The rise and fall (and rise) of Artificial Intelligence
Celent will help qualify your requirements and introduce you to the vendor
Spotted a missing vendor? Use this form to alert a vendor to the Celent service
Create a vendor selection project & run comparison reports
Register to access this feature
Click to express your interest in this report
Indication of coverage against your requirements
Vendor requires PRO subscription to activate this feature
Requires research subscription, contact Celent for more info
21 May 2015Craig Beattie
[avatar user="firstname.lastname@example.org" size="thumbnail" align="right" /] Artificial intelligence has been around nearly as long as humans have been able to think about themselves, about thought and what they do. Empathy is wired into us - some more than others but we are all capable of thinking from another's point of view. This capacity leads us to anthropomorphize things that aren't human, to imbue things in our daily lives with human qualities like moods, characteristics and personality. When we build puppets, robots, models that look sort of human it is easy to for us to assign it with greater power, ability and promise than is really there. For marketers in other fields, to have consumers attribute their products with 'magical' properties would be a dream come true but for artificial intelligence it is a nightmare - one the industry has expended funds marketing against. Artificial intelligence has delivered many great tools which today we take for granted. Our phones listen to us and understand our requests in the context of our calendar, our camera's recognise faces and social networks tell us who those faces belong to, machines translate words from one language to another (although don't get the translations tattooed just yet) and the list goes on. We chuckle at these mistakes these learning and adaptive systems make, we see the huge strides and investment and we expect a new human like intelligence to emerge in the short term. Around the middle of every decade since the 60's there has been a peak in excitement for AI, a frustration with it's lack of progress, and a reduction of funding or AI winters as they are called. In the eighties it was LISP machines, in the nineties it was expert systems. Now in the twenty-tens (I thought it was teenies but that's a kids show apparently) we are seeing a resurgence of AI, a blending of machine learning, predictive modelling and cognitive computing along with self driving cars. This raises some rare and interesting questions:
- Are we headed for a new AI winter?
- Or an AI apocalypse?
- Also, will I still be cleaning my home in 2020?
Asia-Pacific, EMEA, LATAM, North America