First picks
Software legacy code (similar to our physical infrastructure), mobile applications, Internet of things, updating security, and rapidly changing automation environments for manufacturing are orders of magnitude greater efforts yet to be tackled in the large. Standards, simulation training systems, and new software tooling is required to reduce business costs to meet global competition and emergent problems. Defense Advanced Research Agency (DARPA) has identified need for highly innovative approaches to dramatically reduce labor costs associated with increased software production demands.
More inspiring concepts
Math-based algorithms enable machines to “make sense” of large quantitative data sets — at over a billion instructions per second.
We now live in a transitional age — where machines actually supersede human capability in some areas — like those featured in the TED Talks below.
“Athletic” robotics
Algorithms, Math models of physics used to achieve precise, responsive control and coordinated movements
Pervasive applications of Machine Learning
Pattern recognition of human movement, Machine better than coach at evaluating players
Unimaginable design
Machine “Creativity”, Algorithmic process for invention
Glance-visible display of large quantitative data sets
Understanding human language acquisition. Using algorithmic data processing to acquire deep insight — which would be otherwise inscrutable.
The capacity for more software is indefinite. More software production capability will simply open doors which cannot currently be perceived.
