Re:Jeff Hawkins talk on modeling neocortex and its impact on...
by tgflynn on Sunday November 28, 2010 @10:05PM
(#1949224)
The systems we think are simple are only so because we already possess the knowledge necessary to think abstractly.
If by that you mean that science proceeds by first understanding systems in their entirety and then abstracting away the essential elements from that complexity then I can't agree. (Science education may do that but that's an entirely different matter).
Historically we've gained understanding of systems by creating simple models which capture their essential behavior and only later adding more complex effects. One good example is the dynamics of the solar system. The basic phenomenology of central force motion (ie. elliptical orbits) was understood long before N-body interactions were accounted for. I think you would find similar examples in biology. For instance the "rule" that DNA is transcribed to RNA was established long before exceptions like retroviruses were understood.
The challenge is and always has been to somehow "see" or intuit the fundamental behavior in a mass of confusing data then build testable models based on that intuition.
If by that you mean that science proceeds by first understanding systems in their entirety and then abstracting away the essential elements from that complexity then I can't agree. (Science education may do that but that's an entirely different matter).
Historically we've gained understanding of systems by creating simple models which capture their essential behavior and only later adding more complex effects. One good example is the dynamics of the solar system. The basic phenomenology of central force motion (ie. elliptical orbits) was understood long before N-body interactions were accounted for. I think you would find similar examples in biology. For instance the "rule" that DNA is transcribed to RNA was established long before exceptions like retroviruses were understood.
The challenge is and always has been to somehow "see" or intuit the fundamental behavior in a mass of confusing data then build testable models based on that intuition.