This month, August 2014, IBM
unveiled "TrueNorth". It is the most advanced and powerful computer
chip of its kind ever built. This neurosynaptic processor is the
first to achieve one million individually programmable neurons,
sixteen times more than the current largest neuromorphic chip. It is
designed to mimic the structure of the human brain and is uniquely
different from other computer architectures.
TrueNorth is the largest IBM chip ever fabricated, with 5.4 billion
transistors at 28 nanometers (A human hair is approximately 80,000-
100,000 nanometers wide) and it consumes orders of magnitude less
power than a typical modern processor. IBM hopes this combination of
ultra-efficient power consumption and entirely new system
architecture will allow computers to far more accurately emulate the
brain.
TrueNorth is composed of 4,096 cores, with each of these modules
integrating memory, computation and communication. The cores are
able to continue operating when individual cores fail, similar to a
biological system.
Showing posts with label Computers. Show all posts
Showing posts with label Computers. Show all posts
Aug 30, 2014
Feb 7, 2014
Moravec's Paradox
Hans Moravec, adjunct faculty member at
the Robotics Institute of Carnegie Mellon University, pointed out
that machine technology mimicked a savant infant. Machines can do
long math equations instantly and beat humans in chess, but they
can't answer a simple question or walk up a flight of stairs (until
recently). He, along with many others has been working to solve that
paradox and help computers evolve on their own.
Early artificial intelligence (AI) researchers believed intelligence was characterized as the things that highly educated scientists found challenging, such as chess, symbolic integration, and solving complicated word algebra problems. They thought, if those could be done so easily by computers, things that children of four or five years could do effortlessly, such as visually distinguishing between a coffee cup and a chair, or walking around on two legs, or responding to words would be infinitely easier for computers to learn.
Computers/robots are finally beginning to move and think like people. Narrative Science can write earnings summaries that are indistinguishable from wire reports. We can ask our phones, 'I'm lost, help.' and our phones can tell us how to get home. (The smartphone was introduced in 2007, just seven years ago.)
Computers that can drive cars were never supposed to happen and ten years ago, many engineers said it was impossible. Navigating a crowded street requires a combination of spacial awareness, soft focus, and constant anticipation. Yet, today we have Google's self-driving cars and they have been approved by some states as allowable on city streets. Ten years from impossible to common.
IBM, working with Memorial Sloan-Kettering cancer information is using its computers to diagnose diseases and the Cleveland Clinic to help train aspiring physicians. It just invested a billion dollars to set up 'Watson' into a separate business unit for medical and other complex decision making activities.
Bottom line, we are experiencing solutions to the paradox and it is very exciting, although I am not sure machines will ever replace the following or that we will ever want to.
Early artificial intelligence (AI) researchers believed intelligence was characterized as the things that highly educated scientists found challenging, such as chess, symbolic integration, and solving complicated word algebra problems. They thought, if those could be done so easily by computers, things that children of four or five years could do effortlessly, such as visually distinguishing between a coffee cup and a chair, or walking around on two legs, or responding to words would be infinitely easier for computers to learn.
Computers/robots are finally beginning to move and think like people. Narrative Science can write earnings summaries that are indistinguishable from wire reports. We can ask our phones, 'I'm lost, help.' and our phones can tell us how to get home. (The smartphone was introduced in 2007, just seven years ago.)
Computers that can drive cars were never supposed to happen and ten years ago, many engineers said it was impossible. Navigating a crowded street requires a combination of spacial awareness, soft focus, and constant anticipation. Yet, today we have Google's self-driving cars and they have been approved by some states as allowable on city streets. Ten years from impossible to common.
IBM, working with Memorial Sloan-Kettering cancer information is using its computers to diagnose diseases and the Cleveland Clinic to help train aspiring physicians. It just invested a billion dollars to set up 'Watson' into a separate business unit for medical and other complex decision making activities.
Bottom line, we are experiencing solutions to the paradox and it is very exciting, although I am not sure machines will ever replace the following or that we will ever want to.
Jun 21, 2013
Quantum Computing Explained
Today's computers rely on
electrons to deliver information in binary bits, or yes/no, 1/0,
on/off.
Laws of quantum physics allow bits to be in multiple states simultaneously so it has the potential to be millions of times more powerful than today's most powerful supercomputers.
Quantum bits, or Qubits are more versatile than standard bits because they can exist in three states instead of two. Current computers represent things as a one or zero, but a quantum computer can render a qubit as representing a one, a zero, or every fraction between one and zero at the same time.
An interesting thing about qubits is that by just looking at one, it changes its state, so scientists had to devise a way to look without the qubit knowing it was being looked at. (Long story, but fascinating)
A 30-qubit quantum computer is approximately as powerful as a 10 teraflop computer. It can solve 10 trillion floating point operations every second vs. an average computer, which performs about seven gigaflops (seven billion) per second. Quantum computers process multiple calculations at once vs. current computers, which process one at a time.
Google and NASA have a 512-qubit quantum computer housed in a 10 foot black cabinet, but do not expect to buy one for your home in the near future. The NASA Ames machine may be upgraded to a 2,048 qubit chip in the next year or two. There are 25.4 million nanometers in one inch and fingernails grow one nanometer every second.
Laws of quantum physics allow bits to be in multiple states simultaneously so it has the potential to be millions of times more powerful than today's most powerful supercomputers.
Quantum bits, or Qubits are more versatile than standard bits because they can exist in three states instead of two. Current computers represent things as a one or zero, but a quantum computer can render a qubit as representing a one, a zero, or every fraction between one and zero at the same time.
An interesting thing about qubits is that by just looking at one, it changes its state, so scientists had to devise a way to look without the qubit knowing it was being looked at. (Long story, but fascinating)
A 30-qubit quantum computer is approximately as powerful as a 10 teraflop computer. It can solve 10 trillion floating point operations every second vs. an average computer, which performs about seven gigaflops (seven billion) per second. Quantum computers process multiple calculations at once vs. current computers, which process one at a time.
Google and NASA have a 512-qubit quantum computer housed in a 10 foot black cabinet, but do not expect to buy one for your home in the near future. The NASA Ames machine may be upgraded to a 2,048 qubit chip in the next year or two. There are 25.4 million nanometers in one inch and fingernails grow one nanometer every second.
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