d*****r
发帖数: 2583 | 1 http://www.youtube.com/watch?v=cia3XfQT2fk
他们的computing hardware还是基于Carver Mead的neuromorphic silicon neuron和
synchronous spiking neuron network, IBM Research在这个方面投了很多钱，甚至把
Kwabena Bohen的实验室以前的PhD学生(John Arthur/Paul Merolla in the video)都
挖到IBM去。现在这个方向还没有看到有大的突破的迹象。
Scientific American 2005, Neuromorphic Architecture:
http://www.stanford.edu/group/brainsinsilicon/pdf/05_journ_SciA
phChips.pdf
IBM Press Release:
http://www-03.ibm.com/press/us/en/pressrelease/35251.wss
ARMONK, N.Y., - 18 Aug 2011: Today, IBM (NYSE: IBM) researchers
unveiled a new generation of experimental computer chips designed to
emulate the brain’s abilities for perception, action and cognition. The
technology could yield many orders of magnitude less power consumption
and space than used in today’s computers.
In a sharp departure from traditional concepts in designing and building
computers, IBM’s first neurosynaptic computing chips recreate the
phenomena between spiking neurons and synapses in biological systems,
such as the brain, through advanced algorithms and silicon circuitry.
Its first two prototype chips have already been fabricated and are
currently undergoing testing.
Called cognitive computers, systems built with these chips won’t be
programmed the same way traditional computers are today. Rather,
cognitive computers are expected to learn through experiences, find
correlations, create hypotheses, and remember – and learn from – the
outcomes, mimicking the brains structural and synaptic plasticity.
To do this, IBM is combining principles from nanoscience, neuroscience
and supercomputing as part of a multi-year cognitive computing
initiative. The company and its university collaborators also announced
they have been awarded approximately $21 million in new funding from the
Defense Advanced Research Projects Agency (DARPA) for Phase 2 of the
Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE)
project.
The goal of SyNAPSE is to create a system that not only analyzes
complex information from multiple sensory modalities at once, but also
dynamically rewires itself as it interacts with its environment – all
while rivaling the brain’s compact size and low power usage. The IBM
team has already successfully completed Phases 0 and 1.
“This is a major initiative to move beyond the von Neumann paradigm that
has been ruling computer architecture for more than half a century,”
said Dharmendra Modha, project leader for IBM Research. “Future
applications of computing will increasingly demand functionality that is
not efficiently delivered by the traditional architecture. These chips
are another significant step in the evolution of computers from
calculators to learning systems, signaling the beginning of a new
generation of computers and their applications in business, science and
government.”
Neurosynaptic Chips
While they contain no biological elements, IBM’s first cognitive
computing prototype chips use digital silicon circuits inspired by
neurobiology to make up what is referred to as a “neurosynaptic core”
with integrated memory (replicated synapses), computation (replicated
neurons) and communication (replicated axons).
IBM has two working prototype designs. Both cores were fabricated in 45
nm SOI-CMOS and contain 256 neurons. One core contains 262,144
programmable synapses and the other contains 65,536 learning synapses.
The IBM team has successfully demonstrated simple applications like
navigation, machine vision, pattern recognition, associative memory and
classification.
IBM’s overarching cognitive computing architecture is an on-chip network
of light-weight cores, creating a single integrated system of hardware
and software. This architecture represents a critical shift away from
traditional von Neumann computing to a potentially more power-efficient
architecture that has no set programming, integrates memory with
processor, and mimics the brain’s event-driven, distributed and parallel
processing.
IBM’s long-term goal is to build a chip system with ten billion neurons
and hundred trillion synapses, while consuming merely one kilowatt of
power and occupying less than two liters of volume.
Why Cognitive Computing
Future chips will be able to ingest information from complex, real-world
environments through multiple sensory modes and act through multiple
motor modes in a coordinated, context-dependent manner.
For example, a cognitive computing system monitoring the world's water
supply could contain a network of sensors and actuators that constantly
record and report metrics such as temperature, pressure, wave height,
acoustics and ocean tide, and issue tsunami warnings based on its
decision making. Similarly, a grocer stocking shelves could use an
instrumented glove that monitors sights, smells, texture and temperature
to flag bad or contaminated produce. Making sense of real-time input
flowing at an ever-dizzying rate would be a Herculean task for today’s
computers, but would be natural for a brain-inspired system.
“Imagine traffic lights that can integrate sights, sounds and smells and
flag unsafe intersections before disaster happens or imagine cognitive
co-processors that turn servers, laptops, tablets, and phones into
machines that can interact better with their environments,” said Dr.
Modha.
For Phase 2 of SyNAPSE, IBM has assembled a world-class multi-
dimensional team of researchers and collaborators to achieve these
ambitious goals. The team includes Columbia University; Cornell
University; University of California, Merced; and University of
Wisconsin, Madison.
IBM has a rich history in the area of artificial intelligence research
going all the way back to 1956 when IBM performed the world's first
large-scale (512 neuron) cortical simulation. Most recently, IBM
Research scientists created Watson, an analytical computing system that
specializes in understanding natural human language and provides
specific answers to complex questions at rapid speeds. Watson represents
a tremendous breakthrough in computers understanding natural language,
“real language” that is not specially designed or encoded just for
computers, but language that humans use to naturally capture and
communicate knowledge.
IBM’s cognitive computing chips were built at its highly advanced chip-
making facility in Fishkill, N.Y. and are currently being tested at its
research labs in Yorktown Heights, N.Y. and San Jose, Calif.
For more information about IBM Research, please visit ibm.com/research. |
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