Category: Nanodot

According to a press release from 10 September 2001, computer security researchers at the University of California at Davis are studying a system that lets exposed, "untrusted" machines go on providing useful, accurate information, even though they might have been infiltrated and compromised. Their method invokes a digital signature from a "trusted" computer that can help verify the integrity of data received from an "untrusted" computer.

from the blue-sky-research dept.
The Future and Emerging Technologies (FET) division of the European Union's Information Society Technologies (IST) Program has launched a new research initiative to develop "life-like perception systems". The objective of the initiative is "to create integrated perception-response systems that are inspired by the sophistication of solutions adopted by living systems. 'Perception' is meant to include sensorial, cognitive, control and response aspects, whether it refers to vision or hearing, or to any other type of interaction with the environment by a biological organism. Such systems would extend the capabilities of machines or be used to augment the human senses."
More information about the program can be found on the CORDIS website at http://www.cordis.lu/ist/fetbi.htm .

from the visionary dept.
A team of researchers at the Center for Image Processing and Integrated Computing (CIPIC) at the University of California, Davis are applying virtual reality to help scientists to see and handle large, complex sets of data. According to the press release on their work, the researchers say the simplest way to handle this data is to make it visible, so that scientists can "see" what is happening in an experiment. Virtual reality allows researchers to interact with the data while they are looking at it, making changes and seeing what happens.

The center is also offering a graduate-level class in which students learn how to build and work with virtual reality environments.

from the real-world-AI dept.
On a more practical note, the Mindpixel Digital Mind Modeling Project has announced that a standard psychological test used by clinicians worldwide in the evaluation and treatment of adults will be administered to a machine-based artificial personality.
The Mindpixel Project is a large worldwide AI effort, with nearly 40,000 contributing members in more than 200 countries. The project's goal is to build a highly accurate statistical model of an average human mind which they hope can be used as a foundation for true artificial consciousness. The test will be applied to GAC (Generic Artificial Consciousness — pronounced "Jack"), an artificial personality being developed by Mindpixel. GAC will be evaluated over the next several months to assess its learning of human consensus experience from the Mindpixel project's large and diverse group of users from many different cultures.
The test will be supervised and interpreted by Dr. Robert Epstein, an expert on human and machine behavior. "Nothing like this has ever been attempted," said Epstein. "We're evaluating thousands of people worldwide as if they were one collective individual . . . We don't know if it is possible to build a normal personality out of millions of little pieces. This experiment will tell us how reasonable the idea is."

from the Open-the-pod-bay-doors,-HAL dept.
Ronald P. Loui, Ph.D., an associate professor of computer science at Washington University in St. Louis, has described a method for using artificial intelligence that incorporates the ability to argue into computer programs. His work is initially focused on legal arguments.

Louiís article, "Logical Models of Argument," consolidates research results from the mid-80s to the present. It appears in the current ACM Computing Surveys.
According to a press release on Loui's work, A.I argument systems permit a new kind of reasoning to be embedded in complex programs. He says the reasoning is much more natural, more human, more social, even more fair. His proposal for A.I. argumentation is based on defeasible reasoning — which recognizes that a rule supporting a conclusion can be defeated. The conclusion is what A.I. specialists call an argument instead of a proof. Defeasible reasoning draws upon patterns of reasoning outside of mathematical logic, such as ones found in law, political science, rhetoric and ethics. Defeasible reasoning is based on rules that donít always hold if there are good reasons for an exception. It also permits rules to be more or less relevant to a situation. In this sense it is like analogy: One analogy might be good, but a different one might be better.