Decius wrote:
] ] Evolving Self-Diagnosing Hardware was first attempted by
] ] the author for some toy circuits in the hope it would be
] ] possible. The toy circuits attempted where a two bit
] ] multiplier and a one bit adder. After hundreds of
] ] thousands of generations, circuits evolved performing
] ] full diagnosis using about half the overhead the
] ] conventional solution would have required. For example
] ] when using two-input logic-gate technology, a two-bit
] ] multiplier can be implemented using 7 gates. Adding an
] ] extra copy, and 7 more gates for comparing 4 outputs, we
] ] have an overhead of 14 gates for the conventional voting
] ] system BIST solution. After four million generations the
] ] GA found a circuit (diagram) with the same behaviour
] ] using only 9 extra gates. It is hard to work out exactly
] ] what operating principles underlie its operation but it
] ] looks like it tends to use more XOR gates which always
] ] propagate a bit flip in one of their inputs, and also
] ] exploits design diversity to compare multiple sections of
] ] the circuit simultaneously.
]
] I'm going to have to look at this in detail tonight.
]
] I'm a little sceptical. Its not "hard to work out exactly what
] operating principles underlie" a 9 gate circuit. "Exploits
] design diversity" sounds like something a politician would
] say. I'm fairly certain that karnaugh maps produce solutions
] that are proveably optimised for simple cases like this. If he
] got results from this technique he probably started with an
] improperly designed circuit.
]
] This is not to say that evolving hardware isn't interesting.
] It just seems like something isn't right with this example. A
] little math will tell me, and I'll post an update later.

Appears to be derived from Garvie's undergraduate thesis of 2001 and ties into other ongoing research at the Centre for Computational Neuroscience and Robotics. Anyone have insight as to the academic reputation of this group?

RE: Distributed Hardware Evolution

These folks use the term "CMOL" to refer to a hybrid between
CMOS and MOLecular-scale fabrication.

] The CMOL concept combines the advantages of nanoscale
] components, such as the reliability of CMOS circuits and
] the minuscule footprints of molecular devices, and the
] advantages of patterning techniques, which include the
] flexibility of traditional photolithography and the
] potentially low cost of nanoimprinting and chemically
] directed self-assembly. This combination may enable CMOL
] circuits of unparalleled density ... at acceptable
} fabrication costs

] Such success would pave the way for more ambitious goals.
] It is plausible that a cerebral-cortex-scale
] CrossNet-based system -- one with ~10^10 neurons and
] 10^15 synapses that would require a ~30 × 30 cm2 silicon
] substrate--would be able, after initial training by a
] dedicated external tutor, to learn directly from its
] interaction with its environment. In this case, we can
] speak of a "self-evolving" system.

Hybrid Semiconductor

] A microchip that uses chemicals instead of pulses of
] electricity to stimulate neurons has been created. It
] could open the way to implants that interact with our
] nervous system in a far more subtle way than is possible
] now.

Thus facilitating two-way comms between biological systems and electronic systems.

New Scientist

] Technology giants Hewlett-Packard, IBM (NYSE: IBM) and
] Sun Microsystems (Nasdaq: SUNW) have announced
] collaboration with smaller security providers on an
] open-standards initiative to achieve more secure
] computing for their customers.

TechNewsWorld.Com: Real-Time Technology News from Around the World

] Central to the experiment is Potter's
] belief that over time the teams will be able to establish
] a cultured in vitro network system that learns like the
] living brains in people and animals do. To achieve that,
] the information from the robot’s sensors is sent back
] through the system to the cultured network of cells in
] the form of electrical stimuli. By closing the loop, the
] group hopes the robot will learn something about itself
] and its environment.

Is this significant or just fringe science? Potential significance:

- Combination of biological and electronic systems. There's other interesting work in this field, some of which Potter has been involved with.

- Development of effective laboratory technique is an important contribution to research in the squishy sciences.

- An agent whose brain and sensors/actuators interact through the internet.

Researchers Use Lab Cultures to Create Robotic ‘Semi-Living Artist’

] Researchers are working on ways to add social
] intelligence to software, letting people interact with
] computers in a less static way and allowing computers to
] respond to users' emotions more effectively.

This seems to have become the conventional wisdom. Google
on "interface agents" to see that this is very strongly
represented in the agents literature. This article indicates
that it is becoming a significant feature of practice.

TechNewsWorld.Com: Real-Time Technology News from Around the World

] Weaves, says Varadarajan, is a framework that translates
] codes from any programming language into code modules to
] create a highly accurate design, development and analysis
] environment. In effect, Weaves can thread together
] different codes, bindings and other elements to create a
] virtual world that tricks programs into believing they
] are running in their actual intended environment. The
] environments can range from something as relatively
] simple as a Web browser to as complex as a global
] network.

Weaving a Virtual World - Under Development : Virtual Internet - CIO Magazine Jan 15,2003

] At the World Economic Forum in Davos, prominent
] scientists and technologists offered their take on
] robots, cloning, digital life, and the

Fortune.com - Intro - Four Voices on the Future

] This reminds me of a series of conversations I had a few
] years ago with a hotshot mo-bio professor, about the
] national-security implications of bio-attacks versus
] cyber-attacks. I started out convinced that the
] cyber-attack threat, while real, was overstated; but
] bio-attacks terrified me. He had the converse view, that
] bio-attacks were possible but overhyped, while
] cyber-attacks were the real nightmare scenario. Each of
] us tried to reassure the other that really large-scale
] malicious attacks of the type we knew best (cyber- for
] me, bio- for him) were harder to carry out, and less
] likely, than commonly believed.

Freedom to Tinker: Why Aren't Virus Attacks Worse?

] Terry Winograd is Professor of Computer Science at
] Stanford University, where he directs the program on
] human-computer interaction. His SHRDLU program done at
] the MIT AI Lab was one of the early explorations in
] natural language understanding by computers. His book
] with Fernando Flores, Understanding Computers and
] Cognition, critiques the underlying assumptions of AI and
] much of computer system design, introducing directions
] from phenomenology. He was a founder and national
] president of Computer Professionals for Responsibility,
] and is currently on sabbatical at Google, Inc.

ACM: Ubiquity - Talking with Terry Winograd