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Super Smart Revolution

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Peter A.J. van der Made

Peter started his career in 1974, after completing an electronic engineering course at the Technical University in Amsterdam. Because of his interest in digital electronics he started work at Sperry Univac in Sydney, Australia. Sperry Univac realized his potential and sponsored him to attain qualifications in digital electronics in NSW, Australia. After that he worked on large-scale computers and peripheral equipment, before being dispatched to Port Moresby where he was awarded the function of Computer Service Manager. In that position he was responsible for the maintenance of large computer equipment, as well as performing training of local graduates employed by his department. During his time at Univac he developed a keen interest in the then new microprocessors. He purchased an Altair 8008 to use at home. He joined Olivetti when an opportunity presented itself to dive deeper in microprocessors, to develop programming and design skills. Over the next few years he worked at several major companies and became familiar with chip design.

During the early months of 1980 he designed a graphics accelerator, which was later used in the IBM PC. This graphics accelerator had a resolution of 900 x 1200 pixels in 4096 colors and used a 20 inch screen. The graphics processing core was clocked at up to 120 MHz. – pushing the boundaries of the technology at the time This graphics device was well ahead of its time, and PC based CAD programs did not appear until the IBM PC/AT was introduced.

From 1988 to 1994 he worked at a university teaching computer science and digital design. After 1994, Peter turned his attention to the growing problem of computer malware with the development of a new detection method based on real time behaviour analysis. This work resulted in three granted patents.

By the end of the millennium he had created a working prototype of the ‘Analytical Behaviour Method’, a system in which new programs are analysed in a ‘Analytical Virtual Machine’. By 2002 the company was sold to Internet Security Systems (now IBM) in Atlanta, with great benefited to the shareholders.

BrainChip was founded in 2004, initially as vWISP, with the aim to develop a better computational method for machine recognition. Initial experiments were focused on massive parallel processing, using many cores and software. In early 2006 the company changed course, and started the development of hardware circuits that process information in a similar manner as the brain. Much time was devoted to the synapses, these tiny spots that occur on the body of neural cells in the brain. These tiny devices hold the key to learning and brain structure. This development was driven by the fact that the brain is the ultimate recognition engine. When we look at a scene we instantly recognize objects in that scene. Furthermore, when we don’t recognize an object, we learn about it in the context of things that we already know. The brain has a very different structure to a computer.

The research and the path to this new computational structure is documented in a book, published in 2012, called “Higher Intelligence”.

This work has culminated in the BrainChip SNAP (Spiking Neuron Adaptive Processor) technology, an electronic device that learns autonomously and extracts features from an input stream. It works by the same principles as the brain, a process known as

Achievements in chronological order:

  • 1979-1982 Speech synthesis technology
  • 1981-1983 Discrete 1200 x 900 color graphics accelerator, redesigned to fit the IBM PC.
  • 1983-1988 Design and production of the 87371 ASIC graphics accelerator chip.
  • 1986 Patent. Parallel processing RISC core.
  • 1989-1994 Lecturer, Applied Physics and Computer Science at the University of PNG. Waigani Campus
  • 1991-1993 President of the Professional Computer Association
  • 1992-1993 Chairman of the Medical Equipment Standards Committee, Department of Industry & Commerce
  • 1990-1991 Chairman of the Technology Subcommittee for the South Pacific Games
  • 1995-1996 Preliminary research leading to the invention of the Analytical Behavior Method
  • 1996-2000 Invention and prototype development of the Analytical Virtual Machine and Virtual OS.
  • 2000-2003 Commercialization of the Computer Immune System vCIS.
  • 2003-2004 Chief Scientist, ISS. Atlanta, GA. USA, and Brookvale, Sydney, Australia.
  • 2004-Present Founder, CEO and CTO – BrainChip Inc. and BrainChip Holding Ltd. Spiking Neuron Adaptive Processor SNAP



Massive Parallel Processing Computer. European Patent Office, Application Number: 8600233. Published: Nr. 198716, 17/09/1987 (Lapsed)

Computer Immune System and Method for detecting unwanted code in a computer system. US Patent and Trademark Office. Patent No. 7,854,004

Computer Immune System and Method for detecting unwanted code in a computer system. World Intellectual Property Organization. Publication number: WO02/006928A3

Analytical Virtual Machine. World Intellectual Property Organization. Publication Number: WO02/35328A1

Analytical Virtual Machine. US Patent and Trademark Office, Patent No 7,657,419 and 7,146,305

Computer immune system and method for detecting unwanted code in a P-code or partially compiled native-code program executing within a virtual machine. US Patent and Trademark Office, Patent 7,900,258 and 7,370,360

Computer Immune System for detecting unwanted code using a virtual machine European Patent Office, Patent number WO03096607

Computer Immune System and method for detecting unwanted code in a computer system. European Patent Office, Patent Number TW518463

Systeme Informatique immunse detectant les codes indesirables dans un systeme informatique. Canadian Intellectual Property office, Patent Number CA2 416066

Machine Virtuelle Analytique. Canadian Intellectual Property Office. Patent Number: CA2 426065

Analytical Virtual Machine. European Patent Office, Patent number CN1476554

Autonomous Learning Dynamic Artificial Neural Computing Device and Brain Inspired System. U.S. Patent 8,250,011 granted August 21, 2012.

Method and System for creating Dynamic Neural Function Libraries. US Patent Application 13/461,800

Several applications have been lodged with the USPTO during 2013, 2014, 2015 and 2016.


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