster, can store more information, and can do more tasks simultaneously than the most powerful electronic computers we now have. Now considering this, is there research into developing a biologically based computer? Is it even conceivable? |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true.
Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. |
Well, LSD was made for reprogramming the biological computer 
There have been brain cells grown on transistors. There's definitely work being done in the field but I don't know how far it's come. Since our understanding of the brain is rudimentary at best, I think most work in this area is done trying to emulate how the brain works vs harnessing the power. |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true. Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. The first computers weren't terribly impressive either, but continued research and improvement have made them truly astounding. Just random thoughts here. |
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The brain is not really all that fast for a computer. It has a delay due to the transmission of impulses from neurons. This delay is much more than any electronic computer experiences.
What makes the brain powerful is the ability to integrate multiple functions at once and to find a solution without having to convert the problem into a system that will work with binary logic. You can find a guy who can throw a baseball at 100 mph and hit the strike zone, and he can also read the batter and decide which pitch will fool the batter and get a strike call. But he can't write a formula to make a computer control 238 muscles or servos to do that. The level of complexity is beyond our ability to explain, although we can do it without thinking if we find an athlete who can throw the ball. But we can't throw a missile and hit the moon. We understand the math, but we need a computer to solve the equations. It also took twenty five years for the pitcher to learn how to pitch. We have not yet figured out how to make a computer that learns like we do. Once we do that, we still have to define creativity before we can even attempt to make a machine do it. |
| It is called cybernetics and is a very real science. It is more or less the combination of organic\mechanical\computing materials. This also includes the creation and use of biological computers. They have already successfully grafted rat brain cells to small simple robots, that function in lieu of a processor. |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true. Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. The first computers weren't terribly impressive either, but continued research and improvement have made them truly astounding. Just random thoughts here. Sure. They'll get better, no doubt. Will they ever replace actual computers? Not for computational tasks. We're taking our knowledge of silicon right down to the limit. Current microprocessor feature sizes are as small as the smallest virus, and much smaller than any actual living cells. Understanding the brain and then "reimplementing" it in silicon will likely be a far more rewarding path than makimg computers that are actually biological. |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true. Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. The first computers weren't terribly impressive either, but continued research and improvement have made them truly astounding. Just random thoughts here. Sure. They'll get better, no doubt. Will they ever replace actual computers? Not for computational tasks. We're taking our knowledge of silicon right down to the limit. Current microprocessor feature sizes are as small as the smallest virus, and much smaller than any actual living cells. Understanding the brain and then "reimplementing" it in silicon will likely be a far more rewarding path than makimg computers that are actually biological. The future of computing is actually "Optical processing". There was an article about 6 months ago that talked about the first optical processor finally being created. |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true. Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. The first computers weren't terribly impressive either, but continued research and improvement have made them truly astounding. Just random thoughts here. Sure. They'll get better, no doubt. Will they ever replace actual computers? Not for computational tasks. We're taking our knowledge of silicon right down to the limit. Current microprocessor feature sizes are as small as the smallest virus, and much smaller than any actual living cells. Understanding the brain and then "reimplementing" it in silicon will likely be a far more rewarding path than makimg computers that are actually biological. The future of computing is actually "Optical processing". There was an article about 6 months ago that talked about the first optical processor finally being created. They've been saying that since I was in jr. high. We're still a long ways off from them even approaching the level of the original microprocessors (think 8088) in terms of computational complexity and speed. Many researchers doubt they will ever be competitive performance wise. SOI technology is extremely advanced. It will take a long time for anything to replace it; decades, if not centuries. Optical data storage will continue to advance though, and I bet it will not be long (a decade or two) before it replaces magnetic storage entirely. Gains made in storage will translate to optical computing, over time. |
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The brain is good at what it does. It's not good, at all, at what computers do. The reverse of both of those are also true. Research is being done to make computers behave more like the brain, to do brain-like tasks (pattern recognition, for one). Using actual biological cells to do it is just silly though, at our current biotech levels. Some very early attempts have been made, but they aren't terribly impressive as far as computational power; especially when compared to their size. The first computers weren't terribly impressive either, but continued research and improvement have made them truly astounding. Just random thoughts here. Sure. They'll get better, no doubt. Will they ever replace actual computers? Not for computational tasks. We're taking our knowledge of silicon right down to the limit. Current microprocessor feature sizes are as small as the smallest virus, and much smaller than any actual living cells. Understanding the brain and then "reimplementing" it in silicon will likely be a far more rewarding path than makimg computers that are actually biological. The future of computing is actually "Optical processing". There was an article about 6 months ago that talked about the first optical processor finally being created. They've been saying that since I was in jr. high. We're still a long ways off from them even approaching the level of the original microprocessors (think 8088) in terms of computational complexity and speed. Many researchers doubt they will ever be competitive performance wise. SOI technology is extremely advanced. It will take a long time for anything to replace it; decades, if not centuries. Optical data storage will continue to advance though, and I bet it will not be long (a decade or two) before it replaces magnetic storage entirely. Gains made in storage will translate to optical computing, over time. The problem was that they were never able to actually produce a working optical processor until recently. I would bet $100, in the next 10 years it will begin transitioning into mainstream. |
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The brain is not that great of a computer. In fact, if there was enough money involved, we could probably run a mind on silicon today if we had better imaging technology.
People like to say that the brain is some great computer, but that is just not true. It is also not exceptionally good at multitasking. In fact, an FPGA (field-programmable-gate-array) is barely any different from a brain. It is a group of many little logic "blocks", similar to neurons, that (also similarly to neurons) can connect to each other in any configuration. In fact, sitting on my desk here, I have an FPGA device that has 1.2 million logic gates. There are about 100,000 times as many neurons in the human brain. 100,000 of these FPGA devices would probably cost about $4,000,000. Oh, also, the FPGA I am thinking of is easily 10,000 faster than a human brain (that is, it takes about .0002 seconds for a signal to go from one neuron to another, and under .00000002 seconds to go from one logic block to another). So, brain-equivalent processing power is about $400. The point is, brains are not really that good at doing anything considering how long they've had to develop. The only reason I can think of that a bio-computer would be practical is if you wanted it to reproduce. If we had forests of trees that could crunch numbers, that might be useful. |
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The problem was that they were never able to actually produce a working optical processor until recently. I would bet $100, in the next 10 years it will begin transitioning into mainstream. I really doubt it, but we'll see! There are still a lot of problems, challenges to be overcome. Ten years ago, Intel was spending $4 billion/year on optical processor R&D, and their investment has only been increasing since then. Most of the research today is focused on optical interconnects, not on 'pure' optical processors. |
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The problem was that they were never able to actually produce a working optical processor until recently. I would bet $100, in the next 10 years it will begin transitioning into mainstream. I really doubt it, but we'll see! There are still a lot of problems, challenges to be overcome. Ten years ago, Intel was spending $4 billion/year on optical processor R&D, and their investment has only been increasing since then. Most of the research today is focused on optical interconnects, not on 'pure' optical processors. You can spend trillions on a problem and never get any where if a breakthrough is never reached. |
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The brain is not that great of a computer. In fact, if there was enough money involved, we could probably run a mind on silicon today if we had better imaging technology. People like to say that the brain is some great computer, but that is just not true. It is also not exceptionally good at multitasking. In fact, an FPGA (field-programmable-gate-array) is barely any different from a brain. It is a group of many little logic "blocks", similar to neurons, that (also similarly to neurons) can connect to each other in any configuration. In fact, sitting on my desk here, I have an FPGA device that has 1.2 million logic gates. There are about 100,000 times as many neurons in the human brain. 100,000 of these FPGA devices would probably cost about $4,000,000. Oh, also, the FPGA I am thinking of is easily 10,000 faster than a human brain (that is, it takes about .0002 seconds for a signal to go from one neuron to another, and under .00000002 seconds to go from one logic block to another). So, brain-equivalent processing power is about $400. The point is, brains are not really that good at doing anything considering how long they've had to develop. The only reason I can think of that a bio-computer would be practical is if you wanted it to reproduce. If we had forests of trees that could crunch numbers, that might be useful. Ok here I am surfing arfcom. Right now my brain is processing what I am typing while at the same time, it is processing all the input from all my senses. While it is sending signals to my fingers telling them what letters to hit and processing the inputs from all my senses it is also regulating all the functions of my body. It is doing all of this while storing information in whatever part of the brain is responsible for short term memory. then it is processing short term memory and figuring out what to put in long term memory. I know of no computer that can handle that kind of multitasking. |
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The brain is not that great of a computer. In fact, if there was enough money involved, we could probably run a mind on silicon today if we had better imaging technology. People like to say that the brain is some great computer, but that is just not true. It is also not exceptionally good at multitasking. In fact, an FPGA (field-programmable-gate-array) is barely any different from a brain. It is a group of many little logic "blocks", similar to neurons, that (also similarly to neurons) can connect to each other in any configuration. In fact, sitting on my desk here, I have an FPGA device that has 1.2 million logic gates. There are about 100,000 times as many neurons in the human brain. 100,000 of these FPGA devices would probably cost about $4,000,000. Oh, also, the FPGA I am thinking of is easily 10,000 faster than a human brain (that is, it takes about .0002 seconds for a signal to go from one neuron to another, and under .00000002 seconds to go from one logic block to another). So, brain-equivalent processing power is about $400. The point is, brains are not really that good at doing anything considering how long they've had to develop. The only reason I can think of that a bio-computer would be practical is if you wanted it to reproduce. If we had forests of trees that could crunch numbers, that might be useful. Ok here I am surfing arfcom. Right now my brain is processing what I am typing while at the same time, it is processing all the input from all my senses. While it is sending signals to my fingers telling them what letters to hit and processing the inputs from all my senses it is also regulating all the functions of my body. It is doing all of this while storing information in whatever part of the brain is responsible for short term memory. then it is processing short term memory and figuring out what to put in long term memory. I know of no computer that can handle that kind of multitasking. Stop thinking of the brain as a single processor. It isn't. Different parts of the brain handle different functions. Integration of data from multiple sources is the key. |
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The brain is not that great of a computer. In fact, if there was enough money involved, we could probably run a mind on silicon today if we had better imaging technology. People like to say that the brain is some great computer, but that is just not true. It is also not exceptionally good at multitasking. In fact, an FPGA (field-programmable-gate-array) is barely any different from a brain. It is a group of many little logic "blocks", similar to neurons, that (also similarly to neurons) can connect to each other in any configuration. In fact, sitting on my desk here, I have an FPGA device that has 1.2 million logic gates. There are about 100,000 times as many neurons in the human brain. 100,000 of these FPGA devices would probably cost about $4,000,000. Oh, also, the FPGA I am thinking of is easily 10,000 faster than a human brain (that is, it takes about .0002 seconds for a signal to go from one neuron to another, and under .00000002 seconds to go from one logic block to another). So, brain-equivalent processing power is about $400. The point is, brains are not really that good at doing anything considering how long they've had to develop. The only reason I can think of that a bio-computer would be practical is if you wanted it to reproduce. If we had forests of trees that could crunch numbers, that might be useful. Ok here I am surfing arfcom. Right now my brain is processing what I am typing while at the same time, it is processing all the input from all my senses. While it is sending signals to my fingers telling them what letters to hit and processing the inputs from all my senses it is also regulating all the functions of my body. It is doing all of this while storing information in whatever part of the brain is responsible for short term memory. then it is processing short term memory and figuring out what to put in long term memory. I know of no computer that can handle that kind of multitasking. Stop thinking of the brain as a single processor. It isn't. Different parts of the brain handle different functions. Integration of data from multiple sources is the key. You are correct that the brain is not a single processor. Nor is your PC. But both have a central processor that figures out what to do with the information they receive. I am not trying to argue here. Sorry if it sounds that way, but I do enjoy a debate and I just might learn something. 
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The brain is not that great of a computer. In fact, if there was enough money involved, we could probably run a mind on silicon today if we had better imaging technology. People like to say that the brain is some great computer, but that is just not true. It is also not exceptionally good at multitasking. In fact, an FPGA (field-programmable-gate-array) is barely any different from a brain. It is a group of many little logic "blocks", similar to neurons, that (also similarly to neurons) can connect to each other in any configuration. In fact, sitting on my desk here, I have an FPGA device that has 1.2 million logic gates. There are about 100,000 times as many neurons in the human brain. 100,000 of these FPGA devices would probably cost about $4,000,000. Oh, also, the FPGA I am thinking of is easily 10,000 faster than a human brain (that is, it takes about .0002 seconds for a signal to go from one neuron to another, and under .00000002 seconds to go from one logic block to another). So, brain-equivalent processing power is about $400. The point is, brains are not really that good at doing anything considering how long they've had to develop. The only reason I can think of that a bio-computer would be practical is if you wanted it to reproduce. If we had forests of trees that could crunch numbers, that might be useful. Ok here I am surfing arfcom. Right now my brain is processing what I am typing while at the same time, it is processing all the input from all my senses. While it is sending signals to my fingers telling them what letters to hit and processing the inputs from all my senses it is also regulating all the functions of my body. It is doing all of this while storing information in whatever part of the brain is responsible for short term memory. then it is processing short term memory and figuring out what to put in long term memory. I know of no computer that can handle that kind of multitasking. That's the beauty of an FPGA. If I wanted, I could have it do 1.2 million simple things at the same time, or thousands of complex things at the same time. It's not a processor, it's a dynamic circuit. It is capable of rebuilding itself in any pattern, even more than a brain. You can have one part of it doing one thing, completely separate from another part doing something else. |
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Ok here I am surfing arfcom. Right now my brain is processing what I am typing while at the same time, it is processing all the input from all my senses. While it is sending signals to my fingers telling them what letters to hit and processing the inputs from all my senses it is also regulating all the functions of my body. It is doing all of this while storing information in whatever part of the brain is responsible for short term memory. then it is processing short term memory and figuring out what to put in long term memory. I know of no computer that can handle that kind of multitasking. I think you underestimate exactly what your computer is doing while you're surfing, let alone what it can do if running at full load. There are things your brain can do that are very difficult for a computer, that you can do much faster, like detecting a voice or face you recognize in a noisy moving crowd. Likewise there are things your computer can do that your brain can't, and never will be able to do, like calculate PI to 100,000 decimal places while drawing and coloring a few billion triangles in a single second. You can hold a conversation in your native language with what 6? 10? people at a time, so long as they're all taking turns speaking. That isn't remarkable at all. Your PC can talk to thousands of other PCs at a time, with each conversation holding data equal in size to a dozen paperback novels. What's remarkable is that all the people you're talking to will have slightly different dialects and accents, and will unconsciously use metaphors and idioms, where as all the PCs must speak *exactly* the same languages. Your brain has about 100 billion neurons, with each one having 7000 or so synaptic connections to other neurons. By contrast, a modern processor has around a billion transistors and is much less interconnected. The brain is a lot more complex. However, the flip side is the CPU operates at much higher speeds (electrochemical reactions are slow), and is the size of your thumbnail. One isn't better than the other at parallel activities in general, but one is definitely better than the other at specific activities. |
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I am by no means a computer expert, nor am I a biologist. Just an average guy. I do know that the most powerful computer known is the brain. It is faster, can store more information, and can do more tasks simultaneously than the most powerful electronic computers we now have. Now considering this, is there research into developing a biologically based computer? Is it even conceivable? The brain is a massively powerful parallel processor. In other words, it can process many tasks at once. Computers are massively powerful serial processors. They're very good at doing deep complex tasks, but aren't good at handling many tasks at once. The very makeup of the human brain uses processes that are by necessity parallel, convergence for example. In the visual system, you have many rods and cones. You have fewer bipolar cells and even fewer ganglion cells. The degree to which perception in general requires parallel processing is not exactly clear. Long story short, we need computers to handle the serial processing that our brains can't do. Why would we want to create a parallel processor that does what our brains CAN do? |
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I am by no means a computer expert, nor am I a biologist. Just an average guy. I do know that the most powerful computer known is the brain. It is faster, can store more information, and can do more tasks simultaneously than the most powerful electronic computers we now have. Now considering this, is there research into developing a biologically based computer? Is it even conceivable? The brain is a massively powerful parallel processor. In other words, it can process many tasks at once. Computers are massively powerful serial processors. They're very good at doing deep complex tasks, but aren't good at handling many tasks at once. The very makeup of the human brain uses processes that are by necessity parallel, convergence for example. In the visual system, you have many rods and cones. You have fewer bipolar cells and even fewer ganglion cells. The degree to which perception in general requires parallel processing is not exactly clear. Long story short, we need computers to handle the serial processing that our brains can't do. Why would we want to create a parallel processor that does what our brains CAN do? This answers my question. Now maybe we can create a Hybrid computer that does both things equally well? |
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The greatest strengths of our brains vs. computers is that we can receive information about our surroundings with all our senses, and though the amount and types of information received can be staggering, we're able to quickly and automatically sort through it all, categorize it, prioritize it, and act on that information according to our priorities and what's most important at the moment. And we can be exposed to something new that we've never seen before and fit it into the situation. The process is very fast and we don't have to even think about it. What's really impressive, probably more than any other single attribute of our brains, is our ability to perform free association, and even better, we can control the free association process as it occurs in order to direct it toward a desired subject. The process of analysis by free association is really nothing short of making order out of chaos. No computer will be able to match this capability for quite some time to come, I believe. Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ |
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It is called cybernetics and is a very real science. It is more or less the combination of organic\mechanical\computing materials. This also includes the creation and use of biological computers. They have already successfully grafted rat brain cells to small simple robots, that function in lieu of a processor. Cybernetics is serious. Very serious cybernetics. |
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Quoted: The greatest strengths of our brains vs. computers is that we can receive information about our surroundings with all our senses, and though the amount and types of information received can be staggering, we're able to quickly and automatically sort through it all, categorize it, prioritize it, and act on that information according to our priorities and what's most important at the moment. And we can be exposed to something new that we've never seen before and fit it into the situation. The process is very fast and we don't have to even think about it. What's really impressive, probably more than any other single attribute of our brains, is our ability to perform free association, and even better, we can control the free association process as it occurs in order to direct it toward a desired subject. The process of analysis by free association is really nothing short of making order out of chaos. No computer will be able to match this capability for quite some time to come, I believe. Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ I am not so sure about that. Google does something similar to that every time you search. Your brain is matching patters while google is matching keywords. The advantage your brain has is that memories are imperfect and the brain likes to fill in the blanks for you, which it also does while 'searching'. |
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Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ 
You've described a pretty standard semantic search algorithm. Computers like Watson can already do this better than any human can. Watson probably knows more than any human, and can probably think about it faster than anybody as well. Google can process in a fraction of a second what a human can't learn in a lifetime. Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. |
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Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Good compared to what? Obviously brains are far from optimized. If you're referring to attentional bottlenecks and a poor sensory input > attended perceptual cues ratio, then at face value it appears to be a poor processor: there's far more information in the world that we attend to at any given time, and often we get an inaccurate perception of sensory input. It isn't perfect...not by a long shot. When I say it's a "good" parallel processor, I mean that it's "good" in the sense that it can turn a massive amount of data into manageable pieces that are actually usable. Given the ease in creating a human brain (ie: knocking someone up), it's a "good deal" compared to trying to create a computer that can simultaneously process 5 sensory channels, retain a majority of biologically useful data, act on that data and contemplate the nature of itself simultaneously. |
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Computers can FIND information with search algorithms, but do they know how to utilize those items and separate out what's important from what's not? Yes. Again, google does this millions of times faster than any human. That's why I always get what I want when I do a google search. Quoted:
Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Good compared to what? Obviously brains are far from optimized. If you're referring to attentional bottlenecks and a poor sensory input > attended perceptual cues ratio, then at face value it appears to be a poor processor: there's far more information in the world that we attend to at any given time, and often we get an inaccurate perception of sensory input. It isn't perfect...not by a long shot. When I say it's a "good" parallel processor, I mean that it's "good" in the sense that it can turn a massive amount of data into manageable pieces that are actually usable. Given the ease in creating a human brain (ie: knocking someone up), it's a "good deal" compared to trying to create a computer that can simultaneously process 5 sensory channels, retain a majority of biologically useful data, act on that data and contemplate the nature of itself simultaneously. Bad compared to ASICS, GPUs, FPGAs, and a number of other logic devices. Think about how much data a human has to process. Now think about how much data google has to process. |
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Computers can FIND information with search algorithms, but do they know how to utilize those items and separate out what's important from what's not? Yes. Again, google does this millions of times faster than any human. That's why I always get what I want when I do a google search. Quoted:
Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Good compared to what? Obviously brains are far from optimized. If you're referring to attentional bottlenecks and a poor sensory input > attended perceptual cues ratio, then at face value it appears to be a poor processor: there's far more information in the world that we attend to at any given time, and often we get an inaccurate perception of sensory input. It isn't perfect...not by a long shot. When I say it's a "good" parallel processor, I mean that it's "good" in the sense that it can turn a massive amount of data into manageable pieces that are actually usable. Given the ease in creating a human brain (ie: knocking someone up), it's a "good deal" compared to trying to create a computer that can simultaneously process 5 sensory channels, retain a majority of biologically useful data, act on that data and contemplate the nature of itself simultaneously. Bad compared to ASICS, GPUs, FPGAs, and a number of other logic devices. Think about how much data a human has to process. Now think about how much data google has to process. Google is spoon-fed that data in a compatible format. Quantitatively, it's processing more. Qualitatively speaking, it's a half-retarded savant chess player that is good at doing one thing and one thing only. There's a reason that DARPA is trying to design computers that are more like brains. |
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The challenge of large scale parallelism in computing is not the hardware, it is the software to recognize how to break up a task to take advantage of the hardware.
For certain well defined tasks we can develop decent software. For an arbitrary task it is not as easy |
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The challenge of large scale parallelism in computing is not the hardware, it is the software to recognize how to break up a task to take advantage of the hardware. For certain well defined tasks we can develop decent software. For an arbitrary task it is not as easy Also it would have to deal with unexpected occurrences that may pop up while completing the task. |
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Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ
You've described a pretty standard semantic search algorithm. Computers like Watson can already do this better than any human can. Watson probably knows more than any human, and can probably think about it faster than anybody as well. Google can process in a fraction of a second what a human can't learn in a lifetime. Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Your brain is doing a lot of things besides your conscious thought. The simple act of sitting in a chair and typing is really a complex task involving hundreds of muscles and actions that happen in fractions of seconds. Of course, you never think of this, but your brain is doing it, while it also regulates heartrate, etc. You don't think about it, but it took a couple of years for you to learn how to sit in a chair without falling. Beyond that, the conscious mind is constantly exploring its surroundings. While you're typing, your mind perceives the things around you and perhaps something reminds you of your grandfather, or you hear the sound of an engine revving on the street outside and identify it as the neighbor's old Ford without making a conscious effort to do it. Likewise, you're sitting around doing something inconsequential when something you see makes you realize a new solution for a problem you've been trying to solve. |
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Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ
You've described a pretty standard semantic search algorithm. Computers like Watson can already do this better than any human can. Watson probably knows more than any human, and can probably think about it faster than anybody as well. Google can process in a fraction of a second what a human can't learn in a lifetime. Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Your brain is doing a lot of things besides your conscious thought. The simple act of sitting in a chair and typing is really a complex task involving hundreds of muscles and actions that happen in fractions of seconds. Of course, you never think of this, but your brain is doing it, while it also regulates heartrate, etc. You don't think about it, but it took a couple of years for you to learn how to sit in a chair without falling. Beyond that, the conscious mind is constantly exploring its surroundings. While you're typing, your mind perceives the things around you and perhaps something reminds you of your grandfather, or you hear the sound of an engine revving on the street outside and identify it as the neighbor's old Ford without making a conscious effort to do it. Likewise, you're sitting around doing something inconsequential when something you see makes you realize a new solution for a problem you've been trying to solve. Maybe it's just me, but that really doesn't impress me... that kind of stuff is easy for computers. It's just such a roundabout way of doing things we don't want to make computers work like that in most cases. |
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Look at ANYTHING that's near you. Just look at it and think about its origins and history and who else has been involved with it, and then think about the their history and what can be associated with it. You can span an incredible array of topics with just a few key words. For example: a dish of halloween candy. Leads to (just a few examples) the movie Halloween. ANY horror or scary movie. Or the candy can remind you of diabetes and someone who had a long stay in the hospital and maybe lost a leg to it. Which can lead you to thinking about combat troops who lost legs in Afghanistan, which leads you to thoughts of guns and people you'd like to see shot such as the Taliban. Which can lead you to thoughs of 9-11 which occurred in New York City, AKA the Big Apple. You visited there once on vacation. Had a great time and didn't get mugged although the taxi fares kind of felt like it. You could keep going with this. No computer can do this. Not yet. CJ
You've described a pretty standard semantic search algorithm. Computers like Watson can already do this better than any human can. Watson probably knows more than any human, and can probably think about it faster than anybody as well. Google can process in a fraction of a second what a human can't learn in a lifetime. Also, to the people who say that brains are good at parallel processing, do you have any evidence for this? They are, by nature, parallel processors, but they are not particularly good processors. Your brain is doing a lot of things besides your conscious thought. The simple act of sitting in a chair and typing is really a complex task involving hundreds of muscles and actions that happen in fractions of seconds. Of course, you never think of this, but your brain is doing it, while it also regulates heartrate, etc. You don't think about it, but it took a couple of years for you to learn how to sit in a chair without falling. Beyond that, the conscious mind is constantly exploring its surroundings. While you're typing, your mind perceives the things around you and perhaps something reminds you of your grandfather, or you hear the sound of an engine revving on the street outside and identify it as the neighbor's old Ford without making a conscious effort to do it. Likewise, you're sitting around doing something inconsequential when something you see makes you realize a new solution for a problem you've been trying to solve. Maybe it's just me, but that really doesn't impress me... that kind of stuff is easy for computers. It's just such a roundabout way of doing things we don't want to make computers work like that in most cases. I honestly doubt that controlling 100% of the functions of a human would be easy for any computer. |
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Maybe it's just me, but that really doesn't impress me... that kind of stuff is easy for computers. It's just such a roundabout way of doing things we don't want to make computers work like that in most cases. But it is the essence of creativity. The human mind constantly seeks connections between things that seem loosely related or even unrelated. It leads to innovations in technical and artistic fields. |
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it does not follow the same train of thought as this thread (simulating a brain) BUT bacterial computing has been found to be very powerful as solving certain types of problems.
Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof-of-concept experiment demonstrates that bacterial computing is a new way to address NP-complete problems using the inherent advantages of genetic systems. The results of our experiments also validate synthetic biology as a valuable approach to biological engineering. We designed and constructed basic parts, devices, and systems using synthetic biology principles of standardization and abstraction. Baumgardner et al. Solving a Hamiltonian Path Problem with a bacterial computer. J Biol Eng (2009) vol. 3 (1) pp. 11 full pdf and html article is available at hhttp://www.jbioleng.org/content/3/1/11 |
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it does not follow the same train of thought as this thread (simulating a brain) BUT bacterial computing has been found to be very powerful as solving certain types of problems. Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof-of-concept experiment demonstrates that bacterial computing is a new way to address NP-complete problems using the inherent advantages of genetic systems. The results of our experiments also validate synthetic biology as a valuable approach to biological engineering. We designed and constructed basic parts, devices, and systems using synthetic biology principles of standardization and abstraction. Baumgardner et al. Solving a Hamiltonian Path Problem with a bacterial computer. J Biol Eng (2009) vol. 3 (1) pp. 11 full pdf and html article is available at hhttp://www.jbioleng.org/content/3/1/11 Sounds to me like each bacterium is one very slow "core" in the processor. Just like each human could be thought of as part of a 6.8 billion core processor. I wonder if the computational power is comparable to any modern electronic computers. Thanks for the link. |