-> Graphite Computers
A researcher in the University of Newcastle has found that elecctrons travel a thousand times faster over the surface of a single molecule thick layer of graphite than it does on pure silicon which is the standard for current day motherboards. This will essentially allow all data to flow and be processed at a speed a thousand times faster than it is in most computers today.
Anyone can extract a single molecule thick layer of graphite buy wrapping sticky tape over a pencil tip and
then unwrapping it. Also, as silicon though it is abundant in supply but difficult and expensive to purify, a shift to graphite as the raw material, prices for computers whould drop phenomenally. So, next time you shell out to buy a 2400GHZ processor, it will come at a price lower than most 2.4GHz processors today.
-> Salt Hard Drives
Current day hard drives have hit the maximum capacity at 1TB per platter. This is because data storage relies on unevenly distributed cluster nanoscopic magnetic grains each about seven nanometers wide. Dr. Joel Yang of the Institute of Materials Research and Engineering (IMRE) has discovered that by integrating
common table salt (NaCl) into the platters, a single bit of data can be stores on a single 10 nanometer grain of salt thereby increasing potential storage to 3.3TB/square inch bringing the total platter capacity upto 18TB. Dr. Yang's research aims at improving upon the current achievements and increasing platter capacities first up to 6TB/square inch and then finally 10TB/square inch bringing the individual total platter capacity upto 54TB!
-> Quantam Computing
Every time we hear the word "quantam" our ears perk up. Chances are "quantam"-anything is related either to extremely complex science which we will all struggle to understand (except a few superhuman intellects out there) or, it's related to some extremely awesome science fiction. In my opinion, good science fiction is the second best thing to good science.
Quantam computer however, is definitely a science and a highly complex one at that. In this, direct use is made of quantum mechanical phenomena, such as superposition and entanglement, to perform operations on data. Quantum computers are different from traditional computers based on transistors. The basic principle behind quantum computation is that quantum properties can be used to represent data and perform operations on these data.The field of quantum computing was first introduced by Richard Feynman in 1982.
Although quantum computing is still in its infancy, experiments have been carried out in which quantum computational operations were executed on a very small number of qubits (quantum bits). Both practical and theoretical research continues, and many national government and military funding agencies support quantum computing research to develop quantum computers for both civilian and national security purposes, such as cryptanalysis.
Large-scale quantum computers could be able to solve certain problems much faster than any classical computer by using the best currently known algorithms, like integer factorization using Shor's algorithm or the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, which run faster than any possible probabilistic classical algorithm. Given unlimited resources, a classical computer can simulate an arbitrary quantum algorithm so quantum computation does not violate the Church–Turing thesis. However, in practice infinite resources are never available and the computational basis of 500 qubits, for example, would already be too large to be represented on a classical computer because it would require 2500 complex values to be stored. Nielsen and Chuang point out that "Trying to store all these complex numbers would not be possible on any conceivable classical computer."
-> Faster RAM
Everybody likes having as much RAM as possible and for good reason too. However, having more is not much good, if it is not fast enough. For example, 8 gigs of 133MHz RAM will be beaten into the dust by 4GB DDR3 RAM at 1333MHz. If recent reports are to be believed, then by this time next year, we'll al be looking at RAM working at 2333MHz or higher which is way faster than the fastest commercially availale RAM today.
-> Artificial Neural Networking
Ever wonder why our brains work faster than supercomputers. For example, if I take an average gaming rig and my brain and observe them, the computer can run a 3.5GHz processor and my brain still beats it working at a paltry 100MHz. The gaming rig can have 4TB of internal memory while my brain has only about 3TB (approximate), so why is it that my brain can achieve much greater things than a deaf and dumb computer? Well, in the case of the brain each and every memory element is also a processing element and each element is interconnected allowing data to be accessed, passed and processed at phenomenal speeds. On the other hand, computers have to send data all over the place to get stuff done. They have internal memory and RAM, processors, motherboards and what not allowing bottlenecks to be created quite easily. Also, only a limited number of paths for the passing of data exist, whereas in the average human brain (and I assure you, my brains is VERY average), there exists millions of paths for the passing of data.
The solution lies in artificial neural networks. This is a paradigm which attempts to replicate biological neural networks. First created in Holland in 1975, currently much work is being done in the software application of artificial neural networks. Things such as data mining, pattern recognition, density function analysis, calculation of Gaussian functions, etc. is bringing forth programs with capabillities such as voice, handwriting and fingerprint recognition (e.g Apple Siri) and more complex ones which take on nearly AI (Artificial Intelligence) capabilities.
I hope you all enjoyed this article.
These are some of the innovations that embody the near future of computers world-wide.
A researcher in the University of Newcastle has found that elecctrons travel a thousand times faster over the surface of a single molecule thick layer of graphite than it does on pure silicon which is the standard for current day motherboards. This will essentially allow all data to flow and be processed at a speed a thousand times faster than it is in most computers today.
Anyone can extract a single molecule thick layer of graphite buy wrapping sticky tape over a pencil tip and
then unwrapping it. Also, as silicon though it is abundant in supply but difficult and expensive to purify, a shift to graphite as the raw material, prices for computers whould drop phenomenally. So, next time you shell out to buy a 2400GHZ processor, it will come at a price lower than most 2.4GHz processors today.
-> Salt Hard Drives
Current day hard drives have hit the maximum capacity at 1TB per platter. This is because data storage relies on unevenly distributed cluster nanoscopic magnetic grains each about seven nanometers wide. Dr. Joel Yang of the Institute of Materials Research and Engineering (IMRE) has discovered that by integrating
common table salt (NaCl) into the platters, a single bit of data can be stores on a single 10 nanometer grain of salt thereby increasing potential storage to 3.3TB/square inch bringing the total platter capacity upto 18TB. Dr. Yang's research aims at improving upon the current achievements and increasing platter capacities first up to 6TB/square inch and then finally 10TB/square inch bringing the individual total platter capacity upto 54TB!
-> Quantam Computing
Every time we hear the word "quantam" our ears perk up. Chances are "quantam"-anything is related either to extremely complex science which we will all struggle to understand (except a few superhuman intellects out there) or, it's related to some extremely awesome science fiction. In my opinion, good science fiction is the second best thing to good science.
Quantam computer however, is definitely a science and a highly complex one at that. In this, direct use is made of quantum mechanical phenomena, such as superposition and entanglement, to perform operations on data. Quantum computers are different from traditional computers based on transistors. The basic principle behind quantum computation is that quantum properties can be used to represent data and perform operations on these data.The field of quantum computing was first introduced by Richard Feynman in 1982.
Although quantum computing is still in its infancy, experiments have been carried out in which quantum computational operations were executed on a very small number of qubits (quantum bits). Both practical and theoretical research continues, and many national government and military funding agencies support quantum computing research to develop quantum computers for both civilian and national security purposes, such as cryptanalysis.
Large-scale quantum computers could be able to solve certain problems much faster than any classical computer by using the best currently known algorithms, like integer factorization using Shor's algorithm or the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, which run faster than any possible probabilistic classical algorithm. Given unlimited resources, a classical computer can simulate an arbitrary quantum algorithm so quantum computation does not violate the Church–Turing thesis. However, in practice infinite resources are never available and the computational basis of 500 qubits, for example, would already be too large to be represented on a classical computer because it would require 2500 complex values to be stored. Nielsen and Chuang point out that "Trying to store all these complex numbers would not be possible on any conceivable classical computer."
-> Faster RAM
Everybody likes having as much RAM as possible and for good reason too. However, having more is not much good, if it is not fast enough. For example, 8 gigs of 133MHz RAM will be beaten into the dust by 4GB DDR3 RAM at 1333MHz. If recent reports are to be believed, then by this time next year, we'll al be looking at RAM working at 2333MHz or higher which is way faster than the fastest commercially availale RAM today.
-> Artificial Neural Networking
Ever wonder why our brains work faster than supercomputers. For example, if I take an average gaming rig and my brain and observe them, the computer can run a 3.5GHz processor and my brain still beats it working at a paltry 100MHz. The gaming rig can have 4TB of internal memory while my brain has only about 3TB (approximate), so why is it that my brain can achieve much greater things than a deaf and dumb computer? Well, in the case of the brain each and every memory element is also a processing element and each element is interconnected allowing data to be accessed, passed and processed at phenomenal speeds. On the other hand, computers have to send data all over the place to get stuff done. They have internal memory and RAM, processors, motherboards and what not allowing bottlenecks to be created quite easily. Also, only a limited number of paths for the passing of data exist, whereas in the average human brain (and I assure you, my brains is VERY average), there exists millions of paths for the passing of data.
The solution lies in artificial neural networks. This is a paradigm which attempts to replicate biological neural networks. First created in Holland in 1975, currently much work is being done in the software application of artificial neural networks. Things such as data mining, pattern recognition, density function analysis, calculation of Gaussian functions, etc. is bringing forth programs with capabillities such as voice, handwriting and fingerprint recognition (e.g Apple Siri) and more complex ones which take on nearly AI (Artificial Intelligence) capabilities.
I hope you all enjoyed this article.
These are some of the innovations that embody the near future of computers world-wide.
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