How do we train a stone to think? A review of machine intelligence and its implications Academic Article uri icon


  • 2016 Taylor & Francis. Machines have been getting intelligent and they are outpacing humans at certain complex tasks. This paper gives an overview of some of the key technologies used in machine intelligence. We hypothesize that given the future projections in machine capabilities, manmachine symbiosis is a given. Hence, we propose that human learning must be driven to increase the capacity to understand the concepts and apply that knowledge, rather than just memorise the facts or processes. Repetitive human tasks will get automated, freeing us to push the boundaries of creativity and innovation. This will force us to change how we learn and adapt.

published proceedings


author list (cited authors)

  • Koola, P. M., Ramachandran, S., & Vadakkeveedu, K.

citation count

  • 3

complete list of authors

  • Koola, Paul Mario||Ramachandran, Satheesh||Vadakkeveedu, Kalyan

publication date

  • March 2016