In the same way that solar panels are getting more efficient at converting sunlight into electricity, wind turbines are also getting better at harnessing the wind. There are two main levers that engineers can pull to squeeze out improvements: 1) Modifying the physical characteristics of the turbines, such as the shape of the blades, the components inside the nacelle, making them bigger, etc. 2) Optimizing where wind farms are located and where individual turbines are located in relation to each other within the wind farms.
An example of this is the partnership between wind turbine maker Vestas and IT giant IBM:
Vestas is addressing the issue of turbine placement by using IBM BigInsights software and an IBM "Firestorm" supercomputer to analyze petabytes of structured and unstructured data such as weather reports, tidal phases, geospatial and sensor data, satellite images, deforestation maps, and weather modeling research to pinpoint installation. The analysis, which used to take weeks, can now be done in less than one hour. (source)
Because wind turbines can operate for decades and are not mobile, making a wrong decision in the beginning can lead to a huge difference in cumulative energy production over the lifetime of the wind farm. This is important because the lower wind power costs are, the more competitive they will be against fossil fuels such as natural gas and coal.
The supercomputers and modelling software aren't only used in the planning phase. Once the wind farm is up and running, they can keep crunching data to decide when's the best time to schedule maintenance, and what they learn from the operations of the turbines can be incorporated into future models to refine them.