Keynotes
Biologically-Inspired Massively-Parallel Architectures
- computing beyond a million processors
Steve Furber
School of Computer Science, The University of Manchester, UK
http://intranet.cs.man.ac.uk/apt/people/sfurber/
The SpiNNaker project aims to develop parallel computer systems with more than a million embedded processors. The goal of the project is to support large-scale simulations of systems of spiking neurons in biological real time, an application that is highly parallel but also places very high loads on the communication infrastructure due to the very high connectivity of biological neurons. The design of the machine is very much influenced by the biological application it is intended to support, which has a lot to teach us about how we might build more efficient, fault-tolerant parallel computers in the future.
Analysis by Synthesis
Hod Lipson
Cornell University, USA
http://www.mae.cornell.edu/Lipson/
Over the last few decades, evolutionary algorithms have become increasingly popular as a tool for automatically synthesizing solutions to open ended problems. The same process, however, can be reversed for analysis: Starting with an existing solution, evolutionary processes can be used as a reverse engineering tool by evolving models with similar observed behavior. The evolved models essentially provide hypotheses about the hidden target object. This talk will discuss this process, known as "analysis by synthesis", and demonstrate its application across a number of fields ranging from robotics to biology, where analysis challenges are plentiful. In particular, co-evolving tests can serve to disambiguate competing candidate models, essentially "asking questions" that help guide the analysis. Ultimately, can the machine generate new knowledge? We will see what happens when the machine discovers models that we cannot yet explain, giving a glimpse of what might be the future of science.
Hod Lipson is an Associate Professor of Mechanical & Aerospace Engineering and Computing & Information Science at Cornell University in Ithaca, NY. He directs the Computational Synthesis group, which focuses on novel ways for automatic design, fabrication and adaptation of virtual and physical machines. He has led work in areas such as evolutionary robotics, multi-material functional rapid prototyping, machine self-replication and programmable self-assembly. Lipson received his Ph.D. from the Technion - Israel Institute of Technology in 1998, and continued to a postdoc at Brandeis University and MIT. His research focuses primarily on biologically-inspired approaches, as they bring new ideas to engineering and new engineering insights into biology.
Using DNA to construct molecular systems
Andrew Turberfield
Department of Physics, The University of Oxford, UK
http://www.physics.ox.ac.uk/cm/people/turberfield.htm
DNA is a wonderful material for nanoscale construction: it is a structural material whose self-assembly can be programmed through its information-carrying capability, allowing rational design, combinatorial synthesis, selection and the possibility of evolution. I shall describe recent work on self-assembled molecular structures and on molecular machinery, including systems for chemical synthesis and free-running molecular motors.
