Re-framing problems changes how we see and solve them. The intersection of scientific thought and principles parallels much of what we solve as engineers of information (e.g. uncertainty, time, distribution)and need. This talk is an interdisciplinary look at complex systems and how they innately solve things like resource distribution, growth, and rebalancing. We will look at relative concepts in time and space from physics, ensemble forecasting from weather prediction, systems theory, the butterfly effect, viruses, natural feedback loops, self-regulation, evolution, and adaptation from biology.
Can we leverage these principles, behaviors, and strategies to design intelligent systems at scale?
Why is information technology so far behind scientific technology in innovation and functionality?
Can seeing things differently help speed innovation?
