Jim Cast
Headquarters, Washington, DC               September 10, 1998
(Phone:  202/358-1779)

John Watson
Jet Propulsion Laboratory, Pasadena, CA
(Phone:  818/354-5011)

RELEASE:  98-161

JPL NEURAL NETWORK CHIP PAVES THE WAY TO A 
CLEANER AMERICA AS FORD SIGNS LICENSING AGREEMENT

     A new computer chip that mimics how the human mind works is 
making its way from the space program to American industry and may 
end up in millions of American cars in years to come.

     NASA's Jet Propulsion Laboratory (JPL), Pasadena, CA, and the 
Ford Motor Co. have signed a licensing agreement for use of an 
advanced neural network technology to diagnose misfiring under the 
hoods of Ford automobiles, among its many potential applications.  
With the advent of this new chip, vehicles should show a reduction 
in emission levels. 

     The smart fit between JPL's neural net hardware and Ford's 
automotive engineering algorithm expertise will enhance the 
industrial giant's ability to meet ever-stricter Clean Air Act 
requirements as they apply to continuous onboard diagnostics and 
control, officials said. 

     In addition, the chip is designed to improve fuel economy, 
resulting in financial savings for car owners.  Ford engineers do 
not predict a price increase for installation of the chip because 
JPL designed a computationally powerful neuroprocessor that could 
be mass-produced in a highly cost-effective way.  The technology 
also improves customer satisfaction by virtually eliminating 
distracting false alarms about misfiring that vehicle dashboards 
can signal with current under-the-hood diagnostic technology.

     JPL and Ford scientists say the chip represents the first 
significant change in the way computing is done on vehicles since 
computers were first introduced into automobiles in the 1970s. 

     "Neural networks are a new discipline, and diagnostics, 
prognostics and control is a huge field.  Ford's application is 
but the tip of the iceberg of this chip's potential use in 
American industry as a whole," said Tom Hamilton, program manager 
at JPL's Dual-Use Technology Office, one of JPL's many technology 
transfer arms.  "JPL is proud to be able to make this 
revolutionary technology available for U.S. business."  

     The new licensing agreement provides Ford with rights to 
intellectual property of the chip for auto industry applications, 
while JPL, which has applied for patents to the technology, 
retains general rights.  JPL is managed by the California 
Institute of Technology, which serves as the party of record for 
this license.

     Neural systems were inspired by the architecture of nervous 
systems of animals, which use neurons, a form of parallel 
processing elements, to process large volumes of information 
simultaneously.  In vehicle applications, artificial neural 
networks will "learn" both how to diagnose problems like engine 
misfires and control the engine to optimize fuel economy and 
emissions.

     "What JPL has brought to the table is expertise in designing 
and building what are known as neural network 'application-
specific integrated circuits'," said Dr. Raoul Tawel, who led the 
development at JPL for the chip. "With Ford, we are implementing 
highly complex neural network software code in dedicated hardware 
logic. This brings about a tremendous boost in computational 
ability compared to traditional software-based approaches, 
enabling real-time onboard diagnostics for the first time." 

     For misfire diagnostics, it is necessary to observe and 
diagnose every engine firing event, estimated at over one billion 
in the life of each car.  

     In addition, the diagnostic error rate has to be extremely 
small, less than one in a million, in order to avoid sending false 
alarm signals to the driver.  The new chip will accomplish that 
task by "learning" diagnostic tasks during the vehicle development 
process, bypassing the need to develop conventional software that, 
in any event, can neither perform these tasks as well nor be 
implemented in large production volumes with standard 
microprocessors.  The neural network chip, designed to carry out 
parallel neuron computations efficiently, overcomes the 
computational barriers that prevent this technology from being 
exploited today.

     A detailed, technical explanation of the technology written 
by Tawel and Drs. Ken Marko and Lee Feldkamp of Ford's neural 
network team, among several others, is available on the Web.  
"Custom VLSI ASIC for Automotive Applications with Recurrent 
Networks" can be accessed at 
http://www.jpl.nasa.gov/releases/98/ijcnn98.pdf 

     For further information about JPL's technology transfer 
programs, visit http://techtrans.jpl.nasa.gov/tu.html

                             -end-