[next] 2016 overview
Who knows what’s next?
Consistently, TTI/Vanguard members who attend [next] do. At our 2015 meeting, it was how to save Moore’s Law; biotechnology losing its separate status and becoming just more technology; and mobility changing everything—even the Internet itself. And that was just the first three speakers (Stanford professor and former Intel principal engineer Subhasish Mitra; DARPA program manager Alicia Jackson; and Benedict Evans, a partner at Andreessen Horowitz). Come to San Francisco and find out what’s next!
When and where?
December 6–7, 2016, San Francisco
Grand Hyatt San Francisco
345 Stockton Street, San Francisco, California, USA 94108
Prof. Dan V. Nicolau will show how a computer consisting of a nanostructured network can use protein filaments to solve an NP-complete problem (the subset sum problem).
Wednesday, December 7, 9:10 AM (Pacific Standard Time)
Biocomputation and Biosimulation with Molecular-Motors-Propelled Agents
Important and diverse mathematical problems—including cryptography, network routing, and protein folding—require the exploration a large number of candidate solutions. Because the time required for solving these problems grows exponentially with their size, electronic computers, which operate sequentially, cannot solve them in a reasonable timeframe. Unfortunately, the parallel-computation approaches proposed so far—e.g., DNA-, and quantum-computing—suffer from fundamental and practical drawbacks that prevent their successful implementation. Biological entities, from microorganisms to humans, routinely process information in parallel for essential tasks, such as foraging, searching for available space, competition, and cooperation. While several avenues for the use of biological agents for IT tasks exist, the most exciting use a very large number of agents exploring purposefully designed microfluidics networks. For instance, we reported the foundations of a parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, agents, e.g., molecular motor-propelled agents, then solves the mathematical problem. Besides speed, this approach addresses issues related to power consumption and heat dissipation by using orders-of-magnitude less energy than conventional computers.
Live YouTube stream of [next] 2016 conference:
Day 2 – Dec 7, 9:10 am (PST)
Watch Dan Nicolau’s talk here