Google Tech Talk September 29, 2010 Presented by Steve Jurvetson. ABSTRACT Many of the interesting challenges in computer science, nanotechnology, and synthetic biology entail the construction of complex systems. As these systems transcend human comprehension, will we continue to design them or will we increasingly evolve them? As we design for evolvability, the locus of learning shifts from the artifacts themselves to the process that created them. There is no mathematical shortcut for the decomposition of a neural network or genetic program, no way to "reverse evolve" with the ease that we can reverse engineer the artifacts of purposeful design. The beauty of compounding iterative algorithms (evolution, fractals, organic growth, art) derives from their irreducibility. Google itself is a complex system that seeks to perpetually innovate. Leadership in complex organizations shifts from direction setting to a wisdom of crowds. The role of upper management is to tune the parameters of communication. Leaders can embrace a process that promotes innovation with emergent predictability more than they can hope to dictate the product of innovation itself. Innovation is critical to economic growth, progress, and the fate of the planet, yet it seems so random. While innovation may appear inscrutable at the atomic level, patterns emerge in the aggregate nonetheless. A critical pattern, spanning centuries, is that the pace of innovation is perpetually accelerating, and it is ... Saving Plantronic Cs70 Strobel Violin This Instant Buy Nebo Flashlights
