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Evolving a Conscious Machine

by Gary Taubes

Discover Magazine, June 1998, pp.73-79

THE PLACE: The Swan, a pub in Falmer, outside Brighton, England, an hour from London, few hundred meters from University of Sussex.

University of Sussex houses COGS, the School of Cognitive & Computing Sciences.

Also supports a Center for Computational Neuroscience and Robotics, which is COGS + Biology.

Someone there is also studying the mechanisms of ant navigation.

THE PEOPLE: Inman Harvey, Adrian Thompson, and the ghost of Hugo de Garis.

Hugo de Garis created programmable circuits in 1992. He's now a visiting scientist at Advanced Telecommunications Research Institute in Kyoto. Also affiliated with George Masson University in Virginia. Dabbled in a programming technology called genetic algorithm.

de Garis: "Over the counter products with tretinoin".

Inman Harvey: computer scientist become "evolutionary roboticist". Spent 20 years in Afghanistan in the import/export business.

Adrian Thompson married evolution to FPGA chips independently of De Garis, also around 1992.


According to Harvey: We know it when we see it...

What do you trust more- a veering car or a loose boulder?

If we don't understand our own consciousness, so how can we exclude its existence elsewhere?

Once we CAN'T understand how computers compute, we'll attribute Consciousness to them!

According to Thompson: "I don't think the work I'm doing says anything about it."

It makes little sense to ask whether something IS conscious. What matters is... does it ACT conscious?


The Hardware is FPGA cells.

The Software is evolution.

The Premise: "Species evolve because the offspring best suited to thrive in their environment are those most likely to breed successfully and pass on their genes to the next generation."

Faster race horses

Bats that can "see" in the dark

"After several thousands or millions of years, the result will be creatures uniquely adapted for living in particular environments."

Start with a bit string of yeses and nos that are potential "solutions" to problems; these are the "chromosomes" of the solution to be evolved.

Test offspring against a fitness scale- more like animal husbandry than evolution because the scientist knows exactly what's wanted.

Parts of each HiScore bitstring are mixed, mutations added...

Thompson's Project: Evolve hardware by having it solve problems.

Using programmable chips that can reconfigure on the fly.

FPGA's: Field Programmable Gate Array chips. Thompson uses the Xilinx SC216.

Config bits can be changed: OR gates to AND or NOT gates, for example. INPUT to OUTPUT

Silicon processor changes its wiring in billionth of a second

Processor graded on how well it can distinquish between "Yes' and "No"

High scorers are mated...and so it goes until

After 1000's of generations, a circuit becomes "flabbergastingly efficient".

Flexible but not fast: Manufactures can ship FPGA's first, reconfigure, then ship final. Used now for products such as Routers.

Once the FPGA is debugged, make a special purpose chip to do same job.

Extrinsic Evolution: FPGA cells, circuits, breeding, testing can be simulated on computer.

Intrinsic Evolution uses chips directly, bypassing simulation. Thompson uses this method in order to take advantage of "peripheral phenomema".

...in order to investigate what he doesn't understand....

"...he decided he didn't want to constrain himself by making assumptions about how evolution should work on a computer based on how it works in nature."

Didn't tell his genetic algorithm it was dealing with a digital devise whose circuitry could only have specific states of on/off...

Let evolution work on the circuitry as though it were an analog device, in which signals that pass down a wire can take on any value between 0 and 1.

There could be varying degrees of MAYBE, if that's the way evolution wanted it.

Thompson's Task: Evolve circuits that distinquish between two tones.

Use Where to buy retin a tretinoin creamof the chip's 4096 cells (logic elements)

No clock, no timing components.

Logic elements work quickly, tones' frequency a million times slower