After years existing on supercomputers, cognitive computing platforms are being made available on the cloud. The consequences for embedded systems and the Industrial Internet of Things could be huge.
The cloud has been making raw computing power available in virtual environments for some years, but how about on-tap artificial intelligence? It’s currently an expensive, custom-built option for embedded systems, but Google, Microsoft, IBM and others are now making available their AI application programming interfaces (API). Now all a programmer, developer or data scientist has to do is create an app and point it to one of these AI engines, which can add powerful cognitive capabilities to any system. The result will be increasing industrial automation; the smart factory is now just an app away.
The most famous AI engine is IBM’s Watson, a cognitive computing platform that, until recently, was locked away on a supercomputer. Now on the cloud and accessible via the Internet, Watson’s API has so far been used by over 80,000 programmers, data scientists and app developers. Its latest feature, Knowledge Studio, promises machine learning and text analytics to create systems that learn and think for themselves. For industry, it means groundbreaking new insights will be possible from existing data. It will be possible to predict down to the minute when a machine will need maintenance not only from the data it generates, but by using the data generated by all machines like it. An AI system would then be able to schedule maintenance, automatically order spare parts or make a decision to replace it with something more efficient.