Knowledge and aging industrial infrastructure require organizations to think about the knowledge embedded in their infrastructure, and the knowledge required to embrace digital transformation. For most factories, plants, and industrial facilities no artificial intelligence monitors the status of far-flung equipment, and what little data flows from the amalgam of aging … [Read more...] about Sensors and Knowledge Required to Reduce Threats to Aging Industrial Infrastructure
artificial intelligence
Open Note to WEF: Reinvent Economy Don’t Be Threatened by AI
The gnashing of teeth and the fear-mongering about job displacement has started at the World Economic Forum. Robots and artificial intelligence (AI) are out to take many of the most prestigious job classes. See: Davos: Doctors and lawyers could be replaced by robots from the Telegraph. Why we shouldn't be threatened by AI I'm not worried. We Shouldn't Be … [Read more...] about Open Note to WEF: Reinvent Economy Don’t Be Threatened by AI
The Problem with Prediction: How to View Santa Cruz Crime Prevention Software
ABC ran a story about Santa Cruz, CA using software to help identify areas where crime may take place ( see Santa Cruz Police Using Computer Program to Predict, Prevent Crime). This kind of prediction is very different from what futurist do because it is constrained in both time and place. Those constraints are why it works. Those constraints are also the reason that short term … [Read more...] about The Problem with Prediction: How to View Santa Cruz Crime Prevention Software
Watson and Jeopardy and Why I’m Only Marginally Impressed
IBM Watson Logo from IBM Well, Watson beat (NPR) human its human competitors on Jeopardy, but I think the challenge Ken Jennings gave to IBM today sums up the one-trick pony aspect of Watson: Let put it on Dancing with the Stars to see what it can really do. Watson could not see nor hear, and it could not write, let alone dance. Watson was trained, in this instance, … [Read more...] about Watson and Jeopardy and Why I’m Only Marginally Impressed
