The shape of extraterrestrial life
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Noever is developing "Book of Life" technology to identify and classify the tiniest life forms found on Earth and in samples from Mars. The project recently started under a grant from NASA's Advanced Concepts Office in Washington.
When a Mars surface sampler returns in the next century (right), what will be the best way to sort through the soil and rocks and identify possible organisms?
Noever has also been recognized for his inventive use of artificial intelligence to develop new drugs in response to the medical challenges posed by leukemia, E. Coli and HIV, among other important diseases.Discover magazine's July issue, in its annual Discover Awards for innovative technology, selected Noever's In Virtuo program as the top computer software product.
"Artificial intelligence is the main link between these projects," said Noever, a research scientist specializing in biotechnology in the Space Sciences Laboratory at NASA/Marshall. "The computer is the engine that solves problems depending on what kind of fuel - that is, what kind of questions - that you put into it."
Remembering the morph man
The idea of recognizing life when you see it may seem obvious, but its scientific grounding only dates back to Professor D'Arcy Thompson of the University of St. Andrews in Scotland and his 1917 book On Growth and Form.
Now recognized as the world's first biomathematician, Thompson applied the concepts of mathematics to the differences of form he observed in various living things (left; links to). He introduced the idea of systematically studying organisms by their geometric shape and found that changes of shape between species could be visualized by altering mathematical functions. In the days before computer imaging technology, though, Thompson could only draw figures by hand like the ones here.
"Biological shape now ranks as one of at least four principal criteria in analyzing the origin of astrobiological samples," Noever said, citing the importance of Thompson's contribution to astrobiology.
The unusual suspects
Noever plans to use shape to identify life forms just as a detective uses fingerprints to identify suspects. But sifting through the lineup of possible forms is an unprecedented task, even for computers. In fact, Noever expects it will take the largest computation ever.
From the 12 known meteorites believed to have made their way to Earth from Mars, Noever figures that about 20 kg (44 lbs. - as much as three mid-size bowling balls) of material are suitable for searching. Examining these "small" samples of Mars rocks by microscope would be like scouring a desert on foot in search of an occasional dry bone.
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Buying or creating a single computer to conduct the search is out of the question since at least 100 million images will have to be stored digitally and scanned, and classifying these images will require 10,000 times the computing power it took to produce the animated feature film Toy Story , one of the current standards in supercomputing.
Instead, Noever - working together with Dr. Subbiah Baskaran, a visiting scientist from the University of Vienna Institute for Molecular Biotechnology, and Helen Matsos of NASA/Marshall - plans to borrow a few thousand computers to build what might be called the first D'Arcy Machine, a computer dedicated to classifying images for tell-tale biological shapes.
Before considering extraterrestrial sources of life, however, the technology must be in place for an extensive classification of the only life forms we know - life on Earth.
With a little help from my friends
Named after the original morph man, the D'Arcy Machine will borrow processing power from volunteer computers connected to the Internet around the world to perform the giant task.
"We hope to get young scientists from elementary school through college to help us with the search by linking their computers to the D'Arcy Machine," said Noever.
One of the Allan Hills meteorites (links to larger image) after section was cut off for examination. Studying large specimens at high magnifications will be like scouring a desert by hand in search of fossil fragments.
"In Phase One, we will construct image-based family trees of living forms as distinct from inorganic shape features," said Noever, who plans to feed the new machine at least 100,000 images to get it started. The goal for this phase is peer-reviewed publication and presentation at the 1998 conference "On Growth and Form" highlighting scientific progress in the 50 years since D'Arcy Thompson's death.
In the second phase, the D'Arcy Machine will use trained neural networks from Phase One while being re-trained to simultaneously acquire and classify new, often ambiguous images. Noever and his colleagues will also throw the machine some curve balls with artificial data to test its performance.
The goal of the third phase is for the D'Arcy machine to automatically acquire and classify images with minimal human supervision. At this stage, the machine will be equipped for future search scenarios, including the examination of meteorites found on Earth and lunar or interplanetary samples retrieved from new space missions.
A lab assistant that doesn't get tired
Whereas traditional methods of searching for drugs, or searching for life on Mars for that matter, require scientists to labor through a lengthy process of trial and error, artificial intelligence software evolves as it searches.
At right is the cover of the July issue of Discover Magazine, with Dr. Noever pictured, reproduced here by permission of the publisher. Click on image for a larger version. Link to Discover web site in "related links" area below.
Noever likes to compare it to solving Rubik's Cube. A supercomputer randomly working all possible solutions would take about a billion years to get the right answer. In 1983, a Los Angeles high school student set the world's record at just under 23 seconds. If a random search takes too long, then teaching a computer to see patterns like a human might interpret them becomes the challenge to AI researchers: How to empower a software program with some kind of autonomous learning?
Like evolution, Noever's AI technology finds the fittest candidates.
"Before putting the engineer's precision to the final candidate, we first let the computer go to work for us" said Noever.
Left: Noever examines a sample of Aerogel, a super insulator that is sometimes called "frozen smoke." (links to; a larger, print quality image is available from the NASA Image Exchange.)
But computers aren't doing all the work. Noever is conducting innovative research in space flight experiments to make improved forms of Aerogel, a superinsulation with broad applications, and other areas.
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|For more information, please contact:
Dr. John M. Horack , Director of Science Communications
|Author: Dr. Tony Phillips
Curator: Linda Porter
NASA Official: Ron Koczor