This decade, particularly the second part, will be characterised by cross fertilisation deriving from the application to one domain of science of discovery and paradigms coming from other domains.
The last century was a century of specialisation and layering; typically visible in the ICT world where you see great specialisation and the progress of one discipline fuelled by the progress of another because it is layered on it: the progress in information technology is largely the result of progress in electronics, more processing and storage capacity have fuelled progress in ICT, but the electronic specialists have no say in information technology and vice-versa).
The next decade will see paradigms developed in one discipline to change the approach in others.
An example can be seen in this news of the Green Brain project, driven by researchers at the Sheffield University. Their goal is to “copy” a honeybee brain to a tiny robot for having it flying with the same agility of a bee (and they are pretty good at it!).
Clearly there is the mechanical challenge of creating a tiny robot with the appropriate moving parts (and we are still far from dominating this technology, researchers have managed to create a robot that is cumbersome if compared to a bee, as shown in the photo below.
However, once you have a robot you need to provide it with the controls that would allow it to fly and negotiate obstacles, find the good path, take into account any small variation in air flow (they are crucial at this size…) and applying the same aerodynamics of a plane to a tiny flying robots does not work.
Hence the attempt to copy a honeybee brain….
Actually copying it all would be too big a challenge for today’s science and technology and it may be beyond the goal. What scientist are trying to do is to understand how the honeybee interprets the signals coming from its senses (vision, smell, accelerometers, position, airflow) and convert them into action for the flight.
In the drawing you can see the various areas of the honeybee brain in relation to this task.
In the near future we are likely to see more and more research to understand how Nature has solved tricky problems by evolving sophisticated control centres (brain) and to replicate them to solve our problems.
At the same time miniaturisation technique, smart materials and nanotech will likely provide the tools to build micro robots. As noted, we cannot just scale down our science for big planes to these dimension, a brand new approach is needed and copying Nature may be the best way to do it.