Difference between revisions of "Conference 2013"

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(The Physics of Performance Curves: The Nature and Limits of Functional Performance Improvement in Technology Innovation)
(The Physics of Performance Curves: The Nature and Limits of Functional Performance Improvement in Technology Innovation)
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Proposed EDU 2012 Theme:<BR>
 
Proposed EDU 2012 Theme:<BR>
 
=== The Physics of Performance Curves: The Nature and Limits of Functional Performance Improvement in Technology Innovation  ===
 
=== The Physics of Performance Curves: The Nature and Limits of Functional Performance Improvement in Technology Innovation  ===
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Performance curves are
  
 
'''Topics of Investigation:'''<BR>
 
'''Topics of Investigation:'''<BR>
 
* What models do we have for the physical basis of technology and complexity performance curves (also referred to as 'learning curves,' and 'experience curves')?<BR>
 
* What models do we have for the physical basis of technology and complexity performance curves (also referred to as 'learning curves,' and 'experience curves')?<BR>
* What explains the "smoothness" and long-term predictability we find in many technology performance curves (e.g., Moore's 'law')?<BR>
+
* What explains the "smoothness" and long-term predictability we find in many technology performance curves (e.g., Moore's 'law') in our performance curve databases?<BR>
 
* Are such curves representative of undiscovered physical law or constraint, of economic or psychological expectations, or some other set of physical processes?<BR>
 
* Are such curves representative of undiscovered physical law or constraint, of economic or psychological expectations, or some other set of physical processes?<BR>
 
* Why are scale reduction processes persistently exponential in performance improvement, and which physical processes are candidates for continued scale reduction?<BR>
 
* Why are scale reduction processes persistently exponential in performance improvement, and which physical processes are candidates for continued scale reduction?<BR>
 +
* Why are technology product outliers (significantly off the curve) so often market failures, and can this observation lead to better R&D timing, strategy, and policy?
 
* Can we develop unifying theories for any classes (physical, efficiency, computational, informational) of performance curves today?<BR>
 
* Can we develop unifying theories for any classes (physical, efficiency, computational, informational) of performance curves today?<BR>
 
* How do non-computational (physical process, efficiency) performance curves differ from computational (computing, memory, communication) performance curves?<BR>
 
* How do non-computational (physical process, efficiency) performance curves differ from computational (computing, memory, communication) performance curves?<BR>
 +
* How do computer hardware and software performance curves differ, and why does hardware exhibit consistently better long-term exponential performance improvement?
 
* How do we differentiate non-persistently exponential performance curves (market-limited, etc.) from persistently exponential (scale reduction, FERD, etc.) curves?<BR>
 
* How do we differentiate non-persistently exponential performance curves (market-limited, etc.) from persistently exponential (scale reduction, FERD, etc.) curves?<BR>
* When does technology substitution occur in any technology platform? Under what circumstances can we predict it?<BR>
+
* When does technology substitution (creating a composite technology performance curve) occur in any technology platform? Under what circumstances can we predict it?<BR>
 
* When does exponential performance end in any performance curve? Under what circumstances can we predict it?<BR>
 
* When does exponential performance end in any performance curve? Under what circumstances can we predict it?<BR>
 
* What explains "state switches" (transitions to steeper or flatter exponential modes) in several technology performance curves?<BR>
 
* What explains "state switches" (transitions to steeper or flatter exponential modes) in several technology performance curves?<BR>

Revision as of 01:17, 11 November 2010

EDUGraphicBig.jpg


Second International Conference on the

Evolution and Development of the Universe

Proposed EDU 2012 Theme:

The Physics of Performance Curves: The Nature and Limits of Functional Performance Improvement in Technology Innovation

Performance curves are

Topics of Investigation:

  • What models do we have for the physical basis of technology and complexity performance curves (also referred to as 'learning curves,' and 'experience curves')?
  • What explains the "smoothness" and long-term predictability we find in many technology performance curves (e.g., Moore's 'law') in our performance curve databases?
  • Are such curves representative of undiscovered physical law or constraint, of economic or psychological expectations, or some other set of physical processes?
  • Why are scale reduction processes persistently exponential in performance improvement, and which physical processes are candidates for continued scale reduction?
  • Why are technology product outliers (significantly off the curve) so often market failures, and can this observation lead to better R&D timing, strategy, and policy?
  • Can we develop unifying theories for any classes (physical, efficiency, computational, informational) of performance curves today?
  • How do non-computational (physical process, efficiency) performance curves differ from computational (computing, memory, communication) performance curves?
  • How do computer hardware and software performance curves differ, and why does hardware exhibit consistently better long-term exponential performance improvement?
  • How do we differentiate non-persistently exponential performance curves (market-limited, etc.) from persistently exponential (scale reduction, FERD, etc.) curves?
  • When does technology substitution (creating a composite technology performance curve) occur in any technology platform? Under what circumstances can we predict it?
  • When does exponential performance end in any performance curve? Under what circumstances can we predict it?
  • What explains "state switches" (transitions to steeper or flatter exponential modes) in several technology performance curves?
  • What physical processes differentiate superexponential, exponential, logistic, life cycle, and other curves?
  • What do exponential and superexponential performance and efficiency curves imply for the future of technological innovation and sustainability?


We wish to seek out and network transition scholars, periodization, and acceleration, multi-level evolution and development scholars, world system modelers, and their critics. Scholars who approach evolutionary transitions from thermodynamic, informational-computational, evolutionary, developmental, integrative, and systemic perspectives are particularly desired. We will seek to compare logistic, exponential, and superexponential models arising from a variety of complexity transition definitions, and finally, explore a range of scenarios these models propose for the future of innovation and sustainability, underscoring the great technical, political, economic, and social value of better scholarship and science in this area.

Location: (TBD).

We are presently developing a proposal to host EDU 2012 at a U.S. venue. If you have an interest in working on the EDU 2012 conference development committee, sponsoring the event, or providing other assistance, please contact Clément Vidal and/or John Smart.