1,000 times better! Neuro-Computing Colloquium & Workshop October 31, 2002 Silicon Recognition, Inc.

1,000 times better!

Neuro-Computing Colloquium & WorkshopOctober 31, 2002

Silicon Recognition, Inc.

Silicon Recognition, 2002 - Company Confidential

1,000 times better!

About the Founder

Guy PAILLET - Founder and Chairman

• Extensive background in artificial vision

• Worked on parallel processing with Carlo Rubbia, Nobel Prize winner

• Worked on solid state physics with Leon Cooper, Nobel Prize winner


1,000 times better!

Silicon Recognition, Inc.

Mission: Become the World Leader in Silicon-based Pattern Recognition Technology

• Founded in 1997 by Guy Paillet, Chairman

• Worldwide Headquarters in Northern California

• ZISC Original Design by IBM• Patented Technology

1,000 times better!

“The Next DSP!”*

The first chip that mimics the brain!

*Marco Landi, former President EMEA & ASPAC, Texas Instruments

• Unlimited Parallel Processing Scalability• No Operating System• No Computer Language• No Differentiation Memory / Processor• Continual Learning Capability


1,000 times better!

Board of Directors

Guy Paillet – Chairman

Marco Landi – Former President of TI ASPAC and EMEA, and COO of Apple

Len Perham – Former President & CEO of IDT

Frank Lee – Co-founder of IDT & Galventech

Remi Vespa – Former President & CEO of ICD, Application development arm of France Telecom


1,000 times better!

Learning/Recognition

Search&

Sortunit

Category

Distance

Status

Vector

ZISC

Learn

Memory Distanceevaluation

New PEL

Unknownyes

PEL #1


Category

AIF

PEL #2


Category

AIF


Category

PEL #n

AIF

Category

AIF

Recognize


1,000 times better!

ArtificialIntelligence

ZISC

Data

exact

ProcessIll-defined,not linear

easy todescribe

ZISC complements Classical Approaches

Conventional,Algorithms

Pentium,DSP

Imprecise,corrupted


1,000 times better!

Products

Massively ParallelData Mining Machines

EmbeddedSmart sensors


1,000 times better!

ZISC Chips

First Generation1 Technology

36 neurons144 pins

Second Generation0.25 Technology

78 neurons100 pins


1,000 times better!

Boards

First GenerationISAPCI

Second Generation: MURENPCI

Embedded


1,000 times better!

Massively Parallel Engines

34,000,000 Vectors Processed per second


1,000 times better!

Major Market Targets

• Machine Vision (HALS)

• Massively Parallel Engines


1,000 times better!

Selected Users


1,000 times better!

Smart Sensing (part 1)

Data Capture

Learning &

Recognition

Feature

ExtractionHALS

MUREN

ZISC


1,000 times better!

Smart Sensing (cont)

ZISC

MUREN

HALS


1,000 times better!

Smart Sensing (cont)

• Wireless Telecommunications

•Video Compression•Authentication•Noise reduction

• Automotive

•Smart airbags•Obstacle detection•Smart mirrors•Driver alertness

• Toy and gaming

•Smart dolls•Xbox, PlayStation, etc.


1,000 times better!

Example of ApplicationPerson Tracking

Courtesy of Panasonic


1,000 times better!

Example of ApplicationMotion Detection

Courtesy of General Vision


1,000 times better!

Example of ApplicationFacial Expression Recognition


1,000 times better!

Example of ApplicationCar Tracking

Courtesy of Wescam


1,000 times better!

Example of Application“Check the Checker”

Areas Not Checked Yet!

Eye Calibration


1,000 times better!

Example of ApplicationTarget Tracking

Courtesy of French / German Institute of Defense


1,000 times better!

Example of ApplicationWireless Telecommunications

• Noise reduction at the source and destination

• User Identification:– Eye, voice, and fingerprint

• Enabling 3G-based transactions

• Smart compression


1,000 times better!

Massively Parallel Engines (part 1) Comparison of processing time with increasing number of records

Serial Processing @750Mhz

ZISC Parallel Processing @8Mhz

Number of records

Pro

ces s

ing T

i me


1,000 times better!

Massively Parallel Engines (part 2)

• Up to 85% of corporate data are unstructured ones

• Content-Management a $ 10 B market by 2004 (Meta Group)

• Applications:Video Indexing Medical

GenomicsSecurity

1,000 times better!

Accessing Unstructured Data

John Smith

ZISC

1

2’

3

2

Index

Data

Speed Enables Hypothesis Generation


1,000 times better!

Massively Parallel Engines (part 3)Decision Making System

Time

1,000,000

10 billion

1 billion

Numberof cells

per DIMS

2002

100,000

2003 2005


1,000 times better!

Silicon Recognition in New Zealand

• ZISC enables a new industry to be created around smart sensing and parallel computing

• Fast moving, smart entrepreneurs can bring to the market a new series of designs, based on ZISC

• Large corporations will eventually use these designs


1,000 times better!

Silicon Recognition in New Zealand

• Excellence Center•AUT•TfE•Patenting

• SR feeds Entrepreneurs with requests from large corporations

• SR helps sell the prototype to large corporations (US/EMEA/Japan)


1,000 times better!

May Auckland Remain Its Home!

1,000 times better! Neuro-Computing Colloquium & Workshop October 31, 2002 Silicon Recognition, Inc.

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