The revolution won't wait: AI enthusiasm rises, but adoption lags

The sheer amount of computing power required for AI processes has become another bottleneck to adoption. In recent years, cloud computing and parallel processing provided short term solutions, but as data volume grows and as deep learning drives automated creation of increasingly complex algorithms, we're due for another revolution in AI infrastructure. Today, companies are building innovative hardware--neuromorphic chips and tensor processing units (TPUs), for example--in order to improve computing power for scalable AI.